Deep learning method can be used to automatically analyze electrocardiogram (ECG) data and rapidly implement arrhythmia classification, which provides significant clinical value for the early screening of arrhythmias. How to select arrhythmia features effectively under limited abnormal sample supervision is an urgent issue to address. This paper proposed an arrhythmia classification algorithm based on an adaptive multi-feature fusion network. The algorithm extracted RR interval features from ECG signals, employed one-dimensional convolutional neural network (1D-CNN) to extract time-domain deep features, employed Mel frequency cepstral coefficients (MFCC) and two-dimensional convolutional neural network (2D-CNN) to extract frequency-domain deep features. The features were fused using adaptive weighting strategy for arrhythmia classification. The paper used the arrhythmia database jointly developed by the Massachusetts Institute of Technology and Beth Israel Hospital (MIT-BIH) and evaluated the algorithm under the inter-patient paradigm. Experimental results demonstrated that the proposed algorithm achieved an average precision of 75.2%, an average recall of 70.1% and an average F ₁-score of 71.3%, demonstrating high classification accuracy and being able to provide algorithmic support for arrhythmia classification in wearable devices.
Humans ; Arrhythmias, Cardiac/diagnosis* ; Algorithms ; Electrocardiography/methods* ; Neural Networks, Computer ; Signal Processing, Computer-Assisted ; Deep Learning ; Classification Algorithms

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.

ObjectiveTo explore the clinical efficacy and safety of Da Chaihutang （DCH） for the treatment of sepsis with Yang syndrome. MethodsA total of 70 patients suffering from sepsis with Yang syndrome were randomly divided into an observation group and a control group， with 35 cases in each group. They both received standard Western medicine treatment. The observation group was additionally given a dose of DCH， which was boiled into 100 mL and taken twice. The control group was additionally given an equal volume and dosage of warm water. The intervention lasted for three days. The 28-day all-cause mortality and the changes in the following indicators before and after intervention were compared between the two groups， including sequential organ failure assessment （SOFA）， acute physiology and chronic health evaluation Ⅱ （APACHE Ⅱ） score，white blood cell （WBC），the percentage of neutrophils （NEU%），C-reactive protein （CRP），procalcitonin （PCT），alanine transaminase （ALT），aspartate transaminase （AST），total bilirubin （TBil），creatinine （Cr），blood urea nitrogen （BUN），acute gastrointestinal injury （AGI） grade，gastrointestinal dysfunction score （GDS），serum intestinal fatty acid-binding protein （iFABP）， citrulline （CR），platelet （PLT），prothrombin time（PT），activated partial thromboplastin time （APTT），fibrinogen （Fib），international normalized ratio （INR），and D-dimer （D-D）. ResultsThere was no significant difference between the two groups regarding 28-day all-cause mortality. After the intervention，SOFA，WBC，PCT，and Cr were significantly decreased， and PLT was significantly increased in the control group （P<0.05）. SOFA，APACHE Ⅱ，NEU%，CRP，PCT，ALT，AST，Cr，BUN，AGI grade，GDS，and serum iFABP and CR were significantly improved in the observation group （P<0.05）. After the intervention，APACHE Ⅱ，PCT，AGI grade，GDS，and serum iFABP in the observation group were significantly lower than those in the control group ，while CR and PLT were higher （P<0.05，P<0.01）. There were significant differences regarding the gap of SOFA，APACHE Ⅱ，AST，TBil，AGI grade，GDS，iFABP，CR， and PLT between the two groups （P<0.05，P<0.01）. There were slight differences regarding PT，APTT，Fib，INR，and D-D between the two groups，which were in the clinical normal range. ConclusionOn the basis of Western medicine， DCH helped to reduce sepsis severity and improved multiple organ dysfunction with high clinical efficacy and safety， but further research on its impact on the prognosis of patients with sepsis is still required.

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.

Objective To construct and validate a risk prediction model for delayed healing of venous leg ulcer(VLU),so as to provide a reference basis for early identification of people at high risk of delayed healing.Methods Using a convenience sampling method,331 VLU patients attending vascular surgery departments in 2 tertiary A hospitals in Sichuan Province from January 2018 to December 2022 were selected as a modeling group and an internal validation group,and 112 patients admitted to another tertiary A hospital were selected as an external validation group.Risk factors for delayed healing in VLU patients were screened using univariate analysis,LASSO regression,and multivariate logistic regression analysis,and a risk prediction model was constructed using R software,and the predictive effects of the models were examined using the area under the receiver operating characteristic curve,the Hosmer-Lemeshow test,decision curve,and the bootstrap resampling for internal validation and spatial external validation were performed,respectively.Results The predictors that ultimately entered the prediction model were diabetes(OR=4.752),deep vein thrombosis(OR=4.104),lipodermatosclerosis(OR=5.405),ulcer recurrence(OR=3.239),and ankle mobility(OR=5.520).The model had good discrimination(AUC:0.819 for internal validation and 0.858 for external validation),calibration(Hosmer-Lemeshow test:χ2=13.517,P=0.095 for internal validation and χ2=3.375,P=0.909 for external validation)and clinical validity.Conclusion The model constructed in this study has good differentiation and calibration,and it can effectively predict people at high risk of delayed healing of VLU,which facilitates targeted clinical interventions to improve ulcer outcomes and reduce the risk of delayed ulcer healing.

Late-life depression (LLD) is a common mental disorder among the elderly, characterized by a high incidence rate, low recognition rates, and a high risk of progression to dementia. LLD patients generally exhibit varying cognitive impairment, particularly in executive function and processing speed. The article provides an in-depth analysis of the potential pathological mechanisms underlying cognitive impairment in LLD, including prefrontal network dysfunction, cerebrovascular damage, and Alzheimer′s disease-related pathological changes. Regarding treatment, antidepressants can improve some cognitive functions but are limited in executive function. Targeted therapies addressing the pathological mechanisms of cognitive impairment in LLD show potential value but require further research. Given the high heterogeneity of LLD, future studies should focus on unraveling its pathological heterogeneity to achieve more precise individualized treatment strategies. This approach aims to improve the quality of life for LLD patients and reduce the risk of progression to dementia.

Late-life depression (LLD) is a common mental disorder among the elderly, characterized by a high incidence rate, low recognition rates, and a high risk of progression to dementia. LLD patients generally exhibit varying cognitive impairment, particularly in executive function and processing speed. The article provides an in-depth analysis of the potential pathological mechanisms underlying cognitive impairment in LLD, including prefrontal network dysfunction, cerebrovascular damage, and Alzheimer′s disease-related pathological changes. Regarding treatment, antidepressants can improve some cognitive functions but are limited in executive function. Targeted therapies addressing the pathological mechanisms of cognitive impairment in LLD show potential value but require further research. Given the high heterogeneity of LLD, future studies should focus on unraveling its pathological heterogeneity to achieve more precise individualized treatment strategies. This approach aims to improve the quality of life for LLD patients and reduce the risk of progression to dementia.

Purpose: Oligometastatic non–small cell lung cancer (NSCLC) patients have been increasingly regarded as a distinct group that could benefit from local treatment to achieve a better clinical outcome. However, current definitions of oligometastasis are solely numerical, which are imprecise because of ignoring the biological heterogeneity caused by genomic characteristics. Our study aimed to profile the molecular alterations of oligometastatic NSCLC and elucidate its potential difference from polymetastasis. Materials and Methods: We performed next-generation sequencing to analyze tumors and paired peripheral blood from 77 oligometastatic and 21 polymetastatic NSCLC patients to reveal their genomic characteristics and assess the genetic heterogeneity. Results: We found ERBB2, ALK, MLL4, PIK3CB, and TOP2A were mutated at a significantly lower frequency in oligometastasis compared with polymetastasis. EGFR and KEAP1 alterations were mutually exclusive in oligometastatic group. More importantly, oligometastasis has a unique significant enrichment of apoptosis signaling pathway. In contrast to polymetastasis, a highly enriched COSMIC signature 4 and a special mutational process, COSMIC signature 14, were observed in the oligometastatic cohort. According to OncoKB database, 74.03% of oligometastatic NSCLC patients harbored at least one actionable alteration. The median tumor mutation burden of oligometastasis was 5.00 mutations/Mb, which was significantly associated with smoking, DNA damage repair genes, TP53 mutation, SMARCA4 mutation, LRP1B mutation, ABL1 mutation. Conclusion Our results shall help redefine oligometastasis beyond simple lesion enumeration that will ultimately improve the selection of patients with real oligometastatic state and optimize personalized cancer therapy for oligometastatic NSCLC.