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Wang L, Jin G, Zhou Q, Liu Y, Zhao X, Li Z, Yin N, Peng M. Induction of immortal-like and functional CAR T cells by defined factors. J Exp Med 2024; 221:e20232368. [PMID: 38530240 DOI: 10.1084/jem.20232368] [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] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 12/22/2023] [Revised: 01/10/2024] [Accepted: 03/04/2024] [Indexed: 03/27/2024] Open
Abstract
Long-term antitumor efficacy of chimeric antigen receptor (CAR) T cells depends on their functional persistence in vivo. T cells with stem-like properties show better persistence, but factors conferring bona fide stemness to T cells remain to be determined. Here, we demonstrate the induction of CAR T cells into an immortal-like and functional state, termed TIF. The induction of CARTIF cells depends on the repression of two factors, BCOR and ZC3H12A, and requires antigen or CAR tonic signaling. Reprogrammed CARTIF cells possess almost infinite stemness, similar to induced pluripotent stem cells while retaining the functionality of mature T cells, resulting in superior antitumor effects. Following the elimination of target cells, CARTIF cells enter a metabolically dormant state, persisting in vivo with a saturable niche and providing memory protection. TIF represents a novel state of T cells with unprecedented stemness, which confers long-term functional persistence of CAR T cells in vivo and holds broad potential in T cell therapies.
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Affiliation(s)
- Lixia Wang
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory for Immunological Research on Chronic Diseases, School of Medicine, Institute for Immunology, Tsinghua University, Beijing, China
- SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine , Taiyuan, China
- Tsinghua-Peking Center for Life Sciences , Beijing, China
| | - Gang Jin
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory for Immunological Research on Chronic Diseases, School of Medicine, Institute for Immunology, Tsinghua University, Beijing, China
- SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine , Taiyuan, China
- Tsinghua-Peking Center for Life Sciences , Beijing, China
| | - Qiuping Zhou
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory for Immunological Research on Chronic Diseases, School of Medicine, Institute for Immunology, Tsinghua University, Beijing, China
- SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine , Taiyuan, China
- Tsinghua-Peking Center for Life Sciences , Beijing, China
| | - Yanyan Liu
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory for Immunological Research on Chronic Diseases, School of Medicine, Institute for Immunology, Tsinghua University, Beijing, China
- SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine , Taiyuan, China
- Tsinghua-Peking Center for Life Sciences , Beijing, China
| | - Xiaocui Zhao
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory for Immunological Research on Chronic Diseases, School of Medicine, Institute for Immunology, Tsinghua University, Beijing, China
- SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine , Taiyuan, China
- Tsinghua-Peking Center for Life Sciences , Beijing, China
| | - Zhuoyang Li
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory for Immunological Research on Chronic Diseases, School of Medicine, Institute for Immunology, Tsinghua University, Beijing, China
- SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine , Taiyuan, China
- Tsinghua-Peking Center for Life Sciences , Beijing, China
| | - Na Yin
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory for Immunological Research on Chronic Diseases, School of Medicine, Institute for Immunology, Tsinghua University, Beijing, China
- SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine , Taiyuan, China
- Tsinghua-Peking Center for Life Sciences , Beijing, China
| | - Min Peng
- State Key Laboratory of Molecular Oncology, Beijing Key Laboratory for Immunological Research on Chronic Diseases, School of Medicine, Institute for Immunology, Tsinghua University, Beijing, China
- SXMU-Tsinghua Collaborative Innovation Center for Frontier Medicine , Taiyuan, China
- Tsinghua-Peking Center for Life Sciences , Beijing, China
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Schwindt RG, Posey L, Zhou Q, Birch K. Just Another Patient? Student Reflections on Providing Mental Health Care to Transgender and Gender Expansive People During Simulated Encounters. Nurs Educ Perspect 2024; 45:139-144. [PMID: 38099838 DOI: 10.1097/01.nep.0000000000001216] [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: 04/24/2024]
Abstract
AIM This study analyzed psychiatric-mental health nurse practitioner (PMHNP) students' reflections following a virtual simulated encounter with a patient who identified as transgender or gender expansive (TGE). BACKGROUND To reduce mental health disparities, PMHNP students must be prepared to deliver affirming care. Engaging in and reflecting on simulated encounters with standardized patients can improve PMHNP students' affirming care competency. METHOD A thematic analysis process was used to analyze student reflections during simulation debriefings. RESULTS Five themes emerged: application of affirming care principles, recognizing minority stressors, treating all patients the same, desire to learn more, and valuing authentic practice. CONCLUSION PMHNP students' reflections on the experience of providing care to a standardized patient who identified as TGE support the use of virtual simulations to prepare future providers to deliver affirming, person-centered care.
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Affiliation(s)
- Rhonda G Schwindt
- About the Authors Rhonda G. Schwindt, DNP, PMHNP-BC, is associate professor, George Washington University School of Nursing, Washington, DC. Laurie Posey, EdD, RN, is associate professor, George Washington University School of Nursing. Qiuping Zhou, PhD, RN, is associate professor, George Washington University School of Nursing. Kara Birch, DNP, FNP, PMNHP, is associate clinical professor and program director, PMHNP Post-Master's Program, University of California San Francisco School of Nursing, San Francisco, California. This work was supported by a research grant from the National League for Nursing. For more information, contact Dr. Schwindt at
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Zhou Q, Xiao H, Zhang L, Zhang HT, Meng J. [Non-steroidal anti-inflammatory drugs-exacerbated respiratory disease: a case report]. Zhonghua Er Bi Yan Hou Tou Jing Wai Ke Za Zhi 2024; 59:383-388. [PMID: 38622023 DOI: 10.3760/cma.j.cn115330-20231108-00194] [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: 04/17/2024]
Affiliation(s)
- Q Zhou
- Department of Otorhinolaryngology, Allergy Center, West China Hospital, Sichuan University, Chengdu 610041, China
| | - H Xiao
- Department of Otorhinolaryngology, Allergy Center, West China Hospital, Sichuan University, Chengdu 610041, China
| | - L Zhang
- Department of Otorhinolaryngology, Allergy Center, West China Hospital, Sichuan University, Chengdu 610041, China
| | - H T Zhang
- Department of Otorhinolaryngology, Allergy Center, West China Hospital, Sichuan University, Chengdu 610041, China
| | - J Meng
- Department of Otorhinolaryngology, Allergy Center, West China Hospital, Sichuan University, Chengdu 610041, China
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Shinozaki K, Yu PJ, Zhou Q, Cassiere HA, John S, Rolston DM, Garg N, Li T, Johnson J, Saeki K, Goto T, Okuma Y, Miyara SJ, Hayashida K, Aoki T, Wong VK, Molmenti EP, Lampe JW, Becker LB. Low respiratory quotient correlates with high mortality in patients undergoing mechanical ventilation. Am J Emerg Med 2024; 78:182-187. [PMID: 38301368 DOI: 10.1016/j.ajem.2024.01.003] [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: 12/16/2023] [Accepted: 01/06/2024] [Indexed: 02/03/2024] Open
Abstract
OBJECTIVE Oxygen consumption (VO2), carbon dioxide generation (VCO2), and respiratory quotient (RQ), which is the ratio of VO2 to VCO2, are critical indicators of human metabolism. To seek a link between the patient's metabolism and pathophysiology of critical illness, we investigated the correlation of these values with mortality in critical care patients. METHODS This was a prospective, observational study conducted at a suburban, quaternary care teaching hospital. Age 18 years or older healthy volunteers and patients who underwent mechanical ventilation were enrolled. A high-fidelity automation device, which accuracy is equivalent to the gold standard Douglas Bag technique, was used to measure VO2, VCO2, and RQ at a wide range of fraction of inspired oxygen (FIO2). RESULTS We included a total of 21 subjects including 8 post-cardiothoracic surgery patients, 7 intensive care patients, 3 patients from the emergency room, and 3 healthy volunteers. This study included 10 critical care patients, whose metabolic measurements were performed in the ER and ICU, and 6 died. VO2, VCO2, and RQ of survivors were 282 +/- 95 mL/min, 202 +/- 81 mL/min, and 0.70 +/- 0.10, and those of non-survivors were 240 +/- 87 mL/min, 140 +/- 66 mL/min, and 0.57 +/- 0.08 (p = 0.34, p = 0.10, and p < 0.01), respectively. The difference of RQ was statistically significant (p < 0.01) and it remained significant when the subjects with FIO2 < 0.5 were excluded (p < 0.05). CONCLUSIONS Low RQ correlated with high mortality, which may potentially indicate a decompensation of the oxygen metabolism in critically ill patients.
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Affiliation(s)
- Koichiro Shinozaki
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States of America; Department of Emergency Medicine, Zucker School of Medicine at Hofstra/Northwell, New York, NY, United States of America; Department of Emergency Medicine, North Shore University Hospital, Manhasset, NY, United States of America; Department of Emergency Medicine, Kindai University Faculty of Medicine, Osaka, Japan.
| | - Pey-Jen Yu
- Department of Cardiothoracic Surgery, North Shore University Hospital, Manhasset, NY, United States of America
| | - Qiuping Zhou
- Division of Critical Care Medicine of Emergency Medicine, Long Island Jewish Medical Center, New Hyde Park, NY, United States of America
| | - Hugh A Cassiere
- Division of Critical Care Medicine, Department of Medicine, North Shore University Hospital, Manhasset, NY, United States of America
| | - Stanley John
- Department of Respiratory Therapy, Critical Care Serviceline, Northshore University Hospital, Manhasset, NY, United States of America
| | - Daniel M Rolston
- Department of Emergency Medicine, Zucker School of Medicine at Hofstra/Northwell, New York, NY, United States of America; Department of Emergency Medicine, North Shore University Hospital, Manhasset, NY, United States of America
| | - Nidhi Garg
- Department of Emergency Medicine, Zucker School of Medicine at Hofstra/Northwell, New York, NY, United States of America; Department of Emergency Medicine, South Shore University Hospital, Bay Shore, NY, United States of America
| | - Timmy Li
- Department of Emergency Medicine, Zucker School of Medicine at Hofstra/Northwell, New York, NY, United States of America
| | - Jennifer Johnson
- Department of Emergency Medicine, North Shore University Hospital, Manhasset, NY, United States of America
| | - Kota Saeki
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States of America; Nihon Kohden Innovation Center, Cambridge, MA, United States of America
| | | | - Yu Okuma
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States of America
| | - Santiago J Miyara
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States of America; Department of Anesthesiology, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, United States of America
| | - Kei Hayashida
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States of America
| | - Tomoaki Aoki
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States of America
| | - Vanessa K Wong
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States of America
| | - Ernesto P Molmenti
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States of America; Department of Surgery, Medicine, and Pediatrics, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Joshua W Lampe
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States of America; ZOLL Medical, Chelmsford, MA, USA
| | - Lance B Becker
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, United States of America; Department of Emergency Medicine, Zucker School of Medicine at Hofstra/Northwell, New York, NY, United States of America; Department of Emergency Medicine, North Shore University Hospital, Manhasset, NY, United States of America
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Peng JR, Li YF, Zhou Q, Yuan GJ, Chen GX. [Invisible orthodontic treatment for unilateral condylar hypertrophy in a patient with openbite after condylectomy: a case report]. Zhonghua Kou Qiang Yi Xue Za Zhi 2024; 59:255-258. [PMID: 38432657 DOI: 10.3760/cma.j.cn112144-20230923-00166] [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] [Subscribe] [Scholar Register] [Indexed: 03/05/2024]
Affiliation(s)
- J R Peng
- Outpatient Department of Zhongshang Square, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China
| | - Y F Li
- Outpatient Department of Zhongshang Square, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China
| | - Q Zhou
- Outpatient Department of Zhongshang Square, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China
| | - G J Yuan
- Outpatient Department of Zhongshang Square, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China
| | - G X Chen
- Outpatient Department of Zhongshang Square, School & Hospital of Stomatology, Wuhan University, Wuhan 430079, China
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Zhou Q, Xu LE, Lin LL, Huang XR, Chi WZ, Lin J, Lin P. Clinical study of tirofiban compared to low molecular weight heparin in the antithrombotic treatment of progressive pontine infarction. Eur Rev Med Pharmacol Sci 2024; 28:2186-2191. [PMID: 38567581 DOI: 10.26355/eurrev_202403_35722] [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: 04/04/2024]
Abstract
OBJECTIVE To investigate the efficacy and safety of tirofiban and low molecular weight heparin (LMWH) in the treatment of patients undergoing acute progressive pontine infarction. PATIENTS AND METHODS Patients with acute progressive pontine infarction who were hospitalized in the Neurology Department from June 2021 to June 2023 were included in the study and randomly divided into two groups, namely the experimental group (tirofiban group) and the control group (LMWH group). All patients in both groups were required to receive conventional comprehensive treatment and dual antiplatelet therapy with aspirin + clopidogrel at the beginning of admission. The National Institutes of Health Stroke Scale (NIHSS) score and Barthel Index (BI) were used to evaluate the neurological deficits on the first day of admission, the next day with stroke progression, and at discharge after treatment with tirofiban and LMWH, respectively in the two groups. The modified Rankin Scale was employed to assess prognosis on the 90th day after treatment. Clinical adverse events were followed up for 90 days, comparing the clinical efficacy and safety of the two treatment methods. RESULTS There was no statistical significance in NIHSS score and Barthel Index between the tirofiban group and the LMWH group on the first day of admission and the next day with stroke progression (p > 0.05). After stroke progression, tirofiban and LMWH were separately used for treatment in the two groups. We found that the NIHSS score of the tirofiban group was lower than that of the LMWH group, and the Barthel Index score was higher than that of the LMWH group at discharge (p < 0.05). After three months of follow-up, the mRS score of the tirofiban group was dramatically higher than that of the LMWH group (p < 0.05). No significant harmful or adverse reactions, such as bleeding events, were found in the two groups (p > 0.05). CONCLUSIONS Tirofiban may be more effective and safer than LMWH in controlling the progression of acute pontine infarction, but further and large-sample studies are still needed to confirm this finding.
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Affiliation(s)
- Q Zhou
- Department of Neurology, The Third Affiliated Hospital of Wenzhou Medical University, Wenzhou, China.
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Mei T, Zhou Q, Gong Y. Comparison of the Efficacy and Safety of Perioperative Immunochemotherapeutic Strategies for Resectable Non-small Cell Lung Cancer: a Systematic Review and Network Meta-analysis. Clin Oncol (R Coll Radiol) 2024; 36:107-118. [PMID: 38151439 DOI: 10.1016/j.clon.2023.12.006] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/03/2023] [Revised: 12/07/2023] [Accepted: 12/19/2023] [Indexed: 12/29/2023]
Abstract
AIMS The aim of this network meta-analysis was to elucidate the efficacy and safety of various immune checkpoint inhibitors (ICIs) used in combination with chemotherapy for the treatment of non-small cell lung cancer (NSCLC). MATERIALS AND METHODS Data from randomised controlled trials comparing perioperative ICI-chemotherapy and chemotherapy alone were acquired from the EMBASE, Web of Science, Cochrane Library databases, PubMed, and meeting abstracts from inception until August 2023. The endpoints for this analysis were pathological complete response, event-free survival and treatment-related adverse events of any grade or adverse events of grade 3 or higher. RESULTS In total, six randomised controlled trials with 2538 NSCLC patients were selected for this network meta-analysis. Compared with other ICIs, toripalimab + chemotherapy demonstrated increased pathological complete response rates and prolonged event-free survival in NSCLC. In patients with negative/low PD-L1 expression or squamous cell pathology, toripalimab + chemotherapy was the most effective regimen. In contrast, nivolumab + chemotherapy was preferable for patients with high PD-L1 expression or non-squamous cell pathology. Among the analysed regimens, toripalimab + chemotherapy presented the highest risk of adverse events of any grade, whereas nivolumab + chemotherapy showed the highest risk of grade 3-4 adverse events. Conversely, durvalumab + chemotherapy exhibited the lowest risk of grade 3-4 adverse events. CONCLUSIONS Among the evaluated perioperative immunochemotherapy regimens, toripalimab + chemotherapy indicated a significantly increased survival benefit for most resectable NSCLC patients. However, for high PD-L1 expression and non-squamous NSCLC patients, nivolumab + chemotherapy provided the most potent outcomes. Perioperative durvalumab + chemotherapy is a relatively safe treatment. The findings of this investigation are expected to assist clinicians in making informed decisions among promising treatment options.
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Affiliation(s)
- T Mei
- Division of Thoracic Tumor Multidisciplinary Treatment, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, PR China; Department of Medical Oncology, Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, PR China; Lung Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, PR China
| | - Q Zhou
- Lung Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan, PR China.
| | - Y Gong
- Division of Thoracic Tumor Multidisciplinary Treatment, Cancer Center and State Key Laboratory of Biotherapy, West China Hospital, Sichuan University, Chengdu, PR China.
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Du ZQ, Jiang Y, Lu RR, Zhou Q, Zhu HH, Shen Y. Clinical pharmacist intervention in contraindications of the co-administration of cefoperazone and ambroxol hydrochloride injection. Eur Rev Med Pharmacol Sci 2024; 28:1610-1613. [PMID: 38436193 DOI: 10.26355/eurrev_202402_35490] [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: 03/05/2024]
Abstract
BACKGROUND Clinical pharmacists identified contraindications in two cases concerning the co-administration of cefoperazone and ambroxol hydrochloride injection, prompting a thorough investigation. CASE PRESENTATION Clinically, two cases of contraindications for the co-administration of cefoperazone and ambroxol hydrochloride injection were discovered. After the intervention and analysis by clinical pharmacists, the possible reason could be the precipitation of free alkali due to the immediate administration of ambroxol after the infusion of cefoperazone. Clinical pharmacists suggested avoiding the co-administration of the two and recommended flushing the intravenous lines with 5% glucose injection or 0.9% sodium chloride injection during intravenous infusion to prevent direct drug interaction causing precipitation, thereby reducing the occurrence of adverse events. No adverse events occurred after the intervention, and no harm was caused to the patients. CONCLUSIONS The co-administration of cefoperazone and ambroxol hydrochloride injection can lead to the precipitation of free alkali, posing a risk of adverse events. Clinical pharmacists' intervention could prevent this interaction. This practice has been shown to be effective, with no subsequent adverse events reported.
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Affiliation(s)
- Z-Q Du
- Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi, Jiangsu, China.
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Zhou Q, Zhu D, Wang YT, Dong WY, Yang J, Wen J, Liu J, Yang N, Zhao D, Hua XW, Tang YD. [The association between body mass index and in-hospital major adverse cardiovascular and cerebral events in patients with acute coronary syndrome]. Zhonghua Xin Xue Guan Bing Za Zhi 2024; 52:42-48. [PMID: 38220454 DOI: 10.3760/cma.j.cn112148-20230915-00165] [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: 01/16/2024]
Abstract
Objective: To assess the association between body mass index (BMI) and major adverse cardiovascular and cerebrovascular events (MACCE) among patients with acute coronary syndrome (ACS). Methods: This was a multicenter prospective cohort study, which was based on the Improving Care for Cardiovascular Disease in China (CCC) project. The hospitalized patients with ACS aged between 18 and 80 years, registered in CCC project from November 1, 2014 to December 31, 2019 were included. The included patients were categorized into four groups based on their BMI at the time of admission: underweight (BMI<18.5 kg/m2), normal weight (BMI between 18.5 and 24.9 kg/m2), overweight (BMI between 25.0 and 29.9 kg/m2), and obese (BMI≥30.0 kg/m2). Multivariate logistic regression models was used to analyze the relationship between BMI and the risk of in-hospital MACCE. Results: A total of 71 681 ACS inpatients were included in the study. The age was (63.4±14.7) years, and 26.5% (18 979/71 681) were female. And the incidence of MACCE for the underweight, normal weight, overweight, and obese groups were 14.9% (322/2 154), 9.5% (3 997/41 960), 7.9% (1 908/24 140) and 7.0% (240/3 427), respectively (P<0.001). Multivariate logistic regression analysis showed a higher incidence of MACCE in the underweight group compared to the normal weight group (OR=1.30, 95%CI 1.13-1.49, P<0.001), while the overweight and obese groups exhibited no statistically significant difference in the incidence of MACCE compared to the normal weight group (both P>0.05). Conclusion: ACS patients with BMI below normal have a higher risk of in-hospital MACCE, suggesting that BMI may be an indicator for evaluating short-term prognosis in ACS patients.
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Affiliation(s)
- Q Zhou
- Department of Cardiology, Fuwai Hospital and Cardiovascular Institute, National Center for Cardiovascular Diseases, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100037, China
| | - D Zhu
- Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Research Unit of Medical Science Research Management/Basic and Clinical Research of Metabolic Cardiovascular Diseases, Chinese Academy of Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, National Health Commission Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing 100191, China
| | - Y T Wang
- Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Research Unit of Medical Science Research Management/Basic and Clinical Research of Metabolic Cardiovascular Diseases, Chinese Academy of Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, National Health Commission Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing 100191, China
| | - W Y Dong
- Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Research Unit of Medical Science Research Management/Basic and Clinical Research of Metabolic Cardiovascular Diseases, Chinese Academy of Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, National Health Commission Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing 100191, China
| | - J Yang
- Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Research Unit of Medical Science Research Management/Basic and Clinical Research of Metabolic Cardiovascular Diseases, Chinese Academy of Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, National Health Commission Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing 100191, China
| | - J Wen
- Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Research Unit of Medical Science Research Management/Basic and Clinical Research of Metabolic Cardiovascular Diseases, Chinese Academy of Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, National Health Commission Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing 100191, China
| | - J Liu
- Center of Clinical and Epidemiology Researches, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing 100029, China
| | - N Yang
- Center of Clinical and Epidemiology Researches, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing 100029, China
| | - D Zhao
- Center of Clinical and Epidemiology Researches, Beijing Anzhen Hospital, Capital Medical University, Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing 100029, China
| | - X W Hua
- Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Research Unit of Medical Science Research Management/Basic and Clinical Research of Metabolic Cardiovascular Diseases, Chinese Academy of Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, National Health Commission Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing 100191, China
| | - Y D Tang
- Department of Cardiology and Institute of Vascular Medicine, Peking University Third Hospital, Research Unit of Medical Science Research Management/Basic and Clinical Research of Metabolic Cardiovascular Diseases, Chinese Academy of Medical Sciences, State Key Laboratory of Vascular Homeostasis and Remodeling, National Health Commission Key Laboratory of Cardiovascular Molecular Biology and Regulatory Peptides, Beijing Key Laboratory of Cardiovascular Receptors Research, Beijing 100191, China
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Liu X, Onda M, Schlomer J, Bassel L, Kozlov S, Tai CH, Zhou Q, Liu W, Tsao HE, Hassan R, Ho M, Pastan I. Tumor resistance to anti-mesothelin CAR-T cells caused by binding to shed mesothelin is overcome by targeting a juxtamembrane epitope. Proc Natl Acad Sci U S A 2024; 121:e2317283121. [PMID: 38227666 PMCID: PMC10823246 DOI: 10.1073/pnas.2317283121] [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: 10/06/2023] [Accepted: 11/27/2023] [Indexed: 01/18/2024] Open
Abstract
Despite many clinical trials, CAR-T cells are not yet approved for human solid tumor therapy. One popular target is mesothelin (MSLN) which is highly expressed on the surface of about 30% of cancers including mesothelioma and cancers of the ovary, pancreas, and lung. MSLN is shed by proteases that cleave near the C terminus, leaving a short peptide attached to the cell. Most anti-MSLN antibodies bind to shed MSLN, which can prevent their binding to target cells. To overcome this limitation, we developed an antibody (15B6) that binds next to the membrane at the protease-sensitive region, does not bind to shed MSLN, and makes CAR-T cells that have much higher anti-tumor activity than a CAR-T that binds to shed MSLN. We have now humanized the Fv (h15B6), so the CAR-T can be used to treat patients and show that h15B6 CAR-T produces complete regressions in a hard-to-treat pancreatic cancer patient derived xenograft model, whereas CAR-T targeting a shed epitope (SS1) have no anti-tumor activity. In these pancreatic cancers, the h15B6 CAR-T replicates and replaces the cancer cells, whereas there are no CAR-T cells in the tumors receiving SS1 CAR-T. To determine the mechanism accounting for high activity, we used an OVCAR-8 intraperitoneal model to show that poorly active SS1-CAR-T cells are bound to shed MSLN, whereas highly active h15B6 CAR-T do not contain bound MSLN enabling them to bind to and kill cancer cells.
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Affiliation(s)
- X.F. Liu
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - M. Onda
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - J. Schlomer
- Center for Advanced Preclinical Research, Frederick National Lab for Cancer Research Center for Cancer Research, National Cancer Institute, NIH, Frederick, MD 21701
| | - L. Bassel
- Center for Advanced Preclinical Research, Frederick National Lab for Cancer Research Center for Cancer Research, National Cancer Institute, NIH, Frederick, MD 21701
| | - S. Kozlov
- Center for Advanced Preclinical Research, Frederick National Lab for Cancer Research Center for Cancer Research, National Cancer Institute, NIH, Frederick, MD 21701
| | - C.-H. Tai
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - Q. Zhou
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - W. Liu
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - H.-E. Tsao
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - R. Hassan
- Thoracic and Gastrointestinal Malignancies Branch, National Cancer Institute, NIH, Bethesda, MD20892
| | - M. Ho
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
| | - I. Pastan
- Laboratory of Molecular Biology, National Cancer Institute, NIH, Bethesda, MD20892
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11
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Wu YL, Zhou Q. [Clinical pathway in Chinese county for lung cancer diagnosis and treatment (2023 edition)]. Zhonghua Zhong Liu Za Zhi 2024; 46:19-39. [PMID: 38246778 DOI: 10.3760/cma.j.cn112152-20230928-00162] [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: 01/23/2024]
Abstract
Lung cancer (LC) is the leading cause of death among patients with cancer both in worldwide and China. China accounts for 11.4% of the total number of cancer cases and 18.0% of the total number of cancer deaths in the world. Standardizing the diagnosis and treatment of LC is a key measure to improve the survival rate of LC patients and reduce the mortality rate. However, county hospitals generally face the problem of inaccessibility to advanced diagnostic and treatment technologies. Therefore, when developing quality control standards and clinical diagnosis and treatment specifications, it is necessary to combine the actual situation of county hospitals and formulate specific recommendations. The recommendations of treatment measures also need to consider the approval status of indications and whether it is included in the National Reimbursement Drug List (NRDL), to ensure the access to medicines. In order to solve the above problems, based on existing guidelines at home and abroad and the clinical work characteristics of county hospitals, the first clinical pathway in Chinese county for LC diagnosis and treatment (2023 edition) was compiled. This pathway elaborated on the imaging diagnosis, pathological diagnosis, molecular testing, and precision medicine based on histological-pathological types, tumor-node-metastasis (TNM) classification, and molecular classification, developed different diagnosis and treatment processes for different types of LC patients. Simultaneously, according to the actual work situation of county hospitals, the diagnosis and treatment recommendations in clinical scenarios are divided into basic strategies and optional strategies for elaboration. The basic strategies are the standards that county hospitals must meet, while the optional strategies provide more choices for hospitals, which are convenient for county doctors to put into clinical practice. All the recommended diagnostic and treatment plans strictly refer to existing guidelines and consensus, ensuring the scientificity.
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Affiliation(s)
- Y L Wu
- Guangdong Provincial People's Hospital, Guangdong Lung Cancer Institute, Guangzhou, 519041, China
| | - Q Zhou
- Department of Pulmonary Medicine Ⅱ, Guangdong Provincial People's Hospital, Guangzhou 519041, China
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Peng X, Zhou Q, Wang CQ, Zhang ZM, Luo Z, Xu SY, Feng B, Fang ZF, Lin Y, Zhuo Y, Jiang XM, Zhao H, Tang JY, Wu D, Che LQ. Dietary supplementation of proteases on growth performance, nutrient digestibility, blood characteristics and gut microbiota of growing pigs fed sorghum-based diets. Animal 2024; 18:101052. [PMID: 38181459 DOI: 10.1016/j.animal.2023.101052] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/05/2023] [Revised: 12/02/2023] [Accepted: 12/04/2023] [Indexed: 01/07/2024] Open
Abstract
Low-tannin sorghum is an excellent energy source in pig diets. However, sorghum contains several anti-nutritional factors that may have negative effects on nutrient digestibility. The impacts of proteases on growth performance, nutrient digestibility, blood parameters, and gut microbiota of growing pigs fed sorghum-based diets were studied in this study. Ninety-six pigs (20.66 ± 0.65 kg BW) were allocated into three groups (eight pens/group, four pigs/pen): (1) CON (control diet, sorghum-based diet included 66.98% sorghum), (2) PRO1 (CON + 200 mg/kg proteases), (3) PRO2 (CON + 400 mg/kg proteases) for 28 d. No differences were observed in growth performance and apparent total tract digestibility (ATTD) of nutrients between CON and PRO1 groups. Pigs fed PRO2 diet had increased (P < 0.05) BW on d 21 and 28, and increased (P < 0.05) average daily gain during d 14-21 and the overall period compared with pigs fed CON diet. In addition, pigs fed PRO2 diet had improved (P < 0.05) ATTD of gross energy, CP, and DM compared with pigs fed CON and PRO1 diets. Pigs fed PRO2 diet had lower (P < 0.05) plasma globulin (GLB) level and higher (P < 0.05) plasma glucose, albumin (ALB) and immunoglobulin G levels, and ALB/GLB ratio than pigs fed CON and PRO1 diets. Furthermore, pigs fed PRO2 diet had decreased (P < 0.05) the relative abundance of Acidobacteriota at the phylum level and increased (P < 0.05) the relative abundance of Prevotella_9 at the genus level. The linear discriminant analysis effect size analysis also showed that pigs fed PRO2 diet had significantly enriched short-chain fatty acid-producing bacteria, such as Subdoligranulum and Parabacteroides. In conclusion, protease supplementation at 400 mg/kg improved the growth performance of growing pigs fed sorghum-based diets, which may be attributed to the improvement of nutrient digestibility, host metabolism, immune status and associated with the altered gut microbiota profiles.
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Affiliation(s)
- X Peng
- Laboratory for Bio-feed and Molecular Nutrition, College of Animal Science and Technology, Southwest University, Chongqing 400715, China; Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, China
| | - Q Zhou
- Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, China
| | - C Q Wang
- Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, China
| | - Z M Zhang
- College of Animal Science and Technology, Hunan Agricultural University, Changsha 410128, China
| | - Z Luo
- Kemin (China) Technologies Co., Ltd., Sanzao, Zhuhai 519040, China
| | - S Y Xu
- Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, China
| | - B Feng
- Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, China
| | - Z F Fang
- Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, China
| | - Y Lin
- Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, China
| | - Y Zhuo
- Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, China
| | - X M Jiang
- Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, China
| | - H Zhao
- Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, China
| | - J Y Tang
- Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, China
| | - D Wu
- Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, China
| | - L Q Che
- Key Laboratory for Animal Disease-Resistance Nutrition of China Ministry of Education, Institute of Animal Nutrition, Sichuan Agricultural University, Chengdu 611130, China.
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Zhao HY, Han JT, Hu DH, Zhou Q, Zhu C, Xu J, Zhang BW, Qi ZS, Liu JQ. [A randomized controlled trial on the effect of exercise prescription based on a progressive mode in treating elderly patients with lower limb dysfunction after deep burns]. Zhonghua Shao Shang Yu Chuang Mian Xiu Fu Za Zhi 2023; 39:1122-1130. [PMID: 38129298 DOI: 10.3760/cma.j.cn501225-20230721-00012] [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: 12/23/2023]
Abstract
Objective: To explore the effect of exercise prescription based on a progressive mode in treating elderly patients with lower limb dysfunction after deep burns. Methods: A randomized controlled trial was conducted. From January 2021 to January 2023, 60 elderly patients with lower limb dysfunction after deep burns who met the inclusion criteria were admitted to the First Affiliated Hospital of Air Force Medical University. The patients were divided into conventional rehabilitation group (30 cases, 17 males and 13 females, aged (65±3) years) and combined rehabilitation group (30 cases, 16 males and 14 females, aged (64±3) years) according to the random number table. For patients in both groups, the red-light treatment was started after the lower limb wounds healed or when the total area of scattered residual wounds was less than 1% of the total body surface area. After 2 weeks of red-light treatment, the patients in conventional rehabilitation group were given conventional rehabilitation treatments, including joint stretching, resistance, and balance training; in addition to conventional rehabilitation treatments, the patients in combined rehabilitation group were given exercise prescription training based on a progressive mode three times a week, mainly including dumbbell press, Bobath ball horizontal support, and high-level pulldown trainings. The training time for patients in both groups was 12 weeks. Before training (after 2 weeks of red-light treatment) and after 12 weeks of training, the upper limb and lower limb motor functions of the patients were evaluated using the simple Fugl-Meyer scale, the physical fitness of patients was evaluated using the simple physical fitness scale, and the patient's risk of falling was evaluated by the time consumed for the timed up and go test. The adverse events of patients that occurred during training were recorded. After 12 weeks of training, a self-designed satisfaction survey was conducted to investigate patients' satisfaction with the training effect. Data were statistically analyzed with independent sample t test, paired sample t test, Mann-Whitney U test, Wilcoxon signed rank test, and chi-square test. Results: Before training, the scores of upper limb and lower limb motor functions of patients between the two groups were similar (P>0.05). After 12 weeks of training, the scores of upper limb motor function of patients in conventional rehabilitation group and combined rehabilitation group were significantly higher than those before training (with t values of -11.42 and -13.67, respectively, P<0.05), but there was no statistically significant difference between the two groups (P>0.05). The score of lower limb motor function of patients in combined rehabilitation group was 28.9±2.6, which was significantly higher than 26.3±2.6 in conventional rehabilitation group (t=-3.90, P<0.05), and the scores of lower limb motor function of patients in conventional rehabilitation group and combined rehabilitation group were significantly higher than those before training (with t values of -4.14 and -6.94, respectively, P<0.05). Before training, the individual and total scores of physical fitness of patients between the two groups were similar (P>0.05). After 12 weeks of training, the balance ability score, walking speed score, chair sitting score, and total score of physical fitness of patients in conventional rehabilitation group and combined rehabilitation group were significantly increased compared with those before training (with Z values of -4.38, -3.55, -3.88, -4.65, -4.58, -4.68, -4.42, and -4.48, respectively, P<0.05), and the balance ability score, walking speed score, chair sitting score, and total score of physical fitness of patients in combined rehabilitation group were significantly increased compared with those in conventional rehabilitation group (with Z values of -3.93, -3.41, -3.19, and -5.33, P<0.05). Before training, the time consumed for the timed up and go test for patient's risk of falling in the two groups was close (P>0.05). After 12 weeks of training, the time consumed for the timed up and go test for patient's risk of falling in combined rehabilitation group was (28.0±2.1) s, which was significantly shorter than (30.5±1.8) s in conventional rehabilitation group (t=4.94, P<0.05). Moreover, the time consumed for the timed up and go test for patient's risk of falling in both conventional rehabilitation group and combined rehabilitation group was significantly shorter than that before training (with t values of 14.80 and 15.86, respectively, P<0.05). During the training period, no adverse events such as muscle tissue strain, edema, or falling occurred in any patient. After 12 weeks of training, the satisfaction score of patients with the training effect in combined rehabilitation group was 13.5±1.2, which was significantly higher than 8.5±1.4 in conventional rehabilitation group (t=21.78, P<0.05). Conclusions: The exercise prescription training based on a progressive mode can significantly promote the recovery of lower limb motor function and physical fitness of elderly patients with lower limb dysfunction after deep burns, and effectively reduce the patient's risk of falling without causing adverse events during the training period, resulting in patient's high satisfaction with the training effect.
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Affiliation(s)
- H Y Zhao
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital, Air Force Medical University, Xi'an 710032, China
| | - J T Han
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital, Air Force Medical University, Xi'an 710032, China
| | - D H Hu
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital, Air Force Medical University, Xi'an 710032, China
| | - Q Zhou
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital, Air Force Medical University, Xi'an 710032, China
| | - C Zhu
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital, Air Force Medical University, Xi'an 710032, China
| | - J Xu
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital, Air Force Medical University, Xi'an 710032, China
| | - B W Zhang
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital, Air Force Medical University, Xi'an 710032, China
| | - Z S Qi
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital, Air Force Medical University, Xi'an 710032, China
| | - J Q Liu
- Department of Burns and Cutaneous Surgery, Burn Center of PLA, the First Affiliated Hospital, Air Force Medical University, Xi'an 710032, China
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Wang H, Li Y, Jiang S, Liu N, Zhou Q, Li Q, Chen Z, Lin Y, Chen C, Deng Y. LncRNA xist regulates sepsis associated neuroinflammation in the periventricular white matter of CLP rats by miR-122-5p/PKCη Axis. Front Immunol 2023; 14:1225482. [PMID: 38115999 PMCID: PMC10728298 DOI: 10.3389/fimmu.2023.1225482] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/19/2023] [Accepted: 10/30/2023] [Indexed: 12/21/2023] Open
Abstract
Background Neuroinflammation is a common feature of many neurological diseases, and remains crucial for disease progression and prognosis. Activation of microglia and astrocytes can lead to neuroinflammation. However, little is known about the role of lncRNA xist and miR-122-5p in the pathogenesis of sepsis-associated neuroinflammation (SAN). This study aims to investigate the role of lncRNA xist and miR-122-5p in the pathogenesis of SAN. Methods Levels of miR-122-5p and proinflammatory mediators were detected in the cerebrospinal fluid (CSF) of patients with intracranial infection (ICI) by ELISA and qRT-PCR. miRNA expression in the periventricular white matter (PWM) in rats was analyzed by high-throughput sequencing. Levels of lncRNA xist, miR-122-5p and proinflammatory mediators in the PWM were measured using qRT-PCR and western blot. Bioinformatics analysis was used to predict the upstream and downstream of miR-122-5p. The interaction between miR-122-5p and its target protein was validated using luciferase reporter assay. BV2 and astrocytes were used to detect the expression of lncRNA xist, miR-122-5p. Results The level of miR-122-5p was significantly decreased in the CSF of ICI patients, while the expression of IL-1β and TNF-α were significantly upregulated. Furthermore, it was found that the expression of IL-1β and TNF-α were negatively correlated with the level of miR-122-5p. A high-throughput sequencing analysis showed that miR-122-5p expression was downregulated with 1.5-fold changes in the PWM of CLP rats compared with sham group. Bioinformatics analysis found that lncRNA xist and PKCη were the upstream and downstream target genes of miR-122-5p, respectively. The identified lncRNA xist and PKCη were significantly increased in the PWM of CLP rats. Overexpression of miR-122-5p or knockdown of lncRNA xist could significantly downregulate the level of PKCη and proinflammatory mediators from activated microglia and astrocytes. Meanwhile, in vitro investigation showed that silencing lncRNA xist or PKCη or enhancing the expression of miR-122-5p could obviously inhibit the release of proinflammatory mediators in activated BV2 cells and astrocytes. Conclusion LncRNA xist could regulate microglia and astrocytes activation in the PWM of CLP rats via miR-122-5p/PKCη axis, further mediating sepsis associated neuroinflammation.
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Affiliation(s)
- Huifang Wang
- Department of Intensive Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Yichen Li
- Department of Intensive Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Shuqi Jiang
- Department of Intensive Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Nan Liu
- Department of Intensive Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Department of Critical Care Medicine, Guangdong Provincial People’s Hospital, School of Medicine South China University of Technology, Guangzhou, China
| | - Qiuping Zhou
- Department of Intensive Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Qian Li
- Department of Intensive Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Zhuo Chen
- Department of Intensive Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- Department of Critical Care Medicine, Guangdong Provincial People’s Hospital, School of Medicine South China University of Technology, Guangzhou, China
| | - Yiyan Lin
- Department of Intensive Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
- The Second School of Clinical Medicine, Southern Medical University, Guangzhou, China
| | - Chunbo Chen
- Department of Intensive Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
| | - Yiyu Deng
- Department of Intensive Care Medicine, Guangdong Provincial People’s Hospital (Guangdong Academy of Medical Sciences), Southern Medical University, Guangzhou, China
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15
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Yan ZC, Jiang N, Zhang HX, Zhou Q, Liu XL, Sun F, Yang RM, He HB, Zhao ZG, Zhu ZM. [Efficacy and feasibility of catheter-based adrenal ablation on Cushing's syndrome associated hypertension]. Zhonghua Xin Xue Guan Bing Za Zhi 2023; 51:1152-1159. [PMID: 37963750 DOI: 10.3760/cma.j.cn112148-20230801-00045] [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: 11/16/2023]
Abstract
Objective: To explore the value of catheter-based adrenal ablation in treating Cushing's syndrome (CS)-associated hypertension. Methods: A clinical study was conducted in patients with CS, who received catheter-based adrenal ablation between March 2018 and July 2023 in Daping Hospital. Parameters monitored were blood pressure (outpatient and 24-hour ambulatory), body weight, clinical characteristics, serum cortisol and adrenocorticotropic hormone (ACTH) at 8 am, 24-hour urinary free cortisol (24 h UFC), fasting blood glucose and postoperative complications. Procedure effectiveness was defined as blood pressure returning to normal levels (systolic blood pressure<140 mmHg (1 mmHg=0.133 kPa) and diastolic blood pressure<90 mmHg), cortisol and 24 h UFC returning to normal and improvement of clinical characteristics. The parameters were monitored during follow up in the outpatient department at 1, 3, 6, and 12 months after catheter-based adrenal ablation. Results: A total of 12 patients (aged (40.0±13.2) years) were reviewed. There were 5 males, with 5 cases of adenoma and 7 with hyperplasia from imaging studies. Catheter-based adrenal ablation was successful in all without interruption or surgical conversion. No postoperative complication including bleeding, puncture site infection, adrenal artery rupture or adrenal bleeding was observed. The mean follow up was 28 months. Compared to baseline values, body weight declined to (59.48±11.65) kg from (64.81±10.75) kg (P=0.008), fasting blood glucose declined to (4.54±0.83) mmol from (5.53±0.99) mmol (P=0.044), outpatient systolic blood pressure declined to (128±21) mmHg from (140±19) mmHg (P=0.005), diastolic blood pressure declined to (78±10) mmHg from (86±11) mmHg (P=0.041), and the mean ambulatory daytime diastolic blood pressure declined to (79±12) mmHg from (89±8) mmHg (P=0.034). Catheter-based adrenal ablation in 8 patients was defined as effective with their 24 h UFC significantly reduced after the procedure (1 338.41±448.06) mmol/L from (633.66±315.94) mmol/L, P=0.011). The change of 24 h UFC between the effective treatment group and ineffective group was statistically significant (P=0.020). The postoperative systolic blood pressure in the treated adenoma group was significantly lower than those of hyperplasia group (112±13) mmHg vs. (139±20) mmHg, P=0.026). Conclusions: For patients with CS-associated hypertension who are unwilling or unable to undergo surgical treatment, catheter-based adrenal ablation could improve the blood pressure and cortisol level. Catheter-based adrenal ablation could be a safe, effective, and minimally invasive therapy. However, our results still need to be validated in further large-scale studies.
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Affiliation(s)
- Z C Yan
- Department of Hypertension and Endocrinology, Center for Hypertension and Cardiometabolic Diseases, Daping Hospital, Army Medical University, Chongqing Institute of Hypertension, Chongqing 400042, China
| | - N Jiang
- Department of Hypertension and Endocrinology, Center for Hypertension and Cardiometabolic Diseases, Daping Hospital, Army Medical University, Chongqing Institute of Hypertension, Chongqing 400042, China
| | - H X Zhang
- Department of Hypertension and Endocrinology, Center for Hypertension and Cardiometabolic Diseases, Daping Hospital, Army Medical University, Chongqing Institute of Hypertension, Chongqing 400042, China
| | - Q Zhou
- Department of Hypertension and Endocrinology, Center for Hypertension and Cardiometabolic Diseases, Daping Hospital, Army Medical University, Chongqing Institute of Hypertension, Chongqing 400042, China
| | - X L Liu
- Department of Hypertension and Endocrinology, Center for Hypertension and Cardiometabolic Diseases, Daping Hospital, Army Medical University, Chongqing Institute of Hypertension, Chongqing 400042, China
| | - F Sun
- Department of Hypertension and Endocrinology, Center for Hypertension and Cardiometabolic Diseases, Daping Hospital, Army Medical University, Chongqing Institute of Hypertension, Chongqing 400042, China
| | - R M Yang
- Department of Hypertension and Endocrinology, Center for Hypertension and Cardiometabolic Diseases, Daping Hospital, Army Medical University, Chongqing Institute of Hypertension, Chongqing 400042, China
| | - H B He
- Department of Hypertension and Endocrinology, Center for Hypertension and Cardiometabolic Diseases, Daping Hospital, Army Medical University, Chongqing Institute of Hypertension, Chongqing 400042, China
| | - Z G Zhao
- Department of Hypertension and Endocrinology, Center for Hypertension and Cardiometabolic Diseases, Daping Hospital, Army Medical University, Chongqing Institute of Hypertension, Chongqing 400042, China
| | - Z M Zhu
- Department of Hypertension and Endocrinology, Center for Hypertension and Cardiometabolic Diseases, Daping Hospital, Army Medical University, Chongqing Institute of Hypertension, Chongqing 400042, China
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16
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Wen CJ, Wang MH, Yu P, Zhou Q. [Advances in clinical significance and detection methods research of high density lipoprotein subfractions]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:1901-1907. [PMID: 38008584 DOI: 10.3760/cma.j.cn112150-20230220-00134] [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: 11/28/2023]
Abstract
High density lipoprotein (HDL) is an important biochemical index of clinical cardiovascular disease. Many new studies have demonstrated abnormalities of plasma HDL subfractions in patients with this disease,and their clinical significance is greater than the overall abnormalities of HDL. Therefore,the HDL subfraction as an important factor in cardiovascular disease has attracted extensive research and attention. This article summarizes current research on HDL subfractions,their measurements and their relationships with atherosclerosis and coronary artery disease.
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Affiliation(s)
- C J Wen
- Jinyu School of Laboratory Medicine,Guangzhou Medical University, Guangzhou 510260,China
| | - M H Wang
- Laboratory Department, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou 510260,China
| | - P Yu
- Laboratory Department, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou 510260,China
| | - Q Zhou
- Laboratory Department, the Second Affiliated Hospital of Guangzhou Medical University, Guangzhou 510260,China
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17
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Ulrich CM, Ratcliffe SJ, Hochheimer CJ, Zhou Q, Huang L, Gordon T, Knafl K, Richmond T, Schapira MM, Miller V, Mao JJ, Naylor M, Grady C. Informed Consent among Clinical Trial Participants with Different Cancer Diagnoses. AJOB Empir Bioeth 2023:1-13. [PMID: 37921867 DOI: 10.1080/23294515.2023.2262992] [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] [Indexed: 11/04/2023]
Abstract
IMPORTANCE Informed consent is essential to ethical, rigorous research and is important to recruitment and retention in cancer trials. OBJECTIVE To examine cancer clinical trial (CCT) participants' perceptions of informed consent processes and variations in perceptions by cancer type. DESIGN AND SETTING AND PARTICIPANTS Cross-sectional survey from mixed-methods study at National Cancer Institute-designated Northeast comprehensive cancer center. Open-ended and forced-choice items addressed: (1) enrollment and informed consent experiences and (2) decision-making processes, including risk-benefit assessment. Eligibility: CCT participant with gastro-intestinal or genitourinary, hematologic-lymphatic malignancies, lung cancer, and breast or gynecological cancer (N = 334). MAIN OUTCOME MEASURES Percentages satisfied with consent process and information provided; and assessing participation's perceptions of risks/benefits. Multivariable logistic or ordinal regression examined differences by cancer type. RESULTS Most patient-participants felt well informed by the consent process (more than 90% overall and by cancer type) and. most (87.4%) reported that the consent form provided all the information they wanted, although nearly half (44.8%) reported that they read the form somewhat carefully or less. More than half (57.9%) said that talking to research staff (i.e., the consent process) had a greater impact on participation decisions than reading the consent form (2.1%). A third (31.1%) were very sure of joining in research studies before the informed consent process (almost half of lung cancer patients did-47.1%). Most patients personally assessed the risks and benefits before consenting. However, trust in physicians played an important role in the decision to enroll in CCT. CONCLUSIONS AND RELEVANCE Cancer patients rely less on written features of the informed consent process than on information obtained from the research staff and their own physicians. Research should focus on information and communication strategies that support informed consent from referring physicians, researchers, and others to improve patient risk-benefit assessment and decision-making.
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Affiliation(s)
- Connie M Ulrich
- University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | | | | | - Qiuping Zhou
- George Washington University, Washington, District of Columbia, USA
| | - Liming Huang
- University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA
| | - Thomas Gordon
- University of Massachusetts Lowell, Lowell, Massachusetts, USA
| | - Kathleen Knafl
- University of North Carolina at Chapel Hill, Chapel Hill, North Carolina, USA
| | - Therese Richmond
- University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA
| | - Marilyn M Schapira
- University of Pennsylvania Perelman School of Medicine, Philadelphia, Pennsylvania, USA
| | - Victoria Miller
- Children's Hospital of Philadelphia, Philadelphia, Pennsylvania, USA
| | - Jun J Mao
- Memorial Sloan Kettering Cancer Center, New York, New York, USA
| | - Mary Naylor
- University of Pennsylvania School of Nursing, Philadelphia, Pennsylvania, USA
| | - Christine Grady
- National Institutes of Health, Clinical Center Department of Bioethics, Bethesda, Maryland, USA
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Zhou Q, Zhang X, Wu Y, Jiang X, Li T, Chen M, Ni L, Diao G. Polyoxometalates@Metal-Organic Frameworks Derived Bimetallic Co/Mo 2 C Nanoparticles Embedded in Carbon Nanotube-Interwoven Hierarchically Porous Carbon Polyhedron Composite as a High-Efficiency Electrocatalyst for Al-S Batteries. Small 2023; 19:e2304515. [PMID: 37541304 DOI: 10.1002/smll.202304515] [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: 05/30/2023] [Revised: 07/18/2023] [Indexed: 08/06/2023]
Abstract
Al-S battery (ASB) is a promising energy storage device, notable for its safety, crustal abundance, and high theoretical energy density. However, its development faces challenges due to slow reaction kinetics and poor reversibility. The creation of a multifunctional cathode material that can both adsorb polysulfides and accelerate their conversion is key to advancing ASB. Herein, a composite composed of polyoxometalate nanohybridization-derived Mo2 C and N-doped carbon nanotube-interwoven polyhedrons (Co/Mo2 C@NCNHP) is proposed for the first time as an electrochemical catalyst in the sulfur cathode. This composite improves the utilization and conductivity of sulfur within the cathode. DFT calculations and experimental results indicate that Co enables the chemisorption of polysulfides while Mo2 C catalyzes the reduction reaction of long-chain polysulfides. X-ray photoelectron spectroscopy (XPS) and in situ UV analysis reveal the different intermediates of Al polysulfide species in Co/Mo2 C@NCNHP during discharging/charging. As a cathode material for ASB, Co/Mo2 C@NCNHP@S composite can deliver a discharge-charge voltage hysteresis of 0.75 V with a specific capacity of 370 mAh g-1 after 200 cycles at 1A g-1 .
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Affiliation(s)
- Qiuping Zhou
- School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou, 225002, P. R. China
| | - Xuecheng Zhang
- School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou, 225002, P. R. China
| | - Yuchao Wu
- School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou, 225002, P. R. China
| | - Xinyuan Jiang
- School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou, 225002, P. R. China
| | - Tangsuo Li
- School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou, 225002, P. R. China
| | - Ming Chen
- School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou, 225002, P. R. China
| | - Lubin Ni
- School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou, 225002, P. R. China
| | - Guowang Diao
- School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou, 225002, P. R. China
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He YZ, Zhou Q, Deng WY, Huang LY, Lu YY, Ruan YY, Du H. Clinical characteristics and prognostic factors of surgical treatment in children with brainstem tumor. Eur Rev Med Pharmacol Sci 2023; 27:10926-10934. [PMID: 38039022 DOI: 10.26355/eurrev_202311_34460] [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: 12/02/2023]
Abstract
OBJECTIVE Brainstem tumors present a significant challenge in surgical treatment, and the prognostic factors in children are lacking. This study aimed to investigate clinical characteristics and prognostic factors of surgical treatment in children with brainstem tumors. PATIENTS AND METHODS 50 children with brainstem tumors who underwent surgical treatment, including frameless- or frame-based stereotactic biopsy and resection, were included and followed up for clinical and biological analysis. Factors of outcomes were assessed by univariate and multivariate analysis. RESULTS 27 cases (54.0%) underwent resection in all children with brainstem tumors. The rate of resection reached as high as 81.8% in children with non-diffuse intrinsic pontine glioma (DIPG), while in children with DIPG, biopsy was performed in the majority, and resection was obtained in the minority with focal necrosis. A rare complication was found following the surgery. Multivariate analysis considered World Health Organization (WHO) grade 3-4, with hazard ratio (HR)=4.48, 95% confidence interval (CI) of 2.84-8.69, p=0.001, H3K27M mutation (HR=2.50, 95% CI 1.73-5.69, p=0.015), and hydrocephalus (HR=2.17, 95% CI 1.08-5.32, p=0.014) as independent adverse prognostic factors. For Kaplan-Meier analysis, children with WHO grade 3-4, Ki-67 LI ≥ 20%, TP53 mutation, H3K27M mutation, DIPG, and hydrocephalus had significantly decreased overall survival (OS). CONCLUSIONS A high rate of resection has been obtained in non-DIPG, and surgical intervention is remarkably safe and efficient for children with brainstem tumors. WHO grade 3-4, H3K27M mutation, and hydrocephalus indicate poor prognosis in children with brainstem tumors.
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Affiliation(s)
- Y-Z He
- Department of Neurosurgery, Wuhan Children's Hospital (Wuhan Maternal and Child Healthcare Hospital), Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
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Shinozaki K, Yu PJ, Zhou Q, Cassiere HA, John S, Rolston DM, Garg N, Li T, Johnson J, Saeki K, Goto T, Okuma Y, Miyara SJ, Hayashida K, Aoki T, Wong VK, Molmenti EP, Lampe JW, Becker LB. Continuous and repeat metabolic measurements compared between post-cardiothoracic surgery and critical care patients. BMC Pulm Med 2023; 23:390. [PMID: 37840131 PMCID: PMC10577926 DOI: 10.1186/s12890-023-02657-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2022] [Accepted: 09/13/2023] [Indexed: 10/17/2023] Open
Abstract
OBJECTIVE Using a system, which accuracy is equivalent to the gold standard Douglas Bag (DB) technique for measuring oxygen consumption (VO2), carbon dioxide generation (VCO2), and respiratory quotient (RQ), we aimed to continuously measure these metabolic indicators and compare the values between post-cardiothoracic surgery and critical care patients. METHODS This was a prospective, observational study conducted at a suburban, quaternary care teaching hospital. Age 18 years or older patients who underwent mechanical ventilation were enrolled. RESULTS We included 4 post-surgery and 6 critical care patients. Of those, 3 critical care patients died. The longest measurement reached to 12 h and 15 min and 50 cycles of repeat measurements were performed. VO2 of the post-surgery patients were 234 ± 14, 262 ± 27, 212 ± 16, and 192 ± 20 mL/min, and those of critical care patients were 122 ± 20, 189 ± 9, 191 ± 7, 191 ± 24, 212 ± 12, and 135 ± 21 mL/min, respectively. The value of VO2 was more variable in the post-surgery patients and the range of each patient was 44, 126, 71, and 67, respectively. SOFA scores were higher in non-survivors and there were negative correlations of RQ with SOFA. CONCLUSIONS We developed an accurate system that enables continuous and repeat measurements of VO2, VCO2, and RQ. Critical care patients may have less activity in metabolism represented by less variable values of VO2 and VCO2 over time as compared to those of post-cardiothoracic surgery patients. Additionally, an alteration of these values may mean a systemic distinction of the metabolism of critically ill patients.
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Affiliation(s)
- Koichiro Shinozaki
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA.
- Department of Emergency Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA.
- Department of Emergency Medicine, North Shore University Hospital, Manhasset, NY, USA.
- Department of Emergency Medicine, Kindai University Faculty of Medicine, Osaka-Sayama, Osaka, Japan.
| | - Pey-Jen Yu
- Department of Cardiothoracic Surgery, North Shore University Hospital, Manhasset, NY, USA
| | - Qiuping Zhou
- Division of Critical Care Medicine of Emergency Medicine, Long Island Jewish Medical Center, New Hyde Park, NY, USA
| | - Hugh A Cassiere
- Division of Critical Care Medicine, Department of Medicine, North Shore University Hospital, Manhasset, NY, USA
| | - Stanley John
- Division of Critical Care Medicine, Department of Medicine, North Shore University Hospital, Manhasset, NY, USA
| | - Daniel M Rolston
- Department of Emergency Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Emergency Medicine, North Shore University Hospital, Manhasset, NY, USA
| | - Nidhi Garg
- Department of Emergency Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Emergency Medicine, South Shore University Hospital, Bay Shore, NY, USA
| | - Timmy Li
- Department of Emergency Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Jennifer Johnson
- Department of Emergency Medicine, North Shore University Hospital, Manhasset, NY, USA
| | - Kota Saeki
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Nihon Kohden Innovation Center, Cambridge, MA, USA
| | | | - Yu Okuma
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Santiago J Miyara
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Kei Hayashida
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Tomoaki Aoki
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Vanessa K Wong
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
| | - Ernesto P Molmenti
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Department of Surgery, Medicine, and Pediatrics, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
| | - Joshua W Lampe
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- ZOLL Medical, Chelmsford, MA, USA
| | - Lance B Becker
- The Feinstein Institutes for Medical Research, Northwell Health, Manhasset, NY, USA
- Department of Emergency Medicine, Zucker School of Medicine at Hofstra/Northwell, Hempstead, NY, USA
- Department of Emergency Medicine, North Shore University Hospital, Manhasset, NY, USA
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Liu X, Li ZR, Qi X, Zhou Q. Objective Boundary Generation for Gross Target Volume and Organs at Risk Using 3D Multi-Modal Medical Images. Int J Radiat Oncol Biol Phys 2023; 117:e476. [PMID: 37785510 DOI: 10.1016/j.ijrobp.2023.06.1689] [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) Accurate delineation of Gross Target Volume (GTV) and Organs at Risk (OARs) in medical images is an essential but challenging step in radiotherapy. Deep-learning based automated delineation methods, which learn from manual annotations, are currently prevalent in academic research. However, the limited resolution of medical images and the fuzzy boundaries of lesions and organs present a challenge to the precision of manual annotations. By leveraging the complementary information from multi-modal medical images, this study proposed a novel method to generate objective boundaries of GTV and OARs. MATERIALS/METHODS We present a novel method of objective boundary generation, inspired by image matting primarily used for 2D RGB natural images, to process 3D grayscale medical images. The proposed method has the following advantages. 1) It allows for flexible input modalities and assigns weights to each modality according to their relative significance when computing information flows in the matting algorithm. 2) It computes 3D spatial information flow among voxels, which has more advantages over its 2D counterpart. 3) It has a closed-form solution that generates deterministic results. To evaluate the characteristics of the generated boundaries, patients with stage I nasopharyngeal carcinoma (NPC) were studied, with CT images and multi-modal MR images (T1, T1C, T2) aligned using deformable registration. Region of Interests (ROIs), i.e., GTV and parotid gland, were used, with a rough trimap marking extremely few foreground voxels, many background voxels, and a large unknown region. The proposed algorithm leverages the connection between each voxel and its nearest neighbors in the feature space, to propagate the opacity information. RESULTS We evaluated the results by employing both qualitative and quantitative methods. Using qualitative evaluation, experienced clinicians confirmed that the results were in agreement with the input data, especially for areas where borders were visible in most modalities (e.g., between air and tumor). For more challenging regions, where boundaries were unclear in the images, the results displayed fine-grained opacity transitions indicating the confidence of each voxel belonging to the ROI. When compared to the delineations made by clinicians, we found our results are usually more compact. We define a precision metric that evaluates the ratio of the matted foreground inside clinicians' delineations versus the entire matted foreground. Using a threshold of 0.4, our binarized result scored 0.95 for GTV and 0.92 for parotid gland. CONCLUSION The proposed method demonstrated satisfactory results on challenging ROIs. The objective boundaries generated by this method have advantages in many aspects, including improvement of delineation protocols, enhancement of manual annotation consistency, and increase of deep-learning based automated delineation accuracy.
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Affiliation(s)
- X Liu
- Manteia Technologies Co., Ltd, Xiamen, Fujian, China
| | - Z R Li
- Manteia Technologies Co., Ltd, Xiamen, Fujian, China
| | - X Qi
- Dept. of Radiation Oncology, UCLA, Los Angeles, CA
| | - Q Zhou
- Manteia Technologies Co., Ltd, Xiamen, Fujian, China
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Kong L, Li Z, Liu Y, Zhang J, Chen M, Zhou Q, Qi X, Deng XW, Peng Y. A Generalized Deep Learning Method for Synthetic CT Generation. Int J Radiat Oncol Biol Phys 2023; 117:e472. [PMID: 37785502 DOI: 10.1016/j.ijrobp.2023.06.1681] [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) The application of deep learning to generate synthetic CT (sCT) has been widely studied in radiotherapy. Existing methods generally involve data from two different image modalities, such as CBCT-CT or MRI-CT, the quality of sCT is adversely affected by source image quality. We propose a unique method of synthesizing MRI and CBCT into sCT based on single-modal CT for training, and call it SmGAN. MATERIALS/METHODS We used planning CT of a group of 35 head and neck cases to as training data. We then applied two different spatial transformations to the planning CT image to produce the transformed CT1 and CT2. And We used a random style enhancement technique (Shuffle Remap) to modify the image distribution of CT1 which we termed CT1+E. CT1+E was used to simulate the patient's "image of the day" while CT2 to simulate the "planning image". After feeding both CT1+E and CT2 into the generator, we obtained the sCT predicted by the generator. The generator was trained using the Mean Absolute Error (MAE) loss between sCT and CT1. In the actual clinical process, we use the patient's CBCT or MRI instead of CT1+E and the patient's planning CT instead of CT2 as the input of the generator. After processing, we get an sCT that can maintain the spatial position of the image taken on the day, while presenting features similar to the planning CT. The evaluation data we have includes 10 pairs of MRI-Def_CT and 10 pairs of CBCT-Def_CT Head and Neck patients. Def_CT is obtained from the planning CT based on the spatial position deformation of MRI and CBCT. To evaluate the accuracy of sCT based on MRI and CBCT with Def CT, we use a range of metrics, including Hounsfield Unit (HU) difference, peak signal-to-noise ratio (PSNR), structural similarity (SSIM) and gamma pass rate. All results will be benchmarks against the advanced method RegGAN for comparison. RESULTS Compared to RegGAN, the results of SmGAN were significantly better. The mean absolute errors within the body were (44.7±216.2 HU vs. 36.7±131.4 HU) and (64.9±123.7 HU vs. 58.2±152.8 HU) for the CBCT-SCT and MRI-SCT, respectively (Table 1). In addition, experimental results show that SmGAN also outperforms RegGAN in dose calculation accuracy. For example, under the 10% threshold, SmGAN's gamma pass rate of 1mm and 1% is 0.926±0.02, compared with gamma rate of 0.896±0.02 for RegGAN. CONCLUSION We proposed a generalized deep learning model for synthetic CT generation, based on CBCT or MRI images. The proposed algorithm achieved high accuracy of dosimetric metrics, as well as excellent IMRT QA verification results. Compared to other existing synthetic CT generation methods, the proposed SmGAN required a single-modal image for training, which is considered as a major breakthrough in the industry, and is expected to have wide spread of clinical applications.
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Affiliation(s)
- L Kong
- Manteia Technologies Co., Ltd, Xiamen, 361001, People's Republic of China, Xiamen, Fujian, China
| | - Z Li
- Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, Jinan, China
| | - Y Liu
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - J Zhang
- State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Sun Yat-sen University Cancer Center, Guangzhou, China
| | - M Chen
- Department of Radiation Oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangdong Key Laboratory of Nasopharyngeal Carcinoma Diagnosis and Therapy, Guangzhou, China
| | - Q Zhou
- Manteia Technologies Co., Ltd., Xiamen, China
| | - X Qi
- Dept. of Radiation Oncology, UCLA, Los Angeles, CA
| | - X W Deng
- Department of Radiation Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China
| | - Y Peng
- Department of Radiation Oncology, Sun Yat-Sen University Cancer Center, Guangzhou, China
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Liu Y, Chen Z, Zhou Q, Shang X, Zhao W, Zhang G, Xu S. A Feasibility Study of Dose Band Prediction in Radiotherapy: Predicting a Dose Spectrum. Int J Radiat Oncol Biol Phys 2023; 117:e691. [PMID: 37786031 DOI: 10.1016/j.ijrobp.2023.06.2164] [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) Current deep learning-based dose prediction methods can only predict a specific dose distribution. If the predicted dose is inaccurate, no more options can be selected. We proposed a novel dose prediction method named dose band prediction, which outcomes a spectrum of predicted dose distribution for planning and quality assurance (QA). MATERIALS/METHODS Upper-Band and Lower-Band losses were involved in 3D convolution neural networks to establish the Upper-Band Network (UBN) and Lower-Band Network (LBN). Each voxel's ideal dose spectrum (dose band) was defined by the maximum/minimum rational dose predicted by UBN/LBN. 130 NPC cases with Tomotherapy (dataset 1), 49 cervix cases with IMRT (dataset 2) and 43 cervix cases with VMAT (dataset 3) were enrolled to establish and evaluate our dose band prediction method. RESULTS The dose band prediction method can successfully predict a spectrum of doses. Upper-Band/Lower-Band presents maximum/minimum rational dose; Middle-Line presents the average of Upper-Band and Lower-Band. The clinical implement dose was used as the reference dose. We evaluated the maximum interval between the reference and Upper-Band/Middle-Line/Lower-Band doses, and the percentage dose difference was used as the evaluation method. The differences in PTV for Upper-Band, Middle-Line and Lower-Band in dataset 1 were within 2.47%, 0.54%, and 2.8%; in dataset 2, they were within 0.37%, 1.15%, and 2.69%; in dataset 3, they were within 0.96%, 0.35%, and 1.66%. The mean difference of OARs for the Upper-Band, Middle-Line and Lower-Band in dataset 1 were within 8.13%, 4.97%, and 8.19%; in dataset 2, they were within 8.8%, 4.48%, and 5.52%; in dataset 3, they were within 4.01%, 3.13%, and 5.79% (shown in Table 1). CONCLUSION Dose Band prediction achieved high-accuracy dose prediction by the Middle-Line. More importantly, the Upper-Band/Lower-Band provided a spectrum of possible rational doses. Our Dose Band prediction method is based on a specific loss function, so it can easily be applied in various network and patient cases. Dose Band prediction towards a more robust plan QA and planning assistance. Table 1. The maximum interval of doses (percentage dose difference, %).
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Affiliation(s)
- Y Liu
- School of physics, Beijing University, Beijing, China; Department of Radiation Oncology, PLA General Hospital, Beijing, China
| | - Z Chen
- Manteia Technologies Co., Ltd, Xiamen, China
| | - Q Zhou
- Manteia Technologies Co., Ltd, Xiamen, China
| | - X Shang
- School of physics, Beijing University, Beijing, China; Department of Radiation Oncology, PLA General Hospital, Beijing, China
| | - W Zhao
- School of physics, Beijing University, Beijing, China
| | - G Zhang
- School of physics, Beijing University, Beijing, China
| | - S Xu
- National Cancer Center/National Clinical Research Center for Cancer/Hebei Cancer Hospital, Chinese Academy of Medical Sciences, Hebei, China; National Cancer Center/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China
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Li ZR, Weidhaas JB, Raldow A, Zhou Q, Qi X. Early Prediction of Radiation Treatment Response via Longitudinal Analysis of CBCT Radiomic Features for Locally Advanced Rectal Cancer. Int J Radiat Oncol Biol Phys 2023; 117:e474-e475. [PMID: 37785506 DOI: 10.1016/j.ijrobp.2023.06.1686] [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) Patients respond to the same radiation treatment course differently due to inter- and intra- patient variability in radiosensitivity. Despite widespread use of AI/ML in radiation oncology, there is a lack of monitoring strategies used during treatment courses to evaluate early predictors of treatment response in a systematic fashion. This work advances a straightforward, yet effective, method for the early detection of treatment response through systematically analyzing daily CBCT radiomic features. The goal is to aid clinicians in assessing the treatment efficacy routinely with a view towards optimizing personalized treatment. MATERIALS/METHODS We included a cohort of 30 patients diagnosed with locally advanced rectal cancer who underwent neo-adjuvant fractionated radiation treatment (RT) with a prescription dose of 50.4 Gy (28 fractions), followed by total mesorectal excision surgery after completion of ChemoRT. Daily IGRT imaging was acquired prior to each fraction resulting in a total of 840 CBCTs. Patients were divided into responder (14 patients) and non-responder (16 patients) groups based on post-RT pathological response. Mutual information algorithms were utilized to rigorously register daily CBCT images to the planning CT, and longitudinal radiomic features of the target were extracted from the daily CBCTs during the entire treatment course. All longitudinal features for a given patient were standardized with Z-Score normalization, followed by linear fitting using the least square method, resulting in radiomic feature trends (RFT) represented by slope values. Statistical significance was established via a two-sample U test and P-value with a threshold of 0.05. Logistic regression was performed to eliminate RFT with accuracy rates lower than 0.5. The final trending model was developed using random forest. For each patient at fraction N, our investigation involved independent 27 group experiments, where each experiment considered image group from fraction #1 to N, to confirm the effectiveness and stability of the model. RESULTS The proposed RFT demonstrated a high level of precision and consistency for post-RT response based on longitudinal CBCT images for LARC patients. The trending model yielded an accuracy of 0.9556, 95% CI (0.94, 0.972) when each daily image was considered, the prediction consistency was 0.964. Given the first 14 experiments (considering group images of fraction #1-15), the prediction accuracy was 0.9357, 95% CI (0.915, 0.956) and the prediction consistency was 0.952. CONCLUSION A strategy for monitoring and early prediction of LARC patients' radioresponse was evaluated via longitudinal CBCT assessment. Our trending models demonstrate a significant difference between the responder vs non-responder groups as early as the 15th fraction. Our strategy achieved superior accuracy and consistency to predict post-RT response of LARC patients.
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Affiliation(s)
- Z R Li
- Manteia Technologies Co., Ltd, Xiamen, Fujian, China
| | - J B Weidhaas
- Department of Radiation Oncology, UCLA, Los Angeles, CA
| | - A Raldow
- Department of Radiation Oncology, University of California, Los Angeles, Los Angeles, CA
| | - Q Zhou
- Manteia Technologies Co., Ltd, Xiamen, Fujian, China
| | - X Qi
- Dept. of Radiation Oncology, UCLA, Los Angeles, CA
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Wang J, He Q, Li ZR, Huang N, Huang R, Wang JY, Zhou Q, Wang XH, Han F. The Lyman Normal Tissue Complication Probability Model and Risk Prediction for Temporal Lobe Injury after Re-Irradiation in Patients with Recurrent Nasopharyngeal Carcinoma. Int J Radiat Oncol Biol Phys 2023; 117:e587. [PMID: 37785777 DOI: 10.1016/j.ijrobp.2023.06.1932] [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) The risk of temporal lobe injury (TLI) in recurrent nasopharyngeal carcinoma (rNPC) patients with intensity-modulated radiation therapy (IMRT) is high. We aimed to construct the normal tissue complication probability (NTCP) model for TLI of rNPC and establish a risk predictive model. MATERIALS/METHODS We retrospectively analyzed 103 patients with rNPC who had received two courses of IMRT in our institution. The 206 temporal lobes (TLs) of these patients were randomly divided into a training (n = 144) and validation group (n = 62). We determined the mean value of the following parameters to construct the Lyman NTCP model: TD50(1) (the dose with a 50% probability of complications to an organ when all volumes are irradiated), m [steepness of the dose-response at TD50(1)], and n (the parameter related to volume effect). The most predictive dosimetric parameter and clinical variables were integrated in Cox proportional hazards models. A nomogram was developed for predicting risk of TLs. RESULTS The parameters of the fitted NTCP model were TD50(1) = 107.84 Gy (95% confidence interval (CI), [97.15, 118.54]), m = 0.16 (95% CI, [0.14, 0.19]), and n = 0.04 (95% CI, [0.01, 0.06]). The cumulative dose delivered to 0.1 cm3 of temporal lobe volume (D0.1cc-c) was the most predictive dosimetric parameter for TLI. The Kaplan-Meier curves showed a significant difference in 2-year TLI-free survival among different risk groups according to the total score of nomograms. CONCLUSION The TD50(1) of TLI in patients with rNPC is 107.84 Gy in Lyman NTCP model. The nomogram model can accurately predict the risk of TLI for individual.
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Affiliation(s)
- J Wang
- Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - Q He
- Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - Z R Li
- Manteia Technologies Co., Ltd, Xiamen, Fujian, China
| | - N Huang
- Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - R Huang
- Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - J Y Wang
- Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - Q Zhou
- Manteia Technologies Co., Ltd, Xiamen, Fujian, China
| | - X H Wang
- Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
| | - F Han
- Sun Yat-sen University Cancer Center, Guangzhou, Guangdong, China
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Du L, Lei Q, Zhou Q, Du Y, Lin X, Guo J, Li C, Luo Q, Fan C, Guo Q. Effect of MTA3 Inhibition of Glutamine Synthetase-Mediated Glutaminolysis on Radiosensitivity of Patients with Esophageal Cancer. Int J Radiat Oncol Biol Phys 2023; 117:e227-e228. [PMID: 37784918 DOI: 10.1016/j.ijrobp.2023.06.1138] [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) Metastasis-associated protein 3 (MTA3) can serve as a tumor suppressor in many cancer types. However, the role of MTA3 in radiosensitivity of patients with esophageal squamous cell cancer (ESCC) remains unclear. We thus investigated the function of MTA3 in radiosensitivity for ESCC, one of the most common digestive cancers. MATERIALS/METHODS The colony formation assay and nude mice xenograft tumor assay were performed to investigate the effect of MTA3 on radiosensitivity in ESCC. Glutamine consumption assay kit and glutamate production assay kit were used to assess the glutaminolysis. Glutaminase (GLS) Activity Assay Kit and Glutamine Synthetase (GS) Activity Assay Kit were used to analyze the activity of specific metabolic enzymes dominate glutaminolysis. The regulatory mechanism of glutaminolysis by MTA3 was confirmed using Chromatin immunoprecipitation assay and Gaussia luciferase assay. The expression levels of MTA3 and GS in ESCC primary tissues were evaluated using immunohistochemistry. Survival curves were plotted with the Kaplan-Meier method and compared by log-rank test. RESULTS The colony formation assay showed that MTA3 depletion and overexpression caused significantly higher and lower clonogenic survival after different doses of irradiation (IR), respectively. When these cells were subcutaneously injected into nude mice, the tumors derived from the cells with MTA3 overexpression and MTA3 knockdown were significantly smaller and bigger after IR, respectively. These findings suggest that MTA3 can enhance radiosensitivity in vitro and in vivo. Meanwhile, overexpressed and knockdown MTA3 can repress and expedite glutamine consumption and glutamate production uniformly, respectively. To determine how MTA3 acts on glutaminolysis, the activity of two specific metabolic enzymes dominate this metabolism, GS and GLS, were evaluated. It found that overexpressed and knockdown MTA3 can restrain and enhance the activity of GS, respectively, but have less effect on GLS. Moreover, the decreased radiosensitivity mediated by MTA3 knockdown is significantly increased when treated with GS inhibitor, suggesting that GS plays a crucial role in MTA3-mediated radiosensitivity enhancement. Mechanistically, Chromatin immunoprecipitation assay and Gaussia luciferase assay showed that MTA3 was recruited to the promoter of GS and suppressed GS transcription. However, knockdown of GATA3 abolished MTA3's repressive effect on GS and inhibited the MTA3's occupation on the promoter region of GS. These results collectively demonstrated that, in ESCC cells, MTA3 is recruited by GATA3 to inhibit GS expression, then ultimately represses glutaminolysis and enhances radiosensitivity. Finally, we showed that the ESCC patients in the MTA3low/GShigh group is significantly associated with shorter overall survival. CONCLUSION MTA3 is capable of enhancing radiosensitivity through downregulating GS and MTA3low/GShigh might be a potential prognostic factor for ESCC patients.
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Affiliation(s)
- L Du
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Q Lei
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Q Zhou
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Y Du
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - X Lin
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - J Guo
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - C Li
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Q Luo
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - C Fan
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
| | - Q Guo
- Department of Radiation Oncology, Chongqing University Cancer Hospital, Chongqing, China
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Zhang W, Ma Y, Ibrahim G, Qi X, Zhou Q. Unsupervised Domain Adaptation of Auto-Segmentation on Multi-Source MRIs. Int J Radiat Oncol Biol Phys 2023; 117:e497. [PMID: 37785564 DOI: 10.1016/j.ijrobp.2023.06.1736] [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) Deep learning has achieved great success in medical image segmentation. Most existing deep learning (DL) approaches make no adjustments to the model prior to inference. These models can perform well on the data of the same distribution, but their performance usually degrades when applied to the images from different source, i.e., different scanners. To tackle the problem caused by domain shift, we proposed an unsupervised domain adaptation (UDA) method based on entropy minimization and physical consistency constraints. MATERIALS/METHODS The proposed method combines feature-level and instance-level domain adaptation techniques to transfer knowledge from the source to the target domain. Specifically, the feature-level adaptation technique uses a graph-based entropy minimization to reduce the discrepancy between the source and target domains. The instance-level adaptation technique employs a novel consistency loss to regularize the physical consistency of the same object, such as volume, length, and centroid, thus improving the segmentation accuracy of the target domain. A collection of 93 abdominal MR images, comprising 45 cases from a 0.35T MRI scanner (TRUFI) and 48 cases from a 1.5T MRI scanner (T2), was utilized to evaluate the effectiveness of the proposed method. The contours of 6 organs-at-risk were delineated by a senior radiation oncologist, serving as the ground truth. Three models, the source model (SRC) trained on the source domain, the target model (TGT) trained on the target domain, and the UDA model adapted from the source domain to the target domain, were compared on the target domain using the Dice Similarity Coefficient (DSC). RESULTS In the experiment of 0.35T-to-1.5T, the proposed UDA method outperformed the source model, achieving an average DSC score of 0.82 ± 0.11, compared to 0.58 ± 0.23 (SRC) and 0.85 ± 0.09 (TGT), respectively. In the inverse experiment 1.5T-to-0.35T, the UDA model achieved an average DSC score of 0.79±0.13, compared to DSCs of 0.52 ± 0.25 and 0.81 ± 0.11 for the SRC and TGT respectively. The UDA method yielded a significant improvement of 46%, compared to the SRC. Particularly, OARs (organ at risk) with higher deformability such as the stomach and duodenum achieved a 58% and 63% improvement in performance, respectively. CONCLUSION This work presents a compelling approach of UDA for auto-segmentation on multi-source MRIs. Experimental results demonstrate that the UDA effectively improve the segmentation performance of the source model in the target domain, resulting in a more robust segmentation model.
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Affiliation(s)
- W Zhang
- Manteia Technologies Co., Ltd., Xiamen, China
| | - Y Ma
- Manteia Technologies Co., Ltd., Xiamen, China
| | - G Ibrahim
- Dept. of Radiation Oncology, UCLA, Los Angeles, CA
| | - X Qi
- Dept. of Radiation Oncology, UCLA, Los Angeles, CA
| | - Q Zhou
- Manteia Technologies Co., Ltd., Xiamen, China
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Liu N, Zhou Q, Wang H, Li Q, Chen Z, Lin Y, Yi L, Jiang S, Chen C, Deng Y. MiRNA-338-3p Inhibits Neuroinflammation in the Corpus Callosum of LCV-LPS Rats Via STAT1 Signal Pathway. Cell Mol Neurobiol 2023; 43:3669-3692. [PMID: 37479855 DOI: 10.1007/s10571-023-01378-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] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/14/2023] [Accepted: 06/20/2023] [Indexed: 07/23/2023]
Abstract
Neuroinflammation is a common characteristic of intracranial infection (ICI), which is associated with the activation of astrocytes and microglia. MiRNAs are involved in the process of neuroinflammation. This study aimed to investigate the potential mechanism by which miR-338-3p negatively modulate the occurrence of neuroinflammation. We here reported that the decreased levels of miR-338-3p were detected using qRT-PCR and the upregulated expression of TNF-α and IL-1β was measured by ELISA in the cerebrospinal fluid (CSF) in patients with ICI. A negative association between miR-338-3p and TNF-α or IL-1β was revealed by Pearson correlation analysis. Sprague-Dawley (SD) rats were injected with LPS (50 μg) into left cerebral ventricule (LCV), following which the increased expression of TNF-α and IL-1β and the reduction of miR-338-3p expression were observed in the corpus callosum (CC). Moreover, the expression of TNF-α and IL-1β in the astrocytes and microglia in the CC of LCV-LPS rats were saliently inhibited by the overexpression of miR-338-3p. In vitro, cultured astrocytes and BV2 cells transfected with mimic-miR-338-3p produced less TNF-α and IL-1β after LPS administration. Direct interaction between miR-338-3p and STAT1 mRNA was validated by biological information analysis and dual luciferase assay. Furthermore, STAT1 pathway was found to be implicated in inhibition of neuroinflammation induced by mimic miR-338-3p in the astrocytes and BV2 cells. Taken together, our results suggest that miR-338-3p suppress the generation of proinflammatory mediators in astrocyte and BV2 cells induced by LPS exposure through the STAT1 signal pathway. MiR-338-3p could act as a potential therapeutic strategy to reduce the neuroinflammatory response. Diagram describing the cellular and molecular mechanisms associated with LPS-induced neuroinflammation via the miR-338-3p/STAT1 pathway. LPS binds to TLRs on astrocytes or microglia to activate the STAT1 pathway and upregulate the production of pro-inflammatory cytokines. However, miR-338-3p inhibits the expression of STAT1 and reduces the production of inflammatory mediators.
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Affiliation(s)
- Nan Liu
- School of Medicine, South China University of Technology, Guangzhou, 510006, China
- Department of Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, 510080, China
| | - Qiuping Zhou
- School of Medicine, South China University of Technology, Guangzhou, 510006, China
- Department of Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, 510080, China
| | - Huifang Wang
- Department of Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, 510080, China
| | - Qian Li
- Department of Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, 510080, China
- Southern Medical University, Guangzhou, 510515, China
| | - Zhuo Chen
- School of Medicine, South China University of Technology, Guangzhou, 510006, China
- Department of Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, 510080, China
| | - Yiyan Lin
- Department of Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, 510080, China
- Southern Medical University, Guangzhou, 510515, China
| | - Lingling Yi
- School of Medicine, South China University of Technology, Guangzhou, 510006, China
- Department of Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, 510080, China
| | - Shuqi Jiang
- Department of Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, 510080, China
| | - Chunbo Chen
- School of Medicine, South China University of Technology, Guangzhou, 510006, China.
- Department of Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, 510080, China.
| | - Yiyu Deng
- School of Medicine, South China University of Technology, Guangzhou, 510006, China.
- Department of Critical Care Medicine, Guangdong Provincial People's Hospital (Guangdong Academy of Medical Sciences) Southern Medical University, Guangzhou, 510080, China.
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29
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Wu Y, Wu N, Jiang X, Duan S, Li T, Zhou Q, Chen M, Diao G, Wu Z, Ni L. Bifunctional K 3PW 12O 40/Graphene Oxide-Modified Separator for Inhibiting Polysulfide Diffusion and Stabilizing Lithium Anode. Inorg Chem 2023; 62:15440-15449. [PMID: 37700509 DOI: 10.1021/acs.inorgchem.3c01720] [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: 09/14/2023]
Abstract
Lithium-sulfur (Li-S) batteries are considered as promising candidates for next-generation batteries due to their high theoretical energy density. However, the practical application of Li-S batteries is still hindered by several challenges, such as the polysulfide shuttle and the growth of lithium dendrites. Herein, we introduce a bifunctional K3PW12O40/graphene oxide-modified polypropylene separator (KPW/GO/PP) as a highly effective solution for mitigating polysulfide diffusion and protecting the lithium anode in Li-S batteries. By incorporating KPW into a densely stacked nanostructured graphene oxide (GO) barrier membrane, we synergistically capture and rapidly convert lithium polysulfides (LiPSs) electrochemically, thus effectively suppressing the shuttling effect. Moreover, the KPW/GO/PP separator can stabilize the lithium metal anode during cycling, suppress dendrite formation, and ensure a smooth and dense lithium metal surface, owing to regulated Li+ flux and uniform Li nucleation. Consequently, the constructed KPW/GO/PP separator delivered a favorable initial specific capacity (1006 mAh g-1) and remarkable cycling performance at 1.0 C (626 mAh g-1 for up to 500 cycles with a decay rate of 0.075% per cycle).
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Affiliation(s)
- Yuchao Wu
- School of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou, Jiangsu 225002, People's Republic of China
| | - Ni Wu
- School of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou, Jiangsu 225002, People's Republic of China
| | - Xinyuan Jiang
- School of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou, Jiangsu 225002, People's Republic of China
| | - Suqin Duan
- School of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou, Jiangsu 225002, People's Republic of China
| | - Tangsuo Li
- School of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou, Jiangsu 225002, People's Republic of China
| | - Qiuping Zhou
- School of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou, Jiangsu 225002, People's Republic of China
| | - Ming Chen
- School of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou, Jiangsu 225002, People's Republic of China
| | - Guowang Diao
- School of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou, Jiangsu 225002, People's Republic of China
| | - Zhen Wu
- School of Energy and Power Engineering, Jiangsu University, Zhenjiang 212013, People's Republic of China
| | - Lubin Ni
- School of Chemistry and Chemical Engineering, Yangzhou University, Yangzhou, Jiangsu 225002, People's Republic of China
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30
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Ablikim M, Achasov MN, Adlarson P, Ahmed S, Albrecht M, Aliberti R, Amoroso A, An Q, Bai Y, Bakina O, Ferroli RB, Balossino I, Ban Y, Begzsuren K, Berger N, Bertani M, Bettoni D, Bianchi F, Bloms J, Bortone A, Boyko I, Briere RA, Cai H, Cai X, Calcaterra A, Cao GF, Cao N, Cetin SA, Chang JF, Chang WL, Chelkov G, Chen G, Chen HS, Chen ML, Chen SJ, Chen XR, Chen YB, Chen ZJ, Cheng WS, Cibinetto G, Cossio F, Dai HL, Dai JP, Dai XC, Dbeyssi A, de Boer RE, Dedovich D, Deng ZY, Denig A, Denysenko I, Destefanis M, De Mori F, Ding Y, Dong J, Dong LY, Dong MY, Dong X, Du SX, Fang J, Fang SS, Fang Y, Farinelli R, Fava L, Feldbauer F, Felici G, Feng CQ, Fritsch M, Fu CD, Gao YN, Gao Y, Gao Y, Garzia I, Gersabeck EM, Gilman A, Goetzen K, Gong L, Gong WX, Gradl W, Greco M, Gu LM, Gu MH, Gu S, Gu YT, Guan CY, Guo AQ, Guo LB, Guo RP, Guo YP, Guskov A, Han TT, Hao XQ, Harris FA, He KL, Heinsius FHH, Heinz CH, Heng YK, Herold C, Himmelreich M, Holtmann T, Hou YR, Hou ZL, Hu HM, Hu JF, Hu T, Hu Y, Huang GS, Huang LQ, Huang XT, Huang YP, Hussain T, Imoehl W, Irshad M, Jaeger S, Janchiv S, Ji Q, Ji QP, Ji XB, Ji XL, Jiang XS, Jiao JB, Jiao Z, Jin S, Jin Y, Johansson T, Kalantar-Nayestanaki N, Kang XS, Kappert R, Kavatsyuk M, Ke BC, Keshk IK, Khoukaz A, Kiese P, Kiuchi R, Kliemt R, Kolcu OB, Kopf B, Kuemmel M, Kuessner MK, Kupsc A, Kurth MG, Kühn W, Lane JJ, Larin P, Lavania A, Lavezzi L, Lei ZH, Leithoff H, Lellmann M, Lenz T, Li C, Li CH, Li C, Li DM, Li F, Li G, Li H, Li HB, Li HJ, Li JQ, Li JW, Li K, Li LK, Li L, Li PL, Li PR, Li SY, Li WD, Li WG, Li XH, Li XL, Li ZY, Liang H, Liang H, Liang H, Liang YF, Liang YT, Liao GR, Liao LZ, Libby J, Limphirat A, Liu BJ, Liu CX, Liu D, Liu FH, Liu F, Liu F, Liu HB, Liu HM, Liu H, Liu H, Liu JB, Liu JY, Liu K, Liu KY, Liu L, Liu MH, Liu Q, Liu SB, Liu S, Liu T, Liu WM, Liu X, Liu YB, Liu ZA, Liu ZQ, Lou XC, Lu FX, Lu HJ, Lu JD, Lu JG, Lu XL, Lu Y, Lu YP, Luo CL, Luo MX, Luo T, Luo XL, Lusso S, Lyu XR, Ma FC, Ma HL, Ma LL, Ma MM, Ma QM, Ma RQ, Ma RT, Ma XX, Ma XY, Maas FE, Maggiora M, Maldaner S, Malde S, Malik QA, Mangoni A, Mao YJ, Mao ZP, Marcello S, Meng ZX, Messchendorp JG, Mezzadri G, Min TJ, Mitchell RE, Mo XH, Muchnoi NY, Muramatsu H, Nakhoul S, Nefedov Y, Nerling F, Nikolaev IB, Ning Z, Nisar S, Olsen SL, Ouyang Q, Pacetti S, Pan X, Pan Y, Pathak A, Patteri P, Pelizaeus M, Peng HP, Peters K, Ping JL, Ping RG, Pitka A, Poling R, Prasad V, Qi H, Qi HR, Qi M, Qi TY, Qian S, Qian WB, Qiao CF, Qin LQ, Qin XP, Qin XS, Qin ZH, Qiu JF, Qu SQ, Qu SQ, Ravindran K, Redmer CF, Rivetti A, Rodin V, Rolo M, Rong G, Rosner C, Sarantsev A, Schelhaas Y, Schnier C, Schoenning K, Scodeggio M, Shan DC, Shan W, Shan XY, Shao M, Shen CP, Shen PX, Shen XY, Shi HC, Shi RS, Shi X, Shi XD, Song WM, Song YX, Sosio S, Spataro S, Su KX, Sun GX, Sun JF, Sun L, Sun SS, Sun T, Sun WY, Sun YJ, Sun YK, Sun YZ, Sun ZT, Tan YH, Tan YX, Tang CJ, Tang GY, Tang J, Teng JX, Thoren V, Uman I, Wang B, Wang BL, Wang CW, Wang DY, Wang HP, Wang K, Wang LL, Wang M, Wang M, Wang WH, Wang WP, Wang X, Wang XF, Wang XL, Wang Y, Wang YD, Wang YF, Wang YQ, Wang Z, Wang ZY, Wang Z, Wang Z, Wei DH, Weidenkaff P, Weidner F, Wen SP, White DJ, Wiedner UW, Wilkinson G, Wolke M, Wollenberg L, Wu JF, Wu LH, Wu LJ, Wu X, Wu Z, Xia L, Xiao H, Xiao SY, Xiao ZJ, Xie XH, Xie YG, Xie YH, Xing TY, Xu GF, Xu JJ, Xu QJ, Xu W, Xu XP, Xu YC, Yan F, Yan L, Yan WB, Yan WC, Yan X, Yang HJ, Yang HX, Yang L, Yang SL, Yang YH, Yang Y, Ye M, Ye MH, Yin JH, You ZY, Yu BX, Yu CX, Yu G, Yu JS, Yu T, Yuan CZ, Yuan L, Yuan W, Yuan Y, Yuan ZY, Yue CX, Zafar AA, Zeng Y, Zhang BX, Zhang GY, Zhang H, Zhang HH, Zhang HH, Zhang HY, Zhang JJ, Zhang JQ, Zhang JW, Zhang JY, Zhang JZ, Zhang J, Zhang J, Zhang L, Zhang SF, Zhang XD, Zhang XY, Zhang Y, Zhang YT, Zhang YH, Zhang Y, Zhang Y, Zhang ZY, Zhao G, Zhao J, Zhao JY, Zhao JZ, Zhao L, Zhao L, Zhao MG, Zhao Q, Zhao SJ, Zhao YB, Zhao YX, Zhao ZG, Zhemchugov A, Zheng B, Zheng JP, Zheng YH, Zhong B, Zhong C, Zhou LP, Zhou Q, Zhou X, Zhou XK, Zhou XR, Zhu AN, Zhu J, Zhu K, Zhu KJ, Zhu SH, Zhu WJ, Zhu WJ, Zhu YC, Zhu ZA, Zou BS, Zou JH. Search for Λ[over ¯]-Λ Baryon-Number-Violating Oscillations in the Decay J/ψ→pK^{-}Λ[over ¯]+c.c. Phys Rev Lett 2023; 131:121801. [PMID: 37802947 DOI: 10.1103/physrevlett.131.121801] [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: 05/08/2023] [Revised: 08/14/2023] [Accepted: 08/29/2023] [Indexed: 10/08/2023]
Abstract
We report on the first search for Λ[over ¯]-Λ oscillations in the decay J/ψ→pK^{-}Λ[over ¯]+c.c. by analyzing 1.31×10^{9} J/ψ events accumulated with the BESIII detector at the BEPCII collider. The J/ψ events are produced using e^{+}e^{-} collisions at a center of mass energy sqrt[s]=3.097 GeV. No evidence for hyperon oscillations is observed. The upper limit for the oscillation rate of Λ[over ¯] to Λ hyperons is determined to be P(Λ)=[B(J/ψ→pK^{-}Λ+c.c.)/B(J/ψ→pK^{-}Λ[over ¯]+c.c.)]<4.4×10^{-6} corresponding to an oscillation parameter δm_{ΛΛ[over ¯]} of less than 3.8×10^{-18} GeV at the 90% confidence level.
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Affiliation(s)
- M Ablikim
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - M N Achasov
- Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
| | - P Adlarson
- Uppsala University, Box 516, SE-75120 Uppsala, Sweden
| | - S Ahmed
- Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
| | - M Albrecht
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - R Aliberti
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - A Amoroso
- University of Turin and INFN, University of Turin, I-10125, Turin, Italy
- INFN, I-10125, Turin, Italy
| | - Q An
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Y Bai
- Southeast University, Nanjing 211100, People's Republic of China
| | - O Bakina
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - R Baldini Ferroli
- INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044, Frascati, Italy
| | - I Balossino
- INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122, Ferrara, Italy
| | - Y Ban
- Peking University, Beijing 100871, People's Republic of China
| | - K Begzsuren
- Institute of Physics and Technology, Peace Avenue 54B, Ulaanbaatar 13330, Mongolia
| | - N Berger
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - M Bertani
- INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044, Frascati, Italy
| | - D Bettoni
- INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122, Ferrara, Italy
| | - F Bianchi
- University of Turin and INFN, University of Turin, I-10125, Turin, Italy
- INFN, I-10125, Turin, Italy
| | - J Bloms
- University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
| | - A Bortone
- University of Turin and INFN, University of Turin, I-10125, Turin, Italy
- INFN, I-10125, Turin, Italy
| | - I Boyko
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - R A Briere
- Carnegie Mellon University, Pittsburgh, Pennsylvania 15213, USA
| | - H Cai
- Wuhan University, Wuhan 430072, People's Republic of China
| | - X Cai
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - A Calcaterra
- INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044, Frascati, Italy
| | - G F Cao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - N Cao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - S A Cetin
- Turkish Accelerator Center Particle Factory Group, Istinye University, 34010, Istanbul, Turkey
| | - J F Chang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - W L Chang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - G Chelkov
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - G Chen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - H S Chen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - M L Chen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - S J Chen
- Nanjing University, Nanjing 210093, People's Republic of China
| | - X R Chen
- Institute of Modern Physics, Lanzhou 730000, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y B Chen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Z J Chen
- Hunan University, Changsha 410082, People's Republic of China
| | | | - G Cibinetto
- INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122, Ferrara, Italy
| | | | - H L Dai
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - J P Dai
- Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
| | - X C Dai
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - A Dbeyssi
- Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
| | - R E de Boer
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - D Dedovich
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - Z Y Deng
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - A Denig
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - I Denysenko
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - M Destefanis
- University of Turin and INFN, University of Turin, I-10125, Turin, Italy
- INFN, I-10125, Turin, Italy
| | - F De Mori
- University of Turin and INFN, University of Turin, I-10125, Turin, Italy
- INFN, I-10125, Turin, Italy
| | - Y Ding
- Liaoning University, Shenyang 110036, People's Republic of China
| | - J Dong
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - L Y Dong
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - M Y Dong
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X Dong
- Wuhan University, Wuhan 430072, People's Republic of China
| | - S X Du
- Zhengzhou University, Zhengzhou 450001, People's Republic of China
| | - J Fang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - S S Fang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y Fang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - R Farinelli
- INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122, Ferrara, Italy
| | - L Fava
- University of Eastern Piedmont, I-15121, Alessandria, Italy
- INFN, I-10125, Turin, Italy
| | - F Feldbauer
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - G Felici
- INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044, Frascati, Italy
| | - C Q Feng
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - M Fritsch
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - C D Fu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Y N Gao
- Peking University, Beijing 100871, People's Republic of China
| | - Ya Gao
- University of South China, Hengyang 421001, People's Republic of China
| | - Yang Gao
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - I Garzia
- INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122, Ferrara, Italy
- University of Ferrara, I-44122, Ferrara, Italy
| | - E M Gersabeck
- University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
| | - A Gilman
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - K Goetzen
- GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
| | - L Gong
- Liaoning University, Shenyang 110036, People's Republic of China
| | - W X Gong
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - W Gradl
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - M Greco
- University of Turin and INFN, University of Turin, I-10125, Turin, Italy
- INFN, I-10125, Turin, Italy
| | - L M Gu
- Nanjing University, Nanjing 210093, People's Republic of China
| | - M H Gu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - S Gu
- Beihang University, Beijing 100191, People's Republic of China
| | - Y T Gu
- Guangxi University, Nanning 530004, People's Republic of China
| | - C Y Guan
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - A Q Guo
- Indiana University, Bloomington, Indiana 47405, USA
| | - L B Guo
- Nanjing Normal University, Nanjing 210023, People's Republic of China
| | - R P Guo
- Shandong Normal University, Jinan 250014, People's Republic of China
| | - Y P Guo
- Fudan University, Shanghai 200433, People's Republic of China
| | - A Guskov
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - T T Han
- Shandong University, Jinan 250100, People's Republic of China
| | - X Q Hao
- Henan Normal University, Xinxiang 453007, People's Republic of China
| | - F A Harris
- University of Hawaii, Honolulu, Hawaii 96822, USA
| | - K L He
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | | | - C H Heinz
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - Y K Heng
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - C Herold
- Suranaree University of Technology, University Avenue 111, Nakhon Ratchasima 30000, Thailand
| | - M Himmelreich
- GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
| | - T Holtmann
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - Y R Hou
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Z L Hou
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - H M Hu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J F Hu
- South China Normal University, Guangzhou 510006, People's Republic of China
| | - T Hu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y Hu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - G S Huang
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - L Q Huang
- University of South China, Hengyang 421001, People's Republic of China
| | - X T Huang
- Shandong University, Jinan 250100, People's Republic of China
| | - Y P Huang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - T Hussain
- University of the Punjab, Lahore-54590, Pakistan
| | - W Imoehl
- Indiana University, Bloomington, Indiana 47405, USA
| | - M Irshad
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - S Jaeger
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - S Janchiv
- Institute of Physics and Technology, Peace Avenue 54B, Ulaanbaatar 13330, Mongolia
| | - Q Ji
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Q P Ji
- Henan Normal University, Xinxiang 453007, People's Republic of China
| | - X B Ji
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X L Ji
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - X S Jiang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J B Jiao
- Shandong University, Jinan 250100, People's Republic of China
| | - Z Jiao
- Huangshan College, Huangshan 245000, People's Republic of China
| | - S Jin
- Nanjing University, Nanjing 210093, People's Republic of China
| | - Y Jin
- University of Jinan, Jinan 250022, People's Republic of China
| | - T Johansson
- Uppsala University, Box 516, SE-75120 Uppsala, Sweden
| | | | - X S Kang
- Liaoning University, Shenyang 110036, People's Republic of China
| | - R Kappert
- University of Groningen, NL-9747 AA Groningen, The Netherlands
| | - M Kavatsyuk
- University of Groningen, NL-9747 AA Groningen, The Netherlands
| | - B C Ke
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- Shanxi Normal University, Linfen 041004, People's Republic of China
| | - I K Keshk
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - A Khoukaz
- University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
| | - P Kiese
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - R Kiuchi
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - R Kliemt
- GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
| | - O B Kolcu
- Turkish Accelerator Center Particle Factory Group, Istinye University, 34010, Istanbul, Turkey
| | - B Kopf
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - M Kuemmel
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | | | - A Kupsc
- Uppsala University, Box 516, SE-75120 Uppsala, Sweden
| | - M G Kurth
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - W Kühn
- Justus-Liebig-Universitaet Giessen, II. Physikalisches Institut, Heinrich-Buff-Ring 16, D-35392 Giessen, Germany
| | - J J Lane
- University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
| | - P Larin
- Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
| | - A Lavania
- Indian Institute of Technology Madras, Chennai 600036, India
| | - L Lavezzi
- University of Turin and INFN, University of Turin, I-10125, Turin, Italy
- INFN, I-10125, Turin, Italy
| | - Z H Lei
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - H Leithoff
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - M Lellmann
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - T Lenz
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - C Li
- Qufu Normal University, Qufu 273165, People's Republic of China
| | - C H Li
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | - Cheng Li
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - D M Li
- Zhengzhou University, Zhengzhou 450001, People's Republic of China
| | - F Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - G Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - H Li
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - H B Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - H J Li
- Fudan University, Shanghai 200433, People's Republic of China
| | - J Q Li
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - J W Li
- Shandong University, Jinan 250100, People's Republic of China
| | - Ke Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - L K Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Lei Li
- Beijing Institute of Petrochemical Technology, Beijing 102617, People's Republic of China
| | - P L Li
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - P R Li
- Lanzhou University, Lanzhou 730000, People's Republic of China
| | - S Y Li
- Tsinghua University, Beijing 100084, People's Republic of China
| | - W D Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - W G Li
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - X H Li
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - X L Li
- Shandong University, Jinan 250100, People's Republic of China
| | - Z Y Li
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - H Liang
- Jilin University, Changchun 130012, People's Republic of China
| | - H Liang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - H Liang
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Y F Liang
- Sichuan University, Chengdu 610064, People's Republic of China
| | - Y T Liang
- Institute of Modern Physics, Lanzhou 730000, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - G R Liao
- Guangxi Normal University, Guilin 541004, People's Republic of China
| | - L Z Liao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J Libby
- Indian Institute of Technology Madras, Chennai 600036, India
| | - A Limphirat
- Suranaree University of Technology, University Avenue 111, Nakhon Ratchasima 30000, Thailand
| | - B J Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - C X Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - D Liu
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - F H Liu
- Shanxi University, Taiyuan 030006, People's Republic of China
| | - Fang Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Feng Liu
- Central China Normal University, Wuhan 430079, People's Republic of China
| | - H B Liu
- Guangxi University, Nanning 530004, People's Republic of China
| | - H M Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Huanhuan Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Huihui Liu
- Henan University of Science and Technology, Luoyang 471003, People's Republic of China
| | - J B Liu
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - J Y Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - K Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - K Y Liu
- Liaoning University, Shenyang 110036, People's Republic of China
| | - L Liu
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - M H Liu
- Fudan University, Shanghai 200433, People's Republic of China
| | - Q Liu
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - S B Liu
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Shuai Liu
- Soochow University, Suzhou 215006, People's Republic of China
| | - T Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - W M Liu
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - X Liu
- Lanzhou University, Lanzhou 730000, People's Republic of China
| | - Y B Liu
- Nankai University, Tianjin 300071, People's Republic of China
| | - Z A Liu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Z Q Liu
- Shandong University, Jinan 250100, People's Republic of China
| | - X C Lou
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - F X Lu
- Henan Normal University, Xinxiang 453007, People's Republic of China
| | - H J Lu
- Huangshan College, Huangshan 245000, People's Republic of China
| | - J D Lu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J G Lu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - X L Lu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Y Lu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Y P Lu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - C L Luo
- Nanjing Normal University, Nanjing 210023, People's Republic of China
| | - M X Luo
- Zhejiang University, Hangzhou 310027, People's Republic of China
| | - T Luo
- Fudan University, Shanghai 200433, People's Republic of China
| | - X L Luo
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | | | - X R Lyu
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - F C Ma
- Liaoning University, Shenyang 110036, People's Republic of China
| | - H L Ma
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - L L Ma
- Shandong University, Jinan 250100, People's Republic of China
| | - M M Ma
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Q M Ma
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - R Q Ma
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - R T Ma
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X X Ma
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X Y Ma
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - F E Maas
- Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
| | - M Maggiora
- University of Turin and INFN, University of Turin, I-10125, Turin, Italy
- INFN, I-10125, Turin, Italy
| | - S Maldaner
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - S Malde
- University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
| | - Q A Malik
- University of the Punjab, Lahore-54590, Pakistan
| | - A Mangoni
- INFN Sezione di Perugia, I-06100, Perugia, Italy
| | - Y J Mao
- Peking University, Beijing 100871, People's Republic of China
| | - Z P Mao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - S Marcello
- University of Turin and INFN, University of Turin, I-10125, Turin, Italy
- INFN, I-10125, Turin, Italy
| | - Z X Meng
- University of Jinan, Jinan 250022, People's Republic of China
| | - J G Messchendorp
- GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
- University of Groningen, NL-9747 AA Groningen, The Netherlands
| | - G Mezzadri
- INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122, Ferrara, Italy
| | - T J Min
- Nanjing University, Nanjing 210093, People's Republic of China
| | - R E Mitchell
- Indiana University, Bloomington, Indiana 47405, USA
| | - X H Mo
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - N Yu Muchnoi
- Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
| | - H Muramatsu
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - S Nakhoul
- GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
| | - Y Nefedov
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - F Nerling
- GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
| | - I B Nikolaev
- Budker Institute of Nuclear Physics SB RAS (BINP), Novosibirsk 630090, Russia
| | - Z Ning
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - S Nisar
- COMSATS University Islamabad, Lahore Campus, Defence Road, Off Raiwind Road, 54000 Lahore, Pakistan
| | - S L Olsen
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Q Ouyang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - S Pacetti
- INFN Sezione di Perugia, I-06100, Perugia, Italy
- University of Perugia, I-06100, Perugia, Italy
| | - X Pan
- Fudan University, Shanghai 200433, People's Republic of China
| | - Y Pan
- University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
| | - A Pathak
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - P Patteri
- INFN Laboratori Nazionali di Frascati, INFN Laboratori Nazionali di Frascati, I-00044, Frascati, Italy
| | - M Pelizaeus
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - H P Peng
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - K Peters
- GSI Helmholtzcentre for Heavy Ion Research GmbH, D-64291 Darmstadt, Germany
| | - J L Ping
- Nanjing Normal University, Nanjing 210023, People's Republic of China
| | - R G Ping
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - A Pitka
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - R Poling
- University of Minnesota, Minneapolis, Minnesota 55455, USA
| | - V Prasad
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - H Qi
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - H R Qi
- Tsinghua University, Beijing 100084, People's Republic of China
| | - M Qi
- Nanjing University, Nanjing 210093, People's Republic of China
| | - T Y Qi
- Beihang University, Beijing 100191, People's Republic of China
| | - S Qian
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - W B Qian
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - C F Qiao
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - L Q Qin
- Guangxi Normal University, Guilin 541004, People's Republic of China
| | - X P Qin
- Fudan University, Shanghai 200433, People's Republic of China
| | - X S Qin
- Shandong University, Jinan 250100, People's Republic of China
| | - Z H Qin
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - J F Qiu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - S Q Qu
- Nankai University, Tianjin 300071, People's Republic of China
| | - S Q Qu
- Tsinghua University, Beijing 100084, People's Republic of China
| | - K Ravindran
- Indian Institute of Technology Madras, Chennai 600036, India
| | - C F Redmer
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | | | - V Rodin
- University of Groningen, NL-9747 AA Groningen, The Netherlands
| | - M Rolo
- INFN, I-10125, Turin, Italy
| | - G Rong
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Ch Rosner
- Helmholtz Institute Mainz, Staudinger Weg 18, D-55099 Mainz, Germany
| | - A Sarantsev
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - Y Schelhaas
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - C Schnier
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - K Schoenning
- Uppsala University, Box 516, SE-75120 Uppsala, Sweden
| | - M Scodeggio
- INFN Sezione di Ferrara, INFN Sezione di Ferrara, I-44122, Ferrara, Italy
- University of Ferrara, I-44122, Ferrara, Italy
| | - D C Shan
- Soochow University, Suzhou 215006, People's Republic of China
| | - W Shan
- Hunan Normal University, Changsha 410081, People's Republic of China
| | - X Y Shan
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - M Shao
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - C P Shen
- Fudan University, Shanghai 200433, People's Republic of China
| | - P X Shen
- Nankai University, Tianjin 300071, People's Republic of China
| | - X Y Shen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - H C Shi
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - R S Shi
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X Shi
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - X D Shi
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - W M Song
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- Jilin University, Changchun 130012, People's Republic of China
| | - Y X Song
- Peking University, Beijing 100871, People's Republic of China
| | - S Sosio
- University of Turin and INFN, University of Turin, I-10125, Turin, Italy
- INFN, I-10125, Turin, Italy
| | - S Spataro
- University of Turin and INFN, University of Turin, I-10125, Turin, Italy
- INFN, I-10125, Turin, Italy
| | - K X Su
- Wuhan University, Wuhan 430072, People's Republic of China
| | - G X Sun
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - J F Sun
- Henan Normal University, Xinxiang 453007, People's Republic of China
| | - L Sun
- Wuhan University, Wuhan 430072, People's Republic of China
| | - S S Sun
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - T Sun
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - W Y Sun
- Nanjing Normal University, Nanjing 210023, People's Republic of China
| | - Y J Sun
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Y K Sun
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Y Z Sun
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Z T Sun
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Y H Tan
- Wuhan University, Wuhan 430072, People's Republic of China
| | - Y X Tan
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - C J Tang
- Sichuan University, Chengdu 610064, People's Republic of China
| | - G Y Tang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - J Tang
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - J X Teng
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - V Thoren
- Uppsala University, Box 516, SE-75120 Uppsala, Sweden
| | - I Uman
- Near East University, Nicosia, North Cyprus, 99138, Mersin 10, Turkey
| | - B Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - B L Wang
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - C W Wang
- Nanjing University, Nanjing 210093, People's Republic of China
| | - D Y Wang
- Peking University, Beijing 100871, People's Republic of China
| | - H P Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - K Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - L L Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - M Wang
- Shandong University, Jinan 250100, People's Republic of China
| | - Meng Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - W H Wang
- Wuhan University, Wuhan 430072, People's Republic of China
| | - W P Wang
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - X Wang
- Peking University, Beijing 100871, People's Republic of China
| | - X F Wang
- Lanzhou University, Lanzhou 730000, People's Republic of China
| | - X L Wang
- Fudan University, Shanghai 200433, People's Republic of China
| | - Y Wang
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Y D Wang
- North China Electric Power University, Beijing 102206, People's Republic of China
| | - Y F Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y Q Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Z Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Z Y Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Ziyi Wang
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Zongyuan Wang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - D H Wei
- Guangxi Normal University, Guilin 541004, People's Republic of China
| | - P Weidenkaff
- Johannes Gutenberg University of Mainz, Johann-Joachim-Becher-Weg 45, D-55099 Mainz, Germany
| | - F Weidner
- University of Muenster, Wilhelm-Klemm-Strasse 9, 48149 Muenster, Germany
| | - S P Wen
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - D J White
- University of Manchester, Oxford Road, Manchester, M13 9PL, United Kingdom
| | - U W Wiedner
- Bochum Ruhr-University, D-44780 Bochum, Germany
| | - G Wilkinson
- University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
| | - M Wolke
- Uppsala University, Box 516, SE-75120 Uppsala, Sweden
| | | | - J F Wu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - L H Wu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - L J Wu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X Wu
- Fudan University, Shanghai 200433, People's Republic of China
| | - Z Wu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - L Xia
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - H Xiao
- Fudan University, Shanghai 200433, People's Republic of China
| | - S Y Xiao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Z J Xiao
- Nanjing Normal University, Nanjing 210023, People's Republic of China
| | - X H Xie
- Peking University, Beijing 100871, People's Republic of China
| | - Y G Xie
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Y H Xie
- Central China Normal University, Wuhan 430079, People's Republic of China
| | - T Y Xing
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - G F Xu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - J J Xu
- Nanjing University, Nanjing 210093, People's Republic of China
| | - Q J Xu
- Hangzhou Normal University, Hangzhou 310036, People's Republic of China
| | - W Xu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X P Xu
- Soochow University, Suzhou 215006, People's Republic of China
| | - Y C Xu
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - F Yan
- Fudan University, Shanghai 200433, People's Republic of China
| | - L Yan
- Fudan University, Shanghai 200433, People's Republic of China
| | - W B Yan
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - W C Yan
- Zhengzhou University, Zhengzhou 450001, People's Republic of China
| | - Xu Yan
- Soochow University, Suzhou 215006, People's Republic of China
| | - H J Yang
- Shanghai Jiao Tong University, Shanghai 200240, People's Republic of China
| | - H X Yang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - L Yang
- Shanxi Normal University, Linfen 041004, People's Republic of China
| | - S L Yang
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Y H Yang
- Nanjing University, Nanjing 210093, People's Republic of China
| | - Yifan Yang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - M Ye
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - M H Ye
- China Center of Advanced Science and Technology, Beijing 100190, People's Republic of China
| | - J H Yin
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Z Y You
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - B X Yu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - C X Yu
- Nankai University, Tianjin 300071, People's Republic of China
| | - G Yu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J S Yu
- Hunan University, Changsha 410082, People's Republic of China
| | - T Yu
- University of South China, Hengyang 421001, People's Republic of China
| | - C Z Yuan
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - L Yuan
- Beihang University, Beijing 100191, People's Republic of China
| | - W Yuan
- University of Turin and INFN, University of Turin, I-10125, Turin, Italy
- INFN, I-10125, Turin, Italy
| | - Y Yuan
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Z Y Yuan
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - C X Yue
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | - A A Zafar
- University of the Punjab, Lahore-54590, Pakistan
| | - Y Zeng
- Hunan University, Changsha 410082, People's Republic of China
| | - B X Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - G Y Zhang
- Henan Normal University, Xinxiang 453007, People's Republic of China
| | - H Zhang
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - H H Zhang
- Jilin University, Changchun 130012, People's Republic of China
| | - H H Zhang
- Sun Yat-Sen University, Guangzhou 510275, People's Republic of China
| | - H Y Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - J J Zhang
- Shanxi Normal University, Linfen 041004, People's Republic of China
| | - J Q Zhang
- Nanjing Normal University, Nanjing 210023, People's Republic of China
| | - J W Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J Y Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - J Z Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Jianyu Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Jiawei Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Lei Zhang
- Nanjing University, Nanjing 210093, People's Republic of China
| | - S F Zhang
- Nanjing University, Nanjing 210093, People's Republic of China
| | - X D Zhang
- North China Electric Power University, Beijing 102206, People's Republic of China
| | - X Y Zhang
- Shandong University, Jinan 250100, People's Republic of China
| | - Y Zhang
- University of Oxford, Keble Road, Oxford OX13RH, United Kingdom
| | - Y T Zhang
- Zhengzhou University, Zhengzhou 450001, People's Republic of China
| | - Y H Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Yan Zhang
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Yao Zhang
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - Z Y Zhang
- Wuhan University, Wuhan 430072, People's Republic of China
| | - G Zhao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - J Zhao
- Liaoning Normal University, Dalian 116029, People's Republic of China
| | - J Y Zhao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J Z Zhao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Lei Zhao
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Ling Zhao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - M G Zhao
- Nankai University, Tianjin 300071, People's Republic of China
| | - Q Zhao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - S J Zhao
- Zhengzhou University, Zhengzhou 450001, People's Republic of China
| | - Y B Zhao
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Y X Zhao
- Institute of Modern Physics, Lanzhou 730000, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Z G Zhao
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - A Zhemchugov
- Joint Institute for Nuclear Research, 141980 Dubna, Moscow region, Russia
| | - B Zheng
- University of South China, Hengyang 421001, People's Republic of China
| | - J P Zheng
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
| | - Y H Zheng
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - B Zhong
- Nanjing Normal University, Nanjing 210023, People's Republic of China
| | - C Zhong
- University of South China, Hengyang 421001, People's Republic of China
| | - L P Zhou
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - Q Zhou
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X Zhou
- Wuhan University, Wuhan 430072, People's Republic of China
| | - X K Zhou
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - X R Zhou
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - A N Zhu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - J Zhu
- Nankai University, Tianjin 300071, People's Republic of China
| | - K Zhu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - K J Zhu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - S H Zhu
- University of Science and Technology Liaoning, Anshan 114051, People's Republic of China
| | - W J Zhu
- Fudan University, Shanghai 200433, People's Republic of China
| | - W J Zhu
- Nankai University, Tianjin 300071, People's Republic of China
| | - Y C Zhu
- State Key Laboratory of Particle Detection and Electronics, Beijing 100049, Hefei 230026, People's Republic of China
- University of Science and Technology of China, Hefei 230026, People's Republic of China
| | - Z A Zhu
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
- University of Chinese Academy of Sciences, Beijing 100049, People's Republic of China
| | - B S Zou
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
| | - J H Zou
- Institute of High Energy Physics, Beijing 100049, People's Republic of China
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Gao Y, Zhao YJ, Li Y, Song JN, Zhang XZ, Sun Y, Yu M, Zhou Q. [The predictive value of melanin-concentrating hormone combined with other related biomarkers in cerebrospinal fluid in preoperative cognitive dysfunction of elderly patients]. Zhonghua Yi Xue Za Zhi 2023; 103:2772-2777. [PMID: 37723051 DOI: 10.3760/cma.j.cn112137-20230119-00112] [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
Objective: To explore the predictive value of cerebrospinal fluid melanin-concentrating hormone (MCH) combined with other related biomarkers in preoperative cognitive dysfunction of elderly patients. Methods: A total of 80 patients who underwent elective hip or knee replacement under intravertebral anesthesia in Chifeng Municipal Hospital, Inner Mongolia, from March to November 2022 were prospectively included, with 32 males and 48 females, and aged 65-85 (70.7±5.2) years old. According to the evaluation results of the Montreal Cognitive Assessment (MoCA), patients were divided into the preoperative cognitive dysfunction (n=23) and control (n=57) groups. The levels of MCH, amyloid-β 40 (Aβ40), amyloid-β 42 (Aβ42), and phosphorylated tau protein (p-tau) in cerebrospinal fluid were determined by enzyme-linked immunosorbent assay (ELISA). The receiver operating characteristic (ROC) curve was drawn to evaluate the predictive value of each biomarker separately or in combination for preoperative cognitive dysfunction. Spearman's rank correlation analysis was utilized to test the correlation between the level of each biomarker and MoCA scores. Results: The levels of MCH, Aβ40, Aβ42, p-tau, and Aβ42/p-tau in the preoperative cognitive dysfunction group were (35.53±5.94) μg/L, (39.21±9.18) ng/L, (221.83±43.17) ng/L, (42.64±9.74) ng/L, and 5.53±1.92, and the levels of these biomarkers in the control group were (28.74±4.90) μg/L, (36.37±7.87) ng/L, (280.23±45.67) ng/L, (35.00±9.27) ng/L, and 8.62±2.78, respectively. Compared with the control group, the levels of cerebrospinal fluid MCH and p-tau in the preoperative cognitive dysfunction group were significantly increased (all P<0.01), and the levels of Aβ42 and Aβ42/p-tau were significantly decreased (all P<0.001). MCH and Aβ42/p-tau provided higher predictive values. The area under the curve (AUC) of MCH and Aβ42/p-tau were 0.807 (95%CI: 0.703-0.911) and 0.842 (95%CI: 0.741-0.943), the sensitivity were 78.3% and 87.0%, and the specificity were 75.4% and 94.7%. MCH combined with Aβ42/p-tau have the higher AUC of 0.915 (95%CI: 0.837-0.992), the sensitivity (87.0%) and specificity (86.0%) were both high, which had a higher predictive value. The levels of cerebrospinal fluid MCH and p-tau were negatively correlated with MoCA score (r=-0.467, -0.321, all P<0.01), and the levels of Aβ42 and Aβ42/p-tau were positively correlated with MoCA score (r=0.480, 0.520, all P<0.001). Conclusion: The increase in cerebrospinal fluid MCH levels is associated with preoperative cognitive dysfunction in elderly patients. MCH combined with Aβ42/p-tau has the greatest predictive value.
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Affiliation(s)
- Y Gao
- Chifeng Clinical Medical College of Inner Mongolia Medical University, Chifeng 024000, China
| | - Y J Zhao
- Chifeng Clinical Medical College of Inner Mongolia Medical University, Chifeng 024000, China
| | - Y Li
- Department of Anesthesiology, Tianjin Medical University General Hospital, Tianjin Research Institute of Anesthesiology, Tianjin 300052, China
| | - J N Song
- Department of Anesthesiology, Chifeng Municipal Hospital of Inner Mongolia, Chifeng 024000, China
| | - X Z Zhang
- Department of Anesthesiology, Chifeng Municipal Hospital of Inner Mongolia, Chifeng 024000, China
| | - Y Sun
- Department of Anesthesiology, Chifeng Municipal Hospital of Inner Mongolia, Chifeng 024000, China
| | - M Yu
- Department of Anesthesiology, Chifeng Municipal Hospital of Inner Mongolia, Chifeng 024000, China
| | - Q Zhou
- Department of Anesthesiology, Chifeng Municipal Hospital of Inner Mongolia, Chifeng 024000, China
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Jiang AF, Zhou SS, Zhou Q, Zhao J, Li XP, Zhou RR, Li B. [Clinical characteristics and their influences on the survival of leptomeningeal metastasis derived from lung adenocarcinoma harboring epithelial growth factor receptor mutation]. Zhonghua Yi Xue Za Zhi 2023; 103:2713-2719. [PMID: 37675543 DOI: 10.3760/cma.j.cn112137-20221221-02686] [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: 09/08/2023]
Abstract
Objective: To analyze the clinical characteristics of leptomeningeal metastasis (LM) patients from epithelial growth factor receptor (EGFR)-mutated lung adenocarcinoma, and their impacts on the survival of the patients. Methods: From July 2018 to July 2022, the clinicopathological data of 81 patients diagnosed as EGFR-mutated lung adenocarcinoma LM by cytopathology who admitted to the Department of Oncology of Xiangya Hospital of Central South University were retrospectively analyzed, including 33 males and 48 females. The age ranged from 31 to 76 years, with a median age of 54 years. All the 81 patients were followed up, with a median follow-up of 21.0 months (95%CI: 12.5 to 29.5 months). The Kaplan Meier method was used to draw survival curve. Cox proportional hazards regression model was used to analyze the impact of the factors on the survival of patients. Results: Among the 81 patients, the interval between the initial diagnosis of lung cancer and the pathological diagnosis of LM in cerebrospinal fluid (CSF) was 0-108 months, with a median interval of 14 months. Fifty-two patients (64.2%) used the third-generation epithelial growth factor receptor tyrosine kinase inhibitor (EGFR-TKIs), while 17 patients (21.0%) used EGFR-TKIs in combination with other drugs, and 12 patients (14.8%) were treated with best supportive care (BSC). Sixty patients (74.1%) had a Kanofsky performance status (KPS) score of less than 60 points, and 71 patients (87.7%) had brain parenchymal metastasis and/or spinal metastasis. Twenty-two patients (27.2%) used pemetrexed through intrathecal CSF, and 17 patients (21.0%) used pemetrexed through the Ommaya sac to the CSF of the ventricle. The incidence of adverse event related to the administration of pemetrexed through CSF was 64.1% (25/39), mainly manifested as myelosuppression, including 22 patients of leukocyte reduction, 25 patients of hemoglobin reduction, and 14 patients of platelet reduction. The median post-leptomeningeal metastasis overall survival (pLM-OS) in 81 patients was 11.0 (95%CI: 7.7-14.3) months. KPS score≥60 points (HR=0.407, 95%CI: 0.170-0.973, P=0.043), CSF cytology negative after treatment (vs persistent positive, HR=0.351, 95%CI: 0.155-0.792, P=0.012), intraventricular administration of pemetrexed (vs non intraventricular administration of pemetrexed, HR=0.319, 95%CI: 0.137-0.745, P=0.008) and the treatment with third-generation EGFR-TKIs after LM (vs EGFR-TKIs in combination with other drugs, HR=0.486, 95%CI: 0.237-0.998, P=0.049) were a factor affecting pLM-OS of patients. Conclusions: Brain parenchyma, or/and spine are the most sites where the LM patients concurrently metastasize. KPS score≥60 points and CSF cytology negative after treatment, intraventricular administration of pemetrexed and the treatment with third-generation EGFR-TKIs are indictors affecting pLM-OS of the patients.
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Affiliation(s)
- A F Jiang
- Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China
| | - S S Zhou
- Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China
| | - Q Zhou
- Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China
| | - J Zhao
- Department of Neurosurgery, Xiangya Hospital, Central South University, Changsha 410008, China
| | - X P Li
- Department of Pharmacy, Xiangya Hospital, Central South University, Changsha 410008, China
| | - R R Zhou
- Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China
| | - B Li
- Department of Oncology, Xiangya Hospital, Central South University, Changsha 410008, China
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Wu SY, Lan H, Liu YL, Sun YJ, Ren MJ, Wang P, Chen ZJ, Zhou Q, Ke X, Li GB, Guo QQ, Chen YL, Lu SH. [Definition of severe pulmonary tuberculosis: a scoping review]. Zhonghua Jie He He Hu Xi Za Zhi 2023; 46:760-773. [PMID: 37536986 DOI: 10.3760/cma.j.cn112147-20230517-00247] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Subscribe] [Scholar Register] [Indexed: 08/05/2023]
Abstract
Objective: To clarify the definition of severe pulmonary tuberculosis and its inclusion criteria by summarizing and analyzing the studies of severe pulmonary tuberculosis (TB). Methods: A systematic search of Medline (via PubMed), Cochrane Library, Web of Science, Web of Science, Epistemonikos, Embase, CNKI, WanFang database, and CBM database was conducted to collect studies published between 2017 and 2022 on patients with severe pulmonary TB. Searches were performed using a combination of subject terms and free words. The search terms included: tuberculosis, severe, serious, intensive care, critical care, respiratory failure, mechanical ventilation, hospitalization, respiratory distress syndrome, multiple organ failure, pulmonary heart disease, and pneumothorax. The definitions and inclusion criteria for severe pulmonary TB in the included studies were extracted. Results: A total of 19 981 studies were identified and 100 studies were finally included, involving 8 309 patients with severe pulmonary TB. A total of 8 (8.00%) studies explicitly mentioned the definition of severe pulmonary TB, and 53 (53.00%) studies clearly defined the inclusion criteria for patients with severe pulmonary TB. A total of 5 definitions and 30 inclusion criteria were extracted. A total of 132 dichotomous variables and 113 continuous variables were included in the outcome indicators related to patients with severe pulmonary TB of concern in the studies. Conclusions: The definition and diagnostic criteria for severe TB are unclear, and there is an urgent need to develop a clear definition and diagnostic criteria to guide clinical practice.
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Affiliation(s)
- S Y Wu
- School of Public Health, Lanzhou University, Lanzhou 730000, China
| | - H Lan
- School of Public Health, Lanzhou University, Lanzhou 730000, China
| | - Y L Liu
- School of Public Health, Lanzhou University, Lanzhou 730000, China
| | - Y J Sun
- School of Public Health, Lanzhou University, Lanzhou 730000, China
| | - M J Ren
- School of Public Health, Lanzhou University, Lanzhou 730000, China
| | - P Wang
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou 730000, China
| | - Z J Chen
- The First School of Clinical Medical, Lanzhou University, Lanzhou 730000, China
| | - Q Zhou
- Evidence-Based Medicine Center, School of Basic Medical Sciences, Lanzhou 730000, China
| | - X Ke
- Department of Lung Disease, Shenzhen Third People's Hospital, The Second Affiliated Hospital, Southern University of Science and Technology, Shenzhen 518112, China
| | - G B Li
- Department of Lung Disease, Shenzhen Third People's Hospital, The Second Affiliated Hospital, Southern University of Science and Technology, Shenzhen 518112, China
| | - Q Q Guo
- School of Public Health, Lanzhou University, Lanzhou 730000, China
| | - Y L Chen
- Research Unit of Evidence-Based Evaluation and Guidelines, Chinese Academy of Medical Sciences(2021RU017), School of Basic Medical Sciences, Lanzhou University, Lanzhou 730000, China
| | - S H Lu
- Department of Lung Disease, Shenzhen Third People's Hospital, The Second Affiliated Hospital, Southern University of Science and Technology, Shenzhen 518112, China
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34
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Sun LJ, Fu Q, Di MJ, Zhou Q, Chen XD. [Mammary myofibroblastoma with extensive atypical/bizarre cells: report of a case]. Zhonghua Bing Li Xue Za Zhi 2023; 52:862-864. [PMID: 37527998 DOI: 10.3760/cma.j.cn112151-20221221-01053] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 08/03/2023]
Affiliation(s)
- L J Sun
- Department of Pathology, Xiaoshan Affiliated Hospital of Wenzhou Medical University (the First People's Hospital of Xiaoshan District), Hangzhou 311200, China
| | - Q Fu
- Department of Pathology, Xiaoshan Affiliated Hospital of Wenzhou Medical University (the First People's Hospital of Xiaoshan District), Hangzhou 311200, China
| | - M J Di
- Department of Pathology, Xiaoshan Affiliated Hospital of Wenzhou Medical University (the First People's Hospital of Xiaoshan District), Hangzhou 311200, China
| | - Q Zhou
- Department of Pathology, Xiaoshan Affiliated Hospital of Wenzhou Medical University (the First People's Hospital of Xiaoshan District), Hangzhou 311200, China
| | - X D Chen
- Department of Pathology, Xiaoshan Affiliated Hospital of Wenzhou Medical University (the First People's Hospital of Xiaoshan District), Hangzhou 311200, China
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35
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Xu JX, Guo CY, Yuan P, Wang BZ, Zhou Q, Ying JM. [Mediastinal germ cell tumor with somatic-type malignancy: report of a case]. Zhonghua Bing Li Xue Za Zhi 2023; 52:733-735. [PMID: 37408409 DOI: 10.3760/cma.j.cn112151-20230212-00120] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 07/07/2023]
Affiliation(s)
- J X Xu
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - C Y Guo
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - P Yuan
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - B Z Wang
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - Q Zhou
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
| | - J M Ying
- Department of Pathology, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing 100021, China
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Wu QS, Mao SQ, Xu Y, Gong RJ, Zhou Q, Liu M, Liu JY, Zhu DH, Guo X. [Safety of delayed vaccination with the national immunization program vaccines in children aged 0-6 years from 2019 to 2021 in Xuhui District, Shanghai City in China]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:983-991. [PMID: 37482734 DOI: 10.3760/cma.j.cn112150-20220804-00787] [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: 07/25/2023]
Abstract
Objective: To understand the incidence of delayed vaccination with the national immunization program vaccines among children aged 0-6 years in Xuhui District, Shanghai, and to evaluate the safety of delayed vaccination. Methods: A stratified random sampling was used to obtain six vaccination clinics in Xuhui District, Shanghai. The vaccination records of children 0-6 years from these six vaccination clinics were collected from the Shanghai Immunization Program Information Management System. Adverse events following immunization (AEFI) data were collected from the China Information System for Disease Control and Prevention. Descriptive epidemiology was used to analyze the data. Children were divided into the timely vaccination group and delayed vaccination group according whether they were delayed in vaccination (received one month or more after the recommended age among children aged ≤1 year; received three months or more after the recommended age among children aged >1 year). The safety of four vaccination methods-individual vaccination, simultaneous vaccination, routine vaccination and combined vaccination-were further compared. Differences between groups were compared using chi-square test. Results: From 2019 to 2021, six vaccination clinics in Xuhui District administered 124 031 doses of the national immunization program vaccines among children aged 0-6 years, and delayed vaccinations accounted for 25.99% (32 234/124 031) of these doses. In 2020, the delayed vaccination rate during the first-level COVID-19 public health emergency response period in Shanghai was significantly higher than that in the same period in 2019 (34.70% vs. 24.19%, χ2=136.23, P<0.05). The delayed vaccination rate during the COVID-19 vaccination campaign in 2021 was significantly higher than that in the same period in 2019 (25.27% vs. 22.55%, χ2=82.80, P<0.05). From 2019 to 2021, a total of 475 cases of AEFI were reported in six vaccination clinics, with a reported incidence of 382.97 per 100 000 doses, including 421 cases of common adverse reaction (88.63%, 339.43 per 100 000 doses), 51 cases of rare adverse reaction (10.74%, 41.12 per 100 000 doses) and 3 cases of coincidences (0.63%, 2.42 per 100 000 doses). The reported incidence of AEFI among delayed vaccinations was significantly lower than that among timely vaccinations (291.62 per 100 000 doses vs. 415.05 per 100 000 doses). The incidence of AEFI for the four delayed vaccination methods (individual vaccination, simultaneous vaccination, routine vaccination and combined vaccination) was lower than that for timely vaccination. There were significant differences between the groups except for the routine vaccination group (χ2=9.82, P<0.05; χ2=5.46, P<0.05; χ2=2.97, P>0.05; χ2=11.89, P<0.05). Conclusions: In Xuhui District of Shanghai, 25.99% of doses of the national immunization program vaccines administered to children 0-6 years were delayed. Delayed vaccination does not increase the risk of AEFI compared with timely vaccination.
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Affiliation(s)
- Q S Wu
- Department of Immunization, Xuhui District Center for Disease Control and Prevention, Shanghai 200237, China
| | - S Q Mao
- Department of Immunization, Xuhui District Center for Disease Control and Prevention, Shanghai 200237, China
| | - Y Xu
- Department of Immunization, Xuhui District Center for Disease Control and Prevention, Shanghai 200237, China
| | - R J Gong
- Department of Immunization, Xuhui District Center for Disease Control and Prevention, Shanghai 200237, China
| | - Q Zhou
- Department of Immunization, Xuhui District Center for Disease Control and Prevention, Shanghai 200237, China
| | - M Liu
- Department of Immunization, Xuhui District Center for Disease Control and Prevention, Shanghai 200237, China
| | - J Y Liu
- Department of Immunization, Xuhui District Center for Disease Control and Prevention, Shanghai 200237, China
| | - D H Zhu
- Clinic of Vaccination, Xujiahui Community Health Service Centre in Xuhui District, Shanghai 200030, China
| | - X Guo
- Department of Immunization Program, Shanghai Municipal Center for Disease Control and Prevention, Shanghai 200336, China
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37
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Zhu Y, Zhou Q, Yu Y, Cao Y, Chen C, Zhai XW, Wang J, Wang HS. [A case of neonatal multi-system Langerhans cell histiocytosis treated by dabrafenib]. Zhonghua Er Ke Za Zhi 2023; 61:655-658. [PMID: 37385813 DOI: 10.3760/cma.j.cn112140-20230301-00149] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 07/01/2023]
Affiliation(s)
- Y Zhu
- Department of Neonatology,Children's Hospital of Fudan University,National Children's Medical Center, Shanghai 201102,China
| | - Q Zhou
- Department of Neonatology,Children's Hospital of Fudan University,National Children's Medical Center, Shanghai 201102,China
| | - Y Yu
- Department of Hematology,Children's Hospital of Fudan University,National Children's Medical Center, Shanghai 201102, China
| | - Y Cao
- Department of Neonatology,Children's Hospital of Fudan University,National Children's Medical Center, Shanghai 201102,China
| | - C Chen
- Department of Neonatology,Children's Hospital of Fudan University,National Children's Medical Center, Shanghai 201102,China
| | - X W Zhai
- Department of Hematology,Children's Hospital of Fudan University,National Children's Medical Center, Shanghai 201102, China
| | - J Wang
- Department of Neonatology,Children's Hospital of Fudan University,National Children's Medical Center, Shanghai 201102,China
| | - H S Wang
- Department of Hematology,Children's Hospital of Fudan University,National Children's Medical Center, Shanghai 201102, China
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38
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Zhang WH, Zhang ZY, Liu Y, Tan ZY, Zhou Q, Lin YZ. High-throughput miRNA sequencing and identification of a novel ICE1-targeting miRNA in response to low temperature stress in Eucalyptus camaldulensis. Plant Biol (Stuttg) 2023; 25:541-550. [PMID: 36971569 DOI: 10.1111/plb.13520] [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: 09/28/2022] [Accepted: 03/14/2023] [Indexed: 05/17/2023]
Abstract
MicroRNAs (miRNAs) play a crucial role in the growth, development, morphogenesis, signal transduction, and stress response in plants. The ICE (Inducer of CBF expression)-CBF (C-repeat binding factor)-COR (Cold-regulated gene) regulatory cascade is an important signalling pathway in plant response to low temperature stress, and it remains unknown whether this pathway is regulated by miRNAs. In this study, high-throughput sequencing was employed for predicting and identifying the miRNAs that were likely to target the ICE-CBF-COR pathway in Eucalyptus camaldulensis. A novel ICE1-targeting miRNA, eca-novel-miR-259-5p (nov-miR259), was further analysed. A total of 392 conserved miRNAs and 97 novel miRNAs were predicted, including 80 differentially expressed miRNAs. Of these, 30 miRNAs were predicted to be associated with the ICE-CBF-COR pathway. The full-length of mature nov-miR259 was 22 bp and its precursor gene was 60 bp in length, with a typical hairpin structure. The RNA ligase-mediated 5' amplification of cDNA ends (5'-RLM-RACE) and Agrobacterium-mediated tobacco transient expression assays demonstrated that nov-miR259 could cleave EcaICE1 in vivo. Moreover, qRT-PCR and Pearson's correlation analysis further revealed that the expression levels of nov-miR259 were almost significantly negatively correlated with those of its target gene, EcaICE1, and the other genes in the ICE-CBF-COR pathway. We first identified the nov-miR259 as a novel ICE1-targeting miRNA, and the nov-miR259-ICE1 module may be involved in regulating the cold stress response in E. camaldulensis.
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Affiliation(s)
- W-H Zhang
- College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, China
- Guangdong Academy of Forestry, Guangzhou, China
| | - Z-Y Zhang
- College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, China
- Guangzhou Huayin Medical Laboratory Center Limited, Guangzhou, China
| | - Y Liu
- College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, China
- Guangdong Key Laboratory for Innovative Development and Utilization of Forest Plant Germplasm, Guangzhou, China
| | - Z-Y Tan
- College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, China
- Guangdong Key Laboratory for Innovative Development and Utilization of Forest Plant Germplasm, Guangzhou, China
| | - Q Zhou
- College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, China
- Guangdong Key Laboratory for Innovative Development and Utilization of Forest Plant Germplasm, Guangzhou, China
| | - Y-Z Lin
- College of Forestry and Landscape Architecture, South China Agricultural University, Guangzhou, China
- Guangdong Key Laboratory for Innovative Development and Utilization of Forest Plant Germplasm, Guangzhou, China
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Wang D, Zhou Q, Fu H, Lian Y, Zhang H. A Fe 2(SO 4) 3-assisted approach towards green synthesis of cuttlefish ink-derived carbon nanospheres for high-performance supercapacitors. J Colloid Interface Sci 2023; 638:695-708. [PMID: 36780850 DOI: 10.1016/j.jcis.2023.02.024] [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: 11/09/2022] [Revised: 01/29/2023] [Accepted: 02/05/2023] [Indexed: 02/11/2023]
Abstract
The conversion of renewable biomass resources into advanced electrode materials through green, simple, and economical methods has become an important research direction in energy storage. In this study, Fe-decorated N/S-codoped porous carbon nanospheres have been successfully fabricated from cuttlefish ink through Fe2(SO4)3-assisted hydrothermal carbonization coupled with heat treatment. The effects of Fe2(SO4)3 dosage on the structure, chemical composition, and capacitive property of carbon nanospheres were investigated. Herein, environmentally friendly Fe2(SO4)3 plays a multifunctional role as the graphitization catalyst, dopant, and morphology-regulating agent. Benefitting from the moderate graphitization degree, great heteroatom content and hierarchical porous structure, the prepared carbon nanospheres exhibit high specific capacitance (311.9 F g-1 at a current density of 0.5 A g-1), good rate capability (19.1% decrease in specific capacitance as current density increases from 0.5 to 10 A g-1), and ideal cycling stability (94.3% capacitance retention after 5000 cycles). In addition, the symmetric supercapacitor assembled with the carbon nanosphere electrodes achieves an energy density of 9.7 Wh kg-1 at a power density of 0.25 kW kg-1 and maintains 91.3% capacitance after 10,000 cycles. The desirable electrochemical performance of cuttlefish ink-derived carbon nanosphere material makes it a potential electrode candidate for supercapacitors.
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Affiliation(s)
- Dawei Wang
- School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou 225002, China
| | - Qiuping Zhou
- School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou 225002, China
| | - Hongliang Fu
- School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou 225002, China
| | - Yue Lian
- School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou 225002, China
| | - Huaihao Zhang
- School of Chemistry & Chemical Engineering, Yangzhou University, Yangzhou 225002, China.
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Liu HS, Wu Z, Yang RY, Chen GZ, Li Y, Zhou Q, Yuan HP, Yang Z, Sun L. [Association between serum lysophosphatidylcholine level and elderly health index in older people from longevity areas of Guangxi Province]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:649-653. [PMID: 37165812 DOI: 10.3760/cma.j.cn112150-20221124-01144] [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: 05/12/2023]
Abstract
Objective: To investigate the relationship between serum lysophosphatidylcholine (LPC) level and the health index of the elderly. Methods: A total of 251 subjects were selected from the 2016 baseline survey of the Yongfu Longevity Cohort in Guangxi Province among whom 66, 63 and 122 were in the young and middle-aged group (≤59 years old), the young group (60-89 years old) and the longevity group (≥90 years old), respectively. Demographic data were collected and related indicators of height, weight, blood pressure and lipid metabolism were measured. The cognitive and physical functions of the elderly were assessed by the results of the simple mental state scale and the daily living activity scale to construct the health index of the elderly. The serum levels of LPC16∶0, LPC18∶0, LPC18∶1 and LPC18∶2 were determined by liquid chromatography-tandem mass spectrometry, and the differences among different ages and health status groups were compared. The logistic regression model was used to analyze the relationship between the serum LPC level and the health index of the elderly. Results: With the increase in age, the proportion of female subjects increased, and the rate of smoking and drinking decreased. BMI, TC, TG, LDL-C, diastolic blood pressure, and the four LPCs levels decreased with the increase of age, and systolic blood pressure levels increased with the increase of age (all P values<0.05). There was no significant difference in HDL-C levels among age groups (P>0.05). With the decline of health status in the elderly, serum levels of LPC16∶0, LPC18∶0, LPC18∶1 and LPC18∶2 showed a downward trend (all P values<0.001). After adjusting for age and gender, only LPC18∶0 was associated with the health status in old age [OR (95%CI): 0.48 (0.25-0.92)]. For every 1 standard deviation (16.87 nmol/L) increase in serum LPC18∶0 concentration, the risk of poor health status in old age decreased by 52%. Conclusion: Serum LPC18∶0 was associated with the health status in old age independent of age and sex.
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Affiliation(s)
- H S Liu
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - Z Wu
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - R Y Yang
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - G Z Chen
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - Y Li
- Department of Geriatrics, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - Q Zhou
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - H P Yuan
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - Z Yang
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - L Sun
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
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41
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Liu HS, Wu Z, Yang RY, Chen GZ, Li Y, Du SC, Zhou Q, Yuan HP, Yang Z, Sun L. [Research progress on main disease-related factors of healthy life expectancy]. Zhonghua Yu Fang Yi Xue Za Zhi 2023; 57:654-658. [PMID: 37165813 DOI: 10.3760/cma.j.cn112150-20221124-01146] [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: 05/12/2023]
Abstract
International research on healthy life expectancy (HALE) focuses on inequality of socioeconomic status and individual natural attributes. With the acceleration of population ageing and the increase in average life expectancy, the extension of unhealthy life expectancy and the increase of social and economic burden caused by diseases have gradually attracted the attention of countries around the world. Therefore, the evaluation of disease factors affecting HALE is a meaningful direction in the future. This study introduces the development process and commonly used measurement methods of HALE. According to the definition of health from the Global Burden of Disease Study and World Health Organization, physical and mental diseases such as cardiovascular and cerebrovascular diseases, chronic respiratory diseases, diabetes, malignant tumors and depression were selected to summarize the impact of these diseases and pre-disease states on HALE. It is expected to provide a theoretical basis for the formulation of relevant public health policies and the improvement of quality of life in China.
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Affiliation(s)
- H S Liu
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - Z Wu
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - R Y Yang
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - G Z Chen
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - Y Li
- Department of Geriatrics, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - S C Du
- Department of Geriatrics, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
| | - Q Zhou
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - H P Yuan
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - Z Yang
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China
| | - L Sun
- The Key Laboratory of Geriatrics/Beijing Institute of Geriatrics/Institute of Geriatric Medicine/Chinese Academy of Medical Sciences/Beijing Hospital/National Center of Gerontology of National Health Commission,Beijing 100730, China Department of Geriatrics, the First Affiliated Hospital of Kunming Medical University, Kunming 650032, China
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Du ZQ, Jiang Y, Lu RR, Zhou Q, Shen Y, Zhu HH. Pharmaceutical care of vascular dementia patients with drug-induced liver injury caused by the Compound Congrong Yizhi Capsules: a case report. Eur Rev Med Pharmacol Sci 2023; 27:4693-4697. [PMID: 37259753 DOI: 10.26355/eurrev_202305_32481] [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: 06/02/2023]
Abstract
BACKGROUND Drug-induced liver injury (DILI) is a newly discovered adverse drug reaction of Compound Congrong Yizhi Capsules (CCYC) in the treatment of vascular dementia (VD), and targeted pharmaceutical care is urgently needed to be explored. CASE REPORT DILI was found in a patient who was admitted to the hospital with a diagnosis of VD after treatment with Compound Congrong Yizhi Capsules. According to the guidelines, the patient was initially treated with magnesium isoglycyrrhizinate injection. After 4 days, the clinical pharmacist monitored liver function: alanine aminotransferase (ALT): 153 IU/L, aspartate aminotransferase (AST): 160 IU/L, total bilirubin (TBil): 4.5 µmol/L, and alkaline phosphatase (ALP): 551 IU/L, which indicated that DILI was further aggravated. In addition, the increased blood pressure (156/65 mmHg) indicated the requirement to adjust the medication. Then, the hepatoprotective drugs were adjusted with reduced glutathione combined with ursodeoxycholic acid. After 12 days of treatment, the liver function was significantly improved, the clinical treatment was effective, and the blood pressure was controlled stably with no obvious adverse drug reactions. CONCLUSIONS With pharmaceutical care guided by clinical pharmacists, the DILI caused by Compound Congrong Yizhi capsules could be reversed to improve the clinical outcome and avoid the occurrence of serious complications.
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Affiliation(s)
- Z-Q Du
- The Affiliated Mental Health Center of Jiangnan University, Wuxi Central Rehabilitation Hospital, Wuxi, Jiangsu, China.
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Xu YY, Su ZZ, Zheng LM, Zhang MN, Tan JY, Yang YL, Zhang MX, Xu M, Chen N, Chen XQ, Zhou Q. [Read-through circular RNA rt-circ-HS promotes hypoxia inducible factor 1α expression and renal carcinoma cell proliferation, migration and invasiveness]. Beijing Da Xue Xue Bao Yi Xue Ban 2023; 55:217-227. [PMID: 37042131 PMCID: PMC10091263] [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: 04/13/2023]
Abstract
OBJECTIVE To identify and characterize read-through RNAs and read-through circular RNAs (rt-circ-HS) derived from transcriptional read-through hypoxia inducible factor 1α (HIF1α) and small nuclear RNA activating complex polypeptide 1 (SNAPC1) the two adjacent genes located on chromosome 14q23, in renal carcinoma cells and renal carcinoma tissues, and to study the effects of rt-circ-HS on biological behavior of renal carcinoma cells and on regulation of HIF1α. METHODS Reverse transcription-polymerase chain reaction (RT-PCR) and Sanger sequencing were used to examine expression of read-through RNAs HIF1α-SNAPC1 and rt-circ-HS in different tumor cells. Tissue microarrays of 437 different types of renal cell carcinoma (RCC) were constructed, and chromogenic in situ hybridization (ISH) was used to investigate expression of rt-circ-HS in different RCC types. Small interference RNA (siRNA) and artificial overexpression plasmids were designed to examine the effects of rt-circ-HS on 786-O and A498 renal carcinoma cell proliferation, migration and invasiveness by cell counting kit 8 (CCK8), EdU incorporation and Transwell cell migration and invasion assays. RT-PCR and Western blot were used to exa-mine expression of HIF1α and SNAPC1 RNA and proteins after interference of rt-circ-HS with siRNA, respectively. The binding of rt-circ-HS with microRNA 539 (miR-539), and miR-539 with HIF1α 3' untranslated region (3' UTR), and the effects of these interactions were investigated by dual luciferase reporter gene assays. RESULTS We discovered a novel 1 144 nt rt-circ-HS, which was derived from read-through RNA HIF1α-SNAPC1 and consisted of HIF1α exon 2-6 and SNAPC1 exon 2-4. Expression of rt-circ-HS was significantly upregulated in 786-O renal carcinoma cells. ISH showed that the overall positive expression rate of rt-circ-HS in RCC tissue samples was 67.5% (295/437), and the expression was different in different types of RCCs. Mechanistically, rt-circ-HS promoted renal carcinoma cell proliferation, migration and invasiveness by functioning as a competitive endogenous inhibitor of miR-539, which we found to be a potent post-transcriptional suppressor of HIF1α, thus promoting expression of HIF1α. CONCLUSION The novel rt-circ-HS is highly expressed in different types of RCCs and acts as a competitive endogenous inhibitor of miR-539 to promote expression of its parental gene HIF1α and thus the proliferation, migration and invasion of renal cancer cells.
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Affiliation(s)
- Y Y Xu
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Z Z Su
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - L M Zheng
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - M N Zhang
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - J Y Tan
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Laboratory of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Y L Yang
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - M X Zhang
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - M Xu
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - N Chen
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Laboratory of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - X Q Chen
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Laboratory of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Q Zhou
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
- Research Laboratory of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
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Chen N, Zhou Q. [The 5th WHO classification of prostate tumors: an update and interpretation]. Zhonghua Bing Li Xue Za Zhi 2023; 52:321-328. [PMID: 36973190 DOI: 10.3760/cma.j.cn112151-20221208-01030] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Subscribe] [Scholar Register] [Indexed: 03/29/2023]
Affiliation(s)
- N Chen
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
| | - Q Zhou
- Department of Pathology, West China Hospital, Sichuan University, Chengdu 610041, China
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Fu Y, Cai J, Chen Y, Zhou Q, Xu YM, Shi J, Fan XS. [Concordance between three integrated scores based on prostate biopsy and grade-grouping of radical prostatectomy specimen]. Zhonghua Bing Li Xue Za Zhi 2023; 52:353-357. [PMID: 36973195 DOI: 10.3760/cma.j.cn112151-20221125-00992] [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: 03/29/2023]
Abstract
Objective: To analyze three different integrated scoring schemes of prostate biopsy and to compare their concordance with the scoring of radical prostatectomy specimens. Methods: A retrospective analysis of 556 patients with radical prostatectomy performed in Nanjing Drum Tower Hospital, Nanjing, China from 2017 to 2020. In these cases, whole organ sections were performed, the pathological data based on biopsy and radical prostatectomy specimens were summarized, and 3 integrated scores of prostate biopsy were calculated, namely the global score, the highest score and score of the largest volume. Results: Among the 556 patients, 104 cases (18.7%) were classified as WHO/ISUP grade group 1, 227 cases (40.8%) as grade group 2 (3+4=7); 143 cases (25.7%) as grade group 3 (4+3=7); 44 cases (7.9%) as grade group 4 (4+4=8) and 38 cases (6.8%) as grade group 5. Among the three comprehensive scoring methods for prostate cancer biopsy, the consistency of global score was the highest (62.4%). In the correlation analysis, the correlation between the scores of radical specimens and the global scores was highest (R=0.730, P<0.01), while the correlations of the scores based on radical specimens with highest scores and scores of the largest volume based on biopsy were insignificant (R=0.719, P<0.01; R=0.631, P<0.01, respectively). Univariate and multivariate analyses showed tPSA group and the three integrated scores of prostate biopsy were statistically correlated with extraglandular invasion, lymph node metastasis, perineural invasion and biochemical recurrence. Elevated global score was an independent prognostic risk factor for extraglandular invasion and biochemical recurrence in patients; increased serum tPSA was an independent prognostic risk factor for extraglandular invasion; increased hjighest score was an independent risk factor for perineural invasion. Conclusions: In this study, among the three different integrated scores, the overall score is most likely corresponded to the radical specimen grade group, but there is difference in various subgroup analyses. Integrated score of prostate biopsy can reflect grade group of radical prostatectomy specimens, thereby providing more clinical information for assisting in optimal patient management and consultation.
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Affiliation(s)
- Y Fu
- Department of Pathology, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - J Cai
- Department of Pathology, Nanjing Jiangning Hospital, the Affiliated Jiangning Hospital of Nanjing Medical University, Nanjing 210000, China
| | - Y Chen
- Department of Pathology, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - Q Zhou
- Department of Pathology, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - Y M Xu
- Department of Pathology, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - J Shi
- Department of Pathology, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China
| | - X S Fan
- Department of Pathology, the Affiliated Drum Tower Hospital, Medical School of Nanjing University, Nanjing 210008, China
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Wu YL, Zhang L, Fan Y, Zhou J, Zhang L, Zhou Q, Li W, Hu C, Chen G, Zhang X, Zhou C, Arenas C, Chen Z, Yu W, Mok T. 42P Pembrolizumab vs chemotherapy in Chinese patients with non-small cell lung cancer (NSCLC) and PD-L1 TPS ≥1%: 5-year update from KEYNOTE-042. J Thorac Oncol 2023. [DOI: 10.1016/s1556-0864(23)00296-4] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2023]
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Liu SY, Zhou Q, Lu C, Deng JY, Wang Z, Li YS, Zheng MM, Xu BF, Dong XR, Du YY, Cui JW, Chu Q, Bai XY, Sun YL, Li A, Xu CR, Wang BC, Chen HJ, Yang JJ, Wu YL. 20P Efficacy and safety of AZD3759 in previously untreated EGFR-mutant non-small cell lung cancer with central nervous system metastases in a multi-center, phase II umbrella trial (CTONG1702). J Thorac Oncol 2023. [DOI: 10.1016/s1556-0864(23)00274-5] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 04/04/2023]
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Xu R, Zhou D, Liu M, Zhou Q, Xie L, Zeng S. Impaired ascending aortic elasticity in fetuses with tetralogy of Fallot. Ultrasound Obstet Gynecol 2023; 61:497-503. [PMID: 36173559 DOI: 10.1002/uog.26079] [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: 05/17/2022] [Revised: 09/05/2022] [Accepted: 09/06/2022] [Indexed: 06/16/2023]
Abstract
OBJECTIVES Aortic wall stiffness has been reported in infants with tetralogy of Fallot (ToF) and may contribute to long-term aortic dilation even after corrective repair surgery. However, little is known about aortic elasticity in fetuses with ToF and the association with neonatal aortic dilation. The objectives of this study were to assess measures of elasticity of the ascending aorta (AAo) in fetuses with ToF and explore the association with neonatal aortic annular dilation in this population. METHODS Seventy-six singleton fetuses with ToF and 76 control fetuses of singleton low-risk pregnancies were enroled into this prospective study. Fetal measures of AAo elasticity, including mean longitudinal strain (MLS), global circumferential strain (GCS) and fractional area change (FAC), were assessed by velocity vector imaging. The z-score of the aortic valve (AV) diameter at the level of the annulus, as a measure of aortic annular dilation, was determined in newborns. Logistic regression analysis was used to investigate the association between fetal measures of AAo elasticity and neonatal aortic annular dilation (defined as an AV annular z-score > 2) in cases with ToF identified prenatally. RESULTS Median MLS, GCS and FAC in fetuses with ToF were lower than those in normal fetuses (7.52% vs 12.15% for MLS, 22.05% vs 29.73% for GCS and 34.2% vs 48.3% for FAC, all P < 0.001). Aortic annular dilation was present in 53/76 (69.7%) newborns with ToF. After adjustment for gestational age at fetal echocardiography and birth weight, fetal MLS, GCS and FAC were independently associated with aortic annular dilation neonatally, with odds ratios of 0.66, 0.78 and 0.82, respectively (P < 0.05). The best cut-off values of these prenatal measures of AAo elasticity for predicting neonatal aortic annular dilation in fetuses with ToF were 9.02% for MLS, 23.56% for GCS and 37.2% for FAC (P < 0.001), with areas under the receiver-operating-characteristics curves of 0.94, 0.91 and 0.93, respectively. CONCLUSION Measures of AAo elasticity are decreased in fetuses with ToF. Impaired AAo elasticity in the fetal period is associated with aortic annular dilation postnatally. Additional research is needed to evaluate the relationship between the AAo elasticity injury pattern and degeneration of AAo elasticity under stress as well as the long-term outcome in this population. © 2022 International Society of Ultrasound in Obstetrics and Gynecology.
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Affiliation(s)
- R Xu
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
- Department of Urology, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - D Zhou
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - M Liu
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - Q Zhou
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - L Xie
- Department of Cardiovascular Medicine, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
| | - S Zeng
- Department of Ultrasound Diagnosis, The Second Xiangya Hospital of Central South University, Changsha, Hunan, China
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Zhang H, Jiang J, He X, Zhou Q. Circ_0002111/miR-134-5p/FSTL1 signal axis regulates tumor progression and glycolytic metabolism in papillary thyroid carcinoma cells. J Endocrinol Invest 2023; 46:713-725. [PMID: 36227499 DOI: 10.1007/s40618-022-01921-4] [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: 03/30/2022] [Accepted: 09/11/2022] [Indexed: 10/17/2022]
Abstract
BACKGROUND Circular RNAs (circRNAs) have essential roles in the malignant progression of papillary thyroid carcinoma (PTC). Circ_0002111 was reported to facilitate cell proliferation and invasion abilities in PTC. This study was performed to explore the regulatory mechanism of circ_0002111 in PTC progression. METHODS Reverse transcription-quantitative polymerase chain reaction (RT-qPCR) was used for the level detection of circ_0002111, microRNA-134-5p (miR-134-5p) and Follistatin Like 1 (FSTL1). Cell proliferation was assessed by 3-(4, 5-dimethylthiazol-2-y1)-2, 5-diphenyl tetrazolium bromide (MTT) assay, EdU assay and colony formation assay. Cell migration ability was determined by transwell assay. Glycolysis was analyzed by extracellular acidification rate (ECAR), oxygen consumption rate (OCR), glucose consumption and lactate production. The protein quantification was performed through western blot. Xenograft tumor assay was used for the functional analysis of circ_0002111 in vivo. The target interaction was confirmed by dual-luciferase reporter assay and RNA pull-down assay. RESULTS The significant upregulation of circ_0002111 was detected in PTC samples and cells. PTC cell proliferation, migration and glycolytic metabolism were suppressed after circ_0002111 downregulation. PTC tumorigenesis in vivo was also inhibited by circ_0002111 knockdown. In addition, circ_0002111 could target miR-134-5p and si-circ_0002111#1-induced inhibition of PTC progression was relieved by miR-134-5p expression downregulation. Furthermore, FSTL1 was a target gene for miR-134-5p and miR-134-5p served as a tumor repressor in PTC by targeting FSTL1. Moreover, circ_0002111 could increase the FSTL1 level via sponging miR-134-5p. CONCLUSION All results indicated that circ_0002111 promoted the malignant behaviors of PTC cells partly by regulating the miR-134-5p/FSTL1 molecular network.
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Affiliation(s)
- H Zhang
- Department of Ultrasound, The second affiliated hospital of Xi'an Jiaotong University, NO. 157 West Fifth Road, Xi'an, 710004, Shaanxi, China
| | - J Jiang
- Department of Ultrasound, The second affiliated hospital of Xi'an Jiaotong University, NO. 157 West Fifth Road, Xi'an, 710004, Shaanxi, China
| | - X He
- Department of Ultrasound, The second affiliated hospital of Xi'an Jiaotong University, NO. 157 West Fifth Road, Xi'an, 710004, Shaanxi, China
| | - Q Zhou
- Department of Ultrasound, The second affiliated hospital of Xi'an Jiaotong University, NO. 157 West Fifth Road, Xi'an, 710004, Shaanxi, China.
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Zhou Q, He LL, Du LZ, Zhao NB, Lv CP, Liang JF. Impaired function of skeletal stem cells derived from growth plates in ovariectomized mice. J Bone Miner Metab 2023; 41:163-170. [PMID: 36847866 DOI: 10.1007/s00774-023-01406-1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 11/19/2022] [Accepted: 01/18/2023] [Indexed: 03/01/2023]
Abstract
INTRODUCTION Mouse skeletal stem cells (mSSCs, CD45-Ter119-Tie2-CD51+Thy-6C3-CD105-CD200+population) are identified in growth plates (GP) and play important roles in bone regeneration. However, the role of mSSCs in osteoporosis remains unclear. MATERIALS AND METHODS The GP were stained by HE staining, and the mSSC lineage was analyzed by flow cytometry at postnatal of 14 days and 30 days in wild-type mice. The mice (8 weeks) were either sham operated or ovariectomy (OVX) and then sacrificed at 2, 4 and 8 w. The GP were stained by Movat staining, and mSSC lineage was analyzed. Then, mSSCs were sorted by fluorescence-activated cell sorting (FACS); the clonal ability, chondrogenic differentiation and osteogenic differentiation were evaluated, and the changed genes were analyzed by RNA-seq. RESULTS The percentage of mSSCs were decreased with the narrow GP. Heights of GP were decreased significantly in 8w-ovx mice compared with 8w-sham mice. We found the percentage of mSSCs were decreased in mice at 2w after ovx, but the cell numbers were not changed. Further, the percentage and cell numbers of mSSCs were not changed at 4w and 8w after ovx. Importantly, the clonal ability, chondrogenic differentiation and osteogenic differentiation of mSSCs were impaired at 8w after ovx. We found 114 genes were down-regulated in mSSCs, including skeletal developmental genes such as Col10a1, Col2a1, Mef2c, Sparc, Matn1, Scube2 and Dlx5. On the contrary, 526 genes were up-regulated, including pro-inflammatory genes such as Csf1, Nfkbla, Nfatc2, Nfkb1 and Nfkb2. CONCLUSION Function of mSSCs was impaired by up-regulating pro-inflammatory genes in ovx-induced osteoporosis.
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Affiliation(s)
- Q Zhou
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, China
| | - L L He
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, China
| | - L Z Du
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, China
| | - N B Zhao
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, China
| | - C P Lv
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, China
| | - J F Liang
- Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, China.
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