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.

In recent years, the application of artificial intelligence (AI) in the field of biology has witnessed remarkable advancements. Among these, the most notable achievements have emerged in the domain of protein structure prediction and design, with AlphaFold and related innovations earning the 2024 Nobel Prize in Chemistry. These breakthroughs have transformed our ability to understand protein folding and molecular interactions, marking a pivotal milestone in computational biology. Looking ahead, it is foreseeable that the accurate prediction of various physicochemical properties of proteins—beyond static structure—will become the next critical frontier in this rapidly evolving field. One of the most important protein properties is thermodynamic stability, which refers to a protein’s ability to maintain its native conformation under physiological or stress conditions. Accurate prediction of protein stability, especially upon single-point mutations, plays a vital role in numerous scientific and industrial domains. These include understanding the molecular basis of disease, rational drug design, development of therapeutic proteins, design of more robust industrial enzymes, and engineering of biosensors. Consequently, the ability to reliably forecast the stability changes caused by mutations has broad and transformative implications across biomedical and biotechnological applications. Historically, protein stability was assessed via experimental methods such as differential scanning calorimetry (DSC) and circular dichroism (CD), which, while precise, are time-consuming and resource-intensive. This prompted the development of computational approaches, including empirical energy functions and physics-based simulations. However, these traditional models often fall short in capturing the complex, high-dimensional nature of protein conformational landscapes and mutational effects. Recent advances in machine learning (ML) have significantly improved predictive performance in this area. Early ML models used handcrafted features derived from sequence and structure, whereas modern deep learning models leverage massive datasets and learn representations directly from data. Deep neural networks (DNNs), graph neural networks (GNNs), and attention-based architectures such as transformers have shown particular promise. GNNs, in particular, excel at modeling spatial and topological relationships in molecular structures, making them well-suited for protein modeling tasks. Furthermore, attention mechanisms enable models to dynamically weigh the contribution of specific residues or regions, capturing long-range interactions and allosteric effects. Nevertheless, several key challenges remain. These include the imbalance and scarcity of high-quality experimental datasets, particularly for rare or functionally significant mutations, which can lead to biased or overfitted models. Additionally, the inherently dynamic nature of proteins—their conformational flexibility and context-dependent behavior—is difficult to encode in static structural representations. Current models often rely on a single structure or average conformation, which may overlook important aspects of stability modulation. Efforts are ongoing to incorporate multi-conformational ensembles, molecular dynamics simulations, and physics-informed learning frameworks into predictive models. This paper presents a comprehensive review of the evolution of protein thermodynamic stability prediction techniques, with emphasis on the recent progress enabled by machine learning. It highlights representative datasets, modeling strategies, evaluation benchmarks, and the integration of structural and biochemical features. The aim is to provide researchers with a structured and up-to-date reference, guiding the development of more robust, generalizable, and interpretable models for predicting protein stability changes upon mutation. As the field moves forward, the synergy between data-driven AI methods and domain-specific biological knowledge will be key to unlocking deeper understanding and broader applications of protein engineering.

Aromatic immunity in traditional Chinese medicine(TCM) is the medical knowledge accumulated in the process of people's struggling with diseases. It plays an important role in plague prevention, disease treatment, health preservation, and rehabilitation, and has profound TCM basic theoretical support and abundant modern scientific evidence. With the in-depth promotion of the Healthy China initiative and the succession of health needs in the post-COVID-19 era, how to practice the health concept of aromatic immunity in TCM and develop its health service resources with high quality has become an important proposition to be discussed urgently. This paper summarizes the cognitive process, puts forward the basic concept, discusses the scientific connotation and clinical application value, and looks forward to the future development trend of aromatic immunity in TCM, aiming to provide guidance for the development of great health products and promote the application of aromatic immunity in TCM in serving people's health.
Medicine, Chinese Traditional/methods* ; Humans ; COVID-19/immunology* ; China ; Drugs, Chinese Herbal/therapeutic use* ; SARS-CoV-2

PURPOSE: The secondary damage of spinal cord injury (SCI) starts from the collapse of the blood spinal cord barrier (BSCB) to chronic and devastating neurological deficits. Thereby, the retention of the integrity and permeability of BSCB is well-recognized as one of the major therapies to promote functional recovery after SCI. Previous studies have demonstrated that activation of hypoxia inducible factor-1α (HIF-1α) provides anti-apoptosis and neuroprotection in SCI. Endogenous HIF-1α, rapidly degraded by prolylhydroxylase, is insufficient for promoting functional recovery. Dimethyloxalylglycine (DMOG), a highly selective inhibitor of prolylhydroxylase, has been reported to have a positive effect on axon regeneration. However, the roles and underlying mechanisms of DMOG in BSCB restoration remain unclear. Herein, we aim to investigate pathological changes of BSCB restoration in rats with SCI treated by DOMG and evaluate the therapeutic effects of DMOG. METHODS: The work was performed from 2022 to 2023. In this study, Allen's impact model and human umbilical vein endothelial cells were employed to explore the mechanism of DMOG. In the phenotypic validation experiment, the rats were randomly divided into 3 groups: sham group, SCI group, and SCI + DMOG group (10 rats for each). Histological analysis via Nissl staining, Basso-Beattie-Bresnahan scale, and footprint analysis was used to evaluate the functional recovery after SCI. Western blotting, TUNEL assay, and immunofluorescence staining were employed to exhibit levels of tight junction and adhesion junction of BSCB, HIF-1α, cell apoptosis, and endoplasmic reticulum (ER) stress. The one-way ANOVA test was used for statistical analysis. The difference was considered statistically significant at p < 0.05. RESULTS: In this study, we observed the expression of HIF-1α reduced in the SCI model. DMOG treatment remarkably augmented HIF-1α level, alleviated endothelial cells apoptosis and disruption of BSCB, and enhanced functional recovery post-SCI. Besides, the administration of DMOG offset the activation of ER stress induced by SCI, but this phenomenon was blocked by tunicamycin (an ER stress activator). Finally, we disclosed that DMOG maintained the integrity and permeability of BSCB by inhibiting ER stress, and inhibition of HIF-1α erased the protection from DMOG. CONCLUSIONS Our findings illustrate that the administration of DMOG alleviates the devastation of BSCB and HIF-1α-induced inhibition of ER stress.
Spinal Cord Injuries/pathology* ; Animals ; Apoptosis/drug effects* ; Amino Acids, Dicarboxylic/therapeutic use* ; Recovery of Function/drug effects* ; Rats ; Rats, Sprague-Dawley ; Hypoxia-Inducible Factor 1, alpha Subunit/metabolism* ; Male ; Spinal Cord/blood supply*

Objective:To report the results of national surveillance on the distribution and antimicrobial resistance profile of clinical Gram-negative bacteria isolates from bloodstream infections in China in 2022.Methods:The clinical isolates of Gram-negative bacteria from blood cultures in member hospitals of national bloodstream infection Bacterial Resistant Investigation Collaborative System（BRICS）were collected during January 2022 to December 2022. Antibiotic susceptibility tests were conducted by agar dilution or broth dilution methods recommended by Clinical and Laboratory Standards Institute（CLSI）. WHONET 5.6 and SPSS 25.0 software were used to analyze the data.Results:During the study period，9 035 strains of Gram-negative bacteria were collected from 51 hospitals，of which 7 895（87.4%）were Enterobacteriaceae and 1 140（12.6%）were non-fermenting bacteria. The top 5 bacterial species were Escherichia coli（ n=4 510，49.9%）， Klebsiella pneumoniae（ n=2 340，25.9%）， Pseudomonas aeruginosa（ n=534，5.9%）， Acinetobacter baumannii complex（ n=405，4.5%）and Enterobacter cloacae（ n=327，3.6%）. The ESBLs-producing rates in Escherichia coli， Klebsiella pneumoniae and Proteus spp. were 47.1%（2 095/4 452），21.0%（427/2 033）and 41.1%（58/141），respectively. The prevalence of carbapenem-resistant Escherichia coli（CREC）and carbapenem-resistant Klebsiella pneumoniae（CRKP）were 1.3%（58/4 510）and 13.1%（307/2 340）；62.1%（36/58）and 9.8%（30/307）of CREC and CRKP were resistant to ceftazidime/avibactam combination，respectively. The prevalence of carbapenem-resistant Acinetobacter baumannii（CRAB）complex was 59.5%（241/405），while less than 5% of Acinetobacter baumannii complex was resistant to tigecycline and polymyxin B. The prevalence of carbapenem-resistant Pseudomonas aeruginosa（CRPA）was 18.4%（98/534）. There were differences in the composition ratio of Gram-negative bacteria in bloodstream infections and the prevalence of main Gram-negative bacteria resistance among different regions，with statistically significant differences in the prevalence of CRKP and CRPA（ χ2=20.489 and 20.252， P<0.001）. The prevalence of CREC，CRKP，CRPA，CRAB，ESBLs-producing Escherichia coli and Klebsiella pneumoniae were higher in provinicial hospitals than those in municipal hospitals（ χ2=11.953，81.183，10.404，5.915，12.415 and 6.459， P<0.01 or <0.05），while the prevalence of CRPA was higher in economically developed regions（per capita GDP ≥ 92 059 Yuan）than that in economically less-developed regions（per capita GDP <92 059 Yuan）（ χ2=6.240， P=0.012）. Conclusions:The proportion of Gram-negative bacteria in bloodstream infections shows an increasing trend，and Escherichia coli is ranked in the top，while the trend of CRKP decreases continuously with time. Decreasing trends are noted in ESBLs-producing Escherichia coli and Klebsiella pneumoniae. Low prevalence of carbapenem resistance in Escherichia coli and high prevalence in CRAB complex have been observed. The composition ratio and antibacterial spectrum of bloodstream infections in different regions of China are slightly different，and the proportion of main drug resistant bacteria in provincial hospitals is higher than those in municipal hospitals.

With the rapid society development and broad recognition of "Healthy China", the demands for good life and health are increasing. Accordingly, the concept of "food and medicine homologous" have been attractive. The concept of "food and medicine homologous" has a long history in China, and is an essence of various ideas in traditional Chinese medicine, such as diet therapy, medicated diet, regimen and preventive treatment of disease, representing an important field in health science. Many studies have found that the active ingredients of "food and medicine homologous" substances are multiple types, multiple mechanisms and multiple targets, exerting their biological effects after oral administration and chemical or metabolic transformation. In this review, the chemical basis and biological principles of various "food and medicine homologous" substances were summarized as compounds, biological macromolecules and intestinal flora. By focusing on the intestinal flora, we discussed the detailed biological principles of several classic "food and medicine homologous" substances. The scientific significance of "food and medicine homologous" concept were also discussed. This review explores the concept of "food and medicine homologous" from the perspective of modern medicine, in order to provide insights for future drug development and human health.

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 monitor the antifungal resistance of clinical isolates of Candida spp.in the East China region.Methods MALDI-TOF MS or molecular methods were used to re-identify the strains collected from January 2018 to December 2022.Antifungal susceptibility testing was performed using the broth microdilution method.The susceptibility test results were interpreted according to the breakpoints of 2022 Clinical and Laboratory Standards Institute(CLSI)documents M27 M44s-Ed3 and M57s-Ed4.Results A total of 3 026 strains of Candida were collected,65.33％of which were isolated from sterile body sites,mainly from blood(38.86％)and pleural effusion/ascites(10.21％).The predominant species of Candida were Candida albicans(44.51％),followed by Candida parapsilosis complex(19.46％),Candida tropicalis(13.98％),Candida glabrata(10.34％),and other Candida species(0.79％).Candida albicans showed overall high susceptibility rates to the 10 antifungal drugs tested(the lowest rate being 93.62％).Only 2.97％of the strains showed dose-dependent susceptibility(SDD)to fluconazole.Candida parapsilosis complex had a SDD rate of 2.61％and a resistance rate of 9.42％to fluconazole,and susceptibility rates above 90％to other drugs.Candida glabrata had a SDD rate of 92.01％and a resistance rate of 7.99％to fluconazole,resistance rates of 32.27％and 48.24％to posaconazole and voriconazole non-wild-type strains(NWT),respectively,and susceptibility rates above 90％to other drugs.Candida tropicalis had resistance rates of 29.55％and 26.24％to fluconazole and voriconazole,respectively,resistance rates of 76.60％and 21.99％to posaconazole and echinocandins non-wild-type strains(NWT),and a resistance rate of 2.36％to echinocandins.Conclusions The prevalence and species distribution of Candida spp.in the East China region are consistent with previous domestic and international reports.Candida glabrata exhibits certain degree of resistance to fluconazole,while Candida tropicalis demonstrates higher resistance to triazole drugs.Additionally,echinocandins resistance has emerged in Candida albicans,Candida glabrata,Candida tropicalis,and Candida parapsilosis.

Aim To explore the mechanism of modified Wuzi Yanzong pill to reduce testicular toxicity of Tripterygium wilfordii by means of network pharmacolo-gy.Methods The effective chemical composition and target of modified Wuzi Yanzong Pill to reduce testicu-lar toxicity of Tripterygium wilfordii were analyzed by using multiple databases to understand the mechanism of action.Results The first five compounds of modi-fied Wuzi Yanzong pill are quercetin,sucrose,kaempferol,galactose and ellagic acid,respectively.The first five targets were TP53,SRC,EP300,MAPK3,STAT3;KEGG pathway enrichment analysis mainly concentrated in cancer pathway,lipid and atherosclero-sis,hepatitis B,apoptosis,diabetes complications AGE-RAGE signaling pathway,PI3K-Akt signaling pathway and other signaling pathways.Conclusions The ac-tive components of modified Wuzi Yanzong pill can re-duce the testicular toxicity of Tripterygium wilfordii mainly by interfering with TP53,SRC,EP300,MAPK3,STAT3 and other targets,regulating apoptosis,PI3K-Akt signaling pathway,diabetes complications AGE-RAGE signaling pathway,lipid metabolism and other pathways.

Nuclear medicine plays an indispensable role in the diagnosis,treatment,and prognosis of a wide range of diseases.Nuclear medicine using radionuclides for diagnosis has the advantages of accuracy,speed,high sensitivity and high resolution.Currently,several radionuclides play pivotal roles in disease diagnosis.This article primarily examines the clinical application and research of diagnostic radionuclides,including 18 F,89 Zr,68 Ga,99m Tc,131 I,123 I,and 11 C.The objective is to offer valuable insights for disease diagnosis and staging of diseases.