By analyzing the current status of randomized controlled trials （RCTs） on functional dyspepsia （FD） and irritable bowel syndrome （IBS） comorbidity， we identified several critical issues which include insufficient repor-ting of FD and IBS subtypes， inadequate risk assessment of drug combination， lack of composite， objective， and long-term outcomes， and weak evidence support for clinical practice guidelines. It is suggested that future clinical research on FD-IBS comorbidity should further strengthen the application of real-world studies. The use of composite outcomes and long-term follow-up is recommended to improve the quality of evidence， while greater attention should be paid to patients' preferences and self-management to enhance the applicability of findings. Based on the existing issues in clinical studies of traditional Chinese medicine （TCM） for FD-IBS comorbidity， we propose to consolidate the foundation of TCM-specific efficacy evaluation to better reflect the advantages of syndrome differentiation and treatment， optimize real-world study designs to better support clinical decision- making， and introduce intelligent objective evaluation technologies to improve the objectivity and accuracy of TCM clinical efficacy assessment.

By analyzing the current status of randomized controlled trials （RCTs） on functional dyspepsia （FD） and irritable bowel syndrome （IBS） comorbidity， we identified several critical issues which include insufficient repor-ting of FD and IBS subtypes， inadequate risk assessment of drug combination， lack of composite， objective， and long-term outcomes， and weak evidence support for clinical practice guidelines. It is suggested that future clinical research on FD-IBS comorbidity should further strengthen the application of real-world studies. The use of composite outcomes and long-term follow-up is recommended to improve the quality of evidence， while greater attention should be paid to patients' preferences and self-management to enhance the applicability of findings. Based on the existing issues in clinical studies of traditional Chinese medicine （TCM） for FD-IBS comorbidity， we propose to consolidate the foundation of TCM-specific efficacy evaluation to better reflect the advantages of syndrome differentiation and treatment， optimize real-world study designs to better support clinical decision- making， and introduce intelligent objective evaluation technologies to improve the objectivity and accuracy of TCM clinical efficacy assessment.

Objective: Adolescent depression is a highly prevalent and disabling mental disorder with unclear pathophysiology and unfavorable treatment outcomes. Recent efforts have been focusing on searching for biomarkers as specific indicators of adolescent depression. We performed a systematic literature review and meta-analysis, specifically including studies with healthy control groups as an inclusion criterion. This approach helps to avoid confounding factors and provides more accurate results regarding the inflammatory and immune biomarkers associated with adolescent depression. Methods: Three electronic databases were searched for studies comparing the means and changes in the biomarkers between depressed adolescent patients and healthy controls published in English until February 2024. Two authors independently performed the screening, quality assessment, and data extraction of the studies. A meta-analysis was conducted on outcomes reported by two or more studies using a random-effects model and presented Forrest plots and test statistics (I2) for heterogeneity analysis. Results: Nine studies were included in the review, including seven case-control studies and two cross-sectional studies. These studies included 24 target biomarkers, 13 of which were quantified in 2 or more studies. Compared to the healthy controls, the depressed adolescents had significantly higher values in ten indicators. Additionally, the depressed adolescents had lower procalcitonin levels than the healthy controls. The two groups showed no significant differences in the remaining 13 biomarkers. Conclusion Our findings offer fresh insights into the pathophysiology of inflammatory and immune aspects of adolescent depression and provide helpful guidance in developing targeted and effective intervention and prevention strategies to address adolescent depression.

Background: Obesity and chronic pain are related in both directions, according to earlier observational research.This research aimed to analyze the causal association between obesity and chronic pain at the genetic level, as well as to assess whether common factors mediate this relationship. Methods: This study used bidirectional two sample Mendelian randomization (MR) technique to analyze the association between obesity and chronic pain. Obesity's summary genome-wide association data were obtained from European ancestry groups, as measured by body mass index (BMI), waist-to-hip ratio, waist circumference (WC), and hip circumference (HC), genome-wide association study data for chronic pain also came from the UK population, including chronic pain at three different sites (back, hip, and headache), chronic widespread pain (CWP), and multisite chronic pain (MCP). Secondly, a two-step MR and multivariate MR investigation was performed to evaluate the mediating effects of several proposed confounders. Results: The authors discovered a link between chronic pain and obesity. More specifically, a sensitivity analysis was done to confirm the associations between greater BMI, WC, and HC with an increased risk of CWP and MCP.Importantly, the intermediate MR results suggest that education levels and smoking initiation may mediate the causal relationship between BMI on CWP, with a mediation effect of 23.08% and 15.38%, respectively. Conclusions The authors’ findings demonstrate that the importance of education and smoking in understanding chronic pain’s pathogenesis, which is important for the primary prevention and prognosis of chronic pain.

Background: Obesity and chronic pain are related in both directions, according to earlier observational research.This research aimed to analyze the causal association between obesity and chronic pain at the genetic level, as well as to assess whether common factors mediate this relationship. Methods: This study used bidirectional two sample Mendelian randomization (MR) technique to analyze the association between obesity and chronic pain. Obesity's summary genome-wide association data were obtained from European ancestry groups, as measured by body mass index (BMI), waist-to-hip ratio, waist circumference (WC), and hip circumference (HC), genome-wide association study data for chronic pain also came from the UK population, including chronic pain at three different sites (back, hip, and headache), chronic widespread pain (CWP), and multisite chronic pain (MCP). Secondly, a two-step MR and multivariate MR investigation was performed to evaluate the mediating effects of several proposed confounders. Results: The authors discovered a link between chronic pain and obesity. More specifically, a sensitivity analysis was done to confirm the associations between greater BMI, WC, and HC with an increased risk of CWP and MCP.Importantly, the intermediate MR results suggest that education levels and smoking initiation may mediate the causal relationship between BMI on CWP, with a mediation effect of 23.08% and 15.38%, respectively. Conclusions The authors’ findings demonstrate that the importance of education and smoking in understanding chronic pain’s pathogenesis, which is important for the primary prevention and prognosis of chronic pain.

Schizophrenia (SZ) stands as a severe psychiatric disorder. This study applied diffusion tensor imaging (DTI) data in conjunction with graph neural networks to distinguish SZ patients from normal controls (NCs) and showcases the superior performance of a graph neural network integrating combined fractional anisotropy and fiber number brain network features, achieving an accuracy of 73.79% in distinguishing SZ patients from NCs. Beyond mere discrimination, our study delved deeper into the advantages of utilizing white matter brain network features for identifying SZ patients through interpretable model analysis and gene expression analysis. These analyses uncovered intricate interrelationships between brain imaging markers and genetic biomarkers, providing novel insights into the neuropathological basis of SZ. In summary, our findings underscore the potential of graph neural networks applied to multimodal DTI data for enhancing SZ detection through an integrated analysis of neuroimaging and genetic features.
Humans ; Schizophrenia/pathology* ; Diffusion Tensor Imaging/methods* ; Male ; Female ; Adult ; Brain/metabolism* ; Young Adult ; Middle Aged ; White Matter/pathology* ; Gene Expression ; Nerve Net/diagnostic imaging* ; Graph Neural Networks

OBJECTIVE: Microcirculatory disturbance is pathologically critical to acute pancreatitis (AP), which can be effectively alleviated by traditional Chinese medicine (TCM) formulas that activate blood flow. However, there has been no evidence-based research to date. Therefore, a well-designed systematic review and meta-analysis is necessary to elucidate the therapeutic transformative benefit of improving microcirculation during AP. This study aims to confirm the therapeutic efficacy of TCM formulas and explore the potential mechanisms underlying their effects on AP treatment. METHODS: Studies from eight databases including Pubmed, Embase, Web of Science, Cochrane Library, CNKI, CBM, Wanfang, and Chinese VIP, were screened for the eligible randomized controlled trials (RCTs). The APACHE II score and effectiveness rate were set as primary outcomes, while mortality rate, complications, total hospital stays, serum amylase recovery time, the time until the disappearance of abdominal pain, microcirculation indicators, and inflammation indicators were chosen as secondary outcomes. A systematic review and meta-analysis were subsequently conducted. Network pharmacology analysis was performed to analyze potential bioactive components with relevant targets of the core herbs included in the TCM formulas for activating blood flow. RESULTS: A total of 51 RCTs (n = 3 721) were included. Compared with conventional western medical treatments alone, TCM groups were associated with lower APACHE II score (SMD =  - 1.36, 95% CI: -2.01 to - 0.71, P = 0.000) and higher effectiveness rate (RR: 1.22, 95% CI: 1.18 to 1.26, P = 0.000). Furthermore, the formulas for activating blood flow demonstrated significant efficacy in improving both microcirculation and inflammation indicators. Additionally, six core Chinese herbal medicines including Rhei Radix et Rhizoma with the highest frequency, Aurantii Fructus Immaturus, Paeoniae Radix Rubra, Bupleuri Radix, Salviae Miltiorrhizae Radix et Rhizoma, and Corydalis Rhizoma were filtered out from the adopted TCM formulas. Finally, 166 shared targets between the six herbs and AP were identified. KEGG analysis indicated that lipid and atherosclerosis pathway is highly related to microcirculation. CONCLUSION TCM formulas for activating blood flow significantly improve microcirculation and alleviate AP. Further high-quality, well-designed RCTs and deep mechanism exploration are required.

AIM: To investigate the specific molecular mechanism of Yinqiao Powder in affecting macrophage polarization in herpes simplex keratitis(HSK)through the cyclic GMP-AMP synthetase(cGAS)-stimulator of interferon genes(STING)-interferon regulatory factor 3(IRF3)molecular pathway.METHODS:Human corneal epithelial cells(HCE-T)were divided into control, HSK, and HSK + Yinqiao Powder groups. M0 macrophages were grouped as Ctrl, HSV-1, HSV-1+oe-cGAS, HSV-1+Yinqiao Powder, and HSV-1+oe-cGAS+Yinqiao Powder. Conditional medium(CM)from each group of M0 macrophages was collected to intervene in HCE-T cells and divided into Ctrl-CM, HSV-1-CM, HSV-1+oe-cGAS-CM, and HSV-1+Yinqiao Powder-CM groups. Cell viability was detected by MTT assay, and apoptosis was detected by TUNEL assay. ELISA was used to detect the concentrations of Arg-1 and iNOS in cell supernatants, and Western blotting was used to detect the relative protein expressions of cGAS, STING, and IRF3. Balb/c mice were divided into control, model, and drug groups. The model and drug groups were inoculated with HSV-1 on the cornea of Balb/c mice using the corneal scratch method to construct an HSK mouse model, and the drug group was treated with Yinqiao Powder. The incidence and mortality of the three groups were compared on days 1, 3, 5, 7, and 14 after modeling.RESULTS:Compared with the control group, the HCE-T cell viability in the HSK group was decreased but apoptosis was increased, which was reversed by Yinqiao Powder intervention. Compared with the Ctrl group, the Arg-1 concentration in the cell supernatant of the HSV-1 group was decreased, the iNOS concentration was increased, and the protein expressions of cGAS, STING, and IRF3 were decreased. Compared with the HSV-1 group, the Arg-1 concentration was increased, the iNOS concentration was decreased, and the protein expressions of cGAS, STING, and IRF3 were enhanced in the HSV-1+oe-cGAS group and the HSV-1+Yinqiao Powder group, and the same results were obtained in the HSV-1+oe-cGAS+Yinqiao Powder group. Compared with the Ctrl-CM group, the HCE-T cell viability was decreased and apoptosis was increased in the HSV-1-CM group, which was reversed by overexpressing cGAS in macrophages or intervening with Yinqiao Powder. In vivo experiments found that Yinqiao Powder intervention could improve the pathological progression of keratitis.CONCLUSION:Yinqiao Powder inhibits M1 polarization of macrophages through the cGAS-STING-IRF3 molecular pathway, thereby delaying the progression of HSK.

Antimicrobial resistance (AMR) has emerged as a major global public health challenge, with traditional prevention and control methods exhibiting significant limitations in detection efficiency, data processing, and clinical decision-making. Leveraging its robust capabilities in data analysis and pattern recognition, artificial intelligence (AI) technology has been widely applied across multiple critical aspects of AMR containment. Current evidence demonstrates that AI technologies can significantly enhance the efficiency of resistancediagnosis, optimize personalized treatment strategies, and improve real-time monitoring of resistant pathogen transmission. Despite persistent challenges such as data heterogeneity, model interpretability, and ethical compliance in practical applications, AI holds immense promise in supporting precision infection management and addressing the growing crisis of antimicrobial resistance.This article systematically reviews the clinical applications of AI in AMR prevention and control, including resistance detection and prediction based on mass spectrometry and genomic data, the use of clinical decision support systems in anti-infective therapy, as well as the role of AI in epidemiological surveillance, pathogen tracking, early warning systems, and novel antimicrobial drug discovery aiming to provide reference for clinical practice.