AIM: To evaluate the efficacy and safety of 3% diquafosol sodium eye drops in children wearing orthokeratology lenses and with dry eye disease(DED)or at risk of DED.METHODS: Randomized controlled trials. Children with DED or at risk of DED were randomly assigned in a 1:1 ratio to receive either 3% diquafosol sodium eye drops 6 times daily or a blank control at Chongqing Aier Children's Eye Hospital from November 2023 to November 2024. The primary endpoint was the change in the Dry Eye Questionnaire-5(DEQ-5)score from baseline at 12 wk. Secondary assessments included non-invasive breakup time(NIBUT), tear meniscus height, Schirmer's test, corneal fluorescein staining score, and axial length.RESULTS: A total of 80 participants(80 eyes)were enrolled(40 in each group), the average age of the participants was 11.11±1.88 years, with 43 females(54%)and 37 males(46%), and all completed the trial. After 12 wk, the DEQ-5 scores for the diquafosol sodium group and the blank control group were 1.88±2.02 and 2.88±2.79, respectively(P=0.079). The diquafosol sodium group demonstrated a significant improvement in DEQ-5 dryness symptom scores(-0.33±0.66 vs. 0.05±0.81, P=0.023)and NIBUT(6.18±3.73 vs. -1.09±4.40 s, P<0.001)at 12 wk. Additionally, the diquafosol sodium group showed no axial length elongation, in contrast to the blank control group, which exhibited elongation(0.00±0.08 vs. 0.05±0.10 mm, P=0.013). No other significant differences were found in the secondary endpoints. No adverse events occurred during the trial.CONCLUSION: Although no statistically significant improvements were noted in the overall DEQ-5 scores, the 3% diquafosol sodium eye drops significantly improved dryness symptoms and NIBUT when compared to the blank control group.

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.

Traditional Chinese medicine and its bioactive components have garnered increasing attention as potential therapeutic options for allergic asthma. By targeting the phosphatidylinositol 3-kinase (PI3K)/protein kinase B (AKT) signaling pathway, these natural compounds exhibit unique advantages in multilevel immunomodulation and inflammation suppression compared with single-target synthetic drugs. Accumulating pharmacological evidence supports their capacity to restore pathway homeostasis, positioning them as promising candidates for complementary strategies in asthma management. Allergic asthma, a heterogeneous respiratory disorder affecting approximately 150 million individuals worldwide, arises from a complex interplay of genetic predisposition, environmental exposures, and lifestyle factors. Its pathological progression is marked by aberrant activation of the PI3K/AKT signaling cascade, with the mechanistic target of rapamycin serving as a key downstream regulatory node. This evolutionarily conserved pathway orchestrates fundamental cellular processes that contribute to three hallmark pathological features of allergic asthma: chronic airway inflammation, structural remodeling of the bronchial architecture, and airway hyperresponsiveness. This review has 3 primary objectives: (1) to evaluate the role of the PI3K/AKT pathway in allergic asthma pathogenesis, (2) to analyze the molecular mechanisms of representative traditional Chinese medicine preparations and their active ingredients, and (3) to identify novel bioactive inhibitors derived from natural products. Collectively, these investigations provide a conceptual framework for the development of next-generation targeted therapies and for optimizing clinical management strategies for allergic asthma.

Hepatic vascular malformations are a group of congenital or acquired disorders characterized by structural abnormalities of the intrahepatic arterial， venous， or portal venous systems， with the clinical manifestations of hyperdynamic circulation， portal hypertension， and complications of portosystemic shunting. Due to the low incidence rate and nonspecific clinical manifestations of such disorders， they are easily confused with cirrhotic portal hypertension， leading to the delay in diagnosis and treatment. This article introduces the common clinical manifestations and differential diagnosis of hepatic vascular malformations and elaborates on three typical types of hepatic vascular malformations， in order to provide ideas and references for clinical diagnosis and treatment.

Objective To construct a dynamic prediction model for JC polyomavirus (JCV) reactivation after kidney transplantation. Methods A retrospective analysis was conducted on the clinical data of 128 recipients who met the inclusion criteria and received kidney transplantation in Nanfang Hospital, Southern Medical University, from June 2021 to December 2024. Dynamic Cox regression and dynamic restricted mean survival time (RMST) regression based on the landmark method were adopted to establish the dynamic prediction models, and Monte Carlo cross-validation was used to evaluate model performance. Results The dynamic models could predict the incidence and onset time of JCV reactivation within the subsequent 3 months according to covariates at each landmark time point from the 1st to the 6th month after transplantation. Remuzzi score, body mass index and warm ischemia time were independent risk factors for JCV reactivation, while a history of urinary BK polyomavirus reactivation served as a protective factor. The median values of the area under the curve, C-index and Brier score of the dynamic Cox model were 0.873, 0.851 and 0.065 respectively, and the C-index of the dynamic RMST model was 0.829, all of which were superior to those of the static model. Conclusions The landmark-based dynamic models exhibit excellent predictive performance, which may integrate baseline data and post-transplant follow-up information to realize dynamic assessment of the risk and time window of JCV reactivation, thereby providing evidence for optimizing post-operative monitoring and individualized intervention strategies.

To address the challenges of fragmented data, inconsistent standards, and delayed feedback in the full-cycle competency development process at teaching hospitals, this paper proposes the LEADS data governance system for Precision Medical Education (LEADS-PME), drawing on the practical experience of building the integrated medical education management platform at Zhongshan Hospital, Fudan University. The LEADS-PME framework comprises five interconnected core components: Longitudinal foundation, Evidence-chain generation, Analytics and profiling, Decision-support and prediction, and Simulation and digital-twin governance. Currently, Zhongshan Hospital has established a full-cycle educational data infrastructure and achieved multi-system data integration and competency-based profiling and evaluation, while the prediction and simulation modules are still in the prototype exploration phase. A mixed-methods evaluation will be subsequently conducted from the perspectives of data quality, management effectiveness, and predictive intervention. As a locally adapted framework, LEADS-PME can transform operational data derived from clinical practice, teaching, assessment, and management processes into traceable, interpretable, and reusable evidence of competency development. It is expected to facilitate the transformation of medical education management from a outcome-oriented approach to process monitoring, evidence-driven decision-making, and precision governance, thereby providing both a theoretical framework and practical reference for precision medical education in Chinese teaching hospitals.

Objective:To explore the causal association between insulin-like growth factor-1(IGF-1)and colorectal cancer(CRC)based on two sample Mendelian randomization(MR)analysis.Methods:A bidirectional two sample MR analysis was conducted based on publicly aggregated data from the IEU OpenGWAS project.The inverse variance weighted(IVW)method was used as the main analysis model to assess the causal relationship between IGF-1 and CRC.Additional analyses were performed using weighted median(WM),MR-Egger regression,weighted mode estimator(WME),and simple mode(SM)methods.Sensitivity analysis was performed to assess the robustness of the results.Results:A total of 386 single nucleotide polymorphisms(SNPs)were selected as instrumental variables(IVs)with IGF-1 as the exposure factor.The MR analysis results revealed a positive causal association between IGF-1 and the risk of CRC[odds ratio(OR)=1.178,95％confidence interval(CI):1.092-1.272)](P＜0.001),and the association remained significant after adjusting for height[OR(95％CI)=1.214(1.111,1.327)](P＜0.001).Cochran's Q-test showed heterogeneity among the IVs(P＜0.05),while the horizontal pleiotropy of IV was not detected by the MR-Egger regression(P＞0.05).The leave-one-out analysis showed that the MR results were robust.Reverse MR analysis indicated no reverse causal relationship between IGF-1 and CRC[OR(95％CI):1.017(0.997,1.037)](P=0.103).Conclusion:There is a causal relationship between IGF-1 level and CRC,and elevated IGF-1 level could be a risk factor for CRC.

Objective:To discuss the effect of KH-type splicing regulatory protein(KHSRP)on the malignant biological behaviors of colorectal cancer(CRC)by activating the Janus kinase(JAK)/signal transducer and activator of transcription(STAT)signaling pathway,and to clarify its possible mechanism.Methods:The CRC tissue and adjacent normal tissue from 64 CRC patients were selected.The human CRC cells(HT29,SW620,SW480,DLD-1,LOVO,and RKO)and normal human colorectal mucosal FHC cells were cultured in vitro.The total RNA from CRC tissue and cells were extracted,real-time fluorescence quantitative PCR(RT-qPCR)was used to detect the expression levels of KHSRP in the CRC tissue,adjacent normal tissue and all kinds of cells.The HT29 and SW620 cells were divided into sh-NC group(lentiviral plasmid inserted with non-targeting nucleotide sequence)and sh-KHSRP group(transfected with KHSRP knockdown lentivirus).The SW480 and DLD-1 cells were divided into oe-NC group(lentiviral plasmid inserted with non-targeting nucleotide sequence)and oe-KHSRP group(transfected with KHSRP overexpression lentivirus).Immunohistochemistry(IHC)staing in method was used to analyze the expressions of KHSRP in CRC tissue and adjacent normal tissue;CCK-8 method was used to detect the proliferation activities of the CRC cells in various groups;Transwell assay was used to detect the numbers of migration and invasion cells in various groups;Western blotting method was used to detect the expression levels of KHSRP,JAK1,phosphorylated JAK1(p-JAK1),JAK2,phosphorylated JAK2(p-JAK2),STAT1,STAT2,STAT3,and STAT5 proteins in the CRC cells in various groups.The subcutaneous xenograft tumor models in the nude mice were used to measure the tumor volumes and weights of the mice in various groups.Results:Compared with adjacent normal tissue,the expression level of KHSRP in the CRC tissue was increased(P<0.05).Compared with FHC cells,the expression levels of KHSRP in the CRC cells were increased(P<0.05).Therefore,the HT29 and SW620 cells were selected for knockdown of KHSRP,while the SW480 and DLD-1 cells were selected for over-expression of KHSRP.The Western blotting results showed that the expression amounts of KHSRP protein in the CRC tissue and cells were higher than those in adjacent normal tissue and FHC cells.The IHC results showed that compared with adjacent normal tissue,the expression level of KHSRP protein in CRC tissue was increased(P<0.01).The RT-qPCR results showed that compared with sh-NC group,the expression levels of KHSRP mRNA in the HT29 and SW620 cells in sh-KHSRP group were decreased(P<0.01);compared with oe-NC group,the expression levels of KHSRP mRNA in the SW480 and DLD-1 cells in oe-KHSRP group were increased(P<0.01),indicating successful transfection.The CCK-8 results showed that compared with sh-NC group,the proliferation activities of the HT29 and SW620 cells in sh-KHSRP group after knockdown of KHSRP were decreased(P<0.05 or P<0.01);compared with oe-NC group,the proliferation activities of the SW480 and DLD-1 cells in oe-KHSRP group after over-expression of KHSRP were increased(P<0.05 or P<0.01).Compared with sh-NC group,the numbers of migration and invasion cells in the HT29 and SW620 cells in sh-KHSRP group after knockdown of KHSRP were decreased(P<0.05);compared with oe-NC group,the numbers of migration and invasion cells in the CRC cells in oe-KHSRP group after over-expression of KHSRP were increased(P<0.05).After knockdown of KHSRP,the tumor volume and weight in sh-KHSRP group were smaller than those in sh-NC group(P<0.05 or P<0.01),while the tumor volume andweight in oe-KHSRP group were larger than those in oe-NC group after over-expression of KHSRP(P<0.05 or P<0.01).Compared with sh-NC group,the expression levels of JAK1,p-JAK1,and STAT3 proteins in the CRC cells in sh-KHSRP group were significantly decreased(P<0.05 or P<0.01);compared with oe-NC group,the expression levels of JAK1,p-JAK1,and STAT3 proteins in the CRC cells in oe-KHSRP group were significantly increased(P<0.05 or P<0.01).Conclusion:High expression of KHSRP promotes the proliferation,migration,and invasion of the CRC cells and enhances the growth of subcutaneous xenograft tumors in the mice;its mechanism may be associated with its activation of the JAK1/STAT3 signaling pathway.