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.

Heat acclimation provides cardiovascular protection in high-temperature environments through multilevel mechanisms; however, the complete molecular basis of its effects remains unclear. In this paper, we systematically review the effects of heat acclimation on blood volume, vascular function, cardiac structure, energy metabolism, and anti-stress regulation, revealing their potential mechanisms in cardiovascular adaptive protection. We also summarizes the multilevel responses induced by heat stress and heat acclimation, including the modulatory effects of heat acclimation on heat shock proteins (HSPs), hypoxia inducible factor 1 (HIF-1), and apoptotic pathways. Additionally, we highlights the comprehensive protective effects of heat acclimation across various stressors (e.g., hypoxia, heat stress). This review provides a significant physiological basis for cardiovascular disease management and sports medicine, emphasizing the potential application of heat acclimation in response to multiple stressors and supporting its role as an effective tool in cardiovascular health management and stress protection interventions.
Humans ; Acclimatization/physiology* ; Hot Temperature ; Heat-Shock Proteins/metabolism* ; Animals ; Heat-Shock Response/physiology* ; Hypoxia-Inducible Factor 1/metabolism* ; Apoptosis/physiology*

Eight amide alkaloids(1-8) were isolated from the 70% ethanol extract of Cannabis Fructus using silica gel column chromatography, MCI column chromatography, and semi-preparative high-performance liquid chromatography(HPLC). Their structures were identified as hempspiramide A(1), N-[(4-hydroxyphenyl)ethyl]formamide(2), N-acetyltyramide(3), N-trans-p-coumaroyltyramine(4), N-trans-caffeoyltyramine(5), N-trans-feruloyltyramine(6), N-cis-p-coumaroyltyramine(7), N-cis-feruloyltyramine(8) by using spectroscopic methods such as NMR and MS. Among these compounds, compound 1 was a new amide alkaloid, while compounds 2 and 3 were isolated from Cannabis Fructus for the first time. Some of the isolates were assayed for their α-glucosidase inhibitory activity. Compounds 5-7 displayed significant inhibitory activity against α-glucosidase with IC_(50) values ranging from 1.07 to 4.63 μmol·L~(-1).
Cannabis/chemistry* ; Alkaloids/pharmacology* ; Amides/isolation & purification* ; Drugs, Chinese Herbal/isolation & purification* ; Fruit/chemistry* ; Molecular Structure ; alpha-Glucosidases/chemistry* ; Chromatography, High Pressure Liquid

Mycophenolic acid (MPA), the active moiety of both mycophenolate mofetil (MMF) and enteric-coated mycophenolate sodium (EC-MPS), serves as a primary immunosuppressant for maintaining solid organ transplants. Therapeutic drug monitoring (TDM) enhances treatment outcomes through tailored approaches. This study aimed to develop an evidence-based guideline for MPA TDM, facilitating its rational application in clinical settings. The guideline plan was drawn from the Institute of Medicine and World Health Organization (WHO) guidelines. Using the Delphi method, clinical questions and outcome indicators were generated. Systematic reviews, Grading of Recommendations Assessment, Development, and Evaluation (GRADE) evidence quality evaluations, expert opinions, and patient values guided evidence-based suggestions for the guideline. External reviews further refined the recommendations. The guideline for the TDM of MPA (IPGRP-2020CN099) consists of four sections and 16 recommendations encompassing target populations, monitoring strategies, dosage regimens, and influencing factors. High-risk populations, timing of TDM, area under the curve (AUC) versus trough concentration (C₀), target concentration ranges, monitoring frequency, and analytical methods are addressed. Formulation-specific recommendations, initial dosage regimens, populations with unique considerations, pharmacokinetic-informed dosing, body weight factors, pharmacogenetics, and drug‍-‍drug interactions are covered. The evidence-based guideline offers a comprehensive recommendation for solid organ transplant recipients undergoing MPA therapy, promoting standardization of MPA TDM, and enhancing treatment efficacy and safety.
Mycophenolic Acid/administration & dosage* ; Drug Monitoring/methods* ; Humans ; Organ Transplantation ; Immunosuppressive Agents/administration & dosage* ; Delphi Technique

ObjectiveTo explore the syndrome elements and evolving patterns of patients with hepatitis B virus-related acute on chronic liver failure （HBV-ACLF） at different stages. MethodsClinical information of 1,058 hospitalized HBV-ACLF patients， including 618 in the early stage， 355 in the middle stage， and 85 in the late stage， were collected from 18 clinical centers across 12 regions nationwide from January 1， 2012 to February 28， 2015. The “Hepatitis B-related Chronic and Acute Liver Failure Chinese Medicine Clinical Questionnaire” were designed to investigate the basic information of the patients， like the four diagnostic information （including symptoms， tongue， pulse） of traditional Chinese medicine （TCM）， and to count the frequency of the appearance of the four diagnostic information. Factor analysis and cluster analysis were employed to determine and statistically analyze the syndrome elements and patterns of HBV-ACLF patients at different stages. ResultsThere were 76 four diagnostic information from 1058 HBV-ACLF patients， and 53 four diagnostic information with a frequency of occurrence ≥ 5% were used as factor analysis entries， including 36 symptom information， 12 tongue information， and 5 pulse information. Four types of TCM patterns were identified in HBV-ACLF， which were liver-gallbladder damp-heat pattern， qi deficiency and blood stasis pattern， liver-kidney yin deficiency pattern， and spleen-kidney yang-deficiency pattern. In the early stage， heat （39.4%， 359/912） and dampness （27.5%， 251/912） were most common， and the pattern of the disease was dominated by liver-gallbladder damp-heat pattern （74.6%， 461/618）； in the middle stage， dampness （30.2%， 187/619） and blood stasis （20.7%， 128/619） were most common， and the patterns of the disease were dominated by liver-gallbladder damp-heat pattern （53.2%， 189/355）， and qi deficiency and blood stasis pattern （27.6%， 98/355）； and in the late stage， the pattern of the disease was dominated by qi deficiency （26.3%， 40/152） and yin deficiency （20.4%， 31/152）， and the patterns were dominated by qi deficiency and blood stasis pattern （36.5%， 31/85）， and liver-gallbladder damp-heat pattern （25.9%， 22/85）. ConclusionThere are significant differences in the distribution of syndrome elements and patterns at different stages of HBV-ACLF， presenting an overall trend of evolving patterns as "from excess to deficiency， transforming from excess to deficiency"， which is damp-heat → blood stasis → qi-blood yin-yang deficiency.

Objective To evalute the drug resistance characteristics of tuberculosis(TB)patients of all ages in Guangdong Province during 2014-2020,and provide prevention and treatment strategies of tuberculosis.Method We used 39,048 clinical isolates of Mycobacterium tuberculosis(MTB)belonging to patients with confirmed TB from 2014 to 2020,from 32 TB drug-resistant surveillance sites in Guangdong Province,and we retrospectively analyzed the laboratories data of patients with drug-resistant TB,and grouped patients by age and region,to explore the trend of drug-resistance of MTB clinical isolates,the trend and incidence differences of multi-resistant TB(including monodrug-resistant TB(MR-TB),polydrug-resistant TB(PDR-TB),multidrug-resistant TB(MDR-TB)and exten-sively drug-resistant TB(XDR-TB)),and resistance characteristics of MTB clinical isolates to drugs in focus(rifam-picin and ofloxacin).Result The differences in the resistance rates of MTB clinical isolates to nine antituberculosis drugs among patients at 32 TB drug resistance surveillance sites in Guangdong Province from 2014 to 2020 were not statistically significant(P>0.05).The rates of MR-TB,PDR-TB,MDR-TB,XDR-TB,and total resistance isolates of MTB clinical isolates were 14.46%,5.16%,5.16%,4.58%,and 1.29%,respectively.he pediatric group had a higher MR rate(15.4%)than the adult and geriatric groups,while the adult and geriatric groups had higher MDR rates(5.0%and 5.0%,respectively).The geriatric group also had a higher XDR rate(2.1%),with statistically significant differences(P<0.001).The rates of MR-TB(14.8%),PDR-TB(5.3%),MDR-TB(4.7%),XDR-TB(1.4%),ofloxacin resistance(11.33%)and rifampicin resistance(6.92%)of MTB clinical isolates were higher in patients from the Pearl River Delta than in other regions of Guangdong Province,with statistically significant differ-ences(P<0.001).Conclusion According to the data from the surveillance sites,the epidemiological trend of drug-resistant TB in Guangdong Province is leveling off during the period 2014-2020.However,the incidence of drug-resistant TB is higher in specific populations(e.g.children and the elderly),and the incidence of drug-resistant TB and the rate of drug resistance to drugs in focus are higher in the Pearl River Delta than in other regions of Guang-dong Province,necessitating further investigation and the development of novel prevention and control strategies.

Monosodium urate (MSU)-induced the gouty arthritis (GA) model was used to investigate the effect of Nod-like receptor protein 3 (NLRP3) inhibitor N14 in alleviating GA. Firstly, the effect of NLRP3 inhibitor N14 on the viability of mouse monocyte macrophage J774A.1 was examined by the cell counting kit-8 (CCK-8) assay. The expression of mature interleukin 1β (IL-1β) and cysteinyl aspartate specific proteinase-1 (caspase-1) p20 in the cell supernatant and the expression of NLRP3, caspase-1 and pro-IL-1β proteins in the cell lysates was detected by Western blot for the inhibitory effect of N14 on the MSU-induced NLRP3 inflammasome activation in J774A.1 cells. Animal behavioral tests were used to detect redness, swelling, heat and pain in mice with gouty arthritis. Hematoxylin-eosin (H&E) staining revealed pathologic changes and inflammatory infiltration in foot sections. Protein expression of NLRP3, caspase-1, and pro-IL-1β in mouse hind paw tissues were assessed by Western blot. The effect of N14 on the plasma levels of alanine transaminase (ALT), aspartate transaminase (AST), creatinine (CRE), urea, and uric acid (UA) was investigated by the MSU-induced gouty arthritis model in mice. All animal experiments in this paper were approved by the Scientific Ethics Review Board of Qingdao Marine Biomedical Research Institute (grant No. E-MBWNL-2024-20). The experimental results showed that N14 did not exhibit cytotoxicity in mouse monocyte macrophage J774A.1 cells at concentrations up to 100 μmol·L^-1, and N14 effectively prevented MSU-induced activation of NLRP3 inflammasome. In the mouse gouty arthritis model, N14 significantly ameliorated the redness, swelling, heat and pain caused by GA, and down-regulated the levels of NLRP3 inflammasome-associated proteins in mouse hind paw tissues. Meanwhile, N14 appeared to be well tolerated, as it did not significantly affect various biochemical indices in mouse plasma. In conclusion, N14 effectively alleviated GA in mice by inhibiting the NLRP3 inflammasome pathway, which is important for both prevention and treatment of related diseases.

Objective To monitor the susceptibility of clinical isolates to antimicrobial agents in tertiary hospitals in major regions of China in 2022.Methods Clinical isolates from 58 hospitals in China were tested for antimicrobial susceptibility using a unified protocol based on disc diffusion method or automated testing systems.Results were interpreted using the 2022 Clinical &Laboratory Standards Institute(CLSI)breakpoints.Results A total of 318 013 clinical isolates were collected from January 1,2022 to December 31,2022,of which 29.5％were gram-positive and 70.5％were gram-negative.The prevalence of methicillin-resistant strains in Staphylococcus aureus,Staphylococcus epidermidis and other coagulase-negative Staphylococcus species(excluding Staphylococcus pseudintermedius and Staphylococcus schleiferi)was 28.3％,76.7％and 77.9％,respectively.Overall,94.0％of MRSA strains were susceptible to trimethoprim-sulfamethoxazole and 90.8％of MRSE strains were susceptible to rifampicin.No vancomycin-resistant strains were found.Enterococcus faecalis showed significantly lower resistance rates to most antimicrobial agents tested than Enterococcus faecium.A few vancomycin-resistant strains were identified in both E.faecalis and E.faecium.The prevalence of penicillin-susceptible Streptococcus pneumoniae was 94.2％in the isolates from children and 95.7％in the isolates from adults.The resistance rate to carbapenems was lower than 13.1％in most Enterobacterales species except for Klebsiella,21.7％-23.1％of which were resistant to carbapenems.Most Enterobacterales isolates were highly susceptible to tigecycline,colistin and polymyxin B,with resistance rates ranging from 0.1％to 13.3％.The prevalence of meropenem-resistant strains decreased from 23.5％in 2019 to 18.0％in 2022 in Pseudomonas aeruginosa,and decreased from 79.0％in 2019 to 72.5％in 2022 in Acinetobacter baumannii.Conclusions The resistance of clinical isolates to the commonly used antimicrobial agents is still increasing in tertiary hospitals.However,the prevalence of important carbapenem-resistant organisms such as carbapenem-resistant K.pneumoniae,P.aeruginosa,and A.baumannii showed a downward trend in recent years.This finding suggests that the strategy of combining antimicrobial resistance surveillance with multidisciplinary concerted action works well in curbing the spread of resistant bacteria.

Objective To investigate the distribution and antimicrobial resistance profiles of the common pathogens isolated from urine from 2015 to 2021 in the CHINET Antimicrobial Resistance Surveillance Program.Methods The bacterial strains were isolated from urine and identified routinely in 51 hospitals across China in the CHINET Antimicrobial Resistance Surveillance Program from 2015 to 2021.Antimicrobial susceptibility was determined by Kirby-Bauer method,automatic microbiological analysis system and E-test according to the unified protocol.Results A total of 261 893 nonduplicate strains were isolated from urine specimen from 2015 to 2021,of which gram-positive bacteria accounted for 23.8％(62 219/261 893),and gram-negative bacteria 76.2％(199 674/261 893).The most common species were E.coli(46.7％),E.faecium(10.4％),K.pneumoniae(9.8％),E.faecalis(8.7％),P.mirabilis(3.5％),P.aeruginosa(3.4％),SS.agalactiae(2.6％),and E.cloacae(2.1％).The strains were more frequently isolated from inpatients versus outpatients and emergency patients,from females versus males,and from adults versus children.The prevalence of ESBLs-producing strains in E.coli,K.pneumoniae and P.mirabilis was 53.2％,52.8％and 37.0％,respectively.The prevalence of carbapenem-resistant strains in E.coli,K.pneumoniae,P.aeruginosa and A.baumannii was 1.7％,18.5％,16.4％,and 40.3％,respectively.Lower than 10％of the E.faecalis isolates were resistant to ampicillin,nitrofurantoin,linezolid,vancomycin,teicoplanin and fosfomycin.More than 90％of the E.faecium isolates were ressitant to ampicillin,levofloxacin and erythromycin.The percentage of strains resistant to vancomycin,linezolid or teicoplanin was＜2％.The E.coli,K.pneumoniae,P.aeruginosa and A.baumannii strains isolated from ICU inpatients showed significantly higher resistance rates than the corresponding strains isolated from outpatients and non-ICU inpatients.Conclusions E.coli,Enterococcus and K.pneumoniae are the most common pathogens in urinary tract infection.The bacterial species and antimicrobial resistance of urinary isolates vary with different populations.More attention should be paid to antimicrobial resistance surveillance and reduce the irrational use of antimicrobial agents.

Objective To understand the distribution and changing resistance profiles of clinical isolates of Enterococcus in hospitals across China from 2015 to 2021.Methods Antimicrobial susceptibility testing was conducted for the clinical isolates of Enterococcus according to the unified protocol of CHINET program by automated systems,Kirby-Bauer method,or E-test strip.The results were interpreted according to the Clinical & Laboratory Standards Institute(CLSI)breakpoints in 2021.WHONET 5.6 software was used for statistical analysis.Results A total of 124 565 strains of Enterococcus were isolated during the 7-year period,mainly including Enterococcus faecalis(50.7％)and Enterococcus faecalis(41.5％).The strains were mainly isolated from urinary tract specimens(46.9％±2.6％),and primarily from the patients in the department of internal medicine,surgery and ICU.E.faecium and E.faecalis strains showed low level resistance rate to vancomycin,teicoplanin and linezolid(≤3.6％).The prevalence of vancomycin-resistant E.faecalis and E.faecium was 0.1％and 1.3％,respectively.The prevalence of linezolid-resistant E.faecalis increased from 0.7％in 2015 to 3.4％in 2021,while the prevalence of linezolid-resistant E.faecium was 0.3％.Conclusions The clinical isolates of Enterococcus were still highly susceptible to vancomycin,teicoplanin,and linezolid,evidenced by a low resistance rate.However,the prevalence of linezolid-resistant E.faecalis was increasing during the 7-year period.It is necessary to strengthen antimicrobial resistance surveillance to effectively identify the emergence of antibiotic-resistant bacteria and curb the spread of resistant pathogens.