In order to further standardize the vaccination of kidney transplant candidates and recipients in China, the Branch of Organ Transplantation of Chinese Medical Association has organized experts in kidney transplantation and infectious diseases. Based on the "Vaccination of Solid Organ Transplant Candidates and Recipients: Guidelines from the American Society of Transplantation Infectious Diseases Community of Practice", and in combination with the clinical reality of infectious diseases and vaccination after organ transplantation in China, as well as referring to relevant recommendations from home and abroad in recent years, these guidelines are formulated from aspects such as epidemiology, types of vaccines, vaccination principles, target population, and specific vaccine administration. The "Guidelines for Vaccination of Kidney Transplant Candidates and Recipients in China" aims to provide theoretical reference for medical workers in the field of kidney transplantation in China, regarding the vaccination of kidney transplant candidates and recipients. It is expected to better guide the vaccination of kidney transplant candidates and recipients, reduce the risk of postoperative infection, and improve survival outcomes.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Purpose: The genomic characteristics of uterine sarcomas have not been fully elucidated. This study aimed to explore the genomic landscape of the uterine sarcomas (USs). Materials and Methods: Comprehensive genomic analysis through RNA-sequencing was conducted. Gene fusion, differentially expressed genes (DEGs), signaling pathway enrichment, immune cell infiltration, and prognosis were analyzed. A deep learning model was constructed to predict the survival of US patients. Results: A total of 71 US samples were examined, including 47 endometrial stromal sarcomas (ESS), 18 uterine leiomyosarcomas (uLMS), three adenosarcomas, two carcinosarcomas, and one uterine tumor resembling an ovarian sex-cord tumor. ESS (including high-grade ESS [HGESS] and low-grade ESS [LGESS]) and uLMS showed distinct gene fusion signatures; a novel gene fusion site, MRPS18A–PDC-AS1 could be a potential diagnostic marker for the pathology differential diagnosis of uLMS and ESS; 797 and 477 uterine sarcoma DEGs (uDEGs) were identified in the ESS vs. uLMS and HGESS vs. LGESS groups, respectively. The uDEGs were enriched in multiple pathways. Fifteen genes including LAMB4 were confirmed with prognostic value in USs; immune infiltration analysis revealed the prognositic value of myeloid dendritic cells, plasmacytoid dendritic cells, natural killer cells, macrophage M1, monocytes and hematopoietic stem cells in USs; the deep learning model named Max-Mean Non-Local multi-instance learning (MMN-MIL) showed satisfactory performance in predicting the survival of US patients, with the area under the receiver operating curve curve reached 0.909 and accuracy achieved 0.804. Conclusion USs harbored distinct gene fusion characteristics and gene expression features between HGESS, LGESS, and uLMS. The MMN-MIL model could effectively predict the survival of US patients.

Objective To analyze the nonlinear relationship between hypothermic machine perfusion (HMP) parameters and delayed graft function (DGF) and optimize the construction of a predictive model for DGF. Methods The data of 923 recipients who underwent kidney transplantation from deceased donors were retrospectively analyzed. According to the occurrence of DGF, the recipients were divided into DGF group (n=823) and non-DGF group (n=100). Donor data, HMP parameters and recipient data were analyzed for both groups. The nonlinear relationship between HMP parameters and the occurrence of DGF was explored based on restricted cubic splines (RCS). Over-sampling, under-sampling and balanced sampling were used to address the imbalance in the proportion of DGF to construct logistic regression predictive models. The area under the curve (AUC) of each model was compared in the validation set, and a nomogram model was constructed. Results Donor BMI, cold ischemia time of the donor kidney, and HMP parameters (initial and final pressures, resistance, and perfusion time) were significantly different between the DGF and non-DGF groups (all P<0.05). The RCS analysis revealed a threshold-like nonlinear relationship between HMP parameters and the risk of DGF. Among the models constructed using different sampling methods, the balanced sampling model had the highest AUC. Using this model, a nomogram was constructed to stratify recipients based on risk scores. Recipients in the high-risk group had higher serum creatinine levels at 1, 6, and 12 months after kidney transplantation compared to those in the low-risk group (all P<0.05). Conclusions There is a nonlinear relationship between HMP parameters and the risk of DGF, and the threshold is helpful for organ quality assessment and monitoring of graft function after transplantation. The predictive model for DGF constructed on the base of balanced sampling algorithms helps perioperative decision-making and postoperative graft function monitoring of kidney transplantation.

To further standardize the diagnosis and treatment of hypertension after kidney transplantation in China,Branch of Organ Transplantation of Chinese Medical Association organized experts in kidney transplantation and cardiovascular diseases to formulate"Guidelines for Clinical Diagnosis and Treatment of Hypertension in Kidney Transplant Recipients in China"based on"Diagnosis and Treatment Specification for Hypertension after Solid Organ Transplantation in China(2019 edition)"in combination with clinical status of hypertension after organ transplantation in China,and referring to the latest guidelines for diagnosis and treatment of hypertension at home and abroad.This guideline was formulated to provide theoretical reference for medical practitioners in the field of kidney transplantation in China,aiming to better control adult hypertension after kidney transplantation,mitigate adverse outcomes and improve the quality of life.

Objective To investigate the characteristics of adverse drug event(ADE)related to tacrolimus(Tac)in pediatric solid organ transplant recipients.Methods The data were retrieved from the US Food and Drug Administration Adverse Event Reporting System database from the first quarter of 2004 to the second quarter of 2023.The ADE data of pediatric organ transplant recipients with Tac as the primary suspected drug were extracted.The relationship between Tac and ADE was quantitatively analyzed by proportional imbalance method.Basic characteristics and signal strength of ADE related to Tac were analyzed.ADE related to Tac in children of different ages and different types of organ transplantation were analyzed.Results A total of 1 443 children's ADE reports involving Tac were screened,including 188 cases(13.0％)of heart transplantation,668 cases(46.3％)of liver transplantation,531 cases(36.8％)of kidney transplantation and 56 cases(3.9％)of lung transplantation.The median age of children was 10 years old.The top three countries with ADE reporting were the United States,France and the United Kingdom.China reported 26 cases,accounting for 1.8％.Infection and infectious diseases accounted for the highest proportion(20.96％)in ADE related to Tac,including EB virus and cytomegalovirus infection,etc.Infection and infectious diseases occupied the largest proportion of ADE related to Tac in children of different ages,whereas the pathogen types were different.Rejection,unstable immunosuppression level and renal function damage were also common ADE related to Tac in children of all ages.Nervous system disease was the main ADE in heart transplant recipients,while infection and infectious diseases were more common in liver and kidney transplant recipients.Rejection was the most common ADE in lung transplant recipients.Conclusions ADE related to Tac possess different distribution characteristics in different types of organ transplantation.Extensive attention should be paid to individualized drug monitoring and risk assessment in pediatric organ transplant recipients,thereby optimizing Tac treatment and reducing the risk of ADE.

Objective To explore the molecular mechanisms and cell-cell interactions in the injury process of pancreatic islet transplantation.Methods Single-cell transcriptome data from mouse islets treated with inflammatory factors were used,and data processing was performed using the Seurat package,with integrated data to remove batch effects.Cell subpopulations were annotated based on known markers.Cell-cell interactions in the inflammatory factor-treated group were analyzed using the CellChat package,and inferred based on the expression of cell surface receptors and ligands.Gene set enrichment analysis was used to clarify the biological processes enriched in β-cells after treatment with inflammatory factors.Finally,differentially expressed transcription factors were identified and verified using microarray datasets of donor islet ischemic injury and Western blotting.Results A total of 7 different cell subpopulations were found in mouse islets,with β-cells being the most abundant.Cell-cell interaction network analysis showed that the number and strength of interactions between ductal cells and other cells were the highest.Gene set enrichment analysis showed that after treatment with inflammatory factors,the immune response was positively enriched in β-cells,while peptide hormone metabolism,bile acid metabolism,and ion homeostasis were downregulated.The common differential transcription factors identified in the mouse single-cell transcriptome and the microarray dataset of donor islet ischemic injury were early growth response 1(EGR1),nuclear factor-κB inhibitor α(NFKBIA),and activating transcription factor 3(ATF3).Among them,NFKBIA and ATF3 were upregulated,while EGR1 was downregulated.The expression of EGR1 protein was downregulated after 24 h,48 h,and 72 h of cold ischemia.Conclusions EGR1 is a transcription factor closely related to islet cold ischemia,and future research should focus on the specific mechanisms of EGR1 and its downstream target genes,in order to provide more effective strategies for clinical treatment of islet transplantation.

[Objective] To analyze the changes of platelet extracellular vesicles (PEVs) content in apheresis at different storage periods, track the PEVs and transfusion efficacy of patients, and explore the mechanism of PEVs in relation to platelet storage damage and transfusion efficacy. [Methods] From November 2022 to April 2024, a total of 85 apheresis platelets samples were collected at Jiading District Blood Station. Flow cytometry was used to detect the content of PEVs on the day of collection and before transfusion. The changes in the content of PEVs stored for 1 to 5 days were observed. Patients with acute leukemia were selected as transfusion recipients, and their content of platelet count and PEVs before transfusion and within 24 hours after transfusion, and the efficacy were tracked to explore the mechanism of PEVs in relation to storage lesion and transfusion efficacy. [Results] The content of PEVs before platelet infusion (8.73±4.84) was significantly higher than that on the day of platelet collection (5.11±3.33), and the difference was statistically significant (P<0.01). The increase in the content of PEVs in storage for 2 to 5 days was 2.55±1.38, 3.49±2.63, 3.86±3.55 and 4.50±3.91, with statistically significant difference (P<0.05). The PEVs content in patients after blood transfusion was positively correlated with that before transfusion and that in apheresis platelet bags during transfusion (P<0.001) A total of 85 cases of apheresis platelet transfusion were conducted, with 61 effective transfusions having a CCI value of (13.43±4.70), and 24 transfusion refractoriness cases having a CCI value of (2.27±3.67), showing a statistically significant difference (P<0.001). The transfusion effectiveness rates for patients receiving different storage periods of apheresis platelets of 2 to 5 days were 88.89%, 68.42%, 68.18% and 57.14% respectively, with corresponding CCI values of 11.18±6.10, 10.43±6.77, 9.53±6.75 and 9.48±8.86, and there was no significant difference between CCI groups (P>0.05). There was no significant correlation between the PEVs content before and after transfusion and the efficacy of CCI (P>0.05). There was no significant correlation between the PEVs content before apheresis platelet transfusion and the efficacy of CCI (P>0.05). [Conclusion] The content of PEVs increased with the prolongation of storage time, which could be used as a potential blood quality evaluation and monitoring index during the storage period, but it was not significantly correlated with the efficacy of CCI in transfusion.

Permeability is one of the determinants of intestinal absorption and oral bioavailability. The non-cell-based permeation model is a kind of in vitro permeability measurement tool, which has the advantages of high efficiency, low cost, stable property, easy to use and customizable. According to the barrier type, non-cell-based permeation model can be divided into biomimetic barriers containing (phosphate) lipids and non-biomimetic barriers without lipids. Biomimetic permeation models include parallel artificial membrane permeability assay, vesicle-based permeation assay and PermeaPad®. Non biomimetic permeation models include Hollow fiber membrane models based on polyether sulfone materials. In foreign countries, the application of these four barriers for different purposes is gradually becoming a hot spot in drug absorption research. However, in China, there are only more applied studies on PMAPM and few published applied studies on the other three barriers. In order to meet the development needs of insoluble drug formulations, the author summarized the permeability devices and permeability calculation methods, searched the application of non-cell-based permeation model in the permeability of BSCⅡ drugs in recent years, and summarized the characteristic applications of three Biomimetic permeation models and hollow fiber membranes.