ObjectiveTo explore the mechanism of Yishen Qubi Tongluo Formula （益肾祛痹通络方， YQTF） in the treatment of rheumatoid arthritis（RA）. MethodsNetwork pharmacology was employed to retrieve and screen the active components and potential targets of YQTF as well as RA-related targets using databases including TCMSP， BATMAN， ETCM and GEO. The intersection of targets related to active components and RA-related targets was identified， and a protein-protein interaction （PPI） network was constructed. Gene Ontology （GO） functional enrichment analysis and Kyoto Encyclopedia of Genes and Genomes （KEGG） pathway enrichment analysis were performed， and a drug-active component-common target network of YQTF in the treatment of RA was established. The core components of YQTF were molecularly docked with key targets. Human rheumatoid arthritis synovial fibroblast cell line MH7A was divided into blank group， model group， methotrexate group and YQTF group. The blank group was cultured with 10% fetal bovine serum， while the other three groups were stimulated with 10 μg/L of recombinant human tumor necrosis factor-α （TNF-α） for 24 h to establish the RA cell model. On this basis， the methotrexate group was treated with methotrexate suspension at a concentration of 20 μmol/L， and the YQTF group was treated with 10% YQTF-medicated serum. After 48 h of intervention， the levels of TNF-α and interleukin-17A（IL-17A）contents in cell supernatants were detected by enzyme-linked immunosorbent assay （ELISA）， and mRNA expressions of phosphatidylinositol 3-kinase（PI3K）， protein kinase B（AKT） and mammalian target of rapamycin（mTOR） were detected by real-time quantitative polymerase chain reaction （RT-qPCR）. ResultsNetwork pharmacological analysis identified 209 active components and 583 potential target genes of YQTF， as well as 818 RA-related targets. A total of 29 common targets were obtained from the intersection of drug-related targets and RA-related targets. Quercetin，β-sitosterol， kaempferol， stigmasterol and luteolin were the core active components of YQTF for the treatment of RA， while matrix metalloproteinase-9 （MMP9）， prostaglandin-endoperoxide synthase 2 （PTGS2）， Toll-like receptor 4 （TLR4）， tumor protein p53 （TP53） and transcription factor AP-1 subunit JUN were the key targets. The GO and KEGG pathway enrichment analysis showed that the involved biological processes and pathways were mainly associated with antioxidant responses， PI3K-AKT signaling pathway and Toll-like receptor （TLR） signaling pathway. Molecular docking results showed that MMP9 and PTGS2 exhibited high binding affinities with quercetin， β-sitosterol， kaempferol， stigmasterol and luteolin； TLR4 exhibited high binding activities with β-sitosterol， stigmasterol and luteolin； and TP53 showed high binding affinity with luteolin. The results of cell experiments showed that compared with the control group， the contents of TNF-α and IL-17A as well as the mRNA expressions of AKT and mTOR in the model group significantly increased （P＜0.05 or P＜0.01）. Compared with the model group， all the above indicators significantly decreased in the YQTF group， while the contents of TNF-α and the mRNA expression of AKT significantly decreased in the methotrexate group （P＜0.05 or P＜0.01）. ConclusionThe mechanism of YQTF in the treatment of RA may be associated with reducing inflammatory cytokine secretion and inhibiting the activation of the PI3K-AKT-mTOR signaling pathway.

In recent years， repetitive transcranial magnetic stimulation （rTMS） has garnered significant attention as a therapeutic approach for sleep disorders in the elderly. However， the prevailing rTMS protocols are predominantly developed based on normative neurophysiological data derived from young adults and fail to incorporate individualized parameters tailored to the brain characteristics of the elderly. To address this gap， the consensus development group synthesized the latest evidence from 2010 to 2025 and established a standardized rTMS protocol specifically for elderly patients with sleep disorders. Adhering to the Appraisal of Guidelines for Research and Evaluation II （AGREE II） framework， systematically screened randomized controlled trials （RCTs） and systematic reviews regarding rTMS in the treatment of sleep disorders across various conditions. Meanwhile， the Grading of Recommendations Assessment， Development and Evaluation （GRADE） system was employed to rigorously grade the quality of evidence and the strength of recommendations. This consensus guideline delineates precise rTMS protocols for the management of sleep disorders in the elderly， highlights the adjustment of stimulation intensity according to scalp-cortex distance recommends either MRI‑guided neuronavigation or the Beam F3/F4 heuristic approach for accurate target localization， thereby providing precise rTMS intervention protocol for sleep disorders in the elderly， aiming to enhance clinical efficacy while ensuring treatment safety. ［Funded by National Key Research and Development Program （number， 2023YFC3603200）； General Program of Shenzhen Science and Technology Innovation Commission （number， JCYJ20240813112859008， JCYJ20240813112900002）； Youth Program of Shenzhen Kangning Hospital （number， KN2023A004）； www.guidelines-registry.cn number， PREPARE-2026CN530］

AIM:To investigate the current status and influencing factors of knowledge-attitude-practice in myopia prevention and control among children and adolescents in Ningbo City, thereby providing a scientific basis for formulating targeted prevention strategies.METHODS: Children and adolescents aged 6-12 years old were selected from the medical-school collaborative myopia prevention network in Ningbo City between August 2024 and May 2025 using stratified cluster sampling. Information on myopia prevention knowledge(15 items)and practice(9 items)was collected through questionnaire surveys. Logistic regression models were used to analyze factors influencing myopia occurrence in children and adolescents.RESULTS: A total of 664 children and adolescents aged 6-12 years were enrolled in this study. Participants were divided by age into three groups: 6-7 years old(n=221), 8-9 years old(n=221), and 10-12 years old(n=222). Of the 664 questionnaires distributed, 637 valid questionnaires were returned(201 from the 6-7 age group, 235 from the 8-9 age group, and 201 from the 10-12 age group), yielding an effective response rate of 95.9%. Based on myopia screening results, the non-myopic group comprised 203 participants(31.9%), including 100 males and 103 females, with a mean age of 8.82±1.98 years old. The myopic group comprised 434 participants(68.1%), including 213 males and 221 females, with a mean age of 9.10±1.95 years old. The myopia prevalence rates in the 6-7, 8-9, and 10-12 age groups were 37.8%(76/201), 71.9%(169/235), and 94.0%(189/201), respectively(P<0.001). Regarding the knowledge and practice of myopia prevention, the overall awareness rate in the non-myopic group(59.7%±9.7%)was significantly higher than that in the myopic group(48.7%±8.5%; P<0.001). Additionally, the non-myopic group scored higher on the key practice of “regular eye examinations”(4.27±0.96)compared to the myopic group(4.10±1.05; P<0.05). Logistic regression analysis indicated that age was the primary risk factor for myopia occurrence.CONCLUSION: Age is the dominant factor in the onset of myopia, and there is a phenomenon of “knowledge-practice gap”; the traditional health education model has limitations, and a precise prevention and control system based on developmental patterns should be established.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

ObjectiveThis paper aims to find the identified and validated clinical biomarker data building upon a clinical study of early-phase phase Ⅱ and investigate the correlation analysis of Huanglian Jiedu Wan on syndrome improvement and clinical biomarkers in the treatment of "excess heat-toxicity" based on a machine learning model. Additionally， the effective prediction of clinical biomarker values for the main symptoms of the "excess heat-toxicity" syndrome was assessed. MethodsA total of 229 patients meeting the inclusion criteria for "excess heat-toxicity" syndrome were randomly divided into the Huanglian Jiedu Wan group and the placebo group. Syndrome score transition matrices were constructed for the Huanglian Jiedu Wan group and the placebo group based on three main symptoms of "excess heat-toxicity" syndrome， such as oral ulcers， sore throat， and gum swelling and pain. Data from the patients with these three syndromes were also integrated for an overall analysis. The corresponding syndrome score transition matrices were further constructed to visualize symptom change trends of the patients in the two groups via heatmaps. Based on the identified and validated clinical biomarkers related to inflammation， oxidative stress， and energy metabolism in the early phase， Spearman correlation analysis was employed to analyze and evaluate the associations between clinical biomarkers and syndrome improvement. Key clinical biomarkers reflecting the effect of Huanglian Jiedu Wan were screened through the comparison of differences between groups. An extreme gradient boosting （XGBoost） algorithm was used to develop a prediction model for main symptom classification， with classification performance evaluated through 10-fold cross-validation. Feature importance analysis was applied to identify variables with the greatest contribution to the prediction result. ResultsThe syndrome transition matrix results indicated that the Huanglian Jiedu Wan group showed a superior effect to the placebo group in improving oral ulcers， sore throat， and overall symptoms， with significant effects observed especially in sore throat and overall symptom analyses （P<0.01）. Spearman correlation analysis revealed that several clinical biomarkers positively correlated with "excess heat-toxicity" syndrome and its main symptom improvement， were also called "heat-related biomarkers"， including succinic acid， α-ketoglutaric acid， glycine， lactic acid， adenosine monophosphate （AMP）， tumor necrosis factor-α （TNF-α）， interferon-γ （IFN-γ）， interleukin-1β （IL-1β）， interleukin-4 （IL-4）， interleukin-6 （IL-6）， interleukin-8 （IL-8）， interleukin-10 （IL-10）， and so on. Conversely， clinical biomarkers negatively correlated with symptom severity， were also called "heat-clearing related biomarkers" after administration of Huanglian Jiedu Wan， including malic acid， fumaric acid， cis-aconitic acid， adrenocorticotropic hormone （ACTH）， IL-1β， IL-4， IL-8， succinic acid， and citric acid. The XGBoost classification model using all 52 biomarkers as variables achieved an average test accuracy of 0.754 and an average F1 score of 0.777. Feature importance analysis identified the scores of glutamic acid in saliva and IL-6 were the highest in all the variables， with importance scores of 0.081 and 0.080， respectively. After screening out 14 key variables and optimizing the parameters， model performance improved to an average accuracy of 0.758 and an F1 score of 0.798. Feature importance analysis further determined that the glutamic acid in saliva and IL-6 showed obvious changes after screening the variables， confirming the good syndrome prediction ability of the model constructed by these key clinical biomarkers. ConclusionThis study systematically elucidates the correlation between syndrome improvement and clinical biomarkers of Huanglian Jiedu Wan in the treatment of "excess heat-toxicity" syndrome. An XGBoost classification model based on key clinical biomarkers is successfully established， achieving effective prediction of the symptoms related to the "excess heat-toxicity" syndrome such as oral ulcers and sore throat and providing a new insight for objective identification of traditional Chinese medicine syndromes.

Renal Fanconi syndrome (FS) is a rare renal manifestation of primary Sjögren's syndrome (pSS). This study aims to analyze the clinical and prognostic characteristics of patients with pSS-associated renal FS (pSS-FS) and provide insights for clinical management.

Objective: To conduct screening for rare blood types within important blood group systems for the Chinese population, such as Rh, Duffy, Kidd, P1Pk, Diego, and MNS, in the Guangzhou region, and to establish a corresponding rare blood type database and physical repository. Methods: The saline medium microplate method was used to screen blood donors with the ccDEE phenotype combined with either Jk(a-) or Jk(b-). The polybrene microplate method was employed to screen for donors with Fy(a-), s(-), Lu(b-), Di(b-), k(-), and p phenotypes. The urea lysis microplate method was applied to screen for the Jk(a-b-) phenotype. A high-resolution melting (HRM) curve method was established for screening some donors with the Di(b-) phenotype. Subsequently, expanded phenotyping of antigens in the Rh, Kidd, MNS, Duffy, P1Pk, Lewis, Kell, and Lutheran blood group systems was performed on identified rare blood type donors using monoclonal antibodies. The test results are entered into the Rare Blood Type Bank Management System of the Guangzhou Blood Center, enabling functions such as confirmation reminders and cryopreservation storage when the donor donates again. Red blood cells of rare blood types are processed into frozen red blood cells for long-term storage. Results: Among voluntary blood donors, 16 cases of the ccDEE combined with Jk(a-) phenotype were identified (0.221 7%, 16/7 216); 10 cases of the ccDEE combined with Jk(b-) phenotype (0.138 6%, 10/7 216); 78 cases of the Fy(a-) phenotype (0.169 5%, 78/46 012); 39 cases of the Lu(b-) phenotype (0.138 2%, 39/28 214); 31 cases of the s(-) phenotype (0.081 8%, 31/37 913); 22 cases of the Di(b-) phenotype (0.029 9%, 22/73 691); 30 cases of the Jk(a-b-) phenotype (0.010 1%, 30/298 250); and 1 case of the k(-) phenotype (0.001 3%, 1/77 382), which was further identified as KELnull phenotype (K0). No p phenotype donors were identified (0/88 528). A total of 228 units of frozen red blood cells were prepared. The screening results were compared and analyzed with rare blood type data from other regions. Conclusion: This study, through a combination of different screening methods, significantly improved the efficiency of rare blood type screening while remaining cost-effective. By conducting large-scale screening and performing data informatization processing, a database and physical repository of rare blood types in the Guangzhou region were successfully established. This provides a strong guarantee for the timely supply of blood to patients with difficult-to-match and rare blood types in the region, effectively enhances the level of transfusion safety in the region, and offers a practical paradigm for constructing a comprehensive blood transfusion support system.

Objective: To investigate the association between brain and muscle Arnt like protein 1( BMAL 1) gene and ambulatory blood pressure (ABP) parameters in college students, and to explore the influence of the interaction between the gene and weight status on the ABP levels, so as to provide reference for early prevention of chronic cardiovascular diseases related to hypertension. Methods: During September 2022 to June 2024, a total of 510 college students were recruited from a university in Changsha, China for on site questionnaire investigation, physical examination, ABP monitoring and genotyping testing. Multiple linear regression method was used to explore the association between the BMAL 1 gene and ABP indicators. An interaction term was included in the general linear model of multiple linear regression to analyze the interactive effects of BMAL 1 gene polymorphisms and weight status on ABP levels. Results: The prevalence of abnormal 24 hour blood pressure, abnormal daytime blood pressure, and abnormal nighttime blood pressure were 3.3%, 3.1%, and 3.9%, respectively. Multiple linear regression analysis showed that the BMAL 1/rs7950226 polymorphism was positively correlated with the 24 hour diastolic blood pressure(DBP) and the daytime DBP level after adjusting for gender, age, and body mass index( β =0.87,0.99, both P <0.05). Also, interaction between BMAL 1/ rs 11022775 and weight status on the nighttime DBP level ( P interaction =0.03) was found. The CC genotype carriers had significantly higher nighttime DBP level ( β =3.52, P <0.05) among overweight/obesity college students, but no differences in nocturnal DBP levels were observed between CC genotype carriers and TT+CT genotype carriers among college students with normal body weight( P > 0.05). Conclusions The rs 7950226 polymorphism is associated with 24 hours DBP and daytime DBP levels. Significant interaction between rs 11022775 with weight status on the nighttime DBP level is found among college students.

Objective To understand the current situation of healthcare-associated infection(HAI)in China,pro-vide data support and decision-making basis for formulating scientific and effective strategies for HAI prevention and control.Methods A nationwide cross-sectional survey on HAI was conducted among various types and levels of medical institutions in China according to a unified protocol of bedside surveys and case investigations.Results In 2024,a total of 5 736 medical institutions and 2 751 765 patients were surveyed.Among them,34 889 HAI cases were identified,with a prevalence rate of 1.27％.The number of HAI episodes was 38 032,and case prevalence rate was 1.38％.The prevalence rate of HAI in medical institutions in different regions of China ranged from 0.66％to 2.35％.Among medical institutions of different scales,those with a bed capacity of ≥900 had the high-est incidence of HAI,reaching 1.65％.The most common infection site was the lower respiratory tract(44.66％),followed by the urinary tract(12.94％),surgical site(9.32％),upper respiratory tract(7.02％),and bloodstream infection(5.78％).The top 3 departments with the highest HAI rates were the general intensive care unit(10.02％),department of neurosurgery(5.51％),and department(group)of hematology(5.34％).A total of 23 238 strains of HAI pathogens were detected,with 10 714 strains(46.10％)from lower respiratory tract speci-mens.The top 5 detected strains were Klebsiella pneumoniae(14.76％),Pseudomonas aeruginosa(13.33％),Escherichia coli(12.79％),Acinetobacter baumannii(9.23％),and Staphylococcus aureus(7.88％).231 944 pa-tients underwent class Ⅰ incision surgery were monitored,with 1 647 cases experienced surgical site infection,and the prevalence rate of surgical site infection was 0.71％.The number of patients who should undergo pathogen de-tection(patients receiving therapeutic and therapeutic combined prophylactic antimicrobial agents)was 715 179,while the actual number was 480 492,with a pathogen detection rate of 67.18％.425 225 patients received patho-genic detection before treatment,with a detection rate of 59.46％.Conclusion The overall HAI prevalence in Chi-na is lower,showing disparities among medical institutions of different regions and scales.Therefore,precise imple-mentation of measures is necessary for HAI prevention and control,with a focus on high-risk institutions and high-risk departments,key areas,and critical procedures.All levels of medical institutions should continuously reduce the incidence of HAI by strengthening monitoring,standardizing the use of antimicrobial agents,and reinforcing basic HAI prevention and control measures.

This paper reports a case of disseminated infection caused by Fusarium solani in a patient with acute myeloid leukemia after transplantation.Fusariun solani was cultured from the patient's blood as well as foot and ocular secretion.Anti-infection treatment was not effective.Combined with literature review,characteristics,clini-cal diagnosis,and treatment strategies of Fusarium disseminated infection were analyzed,aiming to assist the early detection,early diagnosis,and early treatment in clinical practice.