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.

Objective:To investigate the incidence and risk factors of deep vein thrombosis(DVT)in patients with rheumatoid arthritis(RA).Methods:The clinical data of RA patients who were hospi-talized in the Department of Rheumatology and Immunology of Aerospace Center Hospital from May 2015 to September 2021 was retrospectively analyzed,including demographic characteristics,concomitant diseases,laboratory examinations(blood routine,biochemistry,coagulation,inflammatory markers,rheumatoid factor,antiphospholipid antibodies and lupus anticoagulant,etc.)and treatment regimens.The patients were compared according to the presence or absence of DVT,and the t test,Mann-Whitney U test or Chi-square test were applied to screen for relevant factors for DVT,followed by Logistic regres-sion analysis to determine risk factors for DVT in patients with RA.Results:The incidence of DVT in the RA patients was 9.6％(31/322);the median age of RA in DVT group was significantly older than that in non-DVT group[64(54,71)years vs.50(25,75)years,P＜0.001];the level of disease activity score using 28 joints(DAS28)-erythrocyte sedimentation rate(ESR)in DVT group was higher than that in non-DVT group[5.2(4.5,6.7)vs.4.5(4.5,5.0),P＜0.001];the incidence of hypertension,chronic kidney disease,fracture or surgery history within 3 months,and varicose veins of the lower ex-tremities in DVT group was higher than that in non-DVT group(P＜0.001).The levels of hemoglobin and albumin in DVT group were significantly lower than that in non-DVT group(P=0.009,P=0.004),while the D-dimer level and rheumatoid factor positive rate in DVT group were significantly higher than that in non-DVT group(P＜0.001).The use rate of glucocorticoid in DVT group was higher than that in non-DVT group(P=0.009).Logistic regression analysis showed that the age(OR=1.093,P＜0.001),chronic kidney disease(OR=7.955,P=0.005),fracture or surgery history with-in 3 months(OR=34.658,P=0.002),DAS28-ESR(OR=1.475,P=0.009),and the use of glu-cocorticoid(OR=5.916,P=0.003)were independent risk factors for DVT in RA patients.Conclu-sion:The incidence of DVT in hospitalized RA patients was significantly increased,in addition to tradi-tional factors,such as age and chronic kidney disease,increased DAS28-ESR level and the use of glu-cocorticoid were also independent risk factors for DVT.

Bacterial biofilms gave rise to persistent infections and multi-organ failure, thereby posing a serious threat to human health. Biofilms were formed by cross-linking of hydrophobic extracellular polymeric substances (EPS), such as proteins, polysaccharides, and eDNA, which were synthesized by bacteria themselves after adhesion and colonization on biological surfaces. They had the characteristics of dense structure, high adhesiveness and low drug permeability, and had been found in many human organs or tissues, such as the brain, heart, liver, spleen, lungs, kidneys, gastrointestinal tract, and skeleton. By releasing pro-inflammatory bacterial metabolites including endotoxins, exotoxins and interleukin, biofilms stimulated the body’s immune system to secrete inflammatory factors. These factors triggered local inflammation and chronic infections. Those were the key reason for the failure of traditional clinical drug therapy for infectious diseases.In order to cope with the increasingly severe drug-resistant infections, it was urgent to develop new therapeutic strategies for bacterial-biofilm eradication and anti-bacterial infections. Based on the nanoscale structure and biocompatible activity, nanobiomaterials had the advantages of specific targeting, intelligent delivery, high drug loading and low toxicity, which could realize efficient intervention and precise treatment of drug-resistant bacterial biofilms. This paper highlighted multiple strategies of biofilms eradication based on nanobiomaterials. For example, nanobiomaterials combined with EPS degrading enzymes could be used for targeted hydrolysis of bacterial biofilms, and effectively increased the drug enrichment within biofilms. By loading quorum sensing inhibitors, nanotechnology was also an effective strategy for eradicating bacterial biofilms and recovering the infectious symptoms. Nanobiomaterials could intervene the bacterial metabolism and break the bacterial survival homeostasis by blocking the uptake of nutrients. Moreover, energy-driven micro-nano robotics had shown excellent performance in active delivery and biofilm eradication. Micro-nano robots could penetrate physiological barriers by exogenous or endogenous driving modes such as by biological or chemical methods, ultrasound, and magnetic field, and deliver drugs to the infection sites accurately. Achieving this using conventional drugs was difficult. Overall, the paper described the biological properties and drug-resistant molecular mechanisms of bacterial biofilms, and highlighted therapeutic strategies from different perspectives by nanobiomaterials, such as dispersing bacterial mature biofilms, blocking quorum sensing, inhibiting bacterial metabolism, and energy driving penetration. In addition, we presented the key challenges still faced by nanobiomaterials in combating bacterial biofilm infections. Firstly, the dense structure of EPS caused biofilms spatial heterogeneity and metabolic heterogeneity, which created exacting requirements for the design, construction and preparation process of nanobiomaterials. Secondly, biofilm disruption carried the risk of spread and infection the pathogenic bacteria, which might lead to other infections. Finally, we emphasized the role of nanobiomaterials in the development trends and translational prospects in biofilm treatment.

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.

Objective To understand the respiratory protection competency of staff in hospitals.Methods Staff from six hospitals of different levels and characteristics in Beijing were selected,including doctors,nurses,medical technicians,and servicers,to conduct knowledge assessment on respiratory protection competency.According to exposure risks of respiratory infectious diseases,based on actual cases and daily work scenarios,content of respira-tory protection competency assessment was designed from three aspects:identification of respiratory infectious di-seases,transmission routes and corresponding protection requirements,as well as correct selection and use of masks.The assessment included 6,6,and 8 knowledge points respectively,with 20 knowledge points in total,all of which were choice questions.For multiple-choice questions,full marks,partial marks,and no mark were given respective-ly if all options were correct,partial options were correct and without incorrect options,and partial options were correct but with incorrect options.Difficulty and discrimination analyses on question of each knowledge point was conducted based on classical test theory.Results The respiratory protection competency knowledge assessment for 326 staff members at different risk levels in 6 hospitals showed that concerning the 20 knowledge points,more than 60％participants got full marks for 6 points,while the proportion of full marks for other questions was relatively low.Less than 10％participants got full marks for the following 5 knowledge points:types of airborne diseases,types of droplet-borne diseases,conventional measures for the prevention and control of healthcare-associated infec-tion with respiratory infectious diseases,indications for wearing respirators,and indications for wearing medical protective masks.Among the 20 knowledge questions,5,1,and 14 questions were relatively easy,medium,and difficult,respectively;6,1,4,and 9 questions were with discrimination levels of ≥0.4,0.30-0.39,0.20-0.29,and ≤0.19,respectively.Conclusion There is still much room for hospital staff to improve their respiratory protection competency,especially in the recognition of diseases with different transmission routes and the indications for wearing different types of masks.

Octapeptin has strong antibacterial activity against Gram-negative bacteria such as Escherichia coli, Klebsiella pneumoniae and Acinetobacter baumannii, while it also has activity against some Gram-positive bacteria. This study used natural octapeptin A3 and B3 as lead compounds for structural modification. Twenty-one peptide derivatives (including A3 and B3) containing eight amino acid residues were prepared by solid-phase synthesis, and evaluated for antibacterial activity and renal cytotoxicity. Among them, three compounds 6, 7 and 17 exhibited broad-spectrum antibacterial activity and significantly enhanced the activity for Gram-positive bacteria while maintaining the activity of Gram-negative bacteria. Several compounds improved the activity for Pseudomonas aeruginosa. Compound 7 was active against all test strains and had relatively low renal cytotoxicity. The results provide a basis for the further development of novel polypeptide antibiotics.

Animals ; Macaca mulatta ; Optic Disk ; Glaucoma ; Craniocerebral Trauma ; Intraocular Pressure ; Low Tension Glaucoma

Objective:To explore the application value and surgical experience of neuroendoscopic resection for pediatric patients with cerebellar tumors.Methods:This was a case series study.The clinical data and outcomes of 30 pediatric patients with cerebellar tumors treated through neuroendoscopic surgery in the Department of Neurosurgery, the Guizhou Hospital of Shanghai Children′s Medical Center and Guizhou Provincial People′s Hospital from January 2021 to January 2024 were retrospectively analyzed.Results:Twenty-six patients underwent total resection, 3 patients underwent subtotal resection, and 1 patient underwent biopsy.Postoperative pathological findings showed 9 cases of medulloblastoma, 3 cases of ependymoma, 17 cases of astrocytoma (5 cases of World Health Organization Grade Ⅰ, 3 cases of Grade Ⅱ, and 9 cases of Grade Ⅲ), and 1 case of cerebellar benign lesion.During the perioperative period, malignant arrhythmia occurred and induced death in 1 case, cerebellar mutism occurred in 12 cases, and ataxia occurred in 22 cases.During the 1-36 months of follow-up, 2 cases developed communicating hydrocephalus at the 2 nd and the 6 th month, respectively, and improved after ventriculoperitoneal shunt; cerebellar mutism was relieved to varying degrees after an average postoperative follow-up period of (115±23) days(46-194 days), and ataxia was alleviated after an average postoperative follow-up period of (127±42) days(27-173 days).Tumors relapsed in 5 cases during the last follow-up. Conclusions:Neuroendoscopy provides an alternative to the microscope for experienced operators to achieve the surgical exposure requirements during the resection of pediatric cerebellar vermis tumors.

177Lu-prostate specific membrane antigen(PSMA)radio-ligand therapy has been approved abroad for advanced prostate cancer and has been in several clinical trials in China.Based on domestic clinical practice and experimental data and referred to international experience and viewpoints,the expert group forms a consensus on the clinical application of 177Lu-PSMA radio-ligand therapy in prostate cancer to guide clinical practice.

Objective To investigate the mechanism of the interaction between Wnt/β-catenin signaling and the epithelial mesenchymal transition(EMT)pathway in mediating sunitinib-resistance in renal cancer cells.Methods The sunitinib-resistant kidney cancer cell lines were constructed by stepwise increase in drug concentrations method with sunitinib,and were divided into resistance group,lv-NC group and lv-Twist group,and human kidney cancer cell lines were selected as normal group.The normal and drug-resistant groups were treated with conventional culture;the lv-NC group was treated with 40 μL of lv-NC lentivirus supernatant containing 2.25 × 108 TU·mL-1 for 72 h,and the lv-Twist group was treated with 50 μL of Twist lentivirus supernatant containing 1.64 × 108 TU·mL-1 for 72 h.The apoptosis ability was detected by flow cytometry;the cell migration ability was detected by cell scratch assay;the cell invasion ability was detected by Transwell assay;and the protein expression levels of Wnt1,β-catenin and Twist were detected by Western blotting assay.Results The apoptosis rates of control,resistant,lv-NC and lv-Twist groups were(17.60±0.59)％,(8.61±0.34)％,(8.60±0.40)％and(3.10±0.34)％;the migration rates were(14.10±0.12)％,(27.64±0.41)％,(14.24±0.45)％and(32.74±2.53)％;the number of invading cells was 27.33±1.15,53.33±1.53,46.00±2.65 and 99.33±2.52;the relative expression levels of Wnt1 protein were 0.10±0.01,0.96±0.06,0.39±0.03 and 3.09±0.31;the relative expression levels of β-catenin protein were 0.39±0.01,1.48±0.16,0.81±0.05 and 1.24±0.14;the relative expression levels of Twist protein were 0.10±0.02,0.91±0.04,0.39±0.03 and 3.09±0.31,respectively.The differences of above indexes were statistically significant between the resistant group and the normal group,and between the lv-Twist group and the lv-NC group(all P＜0.05).Conclusion Twist(EMT related protein)mediates sunitinib resistance in renal cell carcinoma by interacting with Wnt/β-catenin signaling pathway.