Rheumatoid arthritis （RA） is a chronic autoimmune disease characterized by synovitis as its pathological basis. Although current therapeutic drugs can alleviate symptoms， they are often accompanied by a high risk of side effects. In recent years， the use of flavonoids from traditional Chinese medicine （TCM） in the treatment of RA has garnered significant attention. Studies have shown that the mechanisms by which flavonoids treat RA include inhibiting the release of pro-inflammatory factors， regulating multiple cellular signaling pathways， alleviating oxidative stress， modulating immune system functions， inhibiting bone destruction， and suppressing angiogenesis. Due to their notable anti-inflammatory， antioxidant， and immunomodulatory activities， flavonoids hold promise as potential therapeutic agents for RA. A substantial number of articles in this field have been published. By reviewing Chinese and international literature and applying bibliometric and visual analysis using CiteSpace， this paper explored research hotspots and frontiers in this field， systematically reviewed the structures and anti-RA mechanisms of TCM flavonoids， provided a theoretical basis for their use in RA treatment and clinical applications， and offered new perspectives and references for the discovery of novel TCM-based anti-RA drugs.

Rheumatoid arthritis （RA） is a chronic autoimmune disease characterized by synovitis as its pathological basis. Although current therapeutic drugs can alleviate symptoms， they are often accompanied by a high risk of side effects. In recent years， the use of flavonoids from traditional Chinese medicine （TCM） in the treatment of RA has garnered significant attention. Studies have shown that the mechanisms by which flavonoids treat RA include inhibiting the release of pro-inflammatory factors， regulating multiple cellular signaling pathways， alleviating oxidative stress， modulating immune system functions， inhibiting bone destruction， and suppressing angiogenesis. Due to their notable anti-inflammatory， antioxidant， and immunomodulatory activities， flavonoids hold promise as potential therapeutic agents for RA. A substantial number of articles in this field have been published. By reviewing Chinese and international literature and applying bibliometric and visual analysis using CiteSpace， this paper explored research hotspots and frontiers in this field， systematically reviewed the structures and anti-RA mechanisms of TCM flavonoids， provided a theoretical basis for their use in RA treatment and clinical applications， and offered new perspectives and references for the discovery of novel TCM-based anti-RA drugs.

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.

Enterobacterales are important pathogens responsible for hospital-acquired infections and can cause various severe infectious diseases. Since their first report, extended-spectrum β-lactamase-producing Enterobacterales(ESBL-E) have become widely prevalent worldwide. These strains often exhibit multidrug resistance, significantly increasing the risk of treatment failure and patient mortality. In China, the prevention and control of ESBL-E face numerous challenges, including high prevalence rates, significant regional distribution disparities, uneven laboratory testing capabilities, and variations in antimicrobial stewardship and prescribing practices. To address these issues, Professors Zhuo Chao, Xu Yingchun and Yu Yunsong initiated the developmentof the Expert Consensus on Clinical Management Strategies for Infections Caused by Extended-Spectrum β-Lactamase-Producing Enterobacterales (2025), in collaboration with multidisciplinary experts. This consensus systematically reviews the global and domestic epidemiological characteristics of ESBL-E, clinical laboratory detection techniques, treatment principles and key therapeutic agents, as well as infection prevention and control measures. Furthermore, it elaborates on the microbiological features and stratified treatment strategies for different infection sources (including bloodstream infections, intracranial infections, respiratory and mediastinal infections, intra-abdominal infections, and urinary tract infections) and special populations (such as neutropenic patients with fever, emergency patients, and pediatric patients). The consensus aims to enhance the detection capacity of clinical laboratories for ESBL-E, standardize diagnosis and treatment strategies in healthcare settings, and provide scientific guidance to curb the spread of ESBL-E in China, thereby reducing associated morbidity and mortality.

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

ObjectiveMyelodysplastic syndromes （MDS） is a group of clonal hematopoietic stem cell disorders，and this study aims to investigate the expression of hypoxia-inducible factor-1α（HIF-1α） in the bone marrow cells of patients with MDS and its correlation with the clinical features of MDS，the therapeutic efficacy of arsenic-containing Chineseherbal compound，and the survival prognosis. MethodAccording to the inclusion and exclusion criteria，27 MDS patients treated with arsenic-containing Chinese herbal compound in the Department of Hematology，Xiyuan Hospital，China Academy of Chinese Medical Sciences from January 2022 to September 2022 were included，and their bone marrow samples were collected by myelotomy. HIF-1α expression level in bone marrow cells was detected by real-time polymerase chain reaction （PCR） to analyze its correlation with clinical features，and logistic and Cox regression was used to analyze the risk factors affecting the efficacy and prognostic survival of MDS patients. ResultThe HIF-1α mRNA expression level was lower in bone marrow cells of MDS patients than in healthy subjects. HIF-1α was positively correlated with the degree of myelodysplasia（r=0.384，P<0.05） and bone marrow granulocytic system%（G%）（r=0.560，P<0.01）. Logistic regression showed that HIF-1α was a risk factor for the prognosis in the follow-up of the efficacy of treatment（P<0.05）and Cox regression showed that HIF-1α was an independent factor affecting the survival prognosis of MDS patients ［odds ratio（OR）=398.968，95% confidence interval（CI）（1.281，116 858.743），P<0.05］. ConclusionThe level of HIF-1α expression in bone marrow cells of MDS patients was closely related to the degree of clinical myelodysplasia and G%，and HIF-1α was a risk factor for the efficacy for and survival prognosis of MDS patients.

Objective:To observe the antidepressant effect of Tongdu Qishen electroacupuncture method; To explore its mechanism of regulating the oxidative stress pathway of protein kinase C (PKC)/reduced coenzymeⅡ (NADPH) in depression model rats.Methods:Totally 32 SD rats were divided into control group, model group, Tongdu Qishen electroacupuncture group and escitalopram group according to random number table method, with 8 rats in each group. The model of depression was established by chronic unpredictable stress except control group. After the start of modeling, Tongdu Qishen electroacupuncture group was treated with electroacupuncture every day, 15 min/time/day; escitalopram group was given 30 mg/kg intragastric intervention. 1 day before the start of the experiment and the 28th day of the experiment, the growth of body mass was observed, and sugar preference experiment and open field experiment were performed. The protein expression levels of protein kinase C α (PKC α), p47phox, t and RAS related C3 botulinum toxin substrate 1 (Rac1) in hypothalamus were detected by Western blot, and the positive area ratio of NOX2 protein in hypothalamus was detected by immunofluorescence technique; ROS content in hypothalamus was detected using DCFH-DA fluorescent probe technique.Results:Compared with the model group, the Tongdu Qishen electroacupuncture group and the escitalopram group showed the body mass growth ( P<0.01) and sugar preference index increased ( P<0.01), and the moving distance ( P<0.05) and residence time ( P<0.01) in the central area of the open field experiment were longer; the protein expression levels of hypothalamic PKC α, p47phox and Rac1 decreased ( P<0.05 or P<0.01), the positive area ratio of NOX2 protein decreased ( P<0.05), and the level of ROS also decreased significantly ( P<0.01) in Tongdu Qishen electroacupuncture group and escitalopram group. Conclusion:Tongdu Qishen electroacupuncture group can improve the behavior of depressed rats, inhibit the oxidative stress response of PKC/NADPH pathway, and reduce the production of ROS, thereby reducing the brain damage caused by oxidative stress, and improving the symptoms of depression.

Objective To make an epidemiological investigation on traditional Chinese medicine(TCM)dampness syndrome manifestations in the population at risk of cerebrovascular diseases in Guangdong area.Methods A cross-sectional study was conducted to analyze the clinical data related to the risk of cerebrovascular diseases in 330 Guangdong permanent residents.The diagnosis of dampness syndrome,quantitative scoring of dampness syndrome and rating of the risk of stroke were performed for the investigation of the distribution pattern of dampness syndrome and its influencing factors.Results(1)A total of 306(92.73%)study subjects were diagnosed as dampness syndrome.The percentage of dampness syndrome in the risk group was 93.82%(258/275),which was slightly higher than that of the healthy group(48/55,87.27%),but the difference was not statistically significant(χ2 = 2.91,P = 0.112).The quantitative score of dampness syndrome in the risk group was higher than that of the healthy group,and the difference was statistically significance(Z =-2.24,P = 0.025).(2)Among the study subjects at risk of cerebrovascular disease,evaluation time(χ2 = 26.11,P = 0.001),stroke risk grading(χ2= 8.85,P = 0.031),and history of stroke or transient ischemic attack(TIA)(χ2 = 9.28,P = 0.015)were the factors influencing the grading of dampness syndrome in the population at risk of cerebrovascular disease.Conclusion Dampness syndrome is the common TCM syndrome in the population of Guangdong area.The manifestations of dampness syndrome are more obvious in the population with risk factors of cerebrovascular disease,especially in the population at high risk of stroke,and in the population with a history of stroke or TIA.The assessment and intervention of dampness syndrome should be taken into account for future project of stroke prevention in Guangdong.

Objective To summarize the epidemiological and clinical features of infectious diseases of the central nervous system(CNS)by a single-center analysis.Methods A retrospective analysis was conducted on the data of 1247 cases of CNS infectious diseases diagnosed and treated in the First Medical Center of PLA General Hospital from 2001 to 2020.Results The data for this group of CNS infectious diseases by disease type in descending order of number of cases were viruses 743(59.6％),Mycobacterium tuberculosis 249(20.0％),other bacteria 150(12.0％),fungi 68(5.5％),parasites 18(1.4％),Treponema pallidum 18(1.4％)and rickettsia 1(0.1％).The number of cases increased by 177 cases(33.1％)in the latter 10 years compared to the previous 10 years(P<0.05).No significant difference in seasonal distribution pattern of data between disease types(P>0.05).Male to female ratio is 1.87︰1,mostly under 60 years of age.Viruses are more likely to infect students,most often at university/college level and above,farmers are overrepresented among bacteria and Mycobacterium tuberculosis,and more infections of Treponema pallidum in workers.CNS infectious diseases are characterized by fever,headache and signs of meningeal irritation,with the adductor nerve being the more commonly involved cranial nerve.Matagenomic next-generation sequencing improves clinical diagnostic capabilities.The median hospital days for CNS infectious diseases are 18.00(11.00,27.00)and median hospital costs are ￥29,500(￥16,000,￥59,200).The mortality rate from CNS infectious diseases is 1.6％.Conclusions The incidence of CNS infectious diseases is increasing last ten years,with complex clinical presentation,severe symptoms and poor prognosis.Early and accurate diagnosis and standardized clinical treatment can significantly reduce the morbidity and mortality rate and ease the burden of disease.

Objective:To explore the current situation of binary coping in patients with perimenopausal syndrome and analyze its influencing factors, in order to provide a basis for improving the level of binary coping.Methods:Using convenience sampling method, a total of 210 patients with perimenopausal syndrome and their spouses from the First Affiliated Hospital of Heilongjiang University of Traditional Chinese Medicine were cross-sectional surveyed by a general data questionnaire, the Binary Coping Scale, and the Modified Kupperman Score Scale. The influencing factors of binary coping level in patients with perimenopausal syndrome were explored by univariate analysis and variance decomposition model analysis.Results:A total of 200 valid questionnaires were retrieved.The patients aged (50.52 ± 2.89) years old. The binary coping score was (79.64 ± 22.74) points. The variance decomposition model analysis showed that marriage age, type of medical insurance, number of children, education level, family monthly income, spouse′s education level, presence of major comorbidities in spouse, modified Kupperman score, presence of generalized anxiety in spouse were the main influencing factors of binary coping in patients with perimenopausal syndrome (all P<0.05). Conclusions:The binary coping scores of patients with perimenopausal syndrome are lower than normal, and considering the influence and involvement of patients' spouses, nursing staff should pay special attention to patients who are married relatively early, have more children, have lower education levels, and have lower family monthly incomes. Additionally, attention should be given to spouses who experience widespread anxiety, have a lower level of education, and suffer from major chronic diseases. By developing and implementing comprehensive intervention measures aimed at improving the Kupperman score and the level of binary coping, both parties can be encouraged to support each other more effectively, thereby improving the marital relationships of patients during the perimenopausal period.