1.Analysis of diagnosis and treatment of Epstein-Barr virus-negative diffuse large B-cell lymphoma (GCB type) after kidney transplantation
Yan LI ; Xiaoyan ZHANG ; Xiang REN ; Tong XU ; Guohui WANG ; Ruochen QI ; Dongjuan WU ; Kepu LIU ; Weijun QIN ; Shuaijun MA
Organ Transplantation 2026;17(2):257-265
Objective To analyze the clinical and therapeutic characteristics of Epstein-Barr virus (EBV)-negative posttransplant lymphoproliferative disease (PTLD) with diffuse large B-cell lymphoma (DLBCL) in the context of specific cases and literature. Methods A case of EBV-negative DLBCL (GCB type) after kidney transplantation is reported. The patient was a 45-year-old male who underwent living-related kidney transplantation in 2016 and has been receiving triple immunosuppressive therapy with tacrolimus, mycophenolate mofetil and methylprednisolone since then. In 2024, the patient presented with intermittent fever, night sweats and gastrointestinal symptoms. The diagnosis was confirmed by endoscopic pathology, immunohistochemical staining and positron emission tomography/computed tomography. The R-CDOP regimen (rituximab + cyclophosphamide + liposomal doxorubicin + vincristine + dexamethasone) was used for treatment. Results The patient was diagnosed with EBV-negative DLBCL (GCB type, Ann Arbor stage Ⅳ B). After 4 cycles of R-CDOP chemotherapy, the efficacy assessment was partial remission, and the transplant kidney function remained stable. Conclusions For EBV-negative PTLD after kidney transplantation, it is necessary to break through the "virus-dependent" diagnostic thinking. In clinical practice, the focus should be on protecting the transplant kidney, and individualized treatment plans should be developed for patients.
2.Effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis:machine learning and 16S rDNA analysis
Fucheng GU ; Meixin YANG ; Weixin WU ; Weijun CAI ; Yangyi QIN ; Mingyi SUN ; Jian SUN ; Qiudong GENG ; Nan LI
Chinese Journal of Tissue Engineering Research 2026;30(4):1058-1072
BACKGROUND:The Guilu Erxian Glue consists of Testudinis Plastrum,Cornu Cervi,Lycii Fructus,and Ginseng Radix.In earlier clinical observations,it is discovered that using Guilu Erxian Glue to treat patients with liver-kidney deficiency type knee osteoarthritis effectively alleviated knee pain,increased the range of motion,and improved walking ability.However,the exact mechanism by which oral administration of Guilu Erxian Glue can produce local therapeutic effects on the knee joint is still unclear.OBJECTIVE:To investigate the effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis and to evaluate its mechanism using 16S rDNA sequencing and machine learning analysis.METHODS:Totally 18 female SD rats were randomly divided into three groups:blank group,model group,and Guilu Erxian Glue group,with 6 rats in each group.A knee osteoarthritis model was prepared using the destabilization of the medial meniscus surgical method.After successful modeling,the Guilu Erxian Glue group was given a decoction of Guilu Erxian Glue by gavage,while the blank and model groups were given an equal amount of distilled water.After 28 days of continuous intervention,high performance liquid chromatography was used to detect the active ingredients of Guilu Erxian Glue.MRI imaging was used to observe the condition of rat knee articular cartilage.Fecal samples were collected;DNA was extracted using a kit,amplified and purified by PCR,and an Illumina sequencing library was constructed.The Illumina MiSeq platform was used for high-throughput sequencing to generate raw sequence data.After obtaining the raw data,QIIME2 software was used to process the data.Linear Discriminant Analysis Effect Size analysis and random forest algorithm were used to screen for differential species in microbial data.KEGG and MetaCyc functional pathway analyses were used to explore the association between key microbial communities and experimental groups.Linear discriminant analysis effect values and random forest algorithm were used to screen for differential species.Association networks were used to analyze the interactions between microbial communities,and machine learning methods were used to analyze the composition and changes of gut microbiota.RESULTS AND CONCLUSION:(1)LC-MS component identification was conducted on the traditional Chinese medicine formula of Guilu Erxian Glue,and a total of 7 effective ingredients were identified.(2)MRI imaging showed that synovitis scope of high-density shadows in rats of the Guilu Erxian Glue group was reduced,and the degeneration of medial femoral condyle cartilage was less than that in the model group.(3)16S rDNA sequencing showed that the model group rats exhibited significant microbial imbalance,with a significant decrease in the abundance of Firmicutes and Bacteroidetes at the phylum level,while the proportion of Proteobacteria increased significantly(P<0.05).The gut microbiota structure of rats in the Guilu Erxian Glue group was significantly improved,and the proportion of Firmicutes and Bacteroidetes increased,restoring a more diverse microbiota composition,approaching that of the blank group(P<0.05).(4)KEGG and MetaCyc functional pathway analysis showed that the Guilu Erxian Glue group significantly activated multiple metabolic pathways,including amino acid metabolism,lipid metabolism,and biotin synthesis pathways(P<0.05).(5)The results indicate that Guilu Erxian Glue contains seven active ingredients,and the changes in gut microbiota of knee osteoarthritis rats were analyzed using 16S rDNA sequencing.Guilu Erxian Glue can significantly improve the imbalance of gut microbiota,restore the abundance of beneficial bacteria,and have a significant impact on the composition of gut microbiota,providing scientific basis for the efficacy and mechanism of Guilu Erxian Glue.
3.Effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis:machine learning and 16S rDNA analysis
Fucheng GU ; Meixin YANG ; Weixin WU ; Weijun CAI ; Yangyi QIN ; Mingyi SUN ; Jian SUN ; Qiudong GENG ; Nan LI
Chinese Journal of Tissue Engineering Research 2026;30(4):1058-1072
BACKGROUND:The Guilu Erxian Glue consists of Testudinis Plastrum,Cornu Cervi,Lycii Fructus,and Ginseng Radix.In earlier clinical observations,it is discovered that using Guilu Erxian Glue to treat patients with liver-kidney deficiency type knee osteoarthritis effectively alleviated knee pain,increased the range of motion,and improved walking ability.However,the exact mechanism by which oral administration of Guilu Erxian Glue can produce local therapeutic effects on the knee joint is still unclear.OBJECTIVE:To investigate the effects of Guilu Erxian Glue on gut microbiota in rats with knee osteoarthritis and to evaluate its mechanism using 16S rDNA sequencing and machine learning analysis.METHODS:Totally 18 female SD rats were randomly divided into three groups:blank group,model group,and Guilu Erxian Glue group,with 6 rats in each group.A knee osteoarthritis model was prepared using the destabilization of the medial meniscus surgical method.After successful modeling,the Guilu Erxian Glue group was given a decoction of Guilu Erxian Glue by gavage,while the blank and model groups were given an equal amount of distilled water.After 28 days of continuous intervention,high performance liquid chromatography was used to detect the active ingredients of Guilu Erxian Glue.MRI imaging was used to observe the condition of rat knee articular cartilage.Fecal samples were collected;DNA was extracted using a kit,amplified and purified by PCR,and an Illumina sequencing library was constructed.The Illumina MiSeq platform was used for high-throughput sequencing to generate raw sequence data.After obtaining the raw data,QIIME2 software was used to process the data.Linear Discriminant Analysis Effect Size analysis and random forest algorithm were used to screen for differential species in microbial data.KEGG and MetaCyc functional pathway analyses were used to explore the association between key microbial communities and experimental groups.Linear discriminant analysis effect values and random forest algorithm were used to screen for differential species.Association networks were used to analyze the interactions between microbial communities,and machine learning methods were used to analyze the composition and changes of gut microbiota.RESULTS AND CONCLUSION:(1)LC-MS component identification was conducted on the traditional Chinese medicine formula of Guilu Erxian Glue,and a total of 7 effective ingredients were identified.(2)MRI imaging showed that synovitis scope of high-density shadows in rats of the Guilu Erxian Glue group was reduced,and the degeneration of medial femoral condyle cartilage was less than that in the model group.(3)16S rDNA sequencing showed that the model group rats exhibited significant microbial imbalance,with a significant decrease in the abundance of Firmicutes and Bacteroidetes at the phylum level,while the proportion of Proteobacteria increased significantly(P<0.05).The gut microbiota structure of rats in the Guilu Erxian Glue group was significantly improved,and the proportion of Firmicutes and Bacteroidetes increased,restoring a more diverse microbiota composition,approaching that of the blank group(P<0.05).(4)KEGG and MetaCyc functional pathway analysis showed that the Guilu Erxian Glue group significantly activated multiple metabolic pathways,including amino acid metabolism,lipid metabolism,and biotin synthesis pathways(P<0.05).(5)The results indicate that Guilu Erxian Glue contains seven active ingredients,and the changes in gut microbiota of knee osteoarthritis rats were analyzed using 16S rDNA sequencing.Guilu Erxian Glue can significantly improve the imbalance of gut microbiota,restore the abundance of beneficial bacteria,and have a significant impact on the composition of gut microbiota,providing scientific basis for the efficacy and mechanism of Guilu Erxian Glue.
4.Report of 4 cases of IgG4-related urinary diseases and literature review
Fanchao WEI ; Zhaoxiang WANG ; Mengwei XU ; Ruochen QI ; Guohui WANG ; Xiaoyan ZHANG ; Tong XU ; Jingliang ZHANG ; Shuaijun MA ; Weijun QIN ; Lijun YANG ; Shichao HAN
Journal of Modern Urology 2025;30(1):59-63
[Objective] To explore the clinical features of IgG4-related urinary diseases so as to provide reference for the diagnosis and treatment of such diseases. [Methods] The clinical data of 4 cases of IgG4-related urinary system diseases diagnosed and treated in Xijing Hospital of Air Force Medical University during Aug.2019 and Dec.2023 were retrospectively collected.Here, we report on the diagnosis and treatment of these patients, analysing their symptoms, serology, imaging and pathology as well as their treatment and outcomes. [Results] The patients included 2 male and 2 female.The lesions were involved with the retroperitoneum and urinary system.Three patients had symptoms of lumbar pain.The imaging manifestations were complex, including retroperitoneal mass involving urinary system organs in 2 cases, tabdense shadow of the right kidney in 1 case, and simple cystic mass of kidney in 1 case.Serum IgG4 value was not detected before surgery.All patients underwent radical surgical treatment.Postoperative pathology showed fibrous tissue hyperplasia with a large number of plasma cells, lymphocytes, a few neutrophil infiltrates, and lymphoid follicles and obliterated vasculitis in some specimens.The number of IgG4+ plasma cells was more than 10 in all tissues under high power microscope.After surgery, 3 patients had symptoms improved, and serum IgG4 value was within the normal range; 1 patient (patem 3) had elevated IgG4 value during follow-up, received subsequent hormone therapy, and the serum IgG 4 level remained stable. [Conclusion] The symptoms of IgG4-related diseases involving the urinary system are non-specific, and the imaging findings are various, easily confused with other diseases.Early detection of serum IgG4 and biopsy pathology can help clinicians make correct diagnosis in the early stage.
5.Non-Invasive Visual Prediction of Pathological Grading in Clear Cell Renal Carcinoma Using Habitat Imaging Based on Enhanced CT
Danqing YIN ; Lei YUAN ; Jingliang ZHANG ; Lina MA ; Weijun QIN ; Jing ZHANG ; Yi HUAN ; Jing REN
Chinese Journal of Medical Imaging 2025;33(9):906-911,919
Purpose To explore the value of contrast-enhanced CT habitat imaging(HI)in preoperative non-invasive visualization for predicting pathological grading of clear cell renal carcinoma(ccRCC).Materials and Methods A retrospective analysis was conducted on enhanced CT images and clinical data from 240 patients with pathologically confirmed ccRCC at Xijing Hospital,the Fourth Military Medical University from January 2020 to December 2023.All patients were randomly divided into training and test sets at a 7:3 ratio and classified into low-grade group(International Society of Urological Pathology Ⅰ-Ⅱ)and high-grade group(International Society of Urological Pathology Ⅲ-Ⅳ)based on postoperative pathology.Using wash-in and wash-out parametric maps,the tumors were segmented into three perfusion-based habitat subregions(low,medium and high)via K-means clustering,and the volume fraction of each subregion was calculated.Predictive factors were selected from habitat features and clinical variables(including sex,age,tumor size,etc.)using Logistic regression.Three models were constructed:a clinical model,a habitat imaging model and a combined clinical-habitat model.Model performance was evaluated using receiver operating characteristic curve,calibration curve and decision curve analysis.Results Habitat 3 exhibited higher wash-in and wash-out gradients compared to Habitats 1 and 2,indicating hyper perfusion.Its proportion was significantly higher in the low-grade group than in the high-grade group(Z=-7.71,-5.11,both P<0.01).Multivariate Logistic regression identified hypertension,maximum tumor diameter and platelet-to-lymphocyte ratio as independent risk factors for high-grade ccRCC,while the proportion of Habitat 3 was a protective factor(OR=0.297,95%CI 0.184-0.479).The combined clinical-habitat model demonstrated the highest predictive performance[area under the curve(AUC)=0.938],significantly outperforming the clinical model(AUC=0.801,Z=-3.832,P<0.01)and the habitat imaging model(AUC=0.895,Z=-2.157,P=0.031).Conclusion The clinical-habitat imaging model achieves the highest predictive performance for ccRCC pathological grading.Contrast-enhanced CT habitat imaging provides significant incremental value in predicting ccRCC pathological grading,showing potential to guide precision medicine in clinical practice.
6.Non-Invasive Visual Prediction of Pathological Grading in Clear Cell Renal Carcinoma Using Habitat Imaging Based on Enhanced CT
Danqing YIN ; Lei YUAN ; Jingliang ZHANG ; Lina MA ; Weijun QIN ; Jing ZHANG ; Yi HUAN ; Jing REN
Chinese Journal of Medical Imaging 2025;33(9):906-911,919
Purpose To explore the value of contrast-enhanced CT habitat imaging(HI)in preoperative non-invasive visualization for predicting pathological grading of clear cell renal carcinoma(ccRCC).Materials and Methods A retrospective analysis was conducted on enhanced CT images and clinical data from 240 patients with pathologically confirmed ccRCC at Xijing Hospital,the Fourth Military Medical University from January 2020 to December 2023.All patients were randomly divided into training and test sets at a 7:3 ratio and classified into low-grade group(International Society of Urological Pathology Ⅰ-Ⅱ)and high-grade group(International Society of Urological Pathology Ⅲ-Ⅳ)based on postoperative pathology.Using wash-in and wash-out parametric maps,the tumors were segmented into three perfusion-based habitat subregions(low,medium and high)via K-means clustering,and the volume fraction of each subregion was calculated.Predictive factors were selected from habitat features and clinical variables(including sex,age,tumor size,etc.)using Logistic regression.Three models were constructed:a clinical model,a habitat imaging model and a combined clinical-habitat model.Model performance was evaluated using receiver operating characteristic curve,calibration curve and decision curve analysis.Results Habitat 3 exhibited higher wash-in and wash-out gradients compared to Habitats 1 and 2,indicating hyper perfusion.Its proportion was significantly higher in the low-grade group than in the high-grade group(Z=-7.71,-5.11,both P<0.01).Multivariate Logistic regression identified hypertension,maximum tumor diameter and platelet-to-lymphocyte ratio as independent risk factors for high-grade ccRCC,while the proportion of Habitat 3 was a protective factor(OR=0.297,95%CI 0.184-0.479).The combined clinical-habitat model demonstrated the highest predictive performance[area under the curve(AUC)=0.938],significantly outperforming the clinical model(AUC=0.801,Z=-3.832,P<0.01)and the habitat imaging model(AUC=0.895,Z=-2.157,P=0.031).Conclusion The clinical-habitat imaging model achieves the highest predictive performance for ccRCC pathological grading.Contrast-enhanced CT habitat imaging provides significant incremental value in predicting ccRCC pathological grading,showing potential to guide precision medicine in clinical practice.
7.Construction and assessment of an intelligent hospital-wide bed management system under smart healthcare framework
Weijun CHEN ; Qin XU ; Ting HE ; You XIE ; Weibing PAN ; Haijing GUO
Modern Hospital 2025;25(11):1743-1747
Objective This study aims to evaluate the effectiveness of intelligent bed management model in integrating bed resources in a large comprehensive hospital.Methods Inpatient data from a tertiary hospital between January 2021 and De-cember 2024 were collected.An intelligent hospital-wide bed management platform was constructed to implement bed resource sharing mechanisms and establish a standardized bed reservation grading system.The implementation effect of the system was e-valuated from the perspective of bed occupancy rate,average length of stay,and patient satisfaction.Results After implementa-tion,bed occupancy rates in key monitored departments moved into a reasonable range:Rehabilitation Medicine Department fell from 113.18%to 101.48%(t=4.26,P<0.01),while Neurology Department increased from 88.18%to 96.20%(t=3.85,P<0.01).Annual inpatient admissions increased from 83,931 to 103,852(x2=156.82,P<0.001),and average length of stay shortened from 7.15 days to 6.21 days(t=4.73,P<0.01).The admission waiting time was cut by 72.7 hours(-43.1%),and satisfaction with bed allocation rationality improved by 11.2 points(t=5.94,P<0.001).Staff time spent on bed-assignment fell by 42 minutes per shift(t=8.92,P<0.001),and cross-department transfers increased by 378 episodes per month(x2=145.26,P<0.001).Conclusion The intelligent bed management model can effectively improve hospital bed utili-zation efficiency,enhance healthcare service quality,reduce staff workload,and merits wider application in similar hospitals.
8.Construction and assessment of an intelligent hospital-wide bed management system under smart healthcare framework
Weijun CHEN ; Qin XU ; Ting HE ; You XIE ; Weibing PAN ; Haijing GUO
Modern Hospital 2025;25(11):1743-1747
Objective This study aims to evaluate the effectiveness of intelligent bed management model in integrating bed resources in a large comprehensive hospital.Methods Inpatient data from a tertiary hospital between January 2021 and De-cember 2024 were collected.An intelligent hospital-wide bed management platform was constructed to implement bed resource sharing mechanisms and establish a standardized bed reservation grading system.The implementation effect of the system was e-valuated from the perspective of bed occupancy rate,average length of stay,and patient satisfaction.Results After implementa-tion,bed occupancy rates in key monitored departments moved into a reasonable range:Rehabilitation Medicine Department fell from 113.18%to 101.48%(t=4.26,P<0.01),while Neurology Department increased from 88.18%to 96.20%(t=3.85,P<0.01).Annual inpatient admissions increased from 83,931 to 103,852(x2=156.82,P<0.001),and average length of stay shortened from 7.15 days to 6.21 days(t=4.73,P<0.01).The admission waiting time was cut by 72.7 hours(-43.1%),and satisfaction with bed allocation rationality improved by 11.2 points(t=5.94,P<0.001).Staff time spent on bed-assignment fell by 42 minutes per shift(t=8.92,P<0.001),and cross-department transfers increased by 378 episodes per month(x2=145.26,P<0.001).Conclusion The intelligent bed management model can effectively improve hospital bed utili-zation efficiency,enhance healthcare service quality,reduce staff workload,and merits wider application in similar hospitals.
9.Plasma exchange and intravenous immunoglobulin prolonged the survival of a porcine kidney xenograft in a sensitized, brain-dead human recipient.
Shuaijun MA ; Ruochen QI ; Shichao HAN ; Zhengxuan LI ; Xiaoyan ZHANG ; Guohui WANG ; Kepu LIU ; Tong XU ; Yang ZHANG ; Donghui HAN ; Jingliang ZHANG ; Di WEI ; Xiaozheng FAN ; Dengke PAN ; Yanyan JIA ; Jing LI ; Zhe WANG ; Xuan ZHANG ; Zhaoxu YANG ; Kaishan TAO ; Xiaojian YANG ; Kefeng DOU ; Weijun QIN
Chinese Medical Journal 2025;138(18):2293-2307
BACKGROUND:
The primary limitation to kidney transplantation is organ shortage. Recent progress in gene editing and immunosuppressive regimens has made xenotransplantation with porcine organs a possibility. However, evidence in pig-to-human xenotransplantation remains scarce, and antibody-mediated rejection (AMR) is a major obstacle to clinical applications of xenotransplantation.
METHODS:
We conducted a kidney xenotransplantation in a brain-dead human recipient using a porcine kidney with five gene edits (5GE) on March 25, 2024 at Xijing Hospital, China. Clinical-grade immunosuppressive regimens were employed, and the observation period lasted 22 days. We collected and analyzed the xenograft function, ultrasound findings, sequential protocol biopsies, and immune surveillance of the recipient during the observation.
RESULTS:
The combination of 5GE in the porcine kidney and clinical-grade immunosuppressive regimens prevented hyperacute rejection. The xenograft kidney underwent delayed graft function in the first week, but urine output increased later and the single xenograft kidney maintained electrolyte and pH homeostasis from postoperative day (POD) 12 to 19. We observed AMR at 24 h post-transplantation, due to the presence of pre-existing anti-porcine antibodies and cytotoxicity before transplantation; this AMR persisted throughout the observation period. Plasma exchange and intravenous immunoglobulin treatment mitigated the AMR. We observed activation of latent porcine cytomegalovirus toward the end of the study, which might have contributed to coagulation disorder in the recipient.
CONCLUSIONS
5GE and clinical-grade immunosuppressive regimens were sufficient to prevent hyperacute rejection during pig-to-human kidney xenotransplantation. Pre-existing anti-porcine antibodies predisposed the xenograft to AMR. Plasma exchange and intravenous immunoglobulin were safe and effective in the treatment of AMR after kidney xenotransplantation.
Transplantation, Heterologous/methods*
;
Kidney Transplantation/methods*
;
Heterografts/pathology*
;
Immunoglobulins, Intravenous/administration & dosage*
;
Graft Survival/immunology*
;
Humans
;
Animals
;
Sus scrofa
;
Graft Rejection/prevention & control*
;
Kidney/pathology*
;
Gene Editing
;
Species Specificity
;
Immunosuppression Therapy/methods*
;
Plasma Exchange
;
Brain Death
;
Biopsy
;
Male
;
Aged
10.Knowledge, attitude and behavior of drinking water and associated factors among primary school students in rural China
Chinese Journal of School Health 2025;46(4):509-513
Objective:
To investigate the status quo and associated factors of drinking water knowledge, attitude and behavior among primary school students in rural areas, so as to provide evidence for health behavioral intervention of drinking water in primary school.
Methods:
Twentythree primary schools in rural area from Hebei, Henan, Shandong and Shanxi provinces were selected by using purposive sampling method from March 1 to April 27 in 2023. Selfdesigned questionnaires regarding knowledge, attitude and behavior of drinking water were distributed to all students in grade 3-6, and 2 173 valid questionnaires were obtained. Multivariate Logistic regression was used to analyze the influencing factors of drinking water knowledge, attitude and behavior of primary school students.
Results:
The attainment rates of drinking water knowledge, attitude and behavior level were 20.02%, 26.65%, and 31.20%, respectively, among primary school students. The median of daily water intake was 1 000 mL, and the average daily water intake was (1 172.99±771.89)mL. In addition, 66.31% of students water intake reached the minimum standard of 800 mL recommended. The results of multiple Logistic regression indicated that drinking water accessibility in school, health education of drinking water, and individual selfcontrol ability were positively correlated with the knowledge (OR=1.31, 1.57, 1.58), attitude (OR=2.07, 1.65, 1.73), behavior (OR=1.40, 1.49, 1.91) of drinking water and daily water intake (OR=1.41, 1.38, 1.20) (P<0.05).
Conclusions
Primary school students in rural areas are generally lack of appropriate health awareness on drinking water including knowledge, attitude and behavior. Schools should take targeted measures to focus on the cultivation of students selfcontrol ability, so as to improve students knowledge and attitudes of drinking water, and furthermore help students shape their healthy behaviors of drinking water.


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