Objective: To evaluate the implementation process of a school-family collaborative "online+offline" tobacco control intervention program in junior high school in Beijing and to explore the execution status, influencing factors and sustainability potential of the intervention, so as to provide evidence for optimizing youth tobacco control strategies. Methods: In November 2024, using the random number table method, four first year junior high school classes were selected from three schools each in Fengtai District, Tongzhou District, and Fangshan District of Beijing. One class served as the control group, while the other three classes were designated as intervention groups (one each for online intervention, offline intervention, and combined online offline intervention). The control group received only conventional education.The online intervention group was engaged in WeChat push interventions, including watching micro videos, viewing promotional materials, participating in online quizzes and mini games; the offline intervention group attended knowledge lectures, played peer games, and participated in offline knowledge competitions; the combined online offline intervention group integrated all the aforementioned online and offline intervention measures. The intervention period was from November 2024 to June 2025, spanning a total of 7 months. Based on the Practical, Robust Implementation and Sustainability Model(PRISM) framework, a qualitative research design was employed to conduct semi structured interviews with 48 participants (12 in each of the intervention groups and 12 organizational staff members) from the Centers for Disease Control and Prevention (CDC) in 3 districts and 3 sampled schools. The interview outlines were designed according to the intervention plan. Data was managed using Nvivo 12.0 software and analyzed following Colaizzi s seven step phenomenological analysis method. Theoretical saturation was assessed using a reserved subset of transcripts. Results: Four core themes were identified in the tobacco control intervention process. Overall fidelity of intervention implementation was largely consistent with the original plan, and students showed strong willingness and positive evaluations toward interactive formats such as knowledge contests and peer games, though occasional breakdowns in school-family communication and blurred boundaries between online and offline components were observed; the participants showed a polarized response in terms of satisfaction and participation, most students and parents recognized the significance of the activity, and some parents observed a reduction in smoking behavior; the implementation of internal tobacco control policies in the school was strict, and the atmosphere was favorable, but there was still room for improvement, such as the scarcity of community tobacco control activities and the difficulty in implementing smoke free units; implementation and sustainability infrastructure were preliminarily established, such as through homeroom teacher supervision and training student assistants to assisted in activities, while the sustainability support system required further refinement. Conclusion The school-family collaborative "online+offline" tobacco control intervention has demonstrated significant positive effects, but further optimization of activity design, enhancement of community reward mechanisms, and standardized training are required to improve the efficacy and sustainability of the intervention.

ObjectiveTo investigate the therapeutic effects and mechanisms of Qinlian Hongqutang （QLHQT） on nonalcoholic steatohepatitis （NASH）. MethodsC57BL/6J mice were randomly divided into normal and modeling groups. The NASH model was established by feeding a high-fat diet for 12 weeks. After successful modeling， mice were randomly assigned to the model group， low-， medium-， and high-dose QLHQT groups （0.51， 1.02， and 2.04 g·kg^-1）， and a positive control metformin group， with six mice in each group. The mice were treated for 8 weeks. Body weight was recorded before and after treatment. Serum levels of total cholesterol （TC）， triglycerides （TG）， and low-density lipoprotein cholesterol （LDL-C）， as well as hepatic TC， TG， and LDL-C contents， were determined by biochemical assays. Hematoxylin-eosin （HE） staining and oil red O staining were used to evaluate liver histopathology and lipid deposition， respectively. Flow cytometry， enzyme-linked immunosorbent assay （ELISA）， and Real-time polymerase chain reaction （Real-time PCR） were used to assess hepatic macrophage expression and related markers. Western blot and immunofluorescence were used to investigate the potential mechanisms of QLHQT in regulating macrophage polarization. ResultsCompared with the normal group， body weight and serum and hepatic levels of TC， TG， and LDL-C were significantly increased in the model group （P<0.01）. Liver histopathology showed unevenly distributed round lipid droplets in the hepatocyte cytoplasm， accompanied by inflammatory cell aggregation. Flow cytometry showed that the proportion of CD86-positive cells was significantly increased， whereas the proportion of CD206-positive cells was markedly decreased （P<0.05）. Hepatic inducible nitric oxide synthase （iNOS） levels and tumor necrosis factor-α （TNF-α） mRNA expression were significantly increased， while hepatic IL-10 levels and IL-4 mRNA expression were significantly decreased （P<0.01）. The protein expression levels of Toll-like receptor 4 （TLR4）， tumor necrosis factor receptor-associated factor 6 （TRAF6）， and myeloid differentiation factor 88 （MyD88） in the liver were significantly increased （P<0.01）. Compared with the model group， body weight was reduced in the high-， medium-， and low-dose QLHQT groups and in the metformin group. Serum and hepatic TC， TG， and LDL-C levels were significantly decreased （P<0.01）. Liver histopathology showed alleviated hepatic lipid deposition， with markedly reduced lipid droplets and inflammation. Immunofluorescence and flow cytometry showed that the proportions of CD86-positive cells were significantly decreased， whereas the proportions of CD206-positive cells were significantly increased in the high-， medium-， and low-dose QLHQT groups （P<0.05）. Hepatic iNOS levels and TNF-α mRNA expression were significantly decreased （P<0.01）， whereas hepatic IL-10 levels and IL-4 mRNA expression were significantly increased （P<0.01）. The hepatic protein expression levels of TLR4， TRAF6， and MyD88 were significantly decreased， while signal transducer and activator of transcription 6 （STAT6） phosphorylation was significantly increased （P<0.05， P<0.01）. There was no statistically significant difference in total STAT6 protein expression. ConclusionQLHQT effectively ameliorates hepatic inflammation in NASH mice， and the mechanism may involve STAT6- and TLR4-mediated signaling pathways driving polarization of M1 macrophages toward the M2 phenotype.

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.

Colorectal cancer， a leading malignant gastrointestinal tumor globally in terms of incidence and mortality， has seen a consistent annual rise in newly diagnosed cases. While conventional therapies like radiotherapy， chemotherapy， and surgery are available， problems such as lack of early diagnosis， poor prognosis， and drug resistance remain significant burdens for patients. Given the complex and diverse pathogenesis of colorectal cancer， there is an urgent clinical need for safe， effective， reliable， and multi-targeted therapeutic strategies. The Hippo signaling pathway， closely linked to mechanisms like tumorigenesis， cancer cell invasion， migration， and drug resistance， extensively participates in the occurrence and development of colorectal cancer， so targeting the signaling pathway for cancer prevention and treatment has become a crucial research direction in recent years. Traditional Chinese medicine （TCM） offers multi-faceted， multi-pathway， and multi-target advantages and becomes an important therapy for colorectal cancer by enhancing patients' immunity， improving the life quality， and prolonging survival. Studies show that the active components of TCM， including flavonoids， terpenoids， phenols， alkaloids， quinones， lignans， and saponins， as well as TCM compounds such as modified Sijunzi decoction， Jiedu Sangen decoction， Jianpi Jiedu compound， and Quyu Jiedu decoction， exhibit significant targeting effects on the Hippo signaling pathway. These TCMs can exert an anti-colorectal cancer effect through various mechanisms， such as inducing cancer cell autophagy and apoptosis， inhibiting epithelial-mesenchymal transition， reversing drug resistance of the tumor， and blocking the cancer cell cycle. This paper reviewed and analyzed Chinese and international research on the action mechanisms of TCM in regulating the Hippo signaling pathway for the prevention and treatment of colorectal cancer with a comprehensive overview presentation， aiming to provide new references and ideas for the clinical application of TCM and the development of new pharmacological agents in the prevention and treatment of colorectal cancer.

Radiomics enables the extraction of high-throughput quantitative features from ophthalmic images, allowing the identification of subvisual information that is imperceptible to the human eye and offering a novel strategy for the precise diagnosis and treatment of retinal diseases. By quantitatively characterizing subtle differences in retinal structure, texture, and hemodynamic characteristics, and integrating these features with clinical data, radiomics has demonstrated substantial potential in early screening, disease stratification, prediction of treatment responses, and individualized risk assessment of retinal diseases, particularly in common conditions such as diabetic retinopathy and age-related macular degeneration. Despite these promising advances, the clinical translation of radiomics remains challenging. Current limitations include suboptimal model performance and generalizability,as well as insufficient clinical interpretability of radiomic feature and predictive models, which hampers their integration into existing imaging systems and routine clinical workflows. Based on a systematic analysis of relevant articles published over the past five years, this paper summarizes recent progress in the application of radiomics combined with machine learning for the diagnosis and prognostic assessment of retinal diseases, and to discuss the key challenges and future directions for its clinical implementation.

Dry eye disease(DED)is a common ocular surface disorder worldwide, primarily characterized by a loss of homeostasis of the tear film, and frequently associated with meibomian gland dysfunction(MGD), decreased tear film stability, ocular discomfort, and visual impairment. In recent years, factors such as the widespread use of digital devices,the aging population, and environmental changes have contributed to a significant increase in its global prevalence, making it a major public health concern. Red light therapy(RLT), also known as low-level laser therapy(LLLT)or photobiomodulation(PBM), is a non-invasive treatment that utilizes low-energy red or near-infrared light to irradiate tissues. It exerts photobiomodulatory effects to promote cellular repair and functional recovery. This therapy has demonstrated considerable potential in treating various ocular conditions. Its broader clinical application could improve therapeutic outcomes, alleviate patient discomfort and financial burden, and reduce the consumption of healthcare resources, thereby yielding significant socio-economic benefits. This paper systematically reviews the multifaceted mechanisms and application prospects of RLT in managing DED, including its anti-inflammatory effects, improvement of meibomian gland function, promotion of conjunctival goblet cell repair, and alleviation of visual fatigue, aiming to provide a theoretical foundation and practical reference for its clinical adoption.

AIM: To explore the therapeutic effect and prognosis of intense pulsed light combined with pralprofen eye drops for meibomian gland cysts in children. METHODS: Children with meibomian gland cysts visited the hospital for treatment from April 2023 to October 2024 were selected as the research subjects. All subjects were grouped using the random number table methed. In the control group, patients were treated with hot compress. In the drug group, patients were treated with pralprofen eye drops combined with hot compress. In the laser group, patients were treated with intense pulsed light combined with hot compress. In the combination group, patients were treated with pralprofen eye drops combined with intense pulsed light and hot compress. The treatment effective rate, cyst surface area, ocular symptom score, and occurrence of adverse reactions of children in each group were compared. RESULTS: A total of 80 children(80 eyes)were enrolled in this study, with 20 cases(20 eyes)in each of the control group, drug group, laser group, and combination group. The mean age was 7.49±1.09 y in the control group(9 males and 11 females), 7.63±0.98 y in the drug group(11 males and 9 females), 7.39±0.59 y in the laser group(12 males and 8 females), and 7.63±1.21 y in the combination group(12 males and 8 females). The total effective rate was 70%(14/20)in the combination group, which was significantly higher than that in the control group, drug group, and laser group(all P<0.05). After treatment, the cyst surface area and ocular symptom scores decreased to varying degrees in all groups. Notably, at 21 d post-treatment, the cyst surface area and ocular symptom scores in the combination group were significantly lower than those in the control group, drug group, and laser group(all P<0.05). No adverse reactions occurred in the combination group, which was lower than that in the control group, drug group, and laser group, with no statistically significant difference among the four groups(P>0.05).CONCLUSION: Intense pulsed light combined with pralprofen eye drops can improve the ocular symptoms of children with meibomian gland cysts, reduce the surface area of meibomian gland cysts, increase the clinical cure rate, and this treatment method is highly safe.

ObjectiveTo investigate the therapeutic effects and mechanisms of Qinlian Hongqutang （QLHQT） on nonalcoholic steatohepatitis （NASH）. MethodsC57BL/6J mice were randomly divided into normal and modeling groups. The NASH model was established by feeding a high-fat diet for 12 weeks. After successful modeling， mice were randomly assigned to the model group， low-， medium-， and high-dose QLHQT groups （0.51， 1.02， and 2.04 g·kg^-1）， and a positive control metformin group， with six mice in each group. The mice were treated for 8 weeks. Body weight was recorded before and after treatment. Serum levels of total cholesterol （TC）， triglycerides （TG）， and low-density lipoprotein cholesterol （LDL-C）， as well as hepatic TC， TG， and LDL-C contents， were determined by biochemical assays. Hematoxylin-eosin （HE） staining and oil red O staining were used to evaluate liver histopathology and lipid deposition， respectively. Flow cytometry， enzyme-linked immunosorbent assay （ELISA）， and Real-time polymerase chain reaction （Real-time PCR） were used to assess hepatic macrophage expression and related markers. Western blot and immunofluorescence were used to investigate the potential mechanisms of QLHQT in regulating macrophage polarization. ResultsCompared with the normal group， body weight and serum and hepatic levels of TC， TG， and LDL-C were significantly increased in the model group （P<0.01）. Liver histopathology showed unevenly distributed round lipid droplets in the hepatocyte cytoplasm， accompanied by inflammatory cell aggregation. Flow cytometry showed that the proportion of CD86-positive cells was significantly increased， whereas the proportion of CD206-positive cells was markedly decreased （P<0.05）. Hepatic inducible nitric oxide synthase （iNOS） levels and tumor necrosis factor-α （TNF-α） mRNA expression were significantly increased， while hepatic IL-10 levels and IL-4 mRNA expression were significantly decreased （P<0.01）. The protein expression levels of Toll-like receptor 4 （TLR4）， tumor necrosis factor receptor-associated factor 6 （TRAF6）， and myeloid differentiation factor 88 （MyD88） in the liver were significantly increased （P<0.01）. Compared with the model group， body weight was reduced in the high-， medium-， and low-dose QLHQT groups and in the metformin group. Serum and hepatic TC， TG， and LDL-C levels were significantly decreased （P<0.01）. Liver histopathology showed alleviated hepatic lipid deposition， with markedly reduced lipid droplets and inflammation. Immunofluorescence and flow cytometry showed that the proportions of CD86-positive cells were significantly decreased， whereas the proportions of CD206-positive cells were significantly increased in the high-， medium-， and low-dose QLHQT groups （P<0.05）. Hepatic iNOS levels and TNF-α mRNA expression were significantly decreased （P<0.01）， whereas hepatic IL-10 levels and IL-4 mRNA expression were significantly increased （P<0.01）. The hepatic protein expression levels of TLR4， TRAF6， and MyD88 were significantly decreased， while signal transducer and activator of transcription 6 （STAT6） phosphorylation was significantly increased （P<0.05， P<0.01）. There was no statistically significant difference in total STAT6 protein expression. ConclusionQLHQT effectively ameliorates hepatic inflammation in NASH mice， and the mechanism may involve STAT6- and TLR4-mediated signaling pathways driving polarization of M1 macrophages toward the M2 phenotype.

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.

Colorectal cancer， a leading malignant gastrointestinal tumor globally in terms of incidence and mortality， has seen a consistent annual rise in newly diagnosed cases. While conventional therapies like radiotherapy， chemotherapy， and surgery are available， problems such as lack of early diagnosis， poor prognosis， and drug resistance remain significant burdens for patients. Given the complex and diverse pathogenesis of colorectal cancer， there is an urgent clinical need for safe， effective， reliable， and multi-targeted therapeutic strategies. The Hippo signaling pathway， closely linked to mechanisms like tumorigenesis， cancer cell invasion， migration， and drug resistance， extensively participates in the occurrence and development of colorectal cancer， so targeting the signaling pathway for cancer prevention and treatment has become a crucial research direction in recent years. Traditional Chinese medicine （TCM） offers multi-faceted， multi-pathway， and multi-target advantages and becomes an important therapy for colorectal cancer by enhancing patients' immunity， improving the life quality， and prolonging survival. Studies show that the active components of TCM， including flavonoids， terpenoids， phenols， alkaloids， quinones， lignans， and saponins， as well as TCM compounds such as modified Sijunzi decoction， Jiedu Sangen decoction， Jianpi Jiedu compound， and Quyu Jiedu decoction， exhibit significant targeting effects on the Hippo signaling pathway. These TCMs can exert an anti-colorectal cancer effect through various mechanisms， such as inducing cancer cell autophagy and apoptosis， inhibiting epithelial-mesenchymal transition， reversing drug resistance of the tumor， and blocking the cancer cell cycle. This paper reviewed and analyzed Chinese and international research on the action mechanisms of TCM in regulating the Hippo signaling pathway for the prevention and treatment of colorectal cancer with a comprehensive overview presentation， aiming to provide new references and ideas for the clinical application of TCM and the development of new pharmacological agents in the prevention and treatment of colorectal cancer.