Objective To discuss the factors influencing the occurrence of frailty in patients with acute myocardial infarction(AMI)after receiving interventional treatment,and to construct a prediction model,to draw a nomogram,and to make the validation of the model.Methods Using convenient sampling method,a total of 462 patients with AMI,who were admitted to the Department of Cardiovascular Medicine of three Grade Ⅲ-A hospitals in Shandong Province of China from July 2023 to January 2024,were selected as the study subjects.Among them,324 AMI patients encountered from July 2023 to November 2023 were selected as modeling group,and logistic regression was used to construct a risk prediction model and draw a nomogram to visualize the model.The remaining 138 AMI patients encountered from December 2023 to January 2024 were used as the validation group.The receiver operating characteristic(ROC)curve and Hosmer-Lemeshow testing were adopted to verify the predictive effect of the model.Results Of 324 patients in the modeling group,170(52.47％)developed frailty.Univariate analysis showed that significant differences in age,education level,body mass index(BMI),Charlson comorbidity index,grip strength,walking speed,brain natriuretic peptide precursor level,physical exercise,multiple medication,and kinesophobia existed between the two groups(all P＜0.05).Multivariate logistic regression analysis revealed that age,BMI,Charlson comorbidity index,grip strength,walking speed,NT-ProBNP precursor level,physical exercise,multiple medication,and kinesophobia were the influencing factors of frailty in patients with AMI after receiving interventional treatment,with an OR value of 1.061,0.630,1.529,0.931,0.005,0.358,1.783,2.929,and 0.497 respectively.The above nine factors were used as independent variables to draw the nomogram,the area under ROC curve of the model was 0.851(95％CI:0.809-0.892),the optimal critical value was 0.562,the sensitivity was 84.1％,and the specificity was 72.1％.Hosmer-Lemeshow goodness of fit testing showed that the model had anx2=12.957 and P=0.113.Conclusion The frailty condition of AMI patients after receiving interventional treatment is at a low to medium levels.The frailty risk prediction model constructed in this study has good prediction effect,which can provide guidance for clinical nurses to timely identify high-risk patients and to promptly adopt interventional measures.

Objective: The aging demographic landscape worldwide portends a heightened prevalence of neurodegenerative disorders. Foremost among these is Alzheimer’s disease (AD), the foremost cause of dementia in older adults. The shortage of efficacious therapies and early diagnostic indicators underscores the imperative to identify non-invasive biomarkers for early detection and disease monitoring. Recently, blood metabolites have emerged as promising candidates for AD biomarkers. Methods: Leveraging nuclear magnetic resonance (NMR) spectroscopy on plasma specimens, we conducted a cross-sectional study encompassing 35 AD patients and 35 age-matched healthy controls. Cognitive function was evaluated using the mini-mental state examination in all participants, followed by peripheral blood sample collection. We utilized univariate and multivariate analyses to perform targeted lipidomic profiling via NMR spectroscopy. Results: Our study revealed significant differences in the expression profiles of low-density lipoprotein-associated subfractions in females and high-density lipoprotein-associated subfractions in males between AD patients and healthy controls (all p<0.05). However, there was no significant metabolite overlap between males and females. Furthermore, receiver operating characteristic curve analysis demonstrated that the combination of lipid metabolites had good diagnostic values (all area under the curve>0.70; p<0.05). Conclusion Our findings suggest that the blood plasma samples using NMR hold promise in distinguishing between AD patients and healthy controls, with significant clinical implications for advancing AD diagnostic methodologies.

Objective: The aging demographic landscape worldwide portends a heightened prevalence of neurodegenerative disorders. Foremost among these is Alzheimer’s disease (AD), the foremost cause of dementia in older adults. The shortage of efficacious therapies and early diagnostic indicators underscores the imperative to identify non-invasive biomarkers for early detection and disease monitoring. Recently, blood metabolites have emerged as promising candidates for AD biomarkers. Methods: Leveraging nuclear magnetic resonance (NMR) spectroscopy on plasma specimens, we conducted a cross-sectional study encompassing 35 AD patients and 35 age-matched healthy controls. Cognitive function was evaluated using the mini-mental state examination in all participants, followed by peripheral blood sample collection. We utilized univariate and multivariate analyses to perform targeted lipidomic profiling via NMR spectroscopy. Results: Our study revealed significant differences in the expression profiles of low-density lipoprotein-associated subfractions in females and high-density lipoprotein-associated subfractions in males between AD patients and healthy controls (all p<0.05). However, there was no significant metabolite overlap between males and females. Furthermore, receiver operating characteristic curve analysis demonstrated that the combination of lipid metabolites had good diagnostic values (all area under the curve>0.70; p<0.05). Conclusion Our findings suggest that the blood plasma samples using NMR hold promise in distinguishing between AD patients and healthy controls, with significant clinical implications for advancing AD diagnostic methodologies.

Objective: The aging demographic landscape worldwide portends a heightened prevalence of neurodegenerative disorders. Foremost among these is Alzheimer’s disease (AD), the foremost cause of dementia in older adults. The shortage of efficacious therapies and early diagnostic indicators underscores the imperative to identify non-invasive biomarkers for early detection and disease monitoring. Recently, blood metabolites have emerged as promising candidates for AD biomarkers. Methods: Leveraging nuclear magnetic resonance (NMR) spectroscopy on plasma specimens, we conducted a cross-sectional study encompassing 35 AD patients and 35 age-matched healthy controls. Cognitive function was evaluated using the mini-mental state examination in all participants, followed by peripheral blood sample collection. We utilized univariate and multivariate analyses to perform targeted lipidomic profiling via NMR spectroscopy. Results: Our study revealed significant differences in the expression profiles of low-density lipoprotein-associated subfractions in females and high-density lipoprotein-associated subfractions in males between AD patients and healthy controls (all p<0.05). However, there was no significant metabolite overlap between males and females. Furthermore, receiver operating characteristic curve analysis demonstrated that the combination of lipid metabolites had good diagnostic values (all area under the curve>0.70; p<0.05). Conclusion Our findings suggest that the blood plasma samples using NMR hold promise in distinguishing between AD patients and healthy controls, with significant clinical implications for advancing AD diagnostic methodologies.

Objective To develop a highly sensitive and rapid nucleic acid detection method for the severe acute respiratory syndrome coronavirus 2(SARS-CoV-2). Methods We designed,developed,and manufactured an integrated disposable device for SARS-CoV-2 nucleic acid extraction and detection.The precision of the liquid transfer and temperature control was tested.A comparison between our device and a commercial kit for SARS-Cov-2 nucleic acid extraction was performed using real-time fluorescence reverse transcription polymerase chain reaction(RT-PCR).The entire process,from SARS-CoV-2 nucleic acid extraction to amplification,was evaluated. Results The precision of the syringe transfer volume was 19.2±1.9 μL(set value was 20),32.2±1.6(set value was 30),and 57.2±3.5(set value was 60).Temperature control in the amplification tube was measured at 60.0±0.0 ℃(set value was 60)and 95.1±0.2 ℃(set value was 95)respectively.SARS-Cov-2 nucleic acid extraction yield through the device was 7.10×106 copies/mL,while a commercial kit yielded 2.98×106 copies/mL.The mean time to complete the entire assay,from SARS-CoV-2 nucleic acid extraction to amplification detection,was 36 min and 45 s.The detection limit for SARS-CoV-2 nucleic acid was 250 copies/mL. Conclusion The integrated disposable devices may be used for SARS-CoV-2 Point-of-Care test(POCT).

Influenza imposes a significant disease burden on society and individuals annually, and influenza vaccination is considered a significant public health measure to prevent influenza and reduce influenza-related severe disease and death. The low influenza vaccination rate in China is partly due to certain factors affecting the willingness and behavior of individuals to receive them. Scientific research and targeted interventions on these factors can effectively improve the vaccination situation. Commonly used individual-level theoretical models for influenza vaccination behavior include the health belief model, protection motivation theory, and theory of planned behavior. This study reviews theoretical models commonly employed in researching influenza vaccination willingness and behavior. An overview of these practical applications and challenges models is presented to provide references for relevant research and intervention programs in China.

Objective:This study aimed to develop a rapid and accurate integrated nucleic acid detection method tailored for the influenza virus.Methods:We designed primers and probes targeting the predominant influenza virus strains circulating in China in recent years. These were integrated with extraction and amplification reagents and a point of care testing (POCT) system to facilitate a seamless and expedited process involving nucleic acid extraction, reaction system preparation, amplification, and result interpretation for the influenza virus. The specificity of the POCT system was evaluated using cultured influenza viruses, while its cross-reactivity was assessed against common respiratory pathogens, including adenovirus and respiratory syncytial virus.Results:Our study successfully developed duplex amplification primers and probes for both influenza A and B viruses, achieving a detection threshold as low as 500 copies/ml. Specificity tests confirmed that the detection reagents did not show cross-reactivity with other respiratory pathogens such as adenovirus and respiratory syncytial virus. The POCT-based rapid nucleic acid detection method for influenza virus was established, it is capable of completing the entire process from nucleic acid extraction to amplification and result interpretation within 50 minutes, while enabling real-time data upload.Conclusions:The POCT-based rapid influenza virus detection kit developed in this study offers a " sample in, results out" convenience, making it suitable for rapid influenza virus detection in primary care settings. This innovation has significant potential for clinical application.

Taking chronic atrophic gastritis （CAG） as an example， the frontier technologies in data science have been introduced into the inheritance， innovation and development of traditional Chinese medicine （TCM）， providing reference for conducting real-world clinical research on specialized diseases of TCM. This paper put forward the construction of CAG data science system by elaborating the connotation of data science and its application value in TCM， and discussed the path to build CAG data science system， namely through "data acquisition-knowledge expression-knowledge reasoning" to establish CAG database， knowledge base and develop diagnosis platform differentiating diseases and syndromes. Besides， this paper analyzed the prospects of CAG data science in improving data governance ability and knowledge discovery efficiency， deepening the level of knowledge sharing， promoting interdisciplinary integration， and strengthening the integration process of industry， academia and research.

Objective: The aging demographic landscape worldwide portends a heightened prevalence of neurodegenerative disorders. Foremost among these is Alzheimer’s disease (AD), the foremost cause of dementia in older adults. The shortage of efficacious therapies and early diagnostic indicators underscores the imperative to identify non-invasive biomarkers for early detection and disease monitoring. Recently, blood metabolites have emerged as promising candidates for AD biomarkers. Methods: Leveraging nuclear magnetic resonance (NMR) spectroscopy on plasma specimens, we conducted a cross-sectional study encompassing 35 AD patients and 35 age-matched healthy controls. Cognitive function was evaluated using the mini-mental state examination in all participants, followed by peripheral blood sample collection. We utilized univariate and multivariate analyses to perform targeted lipidomic profiling via NMR spectroscopy. Results: Our study revealed significant differences in the expression profiles of low-density lipoprotein-associated subfractions in females and high-density lipoprotein-associated subfractions in males between AD patients and healthy controls (all p<0.05). However, there was no significant metabolite overlap between males and females. Furthermore, receiver operating characteristic curve analysis demonstrated that the combination of lipid metabolites had good diagnostic values (all area under the curve>0.70; p<0.05). Conclusion Our findings suggest that the blood plasma samples using NMR hold promise in distinguishing between AD patients and healthy controls, with significant clinical implications for advancing AD diagnostic methodologies.

Objective: The aging demographic landscape worldwide portends a heightened prevalence of neurodegenerative disorders. Foremost among these is Alzheimer’s disease (AD), the foremost cause of dementia in older adults. The shortage of efficacious therapies and early diagnostic indicators underscores the imperative to identify non-invasive biomarkers for early detection and disease monitoring. Recently, blood metabolites have emerged as promising candidates for AD biomarkers. Methods: Leveraging nuclear magnetic resonance (NMR) spectroscopy on plasma specimens, we conducted a cross-sectional study encompassing 35 AD patients and 35 age-matched healthy controls. Cognitive function was evaluated using the mini-mental state examination in all participants, followed by peripheral blood sample collection. We utilized univariate and multivariate analyses to perform targeted lipidomic profiling via NMR spectroscopy. Results: Our study revealed significant differences in the expression profiles of low-density lipoprotein-associated subfractions in females and high-density lipoprotein-associated subfractions in males between AD patients and healthy controls (all p<0.05). However, there was no significant metabolite overlap between males and females. Furthermore, receiver operating characteristic curve analysis demonstrated that the combination of lipid metabolites had good diagnostic values (all area under the curve>0.70; p<0.05). Conclusion Our findings suggest that the blood plasma samples using NMR hold promise in distinguishing between AD patients and healthy controls, with significant clinical implications for advancing AD diagnostic methodologies.