AIM:To investigate the effect of fibroblast growth factor 21(FGF21)on high glucose-induced oxidative stress in retinal pigment epithelial(RPE)cells and to clarify the underlying molecular mechanisms.METHODS:Single-cell sequencing data from the GEO database were analyzed to determine the expression profile of the FGF21 receptor FGFR1 in RPE cells. Human ARPE-19 cells were cultured and randomly assigned to control, high glucose(30 mmol/L), and high glucose+FGF21 analog treatment groups, with additional siFGFR1 and PI3K inhibitor groups. Cell viability in different treatment groups was assessed using CCK-8 assay, intracellular reactive oxygen species(ROS)levels were quantified using DCFH-DA fluorescent probing combined with immunofluorescence staining and flow cytometry. Transcriptome sequencing was performed on cells from the high glucose group and high glucose+FGF21 group to analyze the enrichment level of the PI3K/Akt signaling pathway. Western blotting was performed to detect phosphorylation levels of PI3K/Akt pathway components.RESULTS:Single-cell sequencing revealed specific expression of FGFR1 in RPE cells of retinal tissues from diabetic model mice. Under In vitro experiments, high glucose(30 mmol/L)exposure reduced ARPE-19 cell viability by 49.7% and increased ROS levels by approximately 2-fold. Whereas treatment with the FGF21 analog(60 ng/mL)restored cell viability and attenuated high glucose-induced ROS accumulation. Mechanistic studies demonstrated that FGFR1 knockdown inhibited the antioxidative stress of FGF21. Further validation of the molecular mechanism revealed that high glucose significantly suppressed the PI3K/Akt pathway activation(the levels of p-Akt and p-PI3K were decreased by 33.9% and 36.6%, respectively), while FGF21 effectively reversed this inhibitory effect and restored the expression of p-Akt and p-PI3K. Treatment with the PI3K inhibitor LY294002 inhibited the cytoprotective effect of FGF21 and significantly increased the ROS-positive cells, these findings confirm that PI3K/Akt signaling is indispensable downstream mechanism for FGF21 to exert its effects.CONCLUSION:FGF21 alleviates high glucose-induced oxidative stress and cellular injury in RPE cells by activating the PI3K/Akt signaling pathway through its receptor FGFR1.

To explore the advantages of traditional Chinese medicine （TCM） and integrative TCM-Western medicine approaches in the treatment of diabetic microvascular complications （DMC）， refine key pathophysiological insights and treatment principles， and promote academic innovation and strategic research planning in the prevention and treatment of DMC. The 38th session of the Expert Salon on Diseases Responding Specifically to Traditional Chinese Medicine， hosted by the China Association of Chinese Medicine， was held in Beijing， 2024. Experts in TCM， Western medicine， and interdisciplinary fields convened to conduct a systematic discussion on the pathogenesis， diagnostic and treatment challenges， and mechanism research related to DMC， ultimately forming a consensus on key directions. Four major research recommendations were proposed. The first is addressing clinical bottlenecks in the prevention and control of DMC by optimizing TCM-based evidence evaluation systems. The second is refining TCM core pathogenesis across DMC stages and establishing corresponding "disease-pattern-time" framework. The third is innovating mechanism research strategies to facilitate a shift from holistic regulation to targeted intervention in TCM. The fourth is advancing interdisciplinary collaboration to enhance the role of TCM in new drug development， research prioritization， and guideline formulation. TCM and integrative approaches offer distinct advantages in managing DMC. With a focus on the diseases responding specifically to TCM， strengthening evidence-based support and mechanism interpretation and promoting the integration of clinical care and research innovation will provide strong momentum for the modernization of TCM and the advancement of national health strategies.

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.

As the core vehicle for preserving and transmitting traditional Chinese medicine（TCM） academic thought and clinical experience， the establishment of a robust quality evaluation system for TCM clinical case reports is a crucial component in the current standardization and modernization of TCM. Based on the practical experience of constructing the China Clinical Cases Library of Traditional Chinese Medicine by the China Association of Chinese Medicine， this study conducted a comprehensive analysis of critical challenges， including insufficient authenticity and unfocused evaluation criteria. It proposed a three-dimensional evaluation framework grounded in the structure-process-outcome logic， encompassing three dimensions of authenticity and standardization， characteristics and advantages， application and translational impact. This framework integrated 12 key evaluation indicators in a systematic manner. The model preserved the academic characteristics of TCM syndrome differentiation and treatment， while aligning with modern scientific research standards， achieving a balance between individualized TCM experience and standardized evaluation. Concurrently， this study provided theoretical foundations and methodological guidance for evaluating the quality of TCM clinical cases， contributing significantly to the inheritance of TCM knowledge， evidence-based practice， and the reform of talent evaluation mechanisms.

Objective To understand mosquito density, species composition, and seasonal variations around the Beijing Capital International Airport(BCIA)and provide scientific evidence for mosquito-borne disease prevention and control. Methods Meteorological data were collected from 2016 to 2022, and mosquito density was monitored at seven surveillance sites around the BCIA from May to October each year using CO2-baited mosquito traps to analyze the relationship between mosquito density and meteorological factors. Results In total,68 518 female mosquitoes were captured, with a mosquito density of 10.20 per light · hour. The dominant species was Culex pipiens pallens(73.90%), followed by Aedes albopictus(9.71%)and Ae. vexans(9.29%);the mosquito density was highest in 2016(14.8 per light·hour)and lowest in 2022(4.46 per light·hour). Significant statistical differences were observed in mosquito density among different species(F=18.118, P<0.05). The density of Cx. pipiens pallens and other mosquito species showed a mutually exclusive trend; the peak of mosquito density varied based on years and habitats, with significant statistical differences in mosquito density among different habitats(F=8.504, P<0.05). The highest mosquito density was observed near the Wenyu River(21.50 per light·hour), whereas the lowest was recorded at the BCIA construction site(2.44 per light· hour). The monthly average temperature(r=0.595), monthly average highest temperature(r=0.575), and monthly average lowest temperature(r=0.624)showed moderate positive correlations, whereas the monthly average air pressure(r=-0.484)showed a moderate negative correlation. The monthly average minimum temperature was included in the regression model(F=25.575, P<0.000), and the equation Y=1.029X4-8.181 was used. The monthly average air pressure 2 months prior(b=-2.418, β=-1.619, P<0.05)and the monthly average relative humidity(b=-0.739, β=-1.201, P<0.05)significantly negatively predicted the mosquito density. Notably, the regression equation used was y=2526.170+(-2.418)X9+(-0.739)X13. The exposure-response analysis revealed that the density of mosquitoes was not linearly related to the average monthly air pressure, rainfall, and duration of sunshine. Conclusions The dominant mosquito species around the BCIA was Cx. pipiens pallens, Ae. albopictus, and Ae. vexans. During the control of Cx. pipiens pallens, the impact on other mosquito species must also be considered. Environmental management, breeding sites, and scientific use of pesticides should be prioritized based on the activity periods of mosquitoes. Further studies on mosquitoes and meteorological factors should be conducted to provide references and novel avenues for mosquito control.

BackgroundCurrent studies on the relationship between depressive symptoms and the risks of stroke and all-cause mortality mostly focus on the elderly population or high-risk groups with chronic diseases. The long-term impact of depressive symptoms in young and middle-aged people on the risks of stroke and all-cause mortality still lacks systematic assessment， and the relevant evidence is insufficient. ObjectiveTo explore the association between depressive symptoms and the risks of stroke and all-cause mortality in young and middle-aged adults， thereby expanding the risk evidence in this age group and providing epidemiological basis for early identification of high-risk individuals and the development of targeted intervention strategies. MethodsBased on data from the National Health and Nutrition Examination Survey （NHANES） database （2009–2018）， a total of 14 947 young and middle-aged respondents aged 18 to 64 were included as the research subjects. Logistic regression and restricted cubic spline （RCS） models were employed to examine the association between depressive symptoms and stroke. Cox proportional hazards model， RCS model， and Kaplan-Meier （K-M） survival curves were used to clarify the relationship between depressive symptoms and all-cause mortality risk. To verify the robustness of main findings， sensitivity analysis was conducted stratified by gender， hypertension， diabetes， hyperlipidemia， body mass index （BMI）， and age. ResultsLogistic regression analysis revealed that compared with the non-depressed group， the risk of stroke in the mild depression group increased by 53.50% （OR=1.535， 95% CI： 1.147–2.053）， while the moderate-to-severe depression group showed the highest risk with a 132.90% increase （OR=2.329， 95% CI： 1.733–3.129）. RCS analysis indicated an approximately linear dose-response relationship between PHQ-9 score and the risk of stroke （P_{for non-linearity}=0.089）， with stroke risk increasing as PHQ-9 scores rose. As the PHQ-9 score increased， the risk of stroke also showed an upward trend. Cox regression analysis demonstrated that compared with the non-depressed group， the risk of all-cause mortality in the mild depression group increased by 48.80% （HR=1.488， 95% CI： 1.164–1.902）， and the moderate-to-severe depression group had a 70.60% increased risk （HR=1.706， 95% CI： 1.310–2.221）. RCS analysis showed a linear dose-response relationship between PHQ-9 scores and all-cause mortality risk （P_{for non-linearity}=0.440）. K-M curves indicated that as the severity of depressive symptoms increases， the risk of all-cause mortality gradually rises （P<0.05）. Sensitivity analysis confirmed that the associations between depression symptoms and risks of stroke and all-cause mortality were not modified by gender， hypertension， diabetes， hyperlipidemia， BMI， or age， demonstrating robust findings. ConclusionAmong the young and middle-aged population， both mild and moderate-to-severe depression were associated with increased risks of stroke and all-cause mortality， with the moderate-to-severe depression group showed more pronounced risk elevations. A positive dose-response relationship was observed between depressive symptoms and these risks.

ObjectiveTo systematically review the effect of dual-task training (DTT) on mobility and balance in stroke patients. MethodsCNKI, Wanfang Data, VIP, PubMed, Web of Science, Embase and Cochrane Library were searched for randomized controlled trials (RCT) on DTT in stroke rehabilitation from inception to June, 2025. The quality of the included studies was assessed using the Cochrane Risk of Bias Tool and the PEDro scale. Meta-analysis was performed using RevMan 5.4. ResultsA total of eleven RCT involving 517 stroke patients were included, and the scores of PEDro scale were four to eight. DTT was more effective on the score of Fugl-Meyer Assessment-Lower Extremity (MD = 3.70, 95%CI 1.88 to 5.53, P < 0.001) and Berg Balance Scale (BBS) (MD = 3.04, 95%CI 1.58 to 4.49, P < 0.001), fall incidence (OR = 0.32, 95%CI 0.11 to 0.87, P = 0.025), gait speed under a single-task condition (MD = 0.08, 95%CI 0.03 to 0.12, P = 0.002), gait speed under a dual-task condition (MD = 0.13, 95%CI 0.10 to 0.16, P < 0.001), Timed Up and Go Test time (MD = -2.78, 95%CI -3.85 to -1.72, P < 0.001), and score of modified Barthel Index (MD = 4.77, 95%CI 1.88 to 7.66, P = 0.001). Subgroup analysis indicated that motor-motor DTT was more effective than cognitive-motor DTT on BBS scores and single-task gait speed. ConclusionsDTT can improve mobility and balance in stroke patients, especially with motor-motor tasks.

Lung cancer constitutes the most prevalent and lethal malignant tumor in China. Approximately 85% of lung cancer diagnoses correspond to the non-small cell histological subtype [non-small cell lung cancer (NSCLC)]. Despite surgery being the mainstay for early-stage disease, postoperative recurrence remains high and adjuvant chemotherapy offers limited benefit. In recent years, targeted therapy has demonstrated substantial advantages in driver mutation-positive NSCLC. To this end, the Lung Cancer Medical Education Committee of the Chinese Medical Education Association developed guidelines based on a systematic review of evidence through November 2025, using the Grading of Recommendations, Assessment, Development and Evaluations (GRADE) approach and a modified Delphi method. Focusing on epidermal growth factor receptor (EGFR) and anaplastic lymphoma kinase (ALK), and addressing ROS proto-oncogene 1 (ROS1), B-Raf proto-oncogene serine/threonine kinase (BRAF) V600E mutation, and mesenchymal-epithelial transition factor (MET) exon 14 (METex14) skipping, the guideline covers molecular testing, neoadjuvant/adjuvant therapy, perioperative strategies, minimal residual disease monitoring, and postoperative surveillance. It defines testing requirements, specifies stage-directed and subtype-specific treatments, and standardizes minimal residual disease monitoring. These recommendations emphasize precision and feasibility to improve survival and quality of life.

OBJECTIVE To provide guidance for the individualized use of antiepileptic drugs （AEDs） in patients with epilepsy or bipolar affective disorder.METHODS Clinical data of patients with epilepsy or bipolar affective disorder who received AEDs treatment and underwent therapeutic drug monitoring （TDM） at Xi’an International Medical Center Hospital from January 2023 to December 2025 were retrospectively collected. The baseline information， characteristics of AEDs utilization， implementation status of TDM and laboratory parameters were summarized. Spearman correlation analysis， univariate analysis and multivariate linear regression analysis were performed to identify the independent influencing factors for blood concentrations of AEDs.RESULTS A total of 1 572 patients were enrolled， including 660 males and 912 females. The majority were aged ≥60 years （30.15%）； 71.76% of patients were on monotherapy with AEDs， with valproic acid being the most commonly prescribed （51.97%）； combination therapy was predominantly a two-drug regimen （26.21%）， while three-drug regimens were rare （2.04%）. A total of 2 901 blood samples for TDM were collected， with the highest number of samples for valproic acid and levetiracetam （1 987 and 684 samples， respectively）. TDM for all five drugs was primarily conducted once； among which， the blood concentrations attainment rates exceeded 50% for patients taking valproic acid and levetiracetam， while the median blood concentrations for patients taking lamotrigine， oxcarbazepine， and carbamazepine were all below the lower limit of the therapeutic reference range. Based on the results of Spearman correlation analysis， univariate analysis， and multivariate linear regression analysis， patient gender， platelet count （PLT）， alanine transaminase （ALT）， aspartate transaminase （AST）， and total bilirubin （TBil） were found to be independent factors influencing blood concentration of valproic acid （unstandardized coefficients were －6.770 7， －0.078 6， －0.099 4， 0.083 2， －0.578 9， P ＜0.05）， while age and creatinine （CRE） were found to be independent factors influencing blood concentration of levetiracetam （unstandardized coefficients were 0.108 7， 0.047 8， P ＜0.05）.CONCLUSIONS Female gender and elevated AST levels are risk factors for increased blood concentration of valproic acid， while elevated PLT， ALT and TBil levels are associated with decreased blood concentration of valproic acid. Patients of advanced age and those with renal insufficiency bear a relatively high risk of in vivo levetiracetam accumulation.