BackgroundAnxiety exhibits a rising prevalence among college students. Investigating the mechanisms through which family function relates to anxiety and examining the moderating role of emotion regulation strategies within this context hold substantial implications for promoting mental health among college students. However， existing research has not sufficiently elucidated the complex interplay among family function， emotion regulation， and anxiety among college students. Further research is warranted to clarify the underlying mechanisms linking family function to anxiety outcomes and to examine the potential moderating role of emotion regulation strategies in this causal pathway. ObjectiveTo explore the relationship between family function and anxiety among lower-grade college students， and to validate the moderating role of emotion regulation strategies in this relationship， thereby offering evidence-based insights for anxiety reduction interventions in this population. MethodsIn March 2023， a total of 1 980 first- and second-year students from a comprehensive university in Shanghai were selected using the cluster sampling method. A self-designed demographic questionnaire， the Emotion Regulation Questionnaire （ERQ）， the Family Adaptability and Cohesion Evaluation Scale Ⅱ-Chinese Version （FACES Ⅱ-CV）， and the Symptom Checklist-90 （SCL-90） were utilized for assessment. Pearson correlation analysis and Spearman correlation analysis were employed to test the correlations of each variable. Hierarchical linear regression analysis was conducted to certify the moderating role of emotion regulation strategies in the relationship between family function and anxiety. ResultsCompared with female students， male students scored significantly lower on ERQ cognitive reappraisal （t=-5.793， P<0.01） but significantly higher on ERQ expressive suppression （t=8.359， P<0.01）. For lower-grade college students， scores on adaptability and cohesion subscales of FACES Ⅱ-CV showed a positive association with cognitive reappraisal in ERQ （r=0.251， 0.302， P<0.01）， while simultaneously displaying negative correlations with both expressive suppression in ERQ （r=-0.113， -0.154， P<0.01） and anxiety in SCL-90 （r=-0.243， -0.202， P<0.01）. Notably， anxiety scores in SCL-90 were inversely related to cognitive reappraisal scores in ERQ （r=-0.159， P<0.01） but directly associated with expressive suppression scores in ERQ （r=0.171， P<0.01）. Hierarchical regression analysis indicated that cognitive reappraisal significantly moderated the relationship between family cohesion and anxiety （β=-0.421， P<0.01）. ConclusionThe cognitive reappraisal strategy serves as a moderator in the relationship between family cohesion and anxiety， potentially mitigating the escalation of anxiety levels associated with family dysfunction. ［Funded by Science and Technology Development Fund of Shanghai Pudong New Area （number， PKJ2023-Y21）］

Objective: To develop a depression recognition model by integrating the spirit-expression diagnostic framework of traditional Chinese medicine (TCM) with machine learning algorithms. The proposed model seeks to establish a TCM-informed tool for early depression screening, thereby bridging traditional diagnostic principles with modern computational approaches. Methods: The study included patients with depression who visited the Shanghai Pudong New Area Mental Health Center from October 1, 2022 to October 1, 2023, as well as students and teachers from Shanghai University of Traditional Chinese Medicine during the same period as the healthy control group. Videos of 3 – 10 s were captured using a Xiaomi Pad 5, and the TCM spirit and expressions were determined by TCM experts (at least 3 out of 5 experts agreed to determine the category of TCM spirit and expressions). Basic information, facial images, and interview information were collected through a portable TCM intelligent analysis and diagnosis device, and facial diagnosis features were extracted using the Open CV computer vision library technology. Statistical analysis methods such as parametric and non-parametric tests were used to analyze the baseline data, TCM spirit and expression features, and facial diagnosis feature parameters of the two groups, to compare the differences in TCM spirit and expression and facial features. Five machine learning algorithms, including extreme gradient boosting (XGBoost), decision tree (DT), Bernoulli naive Bayes (BernoulliNB), support vector machine (SVM), and k-nearest neighbor (KNN) classification, were used to construct a depression recognition model based on the fusion of TCM spirit and expression features. The performance of the model was evaluated using metrics such as accuracy, precision, and the area under the receiver operating characteristic (ROC) curve (AUC). The model results were explained using the Shapley Additive exPlanations (SHAP). Results: A total of 93 depression patients and 87 healthy individuals were ultimately included in this study. There was no statistically significant difference in the baseline characteristics between the two groups (P > 0.05). The differences in the characteristics of the spirit and expressions in TCM and facial features between the two groups were shown as follows. (i) Quantispirit facial analysis revealed that depression patients exhibited significantly reduced facial spirit and luminance compared with healthy controls (P < 0.05), with characteristic features such as sad expressions, facial erythema, and changes in the lip color ranging from erythematous to cyanotic. (ii) Depressed patients exhibited significantly lower values in facial complexion L, lip L, and a values, and gloss index, but higher values in facial complexion a and b, lip b, low gloss index, and matte index (all P < 0.05). (iii) The results of multiple models show that the XGBoost-based depression recognition model, integrating the TCM “spirit-expression” diagnostic framework, achieved an accuracy of 98.61% and significantly outperformed four benchmark algorithms—DT, BernoulliNB, SVM, and KNN (P < 0.01). (iv) The SHAP visualization results show that in the recognition model constructed by the XGBoost algorithm, the complexion b value, categories of facial spirit, high gloss index, low gloss index, categories of facial expression and texture features have significant contribution to the model. Conclusion This study demonstrates that integrating TCM spirit-expression diagnostic features with machine learning enables the construction of a high-precision depression detection model, offering a novel paradigm for objective depression diagnosis.

Fundus neovascular diseases(FNDs)are ocular diseases caused by pathological changes in retinal blood vessels, which are the leading cause of visual impairment globally. The overexpression of vascular endothelial growth factor(VEGF)plays an important role in the formation of new blood vessels, and the current first-line treatment for FNDs is anti-VEGF drugs. The eyes have a special blood-eye barrier, which makes it difficult for eye drops, oral or intravenous drugs to enter the eye and exert their effects. Intraocular injection can bypass this barrier and directly inject drugs into the eye, which is the main route of administration for the treatment of eye diseases. Compared with systemic administration, it is more conducive to enrich the drug at the target site and reduce systemic adverse reactions. Intraocular administrations include intravitreal injection(IVI), suprachoroidal space(SCS)injection, subretinal injection(SRI), drug delivery systems and other invasive intraocular treatments. Previous studies have shown that different intraocular administration methods can affect the pharmacokinetic(PK)properties of drugs. This article reviews the PK changes of anti-VEGF drugs under different intraocular administration methods.

This article reports a diagnostically and therapeutically challenging case of small intestinal marginal zone lymphoma. The patient presented with recurrent abdominal pain as the chief complaint, and imaging revealed multifocal small bowel wall thickening with high uptake, multisegmental luminal stenosis, and proximal dilation. Initial diagnostic workup, including gastroscopy, colonoscopy, and enteroscopy with biopsy, failed to establish a definitive diagnosis. Empirical anti-tuberculosis therapy was ineffective. A repeat enteroscopic biopsy performed over eight months after symptom onset eventually confirmed the diagnosis of mucosa-associated lymphoid tissue (MALT) extranodal marginal zone lymphoma. Despite three different chemotherapy regimens, the patient's intestinal obstruction symptoms persisted, with imaging still showing multifocal bowel wall thickening and hypermetabolic activity. A critical diagnostic dilemma arose regarding whether the PET/CT-positive lesions represented residual lymphoma or fibrotic scarring, whether further chemotherapy adjustments were warranted, and whether surgical resection was necessary. Multidisciplinary discussion concluded that imaging had limited discriminatory value in this scenario and that surgical intervention should be pursued if feasible. The patient successfully underwent partial small bowel resection, with postoperative pathology confirming no residual lymphoma but significant fibrotic changes. The patient has since resumed a normal diet, with body weight nearly restored to pre-illness levels. This case highlights that fibrotic transformation is a common sequela of treated marginal zone lymphoma and that PET/CT may misleadingly suggest residual disease, potentially leading to unnecessary chemotherapy. Timely surgical intervention is crucial in such scenarios.

Purpose/Significance To summarize the application progress of artificial intelligence (AI) in the field of digestive endoscopy, to analyze the key challenges and look forward to future trends, so as to provide guidance for clinical practice and research. Method/Process Domestic and international literature databases such as PubMed, Web of Science, and CNKI are retrieved. The application research of AI in the auxiliary diagnosis, process optimization and treatment precision of digestive endoscopy is sorted out. Result/Conclusion Although AI has significant clinical value in the field of digestive endoscopy, its application still faces major challenges, and its prospects and limitations need to be further discussed.

The incidence and mortality rates of hepatocellular carcinoma(HCC)remain high in China,and the application of surgical resection is often limited due to the fact that most patients are in the advanced stage at the time of confirmed diagnosis.This article reviews commonly used advanced locoregional therapies for HCC and the advances in mainstream techniques such as local ablation(radiofrequency ablation,microwave ablation,irreversible electroporation,and cryoablation),intravascular intervention(transcatheter arterial chemoembolization,hepatic arterial infusion chemotherapy,and Y90 hepatic arterial infusion chemotherapy),and radiotherapy(CyberKnife,proton therapy,and heavy-ion therapy),and a multidimensional decision-making framework is constructed for HCC locoregional therapy by comparing treatment principles,indications,limitations,and clinical data of these techniques.This article aims to provide evidence-based support for persistent dilemmas in clinical decision-making,promote the role of locoregional therapies in clinical practice,and propose the directions for future research and clinical application.This article also establishes a comprehensive clinical roadmap for HCC locoregional therapy,which helps to address current challenges regarding technique selection and delineate future directions for innovation,in order to reshape the treatment of HCC through technological integration and paradigm innovation.

Circular RNA(circRNA),as a kind of non-coding RNA,regulates a variety of biological functions.To explore the effect of circRNA on PEDV replication in the host porcine intestinal epi-thelial cells,this study screened and analyzed the differentially expressed circRNAs by bioinforma-tic software in African Green Monkey renal cells(Vero-E6 cells)infected by porcine epidemic di-arrhea virus(PEDV),the differentially expressed circRNA ssc_circ_PIK3C2A was identified and the secondary structure was analyzed.PCR was used to identify the ssc_circ_PIK3C2A circRNA structure,the model of PEDV-infected IPEC-J2 cells was constructed,the TCID50 test was used to validate the viral titer of PEDV.The expression of circ_PIK3C2A was detected by qRT-PCR in IPEC-J2 infected by PEDV.circ_PIK3C2A qRT-PCR was performed to detect the expression of N gene of PEDV when ssc_circ_PIK3C2A was over-expressed in IPEC-J2 cells.The results showed that ssc_circ_PIK3C2 A is a porcine circular RNA with a typical circular structure,the virus titer of PEDV reached 10-6/mL after PEDV infected IPEC-J2 cells for 48 h,the expression of circ_PIK3C2A increased extremely(P＜0.01)at 6 h after PEDV-infection,with the extension of infec-tion time,its expression gradually decreased,and the expression was the lowest at 24 h,but there was no time-dependent trend.The expression of PEDV N gene decreased significantly when ssc_circ_PIK3C2A was over-expressed in IPEC-J2 cells.In conclusion,when PEDV infects IPEC-J2 cells,the expression of porcine circ_PIK3C2A decreases,and replication of PEDV increases signifi-cantly in IPEC-J2 cells.our result provides a basis for further study of the mechanism of circular RNA on PEDV replication and its physiological activities in host cells in the future.

Objective To compare the induction effects of direct treatment with low-temperature plasma(LTP)and treatment with plasma-activated medium(PAM)on immunogenic cell death(ICD)of melanoma cells.Methods After direct treatment of melanoma cell line B16F10 with LTP and treatment of it with PAM for 24 hours,cell viability was detected by MTT assay.Flow cytometry was used to detect cell apoptosis and the expression of calreticulin(CRT)on the cell surface.The adenosine triphosphate(ATP)content in the culture medium was detected by an ATP detection kit.The content of high-mobility group box 1(HMGB1)in the cell culture medium was detected by ELISA.B16F10 cells treated with LTP were co-cultured with immature dendritic cells(DC)DC2.4 cell line,and flow cytometry was used to detect DC surface molecules CD80 and CD86.Results Compared with the control group,both direct treatment and indirect treatment could lead to a decrease in the viability of B16F10 cells,an increase in the apoptosis rate,an increase in intracellular ROS,an increase in CRT expression,and an increase in the secretion of ATP and HMGB1(P＜0.05).At the same treatment time,the expression of CRT and the release of ATP in B16F10 cells directly treated with LTP were higher than those indirectly treated with PAM(P＜0.05).Compared with the DC2.4 group,the expression proportion of the DC cell maturation marker molecule CD80 was significantly increased in LTP-120s group,LTP-180s group,PAM-120s group,and PAM-180s group.The expression proportion of the DC cell maturation marker molecule CD86 was significantly increased in LTP-120s group,LTP-180s group,and PAM-180s group,and the difference was statistically significant(P＜0.05).Conclusion Both direct treatment with LTP and indirect treatment with PAM can induce ICD in melanoma cells.The direct treatment with LTP has a better induction effect.

DKD is a common microvascular complication of diabetes mellitus and the main cause of chronic kidney disease in China.Asprosin is a novel adipokine,which plays an important regulatory role in IR,glucose and lipid metabolism,inflammatory response and mitochondrial function.Asprosin is closely related to diabetes mellitus,obesity and other diseases,and may be involved in the pathophysiological process of DKD.Asprosin is expected to become a new biomarker and potential therapeutic target for early screening and diagnosis of DKD.Therefore,this article reviews the research progress of Asprosin in DKD.

Objective To explore the influencing factors of immune-associated thyroid dysfunction caused by sintilimab treatment in solid tumors and construct a prediction model.Methods Medical records of patients diagnosed with solid tumors and treated with sintilimab at Peking University People's Hospital(Xizhimen Campus,Tongzhou Campus,Shijiazhuang Campus)from January 2023 to September 2024 were collected to explore the influencing factors that caused immune-related thyroid dysfunction using univariate and multifactorial binary logistic regression analyses and to establish a prediction model.The predictive effect of the model was assessed using the receiver operating characteristic(ROC)curve.Results A total of 120 patients were included,and 33 presented with immune-related thyroid dysfunction.Multifactorial logistic regression analysis revealed that thyroid-stimulating hormone(TSH)[OR=2.470,95%CI=(1.279,4.771)]and treatment cycles[OR=1.298,95%CI=(1.117,1.509)]were independent risk factors for the occurrence of immune-associated thyroid dysfunction,and the difference was statistically significant(P＜0.05).The area under the ROC curve was(0.897±0.043)[95%CI=(0.813,0.981)],the Yoden index was 0.703,and the model prediction accuracy was 86.5%.Conclusion The risk of immune-related thyroid dysfunction caused by sintilimab is high,and TSH and treatment cycle are the influencing factors,and the constructed model has certain predictive value and is of reference significance.