BACKGROUND:Autophagy,as a key regulatory mechanism of cell development,plays an important role in different stages of embryonic development.The mechanism of how autophagy regulates embryonic development through histone modifications is currently unclear.OBJECTIVE:To investigate the effect of autophagy on trimethylation of lysine 4 on histone H3(H3K4me3)modification in embryos and its effect on embryonic development.METHODS:Mouse fertilized eggs were divided into control and autophagy inhibitor-treated groups(chloroquine phosphate-treated group and 3-methyladenine-treated group),and cultured in vitro to different periods of time,and were then classified as early 2-cell embryos,middle 2-cell embryos,late 2-cell embryos,4-cell embryos,8-cell embryos,morula stage,and blastocyst stage.Levels of reactive oxygen species,autophagy marker proteins LC3B and P62,DNA loss marker γH2AX,and H3K4me3 were analyzed by immunofluorescence assay in late 2-cell embryos of each group.Changes in H3K4me3 modification in late 2-cell embryos of each group were detected by CUT&Tag.RESULTS AND CONCLUSION:(1)Autophagy inhibition caused embryo development arrest.(2)There was no significant difference in reactive oxygen species and γH2AX between the autophagy inhibitor-treated groups and control group.(3)H3K4me3 levels were significantly elevated in the autophagy inhibitor-treated group compared with the control group.(4)CUT&Tag results showed a significantly increased H3K4me3 peaks on the proximal promoter region of the genes after autophagy inhibition and an increase of H3K4me3-specific modification genes.These findings suggest that autophagy may affect embryonic development by regulating the level of H3K4me3 modification.

BACKGROUND:Autophagy,as a key regulatory mechanism of cell development,plays an important role in different stages of embryonic development.The mechanism of how autophagy regulates embryonic development through histone modifications is currently unclear.OBJECTIVE:To investigate the effect of autophagy on trimethylation of lysine 4 on histone H3(H3K4me3)modification in embryos and its effect on embryonic development.METHODS:Mouse fertilized eggs were divided into control and autophagy inhibitor-treated groups(chloroquine phosphate-treated group and 3-methyladenine-treated group),and cultured in vitro to different periods of time,and were then classified as early 2-cell embryos,middle 2-cell embryos,late 2-cell embryos,4-cell embryos,8-cell embryos,morula stage,and blastocyst stage.Levels of reactive oxygen species,autophagy marker proteins LC3B and P62,DNA loss marker γH2AX,and H3K4me3 were analyzed by immunofluorescence assay in late 2-cell embryos of each group.Changes in H3K4me3 modification in late 2-cell embryos of each group were detected by CUT&Tag.RESULTS AND CONCLUSION:(1)Autophagy inhibition caused embryo development arrest.(2)There was no significant difference in reactive oxygen species and γH2AX between the autophagy inhibitor-treated groups and control group.(3)H3K4me3 levels were significantly elevated in the autophagy inhibitor-treated group compared with the control group.(4)CUT&Tag results showed a significantly increased H3K4me3 peaks on the proximal promoter region of the genes after autophagy inhibition and an increase of H3K4me3-specific modification genes.These findings suggest that autophagy may affect embryonic development by regulating the level of H3K4me3 modification.

With the accelerating trend of population aging, the number of elderly patients with lung cancer continues to rise, and the disease burden is becoming increasingly heavy. The clinical management of these patients faces severe challenges due to their decreased physiological reserve, complex comorbidities, and significant individual heterogeneity. Consequently, under traditional diagnosis and treatment models, doctors often struggle to identify the individualized risks of elderly patients in a timely and comprehensive manner, which can easily lead to decision biases such as undertreatment or overtreatment. In view of this, this study advocates for the establishment of an umbrella decision-making model specifically tailored for elderly lung cancer patients. Grounded in a multidisciplinary team (MDT) platform, this model deeply integrates oncological indicators with the comprehensive geriatric assessment (CGA) system. By holistically considering multidimensional variables including tumor burden, organ function, frailty index, cognitive status, and social support, the model establishes an operational mechanism characterized by "single entry, precise stratification, and targeted selection". Accordingly, patients can be scientifically triaged into distinct intervention tiers, such as active surveillance, minimally invasive surgery, drug therapy, radiotherapy, and best supportive care, thereby achieving real-time alignment between treatment intensity and patient fitness. This article elaborates on the construction logic and key operational procedures of this novel decision-making framework, aiming to guide clinical practice beyond the limitations of a tumor-centric perspective toward a holistic, dynamic, whole-course management strategy. This transition seeks to ensure optimal quality of life and clinical net benefit for elderly patients alongside survival prolongation.

This comprehensive review systematically explores the multifaceted applications, inherent challenges, and promising future directions of artificial intelligence (AI) within the medical domain. It meticulously examines AI's specific contributions to basic medical research, disease prevention, intelligent diagnosis, treatment, rehabilitation, nursing, and health management. Furthermore, the review delves into AI's innovative practices and pivotal roles in clinical trials, hospital administration, medical education, as well as the realms of medical ethics and policy formulation. Notably, the review identifies several key challenges confronting AI in healthcare, encompassing issues such as inadequate algorithm transparency, data privacy concerns, absent regulatory standards, and incomplete risk assessment frameworks. Looking ahead, the future trajectory of AI in healthcare encompasses enhancing algorithm interpretability, propelling generative AI applications, establishing robust data-sharing mechanisms, refining regulatory policies and standards, nurturing interdisciplinary talent, fostering collaboration among industry, academia, and medical institutions, and advancing inclusive, personalized precision medicine. Emphasizing the synergy between AI and emerging technologies like 5G, big data, and cloud computing, this review anticipates a new era of intelligent collaboration and inclusive sharing in healthcare. Through a multidimensional analysis, it presents a holistic overview of AI's medical applications and development prospects, catering to researchers, practitioners, and policymakers in the healthcare sector. Ultimately, this review aims to catalyze the deep integration and innovative deployment of AI technology in healthcare, thereby driving the sustainable advancement of smart healthcare.

As the volume of medical research using large language models (LLM) surges, the need for standardized and transparent reporting standards becomes increasingly critical. In January 2025, Nature Medicine published statement titled by TRIPOD-LLM reporting guideline for studies using large language models. This represents the first comprehensive reporting framework specifically tailored for studies that develop prediction models based on LLM. It comprises a checklist with 19 main items (encompassing 50 sub-items), a flowchart, and an abstract checklist (containing 12 items). This article provides an interpretation of TRIPOD-LLM’s development methods, primary content, scope, and the specific details of its items. The goal is to help researchers, clinicians, editors, and healthcare decision-makers to deeply understand and correctly apply TRIPOD-LLM, thereby improving the quality and transparency of LLM medical research reporting and promoting the standardized and ethical integration of LLM into healthcare.

In observational research,a primary objective is to accurately and reliably assess the causal impact of exposure on outcomes.Identifying and properly adjusting for confounding factors is a key prerequisite and central challenge to achieving this goal.Ineffective management of confounders,whether by neglecting significant ones,(leading to residual confounding),or by over-adjusting for irrelevant factors,(introducing collider bias),can distort effect estimates and lead to erroneous scientific conclusions and clinical decisions.Therefore,it is essential to develop and implement systematic,transparent,and reproducible methods for identifying and selecting confounding factors to enhance the validity and reliability of causal inferences in observational studies.This paper provides a systematic review of directed acyclic graphs(DAGs),a robust visual causal modeling tool,and offers a detailed examination of three prominent criteria for selecting confounding factors based on DAGs:the Pre-exposure criterion,the Common cause criterion,and the Modified disjunctive cause criterion.The aim is to equip researchers with a structured and theoretically grounded framework for identifying and selecting confounding factors,thereby improving the process of estimating causal effects in observational studies.

In observational research,a primary objective is to accurately and reliably assess the causal impact of exposure on outcomes.Identifying and properly adjusting for confounding factors is a key prerequisite and central challenge to achieving this goal.Ineffective management of confounders,whether by neglecting significant ones,(leading to residual confounding),or by over-adjusting for irrelevant factors,(introducing collider bias),can distort effect estimates and lead to erroneous scientific conclusions and clinical decisions.Therefore,it is essential to develop and implement systematic,transparent,and reproducible methods for identifying and selecting confounding factors to enhance the validity and reliability of causal inferences in observational studies.This paper provides a systematic review of directed acyclic graphs(DAGs),a robust visual causal modeling tool,and offers a detailed examination of three prominent criteria for selecting confounding factors based on DAGs:the Pre-exposure criterion,the Common cause criterion,and the Modified disjunctive cause criterion.The aim is to equip researchers with a structured and theoretically grounded framework for identifying and selecting confounding factors,thereby improving the process of estimating causal effects in observational studies.

Objective In order to reasonably reduce QY group and improve the accuracy of DRG,we analyzed the data of QY(ambiguity)group in the Diagnosis Related Groups in urology department of a three A and tertiary hospital.Methods Medical insurance settlement statements of urology department of a hospital in the DRG sub-platform of a municipal medical insur-ance bureau were collected from April 1,2022 to November 30,2022,extracting QY cases.The medical records of QY cases were extracted from the digital medical record browser of a hospital.Senior quality control physicians were organized to check medical records,disease classification and medical insurance settlement statements of QY group cases,analyzing the cases.Excel 2010 was used for statistical analysis of the data.Results ① 2 810 copies of medical insurance settlement statements were obtained,of which 43 cases were in the QY groups,accounting for 1.53％.②The cases mainly distributed in urinary system tumors(27.91％),neurogenic bladder(18.60％),prostatic hyperplasia(16.28％),ureteral diseases(11.62％),and ure-thral diseases(11.62％).(3)The total hospitalization cost of patients in QY groups was 731 684.1 yuan,and the average hospi-talization cost was 17 015.91 yuan.The total payment amount of DRG was 419 807.24 yuan,and the average payment amount was 9 762.96 yuan.④The causes of QY groups were as follows:There were 14 cases of DRG grouping rule defect,accounting for 32.56％;There were 29 cases of hospital management defects,accounting for 67.44％.Among the hospital management de-fects,13 cases(30.23％)of the medical insurance settlement statements were defective;There were 8 cases(18.60％)of er-rors in doctors'major diagnoses and major surgical operations.There were 8 cases(18.60％)of coding errors in major diagno-ses and major surgical operations.Conclusion To reasonable reduction QY group,it is necessary to optimize DRG grouping rules and strengthen hospital internal management.Only by paying attention to improve the connotation quality of medical re-cords,accurately classify disease and surgical name,strengthen the management and review of medical insurance settlement state-ments,and establish a long-term mechanism for DRG data quality control,we can further improve the accuracy of DRG and ac-tively promote the reform of medical insurance payment.

Objective:To evaluate the effect of urethral stent tube irrigation in preventing postoperative complications in adolescents with hypospadias.Methods:A retrospective analysis was conducted using the clinical data of adolescents with hypospadias treated at the Department of Urology, Children’s Hospital of Chongqing Medical University, from April 2016 to July 2023. Patients were divided into control group and study group according to whether urethral stent tube was inserted in urethra during operation. All surgeries were performed by the same surgeon. For two days before surgery, patients were instructed to cleanse the surgical site daily with body wash and a 5% povidone-iodine solution. In the control group, patients received postoperative care with an indwelling urinary catheter. In the study group, in addition to the urinary catheter, a urethral stent tube was placed in the posterior urethra, and postoperative urethral irrigation with saline was performed. Postoperative complications, including wound infection, urethral fistula, urethral stricture, and urethral diverticulum, were monitored. Categorical data were expressed as frequencies and percentages and were analyzed using the χ2 test or Monte Carlo-based χ2 test. Continuous data with normal distribution are presented as Mean±SD and were analyzed using the t-test. Non-normally distributed continuous data were expressed as M ( Q1, Q3) and were analyzed using the Wilcoxon rank-sum test. P<0.05 was considered statistically significant. Results:A total of 76 patients were enrolled in the study, with 43 patients in the control group [median age 12.9(12.2, 13.7) years, reconstructed urethral length (3.88±1.86) cm] and 33 patients in the study group [median age 12.5(11.3, 14.1) years, reconstructed urethral length (3.30±1.45)cm]. Postoperatively, 32 patients (74.4%) in the control group experienced complications, including 24 cases (55.8%) of wound infection, 16 cases (37.2%) of urethral fistula, 6 cases (14.0%) of urethral stricture, and 2 cases (4.7%) of diverticulum. In the study group, only 1 patient (3.0%) developed both wound infection and urethral fistula. The incidence of wound infection, urethral fistula, and overall complications was significantly lower in the study group than in the control group (all P<0.01). Conclusion:Postoperative urethral stent irrigation in adolescents with hypospadias significantly reduces the incidence of wound infection and urethral fistula.

BackgroundThe issue of depression among adolescents is becoming increasingly serious， seriously endangering their healthy development. The issue of sleep disturbances in adolescents with depressive disorder is gradually receiving attention， but there is currently a lack of research on the relationship between sleep quality and suicide risk in this patient population. ObjectiveTo explore the relationship between suicide risk and sleep quality in adolescents with depressive disorders， and analyze the influencing factors of suicide risk， so as to provide references for clinical intervention. MethodsA total of 101 adolescents patients who met the diagnostic criteria for depressive disorder in the International Classification of Diseases， 10th edition （ICD-10） and were hospitalized at Hefei Fourth People's Hospital from June 2020 to February 2023 were selected. The patients were evaluated using the Nurses' Global Assessment of Suicide Risk （NGASR） and Pittsburgh Sleep Quality Index （PSQI）. According to the NGASR score， patients were divided into severe suicide risk group （n=35） and non-severe suicide risk group （n=66）. Pearson correlation analysis was used to examine the correlation between sleep quality and suicide risk in adolescents with depression. Multiple Logistic regression was used to analyze the influencing factors of severe suicide risk in adolescent patients with depression. ResultsStatistically significant differences were found between the two groups in terms of academic pressure， peer relationship and family relationship （t=3.942， 4.378， 6.748， P<0.05）. Moreover， there was a statistically significant difference in PSQI score between two groups （t=7.398， P<0.05）. There was also a statistically significant difference in sleep quality between the two groups （χ²=4.986， P<0.05）. Pearson correlation analysis showed a positive correlation between total PSQI score and NGASR score （r=0.698， P<0.05）. Severe depression （OR=1.628， 95% CI： 1.079~2.457）， high academic pressure （OR=1.118， 95% CI： 1.018~1.228） and poor sleep quality （OR=1.158， 95% CI： 1.033~1.297） were identified as risk factors of severe suicide risk， while good relationships with classmates （OR=0.908， 95% CI： 0.826~0.998） and family （OR=0.904， 95% CI： 0.823~0.993） were protective factors. ConclusionSleep quality in adolescents with depression is negatively correlated with suicide risk and poor sleep quality may be a risk factor for severe suicide risk.