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.

As activated hepatic stellate cells (aHSCs) play a central role in fibrogenesis, they have become key target cells for anti-fibrotic treatment. Nevertheless, the therapeutic efficiency is constrained by the exosomes they secrete, which are linked to energy metabolism and continuously stimulate the activation of neighboring quiescent hepatic stellate cells (qHSCs). Herein, an intercellular communication interference strategy is designed utilizing paeoniflorin (PF) loaded and hyaluronic acid (HA) coated copper-doped ZIF-8 (PF@HA-Cu/ZIF-8, PF@HCZ) to reduce energy-related exosome secretion from aHSCs, thus preserving neighboring qHSCs in a quiescent state. Simultaneously, the released copper and zinc ions disrupt key enzymes involved in glycolysis to reduce bioenergy synthesis in aHSCs, thereby promoting the reversion of aHSCs to a quiescent state and further decreasing exosome secretion. Therefore, PF@HCZ can effectively sustain both aHSCs and qHSCs in a metabolically dormant state to ultimately alleviate liver fibrosis. The study provides an enlightening strategy for interrupting exosome-mediated intercellular communication and remodeling the energy metabolic status of HSCs with boosted antifibrogenic activity.

Chimeric antigen receptor T (CAR-T) cells have reshaped the treatment landscape of hematological malignancies, offering a potentially curative option for patients. Despite these major milestones in the field of immuno-oncology, growing experience with CAR-T cells has also highlighted several limitations of this strategy. The production process of CAR-T cells is complex, time-consuming, and costly, thus leading to poor drug accessibility. The potential carcinogenic risk of viral transfection systems remains a matter of controversy. Treatment-related side effects, such as cytokine release syndrome, can be life-threatening. And the biggest challenge is the inadequate efficacy related to poor infiltration and retention of CAR-T cells in tumor tissues and impaired T cell activation caused by the immunosuppressive tumor microenvironment (TME). Innovative strategies are urgently needed to address these problems, and nanomedicine offers good solutions to these challenges. In this review, we provide a comprehensive summary of recent advancements in the application of nanomaterials to enhance CAR-T cell therapy. We examine the role of innovative nanoparticle-based delivery systems in the production of CAR-T cells, with a particular focus on polymeric delivery systems and lipid nanoparticles (LNPs). Furthermore, we explore various strategies for delivering immune stimulators, which significantly enhance the efficacy of CAR-T cells by modulating T cell viability and functionality or by reprogramming the immunosuppressive TME. In addition, we discuss several novel therapeutic approaches aimed at mitigating the adverse effects associated with CAR-T therapies. Finally, we offer an integrated perspective on the future challenges and opportunities facing CAR-T therapies.
Humans ; Nanomedicine/methods* ; Receptors, Chimeric Antigen/metabolism* ; Immunotherapy, Adoptive/methods* ; T-Lymphocytes/immunology* ; Nanoparticles/chemistry* ; Animals

Inflammatory bowel disease (IBD) is a chronic inflammatory disorder of the gastrointestinal tract, which increases the incidence of colorectal cancer (CRC). In the pathophysiology of IBD, ubiquitination/deubiquitination plays a critical regulatory function. Josephin domain containing 2 (JOSD2), a deubiquitinating enzyme, controls cell proliferation and carcinogenesis. However, its role in IBD remains unknown. Colitis mice model developed by dextran sodium sulfate (DSS) or colon tissues from individuals with ulcerative colitis and Crohn's disease showed a significant upregulation of JOSD2 expression in the macrophages. JOSD2 deficiency exacerbated the phenotypes of DSS-induced colitis by enhancing colon inflammation. DSS-challenged mice with myeloid-specific JOSD2 deletion developed severe colitis after bone marrow transplantation. Mechanistically, JOSD2 binds to the C-terminal of inosine-5'-monophosphate dehydrogenase 2 (IMPDH2) and preferentially cleaves K63-linked polyubiquitin chains at the K134 site, suppressing IMPDH2 activity and preventing activation of nuclear factor kappa B (NF-κB) and inflammation in macrophages. It was also shown that JOSD2 knockout significantly exacerbated increased azoxymethane (AOM)/DSS-induced CRC, and AAV6-mediated JOSD2 overexpression in macrophages prevented the development of colitis in mice. These outcomes reveal a novel role for JOSD2 in colitis through deubiquitinating IMPDH2, suggesting that targeting JOSD2 is a potential strategy for treating IBD.

Objectives:To investigate the incidence of tyrosine kinase inhibitor (TKI) withdrawal syndrome and psychological issues, and their associated factors, in patients with chronic-phase chronic myeloid leukemia (CML-CP) after TKI discontinuation.Methods:We retrospectively analyzed the clinical data of CML-CP patients who discontinued TKI therapy at Peking University People's Hospital after September 2012. Logistic regression models were used to identify independent factors associated with the occurrence of TKI withdrawal syndrome and psychological issues.Results:A total of 158 patients were included, of whom 92 (58%) were female. The median age at discontinuation was 50 ( IQR, 35-60) years. With a median follow-up of 25 ( IQR, 11-49) months, the 4-year rate of sustained major molecular response (MMR) was 60% (95% CI: 51%-70%) . Fifty-one (32%) patients experienced TKI withdrawal syndrome at a median of 1.3 ( IQR, 0.5-2.0) months after TKI discontinuation. Fifty-one (32%) patients reported psychological issues such as anxiety. These concerns stemmed from fears of fluctuating BCR::ABL1 levels or disease relapse, and, for those who discontinued TKI for pregnancy, worries about adverse fetal effects and/or the fetus inheriting CML. Multivariable analyses revealed that older age at discontinuation [ P=0.003 when adjusting for TKI therapy duration; P=0.002 when adjusting for deep molecular response (DMR) duration], longer TKI therapy duration ( P=0.010) , and longer DMR duration before discontinuation ( P=0.005) were significantly associated with a higher risk of TKI withdrawal syndrome; a university degree or higher ( P=0.010) and TKI discontinuation due to pregnancy or adverse events ( P=0.001) were significantly associated with psychological issues after discontinuation. The occurrence of TKI withdrawal syndrome or psychological issues had no impact on the probability of major molecular response loss after discontinuation. Conclusion:TKI withdrawal syndrome and psychological issues are common in CML patients who discontinue TKI therapy. Older age at discontinuation and longer TKI therapy duration or DMR duration are significantly associated with TKI withdrawal syndrome. Higher education level and TKI discontinuation due to pregnancy or adverse events are significantly associated with psychological issues.