Objective To use a physics-informed neural network(PINN)-based model to predict hemodynamics in intracranial aneurysms and address the problems of long simulation time and high computational cost in traditional computational fluid dynamics(CFD)simulations.Methods The PINN model was trained using only the computational domain coordinates and sparse velocity measurement points from CFD data of clinical patients.The predicted blood flow velocity,pressure,and wall shear stress(WSS)from the PINN model were compared with CFD simulation results.Results The proposed method was used to test and validate data from four different patients.For velocity prediction,the average mean absolute error(MAE),average mean relative error(MRE),average mean squared error(MSE)was 4.60％,6.61％,and 0.229％,respectively.For WSS prediction,the average MAE,MRE and MSE was 5.54％,8.58％,and 0.510％,respectively.The PINN model demonstrated a good generalization capability across different aneurysm models and could reduce the computation time of hemodynamics from several hours to just a few seconds.Conclusions The PINN model can effectively compensate for incomplete measurement data through physical constraints,even when boundary conditions are unknown and measurement data are sparse.It can rapidly and accurately simulate the hemodynamics of intracranial aneurysms.This method has the potential to provide effective support for clinical risk prediction in intracranial aneurysms.

Meniere's disease represents an idiopathic inner ear disorder characterized by endolymphatic hy-drops.Currently,the research methods for identifying genes associated with this disease mainly involve first-genera-tion sequencing and second-generation sequencing.This article reviews research on the genetic study of Meniere's disease,mainly summarizing the candidate genes with repeated pedigree validation in familial Meniere's disease,as well as those frequently reported in sporadic Meniere's disease.

Objective:To observe the effects of 4E (explore, express, explain, extend) teaching combined with Gibbs reflective cycle method on the thinking and learning ability of nurse interns in the Department of Burns and Plastic Surgery.Methods:A total of 96 nurse interns in the Department of Burns and Plastic Surgery between June 1, 2022 and September 1, 2023 were selected as the research objects. Based on internship period, they were divided into the control group (from June 2022 to January 2023, traditional teaching) and the observation group (from February 2023 to September 2023, 4E teaching combined with Gibbs reflective cycle method). The critical thinking ability and evidence-based medicine ability before and after the internship were compared, and the recognition of the teaching method was compared between the two groups. SPSS 20.0 was used for t test and χ2 test. Results:After the teaching, the critical thinking ability and evidence-based medicine ability of nurse interns in the two groups were significantly higher than those before the teaching. The scores of critical thinking ability and evidence-based medicine ability were significantly higher in the observation group compared to the control group. Compared with the control group, the observation group showed higher levels of recognition in terms of proactiveness (44/48 vs. 30/48), information access ability (45/48 vs. 32/48), emergency response ability (47/48 vs. 29/48), and enhancement of teacher-student relationships (46/48 vs. 30/48), and the differences were statistically significant ( P<0.05). Conclusions:The application of 4E teaching combined with Gibbs reflective cycle method in training nurse interns in the Department of Burns and Plastic Surgery can improve their critical thinking ability and evidence-based medicine ability, and the nurse interns have a high level of recognition for this teaching method.

Meniere's disease represents an idiopathic inner ear disorder characterized by endolymphatic hy-drops.Currently,the research methods for identifying genes associated with this disease mainly involve first-genera-tion sequencing and second-generation sequencing.This article reviews research on the genetic study of Meniere's disease,mainly summarizing the candidate genes with repeated pedigree validation in familial Meniere's disease,as well as those frequently reported in sporadic Meniere's disease.

Objective:To evaluate the effectiveness of the Total Nutritional Therapy (TNT) course initiated by the Chinese Society for Parenteral and Enteral Nutrition (CSPEN) over the 20 years since its implementation in China.Methods:Participants who attended the CSPEN-organized TNT course between 2005 and 2024 were randomly selected as survey subjects. A four-level questionnaire (reaction, learning, behavior, and results) was developed via expert consensus, based on the Kirkpatrick model. An electronic link to the survey, created via Wenjuanxing, was distributed to invite participants to complete the questionnaire.Results:A total of 1,548 healthcare professionals from various specialties who had received TNT course participated in the online survey. Over 93% of participants reported improvements in theoretical knowledge and 94% in enhanced clinical diagnosis and treatment capabilities. Additionally, 65.4% of participants reported a "significant" or "noticeable" increase in the frequency of nutritional screening and assessments, with the frequency of nutritional support therapy utilization increased by 91.2%. Furthermore, 52.6% of respondents perceived a "significant" or "noticeable" career advancement, particularly in professional title promotion and international academic exchanges. The TNT course also positively impacted discipline development and management: 63.6% of the trainees' hospitals established clinical nutrition departments, 58.98% opened nutrition outpatient clinics, and 56.9% formed nutrition support teams. The adoption rate of standardized procedures, such as nutritional screening, exceeded 92.5% in relevant departments.Conclusions:Over the past 20 years, the CSPEN-led TNT course has successfully established a virtuous cycle of "knowledge dissemination–practice transformation–system innovation" in China. It has played a positive role in enhancing the professional competencies of healthcare workers and promoting the development of clinical nutrition as a discipline.

Gut microorganisms are central to the intestinal microecosystem, regulating digestive functions and related to immune regulation, metabolic disorders, and nervous system development. Recent studies reveal the multifaceted interactions between micronutrients (MNs) and gut microbiota, where MNs provide essential nutrients to the intestinal flora and influence the production and absorption of various MNs through direct or indirect pathways. This article reviews the recent advances in the effects of water-soluble vitamins, fat-soluble vitamins, and micronutrients on the intestinal microecology, aiming to provide new ideas for future research.

Objective To explore the research status and hotspots of umbilical acupuncture over the past 20 years using bibliometric methods,thus to providing references for the subsequent clinical treatment of umbilical acupuncture and studies of the therapeutic mechanism.Methods Literature on umbilical acupuncture published between 2004 and 2024 was retrieved from the CNKI,Wanfang Data Knowledge Service Platform,and VIP Chinese Journal Service Platform.Duplicate check was conducted using NoteExpress 3.9.0 software,and then manual screening was performed.The included literature data were imported into VOSviewer for visualized analysis,including institutional collaboration,author collaboration,and keyword co-occurrence.Results A total of 388 articles were included,comprising 286 original research articles,23 reviews,and 79 dissertations.Annual publication analysis revealed a significant upward trend in umbilical acupuncture research output starting from 2017.Zhejiang Chinese Medical University and Hangzhou Hospital of Traditional Chinese Medicine ranked first in publication volume,and Bao Yehua was the most prolific author.Inter-institutional collaboration remained limited,and author collaborations usually occurred in small-team models.Clinical research was the most commonly-seen keyword,and insomnia and stroke were the diseases being frequently studied.Conclusion Clinical research has become the focus of umbilical acupuncture studies over the past two decades,while mechanism research is still in its early stages.Current research hotspots include the research about insomnia and stroke.

Objective To find the molecular mechanism underlying the effect of congenital cataract related 129th single-site mutation G129C on the thermal stability of human γC crystallin(HγC)protein structure.Methods HγC-WT and HγC-G129C were expressed and purified in vitro.The changes of intrinsic fluorescence intensity and static light scattering intensity of proteins with temperature were measured,and the temperature dependence of the folding and aggregation structures of HγC-WT and HγC-G129C was compared.Results When temperature was be-low 65 ℃,the barycentric mean of the intrinsic fluorescence of HγC-WT and HγC-G129C shifted towards a longer wavelength and the fluorescence intensity decreased with the increasing temperature,which was believed to be the evidence of unfolded protein conformation.When the temperature was higher than 65 ℃,the static light scattering intensity increased significantly with the temperature,indicating the protein aggregation upon heating.The wild-type HγC-G129C showed a stronger aggregation potency.During the thermal de-naturation process of HγC-WT and HγC-G 129C,the crossing-point temperatures were 74.5 ℃ and 55.5 ℃,respectively.HγC-WT showed higher thermal stability.Conclusions The congenital cataract-associated G129C mutation significantly weakens conforma-tional stability of γC-crystallin.

Objective:To develop and validate a clinical prediction model for assessing the risk of postoperative pulmonary complications (PPCs) in elderly patients undergoing surgery with general anesthesia.Methods:This prospective observational study enrolled patients aged ≥65 years who underwent general anesthesia with mechanical ventilation duration >3 hours across six tertiary hospitals between December 2022 and August 2023. Based on follow-up outcomes (until discharge or postoperative day 7), patients were categorized into a non-PPCs group and a PPCs group. Detailed records included baseline patient characteristics, preoperative comorbidities, surgical information (type, duration), and bedside lung ultrasound scores (LUS) assessed within 24 hours postoperatively using a standardized 12-zone protocol. Predictor selection was performed using LASSO regression. Significant predictors identified were incorporated into a multivariate logistic regression analysis to build the prediction model, visualized as a nomogram. Internal validation was conducted via bootstrap resampling (1 000 repetitions). Model performance was evaluated using the area under the receiver operating characteristic curve (AUC) for discrimination, calibration curves for calibration accuracy, and decision curve analysis (DCA) for clinical utility.Results:A total of 130 eligible elderly surgical patients were included. PPCs occurred in 17 patients (incidence rate: 13.1%). Multivariate analysis identified LUS ( OR=1.248, 95% CI: 1.099-1.417, P=0.001) and elective surgery type ( OR=0.206, 95% CI: 0.043-0.988, P=0.048) as independent predictors of PPCs. The nomogram model demonstrated an AUC of 0.867 (95% CI: 0.775-0.959) upon initial testing. Internal validation confirmed good discrimination (AUC=0.863, 95% CI: 0.778-0.972). Calibration curves indicated excellent agreement between predicted probabilities and observed outcomes. Decision curve analysis demonstrated significant clinical net benefit across a wide range of threshold probabilities (0.03-0.89). Conclusions:The clinical prediction model, developed using early postoperative LUS scores and surgical type, effectively predicts the risk of postoperative pulmonary complications in elderly patients following surgery under general anesthesia. The model exhibits strong discrimination, calibration, and clinical utility, providing clinicians with a reliable tool for individualized risk assessment to support clinical decision-making and potentially reduce PPC incidence.

Objective:To investigate the correlation between occupational ionizing radiation exposure and abnormal metabolic indicators, providing a basis for assessing the health risks of occupational ionizing radiation workers and establishing a risk prediction model for chronic metabolic diseases.Methods:In January 2023, 7708 individuals were randomly selected from the occupational health examination data in Zhejiang Province. After excluding 16 individuals due to record errors, 2698 on-the-job workers exposed to ionizing radiation from 2020 to 2021 were selected as the exposure group, 2027 pre-employment workers exposed to ionizing radiation from 2016 to 2022 were selected as the pre-employment control group, and 2967 non-ionizing radiation workers from 2016 to 2022 were selected as the control group. Demographic data, blood routine, urine routine, biochemical indicators, and peripheral blood lymphocyte micronucleus rate of each group were collected. One-way ANOVA and rank sum test were used for comparison of indicators. The exposure group was divided into different groups based on age, exposure duration, and body mass index (BMI), and the correlation between indicators and occupational ionizing radiation was analyzed. Lasso variable selection was conducted by constructing a penalty coefficient (λ), and a complete regression model was established.Results:There were statistically significant differences in indicators such as blood pressure, heart rate, and average hemoglobin concentration between the exposure group and the control group, as well as the pre-employment control group ( P<0.05). Through Lasso variable selection, 19 indicators including exposure length, systolic blood pressure (SBP), diastolic blood pressure (DBP), body weight, body mass index (BMI), urine pH value, red blood cell count, microscopic white blood cells, casts, absolute value of monocytes, mean corpuscular volume of red blood cells, mean hemoglobin concentration, alkaline phosphatase, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, and low-density lipoprotein cholesterol (LDL-C). There were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers of different ages in the exposure group ( P<0.05) ; there were statistically significant differences in SBP, DBP, body weight, BMI, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, and mean corpuscular volume of red blood cells among workers with different exposure durations ( P<0.05) ; there were statistically significant differences in exposure length, SBP, DBP, body weight, BMI, red blood cells, microscopic white blood cells, casts, albumin-to-globulin ratio, total bile acid, α-L-fucosidase, urea, creatinine, LDL-C, absolute value of monocytes, mean corpuscular volume of red blood cells, and mean hemoglobin concentration among workers with different BMIs ( P<0.05) . Conclusion:Occupational ionizing radiation is associated with abnormal metabolic indicators such as blood pressure, heart rate, total bile acid, α-L-fucosidase, urea, and creatinine in the human body. More attention should be paid to the risk of chronic metabolic diseases among workers exposed to ionizing radiation.