1.Monitoring and Analysis of Environmental Microbial Contamination in Laboratory Animal Barrier Facilities
Ying WANG ; Wentao JI ; Shaoqiong XU ; Guoyuan CHEN ; Jie FENG ; Baojin WU
Laboratory Animal and Comparative Medicine 2026;46(2):222-230
ObjectiveTo investigate microbial contamination status and distribution characteristics in laboratory animal barrier facilities, so as to provide a scientific basis for environmental quality control in barrier facilities. MethodsIn accordance with the national standard "Laboratory Animals—Environment and Housing Facilities" and the "Standard Operating Procedures" of the barrier facility, bacterial monitoring was performed on samples of air-settling bacteria, materials, and personnel gloves in the single-corridor barrier facility of the Animal Core Facility, Center for Excellence in Molecular Cell Science, Chinese Academy of Sciences (CEMCS). The monitoring data from January 2020 to December 2024 were collected, organized and statistically analyzed, and partial samples were subjected to species identification using PCR and sequencing methods. ResultsA total of 7 898 samples were collected from 2020 to 2024, including 3 175 air-settling bacteria samples, 3 353 material samples, and 1 370 glove samples. The overall compliance rate was 95.7% (7 559/7 898), among which the compliance rate of air-settling bacteria was 97.1% (3 084/3 175), that of materials was 93.2% (3 125/3 353), and that of personnel gloves was 98.5% (1 350/1 370). Over the five years, the compliance rates of all three types of monitored samples were above 90%. There were statistically significant differences in the compliance rates of air-settling bacteria and material samples among different quarters (P<0.05). Further investigation was conducted on samples collected from January to March 2024, and 190 bacterial strains were obtained through isolation and culture, including 126 strains from air-settling bacteria, 52 strains from materials, and 12 strains from personnel gloves. The strains were identified by PCR amplification and sequencing, and the 190 bacterial strains belonged to 9 genera and 20 species. Gram-positive bacteria accounted for the majority, with Staphylococcus as the dominant genus, accounting for 77.9% (148/190). ConclusionMicroorganisms carried by air, materials, and personnel gloves in barrier facilities are mainly Gram-positive bacteria. Regular monitoring of air-settling bacteria, materials, and personnel gloves in barrier facilities enables timely detection and control of potential risks during husbandry management and facility operation, which is of great significance for maintaining the sound operation of the barrier facility system and ensuring the quality of animal experiments.
2.Long-term survival outcomes and prognostic factors following radical resection of pancreatic body and tail cancer:a retrospective analysis of 992 patients
Dong XU ; Yang WU ; Kai ZHANG ; Nan LYU ; Qianqian WANG ; Pengfei WU ; Jie YIN ; Baobao CAI ; Guodong SHI ; Jianzhen LIN ; Yazhou WANG ; Lingdi YIN ; Zipeng LU ; Min TU ; Jianmin CHEN ; Feng GUO ; Jishu WEI ; Junli WU ; Wentao GAO ; Cuncai DAI ; Yi MIAO ; Kuirong JIANG
Chinese Journal of Surgery 2026;64(1):46-54
Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.
3.Long-term survival outcomes and prognostic factors following radical resection of pancreatic body and tail cancer:a retrospective analysis of 992 patients
Dong XU ; Yang WU ; Kai ZHANG ; Nan LYU ; Qianqian WANG ; Pengfei WU ; Jie YIN ; Baobao CAI ; Guodong SHI ; Jianzhen LIN ; Yazhou WANG ; Lingdi YIN ; Zipeng LU ; Min TU ; Jianmin CHEN ; Feng GUO ; Jishu WEI ; Junli WU ; Wentao GAO ; Cuncai DAI ; Yi MIAO ; Kuirong JIANG
Chinese Journal of Surgery 2026;64(1):46-54
Objective:To investigate the survival outcomes and prognostic factors in patients undergoing radical resection for pancreatic body and tail cancer.Methods:A retrospective case series study was conducted on 992 patients who underwent radical resection for pancreatic body and tail cancer at the Pancreatic Center of the First Affiliated Hospital of Nanjing Medical University from January 2016 to June 2024. In this study, 577 (58.2%) were male and 415 (41.8%) were female,with an age of (65±9) years (range: 26 to 86 years). Follow-up continued until June 2024. Survival rates were estimated using the Kaplan-Meier method,and prognostic factors were identified using univariate and multivariate Cox proportional hazards models.Results:Among 992 patients,open surgery was the predominant approach (89.1%, 884/992), and radical antegrade modular pancreatosplenectomy (RAMPS) was performed in 317 patients (32.0%). Combined organ resection,venous resection,and arterial resection were performed in 23.5%, 9.3%,and 11.2% of patients,respectively. The rates of R0, R1-1 mm, and R1-direct resections were 49.8% (494/992),41.5% (412/992), and 8.7% (86/992),respectively. Stage ⅡB was the most common TNM stage (32.2%,319/992). A total of 801 patients (80.8%) received adjuvant chemotherapy. The median follow-up period was 32.0(8.8) months(range:3.2 to 105.3 months),during which 508 patients (51.2%) died. The overall median survival (OS) was 26.4 months,with 1-,3-, and 5-year survival rates of 79.0%,40.0%, and 29.0%, respectively. In the recent five years (from 2020 to 2024), the median OS improved significantly to 34.1 months compared to 20.0 months from 2016 to 2019 ( P<0.01). Histological subtype analysis showed that the median OS time was 26.7 months for pancreatic ductal adenocarcinoma (PDAC, n=855),58.9 months for invasive intraductal papillary mucinous carcinoma (IPMC, n=32),and 15.7 months for adenosquamous carcinoma of pancreas (ASCP, n=73) ( P=0.001). Among PDAC patients, adjuvant chemotherapy significantly improved survival (29.1 months vs. 14.4 months, P<0.01);in IPMC patients, adjuvant chemotherapy also extended survival (65.7 months vs. 58.9 months, P=0.047). Although ASCP patients receiving chemotherapy had a longer median OS time than those without (18.8 months vs. 8.9 months),the difference was not statistically significant ( P=0.151). Multivariate Cox regression analysis in PDAC patients indicated that adjuvant chemotherapy, R0 resection, T stage,N stage,and tumor differentiation were independent prognostic factors ( P<0.01). The median OS time by TNM stage was:not reached for stage ⅠA, 51.6 months for ⅠB, 25.5 months for ⅡA, 23.7 months for ⅡB, 23.0 months for Ⅲ, and 14.4 months for Ⅳ. The median OS time for R0,R1-1 mm,and R1-direct resections was 34.1,24.7,and 15.7 months,respectively ( P<0.01). Conclusion:Adjuvant chemotherapy,R0 resection,tumor stage,and differentiation are independent prognostic factors for pancreatic body and tail cancer.
4.Expert consensus on prognostic evaluation of cochlear implantation in hereditary hearing loss.
Xinyu SHI ; Xianbao CAO ; Renjie CHAI ; Suijun CHEN ; Juan FENG ; Ningyu FENG ; Xia GAO ; Lulu GUO ; Yuhe LIU ; Ling LU ; Lingyun MEI ; Xiaoyun QIAN ; Dongdong REN ; Haibo SHI ; Duoduo TAO ; Qin WANG ; Zhaoyan WANG ; Shuo WANG ; Wei WANG ; Ming XIA ; Hao XIONG ; Baicheng XU ; Kai XU ; Lei XU ; Hua YANG ; Jun YANG ; Pingli YANG ; Wei YUAN ; Dingjun ZHA ; Chunming ZHANG ; Hongzheng ZHANG ; Juan ZHANG ; Tianhong ZHANG ; Wenqi ZUO ; Wenyan LI ; Yongyi YUAN ; Jie ZHANG ; Yu ZHAO ; Fang ZHENG ; Yu SUN
Journal of Clinical Otorhinolaryngology Head and Neck Surgery 2025;39(9):798-808
Hearing loss is the most prevalent disabling disease. Cochlear implantation(CI) serves as the primary intervention for severe to profound hearing loss. This consensus systematically explores the value of genetic diagnosis in the pre-operative assessment and efficacy prognosis for CI. Drawing upon domestic and international research and clinical experience, it proposes an evidence-based medicine three-tiered prognostic classification system(Favorable, Marginal, Poor). The consensus focuses on common hereditary non-syndromic hearing loss(such as that caused by mutations in genes like GJB2, SLC26A4, OTOF, LOXHD1) and syndromic hereditary hearing loss(such as Jervell & Lange-Nielsen syndrome and Waardenburg syndrome), which are closely associated with congenital hearing loss, analyzing the impact of their pathological mechanisms on CI outcomes. The consensus provides recommendations based on multiple round of expert discussion and voting. It emphasizes that genetic diagnosis can optimize patient selection, predict prognosis, guide post-operative rehabilitation, offer stratified management strategies for patients with different genotypes, and advance the application of precision medicine in the field of CI.
Humans
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Cochlear Implantation
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Prognosis
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Hearing Loss/surgery*
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Consensus
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Connexin 26
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Mutation
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Sulfate Transporters
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Connexins/genetics*
5.Alzheimer's disease diagnosis among dementia patients via blood biomarker measurement based on the AT(N) system.
Tianyi WANG ; Li SHANG ; Chenhui MAO ; Longze SHA ; Liling DONG ; Caiyan LIU ; Dan LEI ; Jie LI ; Jie WANG ; Xinying HUANG ; Shanshan CHU ; Wei JIN ; Zhaohui ZHU ; Huimin SUI ; Bo HOU ; Feng FENG ; Bin PENG ; Liying CUI ; Jianyong WANG ; Qi XU ; Jing GAO
Chinese Medical Journal 2025;138(12):1505-1507
6.Equivalence of SYN008 versus omalizumab in patients with refractory chronic spontaneous urticaria: A multicenter, randomized, double-blind, parallel-group, active-controlled phase III study.
Jingyi LI ; Yunsheng LIANG ; Wenli FENG ; Liehua DENG ; Hong FANG ; Chao JI ; Youkun LIN ; Furen ZHANG ; Rushan XIA ; Chunlei ZHANG ; Shuping GUO ; Mao LIN ; Yanling LI ; Shoumin ZHANG ; Xiaojing KANG ; Liuqing CHEN ; Zhiqiang SONG ; Xu YAO ; Chengxin LI ; Xiuping HAN ; Guoxiang GUO ; Qing GUO ; Xinsuo DUAN ; Jie LI ; Juan SU ; Shanshan LI ; Qing SUN ; Juan TAO ; Yangfeng DING ; Danqi DENG ; Fuqiu LI ; Haiyun SUO ; Shunquan WU ; Jingbo QIU ; Hongmei LUO ; Linfeng LI ; Ruoyu LI
Chinese Medical Journal 2025;138(16):2040-2042
7.Large models in medical imaging: Advances and prospects.
Mengjie FANG ; Zipei WANG ; Sitian PAN ; Xin FENG ; Yunpeng ZHAO ; Dongzhi HOU ; Ling WU ; Xuebin XIE ; Xu-Yao ZHANG ; Jie TIAN ; Di DONG
Chinese Medical Journal 2025;138(14):1647-1664
Recent advances in large models demonstrate significant prospects for transforming the field of medical imaging. These models, including large language models, large visual models, and multimodal large models, offer unprecedented capabilities in processing and interpreting complex medical data across various imaging modalities. By leveraging self-supervised pretraining on vast unlabeled datasets, cross-modal representation learning, and domain-specific medical knowledge adaptation through fine-tuning, large models can achieve higher diagnostic accuracy and more efficient workflows for key clinical tasks. This review summarizes the concepts, methods, and progress of large models in medical imaging, highlighting their potential in precision medicine. The article first outlines the integration of multimodal data under large model technologies, approaches for training large models with medical datasets, and the need for robust evaluation metrics. It then explores how large models can revolutionize applications in critical tasks such as image segmentation, disease diagnosis, personalized treatment strategies, and real-time interactive systems, thus pushing the boundaries of traditional imaging analysis. Despite their potential, the practical implementation of large models in medical imaging faces notable challenges, including the scarcity of high-quality medical data, the need for optimized perception of imaging phenotypes, safety considerations, and seamless integration with existing clinical workflows and equipment. As research progresses, the development of more efficient, interpretable, and generalizable models will be critical to ensuring their reliable deployment across diverse clinical environments. This review aims to provide insights into the current state of the field and provide directions for future research to facilitate the broader adoption of large models in clinical practice.
Humans
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Diagnostic Imaging/methods*
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Precision Medicine/methods*
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Image Processing, Computer-Assisted/methods*
8.Correlation between cognitive impairment and depression in elderly patients with type 2 diabetes mellitus
Yuanyuan ZHAN ; Xinyue XU ; Bowen LU ; Muxin ZHANG ; Fangbo CHEN ; Jie FENG ; Qingrong PAN ; Zhe CHEN
Chinese Journal of Geriatric Heart Brain and Vessel Diseases 2025;27(4):426-430
Objective To investigate the correlation between cognitive impairment and depression in elderly patients with type 2 diabetes mellitus(T2DM).Methods Based on China Health and Retirement Longitudinal Study in 2011,totally 521 elderly T2DM patients were enrolled,and according to the results of minimum mental state examination(MMSE)and their education lev-els,they were divided into a cognitively impaired group(437 cases)and a cognitively normal group(84 cases).Center for ED Epidemiological Survey Depression Scale was used to assess the depression symptoms.The correlation between cognitive impairment and depression was analyzed.Results Compared with the cognitively normal group,the cognitively impaired group had signifi-cantly advanced age(71.98±5.29 year vs 69.42±3.98 year,P=0.000),larger proportion of de-pression(60.6%vs 35.7%,P=0.000),and higher C-reactive protein level(5.09±12.80 mg/L vs 2.25±2.43 mg/L,P=0.000),and obviously lower ratios of being married(72.1%vs 86.9%,P=0.001)and having cardiovascular disease(20.1%vs 32.1%,P=0.010),and decreased estimated glomerular filtration rate[77.15±15.88 ml/(min·1.73 m2)vs 81.91±13.55 ml/(min·1.73 m2),P=0.001].Multivariate logistic regression analysis showed that cognitive impairment was an independent risk factor for the development of depression in elderly T2DM patients(OR=3.44,95%CI:1.89-6.27,P<0.01).ROC curve analysis indicated that the AUC value of MMSE score in predicting depression in elderly T2DM patients was 0.669(95%CI:0.626-0.709,P<0.01).The direct effect of cognitive impairment and the mediating effect of loneliness on depression in elderly T2DM patients accounted for 72.22%and 27.78%of the total effect,respectively.Conclu-sion Cognitive impairment is associated with the presence of depression in elderly T2DM pa-tients,and loneliness plays a mediating role.
9.Clinical analysis of fusion therapy for type Ⅱ painful scaphoid of foot accessory
Jun-jie LI ; Jiang-feng ZHANG ; Jia-bao DONG ; Mi-yang XU ; Gen-rui ZHU ; Xiong-feng LI
China Journal of Orthopaedics and Traumatology 2025;38(6):608-612
Objective To explore clinical effect of accessory scaphoid bone fusion in treating type Ⅱ painful accessory scaphoid bone.Methods A retrospective analysis was performed on 26 patients with type Ⅱ painful accessory navicular bone treated by accessory navicular bone fusion from January 2012 to June 2022,including 1 male and 25 females,aged from 18 to 70 years old with an average of(44.61±16.32)years old;10 patients with type Ⅱ A and 16 patients with type Ⅱ B;20 patients with simple fusion and 6 patients with fusion plus calcaneal translocation osteotomy.Changes of Meary angle,Pitch angle,an-teroposterior talar-first metatarsal angle(T1MA),talonavicular coverage angle(TCA),lateral talocalcaneal angle(LTCA)be-fore operation and 6 months after operation were observed and compared,and American Orthopedic Foot and Ankle Society(AOFAS)foot and ankle score and visual analogue scale(VAS)were used to explore clinical effect.Results All 26 patients were followed up for 7 to 24 months with an average of(10.72±3.94)months.Meary angle,Pitch angle,T1MA,TCA and LTCA were improved from(9.20±2.57)°,(16.45±3.57)°,(33.34±5.02)°,(22.42±5.86)°,(48.89±4.43)° before opertaion to(3.33±1.06)°,(22.33±4.56)°,(23.89±3.48)°,(11.83±2.67)°,(36.50±3.50)° at 6 months after operation,the difference were statistically significant(P<0.01).Postoperative AOFAS foot and ankle score were(86.24±4.33)and(93.18±6.02)for type Ⅱ A and type Ⅱ B at 6 months,which were significantly improved compared with those for type Ⅱ A and type Ⅱ B before op-eration(67.34±6.55)and(65.12±9.51),and the difference was statistically significant(P<0.01);20 patients got excellent re-sult,5 good and 1 poor.Preoperative VAS of type ⅡA(5.67±1.58)and type Ⅱ B(5.77±1.49)were improved to(2.13±1.01)and(1.43±0.68)at 6 months after operation,with statistical significance(P<0.01).Conclusion Fusion of accessory navicular bone in patients with type Ⅱ painful accessory navicular bone combined with internal calcaneal osteotomy in patients with par-tial calcaneal valvaration could effectively correct flat foot deformity and relieve pain,and could be used as a clinical treatment for painful accessory navicular bone.
10.Construction of a machine learning model based on the Ki67 positive index to predict the recurrence risk of hepatocellular carcinoma
Haoran LI ; Yan YU ; Fangying FAN ; Wenzhen DING ; Hui FENG ; Minghua YING ; Jiawei LI ; Qingqing SUN ; Lele BIAN ; Haokai XU ; Zhanyue CHEN ; Jie YU ; Ping LIANG
Chinese Journal of Hepatology 2025;33(9):898-909
Objective:To screen the optimal machine learning model for predicting the recurrence condition of hepatocellular carcinoma (HCC) at different time points post-surgery, based on the cutoff value of the Ki67 positive proliferation index condition calculated from recurrence-free survival and combined with various clinical features.Methods:retrospective study included initially treated patients with solitary HCC who underwent radical surgery at the Fifth Medical Center of the PLA General Hospital from January 2013 to March 2023. Data included general clinical data, preoperative laboratory parameters, and surgical pathology information about the subjects. The postoperative recurrence status was assessed by querying the medical record system or by telephone follow-up. The Ki67 positive index cutoff value was determined by the X-tile software based on the patient's recurrence-free survival status and time analysis. Survival rates were calculated using the Kaplan-Meier method, and survival curves were plotted. The study population was randomly divided into training and testing groups in a 7:3 ratio using a computer-generated random number method. The minimum redundancy maximum relevance (mRMR) method was used for feature variable selection. Predictive models for postoperative HCC recurrence conditions in patients with HCC were constructed using random forest, support vector machine, logistic regression, and gradient boosting decision tree machine learning algorithms. Inter-group comparisons for continuous data were performed using the t-test or Mann-Whitney U test. Inter-group comparisons of enumeration data were performed using the Pearson χ2 test, continuity-corrected χ2 test, or Fisher's exact test. Results:The cutoff values for the Ki67 positivity index were 0.3 and 0.5 in 510 cases, with a follow-up time ranging from 1.2 to 11.4 years (median: 6.2 years). The recurrence-free survival time was between 1 and 135 months (median: 32 months), with recurrence-free survival rates post-surgery at 1, 2, 3, and 5 years were 87.5%, 77.1%, 61.2%, and 54.5%, respectively. The top five variables predicted HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years, in accordance with information obtained by the mRMR screen out. The Ki67 positivity index screened a successfully constructed machine learning model to predict HCC recurrence and non-recurrence conditions following surgical follow-up at 6 months, 1 year, 2 years, and beyond 2 years. The machine learning model based on the gradient boosting decision tree algorithm had the best prediction performance among them (areas under the receiver operating characteristic curves for predicting HCC recurrence within six months in the training and validation sets were 0.996 and 0.946, and accuracies were 0.972 and 0.935, respectively).Conclusion:A machine learning model was successfully constructed using the Ki67 positivity index combined with four readily available clinical features to predict HCC recurrence. The machine learning model based on the gradient boosting decision tree algorithm demonstrated the best performance in terms of predicting HCC recurrence within six months after surgery.

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