This study aims to explore protective effects of Lycium barbarum polysaccharides(LBP)on intestinal damage caused by lipopolysaccharide(LPS)-induced inflammatory bowel disease(IBD)in chicks.Network pharmacology was initially employed to determine the target proteins of wolfberry in the prevention and treatment of IBD.Following this,protein-protein interaction analy-sis,GO and KEGG pathway enrichment analysis,and molecular docking studies were conducted.Subsequently,an animal study was conducted:a total of 100 one-day-old male Hy-line brown lay-ing hens were randomly divided into five groups:a blank control group(CON),an LPS treatment group(LPS),a low-dose LBP group(LPS+LBP 0.25 g/L,L-LBP),a medium-dose LBP group(LPS+LBP 0.5 g/L,M-LBP),and a high-dose LBP group(LPS+LBP 1 g/L,H-LBP).Upon reac-hing 21 days old,duodenal,jejunal,ileal,and cecal tissues were collected to determine SOD and GSH-Px levels.Furthermore,the mRNA expression levels of TNF-α,AKT1,IL-6,IL-1β and TP53 in the intestinal tissues were measured using quantitative real-time PCR.The results demonstrated that network pharmacology identified 45 active ingredients in wolfberry that target 116 key protein sites,including TNF,AKT1 and IL6.The primary objectives focus on signaling pathways including AGE-RAGE,IL-17,TNF,HIF-1,and NF-κB.Molecular docking showed excellent ligand-receptor docking scores,with stable binding facilitated by hydrogen bonds and hydrophobic interactions.Compared to the LPS group,the 0.5 g/L LBP exhibited notably higher levels of SOD and T-AOC.In comparison with the LPS group,the medium and high-dose LBP experimental groups showed notably decreased the mRNA expressions of TNF-α,AKT1,IL-6,and IL-1β,while TP53 mRNA expression was significantly upregulated(P＜0.01).In summary,wolfberry exerts preventive and therapeutic effects on IBD through a multi-component,multi-target,and multi-pathway mecha-nism.

This study aims to explore protective effects of Lycium barbarum polysaccharides(LBP)on intestinal damage caused by lipopolysaccharide(LPS)-induced inflammatory bowel disease(IBD)in chicks.Network pharmacology was initially employed to determine the target proteins of wolfberry in the prevention and treatment of IBD.Following this,protein-protein interaction analy-sis,GO and KEGG pathway enrichment analysis,and molecular docking studies were conducted.Subsequently,an animal study was conducted:a total of 100 one-day-old male Hy-line brown lay-ing hens were randomly divided into five groups:a blank control group(CON),an LPS treatment group(LPS),a low-dose LBP group(LPS+LBP 0.25 g/L,L-LBP),a medium-dose LBP group(LPS+LBP 0.5 g/L,M-LBP),and a high-dose LBP group(LPS+LBP 1 g/L,H-LBP).Upon reac-hing 21 days old,duodenal,jejunal,ileal,and cecal tissues were collected to determine SOD and GSH-Px levels.Furthermore,the mRNA expression levels of TNF-α,AKT1,IL-6,IL-1β and TP53 in the intestinal tissues were measured using quantitative real-time PCR.The results demonstrated that network pharmacology identified 45 active ingredients in wolfberry that target 116 key protein sites,including TNF,AKT1 and IL6.The primary objectives focus on signaling pathways including AGE-RAGE,IL-17,TNF,HIF-1,and NF-κB.Molecular docking showed excellent ligand-receptor docking scores,with stable binding facilitated by hydrogen bonds and hydrophobic interactions.Compared to the LPS group,the 0.5 g/L LBP exhibited notably higher levels of SOD and T-AOC.In comparison with the LPS group,the medium and high-dose LBP experimental groups showed notably decreased the mRNA expressions of TNF-α,AKT1,IL-6,and IL-1β,while TP53 mRNA expression was significantly upregulated(P＜0.01).In summary,wolfberry exerts preventive and therapeutic effects on IBD through a multi-component,multi-target,and multi-pathway mecha-nism.

Objective The mechanism of Huazhuo xingxue decoction(HZXXD)in the treatment of ischemic stroke was explored through network pharmacology,molecular docking and cell validation.Methods TCMSP,TCMID,BATMAN-TCM database and literature search were used to get the chemical components and related target proteins of Huazhuo Xingxue Decoction,and the targets of dementia,stroke and amnesia were obtained from Genecards database and OMIM database.The traditional Chinese medicine-active components-target-network and protein interaction map were constructed by using Cytoscape,and the target was enriched by KEGG pathway by David database.Western blot was used to investigate the effect of HZXXD on inflammation-related core targets expression using oxygen and glucose deprivation/reoxygenation cell model.Finally,Autodock was used for molecular docking of key active ingredients and important targets to evaluate their binding activity.Results 76 active molecules and 33 common targets of herb-disease were screened out.KEGG bioaccumulation results involve multiple inflammatory signal pathways such as TNF,chemical carcinogenesis-reactive oxygen species and HIF-1.TNF-α was found to be the core target of HZXXD by oxygen glucose deprivation/reoxygenation cell experiments.Five compounds with the strongest binding ability to TNF-α,kaempferol,apigenin,aloe-emodin,baicalein and stigasterol,were screened by traditional Chinese medicine-active ingredient-target network map and molecular docking.Conclusion Huazhuo Xingxue Decoction may down regulate the expression of core target TNF-α,kaempferol,apigenin,aloe emodin,baicalein and stigasterol may be the main active substances for TNF-α binding.

Clinical research on rare diseases has always faced multiple challenges in clinical research design and implementation due to small sample sizes of patients,high heterogeneity,and limited research resources.The rapid development of digital intelligence technology has provided innovative solutions for rare disease research.This article systematically explores the current status and response strategies of clinical research on rare diseases in the digital intelligence age.On the one hand,the efficiency of rare disease research has been optimized through adaptive design,mixed trial mode,and precision medicine stratification methods.On the other hand,solutions based on digital technology have been proposed to address the practical challenges of recruitment difficulties and underrepresentation of rare disease clinical research patients,data management and technical barriers,and insufficient coverage of natural medical history and baseline databases through digital intelligence technology.By combining international collaboration,intelligent screening,and remote experiments,a multidisciplinary collaboration and international cooperation,adaptive design,digital data platform,and patient-centered remote research model have been constructed as the core implementation strategies.Typical cases demonstrate that digital intelligence technology not only effectively shortens the drug development cycle,but also significantly enhances patient benefits,providing a replicable practical paradigm for global rare disease research.The practice of digital platforms represented by the International Rare Disease Research Alliance and the China Rare Disease Diagnosis and Treatment Collaboration Network has further verified the feasibility and promotional value of the digitalization path.In summary,digital intelligence technology has shown considerable promise in overcoming the clinical research challenges of rare diseases and accelerating the development of treatment plans,providing systematic references for researchers,regulatory agencies,and patient organizations.It is expected to drive the clinical research of rare diseases towards a more efficient and accurate future.

Clinical research on rare diseases has always faced multiple challenges in clinical research design and implementation due to small sample sizes of patients,high heterogeneity,and limited research resources.The rapid development of digital intelligence technology has provided innovative solutions for rare disease research.This article systematically explores the current status and response strategies of clinical research on rare diseases in the digital intelligence age.On the one hand,the efficiency of rare disease research has been optimized through adaptive design,mixed trial mode,and precision medicine stratification methods.On the other hand,solutions based on digital technology have been proposed to address the practical challenges of recruitment difficulties and underrepresentation of rare disease clinical research patients,data management and technical barriers,and insufficient coverage of natural medical history and baseline databases through digital intelligence technology.By combining international collaboration,intelligent screening,and remote experiments,a multidisciplinary collaboration and international cooperation,adaptive design,digital data platform,and patient-centered remote research model have been constructed as the core implementation strategies.Typical cases demonstrate that digital intelligence technology not only effectively shortens the drug development cycle,but also significantly enhances patient benefits,providing a replicable practical paradigm for global rare disease research.The practice of digital platforms represented by the International Rare Disease Research Alliance and the China Rare Disease Diagnosis and Treatment Collaboration Network has further verified the feasibility and promotional value of the digitalization path.In summary,digital intelligence technology has shown considerable promise in overcoming the clinical research challenges of rare diseases and accelerating the development of treatment plans,providing systematic references for researchers,regulatory agencies,and patient organizations.It is expected to drive the clinical research of rare diseases towards a more efficient and accurate future.

Objective:To investigate the outcomes of natural cycle (NC) and modified natural cycle (MNC) assisted reproductive technology (ART) in patients with diminished ovarian reserve (DOR), and to provide a scientific basis for individualized treatment strategies for DOR patients.Methods:A retrospective cohort analysis was performed on the clinical data of DOR patients who underwent ART at the Center for Reproductive Medicine of the Department of Obstetrics and Gynecology, Peking University Third Hospital from January 1, 2015 to December 31, 2023. Patients were divided into the NC group ( n=801) and the MNC group ( n=385) based on their treatment protocol. The primary outcomes were cycle cancellation rate and oocyte retrieval rate. Secondary outcomes included clinical pregnancy rate and live birth rate per fresh embryo transfer cycle and frozen-thawed embryo transfer cycle, cumulative pregnancy rate and cumulative live birth rate per started cycle and per transfer cycle, as well as laboratory parameters such as the number of retrieved oocytes, the number of two pronuclei (2PN) fertilized oocytes, the number of transferable embryos, and transferable embryo formation rate. Further, multivariate logistic regression was used to analyze the impact of the treatment protocol on pregnancy and live birth outcomes. Results:There were no statistically significant differences between the NC and MNC groups in terms of general characteristics such as age, body mass index, and baseline hormone levels (all P>0.05). The cycle cancellation rate was significantly higher in the NC group [19.10% (153/801)] than in the MNC group [10.65% (41/385), P<0.001], and the oocyte retrieval rate was significantly lower in the NC group [66.31% (431/650)] than in the MNC group [74.86% (259/346), P=0.005]. The number of retrieved oocytes [1 (0,1)], the number of 2PN fertilized oocytes [1 (0,1)], and the number of transferable embryos [0 (0, 1)] were also significantly lower in the NC group than in the MNC group [1 (1, 2), P<0.001; 1 (1, 1), P<0.001; 0 (0, 1), P<0.001]. However, there were no statistically significant differences in 2PN fertilization rate and transferable embryo formation rate between the NC and MNC groups (all P>0.05). In both fresh embryo transfer cycles and frozen-thawed embryo transfer cycles, there were no statistically significant differences in clinical pregnancy rate and live birth rate between the NC and MNC groups (all P>0.05). The cumulative pregnancy rate per started cycle and transfer cycle, the cumulative live birth rate per started cycle and per transfer cycle were also not significantly different between the NC and MNC groups (all P>0.05). Multivariate logistic analysis showed no significant association between NC and clinical pregnancy or live birth compared with MNC. Conclusion:While MNC to some extent reduced the cycle cancellation rate and improved oocyte retrieval rates compared with NC, it did not ultimately improve pregnancy outcomes in DOR patients.

Objective:To explore the relationship between life events, anxiety, depression, and behavior problems in adolescents.Methods:From September to October 2022, the cluster sampling method was used to select 5 341 adolescents from 4 middle schools in Xinxiang urban area.The subjects and their parents were investigated by the adolescent self-rating life events check list (ASLEC), generalized anxiety disorder scale (GAD-7), patient health questionnaire (PHQ-9), and child behavior checklist (CBCL). SPSS 27.0 software was used for Spearman correlation analysis, and AMOS 28.0 software was used to construct the structural equation model.Results:The scores of anxiety, depression, and behavioral problems were 1 (0, 4), 1 (0, 4), and 3 (0, 10). The total score of life events was 5 (1, 13), and the dimensions scored as follows: interpersonal conflict 1 (0, 4), academic pressure 2 (0, 5), punishment 0 (0, 2), loss 0 (0, 0), health and adaptation problem 0 (0, 1), and others 0 (0, 2). There were positive correlations between life events and its dimensions, depression, anxiety and behavioral problems ( r=0.28-0.69, all P<0.01). In the overall population, anxiety and depression played parallel mediating roles in the impact of life events on behavior problems. Life events could positively predict anxiety ( β=0.68, P<0.01), and anxiety could positively predict behavior problems ( β=0.04, P=0.02). Life events could positively predict depression ( β=0.77, P<0.01), and depression could positively predict behavior problems ( β=0.18, P<0.01). The standardized total effect size of the impact of life events on behavioral problems was 0.622 (95% CI=0.564-0.675). The standardized direct effect size and indirect effect size were 0.460 (95% CI=0.374-0.539) and 0.162 (95% CI=0.108-0.218), accounting for 74.0% and 26.0%of the total effect, respectively. After stratification by gender, the results for male adolescents were consistent with the overall population, while the mediating effect of anxiety was not significant in the female adolescents. Conclusion:Life events can lead to anxiety and depression in adolescents, thereby increasing the risk of behavior problems.

Objective:To explore the relationship between life events, anxiety, depression, and behavior problems in adolescents.Methods:From September to October 2022, the cluster sampling method was used to select 5 341 adolescents from 4 middle schools in Xinxiang urban area.The subjects and their parents were investigated by the adolescent self-rating life events check list (ASLEC), generalized anxiety disorder scale (GAD-7), patient health questionnaire (PHQ-9), and child behavior checklist (CBCL). SPSS 27.0 software was used for Spearman correlation analysis, and AMOS 28.0 software was used to construct the structural equation model.Results:The scores of anxiety, depression, and behavioral problems were 1 (0, 4), 1 (0, 4), and 3 (0, 10). The total score of life events was 5 (1, 13), and the dimensions scored as follows: interpersonal conflict 1 (0, 4), academic pressure 2 (0, 5), punishment 0 (0, 2), loss 0 (0, 0), health and adaptation problem 0 (0, 1), and others 0 (0, 2). There were positive correlations between life events and its dimensions, depression, anxiety and behavioral problems ( r=0.28-0.69, all P<0.01). In the overall population, anxiety and depression played parallel mediating roles in the impact of life events on behavior problems. Life events could positively predict anxiety ( β=0.68, P<0.01), and anxiety could positively predict behavior problems ( β=0.04, P=0.02). Life events could positively predict depression ( β=0.77, P<0.01), and depression could positively predict behavior problems ( β=0.18, P<0.01). The standardized total effect size of the impact of life events on behavioral problems was 0.622 (95% CI=0.564-0.675). The standardized direct effect size and indirect effect size were 0.460 (95% CI=0.374-0.539) and 0.162 (95% CI=0.108-0.218), accounting for 74.0% and 26.0%of the total effect, respectively. After stratification by gender, the results for male adolescents were consistent with the overall population, while the mediating effect of anxiety was not significant in the female adolescents. Conclusion:Life events can lead to anxiety and depression in adolescents, thereby increasing the risk of behavior problems.

Objective:To analyze the clinical characteristics of warfarin-related nephropathy (WRN).Methods:Medical records of patients with WRN admitted to Linyi People′s Hospital Affiliated to Shandong Second Medical University from January 1, 2020 to December 31, 2024 were collected. The patients′ basic information (gender, age), warfarin medication details (indications, dosage, frequency, etc.), comorbidities, concomitant medication usage, international normalized ratio (INR) and serum creatinine (Scr) test results before and after the occurrence of WRN, as well as the clinical manifestations, interventions, and outcomes of WRN were extracted. The causal relationship between warfarin and renal dysfunction was evaluated according to the Adverse Drug Reaction Reporting and Monitoring Manual. The clinical data of patients were descriptively and statistically analyzed. Results:A total of 11 patients were entered in the analysis, including 7 males and 4 females; the age ranged from 49 to 85 years, with a median age of 70 years, and 9 cases were older than 60 years. The causality evaluation showed that 3 patients were definite and 8 patients were probable. All the 11 patients had at least one comorbidity, including 6 cases of heart failure, 6 cases of hypoproteinemia, 4 cases of chronic kidney disease, 3 cases of hypertension, 3 cases of pulmonary infection, and 1 case of diabetes. Seven patients were treated with warfarin combined with broad-spectrum antibiotics, 6 combined with diuretics, and 3 combined with renin angiotensin system blockers. The time from the highest INR to the highest Scr level was 0-6 days, with a median time of 2 days, and it was ≤2 days in 9 patients. Six patients had bleeding manifestations such as microscopic hematuria, melena, epistaxis, hematochezia, and skin ecchymosis. Among the 11 patients, 10 stopped warfarin immediately and 1 reduced dosage. All patients received different doses of vitamin K 1 according to the INR level. Among the 6 patients of bleeding, 4 received symptomatic treatments such as omeprazole, tranexamic acid, somatostatin, thrombin powder and octreotide, and 2 patients received hemodialysis due to high Scr level. One patient with severe anemia received blood transfusion. After 1-5 days of treatments (with a median time of 2 days), the INR in all patients decreased to <3.00, of which 5 patients continued to take warfarin, 1 changed warfarin to rivaroxaban, and 5 did not continue anticoagulation therapy. After 2 to 14 days of treatments, Scr in 8 patients recovered to the reference value range, and Scr in 3 patients was still at a high level, of which 1 patient died of unexplained cardiac arrest. Conclusions:WRN is a common adverse reaction of warfarin, with or without bleeding. After the occurrence of WRN, the drug should be stopped as soon as possible and symptomatic treatment should be given. The prognosis is generally good, but it may also lead to chronic kidney disease.

Objective Traditional methods for sample size estimation in clinical trial do not consider the patient size applicable to the results during the estimation process,and use point estimation for unknown true values of parameters,which has certain limitations in rare disease clinical trials.This article introduces a sample size estimation method based on Bayesian decision theory.Methods This article proposes a Tripartite Balanced Benefit Function(TBBF)and constructs a benefit function model based on the characteristics of acute and chronic diseases.The sample size in clinical trial is determined by maximizing expected benefits.Results The case analysis of hemophilia B demonstrated the application process of the model,and the sample size obtained by maximizing expected benefits is feasible in practical situations.This method has the advantage of being suitable for estimating sample sizes in small sample clinical trials.Conclusion TBBF fully utilizes prior information,incorporates patient size into the estimation process,and makes the quantitative form of different stakeholders'interests clearer,making the decision-making process more scientific and interpretable.