ObjectiveTo systematically evaluate the application of narrative education in undergraduate nursing teaching， to understand the current application status of narrative education， and to provide a theoretical basis for the subsequent establishment of a sound narrative education system. MethodsA systematic search was conducted for studies published in Chinese and English databases on applying narrative education to undergraduate nursing teaching， with the search period ranging from database inception to February 23， 2025. Literature was screened， and relevant information was extracted. A rigorous quality evaluation was conducted on the included studies， and a descriptive analysis was performed on their content. ResultsA total of 20 papers were included， involving 3，180 research subjects， all of whom were undergraduate nursing students. The results of descriptive analysis showed that the teaching model of narrative education primarily encompassed reading narrative works， watching films and videos， performing narrative scenarios， and writing reflective journals. The course setting and content covered pre-teaching preparation and in-teaching implementation. The evaluation of teaching effectiveness included the evaluation of teachers’ teaching methods （student evaluation/self-evaluation） and the evaluation of students’ learning effectiveness （course grade evaluation/humanistic care scale/empathy scale assessment， and others）. ConclusionNarrative education combines abstract concepts with concrete clinical situations， which not only enriches students’ learning experiences but also enhances their humanistic literacy. Meanwhile， it provides teachers with opportunities to develop their narrative teaching skills， which requires them to possess profound professional knowledge and employ narrative techniques to guide students in reflection and critical thinking， thereby improving teaching quality and learning outcomes. Future efforts should consistently deepen the connotation research of narrative education and build a systematic nursing education system.

Objective: To systematically evaluate the prevalence and influencing factors of screen exposure among preschool children in China, so as to provide evidence for formulating scientific intervention strategies. Methods: Retrieve relevant studies on screen exposure among preschool children from PubMed, Web of Science, Embase, Cochrane Library, China Biomedical Literature Database, CNKI, VIP, and Wanfang databases from the time of estaldishment to June 29, 2025. Meta analysis was performed using Stata 16.0 software. Results: A total of 43 studies were included. Meta analysis showed that the prevalence of screen exposure among preschool children in China was 46.0% (95% CI = 38.9 %-53.1%, P <0.01). Girls, non only child, father s age<35 years, both parents having an educational level of high school or below, being cared for by grandparents, rural residence, parents having no exercise habit, parental support for the use of screen devices, and parental screen time>1 h/d were influencing factors for screen exposure among preschool children [ OR (95% CI ) were 0.85(0.78-0.92), 1.09(1.04-1.15), 1.45(1.22-1.71), 1.38(1.24- 1.54 ), 1.78(1.32-2.40), 1.39(1.16-1.65), 1.38(1.13-1.69), 1.67(1.40-1.98), 1.70(1.38-2.10), 1.59(1.04-2.43), all P <0.05]. Conclusion The prevalence of screen exposure among preschool children in China is relatively high, and relevant child health promotion strategies should be formulated to reduce its occurrence.

Ochratoxin A (OTA) is ubiquitous in the food and feed fields. It has strong hepatotoxicity and nephrotoxicity, seriously threatening the health of humans and animals. Enzymatic degradation of mycotoxins is considered to be a promising method to control mycotoxin contaminations. In this study, a new ochratoxin A amidohydrolase from Microbulbifer thermotolerans (MiADH) was obtained. After heterologous expression in Escherichia coli and purification, the recombinant protein was studied regarding the hydrolysis activity, hydrolysis products, enzymatic properties, and substrate binding mode. MiADH can degrade OTA into ochratoxin α (OTα) and phenylalanine, demonstrating a detoxifying ability. It demonstrated the best performance at 70 ℃ and pH 8.0, and Cu²⁺ had the strongest inhibitory effect on the activity of MiADH. MiADH with good thermal stability exhibited huge potential for industrial application. Rational design guided by three-dimensional structural models and substrate docking analysis revealed the important amino acids affecting substrate binding and obtained multiple mutants with improved activity. Among these mutants, V324A had the highest activity, which was 4.2-fold that of the wild type. The identification of MiADH enriches the ochratoxin A degradation enzyme library and provides a new candidate enzyme for the biological detoxification of ochratoxin A in the food and feed industry.
Amidohydrolases/chemistry* ; Ochratoxins/metabolism* ; Substrate Specificity ; Escherichia coli/metabolism* ; Recombinant Proteins/metabolism* ; Actinomycetales/genetics*

Stearoyl-coenzyme A desaturase 1 (SCD1) catalyzes the rate-limiting step of de novo lipogenesis and modulates lipid homeostasis. Although numerous SCD1 inhibitors were tested for treating metabolic disorders both in preclinical and clinic studies, the tissue-specific roles of SCD1 in modulating obesity-associated metabolic disorders and determining the pharmacological effect of chemical SCD1 inhibition remain unclear. Here a novel role for intestinal SCD1 in obesity-associated metabolic disorders was uncovered. Intestinal SCD1 was found to be induced during obesity progression both in humans and mice. Intestine-specific, but not liver-specific, SCD1 deficiency reduced obesity and hepatic steatosis. A939572, an SCD1-specific inhibitor, ameliorated obesity and hepatic steatosis dependent on intestinal, but not hepatic, SCD1. Mechanistically, intestinal SCD1 deficiency impeded obesity-induced oxidative stress through its novel function of inducing metallothionein 1 in intestinal epithelial cells. These results suggest that intestinal SCD1 could be a viable target that underlies the pharmacological effect of chemical SCD1 inhibition in the treatment of obesity-associated metabolic disorders.

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.

Objective To explore the perioperative trend of heart rate variability(HRV)in patients undergoing aortic valve replacement(AVR)under cardiopulmonary bypass and investigate the influence of age and/or postoperative atrial fibrillation(POAF)on this trend.Methods Baseline and clinical data of 134 patients undergoing AVR due to aortic valve disease in Department of Car-diovascular Surgery of Northern Theater General Hospital of PLA from January 2021 to January 2023 were collected and retrospectively studied.According to the age and/or POAF,they were divided into group A(aged＜60 years,no POAF,49 cases),group B(aged＜60 years,complicated with POAF,21 cases),group C(aged≥60 years,no POAF,30 cases)and group D(aged≥60 years,with POAF,34 cases).The dynamic electrocardiogram indicators were collected in 7 d be-fore and 7 d after operation.The changes in perioperative HRV were also observed.Results After operation,the standard deviation of sinus heart beat RR intervals,average of the standard devia-tions of NN intervals for each 5 min segment of a 24 h HRV recording(SDNNidx),root mean square of successive RR interval differences,and percentage of successive RR intervals that differ by more than 50 ms were significantly lower than those in 7 d before operation[61.172±17.449 ms vs 804.567±230.518 ms,20.284±9.432 ms vs 42.933±12.876 ms,1.307±0.196 ms vs 1.412±0.148 ms,3.00(1.30,7.23)ms vs 5.30(3.00,10.40)ms,P＜0.01].The group D had obvi-ously lower SDNNidx than the group A in 7 d after surgery(42.568±14.749 ms vs 46.467±11.754 ms,P＜0.05).Conclusion Autonomic dysfunction is observed in the early stage after AVR.For the patients aged≥60 years with POAF,the HRV indicators are significantly decreased,the dys-function of the vagus nerve is aggravated,and the disorder is exacerbated because of their syner-gistic effect.

Objective:To study the epidemiological characteristics of human brucellosis in Ordos City and provide reference and theoretical guidance for prevention and control of the disease.Methods:The surveillance data of human brucellosis cases and the serological surveillance data of key occupational populations reported by the Ordos City Center for Disease Control and Prevention from 2013 to 2022 were collected and analyzed descriptively. ArcGIS 10.8 software was used to draw a spatial distribution map of human brucellosis in Ordos City, and SPSS 26.0 software was used to conduct Spearman correlation analysis to further explore the impact of economic factors on human brucellosis.Results:From 2013 to 2022, a total of 8 676 cases of human brucellosis were reported in Ordos City, with an average annual incidence rate of 40.93/100 000. In 2022, 2 570 cases were reported, with an incidence rate of 116.78/100 000, reaching the peak in the past 10 years. The cases were mainly distributed in Dalad Banner, Hangjin Banner, and Otog Front Banner, with a total of 6 415 cases, accounting for 73.94% of the total number of cases. The spatial distribution spread from north to south and from north to east. The majority of cases were in the age group of 40 to 65 years old (6 061 cases, accounting for 69.86%), male (6 089 cases, accounting for 70.18%), and farmers and herdsmen (7 367 cases, accounting for 84.91%). The median time interval between onset and diagnosis was 16 days. The positive rate of serological surveillance in key occupational groups was 5.38% (7 058/131 229). The results of Spearman correlation analysis showed that the number of agricultural legal entities, the number of animal husbandry legal entities, regional gross domestic product, per capita disposable income of rural and pastoral residents, total agricultural output value, the number of cattle and sheep at the end of the year, milk production, and mutton production were important factors affecting the incidence of brucellosis ( P < 0.05). Conclusions:The incidence of brucellosis in Ordos City is on the rise, and the epidemic situation is severe. It is necessary to strengthen the surveillance and joint prevention and control of human brucellosis to prevent the spread and expansion of the epidemic.

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.

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.

POEMS syndrome is a rare condition associated with plasma cell disorders， and it often involves multiple systems and has diverse clinical manifestations. This article reports two cases of POEMS syndrome with hepatosplenomegaly as the initial manifestation. During the course of the disease， the patients presented with lower limb weakness， hepatosplenomegaly， lymph node enlargement， ascites， hypothyroidism， positive M protein， and skin hyperpigmentation， and ¹⁸F-FDG PET-CT imaging revealed bone lesions mainly characterized by osteolytic changes and plasma cell tumors. There was an increase in the serum level of vascular endothelial growth factor. The patients were finally diagnosed with POEMS syndrome， and the symptoms were relieved after immunomodulatory treatment.