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Huang Y, Li X, Niu L, Zhang H, Zhang C, Feng Y, Wang Z, Zhang F, Luo X. CT venography combined with ultrasound-guided minimally invasive treatment for recurrent varicose veins: a pilot paired-design clinical trial. Clin Radiol 2024; 79:363-370. [PMID: 38290939 DOI: 10.1016/j.crad.2023.12.023] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/14/2023] [Revised: 09/26/2023] [Accepted: 12/24/2023] [Indexed: 02/01/2024]
Abstract
AIM To compare 1-year outcomes of computed tomography venography (CTV) combined with ultrasound-guided minimally invasive treatment with ascending phlebography and ultrasound-guided treatment for recurrent varicose veins. MATERIALS AND METHODS Consecutive patients with unilateral recurrent varicose veins were matched by gender, age, C classification, and degree of obesity, and randomised in a 1:1 ratio to receive either CTV (CTV group) or ascending phlebography (control group) combined with ultrasound-guided minimally invasive treatment. Patients were followed up by clinical and ultrasound examination. Follow-up was scheduled at 1 week, and 3, 6, and 12 months. The primary outcome measure was the Venous Clinical Severity Score (VCSS) at 12 months. Measures of secondary outcome included Chronic Insufficiency Venous International Questionnaire-20 (CIVIQ-20) score, recurrence of varicose vein or ulcer during 12 months, ulcer healing time, detection and location of treated veins. RESULTS Eighty patients were enrolled. Median VCSS in the CTV group was lower than it in the control group (p=0.04) and the CIVIQ-20 score was higher than the control group (p=0.02). By 12 months, no symptomatically recurrent varicose veins or ulcers had occurred. The ulcer healing time in CTV group was shorter (p<0.01). A greater number of patients had treated veins detected using CTV than by ascending venography (p=0.01), especially among patients with recurrence reflux veins in the groin, perineum, and vulva (p<0.01). CONCLUSION CTV combined with ultrasound may be more helpful than ascending phlebography combined with ultrasound to improve treatment efficacy for recurrent varices. These results should be verified by an future study with more patients and long-term follow-up.
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Affiliation(s)
- Y Huang
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - X Li
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - L Niu
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - H Zhang
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - C Zhang
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Y Feng
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - Z Wang
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - F Zhang
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China
| | - X Luo
- Department of Vascular Surgery, Beijing Shijitan Hospital, Capital Medical University, Beijing, China.
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Luo X, Yuan M, Lu P, Zhong X, Zhang Y, Li Y, Xi Z, Zhang H, Li S, Xu H. Integrating multi-index determination coupled with hierarchical cluster analysis to evaluate the quality consistency of PVE30, an anti-HSV "glycoprotein" macromolecule of Prunellae Spica. Phytochem Anal 2024; 35:530-539. [PMID: 38009261 DOI: 10.1002/pca.3309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/21/2023] [Revised: 11/02/2023] [Accepted: 11/04/2023] [Indexed: 11/28/2023]
Abstract
INTRODUCTION Prunellae Spica (PS), derived from the dried fruit spikes of Prunella vulgaris L., is a traditional Chinese medicinal herb. Our previous studies found that PVE30, a water-extracting ethanol-precipitating "glycoprotein" macromolecule of PS, was a potential anti-herpes simplex virus (HSV) candidate. However, due to the complex structure and diverse bioactivity of the "glycoprotein", ensuring its quality consistency across different batches of PVE30 becomes particularly challenging. This poses a significant hurdle for new drug development based on PVE30. OBJECTIVE Our study aimed to integrate multi-index determination coupled with hierarchical cluster analysis (HCA) to holistically profile the quality consistency of "glycoprotein" in PVE30. METHODS High-performance gel permeation chromatography with refractive index detector (HPGPC-RID) was used to characterise the molecular weight (Mw) distribution, HPLC-PDA was used to quantitatively analyse the composed monosaccharides and amino acids, and UV-VIS was used to quantify the contents of polysaccharides and proteins. Qualitative and quantitative consistency was analysed for each single index in 16 batches of PVE30, and a 16 × 38 data matrix, coupled with HCA, was used to evaluate the holistic quality consistency of PVE30. RESULTS The newly developed and validated methods were exclusive, linear, precise, accurate, and stable enough to quantify multi-indexes in PVE30. Single-index analysis revealed that 16 batches of PVE30 were qualitatively consistent in Mw distribution, polysaccharides and proteins, and the composition of composed monosaccharides and amino acids but quantitatively inconsistent in the relative contents of some "glycoprotein" macromolecules, as well as the composed monosaccharides/amino acids. HCA showed that the holistic quality of PVE30 was inconsistent, the inconsistency was uncorrelated with the regions where PS was commercially collected, and the contents of 17 amino acids and 2 monosaccharides contributed most to the holistic quality inconsistency. CONCLUSION Multi-index determination coupled with HCA was successful in evaluating the quality consistency of PVE30, and the significant difference in quantitative indices was not caused by the origin of PS. The cultivating basis should be confirmed for PVE30-based new drug development.
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Affiliation(s)
- Xiaomei Luo
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Centre of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Man Yuan
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Centre of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Ping Lu
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Centre of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Xuanlei Zhong
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Centre of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Yibo Zhang
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Centre of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Yang Li
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Centre of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Zhichao Xi
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Centre of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Hongmei Zhang
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Centre of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Songlin Li
- Department of Metabolomics, Jiangsu Province Academy of Traditional Chinese Medicine and Jiangsu Branch of China Academy of Chinese Medical Sciences, Nanjing, China
| | - Hongxi Xu
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, Shanghai, China
- Engineering Research Centre of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
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Cao W, Wang C, Zhang Y, Yang J, Luo X, Zhao Y, Wu M, Cheng S, Wang Y. Identification of the prognostic value of LACTB2 and its correlation with immune infiltrates in ovarian cancer by integrated bioinformatics analyses. Eur J Med Res 2024; 29:166. [PMID: 38475882 DOI: 10.1186/s40001-024-01762-2] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/26/2023] [Accepted: 03/01/2024] [Indexed: 03/14/2024] Open
Abstract
Ovarian cancer (OC) is one of the most common reproductive tumors in women, whereas current treatment options are limited. β-lactamase-like-protein 2 (LACTB2) has been observed to be associated with various cancers, but its function in OC is unknown. Therefore, we evaluate the prognostic value and the underlying function of LACTB2 in OC. In this study, high expression of LACTB2 was observed in OC compared with normal controls. Kaplan-Meier Plotter analysis revealed that overexpressed LACTB2 is strongly correlated with poor prognosis. We conducted GO/KEGG analysis to investigate the potential biological function of LACTB2 in OC. GESA analysis showed that LACTB2 was closely related to immune-related pathways. Subsequently, we explored the relationship between LACTB2 and 24 types of immune cells in OC. The results suggested that LACTB2 was positively associated with multiple tumor-infiltrating immune cells. Importantly, LACTB2 may modulate immune cell infiltration in OC to influence prognosis. In conclusion, LACTB2 can be used as a promising prognostic biomarker and immunotherapy target for OC.
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Affiliation(s)
- Weiwei Cao
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
| | - Chao Wang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
| | - Yue Zhang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
| | - Jiani Yang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
| | - Xiaomei Luo
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
| | - Yaqian Zhao
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China
| | - Meixuan Wu
- Department of Obstetrics and Gynecology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201204, China
| | - Shanshan Cheng
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.
- Department of Obstetrics and Gynecology, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, 201204, China.
| | - Yu Wang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, China.
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Chao WH, Luo X, Liang GX, Zhang H, Yuan T, Wu QW, Shi ZH, Yang QT. [Application of image-based artificial intelligence in rhinology]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2024; 59:277-283. [PMID: 38561271 DOI: 10.3760/cma.j.cn115330-20231025-00169] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 04/04/2024]
Affiliation(s)
- W H Chao
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - X Luo
- Department of Allergy, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China Department of Clinical Data Center, the Third Affiliated Hospital, Sun Yat-sen University, Guangzhou 510630, China
| | - G X Liang
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - H Zhang
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - T Yuan
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Q W Wu
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Z H Shi
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Allergy, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - Q T Yang
- Department of Otorhinolaryngology Head and Neck Surgery, the Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Allergy, the Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
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Luo X, Zhang Y, Zhou M, Liu K, Zhang S, Ye D, Tang C, Cao J. Overexpression of HbGRF4 or HbGRF4-HbGIF1 Chimera Improves the Efficiency of Somatic Embryogenesis in Hevea brasiliensis. Int J Mol Sci 2024; 25:2921. [PMID: 38474173 DOI: 10.3390/ijms25052921] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/11/2024] [Revised: 02/26/2024] [Accepted: 02/27/2024] [Indexed: 03/14/2024] Open
Abstract
Transgenic technology is a crucial tool for gene functional analysis and targeted genetic modification in the para rubber tree (Hevea brasiliensis). However, low efficiency of plant regeneration via somatic embryogenesis remains a bottleneck of successful genetic transformation in H. brasiliensis. Enhancing expression of GROWTH-REGULATING FACTOR 4 (GRF4)-GRF-INTERACTING FACTOR 1 (GIF1) has been reported to significantly improve shoot and embryo regeneration in multiple crops. Here, we identified endogenous HbGRF4 and HbGIF1 from the rubber clone Reyan7-33-97, the expressions of which dramatically increased along with somatic embryo (SE) production. Intriguingly, overexpression of HbGRF4 or HbGRF4-HbGIF1 markedly enhanced the efficiency of embryogenesis in two H. brasiliensis callus lines with contrasting rates of SE production. Transcriptional profiling revealed that the genes involved in jasmonic acid response were up-regulated, whereas those in ethylene biosynthesis and response as well as the S-adenosylmethionine-dependent methyltransferase activity were down-regulated in HbGRF4- and HbGRF4-HbGIF1-overexpressing H. brasiliensis embryos. These findings open up a new avenue for improving SE production in rubber tree, and help to unravel the underlying mechanisms of HbGRF4-enhanced somatic embryogenesis.
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Affiliation(s)
- Xiaomei Luo
- School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, China
- School of Tropical Agriculture and Forestry, Hainan University, Sanya 572025, China
| | - Yi Zhang
- School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, China
- School of Tropical Agriculture and Forestry, Hainan University, Sanya 572025, China
- National Key Laboratory for Biological Breeding of Tropical Crops, Hainan University, Haikou 570228, China
- Natural Rubber Cooperative Innovation Center of Hainan Province and Ministry of Education of PRC, Hainan University, Haikou 570228, China
| | - Miaomiao Zhou
- School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, China
- School of Tropical Agriculture and Forestry, Hainan University, Sanya 572025, China
| | - Kaiye Liu
- School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, China
- School of Tropical Agriculture and Forestry, Hainan University, Sanya 572025, China
- National Key Laboratory for Biological Breeding of Tropical Crops, Hainan University, Haikou 570228, China
- Natural Rubber Cooperative Innovation Center of Hainan Province and Ministry of Education of PRC, Hainan University, Haikou 570228, China
| | - Shengmin Zhang
- School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, China
- School of Tropical Agriculture and Forestry, Hainan University, Sanya 572025, China
- National Key Laboratory for Biological Breeding of Tropical Crops, Hainan University, Haikou 570228, China
- Natural Rubber Cooperative Innovation Center of Hainan Province and Ministry of Education of PRC, Hainan University, Haikou 570228, China
| | - De Ye
- School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, China
- School of Tropical Agriculture and Forestry, Hainan University, Sanya 572025, China
- National Key Laboratory for Biological Breeding of Tropical Crops, Hainan University, Haikou 570228, China
- Natural Rubber Cooperative Innovation Center of Hainan Province and Ministry of Education of PRC, Hainan University, Haikou 570228, China
| | - Chaorong Tang
- School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, China
- School of Tropical Agriculture and Forestry, Hainan University, Sanya 572025, China
- National Key Laboratory for Biological Breeding of Tropical Crops, Hainan University, Haikou 570228, China
- Natural Rubber Cooperative Innovation Center of Hainan Province and Ministry of Education of PRC, Hainan University, Haikou 570228, China
| | - Jie Cao
- School of Breeding and Multiplication (Sanya Institute of Breeding and Multiplication), Hainan University, Sanya 572025, China
- School of Tropical Agriculture and Forestry, Hainan University, Sanya 572025, China
- National Key Laboratory for Biological Breeding of Tropical Crops, Hainan University, Haikou 570228, China
- Natural Rubber Cooperative Innovation Center of Hainan Province and Ministry of Education of PRC, Hainan University, Haikou 570228, China
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Chen W, Bai Y, Fang P, Chen J, Wang X, Li Y, Luo X, Xiao Z, Iyer R, Shan F, Yuan T, Wu M, Huang X, Fang D, Yang Q, Zhang Y. Body mass index's effect on CRSwNP extends to pathological endotype and recurrence. Rhinology 2024; 0:3161. [PMID: 38416065 DOI: 10.4193/rhin23.402] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 02/29/2024]
Abstract
BACKGROUND Elevated body mass index (BMI) has been recognized as an important contributor to corticosteroid insensitivity in chronic rhinosinusitis with nasal polyps (CRSwNP). We aimed to delineate the effects of elevated BMI on immunological endotype and recurrence in CRSwNP individuals. METHODOLOGY A total of 325 patients with CRSwNP undergoing FESS were recruited and stratified by BMI. H&E staining was employed for histological evaluation. Characteristics of inflammatory patterns were identified by immunohistochemical staining. The predictive factors for recurrence were determined and evaluated by multivariable logistic regression analysis and the receiver operating characteristic (ROC) curves across all subjects and by weight group. RESULTS In all patients with CRSwNP, 26.15% subjects were classified as overweight/obese group across BMI categories and exhibited a higher symptom burden. The upregulated eosinophil/neutrophil-dominant cellular endotype and amplified type 2/ type 3 coexisting inflammation was present in overweight/obese compared to underweight/normal weight controls. Additionally, a higher recurrent proportion was shown in overweight/obese patients than that in underweight/normal weight cohorts. Multivariable logistic regression analysis identified BMI as an independent predictor for recurrence. The predictive capacity of each conventional parameter (tissue eosinophil and CLCs count, and blood eosinophil percentage) alone or in combination was poor in overweight/obese subjects. CONCLUSIONS Overweight/obese CRSwNP stands for a unique phenotype and endotype. Conventional parameters predicting recurrence are compromised in overweight/obese CRSwNP, and there is an urgent need for novel biomarkers that predict recurrence for these patients.
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Affiliation(s)
- W Chen
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Y Bai
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - P Fang
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - J Chen
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - X Wang
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Y Li
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - X Luo
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Z Xiao
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - R Iyer
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - F Shan
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - T Yuan
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - M Wu
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - X Huang
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - D Fang
- Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA
| | - Q Yang
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
| | - Y Zhang
- Department of Otolaryngology-Head and Neck Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
- Guangdong Provincial Key Laboratory of Diabetology, Guangzhou Key Laboratory of Mechanistic and Translational Obesity Research, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou, China
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Wu M, Gu S, Yang J, Zhao Y, Sheng J, Cheng S, Xu S, Wu Y, Ma M, Luo X, Zhang H, Wang Y, Zhao A. Comprehensive machine learning-based preoperative blood features predict the prognosis for ovarian cancer. BMC Cancer 2024; 24:267. [PMID: 38408960 PMCID: PMC10895771 DOI: 10.1186/s12885-024-11989-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/07/2023] [Accepted: 02/10/2024] [Indexed: 02/28/2024] Open
Abstract
PURPOSE Significant advancements in improving ovarian cancer (OC) outcomes have been limited over the past decade. To predict prognosis and improve outcomes of OC, we plan to develop and validate a robust prognosis signature based on blood features. METHODS We screened age and 33 blood features from 331 OC patients. Using ten machine learning algorithms, 88 combinations were generated, from which one was selected to construct a blood risk score (BRS) according to the highest C-index in the test dataset. RESULTS Stepcox (both) and Enet (alpha = 0.7) performed the best in the test dataset with a C-index of 0.711. Meanwhile, the low RBS group possessed observably prolonged survival in this model. Compared to traditional prognostic-related features such as age, stage, grade, and CA125, our combined model had the highest AUC values at 3, 5, and 7 years. According to the results of the model, BRS can provide accurate predictions of OC prognosis. BRS was also capable of identifying various prognostic stratifications in different stages and grades. Importantly, developing the nomogram may improve performance by combining BRS and stage. CONCLUSION This study provides a valuable combined machine-learning model that can be used for predicting the individualized prognosis of OC patients.
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Affiliation(s)
- Meixuan Wu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Sijia Gu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Jiani Yang
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Yaqian Zhao
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Jindan Sheng
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Shanshan Cheng
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Shilin Xu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Yongsong Wu
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China
| | - Mingjun Ma
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Xiaomei Luo
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Hao Zhang
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China
| | - Yu Wang
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, China.
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, 200092, Shanghai, China.
| | - Aimin Zhao
- Department of Obstetrics and Gynecology, Renji Hospital, School of Medicine, Shanghai Jiaotong University, Shanghai, China.
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Abratenko P, Alterkait O, Andrade Aldana D, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow D, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhat A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Brunetti MB, Camilleri L, Cao Y, Caratelli D, Cavanna F, Cerati G, Chappell A, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Cross R, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Englezos P, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Franco D, Furmanski AP, Gao F, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Gramellini E, Green P, Greenlee H, Gu L, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hilgenberg C, Horton-Smith GA, Imani Z, Irwin B, Ismail M, James C, Ji X, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Liu H, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Martynenko S, Mastbaum A, Mawby I, McConkey N, Meddage V, Micallef J, Miller K, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Moudgalya MM, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Pophale I, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Safa I, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, St John J, Strauss T, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. Search for Heavy Neutral Leptons in Electron-Positron and Neutral-Pion Final States with the MicroBooNE Detector. Phys Rev Lett 2024; 132:041801. [PMID: 38335355 DOI: 10.1103/physrevlett.132.041801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/12/2023] [Accepted: 11/30/2023] [Indexed: 02/12/2024]
Abstract
We present the first search for heavy neutral leptons (HNLs) decaying into νe^{+}e^{-} or νπ^{0} final states in a liquid-argon time projection chamber using data collected with the MicroBooNE detector. The data were recorded synchronously with the NuMI neutrino beam from Fermilab's main injector corresponding to a total exposure of 7.01×10^{20} protons on target. We set upper limits at the 90% confidence level on the mixing parameter |U_{μ4}|^{2} in the mass ranges 10≤m_{HNL}≤150 MeV for the νe^{+}e^{-} channel and 150≤m_{HNL}≤245 MeV for the νπ^{0} channel, assuming |U_{e4}|^{2}=|U_{τ4}|^{2}=0. These limits represent the most stringent constraints in the mass range 35
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - O Alterkait
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - D Barrow
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
- Michigan State University, East Lansing, Michigan 48824, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - A Bhat
- University of Chicago, Chicago, Illinois 60637, USA
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - M B Brunetti
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - Y Cao
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Chappell
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | | | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - R Cross
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | - P Englezos
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - A Ereditato
- University of Chicago, Chicago, Illinois 60637, USA
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- University of Chicago, Chicago, Illinois 60637, USA
| | - D Franco
- University of Chicago, Chicago, Illinois 60637, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - F Gao
- University of California, Santa Barbara, California 93106, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - E Gramellini
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Green
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Gu
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- University of Chicago, Chicago, Illinois 60637, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - Z Imani
- Tufts University, Medford, Massachusetts 02155, USA
| | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - M Ismail
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Nankai University, Nankai District, Tianjin 300071, China
| | - J H Jo
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - H Liu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Viriginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - S Martynenko
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - I Mawby
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N McConkey
- University College London, London WC1E 6BT, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Micallef
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tufts University, Medford, Massachusetts 02155, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
- Indiana University, Bloomington, Indiana 47405, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M M Moudgalya
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - N Oza
- Columbia University, New York, New York 10027, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - I Safa
- Columbia University, New York, New York 10027, USA
| | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- University of Chicago, Chicago, Illinois 60637, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - W Wu
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Zhong X, Zhang Y, Yuan M, Xu L, Luo X, Wu R, Xi Z, Li Y, Xu H. Prunella vulgaris polysaccharide inhibits herpes simplex virus infection by blocking TLR-mediated NF-κB activation. Chin Med 2024; 19:6. [PMID: 38185640 PMCID: PMC10773030 DOI: 10.1186/s13020-023-00865-y] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/21/2023] [Accepted: 11/22/2023] [Indexed: 01/09/2024] Open
Abstract
BACKGROUND Prunella vulgaris polysaccharide extracted by hot water and 30% ethanol precipitation (PVE30) was reported to possess potent antiviral effects against herpes simplex virus (HSV) infection. However, its anti-HSV mechanism has not yet been fully elucidated. PURPOSE This study aimed to investigate the potential mechanisms of PVE30 against HSV infection. METHODS Antiviral activity was evaluated by a plaque reduction assay, and the EC50 value was calculated. Immunofluorescence staining and heparin bead pull-down assays confirmed the interactions between PVE30 and viral glycoproteins. Real-time PCR was conducted to determine the mRNA levels of viral genes, including UL54, UL29, UL27, UL44, and US6, and the proinflammatory cytokines IL-6 and TNF-α. The protein expression of viral proteins (ICP27, ICP8, gB, gC, and gD), the activity of the TLR-NF-κB signalling pathway, and necroptotic-associated proteins were evaluated by Western blotting. The proportion of necroptotic cells was determined by flow cytometric analysis. RESULTS The P. vulgaris polysaccharide PVE30 was shown to compete with heparan sulfate for interaction with HSV surface glycoprotein B and gC, thus strongly inhibiting HSV attachment to cells. In addition, PVE30 downregulated the expression of IE genes, which subsequently downregulated the expression of E and L viral gene products, and thus effectively restricted the yield of progeny virus. Further investigation confirmed that PVE30 inhibited TLR2 and TLR3 signalling, leading to the effective suppression of NF-κB activation and IL-6 and TNF-α expression levels, and blocked HSV-1-induced necroptosis by reducing HSV-1-induced phosphorylation of MLKL. CONCLUSION Our results demonstrate that the P. vulgaris polysaccharide PVE30 is a potent anti-HSV agent that blocks TLR-mediated NF-κB activation.
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Affiliation(s)
- Xuanlei Zhong
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, No. 1200, Cailun Road, Shanghai, 201203, China
- Engineering Research Center of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Yibo Zhang
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, No. 1200, Cailun Road, Shanghai, 201203, China
- Engineering Research Center of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Man Yuan
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, No. 1200, Cailun Road, Shanghai, 201203, China
- Engineering Research Center of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Lin Xu
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, No. 1200, Cailun Road, Shanghai, 201203, China
- Engineering Research Center of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Xiaomei Luo
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, No. 1200, Cailun Road, Shanghai, 201203, China
- Engineering Research Center of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Rong Wu
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, No. 1200, Cailun Road, Shanghai, 201203, China
- Engineering Research Center of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Zhichao Xi
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, No. 1200, Cailun Road, Shanghai, 201203, China
- Engineering Research Center of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China
| | - Yang Li
- School of Pharmacy, Shanghai University of Traditional Chinese Medicine, No. 1200, Cailun Road, Shanghai, 201203, China.
- Engineering Research Center of Shanghai Colleges for TCM New Drug Discovery, Shanghai, China.
| | - Hongxi Xu
- Shuguang Hospital, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
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Li Q, Li X, Li W, Fan R, Ma Q, Luo X, Jian H, Chen X, Cao C, Zheng W. Development of IL-17A inhibitor-induced atopic dermatitis-like rash in psoriasis patients: Insights into immune shift. Exp Dermatol 2024; 33:e14958. [PMID: 38009235 DOI: 10.1111/exd.14958] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/30/2023] [Revised: 09/24/2023] [Accepted: 09/25/2023] [Indexed: 11/28/2023]
Abstract
Cases of atopic dermatitis (AD)-like rash induced by IL-17A inhibitor secukinumab treatment (SI-AD) have been recently reported in psoriasis patients. To identify immune and inflammatory factors expression in SI-AD. A panel of 15 immune and inflammatory factors in peripheral blood samples from various groups, including patients with patients with SI-AD, psoriasis with secukinumab (S-stable), advanced psoriasis patients (Advanced) and healthy controls (HC). Interleukin-10 (IL-10), IL-4 and IL-17A were detected in skin tissue biopsy samples by immunohistochemistry and real-time quantitative polymerase chain reaction. The immunoglobulin E levels in the SI-AD patients exceeded normal values. The IL-10 levels in SI-AD patients were higher than those in S-stable patients, advanced patients and HC. The IL-4 levels in SI-AD patients were higher than that in S-stable patients and HC. The IL-17A levels in SI-AD patients were higher than those in advanced psoriasis patients and HC, but no significant differences were observed between SI-AD patients and S-stable patients. IL-10 and IL-4 levels were higher in AD-like rashes than in healthy skin, while IL-17A did not differ significantly between the two. Upon discontinuing secukinumab, and switching to oral cyclosporine, antihistamines, Janus kinase 1 inhibitor and topical glucocorticoids, SI-AD patients experienced significant improvement in their skin lesions. Upon reexamination, all 15 immune and inflammatory factors returned to normal levels. Immune shift from Th17 towards Th2 may occur in SI-AD, as indicated by abnormal expression of multiple immune and inflammatory factors observed in peripheral blood and skin tissues.
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Affiliation(s)
- Qiuju Li
- Department of Dermatology and Venereology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Xiuying Li
- Department of Dermatology and Venereology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Wenyu Li
- Department of Dermatology and Venereology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Runge Fan
- Department of Dermatology and Venereology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Qing Ma
- Department of Dermatology and Venereology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Xiaomei Luo
- Department of Dermatology and Venereology, Baise People's Hospital, Baise, China
| | - Huahui Jian
- Department of Dermatology and Venereology, Baise People's Hospital, Baise, China
| | - Xiaozhi Chen
- Department of Dermatology and Venereology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Cunwei Cao
- Department of Dermatology and Venereology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
| | - Wenjun Zheng
- Department of Dermatology and Venereology, The First Affiliated Hospital of Guangxi Medical University, Nanning, China
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11
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Liang H, Wang C, Zhu PF, Zeng QL, Huang XB, Pan YF, Pan YJ, Hu QY, Luo X, Chen H, Yu ZJ, Lu FM, Lyu J. [A study of the clinical curative effect of nucleos(t)ide analogues treated to pegylated interferon-α add-on therapy in patients with chronic hepatitis B]. Zhonghua Gan Zang Bing Za Zhi 2023; 31:1297-1305. [PMID: 38253074 DOI: 10.3760/cma.j.cn501113-20230505-00206] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/24/2024]
Abstract
Objective: To investigate the hepatitis B surface antigen (HBsAg) clearance condition and its predictive factors after treatment with nucleos(t)ide analogues to pegylated interferon-α add-on therapy in patients with chronic hepatitis B. Methods: Patients with chronic hepatitis B who visited the First Affiliated Hospital of Zhengzhou University from 2018~2019 were prospectively enrolled. HBsAg≤ 1500 IU/mL, hepatitis B e antigen-negative, HBV DNA undetectable, received antiviral treatment with nucleos(t)ide analogues for at least one year, and pegylated interferon-α add-on therapy for 48 weeks were included. The primary endpoint of study was to determine the proportion of HBsAg clearance at 72 weeks. Concurrently, the predictive factors for HBsAg clearance were analyzed. Quantitative and qualitative data were analyzed using a t-test or non-parametric test and a Fisher's exact test. Results: A total of 38 cases were included in this study, of which 13 cases obtained HBsAg clearance at 48 weeks of therapy and another six cases obtained HBsAg clearance throughout the extended treatment period of 72 weeks, accounting for 50.00% of all enrolled patients. There was a significant difference in HBsAg dynamics between the HBsAg clearance group and the non-clearance group (P < 0.05). Univariate logistic regression analysis showed that patients' age, baseline, 12-and 24-week HBsAg levels, and early HBsAg reduction were predictive factors for HBsAg clearance at 72 weeks of treatment. Multivariate logistic regression analysis showed that age (OR = 1.311; P = 0.016; 95% confidence interval: 1.051~1.635) and HBsAg levels at 24 weeks of treatment (OR = 4.481; P = 0.004; 95% confidence interval: 1.634~12.290) were independent predictors for HBsAg clearance. Conclusion: Hepatitis B e antigen-negative, nucleos(t)ide analogue treated, HBsAg ≤ 1500 IU/mL, and HBV DNA undetectable, peg-IFNα add-on treatment for 48 weeks could promote HBsAg clearance in patients with chronic hepatitis B. Six of the sixteen cases (37.50%) who did not obtain HBsAg clearance at week 48 did so with the course of therapy extended to week 72. Hence, the optimal individualized treatment strategy should be customized according to the predictors rather than the fixed 48-week course. Age (≤ 38), baseline HBsAg level (≤2.86 log(10)IU/ml), HBsAg level at 24 weeks (≤ 0.92 log(10)IU/ml), and 12-week HBsAg decrease from baseline (≥ 0.67 log(10)IU/ml) indicate that patients are highly likely to obtain HBsAg clearance at the 72 weeks of combination therapy, in which the combined indicator based on HBsAg level ≤0.92 log(10)IU/ml at 24 weeks will identify 85.0% to 100.0% of patients with HBsAg clearance.
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Affiliation(s)
- H Liang
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - C Wang
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - P F Zhu
- Department of Clinical Laboratory, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Q L Zeng
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - X B Huang
- Department of Clinical Laboratory, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Y F Pan
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Y J Pan
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Q Y Hu
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - X Luo
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - H Chen
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - Z J Yu
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
| | - F M Lu
- Department of Microbiology, School of Basic Medical Sciences, Peking University Health Science Center, Beijing 100191, China
| | - J Lyu
- Department of Infectious Diseases, the First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China
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Zhang H, Zhou M, Zhou QL, Luo X, Zheng R, Su J, Xiong GW, Cheng Y, Li YT, Zhang PP, Zhang K, Dai M, Huang XK, Zhang YN, Shi ZH, Tao J, Zhou YQ, Feng PY, Chen ZG, Yang QT. [Preliminary insights into the practice of hypoallergenic home visiting program]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:1957-1963. [PMID: 38186142 DOI: 10.3760/cma.j.cn112150-20230903-00151] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 01/09/2024]
Abstract
Allergic diseases affect about 40% of the world's population. Environmental factors are important in the occurrence and development of allergic diseases. Dust mites are one of the most important allergens in the indoor environment. The World Health Organization proposes the "four-in-one, combination of prevention and treatment" treatment principle for allergic diseases, in which environmental control to avoid or reduce allergens is the first choice for treatment. Modern people spend much more time at home (including sleeping) than outdoors, and the control of the home environment is particularly critical. This practice introduces the hypoallergenic home visit program, which including home environment assessment, environmental and behavioral intervention guidance, and common household hypoallergenic supplies and service guidance for the patient's home environment. The real-time semi-quantitative testing of dust mite allergens, qualitative assessments of other indoor allergens, record of patients' household items and lifestyle, and precise, individualized patient prevention and control education will be conducted. The hypoallergenic home visit program improves the doctors' diagnosis and treatment data dimension, and becomes a patient management tool for doctors outside the hospital. It also helps patients continue to scientifically avoid allergens and irritants in the environment, effectively build a hypoallergenic home environment, reduce exposure to allergens in the home environment, and achieve the goal of combining the prevention and treatment of allergic diseases.
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Affiliation(s)
- H Zhang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - M Zhou
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Q L Zhou
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - X Luo
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - R Zheng
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - J Su
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - G W Xiong
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y Cheng
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y T Li
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - P P Zhang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - K Zhang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Traditional Chinese Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - M Dai
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Traditional Chinese Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - X K Huang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y N Zhang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Z H Shi
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - J Tao
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y Q Zhou
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Respiratory and Intensive Care, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - P Y Feng
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Dermatology and Cosmetic Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Z G Chen
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Q T Yang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
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Huang YX, Zou XP, Zhang ZL, Ning K, Luo X, Xiong LB, Peng YL, Zhou ZH, Dong P, Guo SJ, Han H, Zhou FJ. [Relation factor analysis for the short-term preservation of ipsilateral renal function after partial nephrectomy]. Zhonghua Wai Ke Za Zhi 2023; 61:1099-1103. [PMID: 37932147 DOI: 10.3760/cma.j.cn112139-20230228-00086] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 11/08/2023]
Abstract
Objectives: To analyze the factors relative to the short-term preservation of ipsilateral renal function after partial nephrectomy. Methods: The clinical data of 83 patients who were treated with partial nephrectomy from December 2014 to December 2019 in the Department of Urology, Sun Yat-sen University Cancer Center were retrospectively analyzed. There were 54 males and 29 females, aging (M (IQR)) 49 (17) years (range: 27 to 74 years). The ischemia time in operation was 25 (18) minutes (range: 10 to 67 minutes). Emission computed tomography scan and CT scan were performed before (within 1 month) and after (3 to 12 months) surgery. The volume of the ipsilateral and contralateral kidney was measured on the basis of preoperative and postoperative CT scans. The glomerular filtration rate (GFR) specifically in each kidney was estimated by emission computed tomography. Recovery from ischemia is determined by the formula: GFR preservation/volume saved×100%. Linear regression was used to explore the factors ralative to the short-term preservation of ipsilateral renal function after partial nephrectomy. Results: The GFR preservation of the ipsilateral kidney was 80.9 (25.2) % (range: 31.0% to 109.4%). The volume loss of the kidney resulted in a decrease of 12.0% (5.8 ml/(min×1.96 m2)) of GFR, while the ischemic injury resulted in a decrease of 6.5% (2.5 ml/(min×1.96 m2)) of GFR. The volume saved from the ipsilateral kidney was 87.1 (12.9) % (range: 27.0% to 131.7%). Recovery from ischemia was 93.5 (17.5) % (range:44.3% to 178.3%). In multivariate analysis, GFR preservation of the ipsilateral kidney was significantly correlated with the volume saved of the ipsilateral kidney (β=0.383, 95%CI: 0.144 to 0.622, P=0.002). It was not related to the ischemia time (β=0.046, 95%CI:-0.383 to 0.475, P=0.831). Conclusion: In the condition of limited ischemic time, in the short term ipsilateral renal function after partial nephrectomy is mainly determined by the loss of kidney volume, while ischemic injury only plays a minor role.
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Affiliation(s)
- Y X Huang
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - X P Zou
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z L Zhang
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - K Ning
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - X Luo
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - L B Xiong
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Y L Peng
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z H Zhou
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - P Dong
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - S J Guo
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - H Han
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - F J Zhou
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
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14
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Luo X, Wang Y, Zhang H, Chen G, Sheng J, Tian X, Xue R, Wang Y. Identification of a Prognostic Signature for Ovarian Cancer Based on Ubiquitin-Related Genes Suggesting a Potential Role for FBXO9. Biomolecules 2023; 13:1724. [PMID: 38136595 PMCID: PMC10742228 DOI: 10.3390/biom13121724] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/12/2023] [Revised: 10/19/2023] [Accepted: 11/28/2023] [Indexed: 12/24/2023] Open
Abstract
BACKGROUND Ovarian cancer (OV) is associated with high mortality and poses challenges in diagnosis and prognosis prediction. Ubiquitin-related genes (UbRGs) are involved in the initiation and progression of cancers, but have still not been utilized for diagnosis and prognosis of OV. METHODS K48-linked ubiquitination in ovarian tissues from our OV and control cohort was assessed using immunohistochemistry. UbRGs, including ubiquitin and ubiquitin-like regulators, were screened based on the TCGA-OV and GTEx database. Univariate Cox regression analysis identified survival-associated UbRGs. A risk model was established using the LASSO regression and multivariate Cox regression analysis. The relationship between UbRGs and immune cell infiltration, tumor mutational burden, drug sensitivity, and immune checkpoint was determined using the CIBERSORT, ESTIMATE, and Maftools algorithms, based on the Genomics of Drug Sensitivity in Cancer and TCGA-OV databases. GEPIA2.0 was used to analyze the correlation between FBXO9/UBD and DNA damage repair-related genes. Finally, FBXO9 and UBD were accessed in tissues or cells using immunohistochemistry, qPCR, and Western blot. RESULTS We confirmed the crucial role for ubiquitination in OV as a significant decrease of K48-linked ubiquitination was observed in primary OV lesions. We identified a prognostic signature utilizing two specific UbRGs, FBXO9 and UBD. The risk score obtained from this signature accurately predicted the overall survival of TCGA-OV training dataset and GSE32062 validation dataset. Furthermore, this risk score also showed association with immunocyte infiltration and drug sensitivity, revealing potential mechanisms for ubiquitination mediated OV risk. In addition, FBXO9, but not UBD, was found to be downregulated in OV and positively correlated with DNA damage repair pathways, suggesting FBXO9 as a potential cancer suppressor, likely via facilitating DNA damage repair. CONCLUSIONS We identified and validated a signature of UbRGs that accurately predicts the prognosis, offers valuable guidance for optimizing chemotherapy and targeted therapies, and suggests a potential role for FBXO9 in OV.
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Affiliation(s)
- Xiaomei Luo
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China (G.C.)
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translational Research Center, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Yingjie Wang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China (G.C.)
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translational Research Center, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
- School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Hao Zhang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China (G.C.)
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translational Research Center, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Guangquan Chen
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China (G.C.)
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translational Research Center, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Jindan Sheng
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China (G.C.)
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translational Research Center, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Xiu Tian
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China (G.C.)
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translational Research Center, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Renhao Xue
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China (G.C.)
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translational Research Center, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
- School of Life Sciences and Technology, Tongji University, Shanghai 200092, China
| | - Yu Wang
- Department of Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China (G.C.)
- Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Clinical and Translational Research Center, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
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15
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Gao S, Wang J, Wu X, Luo X, Li Q, Chen D, Liu X, Li W. [Molecular detection and subtyping of Blastocystis sp. in pigs in Anhui Province]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2023; 35:508-512. [PMID: 38148541 DOI: 10.16250/j.32.1374.2023082] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 12/28/2023]
Abstract
OBJECTIVE To investigate the prevalence and subtype distribution of Blastocystis sp. in pigs in Anhui Province. METHODS A total of 500 stool samples were collected from large-scale pig farms in Bozhou, Anqing, Chuzhou, Hefei, Fuyang, and Lu'an cities in Anhui Province from October to December 2015. Blastocystis was detected in pig stool samples using a PCR assay based on the small subunit ribosomal RNA (SSU rRNA) gene, and positive samples were subjected to sequencing and sequence analysis. Blastocystis subtypes were characterized in the online PubMLST database, and verified using phylogenetic tree created with the neighbor-joining algorithm in the Meta software. RESULTS The prevalence of Blastocystis infection was 43.2% (216/500) in pigs in 6 cities of Anhui Province, and all pig farms were tested positive for Blastocystis. There was a region-specific prevalence rate of Blastocystis (17.2% to 50.0%) (χ2 = 26.084, P < 0.01), and there was a significant difference in the prevalence of Blastocystis sp. among nursery pigs (39.6%), preweaned pigs (19.1%), and growing pigs (62.3%) (χ2 = 74.951, P < 0.01). Both online inquiry and phylogenetic analysis revealed ST1, ST3, and ST5 subtypes in pigs, with ST5 as the predominant subtype. CONCLUSIONS The prevalence of Blastocystis sp. is high in pigs in Anhui Province, with three zoonotic subtypes identified, including ST1, ST3, and ST5.
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Affiliation(s)
- S Gao
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - J Wang
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - X Wu
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - X Luo
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - Q Li
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - D Chen
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - X Liu
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
| | - W Li
- College of Animal Science, Anhui Science and Technology University, Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, Fengyang, Anhui 233100, China
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16
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Luo X, Li Y, Wang B, Zhu S, Liu X, Liu X, Qi X, Wu Y. Carnosine alleviates cisplatin-induced acute kidney injury by targeting Caspase-1 regulated pyroptosis. Biomed Pharmacother 2023; 167:115563. [PMID: 37742605 DOI: 10.1016/j.biopha.2023.115563] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/01/2023] [Revised: 09/13/2023] [Accepted: 09/19/2023] [Indexed: 09/26/2023] Open
Abstract
Acute kidney injury (AKI) is a syndrome characterized by rapid loss of renal excretory function. Its underlying mechanisms remain unclear. Pyroptosis, a form of programmed cell death, plays an important role in AKI. It is characterized by cell swelling and membrane rupture, triggering the release of cellular contents and activating robust inflammatory responses. Carnosine, a dipeptide with antioxidant and anti-inflammatory properties, has therapeutic effects in AKI. However, the mechanism by which carnosine treats AKI-associated pyroptosis remains unexplored. In this study, we investigated the protective effect of carnosine on renal tubule cells using in vivo and in vitro models of AKI. We found that carnosine therapy significantly alleviated altered serum biochemical markers and histopathological changes in mice with cisplatin-induced AKI. It also reduced the levels of inflammation and pyroptosis. These results were consistent with those seen in human kidney tubular epithelial cells (HK-2) treated with cisplatin. Through molecular docking and cellular thermal shift assay, we identified caspase-1 as a target of carnosine. By knocking down caspase-1 in HK-2 cells using caspase-1 siRNA, we demonstrated that carnosine did not exhibit a protective role in cisplatin-induced HK-2 cells. This study provides the first evidence that carnosine alleviates damage to kidney tubular epithelial cells by targeting caspase-1 and inhibiting pyroptosis. Therefore, carnosine holds promise as a potential therapeutic agent for AKI, with caspase-1 representing an effective therapeutic target in this pathology.
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Affiliation(s)
- Xiaomei Luo
- Department of Nephropathy, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, PR China
| | - Yuanyuan Li
- Department of Nephropathy, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, PR China
| | - Bingdian Wang
- School of Nursing, Anhui Medical University, Hefei, Anhui 230022, PR China
| | - Sai Zhu
- Department of Nephropathy, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, PR China
| | - Xinran Liu
- Department of Nephropathy, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, PR China
| | - Xueqi Liu
- Department of Nephropathy, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, PR China
| | - Xiangming Qi
- Department of Nephropathy, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, PR China
| | - Yonggui Wu
- Department of Nephropathy, the First Affiliated Hospital of Anhui Medical University, Hefei, Anhui 230022, PR China.
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Wu Y, Wang S, Chen Y, Liao Y, Yin X, Li T, Wang R, Luo X, Xu W, Zhou J, Wang S, Bu J, Zhang X. A Multicenter Study on Preoperative Assessment of Lymphovascular Space Invasion in Early-Stage Cervical Cancer Based on Multimodal MR Radiomics. J Magn Reson Imaging 2023; 58:1638-1648. [PMID: 36929220 DOI: 10.1002/jmri.28676] [Citation(s) in RCA: 2] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/13/2022] [Revised: 03/02/2023] [Accepted: 03/04/2023] [Indexed: 03/18/2023] Open
Abstract
BACKGROUND As lymphovascular space invasion (LVSI) was closely related to lymph node metastasis and prognosis, the preoperative assessment of LVSI in early-stage cervical cancer is crucial for patients. PURPOSE To develop and validate nomogram based on multimodal MR radiomics to assess LVSI status in cervical cancer patients. STUDY TYPE Retrospective. POPULATION The study included 168 cervical cancer patients, of whom 129 cases (age 51.36 ± 9.99 years) from institution 1 were included as the training cohort and 39 cases (age 52.59 ± 10.23 years) from institution 2 were included as the external test cohort. FIELD STRENGTH/SEQUENCE There were 1.5 T and 3.0 T MRI scans (T1-weighted imaging [T1WI], fat-saturated T2-weighted imaging [FS-T2WI], and contrast-enhanced [CE]). ASSESSMENT Six machine learning models were built and selected to construct the radiomics signature. The nomogram model was constructed by combining the radiomics signature with the clinical signature, which was then validated for discrimination, calibration, and clinical usefulness. STATISTICAL TESTS The clinical characteristics were compared using t-tests, Mann-Whitney U tests, or chi-square tests. The Spearman and LASSO methods were used to select radiomics features. The receiver operating characteristic (ROC) analysis was performed, and the area under the curve (AUC), accuracy, sensitivity, and specificity were calculated. RESULTS The logistic regression (LR) model performed best in each sequence. The AUC of CE-T1-T2WI-combined was the highest in the LR model, with an AUC of 0.775 (95% CI: 0.570-0.979) in external test cohort. The nomogram showed high predictive performance in the training (AUC: 0.883 [95% CI: 0.823-0.943]) and test cohort (AUC: 0.830 [95% CI: 0.657-1.000]) for predicting LVSI. Decision curve analysis demonstrated that the nomogram was clinically useful. DATA CONCLUSION Our findings suggest that the proposed nomogram model based on multimodal MRI of CE T1WI-T2WI-combined could be used to assess LVSI status in early cervical cancer. EVIDENCE LEVEL 4. TECHNICAL EFFICACY Stage 2.
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Affiliation(s)
- Yu Wu
- Department of Radiology, Guangzhou Women and Children's Medical Center, Guangzhou, China
| | - Shuxing Wang
- Department of Radiology, Guangzhou Red Cross Hospital of Jinan University, Guangzhou, China
| | - Yiqing Chen
- Department of Radiology, Guangzhou Red Cross Hospital of Jinan University, Guangzhou, China
| | | | - Xuntao Yin
- Department of Radiology, Guangzhou Women and Children's Medical Center, Guangzhou, China
| | - Ting Li
- Department of Radiology, Guangzhou Women and Children's Medical Center, Guangzhou, China
| | - Rui Wang
- Department of Radiology, Guangzhou Women and Children's Medical Center, Guangzhou, China
| | - Xiaomei Luo
- Department of Radiology, Guangzhou Women and Children's Medical Center, Guangzhou, China
| | - Wenchan Xu
- Department of Radiology, Guangzhou Women and Children's Medical Center, Guangzhou, China
| | - Jing Zhou
- Department of Radiology, Guangzhou Red Cross Hospital of Jinan University, Guangzhou, China
| | - Simin Wang
- Department of Radiology, Guangzhou Red Cross Hospital of Jinan University, Guangzhou, China
| | - Jun Bu
- Department of Radiology, Guangzhou Red Cross Hospital of Jinan University, Guangzhou, China
| | - Xiaochun Zhang
- Department of Radiology, Guangzhou Women and Children's Medical Center, Guangzhou, China
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Lu Y, Liu H, Ye SG, Zhou LL, Luo X, Dang XY, Yuan XG, Qian WB, Liang AB, Li P. [Efficacy and safety analysis of the zanubrutinib-based bridging regimen in chimeric antigen receptor T-cell therapy for relapsed/refractory diffuse large B-cell lymphoma]. Zhonghua Xue Ye Xue Za Zhi 2023; 44:813-819. [PMID: 38049332 PMCID: PMC10694070 DOI: 10.3760/cma.j.issn.0253-2727.2023.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Received: 08/14/2023] [Indexed: 12/06/2023]
Abstract
Objective: To further elucidate the clinical efficacy and safety of a combination regimen based on the BTK inhibitor zebutanil bridging CD19 Chimeric antigen receptor T cells (CAR-T cells) in the treatment of relapsed/refractory diffuse large B-cell lymphoma (r/r DLBCL) . Methods: Twenty-one patients with high-risk r/r DLBCL were treated with a zanubrutinib-based regimen bridging CAR-T between June 2020 and June 2023 at the Department of Hematology, Tongji Hospital, Tongji University and the Second Affiliated Hospital of Zhejiang University, and the efficacy and safety were retrospectively analyzed. Results: All 21 patients were enrolled, and the median age was 57 years (range: 38-76). Fourteen patients (66.7%) had an eastern cooperative oncology group performance status score (ECOG score) of ≥2. Eighteen patients (85.7%) had an international prognostic index (IPI) score of ≥3. Three patients (14.3%) had an IPI score of 2 but had extranodal infiltration. Fourteen patients (66.7%) had double-expression of DLBCL and seven (33.3%) had TP53 mutations. With a median follow-up of 24.8 (95% CI 17.0-31.6) months, the objective response rate was 81.0%, and 11 patients (52.4%) achieved complete remission. The median progression-free survival (PFS) was 12.8 months, and the median overall survival (OS) was not reached. The 1-year PFS rate was 52.4% (95% CI 29.8% -74.3%), and the 1-year OS rate was 80.1% (95% CI 58.1% -94.6%). Moreover, 18 patients (85.7%) had grade 1-2 cytokine-release syndrome, and two patients (9.5%) had grade 1 immune effector cell-associated neurotoxicity syndrome. Conclusion: Zanubrutinib-based combination bridging regimen of CAR-T therapy for r/r DLBCL has high efficacy and demonstrated a good safety profile.
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Affiliation(s)
- Y Lu
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - H Liu
- Department of Hematology, the Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310009, China
| | - S G Ye
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - L L Zhou
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - X Luo
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - X Y Dang
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - X G Yuan
- Department of Hematology, the Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310009, China
| | - W B Qian
- Department of Hematology, the Second Affiliated Hospital, College of Medicine, Zhejiang University, Hangzhou 310009, China
| | - A B Liang
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
| | - P Li
- Department of Hematology, Tongji Hospital, Tongji University School of Medicine, Shanghai 200065, China
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Pei S, Liu N, Luo X, Don YL, Chen Z, Li D, Miao D, Duan J, Yan OY, Sheng L, Ouyang G, Wang S, Wang X. An Immune-Related Gene Prognostic Prediction Risk Model for Neoadjuvant Chemoradiotherapy in Rectal Cancer Using Artificial Intelligence. Int J Radiat Oncol Biol Phys 2023; 117:e350. [PMID: 37785213 DOI: 10.1016/j.ijrobp.2023.06.2422] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/04/2023]
Abstract
PURPOSE/OBJECTIVE(S) To develop and validate an immune-related gene prognostic model (IRGPM) that can predict disease-free survival (DFS) in patients with locally advanced rectal cancer (LARC) who received neoadjuvant chemoradiotherapy and to clarify the immune characteristics of patients with different prognostic risks. MATERIALS/METHODS In this study, we obtained transcriptomic and clinical data from the Gene Expression Omnibus (GEO) database and rectal cancer database of West China Hospital. Genes in the RNA immune-oncology panel were extracted. Elastic net was used to identify the immune-related genes that significantly affected the DFS of patients. A prognostic risk model (IRGPM) for rectal cancer was constructed with the random forest method. The prognostic risk score was calculated by the model, and the patients were divided into high- and low-risk groups according to the median risk score. Immune characteristics were analyzed and compared between the high- and low-risk groups. RESULTS A total of 407 LARC samples were used in this study. A 20-gene signature was identified by elastic net and was found to be significantly correlated with DFS. The IRGPM was constructed on the basis of the 20 immune-related genes. Kaplan‒Meier survival analysis showed poorer 5-year DFS in the high-risk group than in the low-risk group, and the receiver operating characteristic (ROC) curve suggested good model prediction (areas under the curve (AUCs) of 0.87, 0.94, 0.95 at 1, 3, and 5 years, respectively). The model was validated in the GSE190826 cohort (AUCs of 0.79, 0.64, and 0.63 at 1, 3, and 5 years, respectively) and the cohort from our institution (AUCs of 0.64, 0.66, and 0. 64 at 1, 3, and 5 years, respectively). The differentially expressed genes between the high- and low-risk groups were enriched in cytokine‒cytokine receptor interactions. The patients in the low-risk group had higher immune scores than the patients in the high-risk group. Subsequently, we found that activated B cells, activated CD8 T cells, central memory CD8 T cells, macrophages, T follicular helper cells and type 2 helper cells were more abundant in the low-risk group. Moreover, we compared the expression of immune checkpoints and found that the low-risk group had a higher PDCD1 expression level. CONCLUSION The IRGPM, which was constructed based on the random forest and elastic net methods, is a promising method to distinguish DFS in LARC patients treated with a standard strategy. The low-risk group identified by IRGPM was characterized by the activation of adaptive immunity in tumor microenvironment.
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Affiliation(s)
- S Pei
- West China Hospital, Sichuan University, Chengdu, China
| | - N Liu
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - X Luo
- Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu, China
| | - Y L Don
- West China Hospital Sichuan University, China, Chengdu, China
| | - Z Chen
- Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu, China
| | - D Li
- West China Hospital, Sichuan University, Chengdu, China
| | - D Miao
- Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu, China
| | - J Duan
- West China Hospital of Sichuan University, Chengdu, China
| | - O Y Yan
- West China Hospital, Sichuan University, Chengdu, China
| | - L Sheng
- West China Hospital of Sichuan University, Chengdu, China
| | - G Ouyang
- Department of Radiation Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
| | - S Wang
- Chengdu Institute of Computer Application, Chinese Academy of Sciences, Chengdu, China
| | - X Wang
- Department of Radiation Oncology/Abdominal Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, China
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Zhang J, Luo X, Zhou R, Dai Z, Guo C, Qu G, Li J, Zhang Z. The axial and sagittal CT values of the 7th thoracic vertebrae in screening for osteoporosis and osteopenia. Clin Radiol 2023; 78:763-771. [PMID: 37573241 DOI: 10.1016/j.crad.2023.07.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Revised: 07/06/2023] [Accepted: 07/11/2023] [Indexed: 08/14/2023]
Abstract
AIM To evaluate the difference in computed tomography (CT) attenuation value of different planes of the 7th thoracic vertebra and investigate the efficacy of axial and sagittal vertebral CT measurements in predicting osteoporosis. MATERIALS AND METHODS Patients who underwent routine chest CT and dual-energy X-ray absorptiometry (DXA) within 1 month were included in this retrospective study. The CT attenuation values of different planes were compared. Logistic regression and receiver operating characteristic (ROC) were used to analyse the difference of each plane in the diagnosis of osteoporosis. RESULTS The study included 1,338 patients (mean age of 61.9±11.9; 54% female). The CT attenuation values decreased successively in the normal group, osteopenia group, and osteoporosis group. The paired t-test results showed that the mid-axial measurements were greater than mid-sagittal measurements, with a mean difference of 9 HU, the difference was statistically significant (p<0.001, 95% confidence interval [CI] = 7.8-10.1). For each one-unit reduction in mid-sagittal CT attenuation value, the risk of osteopenia or osteoporosis increased by 3.6%. To distinguish osteoporosis from non-osteoporosis (osteopenia + normal), the sensitivity was 90% and the specificity was 52.4% at the mid-sagittal threshold of 113.7 HU. CONCLUSIONS The CT attenuation values of mid-sagittal plane have higher diagnostic efficacy than axial planes in predicting osteoporosis. For patients with a sagittal CT attenuation value of <113.7 HU in the T7, further DXA examination is warranted.
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Affiliation(s)
- J Zhang
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China
| | - X Luo
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China
| | - R Zhou
- Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China
| | - Z Dai
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China
| | - C Guo
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China
| | - G Qu
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China
| | - J Li
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Medical Department of Graduate School, Nanchang University, Nanchang, Jiangxi 330006, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China
| | - Z Zhang
- Department of Orthopedics, The First Hospital of Nanchang, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China; Nanchang Key Laboratory of Orthopaedics, The Third Affiliated Hospital of Nanchang University, Nanchang, Jiangxi 330008, China.
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Feng SM, Luo X, Xue C, Chen J, Wang K, Shao CQ, Ma C. [Effect of hollow compression screw internal fixation in treating McCrory-Bladin type Ⅱ lateral process fracture of the talus: open versus arthroscopy surgery]. Zhonghua Yi Xue Za Zhi 2023; 103:2808-2812. [PMID: 37723056 DOI: 10.3760/cma.j.cn112137-20230403-00541] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/20/2023]
Abstract
In order to explore the clinical efficacy of hollow compression screw internal fixation in the treatment of lateral process fracture of the talus under open surgery versus arthroscopy procedure, a retrospective cohort study was conducted to analyze the clinical data of 33 patients with lateral process fracture of the talus admitted to Xuzhou Central Hospital from January 2019 to December 2021. There were 19 males (19 feet) and 14 females (14 feet), aged 18 to 50 years, with an average age of (32.2±9.3) years. According to the modified McCrory-Bladin classification, all patients were classified as type Ⅱ. Based on the different surgical methods, the patients were divided into the arthroscopy group (21 cases, treated with double-tunnel subtalar arthroscopy combined with hollow compression screw internal fixation) and the open group (12 cases, treated with open reduction and internal fixation with hollow compression screw). The operation time was observed and the surgical effects were evaluated using the visual analogue scale (VAS) of pain, the American Orthopedic Foot and Ankle Society (AOFAS) ankle-hindfoot score, the Foot Function Index (FFI), and the Foot and Ankle Ability Measure (FAAM), which includes the FAAM-ADL (activity of daily living subscale) and the FAAM-S (sport subscale). All the patients of the two groups achieved stage Ⅰ wound healing. On the first day after the operation, the mean VAS score of the arthroscopy group was 2.4±0.7, which was significantly lower than that of the open group (3.4±1.6) (P=0.020). No significant difference was observed in terms of the follow-up time, operation time and AOFAS score between the two groups (all P>0.05). The FFI score of the arthroscopy group was significantly lower than that of the open group, and the FAAM-ADL and FAAM-S scores were significantly higher than those in the open group (all P<0.05). Two cases of dorsal foot numbness occurred in the open group after the operation, and the incidence of complications was not significantly different from that of the arthroscopy group (P=0.054). For McCrory-Bladin type Ⅱ lateral process fracture of the talus, the use of compression screw internal fixation could achieve reliable results, however, compared to open surgery, arthroscopy procedure obtained mini trauma and better functions.
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Affiliation(s)
- S M Feng
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
| | - X Luo
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
| | - C Xue
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
| | - J Chen
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
| | - K Wang
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
| | - C Q Shao
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
| | - C Ma
- Department of Orthopedics, Xuzhou Central Hospital (Xuzhou Medical University Xuzhou Clinical College), Xuzhou 221009, China
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Lin LL, Liu HY, Luo X, Zheng Q, Shi B, Gong M, Li CH. [Untargeted metabolomics study of dexamethasone-induced congenital cleft palate in New Zealand rabbits]. Zhonghua Kou Qiang Yi Xue Za Zhi 2023; 58:938-943. [PMID: 37659853 DOI: 10.3760/cma.j.cn112144-20230627-00254] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/04/2023]
Abstract
Objective: To investigate the metabolic disorders in placental tissues of dexamethasone induced cleft palate mode. Methods: Twelve pregnant rabbits were randomly divided into dexamethasone group (experimental group, 8) and saline control group (4), and a certain amount of dexamethasone and saline were administered intramuscularly to the experimental and control groups respectively from embryonic days (ED) 13 to 16, and placental tissue samples were collected on day 21 of gestation. The corresponding profiles of the embryonic placental tissue samples were obtained by liquid chromatography-triple tandem quadrupole(LC-MS), and the metabolites of the embryonic placental tissues were characterized by principal component analysis among the dexamethasone-treated group with cleft palate (D-CP group), the dexamethasone-treated group without cleft palate (D-NCP group) and the control group. Results: There were significant metabolic differences among the D-CP group, D-NCP group and control group, with a total of 133 differential metabolites (VIP>1, P<0.05) involving in important metabolic pathways including vitamin B6 metabolism, lysine metabolism, arginine anabolic metabolism, and galactose metabolism. The four metabolites, vitamin B6, galactose, lysine and urea, differed among the three groups (P<0.05). There were significant differences in vitamin B6 (0.960±0.249, 0.856±0.368, 1.319±0.322), galactose (0.888±0.171, 1.033±0.182, 1.127±0.127), lysine (1.551±0.924, 1.789±1.435, 0.541±0.424) and urea (0.743±0.142, 1.137±0.301, 1.171±0.457, respectively) levels among control group, D-NCP group and D-CP group (F=5.90, P=0.008; F=5.59, P=0.009; F=4.26, P=0.025; F=5.29, P=0.012). Conclusions: The results indicated that dexamethasone induced cleft palate may be highly correlated with metabolic disorders including vitamin B6 metabolism, lysine metabolism, arginine anabolic metabolism and galactose metabolism.
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Affiliation(s)
- L L Lin
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - H Y Liu
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - X Luo
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - Q Zheng
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - B Shi
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - M Gong
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
| | - C H Li
- Department of Cleft Lip and Palate Surgery, West China Hospital of Stomatology, Sichuan University & State Key Laboratory of Oral Diseases & National Center for Stomatology & National Clinical Research Center for Oral Diseases, Chengdu 610041, China
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Abratenko P, Alterkait O, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Cohen EO, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, John JS, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Double-Differential Measurement of Kinematic Imbalance in Neutrino Interactions with the MicroBooNE Detector. Phys Rev Lett 2023; 131:101802. [PMID: 37739352 DOI: 10.1103/physrevlett.131.101802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/11/2023] [Revised: 05/09/2023] [Accepted: 07/14/2023] [Indexed: 09/24/2023]
Abstract
We report the first measurement of flux-integrated double-differential quasielasticlike neutrino-argon cross sections, which have been made using the Booster Neutrino Beam and the MicroBooNE detector at Fermi National Accelerator Laboratory. The data are presented as a function of kinematic imbalance variables which are sensitive to nuclear ground-state distributions and hadronic reinteraction processes. We find that the measured cross sections in different phase-space regions are sensitive to different nuclear effects. Therefore, they enable the impact of specific nuclear effects on the neutrino-nucleus interaction to be isolated more completely than was possible using previous single-differential cross section measurements. Our results provide precision data to help test and improve neutrino-nucleus interaction models. They further support ongoing neutrino-oscillation studies by establishing phase-space regions where precise reaction modeling has already been achieved.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - O Alterkait
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - O Benevides Rodrigues
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
- Syracuse University, Syracuse, New York 13244, USA
| | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - E O Cohen
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University College London, London WC1E 6BT, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - N Oza
- Columbia University, New York, New York 10027, USA
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Salihoglu H, Shi J, Li Z, Wang Z, Luo X, Bondarev IV, Biehs SA, Shen S. Nonlocal Near-Field Radiative Heat Transfer by Transdimensional Plasmonics. Phys Rev Lett 2023; 131:086901. [PMID: 37683160 DOI: 10.1103/physrevlett.131.086901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 01/18/2023] [Accepted: 07/25/2023] [Indexed: 09/10/2023]
Abstract
Using transdimensional plasmonic materials (TDPM) within the framework of fluctuational electrodynamics, we demonstrate nonlocality in dielectric response alters near-field heat transfer at gap sizes on the order of hundreds of nanometers. Our theoretical study reveals that, opposite to the local model prediction, propagating waves can transport energy through the TDPM. However, energy transport by polaritons at shorter separations is reduced due to the metallic response of TDPM stronger than that predicted by the local model. Our experiments conducted for a configuration with a silica sphere and a doped silicon plate coated with an ultrathin layer of platinum as the TDPM show good agreement with the nonlocal near-field radiation theory. Our experimental work in conjunction with the nonlocal theory has important implications in thermophotovoltaic energy conversion, thermal management applications with metal coatings, and quantum-optical structures.
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Affiliation(s)
- H Salihoglu
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - J Shi
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Z Li
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - Z Wang
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - X Luo
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - I V Bondarev
- Mathematics & Physics Department, North Carolina Central University, Durham, North Carolina 27707, USA
| | - S-A Biehs
- Institut für Physik, Carl von Ossietzky Universität, 26111, Oldenburg, Germany
| | - S Shen
- Department of Mechanical Engineering, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
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25
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Adam J, Adamczyk L, Adams JR, Adkins JK, Agakishiev G, Aggarwal MM, Ahammed Z, Alekseev I, Anderson DM, Aparin A, Aschenauer EC, Ashraf MU, Atetalla FG, Attri A, Averichev GS, Bairathi V, Barish K, Behera A, Bellwied R, Bhasin A, Bielcik J, Bielcikova J, Bland LC, Bordyuzhin IG, Brandenburg JD, Brandin AV, Butterworth J, Caines H, Calderón de la Barca Sánchez M, Cebra D, Chakaberia I, Chaloupka P, Chan BK, Chang FH, Chang Z, Chankova-Bunzarova N, Chatterjee A, Chen D, Chen J, Chen JH, Chen X, Chen Z, Cheng J, Cherney M, Chevalier M, Choudhury S, Christie W, Chu X, Crawford HJ, Csanád M, Daugherity M, Dedovich TG, Deppner IM, Derevschikov AA, Didenko L, Dong X, Drachenberg JL, Dunlop JC, Edmonds T, Elsey N, Engelage J, Eppley G, Esumi S, Evdokimov O, Ewigleben A, Eyser O, Fatemi R, Fazio S, Federic P, Fedorisin J, Feng CJ, Feng Y, Filip P, Finch E, Fisyak Y, Francisco A, Fulek L, Gagliardi CA, Galatyuk T, Geurts F, Ghimire N, Gibson A, Gopal K, Gou X, Grosnick D, Guryn W, Hamad AI, Hamed A, Harabasz S, Harris JW, He S, He W, He XH, He Y, Heppelmann S, Heppelmann S, Herrmann N, Hoffman E, Holub L, Hong Y, Horvat S, Hu Y, Huang HZ, Huang SL, Huang T, Huang X, Humanic TJ, Huo P, Igo G, Isenhower D, Jacobs WW, Jena C, Jentsch A, Ji Y, Jia J, Jiang K, Jowzaee S, Ju X, Judd EG, Kabana S, Kabir ML, Kagamaster S, Kalinkin D, Kang K, Kapukchyan D, Kauder K, Ke HW, Keane D, Kechechyan A, Kelsey M, Khyzhniak YV, Kikoła DP, Kim C, Kimelman B, Kincses D, Kinghorn TA, Kisel I, Kiselev A, Kocan M, Kochenda L, Kosarzewski LK, Kramarik L, Kravtsov P, Krueger K, Kulathunga Mudiyanselage N, Kumar L, Kumar S, Kunnawalkam Elayavalli R, Kwasizur JH, Lacey R, Lan S, Landgraf JM, Lauret J, Lebedev A, Lednicky R, Lee JH, Leung YH, Li C, Li C, Li W, Li W, Li X, Li Y, Liang Y, Licenik R, Lin T, Lin Y, Lisa MA, Liu F, Liu H, Liu P, Liu P, Liu T, Liu X, Liu Y, Liu Z, Ljubicic T, Llope WJ, Longacre RS, Lukow NS, Luo S, Luo X, Ma GL, Ma L, Ma R, Ma YG, Magdy N, Majka R, Mallick D, Margetis S, Markert C, Matis HS, Mazer JA, Minaev NG, Mioduszewski S, Mohanty B, Mooney I, Moravcova Z, Morozov DA, Nagy M, Nam JD, Nasim M, Nayak K, Neff D, Nelson JM, Nemes DB, Nie M, Nigmatkulov G, Niida T, Nogach LV, Nonaka T, Nunes AS, Odyniec G, Ogawa A, Oh S, Okorokov VA, Page BS, Pak R, Pandav A, Panebratsev Y, Pawlik B, Pawlowska D, Pei H, Perkins C, Pinsky L, Pintér RL, Pluta J, Pokhrel BR, Porter J, Posik M, Pruthi NK, Przybycien M, Putschke J, Qiu H, Quintero A, Radhakrishnan SK, Ramachandran S, Ray RL, Reed R, Ritter HG, Rogachevskiy OV, Romero JL, Ruan L, Rusnak J, Sahoo NR, Sako H, Salur S, Sandweiss J, Sato S, Schmidke WB, Schmitz N, Schweid BR, Seck F, Seger J, Sergeeva M, Seto R, Seyboth P, Shah N, Shahaliev E, Shanmuganathan PV, Shao M, Sheikh AI, Shen WQ, Shi SS, Shi Y, Shou QY, Sichtermann EP, Sikora R, Simko M, Singh J, Singha S, Smirnov N, Solyst W, Sorensen P, Spinka HM, Srivastava B, Stanislaus TDS, Stefaniak M, Stewart DJ, Strikhanov M, Stringfellow B, Suaide AAP, Sumbera M, Summa B, Sun XM, Sun X, Sun Y, Sun Y, Surrow B, Svirida DN, Szymanski P, Tang AH, Tang Z, Taranenko A, Tarnowsky T, Thomas JH, Timmins AR, Tlusty D, Tokarev M, Tomkiel CA, Trentalange S, Tribble RE, Tribedy P, Tripathy SK, Tsai OD, Tu Z, Ullrich T, Underwood DG, Upsal I, Van Buren G, Vanek J, Vasiliev AN, Vassiliev I, Videbæk F, Vokal S, Voloshin SA, Wang F, Wang G, Wang JS, Wang P, Wang Y, Wang Y, Wang Z, Webb JC, Weidenkaff PC, Wen L, Westfall GD, Wieman H, Wissink SW, Witt R, Wu Y, Xiao ZG, Xie G, Xie W, Xu H, Xu N, Xu QH, Xu YF, Xu Y, Xu Z, Xu Z, Yang C, Yang Q, Yang S, Yang Y, Yang Z, Ye Z, Ye Z, Yi L, Yip K, Yu Y, Zbroszczyk H, Zha W, Zhang C, Zhang D, Zhang S, Zhang S, Zhang XP, Zhang Y, Zhang Y, Zhang ZJ, Zhang Z, Zhang Z, Zhao J, Zhong C, Zhou C, Zhu X, Zhu Z, Zurek M, Zyzak M. Erratum: Global Polarization of Ξ and Ω Hyperons in Au+Au Collisions at sqrt[s_{NN}]=200 GeV [Phys. Rev. Lett. 126, 162301 (2021)]. Phys Rev Lett 2023; 131:089901. [PMID: 37683178 DOI: 10.1103/physrevlett.131.089901] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 07/28/2023] [Indexed: 09/10/2023]
Abstract
This corrects the article DOI: 10.1103/PhysRevLett.126.162301.
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26
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Xiong LB, Zou XP, Ning K, Luo X, Peng YL, Zhou ZH, Wang J, Li Z, Yu CP, Dong P, Guo SJ, Han H, Zhou FJ, Zhang ZL. [Establishment and validation of a novel nomogram to predict overall survival after radical nephrectomy]. Zhonghua Zhong Liu Za Zhi 2023; 45:681-689. [PMID: 37580273 DOI: 10.3760/cma.j.cn112152-20221027-00722] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/16/2023]
Abstract
Objective: To establish a nomogram prognostic model for predicting the 5-, 10-, and 15-year overall survival (OS) of non-metastatic renal cell carcinoma patients managed with radical nephrectomy (RN), compare the modelled results with the results of pure pathologic staging, the Karakiewicz nomogram and the Mayo Clinic Stage, Size, Grade, and Necrosis (SSIGN) score commonly used in foreign countries, and stratify the patients into different prognostic risk subgroups. Methods: A total of 1 246 non-metastatic renal cell carcinoma patients managed with RN in Sun Yat-sen University Cancer Center (SYSUCC) from 1999 to 2020 were retrospectively analyzed. Multivariate Cox regression analysis was used to screen the variables that influence the prognosis for nomogram establishment, and the bootstrap random sampling was used for internal validation. The time-receiver operating characteristic curve (ROC), the calibration curve and the clinical decision curve analysis (DCA) were applied to evaluate the nomogram. The prediction efficacy of the nomogram and that of the pure pathologic staging, the Karakiewicz nomogram and the SSIGN score was compared through the area under the curve (AUC). Finally, patients were stratified into different risk subgroups according to our nomogram scores. Results: A total of 1 246 patients managed with RN were enrolled in this study. Multivariate Cox regression analysis showed that age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological T and N stages were independent prognostic factors for RN patients (all P<0.05). A nomogram model named SYSUCC based on these factors was built to predict the 5-, 10-, and 15-year survival rate of the participating patients. In the bootstrap random sampling with 1 000 iterations, all these factors occurred for more than 800 times as independent predictors. The Harrell's concordance index (C-index) of SYSUCC was higher compared with pure pathological staging [0.770 (95% CI: 0.716-0.823) vs 0.674 (95% CI: 0.621-0.728)]. The calibration curve showed that the survival rate as predicted by the SYSUCC model simulated the actual rate, while the clinical DCA showed that the SYSUCC nomogram has a benefit in certain probability ranges. In the ROC analysis that included 857 patients with detailed pathological nuclear stages, the nomogram had a larger AUC (5-/10-year AUC: 0.823/0.804) and better discriminating ability than pure pathological staging (5-/10-year AUC: 0.701/0.658), Karakiewicz nomogram (5-/10-year AUC: 0.772/0.734) and SSIGN score (5-/10-year AUC: 0.792/0.750) in predicting the 5-/10-year OS of RN patients (all P<0.05). In addition, the AUC of the SYSUCC nomogram for predicting the 15-year OS (0.820) was larger than that of the SSIGN score (0.709), and there was no statistical difference (P<0.05) between the SYSUCC nomogram, pure pathological staging (0.773) and the Karakiewicz nomogram (0.826). The calibration curve was close to the standard curve, which indicated that the model has good predictive performance. Finally, patients were stratified into low-, intermediate-, and high-risk subgroups (738, 379 and 129, respectively) according to the SYSUCC nomogram scores, among whom patients in intermediate- and high-risk subgroups had a worse OS than patients in the low-risk subgroup (intermediate-risk group vs. low-risk group: HR=4.33, 95% CI: 3.22-5.81, P<0.001; high-risk group vs low-risk group: HR=11.95, 95% CI: 8.29-17.24, P<0.001), and the high-risk subgroup had a worse OS than the intermediate-risk group (HR=2.63, 95% CI: 1.88-3.68, P<0.001). Conclusions: Age, smoking history, pathological nuclear grade, sarcomatoid differentiation, tumor necrosis and pathological stage were independent prognostic factors for non-metastasis renal cell carcinoma patients after RN. The SYSUCC nomogram based on these independent prognostic factors can better predict the 5-, 10-, and 15-year OS than pure pathological staging, the Karakiewicz nomogram and the SSIGN score of patients after RN. In addition, the SYSUCC nomogram has good discrimination, agreement, risk stratification and clinical application potential.
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Affiliation(s)
- L B Xiong
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - X P Zou
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - K Ning
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - X Luo
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Y L Peng
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z H Zhou
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - J Wang
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z Li
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - C P Yu
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - P Dong
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - S J Guo
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - H Han
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - F J Zhou
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z L Zhang
- Department of Urology, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
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Zhang X, Ma LN, Wang MT, Liu HJ, Tian YL, Luo X, Ding XC. [Short-term prognostic predictive value of the neutrophil/lymphocyte ratio combined with prognostic nutritional index in hepatitis B virus-related acute-on-chronic liver failure]. Zhonghua Gan Zang Bing Za Zhi 2023; 31:847-854. [PMID: 37723067 DOI: 10.3760/cma.j.cn501113-20220402-00159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 09/20/2023]
Abstract
Objective: To explore the prognostic predictive value of neutrophil/lymphocyte ratio (NLR) combined with prognostic nutritional index (PNI) in patients with hepatitis B virus-related acute-on-chronic liver failure (HBV-ACLF). Methods: Clinical data from 149 HBV-ACLF patients admitted to the infectious diseases Department of the General Hospital of Ningxia Medical University were retrospectively analyzed. Demographic data of the enrolled patients and the initial clinical-related data after admission were collected. Patients were divided into survival (93 cases) and death groups (56 cases) according to their prognostic condition 90 days after discharge. Demographic and clinical differences were compared between the two groups data. Receiver operating characteristic (ROC) curves were plotted to determine the optimal cutoff values for NLR and PNI in predicting the 90-day mortality rate of HBV-ACLF patients. The COX regression model was used to conduct univariate and multivariate analyses to investigate the correlation between NLR and PNI and the prognosis of HBV-ACLF patients. Kaplan-Meier survival analysis was used to explore the effects of NLR and PNI on the survival of HBV-ACLF patients. Results: The death group NLR was higher than that of the survival group, while the PNI was lower than that of the survival group, with a statistically significant difference. The area under the receiver operating characteristic curve (0.842, 95% CI: 0.779-0.906) showed patients with adverse prognosis assessed by NLR combined with PNI had a superior prognosis than that of the Model for End-Stage Liver Disease (MELD) and its combined serum sodium (MELD-Na) and Child-Turcotte-Pugh (CTP) scores. COX regression analysis showed that NLR≥3.03 and MELD score were independent risk factors affecting the prognosis of HBV-ACLF patients. PNI > 36.13 was a protective factor for evaluating the prognosis of HBV-ACLF patients. Conclusion: NLR combined with PNI can enhance the prognostic predictive value of HBV-ACLF.
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Affiliation(s)
- X Zhang
- Department of Infectious Diseases, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - L N Ma
- Department of Infectious Diseases, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - M T Wang
- Ningxia Medical University, Yinchuan 750004, China
| | - H J Liu
- Department of Infectious Diseases, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - Y L Tian
- Ningxia Medical University, Yinchuan 750004, China
| | - X Luo
- Department of Infectious Diseases, General Hospital of Ningxia Medical University, Yinchuan 750004, China
| | - X C Ding
- Department of Infectious Diseases, General Hospital of Ningxia Medical University, Yinchuan 750004, China
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Zhou M, Luo X, Zhou QL, Zhou WH, Zheng R, Zhang YN, Wu XF, Wu S, Su J, Xiong GW, Cheng Y, Li YT, Zhang PP, Zhang K, Dai M, Huang XK, Shi ZH, Tao J, Zhou YQ, Feng PY, Chen ZG, Yang QT. [Diagnosis and treatment procedures and health management for patients with hereditary angioedema]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:1280-1285. [PMID: 37574324 DOI: 10.3760/cma.j.cn112150-20230509-00359] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Subscribe] [Scholar Register] [Indexed: 08/15/2023]
Abstract
As a recognized rare and highly fatal disease, hereditary angioedema (HAE) is difficult to diagnose and characterized by recurrent edema involving the head, limbs, genitals and larynx, etc. Diagnosis of HAE is not difficult. However, low incidence and lack of clinical characteristics lead to difficulty of doctors on timely diagnosis and correct intervention for HAE patients. Therefore, it is crucial to improve the awareness of this disease and prevent its recurrence. for HAE patients. In view of absent cognition of doctors and the general public on HAE, patients often suffer from sudden death or become disabled due to laryngeal edema which cannot be treated in time. Thus, based on the Internet mobile terminal platform, the team set up an all-day rapid emergency response system which is provided for HAE patients by setting up "one-click help". The aim is to offer optimization on overall management of HAE and designed the intelligent follow-up management to provide timely assistance and specialized suggestion for patients with acute attacks.
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Affiliation(s)
- M Zhou
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - X Luo
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - Q L Zhou
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - W H Zhou
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - R Zheng
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - Y N Zhang
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - X F Wu
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - S Wu
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - J Su
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - G W Xiong
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y Cheng
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y T Li
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - P P Zhang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - K Zhang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Traditional Chinese Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - M Dai
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Traditional Chinese Medicine, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - X K Huang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - Z H Shi
- Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
| | - J Tao
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Gastroenterology, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Y Q Zhou
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Respiratory and Intensive Care, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - P Y Feng
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Dermatology and Cosmetic Surgery, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Z G Chen
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Pediatrics, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China
| | - Q T Yang
- Department of Allergy, The Third Affiliated Hospital of Sun Yat-Sen University, Guangzhou 510630, China Department of Otolaryngology, The Third Affiliated Hospital of Sun Yat-sen University, Guangzhou 510630, China
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Luo X, Cheng Y, Wu C, He J. [An interpretable machine learning-based prediction model for risk of death for patients with ischemic stroke in intensive care unit]. NAN FANG YI KE DA XUE XUE BAO = JOURNAL OF SOUTHERN MEDICAL UNIVERSITY 2023; 43:1241-1247. [PMID: 37488807 PMCID: PMC10366517 DOI: 10.12122/j.issn.1673-4254.2023.07.21] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 07/26/2023]
Abstract
OBJECTIVE To construct an inherent interpretability machine learning model as an explainable boosting machine model (EBM) for predicting one-year risk of death in patients with severe ischemic stroke. METHODS We randomly divided the data of 2369 eligible patients with severe ischemic stroke in the MIMIC-Ⅳ(2.0) database, who were admitted in ICU in 2008 to 2019, into a training dataset (80%) and a test dataset (20%), and assessed the prognosis of the patients using the EBM model. The prediction performance of the model was evaluated by calculating the area under the receiver operating characteristic (AUC) curve. The calibration curve and Brier score were used to evaluate the degree of calibration of the model, and a decision curve was generated to assess the net clinical benefit. RESULTS The EBM model constructed in this study had good discrimination power, calibration and net benefit, with an AUC of 0.857 (95% CI: 0.831-0.887) for predicting prognosis of severe ischemic stroke. Calibration curve analysis showed that the standard curve of the EBM model was the closest to the ideal curve. Decision curve analysis showed that the model had the greatest net benefit rate at the prediction probability threshold of 0.10 to 0.80. The top 5 independent predictive variables based on the EBM model were age, SOFA score, mean heart rate, mechanical ventilation, and mean respiratory rate, whose significance scores ranged from 0.179 to 0.370. CONCLUSION This EBM model has a good performance for predicting the risk of death within one year in patients with severe ischemic stroke and allows clinicians to better understand the contributing factors of the patients' outcomes through the model interpretability.
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Affiliation(s)
- X Luo
- Department of Military Health Statistics, Naval Medical University, Shanghai 200433, China
| | - Y Cheng
- Department of Military Health Statistics, Naval Medical University, Shanghai 200433, China
| | - C Wu
- Department of Military Health Statistics, Naval Medical University, Shanghai 200433, China
| | - J He
- Department of Military Health Statistics, Naval Medical University, Shanghai 200433, China
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He Z, Lei Y, Gong W, Ye M, Luo X. Karyotype and Phylogenetic Relationship Analysis of Five Varieties and Cultivars of Zanthoxylum armatum Based on Oligo-FISH. Genes (Basel) 2023; 14:1459. [PMID: 37510363 PMCID: PMC10379346 DOI: 10.3390/genes14071459] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 07/12/2023] [Accepted: 07/14/2023] [Indexed: 07/30/2023] Open
Abstract
Green prickly ash (Zanthoxylum armatum) has edible and medicinal value and is an economically significant plant in many countries. Z. armatum has many cultivars and varieties with similar phenotypes that are difficult to distinguish via traditional methods. In this study, we utilized oligo-FISH to distinguish five varieties and cultivars of Z. armatum on the basis of three oligonucleotide probes of 5S rDNA, (AG3T3)3, and (GAA)6. Karyotype analysis of the five varieties and cultivars of Z. armatum showed that the Z. armatum 'Tengjiao' karyotype formula was 2n = 2x = 98m with karyotype type 1C and an arm ratio of 4.3237, including two pairs of 5S rDNA signals and five pairs of (GAA)6 signals. The karyotype formula of Z. armatum 'Youkangtengjiao' was 2n = 2x = 128m + 8sm with karyotype type 2B and an arm ratio of 3.5336, including three pairs of 5S rDNA signals and 17 pairs of (GAA)6 signals. The karyotype formula of Z. armatum var. novemfolius was 2n = 2x = 134m + 2sm with karyotype type 1C and an arm ratio of 5.5224, including two pairs of 5S rDNA signals and eight pairs of (GAA)6 signals. The karyotype formula of Z. armatum 'YT-03' was 2n = 2x = 2M + 128m + 4sm + 2st with karyotype type 2C and an arm ratio of 4.1829, including three pairs of 5S rDNA signals and nine pairs of (GAA)6 signals. The karyotype formula of Z. armatum 'YT-06' was 2n = 2x = 126m + 10sm with cytotype 2B and an arm ratio of 3.3011, including three pairs of 5S rDNA signals and two pairs of (GAA)6 signals. The five varieties and cultivars of Z. armatum had (AG3T3)3 signals on all chromosomes. The chromosomal symmetry of Z. armatum 'Tengjiao' was high, whereas the chromosomal symmetry of Z. armatum 'YT-03' was low, with the karyotypes of the five materials showing a trend toward polyploid evolution. The phylogenetic relationship between Z. armatum 'Tengjiao' and Z. armatum var. novemfolius was the closest, while that between Z. armatum 'YT-03' and Z. armatum 'YT-06' was closer than with Z. armatum 'Youkangtengjiao' according to oligo-FISH. The results provided a karyotype profile and a physical map that contributes to the distinction of varieties and cultivars of Z. armatum and provides strategies for distinguishing other cultivated species.
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Affiliation(s)
- Zhoujian He
- College of Forestry, Sichuan Agricultural University, Chengdu 611130, China
| | - Yuting Lei
- College of Forestry, Sichuan Agricultural University, Chengdu 611130, China
| | - Wei Gong
- College of Forestry, Sichuan Agricultural University, Chengdu 611130, China
| | - Meng Ye
- College of Forestry, Sichuan Agricultural University, Chengdu 611130, China
| | - Xiaomei Luo
- National Forestry and Grassland Administration Key Laboratory of Forest Resources Conservation and Ecological Safety on the Upper Reaches of the Yangtze River & Forestry Ecological Engineering in the Upper Reaches of the Yangtze River Key Laboratory of Sichuan Province, Sichuan Agricultural University, Chengdu 611130, China
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Luo X, Tang KY, Wang YY. Preparation of drug-loaded chitosan microspheres repair materials. Eur Rev Med Pharmacol Sci 2023; 27:6489-6495. [PMID: 37522660 DOI: 10.26355/eurrev_202307_33119] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Subscribe] [Scholar Register] [Indexed: 08/01/2023]
Abstract
OBJECTIVE With the development of society and the progress of science and technology, microspheres, as a new polymer material, have been applied to all aspects of human beings. Microspheres can play a huge role in food safety, electronic technology, sewage treatment, biomedicine, etc., and are non-toxic or harmless. There are three main types of substrates for the preparation of microspheres: natural polymers, semi-synthetic polymer materials, and synthetic polymer materials. MATERIALS AND METHODS In this study, the inorganic material kaolin was modified by the emulsification-crosslinking method with chitosan and composite microspheres with large interlayer spacing were prepared, which were characterized by Fourier Transform Ioncyclotron Resonancel (FTIR) analysis and Scanning Electron Microscope (SEM). The prepared kaolin/chitosan microspheres were then placed in different amounts of aspirin and the optimal dose was investigated by encapsulation efficiency and drug loading rate. The drug release rate of 0.5 h, 1 h, 1.5 h, 2 h, 4 h, 6 h, and 12 h was then determined by simulating the human colon to determine the performance of the sustained-release drug. RESULTS The experimental results showed that after the prepared composite microspheres were loaded with aspirin drug, we got the optimal dosage of 0.1 g by discussing the encapsulation efficiency and drug loading rate of the drug-loaded microspheres, and the encapsulation efficiency reached 80.80%, while the drug loading rate was 24.40%, the drug release capacity reached about 83% in about 12 hours. CONCLUSIONS The research shows that the kaolin/chitosan drug-loaded microspheres prepared by the emulsification and cross-linking method are excellent drug-loading materials.
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Affiliation(s)
- X Luo
- School of Material Science and Engineering, Zhengzhou University, Zhengzhou, Henan, China.
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Abratenko P, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Djurcic Z, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Nunes M, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Rafique A, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, John JS, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Measurement of Quasielastic Λ Baryon Production in Muon Antineutrino Interactions in the MicroBooNE Detector. Phys Rev Lett 2023; 130:231802. [PMID: 37354393 DOI: 10.1103/physrevlett.130.231802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/16/2022] [Revised: 04/07/2023] [Accepted: 04/28/2023] [Indexed: 06/26/2023]
Abstract
We present the first measurement of the cross section of Cabibbo-suppressed Λ baryon production, using data collected with the MicroBooNE detector when exposed to the neutrinos from the main injector beam at the Fermi National Accelerator Laboratory. The data analyzed correspond to 2.2×10^{20} protons on target running in neutrino mode, and 4.9×10^{20} protons on target running in anti-neutrino mode. An automated selection is combined with hand scanning, with the former identifying five candidate Λ production events when the signal was unblinded, consistent with the GENIE prediction of 5.3±1.1 events. Several scanners were employed, selecting between three and five events, compared with a prediction from a blinded Monte Carlo simulation study of 3.7±1.0 events. Restricting the phase space to only include Λ baryons that decay above MicroBooNE's detection thresholds, we obtain a flux averaged cross section of 2.0_{-1.7}^{+2.2}×10^{-40} cm^{2}/Ar, where statistical and systematic uncertainties are combined.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - Z Djurcic
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - M Nunes
- Syracuse University, Syracuse, New York 13244, USA
| | - N Oza
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Rafique
- Argonne National Laboratory (ANL), Lemont, Illinois 60439, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Acciarri R, Adams C, Baller B, Basque V, Cavanna F, Co RT, Fitzpatrick RS, Fleming B, Green P, Harnik R, Kelly KJ, Kumar S, Lang K, Lepetic I, Liu Z, Luo X, Lyu KF, Palamara O, Scanavini G, Soderberg M, Spitz J, Szelc AM, Wu W, Yang T. First Constraints on Heavy QCD Axions with a Liquid Argon Time Projection Chamber Using the ArgoNeuT Experiment. Phys Rev Lett 2023; 130:221802. [PMID: 37327426 DOI: 10.1103/physrevlett.130.221802] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/23/2022] [Accepted: 04/21/2023] [Indexed: 06/18/2023]
Abstract
We present the results of a search for heavy QCD axions performed by the ArgoNeuT experiment at Fermilab. We search for heavy axions produced in the NuMI neutrino beam target and absorber decaying into dimuon pairs, which can be identified using the unique capabilities of ArgoNeuT and the MINOS near detector. This decay channel is motivated by a broad class of heavy QCD axion models that address the strong CP and axion quality problems with axion masses above the dimuon threshold. We obtain new constraints at a 95% confidence level for heavy axions in the previously unexplored mass range of 0.2-0.9 GeV, for axion decay constants around tens of TeV.
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Affiliation(s)
- R Acciarri
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - C Adams
- Argonne National Laboratory, Lemont, Illinois 60439, USA
| | - B Baller
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - V Basque
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - R T Co
- School of Physics and Astronomy, University of Minnesota, Minneapolis, Minnesota 55455, USA
- William I. Fine Theoretical Physics Institute, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Fleming
- Yale University, New Haven, Connecticut 06520, USA
| | - P Green
- University of Manchester, Manchester M13 9PL, United Kingdom
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - R Harnik
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - K J Kelly
- CERN, Esplande des Particules, 1211 Geneva 23, Switzerland
| | - S Kumar
- University of California, Berkeley, California 94720, USA
- Lawrence Berkeley National Laboratory, Berkeley, California 94720, USA
| | - K Lang
- University of Texas at Austin, Austin, Texas 78712, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - Z Liu
- School of Physics and Astronomy, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - X Luo
- University of California, Santa Barbara, California, 93106, USA
| | - K F Lyu
- School of Physics and Astronomy, University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - O Palamara
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - G Scanavini
- Yale University, New Haven, Connecticut 06520, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Wu
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
| | - T Yang
- Fermi National Accelerator Laboratory, Batavia, Illinois 60510, USA
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Zou XP, Ning K, Zhang ZL, Xiong LB, Peng YL, Zhou ZH, Huang YX, Luo X, Li JB, Dong P, Guo SJ, Han H, Zhou FJ. [Efficacy of partial nephrectomy in patients with localized renal carcinoma: a 20-year experience of 2 046 patients in a single center]. Zhonghua Wai Ke Za Zhi 2023; 61:395-402. [PMID: 36987674 DOI: 10.3760/cma.j.cn112139-20221002-00416] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/30/2023]
Abstract
Objectives: To analyze the long-term survival of patients with localized renal cell carcinoma after partical nephrectomy. Methods: The clinicopathological records and survival follow-up data of 2 046 patients with localized renal cell carcinoma, who were treated with partial nephrectomy from August 2001 to February 2021 in the Department of Urology, Sun Yat-sen University Cancer Center, were retrospectively analyzed. There were 1 402 males and 644 females, aged (M(IQR)) 51 (19) years (range: 6 to 86 years). The primary end point of this study was cancer-specific survival. Survival curves were estimated using the Kaplan-Meier method, and the difference test was performed by Log-rank test. Univariate and multivariate Cox analysis were fitted to determine factors associated with cancer-specific survival. Results: The follow-up time was 49.2 (48.0) months (range: 1 to 229 months), with 1 974 patients surviving and 72 dying. The median cancer-specific survival time has not yet been reached. The 5- and 10-year cancer specific survival rates were 97.0% and 91.2%, respectively. The 10-year cancer-specific survival rates for stage pT1a (n=1 447), pT1b (n=523) and pT2 (n=58) were 95.3%, 81.8%, and 81.7%, respectively. The 10-year cancer-specific survival rates of patients with nuclear grade 1 (n=226), 2 (n=1 244) and 3 to 4 (n=278) were 96.6%, 89.4%, and 85.5%, respectively. There were no significant differences in 5-year cancer-specific survival rates among patients underwent open, laparoscopic, or robotic surgery (96.7% vs. 97.1% vs. 97.5%, P=0.600). Multivariate analysis showed that age≥50 years (HR=3.93, 95%CI: 1.82 to 8.47, P<0.01), T stage (T1b vs. T1a: HR=3.31, 95%CI: 1.83 to 5.99, P<0.01; T2+T3 vs. T1a: HR=2.88, 95%CI: 1.00 to 8.28, P=0.049) and nuclear grade (G3 to 4 vs. G1: HR=2.81, 95%CI: 1.01 to 7.82, P=0.048) were independent prognostic factors of localized renal cell carcinoma after partial nephrectomy. Conclusions: The long-term cancer-specific survival rates of patients with localized renal cancer after partial nephrectomy are satisfactory. The type of operation (open, laparoscopic, or robotic) has no significant effect on survival. However, patients with older age, higher nuclear grade, and higher T stage have a lower cancer-specific survival rate. Grasping surgical indications, attaching importance to preoperative evaluation, perioperative management, and postoperative follow-up, could benefit achieving satisfactory long-term survival.
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Affiliation(s)
- X P Zou
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - K Ning
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z L Zhang
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - L B Xiong
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Y L Peng
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Z H Zhou
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - Y X Huang
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - X Luo
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - J B Li
- Department of Clinical Research, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - P Dong
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - S J Guo
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - H Han
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
| | - F J Zhou
- Department of Urology, Sun Yat-sen University Cancer Center, Guangzhou 510060, China
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Munns CF, Yoo HW, Jalaludin MY, Vasanwala RF, Chandran M, Rhee Y, But WM, Kong AP, Su PH, Numbenjapon N, Namba N, Imanishi Y, Clifton‐Bligh R, Luo X, Xia W. Asia‐Pacific
Consensus Recommendations on
X‐Linked
Hypophosphatemia: Diagnosis, Multidisciplinary Management, and Transition from Pediatric to Adult Care. JBMR Plus 2023. [DOI: 10.1002/jbm4.10744] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 03/30/2023] Open
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Lin Z, Shi G, Liao X, Liu W, Luo X, Zhan H, Cai X. Effect of pulmonary function on bone mineral density in the United States: results from the NHANES 2007-2010 study. Osteoporos Int 2023; 34:955-963. [PMID: 36952024 DOI: 10.1007/s00198-023-06727-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 12/15/2022] [Accepted: 03/16/2023] [Indexed: 03/24/2023]
Abstract
UNLABELLED The relationship between pulmonary function (PF) and bone mineral density (BMD) remains controversial. In the US population, we found a positive association between PF and BMD. Mixed variables such as age, gender, and race may influence this association. INTRODUCTION Based on the data from the National Health and Nutrition Examination Survey (NHANES) from 2007 to 2010, this study explored whether there is a correlation between PF (1st second forceful expiratory volume as a percentage of expected value (FEV1(% predicted)), (one-second rate (FEV1/FVC)), and bone mineral density. METHODS We evaluated the relationship between PF and BMD in 6327 NHANES subjects (mean age 44.51 ± 15.64 years) from 2007 to 2010. The bone mineral density of the whole femur was measured by dual-energy X-ray absorptiometry (DXA). After adjusting for a wide range of confounders, we examined the relationship between PF and total femur BMD using a multiple linear regression model. RESULTS Correction of race, age, alcohol consumption, body mass index (BMI), height, poor income ratio (PIR), total protein, serum calcium, serum uric acid, cholesterol, serum phosphorus, blood urea nitrogen, FEV1(% predicted), and femur BMD were positively correlated (β = 0.032, 95% CI: 0.010-0.054, P = 0.004). FEV1/FVC was positively correlated with spine BMD (β = 0.275 95%CI: 0.102-0.448, P = 0.002). CONCLUSIONS Our study shows that PF is positively associated with BMD in the US population. A variety of factors such as race and age influence this relationship. the relationship between PF and BMD needs to be further investigated, including specific regulatory mechanisms and confounding factors.
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Affiliation(s)
- Z Lin
- Department of Orthopedics, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China
| | - G Shi
- Department of Orthopedics, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China
| | - X Liao
- Department of Orthopedics, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China
| | - W Liu
- Department of Orthopedics, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China
| | - X Luo
- Department of Orthopedics, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China
| | - H Zhan
- Department of Rehabilitation, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China
| | - X Cai
- Department of Orthopedics, Fifth Affiliated Hospital of Sun Yat-sen University, Guangdong Province, Zhuhai, China.
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Luo X, Wang R, Sun Y, Qiu W, Lu D, Wang Y, Gong Z, Zhang H, Han L, Liang L, Gu X, Yu Y, Xiao B. Deep Intronic PAH Variants Explain Missing Heritability in Hyperphenylalaninemia. J Mol Diagn 2023; 25:284-294. [PMID: 36849017 DOI: 10.1016/j.jmoldx.2023.02.001] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/21/2022] [Revised: 01/18/2023] [Accepted: 02/02/2023] [Indexed: 02/27/2023] Open
Abstract
Phenylalanine hydroxylase (PAH) deficiency or phenylketonuria (PKU) is the most common cause of hyperphenylalaninemia (HPA), and approximately 5% of patients remain genetically unsolved. Identifying deep intronic PAH variants may help improve their molecular diagnostic rate. Next-generation sequencing was utilized to detect the whole PAH gene in 96 patients with genetically unsolved HPA from 2013 to 2022. The effects of deep intronic variants on pre-mRNA splicing were investigated by minigene-based assay. The allelic phenotype values of recurrent deep intronic variants were calculated. Twelve deep intronic PAH variants, located in intron 5 (c.509+434C>T), intron 6 (c.706+288T>G, c.706+519T>C, c.706+531T>C, c.706+535G>T, c.706+600A>C, c.706+603T>G, and c.706+608A>C), intron 10 (c.1065+241C>A and c.1065+258C>A), and intron 11 (c.1199+502A>T and c.1199+745T>A) were identified in 80.2% (77/96) patients. Ten of the 12 variants were novel, and they all generated pseudoexons in mRNA, leading to frameshift or lengthened proteins. The most prevalent deep intronic variant was c.1199+502A>T, followed by c.1065+241C>A, c.1065+258C>A, and c.706+531T>C. The metabolic phenotypes of the four variants were assigned as classic PKU, mild HPA, mild HPA, and mild PKU, respectively. The results suggest that deep intronic PAH variants improved the diagnostic rate from 95.3% to 99.3% in the overall patients with HPA. Our data demonstrate the importance of assessing noncoding variants in genetic diseases. Pseudoexon inclusion caused by deep intronic variants could represent a recurrent mechanism.
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Affiliation(s)
- Xiaomei Luo
- Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Institute for Pediatric Research, Shanghai, China
| | - Ruifang Wang
- Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Institute for Pediatric Research, Shanghai, China
| | - Yu Sun
- Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Institute for Pediatric Research, Shanghai, China
| | - Wenjuan Qiu
- Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Institute for Pediatric Research, Shanghai, China
| | - Deyun Lu
- Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Institute for Pediatric Research, Shanghai, China
| | - Yu Wang
- Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Institute for Pediatric Research, Shanghai, China
| | - Zhuwen Gong
- Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Institute for Pediatric Research, Shanghai, China
| | - Huiwen Zhang
- Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Institute for Pediatric Research, Shanghai, China
| | - Lianshu Han
- Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Institute for Pediatric Research, Shanghai, China
| | - Lili Liang
- Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Institute for Pediatric Research, Shanghai, China
| | - Xuefan Gu
- Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Institute for Pediatric Research, Shanghai, China
| | - Yongguo Yu
- Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Institute for Pediatric Research, Shanghai, China.
| | - Bing Xiao
- Department of Pediatric Endocrinology and Genetic Metabolism, Xinhua Hospital, School of Medicine, Shanghai Jiao Tong University, Shanghai, China; Shanghai Institute for Pediatric Research, Shanghai, China.
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Luo X, Cai XB, Lu LG. [Research progress of liver sinusoidal endothelial cells in nonalcoholic fatty liver disease]. Zhonghua Gan Zang Bing Za Zhi 2023; 31:212-215. [PMID: 37137841 DOI: 10.3760/cma.j.cn501113-20211009-00497] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Subscribe] [Scholar Register] [Indexed: 05/05/2023]
Abstract
Non-alcoholic fatty liver disease (NAFLD) is widespread worldwide and thereby a very serious public health problem. There are currently no effective drug treatment measures. Liver sinusoidal endothelial cells (LSECs) are the most abundant non-parenchymal cells in the liver; however, it is still not clear what role LSECs play in NAFLD. This article reviews the research progress of LSECs in NAFLD in recent years in order to provide some reference for subsequent research.
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Affiliation(s)
- X Luo
- Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - X B Cai
- Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
| | - L G Lu
- Department of Gastroenterology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai 200080, China
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Chen J, Luo X, Wang G, Zhang J, Zhang Y. Analysis of m 6A methylation patterns and tumor microenvironment in endometrial cancer. Gene 2023; 852:147052. [PMID: 36395970 DOI: 10.1016/j.gene.2022.147052] [Citation(s) in RCA: 1] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/04/2022] [Revised: 10/25/2022] [Accepted: 11/09/2022] [Indexed: 11/15/2022]
Abstract
BACKGROUND The N6-methyladenosine (m6A) modification is the most common epigenetic modification in eukaryotic mRNA. In recent years, lots of studies have shown that the tumor microenvironment (TME) plays a critical role in tumor growth and development. However, there are few studies on the interaction between m6A methylation and the TME in uterine corpus endometrial carcinoma (UCEC). METHODS Three distinct m6A modification patterns were based on 21 m6A regulators of UCEC patients and tumor-free individuals. We investigated the relationship between m6A modification patterns and associated features of the TME. Differentially expressed genes were selected and the m6A score was established to evaluate the prognosis and immunotherapeutic efficacy of UCEC patients. RESULTS We identified three different m6A modification patterns. The TME infiltrating characteristics were highly consistent with tumors with three distinct immune phenotypes. Besides, our analysis showed that the m6A score was shown to be useful in predicting clinical outcomes. Patients with the low m6A score seemed to have a better prognosis, a stronger immunotherapeutic response, and a higher tumor mutation burden. CONCLUSION Our study explored the influence of m6A modification and TME on the prognosis of cancer patients, which will contribute to the discovery of immunotherapy strategies to improve their prognosis.
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Affiliation(s)
- Junfeng Chen
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Xiaomei Luo
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Guocheng Wang
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China
| | - Jing Zhang
- Department of Gynecological Oncology, The First Affiliated Hospital of Bengbu Medical College, Anhui, China.
| | - Yongli Zhang
- Department of Obstetrics and Gynecology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai 200092, China.
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Zhang J, Zhou Y, Guo J, Li J, Wu Y, Zhou Z, Zhu H, Luo X, Chen D, Li Q, Liu X, Li W. [Prevalence and molecular characterization of Cryptosporidium in captive-bred Mustela putorius furo in Jiangsu Province]. Zhongguo Xue Xi Chong Bing Fang Zhi Za Zhi 2023; 35:73-77. [PMID: 36974018 DOI: 10.16250/j.32.1374.2022159] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Grants] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Abstract
OBJECTIVE To investigate the prevalence and molecular features of Cryptosporidium in captive-bred Mustela putorius furo in Jiangsu Province. METHODS A total of 290 fresh stool samples were collected from a ferret farm in Jiangsu Province on May 2017, and the small subunit rRNA (SSU rRNA) gene of Cryptosporidium was amplified in stool samples using nested PCR assay. The actin, cowp and gp60 genes were amplified in positive samples and sequenced to characterize Cryptosporidium species/genotypes. RESULTS A total of 18 stool samples were tested positive for Cryptosporidium SSU rRNA gene, with a detection rate of 6.2%. Sequence and phylogenetic analyses of SSU rRNA, actin and cowp genes characterized Cryptosporidium isolated from captive-bred ferrets as Cryptosporidium sp. ferret genotype. In addition, gp60 gene was amplified in 10 out of 18 stool samples tested positive for Cryptosporidium. CONCLUSIONS Cryptosporidium is widely prevalent in captive-bred ferrets in Jiangsu Province, and Cryptosporidium sp. ferret genotype is the only Cryptosporidium genotype in ferrets.
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Affiliation(s)
- J Zhang
- Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, College of Animal Science, Anhui Science and Technology University, Fengyang, Anhui 233100, China
| | - Y Zhou
- Jiangsu Institute of Parasitic Diseases, Key Laboratory of National Health Commission on Parasitic Disease Control and Prevention, China
| | - J Guo
- Animal Husbandry Development Center of Lu'an City, China
| | - J Li
- Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, College of Animal Science, Anhui Science and Technology University, Fengyang, Anhui 233100, China
| | - Y Wu
- Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, College of Animal Science, Anhui Science and Technology University, Fengyang, Anhui 233100, China
| | - Z Zhou
- Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, College of Animal Science, Anhui Science and Technology University, Fengyang, Anhui 233100, China
| | - H Zhu
- Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, College of Animal Science, Anhui Science and Technology University, Fengyang, Anhui 233100, China
| | - X Luo
- Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, College of Animal Science, Anhui Science and Technology University, Fengyang, Anhui 233100, China
| | - D Chen
- Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, College of Animal Science, Anhui Science and Technology University, Fengyang, Anhui 233100, China
| | - Q Li
- Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, College of Animal Science, Anhui Science and Technology University, Fengyang, Anhui 233100, China
| | - X Liu
- Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, College of Animal Science, Anhui Science and Technology University, Fengyang, Anhui 233100, China
| | - W Li
- Anhui Province Key Laboratory of Animal Nutritional Regulation and Health, College of Animal Science, Anhui Science and Technology University, Fengyang, Anhui 233100, China
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41
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Fan Y, Zhou Y, Liu H, Luo X, Xu T, Sun Y, Yang T, Chen L, Gu X, Yu Y. Improving variant prioritization in exome analysis by entropy-weighted ensemble of multiple tools. Clin Genet 2023; 103:190-199. [PMID: 36309956 DOI: 10.1111/cge.14257] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/08/2022] [Revised: 10/09/2022] [Accepted: 10/22/2022] [Indexed: 01/07/2023]
Abstract
Variant prioritization is a crucial step in the analysis of exome and genome sequencing. Multiple phenotype-driven tools have been developed to automate the variant prioritization process, but the efficacy of these tools in clinical setting with fuzzy phenotypic information and whether ensemble of these tools could outperform single algorithm remains to be assessed. A large rare disease cohort with heterogeneous phenotypic information, including a primary cohort of 1614 patients and a replication cohort of 1904 patients referred to exome sequencing, were recruited to assess the efficacy of variant prioritization and their ensemble. Three freely available tools-Exomiser, Xrare, and DeepPVP-and their ensemble were evaluated. The performance of all three tools was influenced by the attributes of phenotypic input. When combining these three tools by weighted-sum entropy method (EWE3), the ensemble outperformed any single algorithm, achieving a rate of 78% diagnostic variants in top 3 (13% improvement over current best performer, compared to Exomiser: 63%, Xrare: 65%, and DeepPVP: 51%), 88% in top 10 and 96% in top 30. The results were replicated in another independent cohort. Our study supports using entropy-weighted ensemble of multiple tools to improve variant prioritization and accelerate molecular diagnosis in exome/genome sequencing.
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Affiliation(s)
- Yanjie Fan
- Shanghai Institute of Pediatric Research, Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | | | - Huili Liu
- Shanghai Institute of Pediatric Research, Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Xiaomei Luo
- Shanghai Institute of Pediatric Research, Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Ting Xu
- Shanghai Institute of Pediatric Research, Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yu Sun
- Shanghai Institute of Pediatric Research, Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Tingting Yang
- Shanghai Institute of Pediatric Research, Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Linlin Chen
- Shanghai Institute of Pediatric Research, Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Xuefan Gu
- Shanghai Institute of Pediatric Research, Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
| | - Yongguo Yu
- Shanghai Institute of Pediatric Research, Xinhua Hospital affiliated to Shanghai Jiaotong University School of Medicine, Shanghai, China
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42
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Abratenko P, Andrade Aldana D, Anthony J, Arellano L, Asaadi J, Ashkenazi A, Balasubramanian S, Baller B, Barr G, Barrow J, Basque V, Bathe-Peters L, Benevides Rodrigues O, Berkman S, Bhanderi A, Bhattacharya M, Bishai M, Blake A, Bogart B, Bolton T, Book JY, Camilleri L, Caratelli D, Caro Terrazas I, Cavanna F, Cerati G, Chen Y, Conrad JM, Convery M, Cooper-Troendle L, Crespo-Anadón JI, Del Tutto M, Dennis SR, Detje P, Devitt A, Diurba R, Dorrill R, Duffy K, Dytman S, Eberly B, Ereditato A, Evans JJ, Fine R, Finnerud OG, Foreman W, Fleming BT, Foppiani N, Franco D, Furmanski AP, Garcia-Gamez D, Gardiner S, Ge G, Gollapinni S, Goodwin O, Gramellini E, Green P, Greenlee H, Gu W, Guenette R, Guzowski P, Hagaman L, Hen O, Hicks R, Hilgenberg C, Horton-Smith GA, Irwin B, Itay R, James C, Ji X, Jiang L, Jo JH, Johnson RA, Jwa YJ, Kalra D, Kamp N, Karagiorgi G, Ketchum W, Kirby M, Kobilarcik T, Kreslo I, Leibovitch MB, Lepetic I, Li JY, Li K, Li Y, Lin K, Littlejohn BR, Louis WC, Luo X, Manivannan K, Mariani C, Marsden D, Marshall J, Martinez N, Martinez Caicedo DA, Mason K, Mastbaum A, McConkey N, Meddage V, Miller K, Mills J, Mogan A, Mohayai T, Mooney M, Moor AF, Moore CD, Mora Lepin L, Mousseau J, Mulleriababu S, Naples D, Navrer-Agasson A, Nayak N, Nebot-Guinot M, Nowak J, Nunes M, Oza N, Palamara O, Pallat N, Paolone V, Papadopoulou A, Papavassiliou V, Parkinson HB, Pate SF, Patel N, Pavlovic Z, Piasetzky E, Ponce-Pinto ID, Pophale I, Prince S, Qian X, Raaf JL, Radeka V, Reggiani-Guzzo M, Ren L, Rochester L, Rodriguez Rondon J, Rosenberg M, Ross-Lonergan M, Rudolf von Rohr C, Scanavini G, Schmitz DW, Schukraft A, Seligman W, Shaevitz MH, Sharankova R, Shi J, Smith A, Snider EL, Soderberg M, Söldner-Rembold S, Spitz J, Stancari M, St John J, Strauss T, Sword-Fehlberg S, Szelc AM, Tang W, Taniuchi N, Terao K, Thorpe C, Torbunov D, Totani D, Toups M, Tsai YT, Tyler J, Uchida MA, Usher T, Viren B, Weber M, Wei H, White AJ, Williams Z, Wolbers S, Wongjirad T, Wospakrik M, Wresilo K, Wright N, Wu W, Yandel E, Yang T, Yates LE, Yu HW, Zeller GP, Zennamo J, Zhang C. First Constraints on Light Sterile Neutrino Oscillations from Combined Appearance and Disappearance Searches with the MicroBooNE Detector. Phys Rev Lett 2023; 130:011801. [PMID: 36669216 DOI: 10.1103/physrevlett.130.011801] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 10/19/2022] [Accepted: 12/08/2022] [Indexed: 06/17/2023]
Abstract
We present a search for eV-scale sterile neutrino oscillations in the MicroBooNE liquid argon detector, simultaneously considering all possible appearance and disappearance effects within the 3+1 active-to-sterile neutrino oscillation framework. We analyze the neutrino candidate events for the recent measurements of charged-current ν_{e} and ν_{μ} interactions in the MicroBooNE detector, using data corresponding to an exposure of 6.37×10^{20} protons on target from the Fermilab booster neutrino beam. We observe no evidence of light sterile neutrino oscillations and derive exclusion contours at the 95% confidence level in the plane of the mass-squared splitting Δm_{41}^{2} and the sterile neutrino mixing angles θ_{μe} and θ_{ee}, excluding part of the parameter space allowed by experimental anomalies. Cancellation of ν_{e} appearance and ν_{e} disappearance effects due to the full 3+1 treatment of the analysis leads to a degeneracy when determining the oscillation parameters, which is discussed in this Letter and will be addressed by future analyses.
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Affiliation(s)
- P Abratenko
- Tufts University, Medford, Massachusetts 02155, USA
| | - D Andrade Aldana
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - J Anthony
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - L Arellano
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Asaadi
- University of Texas, Arlington, Texas 76019, USA
| | - A Ashkenazi
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - S Balasubramanian
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - B Baller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Barr
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - J Barrow
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - V Basque
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | | | | | - S Berkman
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - A Bhanderi
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - M Bhattacharya
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Bishai
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - A Blake
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - B Bogart
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - T Bolton
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - J Y Book
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - L Camilleri
- Columbia University, New York, New York 10027, USA
| | - D Caratelli
- University of California, Santa Barbara, California 93106, USA
| | - I Caro Terrazas
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - F Cavanna
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Cerati
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y Chen
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J M Conrad
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - M Convery
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - L Cooper-Troendle
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - J I Crespo-Anadón
- Centro de Investigaciones Energéticas, Medioambientales y Tecnológicas (CIEMAT), Madrid E-28040, Spain
| | - M Del Tutto
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S R Dennis
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - P Detje
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Devitt
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - R Diurba
- Universität Bern, Bern CH-3012, Switzerland
| | - R Dorrill
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - K Duffy
- University of Oxford, Oxford OX1 3RH, United Kingdom
| | - S Dytman
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - B Eberly
- University of Southern Maine, Portland, Maine 04104, USA
| | | | - J J Evans
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - R Fine
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O G Finnerud
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - W Foreman
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - B T Fleming
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - N Foppiani
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - D Franco
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - A P Furmanski
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - S Gardiner
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - G Ge
- Columbia University, New York, New York 10027, USA
| | - S Gollapinni
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - O Goodwin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - E Gramellini
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - P Green
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - H Greenlee
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Gu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - R Guenette
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - P Guzowski
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Hagaman
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - O Hen
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - R Hicks
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - C Hilgenberg
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | | | - B Irwin
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - R Itay
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C James
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - X Ji
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - L Jiang
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - J H Jo
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - R A Johnson
- University of Cincinnati, Cincinnati, Ohio 45221, USA
| | - Y-J Jwa
- Columbia University, New York, New York 10027, USA
| | - D Kalra
- Columbia University, New York, New York 10027, USA
| | - N Kamp
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - G Karagiorgi
- Columbia University, New York, New York 10027, USA
| | - W Ketchum
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Kirby
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Kobilarcik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - I Kreslo
- Universität Bern, Bern CH-3012, Switzerland
| | - M B Leibovitch
- University of California, Santa Barbara, California 93106, USA
| | - I Lepetic
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - J-Y Li
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - K Li
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Y Li
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - K Lin
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - B R Littlejohn
- Illinois Institute of Technology (IIT), Chicago, Illinois 60616, USA
| | - W C Louis
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - X Luo
- University of California, Santa Barbara, California 93106, USA
| | - K Manivannan
- Syracuse University, Syracuse, New York 13244, USA
| | - C Mariani
- Center for Neutrino Physics, Virginia Tech, Blacksburg, Virginia 24061, USA
| | - D Marsden
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Marshall
- University of Warwick, Coventry CV4 7AL, United Kingdom
| | - N Martinez
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - D A Martinez Caicedo
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - K Mason
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mastbaum
- Rutgers University, Piscataway, New Jersey 08854, USA
| | - N McConkey
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - V Meddage
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - K Miller
- University of Chicago, Chicago, Illinois 60637, USA
| | - J Mills
- Tufts University, Medford, Massachusetts 02155, USA
| | - A Mogan
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - T Mohayai
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Mooney
- Colorado State University, Fort Collins, Colorado 80523, USA
| | - A F Moor
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - C D Moore
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L Mora Lepin
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - J Mousseau
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | | | - D Naples
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Navrer-Agasson
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - N Nayak
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Nebot-Guinot
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - J Nowak
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - M Nunes
- Syracuse University, Syracuse, New York 13244, USA
| | - N Oza
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | - O Palamara
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - N Pallat
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Paolone
- University of Pittsburgh, Pittsburgh, Pennsylvania 15260, USA
| | - A Papadopoulou
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - V Papavassiliou
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - H B Parkinson
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - S F Pate
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - N Patel
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - Z Pavlovic
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Piasetzky
- Tel Aviv University, Tel Aviv, Israel, 69978
| | - I D Ponce-Pinto
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - I Pophale
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - S Prince
- Harvard University, Cambridge, Massachusetts 02138, USA
| | - X Qian
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - J L Raaf
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - V Radeka
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Reggiani-Guzzo
- The University of Manchester, Manchester M13 9PL, United Kingdom
| | - L Ren
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - L Rochester
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Rodriguez Rondon
- South Dakota School of Mines and Technology (SDSMT), Rapid City, South Dakota 57701, USA
| | - M Rosenberg
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Ross-Lonergan
- Los Alamos National Laboratory (LANL), Los Alamos, New Mexico 87545, USA
| | | | - G Scanavini
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - D W Schmitz
- University of Chicago, Chicago, Illinois 60637, USA
| | - A Schukraft
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - W Seligman
- Columbia University, New York, New York 10027, USA
| | - M H Shaevitz
- Columbia University, New York, New York 10027, USA
| | - R Sharankova
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Shi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - A Smith
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - E L Snider
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - M Soderberg
- Syracuse University, Syracuse, New York 13244, USA
| | | | - J Spitz
- University of Michigan, Ann Arbor, Michigan 48109, USA
| | - M Stancari
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J St John
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Strauss
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - S Sword-Fehlberg
- New Mexico State University (NMSU), Las Cruces, New Mexico 88003, USA
| | - A M Szelc
- University of Edinburgh, Edinburgh EH9 3FD, United Kingdom
| | - W Tang
- University of Tennessee, Knoxville, Tennessee 37996, USA
| | - N Taniuchi
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - K Terao
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - C Thorpe
- Lancaster University, Lancaster LA1 4YW, United Kingdom
| | - D Torbunov
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - D Totani
- University of California, Santa Barbara, California 93106, USA
| | - M Toups
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - Y-T Tsai
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - J Tyler
- Kansas State University (KSU), Manhattan, Kansas 66506, USA
| | - M A Uchida
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - T Usher
- SLAC National Accelerator Laboratory, Menlo Park, California 94025, USA
| | - B Viren
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - M Weber
- Universität Bern, Bern CH-3012, Switzerland
| | - H Wei
- Louisiana State University, Baton Rouge, Louisiana 70803, USA
| | - A J White
- Wright Laboratory, Department of Physics, Yale University, New Haven, Connecticut 06520, USA
| | - Z Williams
- University of Texas, Arlington, Texas 76019, USA
| | - S Wolbers
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - T Wongjirad
- Tufts University, Medford, Massachusetts 02155, USA
| | - M Wospakrik
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - K Wresilo
- University of Cambridge, Cambridge CB3 0HE, United Kingdom
| | - N Wright
- Massachusetts Institute of Technology (MIT), Cambridge, Massachusetts 02139, USA
| | - W Wu
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - E Yandel
- University of California, Santa Barbara, California 93106, USA
| | - T Yang
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - L E Yates
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - H W Yu
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
| | - G P Zeller
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - J Zennamo
- Fermi National Accelerator Laboratory (FNAL), Batavia, Illinois 60510, USA
| | - C Zhang
- Brookhaven National Laboratory (BNL), Upton, New York 11973, USA
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Zhu Q, Tang Y, Tian Q, Cheng H, Yang J, Xiong L, Li W, Zou L, Cheng W, Luo X. Clinical efficacy and safety analysis of different treatment options for Cervical pregnancy. Int J Hyperthermia 2023; 40:2255757. [PMID: 37699591 DOI: 10.1080/02656736.2023.2255757] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/09/2023] [Revised: 08/18/2023] [Accepted: 08/31/2023] [Indexed: 09/14/2023] Open
Abstract
OBJECTIVE To compare the efficacy and safety of different treatment options for cervical pregnancy (CP). MATERIALS AND METHODS A total of 74 patients diagnosed with CP at Hunan Provincial Maternal and Child Health Care Hospital between January 2016 and September 2022 were retrospectively analyzed. Among them, 31 were treated with uterine artery embolization (UAE) followed by hysteroscopic curettage, 34 were treated with hysteroscopic curettage alone, and nine were treated with high-intensity focused ultrasound (HIFU) followed by hysteroscopic curettage. Medical records and pregnancy outcomes were analyzed. RESULTS There were no significant differences in age, gravidity, parity, abortion, or preoperative hemoglobin levels among the patients in the three groups; however, significant differences in gestational age, gestational sac diameter, preoperative β-hCG, and presence of cardiac pulsation were observed (p < 0.05). After treatment, there was no conversion to laparotomy, and the uterus was preserved in all patients. Significant differences in blood loss during curettage, hospitalization costs, hospital days, menstrual recovery interval, β-hCG decline rates, retained products of conception, and intrauterine adhesions rate among the three groups were observed (p < 0.05). There were no significant differences in the placement of the uterine Foley balloon, effective curettage rate, pre-and postoperative hemoglobin decline, live birth rate, or proportion of subsequent pregnancies among the three groups. CONCLUSION Our results showed that hysteroscopic curettage, HIFU, and UAE followed by hysteroscopic curettage are safe and effective for treating patients with CP. Compared with the UAE, HIFU has the advantages of lower hospitalization costs, shorter hospital stays, and shorter menstrual recovery intervals.
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Affiliation(s)
- Qiaoling Zhu
- Department of Obstetrics and Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, P.R. China
| | - Yi Tang
- Department of Obstetrics and Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, P.R. China
| | - Qi Tian
- Department of Obstetrics and Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, P.R. China
| | - Hui Cheng
- Department of Obstetrics and Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, P.R. China
| | - Jing Yang
- Department of Obstetrics and Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, P.R. China
| | - Li Xiong
- Department of Obstetrics and Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, P.R. China
| | - Wei Li
- Department of Obstetrics and Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, P.R. China
| | - Lingzhi Zou
- Department of Obstetrics and Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, P.R. China
| | - Wei Cheng
- Department of Obstetrics and Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, P.R. China
| | - Xiaomei Luo
- Department of Obstetrics and Gynecology, Hunan Provincial Maternal and Child Health Care Hospital, Changsha, Hunan, P.R. China
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Wu X, Xia L, Wang J, Wang C, Zhang Q, Zhu J, Rao Q, Cheng H, Liu Z, Y. Yin, Ai X, Gulina K, Zheng H, Luo X, Chang B, Li L, Liu H, Li Y, Zhu J. 79P Efficacy and safety of zimberelimab (GLS-010) monotherapy in patients with recurrent or metastatic cervical cancer: A multicenter, open-label, single-arm, phase II study. Immuno-Oncology and Technology 2022. [DOI: 10.1016/j.iotech.2022.100183] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 12/14/2022]
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He Z, Luo X, Lei Y, Zhang W. Five Species of Taxus Karyotype Based on Oligo-FISH for 5S rDNA and (AG 3T 3) 3. Genes (Basel) 2022; 13:genes13122209. [PMID: 36553477 PMCID: PMC9778077 DOI: 10.3390/genes13122209] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/27/2022] [Revised: 11/07/2022] [Accepted: 11/21/2022] [Indexed: 11/29/2022] Open
Abstract
As a relict plant, Taxus is used in a variety of medicinal ingredients, for instance to treat a variety of cancers. Taxus plants are difficult to distinguish from one another due to their similar morphology; indeed, some species of Taxus cytogenetic data still are unclear. Oligo-FISH can rapidly and efficiently provide insight into the genetic composition and karyotype. This is important for understanding the organization and evolution of chromosomes in Taxus species. We analysed five Taxus species using two oligonucleotide probes. (AG3T3)3 signals were distributed at the chromosome ends and the centromere of five species of Taxus. The 5S rDNA signal was displayed on two chromosomes of five species of Taxus. In addition to Taxus wallichiana var. mairei, 5S rDNA signals were found proximal in the remaining four species, which signals a difference in its location. The karyotype formula of Taxus wallichiana was 2n = 2x = 24m, its karyotype asymmetry index was 55.56%, and its arm ratio was 3.0087. Taxus × media's karyotype formula was 2n = 2x = 24m, its karyotype asymmetry index was 55.09%, and its arm ratio was 3.4198. The karyotype formula of Taxus yunnanensis was 2n = 2x = 24m, its karyotype asymmetry index was 55.56%, and its arm ratio was 2.6402. The karyotype formula of Taxus cuspidate was 2n = 2x = 24m, its karyotype asymmetry index was 54.67%, its arm ratio was 3.0135, and two chromosomes exhibited the 5S rDNA signal. The karyotype formula of T. wallichiana var. mairei was 2n= 2x = 22m + 2sm, its karyotype asymmetry index was 54.33%, and its arm ratio was 2.8716. Our results provide the karyotype analysis and physical genetic map of five species of Taxus, which contributes to providing molecular cytogenetics data for Taxus.
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Zhang M, Wu W, Jin F, Li Y, Long J, Luo X, Gong X, Chen X. A Randomized Phase III Trial Observed the Feasibility and Safety of Loplatin Combination Regimen of Sequential Loplatin in Locally Advanced Head and Neck SCC. Int J Radiat Oncol Biol Phys 2022. [DOI: 10.1016/j.ijrobp.2022.07.1309] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/28/2022]
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Yang HF, He KY, Koo J, Shen SW, Zhang SH, Liu G, Liu YZ, Chen C, Liang AJ, Huang K, Wang MX, Gao JJ, Luo X, Yang LX, Liu JP, Sun YP, Yan SC, Yan BH, Chen YL, Xi X, Liu ZK. Visualization of Chiral Electronic Structure and Anomalous Optical Response in a Material with Chiral Charge Density Waves. Phys Rev Lett 2022; 129:156401. [PMID: 36269973 DOI: 10.1103/physrevlett.129.156401] [Citation(s) in RCA: 6] [Impact Index Per Article: 3.0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/16/2022] [Accepted: 09/07/2022] [Indexed: 05/02/2023]
Abstract
Chiral materials have attracted significant research interests as they exhibit intriguing physical properties, such as chiral optical response, spin-momentum locking, and chiral induced spin selectivity. Recently, layered transition metal dichalcogenide 1T-TaS_{2} has been found to host a chiral charge density wave (CDW) order. Nevertheless, the physical consequences of the chiral order, for example, in electronic structures and the optical properties, are yet to be explored. Here, we report the spectroscopic visualization of an emergent chiral electronic band structure in the CDW phase, characterized by windmill-shaped Fermi surfaces. We uncover a remarkable chirality-dependent circularly polarized Raman response due to the salient in-plane chiral symmetry of CDW, although the ordinary circular dichroism vanishes. Chiral Fermi surfaces and anomalous Raman responses coincide with the CDW transition, proving their lattice origin. Our Letter paves a path to manipulate the chiral electronic and optical properties in two-dimensional materials and explore applications in polarization optics and spintronics.
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Affiliation(s)
- H F Yang
- School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, People's Republic of China
| | - K Y He
- National Laboratory of Solid State Microstructures and Department of Physics, Nanjing University, Nanjing 210093, People's Republic of China
| | - J Koo
- Department of Condensed Matter Physics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - S W Shen
- School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, People's Republic of China
| | - S H Zhang
- School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, People's Republic of China
| | - G Liu
- National Laboratory of Solid State Microstructures and Department of Physics, Nanjing University, Nanjing 210093, People's Republic of China
| | - Y Z Liu
- Department of Condensed Matter Physics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - C Chen
- School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, People's Republic of China
- Department of Physics, University of Oxford, Oxford, OX1 3PU, United Kingdom
| | - A J Liang
- School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, People's Republic of China
- ShanghaiTech Laboratory for Topological Physics, Shanghai 201210, People's Republic of China
| | - K Huang
- School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, People's Republic of China
| | - M X Wang
- School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, People's Republic of China
- ShanghaiTech Laboratory for Topological Physics, Shanghai 201210, People's Republic of China
| | - J J Gao
- Key Laboratory of Materials Physics, Institute of Solid State Physics, Chinese Academy of Sciences, HFIPS, Hefei 230031, People's Republic of China
| | - X Luo
- Key Laboratory of Materials Physics, Institute of Solid State Physics, Chinese Academy of Sciences, HFIPS, Hefei 230031, People's Republic of China
| | - L X Yang
- State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics, Tsinghua University, Beijing 100084, People's Republic of China
| | - J P Liu
- School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, People's Republic of China
- ShanghaiTech Laboratory for Topological Physics, Shanghai 201210, People's Republic of China
| | - Y P Sun
- Key Laboratory of Materials Physics, Institute of Solid State Physics, Chinese Academy of Sciences, HFIPS, Hefei 230031, People's Republic of China
- High Magnetic Field Laboratory, Chinese Academy of Sciences, HFIPS, Hefei, 230031, People's Republic of China
- Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, People's Republic of China
| | - S C Yan
- School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, People's Republic of China
- ShanghaiTech Laboratory for Topological Physics, Shanghai 201210, People's Republic of China
| | - B H Yan
- Department of Condensed Matter Physics, Weizmann Institute of Science, Rehovot 76100, Israel
| | - Y L Chen
- School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, People's Republic of China
- Department of Physics, University of Oxford, Oxford, OX1 3PU, United Kingdom
- ShanghaiTech Laboratory for Topological Physics, Shanghai 201210, People's Republic of China
- State Key Laboratory of Low Dimensional Quantum Physics and Department of Physics, Tsinghua University, Beijing 100084, People's Republic of China
| | - X Xi
- National Laboratory of Solid State Microstructures and Department of Physics, Nanjing University, Nanjing 210093, People's Republic of China
- Collaborative Innovation Center of Advanced Microstructures, Nanjing University, Nanjing 210093, People's Republic of China
| | - Z K Liu
- School of Physical Science and Technology, ShanghaiTech University, Shanghai 201210, People's Republic of China
- ShanghaiTech Laboratory for Topological Physics, Shanghai 201210, People's Republic of China
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Dhamane AD, Noxon V, Bruette R, Shah S, Ferri M, Liu X, Jang J, Luo X. Anticoagulant treatment patterns and thromboembolic events by tumor type among patients with VTE and cancer. Eur Heart J 2022. [DOI: 10.1093/eurheartj/ehac544.1906] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Indexed: 11/14/2022] Open
Abstract
Abstract
Background
Patients with venous thromboembolism (VTE) and cancer are at higher risk of adverse outcomes (mortality, recurrent VTE etc.) versus patients with cancer alone; as such, clinical guidelines recommend anticoagulant treatment for patients with VTE and cancer. There is limited real world data about how anticoagulant treatment and thromboembolic outcomes differ by tumor type in patients with VTE and cancer. Understanding such differences may help identify appropriate anticoagulant treatment for specific tumor types.
Purpose
To describe anticoagulant treatment patterns and thromboembolic outcomes by tumor type among patients with VTE and cancer.
Methods
Patients with VTE and cancer age ≥65 were identified from the Surveillance, Epidemiology and End Results (SEER) Medicare database from 1/1/2014–12/31/2019. Patients were required to be enrolled for ≥6-months prior to their first VTE diagnosis (index) and without evidence of other conditions requiring anticoagulant (i.e., atrial fibrillation) prior to index. Cancer status and tumor type were identified from SEER or Medicare database in the 6-months prior through 30-days post VTE. This analysis focused on the following specific tumor types: high risk (brain, pancreas, and stomach) and common tumor types (breast, and prostate). Patients treated with an anticoagulant within 30-days after index were included in the final population. Major bleeding (MB) and recurrent VTE events were measured during follow-up (index date through earliest of disenrollment, death or 12/31/2019).
Results
A total of 3,546 anticoagulated patients with VTE and cancer of interest met all study criteria (breast [n=1,197], prostate [n=849], pancreatic [n=995], brain [n=248] and stomach [n=257] cancer). Patient mean age ranged from 73 (brain) to 76 (stomach) at index. Anticoagulant treatment patterns varied by tumor type (Figure 1). LMWH was more likely to be used in the 3 high risk tumor types whereas apixaban and rivaroxaban were more likely to be used in the 2 common tumor types. The incidence rate of recurrent VTE and major bleeding events also varied among different tumor types: ranging from 1.4 (breast) to 6.4 (pancreatic) per 100 person-years for recurrent VTE and from 4.3 (prostate) to 15.1 (pancreatic) per 100 person-years for major bleeding (Figure 2).
Conclusion
There are notable variations in anticoagulant treatment patters and the risks of major bleeding and recurrent VTE events by tumor type among patients with VTE and cancer. Further research is needed to understand which anticoagulant treatment option is more appropriate for VTE patients with specific tumor type.
Funding Acknowledgement
Type of funding sources: Private company. Main funding source(s): Pfizer Inc. and Bristol Myers Squibb Company
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Affiliation(s)
- A D Dhamane
- Bristol Myers Squibb Company , Lawrenceville , United States of America
| | - V Noxon
- STATinMED , Ann Arbor , United States of America
| | - R Bruette
- STATinMED , Ann Arbor , United States of America
| | - S Shah
- STATinMED , Ann Arbor , United States of America
| | - M Ferri
- Bristol Myers Squibb Company , Lawrenceville , United States of America
| | - X Liu
- Bristol Myers Squibb Company , Lawrenceville , United States of America
| | - J Jang
- Bristol Myers Squibb Company , Lawrenceville , United States of America
| | - X Luo
- Pfizer Inc. , Groton , United States of America
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Chen J, Wang G, Luo X, Zhang J, Zhang Y. Cuproptosis patterns and tumor microenvironment in endometrial cancer. Front Genet 2022; 13:1001374. [PMID: 36226180 PMCID: PMC9549213 DOI: 10.3389/fgene.2022.1001374] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/23/2022] [Accepted: 09/06/2022] [Indexed: 11/22/2022] Open
Abstract
Cuproptosis is the most recently discovered mode of cell death. It could affect the metabolism of cancer cells and surrounding infiltrating immune cells. In recent years, many studies have also shown that the tumor microenvironment (TME) plays a critical role in tumor growth and development. Mounting evidence suggests that Cuproptosis would bring unique insights into the development of pharmacological and nonpharmacological therapeutic techniques for cancer prevention and therapy. However, no study has been done on the combination of cuproptosis and TME in any cancer. Herein, we investigated the relationship between cuproptosis-related genes (CRGs), TME, and the prognosis of patients with Uterine Corpus Endometrial Carcinoma (UCEC). We identified three CRGs clusters based on 10 CRGs and three CRGs gene clusters based on 600 differentially expressed genes (DEGs) with significant prognostic differences. Following that, the CRGs score based on DEGs with significant prognostic differences was established to evaluate the prognosis and immunotherapeutic efficacy of UCEC patients. The CRGs score was shown to be useful in predicting clinical outcomes. Patients with a low CRGs score seemed to have a better prognosis, a better immunotherapeutic response, and a higher tumor mutation burden (TMB). In conclusion, our study explored the influence of cuproptosis patterns and TME on the prognosis of cancer patients, thereby improving their prognosis.
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Wu Y, Wang Y, Lu Y, Luo X, Huang Y, Xie T, Pilarsky C, Dang Y, Zhang J. Microfluidic Technology for the Isolation and Analysis of Exosomes. Micromachines (Basel) 2022; 13:1571. [PMID: 36295924 PMCID: PMC9607600 DOI: 10.3390/mi13101571] [Citation(s) in RCA: 9] [Impact Index Per Article: 4.5] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [Track Full Text] [Figures] [Subscribe] [Scholar Register] [Received: 07/13/2022] [Revised: 09/14/2022] [Accepted: 09/19/2022] [Indexed: 06/16/2023]
Abstract
Exosomes are lipid-bilayer enclosed vesicles with diameters of 30-150 nm, which play a pivotal role in cell communication by transporting their cargoes such as proteins, lipids, and genetic materials. In recent years, exosomes have been under intense investigation, as they show great promise in numerous areas, especially as bio-markers in liquid biopsies. However, due to the high heterogeneity and the nano size of exosomes, the separation of exosomes is not easy. This review will deliver an outline of the conventional methods and the microfluidic-based technologies for exosome separation. Particular attention is devoted to microfluidic devices, highlighting the efficiency of exosome isolation by these methods. Additionally, this review will introduce advances made in the integrated microfluidics technologies that enable the separation and analysis of exosomes.
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Affiliation(s)
- Yusong Wu
- Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target & Clinical Pharmacology, NMPA and State Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences and the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou 511436, China
| | - Yuqing Wang
- Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target & Clinical Pharmacology, NMPA and State Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences and the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou 511436, China
| | - Yanjun Lu
- Guangdong Provincial Key Laboratory of Micro/Nano Optomechatronics Engineering, College of Mechatronics and Control Engineering, Shenzhen University, Shenzhen 518060, China
| | - Xiaomei Luo
- Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target & Clinical Pharmacology, NMPA and State Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences and the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou 511436, China
| | - Yinghong Huang
- Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target & Clinical Pharmacology, NMPA and State Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences and the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou 511436, China
| | - Ting Xie
- Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target & Clinical Pharmacology, NMPA and State Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences and the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou 511436, China
| | - Christian Pilarsky
- Department of Surgery, Friedrich-Alexander University of Erlangen-Nuremberg (FAU), University Hospital of Erlangen, 91054 Erlangen, Germany
| | - Yuanye Dang
- Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target & Clinical Pharmacology, NMPA and State Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences and the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou 511436, China
| | - Jianye Zhang
- Guangzhou Municipal and Guangdong Provincial Key Laboratory of Molecular Target & Clinical Pharmacology, NMPA and State Key Laboratory of Respiratory Disease, School of Pharmaceutical Sciences and the Fifth Affiliated Hospital, Guangzhou Medical University, Guangzhou 511436, China
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