OBJECTIVE: To explore the relationship between serum chloride levels and prognosis in patients with hepatic coma in the intensive care unit (ICU). METHODS: We analyzed 545 patients with hepatic coma in the ICU from the Medical Information Mart for Intensive Care IV (MIMIC-IV) database. Associations between serum chloride levels and 28-day and 1-year mortality rates were assessed using restricted cubic splines (RCSs), Kaplan-Meier (KM) curves, and Cox regression. Subgroup analyses, external validation, and mechanistic studies were also performed. RESULTS: A total of 545 patients were included in the study. RCS analysis revealed a U-shaped association between serum chloride levels and mortality in patients with hepatic coma. The KM curves indicated lower survival rates among patients with low chloride levels (< 103 mmol/L). Low chloride levels were independently linked to increased 28-day and 1-year all-cause mortality rates. In the multivariate models, the hazard ratio ( HR) for 28-day mortality in the low-chloride group was 1.424 (95% confidence interval [ CI]: 1.041-1.949), while the adjusted hazard ratio for 1-year mortality was 1.313 (95% CI: 1.026-1.679). Subgroup analyses and external validation supported these findings. Cytological experiments suggested that low chloride levels may activate the phosphorylation of the NF-κB signaling pathway, promote the expression of pro-inflammatory cytokines, and reduce neuronal cell viability. CONCLUSION Low serum chloride levels are independently associated with increased mortality in patients with hepatic coma.
Humans ; Male ; Female ; Middle Aged ; Intensive Care Units ; Prognosis ; Chlorides/blood* ; Aged ; Coma/blood* ; Adult

Objective To analyze the research status of in situ simulation in the medical field and explore its hotspots and trends. Methods Relevant literature was searched in China National Knowledge Infrastructure and Web of Science core collection from the inception to February 2024.CiteSpace 6.3.R1 was used to analyze the authors,institutions,and keywords and draw visual knowledge maps. Results A total of 25 Chinese articles and 438 English articles were included.Only 14 English articles were from China.In Chinese articles,the authors with the largest number of articles were Dai Hengmao and Liu Shangkun,and the institution with the largest number of articles was Tongji Hospital affiliated to Tongji Medical College of Huazhong University of Science and Technology.There was little cooperation between the authors and institutions.In English articles,the author and institution with the largest number of articles was Auerbach Marc and Yale University,respectively,and the cooperation between authors and institutions was close.Emergency medicine,emergency event handling,and on-the-job training were the keywords with high frequency in Chinese articles.Patient safety,medical education,and cardiac arrest were the keywords with high frequency in English articles.A total of 4 clusters were generated for Chinese keywords and 13 clusters for English keywords. Conclusions The application of in situ simulation in the medical field is still in the initial stage,and the development is not balanced at home and abroad.The number of articles published and the cooperation between authors and institutions in China obviously lags behind those abroad.Treatment and care of emergency critical patients,emergency event handling and skill training,identification of latent safety threats,improvement of readiness,and promotion of medical quality improvement are the future research hotspots and research trends in this field.
Bibliometrics ; Humans ; China ; Simulation Training ; Education, Medical ; Emergency Medicine/education*

The scientific research and innovation capabilities of medical students are intrinsically linked to the sustained and high-quality development of national healthcare initiatives.Cultivating outstanding medi-cal students with independent scientific capabilities and innovative consciousness is a critical component in the education and training of high-level medical professionals.Our investigation revealed that within the imperfections of the cultivating model,some faculty and students at medical schools have an insufficient understanding of scientific research and innovation and lack motivation for engaging in such activities,which hinder the progression of scientific research activities.Consequently,we initiated a teaching practice and exploratory study on the"tutorial system"aimed at fostering medical students'scientific research and innovation abilities.Based on the principle of"research informing teaching,teaching and research advan-cing together,"this study implements a"tutorial system"coordinated by tutors,supplemented by graduate and undergraduate student mentors,to cultivate innovative thinking,stimulate interest in scientific re-search,and enhance practical and research skills among medical students.Through collaborative efforts within"scientific research innovation teams,"various educational methods—including preliminary re-search,in-class and extracurricular activities,intra-group and inter-group interactions,and theoretical and practical applications—are employed to improve and strengthen the cultivation of medical students'scientif-ic research and innovation abilities.This study aims to provide valuable references for optimizing medical education management systems and enhancing the quality of medical student training.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]

With the continuous deepening of the reform of medical insurance payment methods,diagnosis-related groups(diagnosis-related groups,DRG)and diagnosis-intervention packet(diagnosis-intervention packet,DIP)have gradually become important methods of medical insurance payment.Constructing a disease cost accounting and performance evaluation system that is compatible with it is of crucial significance for optimizing hospital management,rationally allocating medical insurance funds and improving the quality of medical services.By integrating multidisciplinary theories and methods,this paper comprehensively sorts out and analyzes the existing research results,and clarifies the key elements,methods,practical results and challenges in the construction process of the system,aiming to provide a comprehensive reference for subsequent research and practice.

Objective To propose a brain electrical phase prediction method based on long short-term memory network(LSTM)to improve the accuracy and robustness of phase synchronization prediction in transcranial magnetic stimulation(TMS).Methods First,an LSTM consisting of an input layer,an LSTM layer,an ReLU activation layer,a fully connected layer and a regression layer was constructed to capture the EEG signal features through the synergistic action of input gates,forgetting gates and output gates.Second,eye-open resting-state EEG data from 30 healthy subjects were trained using the LSTM to obtain a predictive model for EEG signal and EEG phase prediction.Finally,the LSTM method and the traditional autoregressive(AR)method were compared in terms of the phase prediction errors at the overall and individual levels and the prediction performance for peaks and troughs.A regression model was used to explore the relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error with the LSTM method.Results The LSTM method achieved a total phase prediction error of 0.04°±5.69°,which was lower than that of the traditional AR method(-3.36°±51.13°).For each subject,the LSTM method demonstrated superior phase prediction accuracy compared to the traditional AR method(P＜0.001).The accuracy for predicting peaks(troughs)by the LSTM method(about 89％)was higher than that by the traditional AR method(about 10％).Unlike the traditional AR method,the LSTM method didnot result in linear relationships between instantaneous EEG amplitude,signal-to-noise ratio and phase prediction error,with Pvalues being 0.58 and 0.18,respectively.Conclusion The LSTM-based brain electrical phase prediction method shows high accuracy and robustness when used for EEG phase-synchronized TMS.[Chinese Medical Equipment Journal,2025,46(3):1-8]

The scientific research and innovation capabilities of medical students are intrinsically linked to the sustained and high-quality development of national healthcare initiatives.Cultivating outstanding medi-cal students with independent scientific capabilities and innovative consciousness is a critical component in the education and training of high-level medical professionals.Our investigation revealed that within the imperfections of the cultivating model,some faculty and students at medical schools have an insufficient understanding of scientific research and innovation and lack motivation for engaging in such activities,which hinder the progression of scientific research activities.Consequently,we initiated a teaching practice and exploratory study on the"tutorial system"aimed at fostering medical students'scientific research and innovation abilities.Based on the principle of"research informing teaching,teaching and research advan-cing together,"this study implements a"tutorial system"coordinated by tutors,supplemented by graduate and undergraduate student mentors,to cultivate innovative thinking,stimulate interest in scientific re-search,and enhance practical and research skills among medical students.Through collaborative efforts within"scientific research innovation teams,"various educational methods—including preliminary re-search,in-class and extracurricular activities,intra-group and inter-group interactions,and theoretical and practical applications—are employed to improve and strengthen the cultivation of medical students'scientif-ic research and innovation abilities.This study aims to provide valuable references for optimizing medical education management systems and enhancing the quality of medical student training.

Body weight abnormalities, including overweight, obesity, and underweight, have become a dual public health challenge in Chinese adults: overweight and obesity lead to a variety of chronic complications, while underweight increases the risks of malnutrition, sarcopenia, and organ dysfunction. To systematically address these issues, multidisciplinary experts in endocrinology, sports science, nutrition, and psychiatry from various regions have held multiple weight management seminars. Based on the latest epidemiological data and clinical evidence, they expanded the guideline to include assessment and intervention strategies for underweight, in addition to the core content of obesity management. This guideline outlines the etiological mechanisms, evaluation methods, and multidimensional management strategies for overweight and obesity, covering key areas such as diagnosis and assessment, medical nutrition therapy, exercise prescription, pharmacological intervention, and psychological support. It is intended to provide a scientific and standardized approach to weight management across the adult population, aiming to curb the rising prevalence of obesity, mitigate complications associated with abnormal body weight, and improve nutritional status and overall quality of life.

Metastasis serves as an indicator of malignancy and is a biological characteristic of carcinomas. Epithelial-mesenchymal transition (EMT) plays a key role in the promotion of tumor invasion and metastasis and in the enhancement of tumor cell aggressiveness. Prostaglandin E synthase 3 (p23) is a cochaperone for heat shock protein 90 (HSP90). Our previous study showed that p23 is an HSP90-independent transcription factor in cancer-associated inflammation. The effect and mechanism of action of p23 on lung cancer metastasis are tested in this study. By utilizing cell models in vitro and mouse tail vein metastasis models in vivo, the results provide solid evidence that p23 is critical for promoting lung cancer metastases by regulating downstream CXCL1 expression. Rather than acting independently, p23 forms a complex with RNA-binding motif protein 14 (RBM14) to facilitate EMT progression in lung cancer. Therefore, our study provides evidence for the potential role of the RBM14-p23-CXCL1-EMT axis in the metastasis of lung cancer.

ObjectiveObesity has been identified as one of the most important risk factors for cognitive dysfunction. Physical exercise can ameliorate learning and memory deficits by reversing synaptic plasticity in the hippocampus and cortex in diseases such as Alzheimer’s disease. In this study, we aimed to determine whether 8 weeks of treadmill exercise could alleviate hippocampus-dependent memory impairment in high-fat diet-induced obese mice and investigate the potential mechanisms involved. MethodsA total of sixty 6-week-old male C57BL/6 mice, weighing between 20-30 g, were randomly assigned to 3 distinct groups, each consisting of 20 mice. The groups were designated as follows: control (CON), high-fat diet (HFD), and high-fat diet with exercise (HFD-Ex). Prior to the initiation of the treadmill exercise protocol, the HFD and HFD-Ex groups were fed a high-fat diet (60% fat by kcal) for 20 weeks. The mice in the HFD-Ex group underwent treadmill exercise at a speed of 8 m/min for the first 10 min, followed by 12 m/min for the subsequent 50 min, totally 60 min of exercise at a 0° slope, 5 d per week, for 8 weeks. We employed Y-maze and novel object recognition tests to assess hippocampus-dependent memory and utilized immunofluorescence, Western blot, Golgi staining, and ELISA to analyze axon length, dendritic complexity, number of spines, the expression of c-fos, doublecortin (DCX), postsynaptic density-95 (PSD95), synaptophysin (Syn), interleukin-1β (IL-1β), and the number of major histocompatibility complex II (MHC-II) positive cells. ResultsMice with HFD-induced obesity exhibit hippocampus-dependent memory impairment, and treadmill exercise can prevent memory decline in these mice. The expression of DCX was significantly decreased in the HFD-induced obese mice compared to the control group (P<0.001). Treadmill exercise increased the expression of c-fos (P<0.001) and DCX (P=0.001) in the hippocampus of the HFD-induced obese mice. The axon length (P<0.001), dendritic complexity (P<0.001), the number of spines (P<0.001) and the expression of PSD95 (P<0.001) in the hippocampus were significantly decreased in the HFD-induced obese mice compared to the control group. Treadmill exercise increased the axon length (P=0.002), dendritic complexity(P<0.001), the number of spines (P<0.001) and the expression of PSD95 (P=0.001) of the hippocampus in the HFD-induced obese mice. Our study found a significant increase in MHC-II positive cells (P<0.001) and the concentration of IL-1β (P<0.001) in the hippocampus of HFD-induced obese mice compared to the control group. Treadmill exercise was found to reduce the number of MHC-II positive cells (P<0.001) and the concentration of IL-1β (P<0.001) in the hippocampus of obese mice induced by a HFD. ConclusionTreadmill exercise led to enhanced neurogenesis and neuroplasticity by increasing the axon length, dendritic complexity, dendritic spine numbers, and the expression of PSD95 and DCX, decreasing the number of MHC-II positive cells and neuroinflammation in HFD-induced obese mice. Therefore, we speculate that exercise may serve as a non-pharmacologic method that protects against HFD-induced hippocampus-dependent memory dysfunction by enhancing neuroplasticity and neurogenesis in the hippocampus of obese mice.