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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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Chen Y, Zheng J, Weng Y, Wu Z, Luo X, Qiu Y, Lin Y, Hu J, Wu Y. Myelodysplasia-related gene mutations are associated with favorable prognosis in patients with TP53-mutant acute myeloid leukemia. Ann Hematol 2024; 103:1211-1220. [PMID: 38409598 DOI: 10.1007/s00277-024-05679-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] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/07/2023] [Accepted: 02/20/2024] [Indexed: 02/28/2024]
Abstract
This study aimed to examine the characteristics and treatment outcomes of patients with TP53-mutant acute myeloid leukaemia (AML) and to explore potential prognostic factors. This retrospective analysis included 130 patients diagnosed with TP53-mutant AML at the Fujian Medical University Union Hospital between January 2016 and June 2023. Patients' ages ranged from 17 to 80 years, with a median age of 59 years. The proportions of de novo, therapy-related, and secondary AML cases were 71.5%, 7.7%, and 20.8%, respectively. Complex karyotypes were observed in 60.6% of patients, and the proportions of -5 or del(5q), -7 or del(7q), and - 17 or del(17p) were 41.7%, 27.9% and 14.4%, respectively. DNA methylation- and myelodysplasia-related (MR) gene mutations were observed in 36.9% and 25.4% of patients, respectively. These patients showed poor survival, with a median overall survival (OS) of 4.5 months, a 1-year OS rate of 32.5%, a 3-year OS rate of 18.8%, and a 5-year OS rate of 11.3%. The complete response rates for intensive chemotherapy (IC), hypomethylating agent (HMAs)-based therapies, and azacitidine plus venetoclax were 35.7%, 22.2%, and 37.5%, respectively. Patients who did or did not receive allogeneic haematopoietic stem cell transplantation (allo-HSCT) had similar prognoses (median OS: 6.0 vs. 3.9 months; P = 0.6415). Multivariate analysis indicated that MR gene mutations is an independent favorable prognostic factor of OS (HR = 0.366, 95% CI: 0.181-0.738, P = 0.005). In conclusion, patients with TP53-mutant AML have poor prognoses under current treatment strategies and MR gene mutations are associated with a more favorable survival. Therefore, further studies are needed to improve the survival rates in this population.
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Affiliation(s)
- Yi Chen
- Fujian Medical University Union Hospital, Fujian Provincial Key Laboratory on Hematology, Fujian Institute of Hematology, Xinquan Road 29, Fuzhou, China
| | - Jing Zheng
- Fujian Medical University Union Hospital, Fujian Provincial Key Laboratory on Hematology, Fujian Institute of Hematology, Xinquan Road 29, Fuzhou, China
| | - Yimei Weng
- Department of Hematology Nursing, Fujian Medical University Union Hospital, Xinquan Road 29, Fuzhou, China
| | - Zhengjun Wu
- Fujian Medical University Union Hospital, Fujian Provincial Key Laboratory on Hematology, Fujian Institute of Hematology, Xinquan Road 29, Fuzhou, China
| | - Xiaofeng Luo
- Fujian Medical University Union Hospital, Fujian Provincial Key Laboratory on Hematology, Fujian Institute of Hematology, Xinquan Road 29, Fuzhou, China
| | - Yanyan Qiu
- Fujian Medical University Union Hospital, Fujian Provincial Key Laboratory on Hematology, Fujian Institute of Hematology, Xinquan Road 29, Fuzhou, China
| | - Yanjuan Lin
- Fujian Medical University Union Hospital, Fujian Provincial Key Laboratory on Hematology, Fujian Institute of Hematology, Xinquan Road 29, Fuzhou, China
| | - Jianda Hu
- Fujian Medical University Union Hospital, Fujian Provincial Key Laboratory on Hematology, Fujian Institute of Hematology, Xinquan Road 29, Fuzhou, China.
- The Second Affiliated Hospital of Fujian Medical University, Zhongshanbei Road 34, Quanzhou, China.
- Institute of Precision Medicine, Fujian Medical University, Fuzhou, China.
| | - Yong Wu
- Fujian Medical University Union Hospital, Fujian Provincial Key Laboratory on Hematology, Fujian Institute of Hematology, Xinquan Road 29, Fuzhou, China.
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Qin J, Jiang S, Luo X, Wang T, Liu P, Yuan B, Yan R. I 2-catalyzed synthesis of 3-aminopyrrole with homopropargylic amines and nitrosoarenes. Chem Commun (Camb) 2024. [PMID: 38477099 DOI: 10.1039/d4cc00482e] [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: 03/14/2024]
Abstract
The synthesis of 3-aminopyrrole using the amination reagent nitrosoarenes and homopropargylic amines catalyzed by I2 through cyclization and amination has been developed. This protocol features excellent functional group tolerance and mild reaction conditions, yielding 3-aminopyrroles in moderate to good yields without a metal catalyst. This method realizes the construction and amination of the 3-aminopyrroles in which nitrosoarenes serve as the amine source and oxidant.
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Affiliation(s)
- Jiaze Qin
- State Key Laboratory of Applied Organic Chemistry, College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou 73000, Gansu, China.
| | - Shixuan Jiang
- State Key Laboratory of Applied Organic Chemistry, College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou 73000, Gansu, China.
| | - Xiaofeng Luo
- Chengdu Guibao Science and Technology Co., Ltd, Chengdu 610041, Sichuan, China
| | - Tianqiang Wang
- Chengdu Guibao Science and Technology Co., Ltd, Chengdu 610041, Sichuan, China
| | - Peihua Liu
- Research Institute of Oil and Gas Technology of Changqing Oilfield Company, Xian 710018, Shaanxi, China
| | - Bingxiang Yuan
- State Key Laboratory of Applied Organic Chemistry, College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou 73000, Gansu, China.
| | - Rulong Yan
- State Key Laboratory of Applied Organic Chemistry, College of Chemistry and Chemical Engineering, Lanzhou University, Lanzhou 73000, Gansu, China.
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4
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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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Xian B, Rehmani MS, Fan Y, Luo X, Zhang R, Xu J, Wei S, Wang L, He J, Fu A, Shu K. The ABI4-RGL2 module serves as a double agent to mediate the antagonistic crosstalk between ABA and GA signals. New Phytol 2024; 241:2464-2479. [PMID: 38287207 DOI: 10.1111/nph.19533] [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: 12/05/2023] [Accepted: 12/22/2023] [Indexed: 01/31/2024]
Abstract
Abscisic acid (ABA) and gibberellins (GA) antagonistically mediate several biological processes, including seed germination, but the molecular mechanisms underlying ABA/GA antagonism need further investigation, particularly any role mediated by a transcription factors module. Here, we report that the DELLA protein RGL2, a repressor of GA signaling, specifically interacts with ABI4, an ABA signaling enhancer, to act as a transcription factor complex to mediate ABA/GA antagonism. The rgl2, abi3, abi4 and abi5 mutants rescue the non-germination phenotype of the ga1-t. Further, we demonstrate that RGL2 specifically interacts with ABI4 to form a heterodimer. RGL2 and ABI4 stabilize one another, and GA increases the ABI4-RGL2 module turnover, whereas ABA decreases it. At the transcriptional level, ABI4 enhances the RGL2 expression by directly binding to its promoter via the CCAC cis-element, and RGL2 significantly upregulates the transcriptional activation ability of ABI4 toward its target genes, including ABI5 and RGL2. Abscisic acid promotes whereas GA inhibits the ability of ABI4-RGL2 module to activate transcription, and ultimately ABA and GA antagonize each other. Genetic analysis demonstrated that both ABI4 and RGL2 are essential for the activity of this transcription factor module. These results suggest that the ABI4-RGL2 module mediates ABA/GA antagonism by functioning as a double agent.
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Affiliation(s)
- Baoshan Xian
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Muhammad Saad Rehmani
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
| | - Yueni Fan
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Xiaofeng Luo
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Ranran Zhang
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Jiahui Xu
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Shaowei Wei
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Lei Wang
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Juan He
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Aigen Fu
- Shaanxi Fundamental Science Research Project for Chemistry & Biology, the College of Life Sciences, Northwest University, Xi'an, 710127, China
| | - Kai Shu
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
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6
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Luo X, Jin Q, Du M, Wang D, Duan L, Zhang Y. An Ideal Molecular Construction Strategy for Ultra-Narrow-Band Deep-Blue Emitters: Balancing Bathochromic-Shift Emission, Spectral Narrowing, and Aggregation Suppression. Adv Sci (Weinh) 2024; 11:e2307675. [PMID: 38161235 PMCID: PMC10953554 DOI: 10.1002/advs.202307675] [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] [Subscribe] [Scholar Register] [Received: 10/13/2023] [Revised: 12/02/2023] [Indexed: 01/03/2024]
Abstract
Narrowband emissive multiple resonance (MR) emitters promise high efficiency and stability in deep-blue organic light-emitting diodes (OLEDs). However, the construction of ideal ultra-narrow-band deep-blue MR emitters still faces formidable challenges, especially in balancing bathochromic-shift emission, spectral narrowing, and aggregation suppression. Here, DICz is chosen, which possesses the smallest full-width-at-half-maximum (FWHM) in MR structures, as the core and solved the above issue by tuning its peripheral substitution sites. The 1-substituted molecule Cz-DICz is able to show a bright deep-blue emission with a peak at 457 nm, an extremely small FWHM of 14 nm, and a CIE coordinate of (0.14, 0.08) in solution. The corresponding OLEDs exhibit high maximum external quantum efficiencies of 22.1%-25.6% and identical small FWHMs of 18 nm over the practical mass-production concentration range (1-4 wt.%). To the best of the knowledge, 14 and 18 nm are currently the smallest FWHM values for deep-blue MR emitters with similar emission maxima under photoluminescence and electroluminescence conditions, respectively. These discoveries will help drive the development of high-performance narrowband deep-blue emitters and bring about a revolution in OLED industry.
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Affiliation(s)
- Xiaofeng Luo
- Key Lab of Organic Optoelectronics and Molecular Engineering of Ministry of EducationDepartment of ChemistryTsinghua UniversityBeijing100084P. R. China
| | - Qian Jin
- Key Lab of Organic Optoelectronics and Molecular Engineering of Ministry of EducationDepartment of ChemistryTsinghua UniversityBeijing100084P. R. China
| | - Mingxu Du
- Key Lab of Organic Optoelectronics and Molecular Engineering of Ministry of EducationDepartment of ChemistryTsinghua UniversityBeijing100084P. R. China
| | - Dong Wang
- Laboratory of Flexible Electronics TechnologyTsinghua UniversityBeijing100084P. R. China
| | - Lian Duan
- Key Lab of Organic Optoelectronics and Molecular Engineering of Ministry of EducationDepartment of ChemistryTsinghua UniversityBeijing100084P. R. China
- Laboratory of Flexible Electronics TechnologyTsinghua UniversityBeijing100084P. R. China
| | - Yuewei Zhang
- Laboratory of Flexible Electronics TechnologyTsinghua UniversityBeijing100084P. R. China
- Applied Mechanics LabSchool of Aerospace EngineeringTsinghua UniversityBeijing100084P. R. China
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7
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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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8
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Luo X, Dai Y, Xian B, Xu J, Zhang R, Rehmani MS, Zheng C, Zhao X, Mao K, Ren X, Wei S, Wang L, He J, Tan W, Du J, Liu W, Yuan S, Shu K. PIF4 interacts with ABI4 to serve as a transcriptional activator complex to promote seed dormancy by enhancing ABA biosynthesis and signaling. J Integr Plant Biol 2024. [PMID: 38328870 DOI: 10.1111/jipb.13615] [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] [Subscribe] [Scholar Register] [Received: 04/20/2023] [Revised: 12/21/2023] [Accepted: 12/28/2023] [Indexed: 02/09/2024]
Abstract
Transcriptional regulation plays a key role in the control of seed dormancy, and many transcription factors (TFs) have been documented. However, the mechanisms underlying the interactions between different TFs within a transcriptional complex regulating seed dormancy remain largely unknown. Here, we showed that TF PHYTOCHROME-INTERACTING FACTOR4 (PIF4) physically interacted with the abscisic acid (ABA) signaling responsive TF ABSCISIC ACID INSENSITIVE4 (ABI4) to act as a transcriptional complex to promote ABA biosynthesis and signaling, finally deepening primary seed dormancy. Both pif4 and abi4 single mutants exhibited a decreased primary seed dormancy phenotype, with a synergistic effect in the pif4/abi4 double mutant. PIF4 binds to ABI4 to form a heterodimer, and ABI4 stabilizes PIF4 at the protein level, whereas PIF4 does not affect the protein stabilization of ABI4. Subsequently, both TFs independently and synergistically promoted the expression of ABI4 and NCED6, a key gene for ABA anabolism. The genetic evidence is also consistent with the phenotypic, physiological and biochemical analysis results. Altogether, this study revealed a transcriptional regulatory cascade in which the PIF4-ABI4 transcriptional activator complex synergistically enhanced seed dormancy by facilitating ABA biosynthesis and signaling.
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Affiliation(s)
- Xiaofeng Luo
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development, Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Yujia Dai
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development, Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Baoshan Xian
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development, Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Jiahui Xu
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
| | - Ranran Zhang
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
| | - Muhammad Saad Rehmani
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
| | - Chuan Zheng
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
| | - Xiaoting Zhao
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
| | - Kaitao Mao
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
| | - Xiaotong Ren
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
| | - Shaowei Wei
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development, Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Lei Wang
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development, Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Juan He
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development, Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
| | - Weiming Tan
- College of Agronomy and Biotechnology, China Agricultural University, Beijing, 100193, China
| | - Junbo Du
- Institute of Ecological Agriculture, Sichuan Agricultural University, Chengdu, 611130, China
| | - Weiguo Liu
- Institute of Ecological Agriculture, Sichuan Agricultural University, Chengdu, 611130, China
| | - Shu Yuan
- College of Resources, Sichuan Agricultural University, Chengdu, 611130, China
| | - Kai Shu
- Shaanxi Key Laboratory of Qinling Ecological Intelligent Monitoring and Protection, School of Ecology and Environment, Northwestern Polytechnical University, Xi'an, 710129, China
- Research & Development, Institute of Northwestern Polytechnical University in Shenzhen, Shenzhen, 518057, China
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9
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Yan A, Luo X, Tang L, Huang Y, Du S. Can socialized pest control service reduce the intensity of pesticide use? Evidence from rice farmers in China. Pest Manag Sci 2024; 80:317-332. [PMID: 37688776 DOI: 10.1002/ps.7764] [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: 05/24/2022] [Revised: 08/31/2023] [Accepted: 09/09/2023] [Indexed: 09/11/2023]
Abstract
BACKGROUND Although a great deal of research has examined the impact of socialized pest control service, few studies have discussed the relationship between socialized pest control service and pesticide use intensity. In particular, the literature ignores the impact of advanced application technologies (drone sprayers) on the intensity of pesticide use by farmers. RESULTS Based on a survey of 1185 rice growers in Hubei Province, China, this study found that 64.13% of the sample farmers used pesticides more than three times in one rice season. Importantly, socialized pest control services have a significant negative effect on the pesticide use intensity of farmers. Compared to the sample that did not purchase the service, farmers who purchased socialized pest control services demonstrated 9.30% less pesticide intensity. Further, there was a significant difference among farmers using different application devices on pesticide use intensity. Compared to the sample using ground backpack sprayers, farmers using drone sprayers used 12.40% less pesticide intensity. CONCLUSION This study found that the frequency of pesticide use by farmers during rice cultivation was generally high. Socialized pest control services have played a positive role in reducing the intensity of pesticide use, especially with the more obvious pesticide reduction effect of the adoption of drone sprayers. Therefore, improving socialized pest control services and promoting advanced equipment such as drone sprayers may be an important way to reduce the use of pesticides in China. © 2023 Society of Chemical Industry.
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Affiliation(s)
- Aqian Yan
- College of Economics and Management, Huazhong Agricultural University, Wuhan, China
- Hubei Rural Development Research Center, Huazhong Agricultural University, Wuhan, China
| | - Xiaofeng Luo
- College of Economics and Management, Huazhong Agricultural University, Wuhan, China
- International Joint Laboratory of Climate Change Response and Sustainable Agriculture, Huazhong Agricultural University, Wuhan, China
| | - Lin Tang
- School of Law and Business, Wuhan Institute of Technology, Wuhan, China
| | - Yanzhong Huang
- School of Law and Business, Wuhan Institute of Technology, Wuhan, China
| | - Sanxia Du
- College of Economics and Management, Huazhong Agricultural University, Wuhan, China
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10
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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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Liu P, Kang X, Chen X, Luo X, Li C, Wang G. Quercetin targets SarA of methicillin-resistant Staphylococcus aureus to mitigate biofilm formation. Microbiol Spectr 2024; 12:e0272223. [PMID: 38018987 PMCID: PMC10783115 DOI: 10.1128/spectrum.02722-23] [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: 06/30/2023] [Accepted: 10/16/2023] [Indexed: 11/30/2023] Open
Abstract
IMPORTANCE Anti-biofilm is an important strategy against Staphylococcus aureus chronic infection. SarA is a positive regulator of biofilm formation in S. aureus. In this study, we identified the SarA inhibitor quercetin using computer simulation screening. Previous studies have shown that quercetin inhibits biofilm; however, the underlying mechanism remains unknown. This study revealed the inhibitory effect of quercetin on the SarA protein. We also isolated the SarA protein and confirmed its interaction with quercetin in vitro. Besides, the inhibitory effect of quercetin on the transcription and translation levels of the SarA protein was also determined. The effects of quercetin on S. aureus biofilm inhibition and biofilm components were consistent with the changes in the transcription level of biofilm-related genes regulated by SarA. In summary, our study revealed the mechanism by which quercetin affects biofilm formation by inhibiting the transcriptional regulator SarA of S. aureus.
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Affiliation(s)
- Panpan Liu
- College of Animal Science and Technology, Ningxia University, Yinchuan, China
| | - Xinyun Kang
- College of Animal Science and Technology, Ningxia University, Yinchuan, China
| | - Xiaohui Chen
- College of Animal Science and Technology, Ningxia University, Yinchuan, China
| | - Xiaofeng Luo
- College of Animal Science and Technology, Ningxia University, Yinchuan, China
| | - Caixia Li
- College of Animal Science and Technology, Ningxia University, Yinchuan, China
| | - Guiqin Wang
- College of Animal Science and Technology, Ningxia University, Yinchuan, China
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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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Zhang Y, Luo X, Ma L, Ding G, Zhang B. Effect of Ambient Temperature on Hospital Admissions for Respiratory Disease in Suburban Rural Villages of a Semi-Arid Region in Northwest China. J Occup Environ Med 2023; 65:1023-1031. [PMID: 37705416 DOI: 10.1097/jom.0000000000002962] [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] [Indexed: 09/15/2023]
Abstract
OBJECTIVE This study evaluated the effects of extreme temperatures on hospital admissions for respiratory diseases (RDs) in a semi-arid region in the Northwest of China. METHODS Distributed lag nonlinear model was constructed, and stratified analysis by gender and age was performed. RESULTS The exposure-response curve between temperature and RD hospital admissions was almost W-shaped. Either extremely cold temperatures or moderately cold temperatures presented a short-term acute harmful effect, and the relative risks were higher among males (1.976, 95% confidence interval [CI]: 1.773-2.203; 1.242, 95% CI: 1.203-1.282) and the elderly (2.363, 95% CI: 1.724-3.240; 1.267, 95% CI: 1.154-1.390). Both extreme and moderately hot temperatures had higher risks among females (2.040, 95% CI: 1.815-2.292; 1.328, 95% CI: 1.276-1.381). CONCLUSIONS The relationship between air temperature and RD hospital admissions was nonlinear. Vulnerable populations varied according to extreme temperature conditions.
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Affiliation(s)
- Yanan Zhang
- From the School of Public Health, Lanzhou University, Lanzhou, Gansu, 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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Du S, Luo X, Tang L. Aging, crops and pesticide input: empirical evidence from rural China. Pest Manag Sci 2023; 79:5130-5139. [PMID: 37574450 DOI: 10.1002/ps.7714] [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: 01/16/2023] [Revised: 07/29/2023] [Accepted: 08/14/2023] [Indexed: 08/15/2023]
Abstract
BACKGROUND Although scholars have elaborated on the effects of aging, there is no consensus on the relationship between the aging and farmers' pesticide input. Regional differences in agricultural crops in China, namely 'Southern Rice and Northern Wheat', have not been considered in any of the existing studies. RESULTS Based on the data of 443 wheat farmers and 324 rice farmers in China, this study found that aging significantly increased pesticide input. After sorting out the types of pesticides, it was found that the aging significantly increased the input of biological pesticides, but did not affect the input of chemical pesticides. After considering the planting pattern of 'Southern Rice and Northern Wheat', aging did not have a significant impact on the pesticide input of wheat farmers, but had a significant positive impact on the pesticide input of rice farmers. For wheat farmers in the north, social services have a significant inhibitory effect on the relationship between aging and pesticide input. For rice farmers, path dependence has a significant role in promoting the relationship between aging and pesticide input. CONCLUSION The planting pattern of 'Southern Rice and Northern Wheat' will indeed affect the relationship between aging and pesticide input, and social services and path dependence are the main reasons for this heterogeneity effect. Therefore, improving agricultural socialization services and reducing farmers' dependence on traditional production experience will be an important way to effectively reduce the impact of aging. © 2023 Society of Chemical Industry.
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Affiliation(s)
- Sanxia Du
- College of Economics and Management, Huazhong Agricultural University, Wuhan, China
- Hubei Rural Development Research Center, Wuhan, China
| | - Xiaofeng Luo
- College of Economics and Management, Huazhong Agricultural University, Wuhan, China
| | - Lin Tang
- School of Law and Business, Wuhan Institute of Technology, Wuhan, China
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Chen Y, Zheng J, Qiu Y, Wu Z, Luo X, Zhu L, Wu Y, Lin Y. Pulmonary infection associated with immune dysfunction is associated with poor prognosis in patients with myelodysplastic syndrome accompanied by TP53 abnormalities. Front Oncol 2023; 13:1294037. [PMID: 38098502 PMCID: PMC10720429 DOI: 10.3389/fonc.2023.1294037] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/14/2023] [Accepted: 11/10/2023] [Indexed: 12/17/2023] Open
Abstract
The aim of this study was to examine the characteristics and prognosis of patients with myelodysplastic syndrome (MDS) accompanied by TP53 abnormalities and explore potential prognostic factors and treatment responses. This retrospective analysis included 95 patients with MDS and TP53 abnormalities and 173 patients with MDS without TP53 abnormalities at the Fujian Medical University Union Hospital between January 2016 and June 2023. Among patients with TP53 abnormalities, 26 (27.4%) developed AML during the disease course, with a median transformation time of 5.7 months. Complex karyotypes were observed in 73.1% of patients, and the proportions of -5 or del(5q), -7 or del(7q), +8, and -20 or del(20q) were 81.8%, 54.5%, 30.7%, and 25.0%, respectively. These patients exhibited poor survival, with a median overall survival (OS) of 7.3 months, and had 1- and 2-year OS rates of 42.2% and 21.5%, respectively. The complete response rates for azacitidine monotherapy, venetoclax combined with azacitidine, decitabine monotherapy, and decitabine combined with low-dose chemotherapy were 9.1%, 41.7%, 37.5%, and 33.3%, respectively. Long-term survival was similar among the four treatment groups. Patients who underwent allogeneic hematopoietic stem cell transplantation (allo-HSCT) had a median OS of 21.3 months, which trended to be longer than that of patients who did not undergo allo-HSCT (5.6 months; P = 0.1449). Patients with pulmonary infection at diagnosis experienced worse OS than those without pulmonary infection (2.3 months vs. 15.4 months; P < 0.0001). Moreover, 61.9% of patients with pulmonary infection had immune dysfunction, with a ratio of CD4+ to CD8+ T lymphocytes below two. Pulmonary infections and complex karyotypes were independent adverse prognostic factors for OS. In conclusion, TP53 abnormalities in patients with MDS were frequently accompanied by complex karyotypes, and treatments based on hypomethylating agents or venetoclax have limited efficacy. Pulmonary infections associated with immune dysfunction is associated with poor prognosis.
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Affiliation(s)
| | | | | | | | | | | | - Yong Wu
- Fujian Medical University Union Hospital, Fujian Institute of Hematology, Fujian Provincial Key Laboratory on Hematology, Fuzhou, Fujian, China
| | - Yanjuan Lin
- Fujian Medical University Union Hospital, Fujian Institute of Hematology, Fujian Provincial Key Laboratory on Hematology, Fuzhou, Fujian, China
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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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Lin Q, Chen J, Li K, Yang J, Luo X, Cai Q, Lin W, Peng G, Chen D, Qin C, He T, Wang Z. Is Lymphadenectomy Reasonable for Elderly Intrahepatic Cholangiocarcinoma Patients? J Gastrointest Surg 2023; 27:2451-2463. [PMID: 37783911 PMCID: PMC10661814 DOI: 10.1007/s11605-023-05846-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] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/29/2023] [Accepted: 09/13/2023] [Indexed: 10/04/2023]
Abstract
BACKGROUND In this study, we aimed to determine the impact of lymphadenectomy (LND) on clinical outcomes in ICC patients aged ≥ 70 years. METHODS Four hundred and three eligible patients diagnosed with ICC who underwent hepatectomy between 2004 and 2019 were enrolled in the Surveillance, Epidemiology, and End Results database. The impact of LND on perioperative mortality and overall survival (OS) as well as the optimal total number of lymph nodes examined (TNLE) was estimated. RESULTS One hundred thirty-nine pairs of patients were matched by propensity score matching. Perioperative mortality was comparable between the LND and non-LND (nLND) groups (0.7% vs. 2.9%, P = 0.367). The median OS in the LND group was significantly longer (44 vs. 32 months, P = 0.045) and LND was identified as an independent protective factor for OS by multivariate analysis (HR 0.65, 95% CI 0.46-0.92, P = 0.014). Patients with the following characteristics were potential beneficiaries of LND: white, female, no/moderate fibrosis, tumor size > 5 cm, solitary tumor, and localized invasion (all P < 0.05). TNLE ≥ 6 had the greatest discriminatory power for identifying lymph node metastasis (area under the curve, 0.704, Youden index, 0.365, P = 0.002). Patients with pathologically confirmed lymph node metastasis are likely to benefit from adjuvant therapy (40 months vs. 4 months, P = 0.052). CONCLUSIONS Advanced age (≥ 70 years) was not a contraindication for LND, which facilitates accurate nodal staging and guides postoperative management. Appropriately selected elderly populations could benefit from LND.
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Affiliation(s)
- Qianyi Lin
- Sixth Department of General Surgery, Central People's Hospital of Zhanjiang, Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong Province, China
| | - Jianjun Chen
- Second Department of General Surgery, Central People's Hospital of Zhanjiang, Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong Province, China
| | - Kangde Li
- Sixth Department of General Surgery, Central People's Hospital of Zhanjiang, Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong Province, China
| | - Junxing Yang
- Seventh Department of General Surgery, Central People's Hospital of Zhanjiang, Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong Province, China
| | - Xiaofeng Luo
- Seventh Department of General Surgery, Central People's Hospital of Zhanjiang, Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong Province, China
| | - Qi Cai
- Sixth Department of General Surgery, Central People's Hospital of Zhanjiang, Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong Province, China
| | - Weihong Lin
- Sixth Department of General Surgery, Central People's Hospital of Zhanjiang, Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong Province, China
| | - Guanjing Peng
- Sixth Department of General Surgery, Central People's Hospital of Zhanjiang, Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong Province, China
| | - Dexiong Chen
- Sixth Department of General Surgery, Central People's Hospital of Zhanjiang, Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong Province, China
| | - Chunhong Qin
- Sixth Department of General Surgery, Central People's Hospital of Zhanjiang, Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong Province, China
| | - Tao He
- Sixth Department of General Surgery, Central People's Hospital of Zhanjiang, Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong Province, China
| | - Zhenlong Wang
- Seventh Department of General Surgery, Central People's Hospital of Zhanjiang, Zhanjiang Central Hospital, Guangdong Medical University, Zhanjiang, Guangdong Province, 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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Li H, Liu X, Zheng Q, Zeng S, Luo X. Minority stress, social support and mental health among lesbian, gay, and bisexual college students in China: a moderated mediation analysis. BMC Psychiatry 2023; 23:746. [PMID: 37833656 PMCID: PMC10576333 DOI: 10.1186/s12888-023-05202-z] [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] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 03/18/2023] [Accepted: 09/18/2023] [Indexed: 10/15/2023] Open
Abstract
BACKGROUND The existing body of research exploring minority stressors and their impact on the mental health of Lesbian, Gay, and Bisexual (LGB) students in China remains limited in scope and often restricted to specific geographic regions.. METHODS A combination of snowball and targeted sampling strategies was used to recruit lesbian, gay and bisexual students (N = 1,393) for a cross-sectional, online survey in China. Participants (Mage = 20.00 years; 60.23% assigned male at birth) were tasked with completing a comprehensive questionnaire designed to capture various dimensions, including gender expression, minority stressors (e.g., school bullying, internalized homophobia), social psychological resources (e.g., perceived social support), and mental health-related outcomes (e.g., depression, anxious and stress). Our analytical approach involved hierarchical multiple regression analyses, mediation and moderated mediation modeling to elucidate the intricate interplay among these factors. RESULTS Our findings shed light on the pronounced mental health disparities afflicting LGB college students in China, with notable prevalence rates of depression (48.1%), anxiety (57.1%), and stress (37.5%). A significant positive correlation was observed between experiences of school-based victimization and internalized homophobia, which, in turn, exhibited a direct association with affective symptoms.School bullying was positive with internalized homophobia, which was positively associated with affective symptoms.In addition to unveiling the indirect effects of school bullying on affective symptoms, our study identified direct links in this complex relationship. Notably, the availability of social support emerged as a pivotal factor, serving as a moderator within the mediation model by mitigating the path from school-based victimization bullying to internalized homophobia (β = -0.077, P = 0.040). CONCLUSIONS This study underscores the pervasive and concerning mental health disparities experienced by LGB college students in China. In response, institutions of higher learning should intensify anti-bullying initiatives tailored to LGB students and implement comprehensive gender education programs. Moreover, concerted efforts should be directed at enhancing the accessibility of social support resources for LGB college students, with the aim of cultivating and sustaining favorable psychological well-being.
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Affiliation(s)
- Huijun Li
- School of Public Health, Lanzhou University, Lanzhou, China
- Wenzhou Center for Disease Control and Prevention, Wenzhou, China
| | - Xiaoling Liu
- School of Public Health, Lanzhou University, Lanzhou, China
| | - Qingyong Zheng
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou University, Lanzhou, China
| | - Siyuan Zeng
- The First School of Clinical Medicine, Lanzhou University, Lanzhou, China
| | - Xiaofeng Luo
- School of Public Health, Lanzhou University, Lanzhou, 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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Luo S, Kang X, Luo X, Li C, Wang G. Study on the inhibitory effect of quercetin combined with gentamicin on the formation of Pseudomonas aeruginosa and its bioenvelope. Microb Pathog 2023; 182:106274. [PMID: 37516213 DOI: 10.1016/j.micpath.2023.106274] [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: 05/21/2023] [Revised: 07/13/2023] [Accepted: 07/26/2023] [Indexed: 07/31/2023]
Abstract
OBJECTIVE The potential effects of quercetin and gentamicin combination on the bacteriostatic activity and biofilm formation of Pseudomonas aeruginosa (PA) were examined, and the findings provided a theoretical basis for the development of quercetin as a new biofilm inhibitor. METHODS The minimum inhibitory concentration (MIC) of eight PAs was determined by microdilution method and the partial inhibitory concentration index (FICI) of the combined drug was analyzed by micro-dilution method. Thereafter, the lowest film inhibitory concentration (MBIC) of quercetin and gentamicin alone and in combination was evaluated by crystal violet staining. Finally, scanning electron microscopy (SEM) and laser confocal microscopy (CLSM) were used to decipher the inhibitory effect of the combination on biofilm formation. OUTCOME The antibacterial activity of quercetin alone was relatively weak, but after combination with gentamicin, the antibacterial activity was significantly enhanced, as evident by FICI of 0.28 and 0.53 and manifested as synergistic or additive effect, which indicated that quercetin can enhance gentamicin antibacterial activity. The results of crystal violet staining revealed that quercetin and gentamicin alone exhibited a similar biofilm formation inhibitory effect, but the inhibitory effect was substantially weaker, and the antibiofilm activity was stronger and exhibited a dose-dependent response after the combination of the two with 1/2FICI. The results of scanning electron microscopy and laser confocal microscopy also showed that the treatment of PA biofilm after combining quercetin and gentamicin with 1/2FICI could completely destroy the spatial structure of the complete biofilm, significantly reduce the thickness of bacteria, and markedly reduce the proportion of viable bacteria in the membrane. CONCLUSION The combination of quercetin and gentamicin can effectively inhibit the formation of PA as well as its biofilm, and exhibit synergistic and additive effects.
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Affiliation(s)
- Shuangyan Luo
- School of Agriculture, Ningxia University, 750021, Yinchuan, China
| | - Xinyun Kang
- School of Agriculture, Ningxia University, 750021, Yinchuan, China
| | - Xiaofeng Luo
- School of Agriculture, Ningxia University, 750021, Yinchuan, China
| | - Caixia Li
- School of Agriculture, Ningxia University, 750021, Yinchuan, China
| | - Guiqin Wang
- School of Agriculture, Ningxia University, 750021, Yinchuan, China.
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Li W, Zheng Q, Luo X, Zhang X, Zheng X, Yang Y. The predictive implication of programmed cell death ligand 1 expression in extranodal natural killer/T-Cell lymphoma and its correlation with clinicopathological features: a systematic review and meta-analysis. Transl Cancer Res 2023; 12:2115-2127. [PMID: 37701117 PMCID: PMC10493804 DOI: 10.21037/tcr-22-2569] [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: 12/17/2022] [Accepted: 07/14/2023] [Indexed: 09/14/2023]
Abstract
Background Although programmed cell death ligand 1 (PD-L1) expression and function in hematologic malignancies have aroused extensive attention, its prognostic value for extranodal natural killer/T-cell lymphoma (ENKTL) is still unknown. Therefore, we conducted this meta-analysis to explore the predictive value of neoplastic PD-L1 expression for ENKTL. Methods The PubMed, Embase, Web of Science, and CNKI databases were searched to identify eligible observational studies reporting PD-L1 expression and survival outcomes of ENKTL patients. The search was conducted in accordance with the Meta-analyses Of Observative Studies in Epidemiology (MOOSE) guidelines. The pooled hazard ratios (HRs) and 95% confidence intervals (95% CIs) were adopted to analyze survival outcomes, and the odds ratios (ORs) and 95% CIs were adopted for clinicopathological parameters. Review Manager 5.3 and STATA 17.0 were used for statistical analysis. Potential publication bias was evaluated by funnel plot and Egger's test. Results A total of 433 patients with ENKTL were included across seven studies. The pooled results showed no significant relationship between neoplastic PD-L1 expression and overall survival (OS) (HR =1.35, 95% CI: 0.49-3.75, P=0.559). We also performed subgroup analyses. However, increased PD-L1 expression was associated with a low international prognostic index (IPI) score of 0-1 (OR =2.46; 95% CI: 1.11-5.45, P=0.03), good performance status (OR =1.97; 95% CI: 1.11-3.51, P=0.02), and a good treatment effect (OR =2.61; 95% CI: 1.01-6.70, P=0.05). Conclusions PD-L1-positive expression in patients with ENKTL was correlated with favorable clinical features. Thus, PD-L1-positive expression appears to be a potential predictor of treatment benefits. Additional large-scale, high-quality studies are needed to further explore its predictive value.
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Affiliation(s)
- Wen Li
- Department of Pathology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Qiaoling Zheng
- Department of Pathology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Xiaofeng Luo
- Fujian Institute of Hematology, Fujian Provincial Key Laboratory on Hematology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Xinyue Zhang
- Department of Pathology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Xin Zheng
- Department of Pathology, Fujian Medical University Union Hospital, Fuzhou, China
| | - Yinghong Yang
- Department of Pathology, Fujian Medical University Union Hospital, Fuzhou, China
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Yang G, Chen Z, Lv C, Deng L, Luo X, Li Y, He S, Liu Q. Preparation and Performance of H-PDMS/PMHS/OTS Hybrid Nanosilica Hydrophobic and Self-Cleaning Coatings on Phosphogypsum Surface. Polymers (Basel) 2023; 15:3574. [PMID: 37688197 PMCID: PMC10490376 DOI: 10.3390/polym15173574] [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: 07/27/2023] [Revised: 08/21/2023] [Accepted: 08/22/2023] [Indexed: 09/10/2023] Open
Abstract
Hemihydrate phosphogypsum, an industrial solid waste product of phosphoric acid production, is abundant and inexpensive. If the problem of poor water resistance is solved, this material could be substituted for cement and other traditional energy-consuming cementitious materials in the construction industry. This approach would confer important economic and environmental benefits while promoting the resource utilization of phosphogypsum (PG). In this study, hydrophobic and self-cleaning coatings of H-PDMS/PMHS/OTS hybrid nanosilica were prepared on a post-hydroxylated PG surface using sol-gel and impregnation methods. The water contact angle, Fourier-transform infrared spectroscopy, Three-dimensional surface morphology and roughness analysis, X-ray photoelectron spectroscopy, scanning electron microscopy, surface abrasion tests, and tape adhesion tests were used to evaluate the hydrophobicity of the coatings. The results demonstrated that the in situ reaction produced a hydrophobic siloxane/nanosilica hybrid network that bonded to the PG surface via hydrogen bonding, making the otherwise completely hydrophilic PG hydrophobic (PGH-3, contact angle (CA) = 144.1°). The PGH-3 sample exhibited excellent chemical stability, maintaining a contact angle greater than 135° under strongly acidic or alkaline conditions. The contact angle remained at 123.7° after 50 tape-bonding tests. After 100 wear cycles, the contact angle remained at 121.9°. This study presents an environmentally friendly method and a straightforward application procedure to impart hydrophobicity to solid waste PG. Its potential is thus demonstrated in the field of PG-based construction materials and the comprehensive utilization of solid waste.
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Affiliation(s)
- Guang Yang
- College of Materials and Metallurgy, Guizhou University, Guiyang 550025, China; (G.Y.)
| | - Zhonghua Chen
- Guizhou Phosphating Green Environmental Protection Industry Co., Ltd., Guiyang 551100, China
| | - Changwei Lv
- KZJ New Materials Group Guizhou Co., Ltd., Longli 551206, China
| | - Lei Deng
- KZJ New Materials Group Guizhou Co., Ltd., Longli 551206, China
| | - Xiaofeng Luo
- KZJ New Materials Group Guizhou Co., Ltd., Longli 551206, China
| | - Yi Li
- College of Materials and Metallurgy, Guizhou University, Guiyang 550025, China; (G.Y.)
| | - Songtao He
- Guizhou Phosphating Green Environmental Protection Industry Co., Ltd., Guiyang 551100, China
| | - Qibin Liu
- College of Materials and Metallurgy, Guizhou University, Guiyang 550025, China; (G.Y.)
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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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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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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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Cao X, Yang Q, Wang Q, Hu S, Hou L, Sun M, Lai H, Wu C, Wu Y, Xiao L, Luo X, Tian J, Ge L, Luo C. PFMT relevant strategies to prevent perineal trauma: a systematic review and network meta-analysis. Arch Gynecol Obstet 2023; 308:387-401. [PMID: 36107230 DOI: 10.1007/s00404-022-06769-w] [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: 05/13/2022] [Accepted: 08/12/2022] [Indexed: 11/27/2022]
Abstract
BACKGROUND Most women suffer from perineal trauma during childbirth, whether it is natural tears or episiotomy. OBJECTIVES To perform a systematic review and network meta-analysis investigating the effectiveness of different PFMT relevant strategies in the prevention of perineal trauma. SEARCH STRATEGY PubMed, Embase, the Cochrane Library, CINAHL, CNKI, CBM, WANFANG DATABASE, and ClinicalTrials.gov were searched for citations published in any language from inception to 1 July 2021. SELECTION CRITERIA Randomized controlled trials (RCTs) of PFMT relevant prevention strategies for preventing perineal trauma during childbirth. DATA COLLECTION AND ANALYSIS Data were independently extracted by two reviewers. Relative treatment effects were estimated using network meta-analysis (NMA). MAIN RESULTS Of 12 632 citations searched, 21 RCTs were included. Comparing with usual care, "PFMT combine with perineal massage" and PFMT alone showed more superiority in intact perineum (RR = 5.37, 95% CI: 3.79 to 7.60, moderate certainty; RR = 2.58, 95% CI 1.34-4.97, moderate certainty, respectively), episiotomy (RR = 0.26, 95% CI 0.14-0.49, very low certainty; RR = 0.63, 95% CI 0.45-0.90, very low certainty, respectively), and OASIS (RR = 0.35, 95% CI 0.16-0.78, moderate certainty; RR = 0.49, 95% CI 0.28-0.85, high certainty, respectively). "PFMT combine with perineal massage" showed superiority in reducing perineal tear (RR = 0.41, 95% CI 0.20-0.85, moderate certainty). CONCLUSIONS In view of the results, antenatal "PFMT combine with perineal massage" and PFMT were effective strategies for the prevention of perineal trauma.
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Affiliation(s)
- Xiao Cao
- Evidence-Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou, China
| | - Qiuyu Yang
- Evidence-Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou, China
| | - Qi Wang
- Department of Social Medicine and Health Management, and Evidence Based Social Science Research Centre, School of Public Health, Lanzhou University, Lanzhou, China
| | - Shasha Hu
- Department of Obstetrics and Gynecology, First Hospital of Lanzhou University, Lanzhou, China
| | - Liangying Hou
- Department of Social Medicine and Health Management, and Evidence Based Social Science Research Centre, School of Public Health, Lanzhou University, Lanzhou, China
| | - Mingyao Sun
- Evidence-Based Nursing Centre, School of Nursing, Lanzhou University, Lanzhou, China
| | - Honghao Lai
- Department of Social Medicine and Health Management, and Evidence Based Social Science Research Centre, School of Public Health, Lanzhou University, Lanzhou, China
| | - Cailiang Wu
- Department of Obstetrics and Gynecology, Shanghai General Hospital, Shanghai, China
| | - Yu Wu
- Department of Obstetrics and Gynecology, First Hospital of Lanzhou University, Lanzhou, China
- Key Laboratory of Gynecologic Oncology of Gansu Province, Lanzhou, China
| | - Lin Xiao
- Evidence-Based Nursing and Midwifery Practice Center, School of Nursing, Southern Medical University, Guangzhou, China
| | - Xiaofeng Luo
- School of Public Health, Lanzhou University, Lanzhou, China
| | - Jinhui Tian
- Evidence-Based Medicine Center, School of Basic Medicine Science, Lanzhou University, Lanzhou, China
- Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, China
| | - Long Ge
- Department of Social Medicine and Health Management, and Evidence Based Social Science Research Centre, School of Public Health, Lanzhou University, Lanzhou, China.
- Key Laboratory of Evidence Based Medicine and Knowledge Translation of Gansu Province, Lanzhou, China.
| | - Chenling Luo
- Evidence-Based Nursing and Midwifery Practice Center, School of Nursing, Southern Medical University, Guangzhou, 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 R, Luo X, Asamoah JKK, Zhang Y, Li Y, Jin Z, Sun GQ. A hierarchical intervention scheme based on epidemic severity in a community network. J Math Biol 2023; 87:29. [PMID: 37452969 DOI: 10.1007/s00285-023-01964-y] [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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/30/2022] [Revised: 06/01/2023] [Accepted: 07/05/2023] [Indexed: 07/18/2023]
Abstract
As there are no targeted medicines or vaccines for newly emerging infectious diseases, isolation among communities (villages, cities, or countries) is one of the most effective intervention measures. As such, the number of intercommunity edges ([Formula: see text]) becomes one of the most important factor in isolating a place since it is closely related to normal life. Unfortunately, how [Formula: see text] affects epidemic spread is still poorly understood. In this paper, we quantitatively analyzed the impact of [Formula: see text] on infectious disease transmission by establishing a four-dimensional [Formula: see text] edge-based compartmental model with two communities. The basic reproduction number [Formula: see text] is explicitly obtained subject to [Formula: see text] [Formula: see text]. Furthermore, according to [Formula: see text] with zero [Formula: see text], epidemics spread could be classified into two cases. When [Formula: see text] for the case 2, epidemics occur with at least one of the reproduction numbers within communities greater than one, and otherwise when [Formula: see text] for case 1, both reproduction numbers within communities are less than one. Remarkably, in case 1, whether epidemics break out strongly depends on intercommunity edges. Then, the outbreak threshold in regard to [Formula: see text] is also explicitly obtained, below which epidemics vanish, and otherwise break out. The above two cases form a severity-based hierarchical intervention scheme for epidemics. It is then applied to the SARS outbreak in Singapore, verifying the validity of our scheme. In addition, the final size of the system is gained by demonstrating the existence of positive equilibrium in a four-dimensional coupled system. Theoretical results are also validated through numerical simulation in networks with the Poisson and Power law distributions, respectively. Our results provide a new insight into controlling epidemics.
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Affiliation(s)
- Runzi He
- Department of Mathematics, North University of China, Shanxi, Taiyuan, 030051, China
| | - Xiaofeng Luo
- Department of Mathematics, North University of China, Shanxi, Taiyuan, 030051, China.
| | - Joshua Kiddy K Asamoah
- Department of Mathematics, Kwame Nkrumah University of Science and Technology, Kumasi, Ghana
| | - Yongxin Zhang
- Department of Mathematics, North University of China, Shanxi, Taiyuan, 030051, China
| | - Yihong Li
- Department of Mathematics, North University of China, Shanxi, Taiyuan, 030051, China
| | - Zhen Jin
- Complex Systems Research Center, Shanxi University, Shanxi, Taiyuan, 030006, China
| | - Gui-Quan Sun
- Department of Mathematics, North University of China, Shanxi, Taiyuan, 030051, China.
- Complex Systems Research Center, Shanxi University, Shanxi, Taiyuan, 030006, China.
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Li H, Luo X, Haruna SA, Zareef M, Chen Q, Ding Z, Yan Y. Au-Ag OHCs-based SERS sensor coupled with deep learning CNN algorithm to quantify thiram and pymetrozine in tea. Food Chem 2023; 428:136798. [PMID: 37423106 DOI: 10.1016/j.foodchem.2023.136798] [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: 11/17/2022] [Revised: 06/29/2023] [Accepted: 07/01/2023] [Indexed: 07/11/2023]
Abstract
Pesticide residue detection in food has become increasingly important. Herein, surface-enhanced Raman scattering (SERS) coupled with an intelligent algorithm was developed for the rapid and sensitive detection of pesticide residues in tea. By employing octahedral Cu2O templates, Au-Ag octahedral hollow cages (Au-Ag OHCs) were developed, which improved the surface plasma effect via rough edges and hollow inner structure, amplifying the Raman signals of pesticide molecules. Afterward, convolutional neural network (CNN), partial least squares (PLS), and extreme learning machine (ELM) algorithms were applied for the quantitative prediction of thiram and pymetrozine. CNN algorithms performed optimally for thiram and pymetrozine, with correlation values of 0.995 and 0.977 and detection limits (LOD) of 0.286 and 29 ppb, respectively. Accordingly, no significant difference (P greater than 0.05) was observed between the developed approach and HPLC in detecting tea samples. Hence, the proposed Au-Ag OHCs-based SERS technique could be utilized for quantifying thiram and pymetrozine in tea.
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Affiliation(s)
- Huanhuan Li
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China
| | - Xiaofeng Luo
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China
| | - Suleiman A Haruna
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China
| | - Muhammad Zareef
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China
| | - Quansheng Chen
- School of Food and Biological Engineering, Jiangsu University, Zhenjiang 212013, PR China; College of Food and Biological Engineering, Jimei University, Xiamen 361021, PR China.
| | - Zhen Ding
- Changzhou Jintan Jiangnan Powder Co., Ltd, Changzhou 213200, PR China
| | - Yiyong Yan
- Shenzhen Bioeasy Biotechnology Co. Ltd, Shenzhen 518101, PR China; Shenzhen Senlanthy Technology Co., Ltd, Shenzhen 518107, PR 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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40
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Wang H, Du Z, Liu G, Luo X, Yang C. Effect of Long-Term Aging on Fatigue and Thermal Cracking Performance of Polyphosphoric Acid and Styrene-Butadiene-Styrene-Modified Bio-Blend Bitumen. Polymers (Basel) 2023; 15:2911. [PMID: 37447556 DOI: 10.3390/polym15132911] [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: 06/04/2023] [Revised: 06/23/2023] [Accepted: 06/27/2023] [Indexed: 07/15/2023] Open
Abstract
Polyphosphoric acid (PPA) and styrene-butadiene-styrene (SBS) were adopted to produce PPA-SBS-modified bio-blend bitumen, which achieved excellent mechanical performance. However, its long-range performance, such as the fatigue and thermal cracking behavior under long-term thermal oxidation, is not well understood. Therefore, a pressure aging vessel (PAV) system was applied to simulate the aging behavior of the bitumen under the action of thermal oxidation. Then, a linear amplitude sweep (LAS) test combined with a viscoelastic continuum damage (VECD) model was applied to investigate the fatigue properties of the bitumen. Moreover, a bending beam rheometer (BBR) test was conducted to evaluate the thermal cracking resistance of the bitumen before and after PAV aging. Meanwhile, an atomic force microscope (AFM) was applied to observe the microscopic topography. The results show that the original compound-modified bitumen can bear more fatigue damage than that of the control bitumen at the failure point, and it also has excellent fatigue resistance at 2.5%, 5%, 7.5%, and 10% applied strain. Moreover, the VECD model can accurately predict the fatigue life of the bitumen under different applied strains. The variation ratio of stiffness modulus for the compound-modified bitumen is below that of the control bitumen after PAV aging, so it shows a better anti-aging performance. Finally, the AFM test shows that PPA and bio-bitumen decrease the heterogeneity of the bitumen, reducing the difference between phases.
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Affiliation(s)
- Haitao Wang
- China Construction First Group Corporation Limited, Beijing 100071, China
| | - Zhongming Du
- China Construction First Group Corporation Limited, Beijing 100071, China
| | - Guiyong Liu
- School of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China
| | - Xiaofeng Luo
- China Construction First Group Corporation Limited, Beijing 100071, China
| | - Chunlu Yang
- China Construction First Group Corporation Limited, Beijing 100071, China
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41
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Mao Y, Wang Y, Luo X, Chen X, Wang G. Impact of cell-free supernatant of lactic acid bacteria on Staphylococcus aureus biofilm and its metabolites. Front Vet Sci 2023; 10:1184989. [PMID: 37397004 PMCID: PMC10310794 DOI: 10.3389/fvets.2023.1184989] [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] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/13/2023] [Accepted: 05/26/2023] [Indexed: 07/04/2023] Open
Abstract
Introduction A safe bio-preservative agent, lactic acid bacteria (LAB) can inhibit the growth of pathogenic bacteria and spoilage organisms. Its cell-free supernatant (LAB-CFS), which is rich in bioactive compounds, is what makes LAB antibacterial work. Methods This study focused on the changes in biofilm activity and related metabolic pathways of S. aureus treated with lactic acid bacteria planktonic CFS (LAB-pk-CFS) and biofilm state (LAB-bf-CFS). Results The findings demonstrated that the LAB-CFS treatment considerably slowed Staphylococcus aureus (S. aureus) growth and prevented it from forming biofilms. Additionally, it inhibits the physiological traits of the S. aureus biofilm, including hydrophobicity, motility, eDNA, and PIA associated to the biofilm. The metabolites of S. aureus biofilm treated with LAB-CFS were greater in the LAB-bf-CFS than they were in the LAB-pk-CFS, according to metabolomics studies. Important metabolic pathways such amino acids and carbohydrates metabolism were among the most noticeably altered metabolic pathways. Discussion These findings show that LAB-CFS has a strong potential to combat S. aureus infections.
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Affiliation(s)
- Yanni Mao
- Veterinary Pharmacology Lab, School of Animal Science and Technology, Ningxia University, Yinchuan, China
| | - Yuxia Wang
- Veterinary Pharmacology Lab, School of Animal Science and Technology, Ningxia University, Yinchuan, China
| | - Xiaofeng Luo
- Veterinary Pharmacology Lab, School of Animal Science and Technology, Ningxia University, Yinchuan, China
| | - Xiaohui Chen
- Veterinary Pharmacology Lab, School of Animal Science and Technology, Ningxia University, Yinchuan, China
| | - Guiqin Wang
- Veterinary Pharmacology Lab, School of Animal Science and Technology, Ningxia University, Yinchuan, 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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Chen Q, Zhang Y, Zhu H, Yuan X, Luo X, Wu X, Chen S, Chen Y, Xu J, Issa HA, Zheng Z, Hu J, Yang T. Corrigendum to "Bone marrow mesenchymal stem cells alleviate the daunorubicin-induced subacute myocardial injury in rats through inhibiting infiltration of T lymphocytes and antigen-presenting cells" [Biomed. Pharmacother. 121 (2020) 109157]. Biomed Pharmacother 2023:114940. [PMID: 37258310 DOI: 10.1016/j.biopha.2023.114940] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 06/02/2023] Open
Affiliation(s)
- Qiuru Chen
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou 350000, PR China.
| | - Yuxin Zhang
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou 350000, PR China
| | - Haojie Zhu
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou 350000, PR China
| | - Xiaohong Yuan
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou 350000, PR China
| | - Xiaofeng Luo
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou 350000, PR China
| | - Xueqiong Wu
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou 350000, PR China
| | - Shaozhen Chen
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou 350000, PR China
| | - Yongquan Chen
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou 350000, PR China
| | - Jingjing Xu
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou 350000, PR China
| | - Hajji Ally Issa
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou 350000, PR China
| | - Zhihong Zheng
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou 350000, PR China
| | - Jianda Hu
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou 350000, PR China
| | - Ting Yang
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, Fuzhou 350000, PR China
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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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47
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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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Ren J, Lin Q, Chen Q, Xu J, Chen D, Chen R, Lin K, Zhu H, Ye C, Luo X, Chen S, Kong H, Lin Q, Li N, Lin X, Chen Z, Hu J, Yang T. Adoptive immune transfer from donors offers Anti-HBV protection to HBsAb-negative patients after Allo-HSCT. iScience 2023; 26:106290. [PMID: 36936790 PMCID: PMC10014299 DOI: 10.1016/j.isci.2023.106290] [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: 09/20/2022] [Revised: 01/07/2023] [Accepted: 02/22/2023] [Indexed: 03/04/2023] Open
Abstract
Adoptive transfer of hepatitis B virus (HBV) immunity may occur following allogeneic hematopoietic stem cell transplantation (allo-HSCT). Here, we investigated the adoptive transfer of HBV immunity in 112 patients without HBV surface antibody (HBsAb) (HBsAb-) at the time of their first allo-HSCT. After allo-HSCT, HBV-DNA(87.5%) and HBsAg(11.1%%)cleared in HBsAg+ patients. All HBsAg- patients acquired HBsAb immediately. Nevertheless, HBsAb titers subsequently declined, and 39/67 (58.2%) patients lost HBsAb during follow-up. The 5-year overall survival (OS) was better in patients who lost HBsAb. Multivariate analysis showed that the independent risk factors for OS were lack of cytomegalovirus (CMV) clearance, acute graft-versus-host disease (aGVHD), and no HBsAb loss. Overall, adoptive immune transfer offers anti-HBV protection to patients without HBsAb, as they acquire HBsAb and clear HBV-DNA and HBsAg, while HBsAb loss after allo-HSCT predicts better survival.
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Affiliation(s)
- Jinhua Ren
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, 29 Xinquan Road, 350001, Fuzhou, Fujian, P. R. China
| | - QiaoXian Lin
- Department of Hematology, The First Affiliated Hospital of Fujian Medical University, 20 Cha Zhong Road, 350005, Fuzhou, Fujian, P. R. China
| | - Qi Chen
- Department of Hematology, Ningde municipal hospital of Ningde normal university, 13 Mindong Dong Road, 352100, Ningde, Fujian, P. R. China
| | - Jingjing Xu
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, 29 Xinquan Road, 350001, Fuzhou, Fujian, P. R. China
| | - Dabin Chen
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, 29 Xinquan Road, 350001, Fuzhou, Fujian, P. R. China
| | - Renli Chen
- Department of Hematology, Ningde municipal hospital of Ningde normal university, 13 Mindong Dong Road, 352100, Ningde, Fujian, P. R. China
| | - Kangni Lin
- Department of Critical Care Medicine, Fujian Medical University Cancer Hospital & Fujian Cancer Hospital, 420 Fuma Road, Fuzhou, Fujian, P. R. China
| | - Haojie Zhu
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, 29 Xinquan Road, 350001, Fuzhou, Fujian, P. R. China
| | - Chenjing Ye
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, 29 Xinquan Road, 350001, Fuzhou, Fujian, P. R. China
| | - Xiaofeng Luo
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, 29 Xinquan Road, 350001, Fuzhou, Fujian, P. R. China
| | - Shaozhen Chen
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, 29 Xinquan Road, 350001, Fuzhou, Fujian, P. R. China
| | - Hui Kong
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, 29 Xinquan Road, 350001, Fuzhou, Fujian, P. R. China
| | - Qiong Lin
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, 29 Xinquan Road, 350001, Fuzhou, Fujian, P. R. China
| | - Nan Li
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, 29 Xinquan Road, 350001, Fuzhou, Fujian, P. R. China
| | - Xu Lin
- Key Laboratory of Gastrointestinal Cancer (Fujian Medical University), Ministry of Education, Fuzhou 350122, China
| | - Zhizhe Chen
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, 29 Xinquan Road, 350001, Fuzhou, Fujian, P. R. China
| | - Jianda Hu
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, 29 Xinquan Road, 350001, Fuzhou, Fujian, P. R. China
- Corresponding author
| | - Ting Yang
- Department of Hematology, Fujian Institute of Hematology, Fujian Provincial Key Laboratory of Hematology, Fujian Medical University Union Hospital, 29 Xinquan Road, 350001, Fuzhou, Fujian, P. R. China
- Corresponding author
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49
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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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50
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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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