Cardiovascular diseases and psychological disorders represent two major threats to human physical and mental health. Research on electrocardiogram (ECG) signals offers valuable opportunities to address these issues. However, existing methods are constrained by limitations in understanding ECG features and transferring knowledge across tasks. To address these challenges, this study developed a multi-resolution feature encoding network based on residual networks, which effectively extracted local morphological features and global rhythm features of ECG signals, thereby enhancing feature representation. Furthermore, a model compression-based continual learning method was proposed, enabling the structured transfer of knowledge from simpler tasks to more complex ones, resulting in improved performance in downstream tasks. The multi-resolution learning model demonstrated superior or comparable performance to state-of-the-art algorithms across five datasets, including tasks such as ECG QRS complex detection, arrhythmia classification, and emotion classification. The continual learning method achieved significant improvements over conventional training approaches in cross-domain, cross-task, and incremental data scenarios. These results highlight the potential of the proposed method for effective cross-task knowledge transfer in ECG analysis and offer a new perspective for multi-task learning using ECG signals.
Humans ; Electrocardiography/methods* ; Mental Health ; Algorithms ; Signal Processing, Computer-Assisted ; Machine Learning ; Arrhythmias, Cardiac/diagnosis* ; Cardiovascular Diseases ; Neural Networks, Computer ; Mental Disorders

OBJECTIVE To study the extraction technology of Sophora flavescens-Phellodendron chinense drug pair and provide a reference for the development of new drugs for the treatment of anorectal diseases. METHODS Using the contents of total alkaloids of S. flavescens （matrine+oxymatrine）， berberine hydrochloride and total flavonoid， and extract yield as evaluation indicators， analytic hierarchy process-entropy weight method was used to calculate the weight coefficient of each indicator， and was combined with Box-Behnken design-response surface method to study the extraction technology of S. flavescens-P. chinense drug pair and verify it. RESULTS The optimal extraction technology of S. flavescens-P. chinense drug pair was immersed in 12-fold amount of 58% ethanol for 30 minutes and extracted twice， each time for 120 minutes. The relative error between the verification experimental results and the predicted value was 1.88%. CONCLUSIONS The obtained extraction technology is stable and feasible and can provide reference for the application of S. flavescens-P. chinense drug pair and development of new drugs.

ObjectiveTo understand the mortality trends among residents of Fuling District， Chongqing， before and after theCOVID-19 outbreak， and to provide references for the government to formulate disease prevention and control policies and measures. MethodsData on mortality and population in Fuling District from 2017 to 2022 were collected to analyze population mortality and standardized mortality rates， and to compare the changes in the causes of death by year and before and after the pandemic. ResultsFrom 2017 to 2022， the crude mortality rate in Fuling District showed an upward trend （APC=3.04%， P<0.05）， while the standardized mortality rate showed a downward trend （APC=-6.47%， P<0.01）. The mortality rate of males was higher than that of females （P<0.05）， with different age groups having different causes of death composition. The highest proportion of deaths in 0-year-old group was from infectious diseases， maternal and neonatal diseases， and nutritional deficiencies， the highest proportion of deaths in the 1‒24 age group， with the exception of those aged 5‒9， was from injuries， and the main cause of death for residents aged 25 and above was chronic diseases. The mortality rate of mental and behavioral disorders rose from the 13th to the 9th place. According to the epidemic situation of COVID-19， there were no changes in the top five causes of death among the entire population. The motility rate of endocrine， nutritional and metabolic diseases rose from the sixth to the fifth place in male population， and the motility rate of malignant tumor rose from the 3rd to the 2nd place in female population. ConclusionThere are no changes in the top five causes of death among the entire population of Fuling District before and after the COVID-19 outbreak. Chronic diseases remain the main cause of death. It is necessary to control the risk factors for cardiovascular and cerebrovascular diseases such as hypertension， diabetes， and dyslipidemia， and to curb the rising trend of mortality rates from strokes and acute myocardial infarction. For deaths caused by accidental injuries， targeted health education should be conducted for different populations.

To promote the development of extracellular vesicles of herbal medicine especially the establishment of standardization, led by the National Expert Committee on Research and Application of Chinese Herbal Vesicles, research experts in the field of herbal medicine and extracellular vesicles were invited nationwide with the support of the Expert Committee on Research and Application of Chinese Herbal Vesicles, Professional Committee on Extracellular Vesicle Research and Application, Chinese Society of Research Hospitals and the Guangdong Engineering Research Center of Chinese Herbal Vesicles. Based on the collation of relevant literature, we have adopted the Delphi method, the consensus meeting method combined with the nominal group method to form a discussion draft of "Consensus statement on research and application of Chinese herbal medicine derived extracellular vesicles-like particles (2023)". The first draft was discussed in online and offline meetings on October 12, 14, November 2, 2022 and April and May 2023 on the current status of research, nomenclature, isolation methods, quality standards and research applications of extracellular vesicles of Chinese herbal medicines, and 13 consensus opinions were finally formed. At the Third Academic Conference on Research and Application of Chinese Herbal Vesicles, held on May 26, 2023, Kewei Zhao, convenor of the consensus, presented and read the consensus to the experts of the Expert Committee on Research and Application of Chinese Herbal Vesicles. The consensus highlights the characteristics and advantages of Chinese medicine, inherits the essence, and keeps the righteousness and innovation, aiming to provide a reference for colleagues engaged in research and application of Chinese herbal vesicles at home and abroad, decode the mystery behind Chinese herbal vesicles together, establish a safe, effective and controllable accurate Chinese herbal vesicle prevention and treatment system, and build a bridge for Chinese medicine to the world.

BACKGROUND:A large number of domestic and international documents have confirmed that elevated interleukin-1β is associated with primary frozen shoulder.Interleukin-1B gene polymorphisms can affect the transcription and protein expression of interleukin 1β-related genes,resulting in altered levels of cytokines in vivo,and thus altering the incidence of primary frozen shoulder.Through the study of interleukin-1B gene polymorphism and susceptibility to primary frozen shoulder,this study aimed to explore new breakthroughs in the pathogenesis of primary frozen shoulder from the perspective of molecular biology,and to search for susceptibility genes of primary frozen shoulder. OBJECTIVE:To explore the association between linkage disequilibrium of three gene loci in interleukin-1B gene and susceptibility to primary frozen shoulder. METHODS:A case-control study was conducted.There were two groups in this study.One group consisted of 184 patients with primary frozen shoulder,while the other group included 260 healthy controls.The genotypes of interleukin-1B gene loci-511C/T(rs16944),+3954C/T(rs1143634),and-31C/T(rs1143627)were detected by polymerase chain reaction and restriction fragment length polymorphism.The correlation between the probability of linkage disequilibrium and haplotypes and the risk of primary frozen shoulder disease was compared and analyzed. RESULTS AND CONCLUSION:Unconditional Logistic regression analysis showed that the proportion of CT genotypes at rs1143634 and rs1143627 sites increased significantly in the primary frozen shoulder.Linkage disequilibrium analysis showed that rs16944,rs1143634 and rs1143627 tended to be balanced in the control group(D'value<0.1),while there was a certain degree of linkage disequilibrium at rs1143627 and rs1143634 sites in the primary frozen shoulder group(D'value=0.595).Haplotype TTT increased the risk of primary frozen shoulder by 6.66 times compared with CCT type(TTT,OR=6.66,95%CI=1.59-27.88,P=0.009 7).To conclude,there is a certain degree of linkage disequilibrium between interleukin-1B gene loci rs1143627and rs1143634 in patients with primary frozen shoulder;haplotype TTT formed by these three gene loci may increase the risk of developing primary frozen shoulder.

Objective:To investigate the pollution levels and influencing factors of polybrominated diphenyl ethers (PBDEs) in household dust in five cities in northern China.Methods:Based on the "Chinese Indoor Environment and Health Surveillance" project carried out by the National Institute of Environmental Health, Chinese Center for Disease Control and Prevention in 2018-2019, during the warm season (April 2018 to September 2018) and the cold season (November 2018 to March 2019), Lanzhou in Northwest China, Shijiazhuang in North China, Panjin in Northeast China, Luoyang in Central China, and Qingdao in East China were selected as the research sites. A total of 87 families were recruited to study residences in real-life scenarios. At the same time, dust samples were collected to detect the concentration of PBDEs. The level of household environmental indicators was measured, and the residential building characteristics and family behavior habits were collected through questionnaires. A total of 142 valid dust samples and 140 valid questionnaires were obtained. The differences in PBDE concentrations across seasons, wind zones, residential building characteristics, and family habits were analyzed. The exploratory factor analysis was performed to investigate the possible sources of PBDEs, and multivariate linear regression was used to explore the factors influencing PBDEs in household dust.Results:The M ( Q1,Q3) of total PBDE concentrations in 142 household dust samples in five cities was 144.51 (106.61, 222.65) ng/g in the warm season and 145.10 (98.57, 180.65) ng/g in the cold season, respectively. There were seasonal differences in the concentration of ∑ 12PBDEs in Luoyang and Shijiazhuang ( P<0.01). The concentration of BDE-71 was highest among PBDE homologues, followed by BDE-66 and BDE-47. Three factors were extracted by exploratory factor analysis in the warm season, and the cumulative variance contribution rate was 67.90%. The multivariate linear regression showed that the house completion less than ten years [ β (95% CI): 0.186 (0.013, 0.359)], infrequent home cooking [ β (95% CI):-0.342 (-0.570, -0.114)], and increased residential PM 10 concentration [ β (95% CI): 0.001 (0.000, 0.002)] during the warm season, as well as the house far from driveway [ β (95% CI): 0.093 (0.013, 0.172)], house area less than 90 m 2 [ β (95% CI):-0.138 (-0.264, -0.013)], and lower residential xylene concentration [ β (95% CI):-0.006 (-0.011, -0.001)] during the cold season might be related to the elevated concentrations of ∑ 12PBDEs in household dust. Conclusion:The pollution of PBDEs in household dust in five northern cities is at a medium to high level. Years of house completion, frequency of cooking at home, residential PM 10 concentration, distance from house to driveway, house area, and residential xylene concentration may influence household PBDE concentrations.

Objective:To investigate the pollution levels and influencing factors of polybrominated diphenyl ethers (PBDEs) in household dust in five cities in northern China.Methods:Based on the "Chinese Indoor Environment and Health Surveillance" project carried out by the National Institute of Environmental Health, Chinese Center for Disease Control and Prevention in 2018-2019, during the warm season (April 2018 to September 2018) and the cold season (November 2018 to March 2019), Lanzhou in Northwest China, Shijiazhuang in North China, Panjin in Northeast China, Luoyang in Central China, and Qingdao in East China were selected as the research sites. A total of 87 families were recruited to study residences in real-life scenarios. At the same time, dust samples were collected to detect the concentration of PBDEs. The level of household environmental indicators was measured, and the residential building characteristics and family behavior habits were collected through questionnaires. A total of 142 valid dust samples and 140 valid questionnaires were obtained. The differences in PBDE concentrations across seasons, wind zones, residential building characteristics, and family habits were analyzed. The exploratory factor analysis was performed to investigate the possible sources of PBDEs, and multivariate linear regression was used to explore the factors influencing PBDEs in household dust.Results:The M ( Q1,Q3) of total PBDE concentrations in 142 household dust samples in five cities was 144.51 (106.61, 222.65) ng/g in the warm season and 145.10 (98.57, 180.65) ng/g in the cold season, respectively. There were seasonal differences in the concentration of ∑ 12PBDEs in Luoyang and Shijiazhuang ( P<0.01). The concentration of BDE-71 was highest among PBDE homologues, followed by BDE-66 and BDE-47. Three factors were extracted by exploratory factor analysis in the warm season, and the cumulative variance contribution rate was 67.90%. The multivariate linear regression showed that the house completion less than ten years [ β (95% CI): 0.186 (0.013, 0.359)], infrequent home cooking [ β (95% CI):-0.342 (-0.570, -0.114)], and increased residential PM 10 concentration [ β (95% CI): 0.001 (0.000, 0.002)] during the warm season, as well as the house far from driveway [ β (95% CI): 0.093 (0.013, 0.172)], house area less than 90 m 2 [ β (95% CI):-0.138 (-0.264, -0.013)], and lower residential xylene concentration [ β (95% CI):-0.006 (-0.011, -0.001)] during the cold season might be related to the elevated concentrations of ∑ 12PBDEs in household dust. Conclusion:The pollution of PBDEs in household dust in five northern cities is at a medium to high level. Years of house completion, frequency of cooking at home, residential PM 10 concentration, distance from house to driveway, house area, and residential xylene concentration may influence household PBDE concentrations.

Objective:To evaluate the clinical application effects of a domestic bone-level implant system for restoring single tooth loss, and provide clinical evidence for the promotion and application of domestic implants.Methods:A prospective, multicenter clinical trial was conducted from April 2018 to January 2020 in three institutions: Department of Oral Implantology, School & Hospital of Stomatology, Wuhan University, Department of Stomatology, The First Affiliated Hospital of Zhejiang University School of Medicine, and Department of Stomatology, The Third Hospital of Hebei Medical University. The trial planned to include 100 patients for single tooth implantation and restoration, followed up for 1 year, to evaluate the implantation success rate and other related outcomes.Results:This study screened a total of 142 patients and ultimately included 100, comprising 43 males and 57 females with age of (47.0±12.2) years. Ninety-eight out of 100 patients completed a one-year follow-up (98.0%), while 2 patients terminated the trial early due to implant loosening (2.0%). After a one-year follow-up, the implants of the 98 patients were all functioning successfully, with a success rate of 98.0% (98/100). The patients were satisfied with the overall restoration effect.Conclusions:This study indicates that the domestic bone-level implant system has achieved favorable short-term clinical outcomes for single-tooth implantation and restoration.

Objective To evaluate the apparent diffusion coefficient(ADC)values of different bone marrow infiltration patterns in multiple myeloma(MM)patients with MR whole-body diffusion weighted imaging(WB-DWI)and to determine the ADC thresholds for different bone marrow infiltration patterns.Methods Nineteen MM patients diagnosed for the first time were selected.The lesions types of each site(cervical spine,ribs,sternum,humerus,scapula,sacral spine,ilium,femur,thoracic spine,and lumbar spine)after the WB-DWI images were visually evaluated,which were divided into focal group(including focal lesion in combined focal and diffuse infiltration)[region of interest(ROI)=141],pure diffuse infiltration group(ROI=150),diffuse lesion in combined focal and diffuse infiltration group(ROI=127),"salt-and-pepper"group(ROI=54),and normal appearance group(ROI=68).ADC values were measured and compared between each group and the receiver operating characteristic(ROC)curve was drawn to distinguish different patterns of bone marrow infiltration.Results There was no statistically significant difference in ADC values between the diffuse lesion in combined focal and diffuse infiltration group and the"salt-and-pepper"group(P＞0.99),and there was statistically significant difference in ADC values between the other groups(P＜0.05).The ROC curve showed that the area under the curve(AUC)for identifying focal group and the"salt-and-pepper"group was 0.889[95％confidence interval(CI)0.844-0.934],the AUC for identifying pure diffuse infiltration group and the normal appearance group was 0.968(95％CI 0.949-0.987).ADC values were able to accurately and visually differentiate between the different patterns of bone marrow infiltration.Conclusion The ADC values can be used as a quantitative tool to objectively distinguish different bone marrow infiltration patterns in MM patients.

Artificial intelligence has gradually become an important tool in the field of clinical nutrition. Artificial intelligence can not only simplify the current dietary assessment methods, but also develop nutritional assessment models with favorable accuracy through machine learning. Digital technologies and devices such as mobile applications and wearable devices have expanded the accessibility of dietary nutritional assessment. Mobile applications can be used for convenient and quick dietary nutritional assessment based on food images and videos, with real-time output of the types and amount of nutrients. Wearable devices can provide real-time feedback of individual dynamic nutrient intake and absorption by monitoring the fluctuation of the levels of biomarkers in body fluids. Nutritional assessment based on machine learning can improve the accuracy of malnutrition diagnosis, predict adverse events such as enteral nutrition intolerance, and guide nutritional intervention and prognosis prediction.