The American Heart Association (AHA) and the American College of Cardiology (ACC), in collaboration with multiple professional organizations, jointly released the "Guideline for the Prevention, Detection, Evaluation and Management of High Blood Pressure in Adults" in August 2025. Based on the latest evidence-based medical findings from February 2015 to January 2025, the guideline proposes an individualized treatment strategy grounded in total cardiovascular disease risk stratification, incorporates the novel PREVENT risk assessment model, lowers the medication initiation threshold and control targets for high-risk populations, and provides specific management recommendations for special populations. This article provides an interpretation of these updates and conducts a comparative analysis with the current status of hypertension prevention and treatment in China as well as Chinese guidelines, aiming to offer reference for hypertension control practices in China.

The American Heart Association (AHA) officially released the "2025 Heart Disease and Stroke Statistics: A Report of US and Global Data From the American Heart Association" on January 27, 2025. This report systematically compiles the latest statistics on major cardiovascular diseases worldwide, while simultaneously integrating relevant outcome indicators, including quality of care, procedures, and economic costs, and updating the global prevalence patterns and evolving trends of diverse risk factors impacting cardiovascular health, providing essential guidance for the prevention, diagnosis, and treatment of cardiovascular diseases. Synthesizing insights from this pivotal report and other relevant studies, this article highlights key findings concerning the global prevalence and mortality of heart diseases, associated risk factors, and emerging diagnostic and therapeutic technologies.

Objective This study aimed to investigate the relationship between multiple inflammatory markers and poor outcome in patients with intracerebral hemorrhage,and to compare their predictive abilities.Methods We retrospectively analyzed the patients with intracerebral hemorrhage admitted to the Department of Neurology of the First Affiliated Hospital of Nanchang University from January 1,2015 to March 31,2023.According to the Modified Rankin Scale at 90 days after onset,the patients were divided into good outcome(mRS≤2 points)and poor outcome(mRS score≥3 points).Clinical information,laboratory examinations and follow-up data were compared between the two groups.Inflammatory markers include neutrophil to lymphocyte ratio(NLR),platelet to lymphocyte ratio(PLR),monocyte to high-density lipoprotein ratio(MHR),systemic inflammatory response index(SIRI),systemic immune-inflammation index(SII),white blood cell count to mean platelet volume ratio(WMR),lymphocyte to monocyte ratio(LMR),and systemic coagulation-inflammation index(SCI).Univariate and multivariate logistic regression analysis were used to analyze the predictors of poor prognosis after intracerebral hemorrhage,and receiver operating characteristic curve(ROC)was constructed to compare their predictive ability.Results A total of 510 patients with intracerebral hemorrhage were included.Of those,297(58.2%)had good outcome,and 213(41.8%)had poor outcome.Comparison of baseline characteristics demonstrated that patients with poor prognosis had higher levels of white blood cells,neutrophils,high-density lipoprotein,fibrinogen,NLR,PLR,SIRI,SII,WMR at admission,larger baseline hematoma volume and baseline perihematomal edema volume,a higher proportion of lobar hemorrhage,older age,and lower levels of platelets,lymphocytes,LMR,and SCI(P<0.05).Multivariate regression analysis showed that NLR(OR:1.081,95%CI:1.032～1.1131,P=0.001),SIRI(OR:1.089,95%CI:1.014～1.169,P=0.019),SII(OR:1.000,95%CI:1.000～1.001,P=0.011),WMR(OR:2.627,95%CI:1.267～5.445,P=0.009)were independently associated with poor prognosis in patients with ICH.In ROC analysis,the area under the curve of NLR(0.729,95%CI:0.685～0.774)was higher than SIRI(0.692,95%CI:0.645～0.738),SII(0.688,95%CI:0.641～0.735)and WMR(0.65,95%CI:0.602～0.698)for predicting poor outcomes.Conclusion NLR,SIRI,SII and WMR at admission are independently associated with poor outcomes in patients with intracerebral hemorrhage,and NLR has the strongest predictive ability.

Objective To investigate the role of the GPR120 gene in the progression of sepsis,explore the molecular mechanisms through which GPR120 gene regulates NOD-,LRR-and pyrin domain-containing protein 3(NLRP3)inflammasome activation and macrophage polarization.Methods The blood and pleural fluid samples were collected from the sepsis patients and the control group.The expression of inflammatory factors and the associated proteins were detected by flow cytometry and ELISA.C57BL/6 mice and monocyte-macrophage cell line(Raw264.7)were treated with lipopolysaccharide(LPS)to construct the sepsis models.After the intervention of GPR120 agonist TUG891,the expression of GPR120 gene,NLRP3 inflammasome protein and macrophage polarization protein were detected between the control group and the sepsis group.Results The expression of inflammatory factors,such as IL-1β in the serum of septic patients,significantly increased compared with the control(P<0.001).And the expression of inflammasome proteins such as NLRP3,Caspase-1 and IL-1β in the pleural fluid also increased(all P<0.05).In vivo,LPS could induce severe inflammation in lung tissue,the GPR120 gene expression decreased in lung tissue,and inflammatory factors were up-regulated in mouse serum(P<0.01).The inflammasome-associated protein and M1 type polarization of macrophages were enhanced,the TUG891 could reduce the inflammatory response,inhibit the NLRP3 inflammasome activating,and promote the M2 polarization of macrophages(P<0.01).In vitro,LPS could inhibit the intracellular GPR120 expression.The inflammatory factors secreted more in LPS-induced sepsis cells.TUG891 could promote the up-regulation of GPR120 protein and alleviate the secretion of inflammatory factors(P<0.05).Conclusion In sepsis,GPR120 gene activation could inhibit the NLRP3 inflammasome activation,promote macrophage polarization,and reduce the inflammatory damage,thereby delay the rapid progression of sepsis.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

Objective To propose a multiple regression-variational auto-encoders(MR-VAE)model to realize precise and non-invasive prediction of intra-abdominal pressure(IAP)in critically ill patients.Methods At first,a dataset was constructed by retrospectively analysing baseline characteristics and clinical indicators of 100 critically ill patients admitted to the Intensive Care Unit of Daping Hospital of Army Medical University between 30 August 2019 and 30 March 2021.Then,a MR-VAE prediction model was developed by integrating a feedforward neural network for supervised regression onto a variational autoencoder(VAE)framework and incorporating multiple regression strategies to mitigate feature interference.Finally,the MR-VAE model had its performance evaluated by its comparison with five classical models including support vector machines(SVM),convolutional neural networks(CNN),Scikit-learn integrated model(SIM),multi-layer perceptron(MLP)and K-nearest neighbors(KNN),and its prediction accuracy verified by testing the data of 10 randomly selected patients.Results The MR-VAE model behaved the best when compared with the five classical models,with a mean squared error(MSE)of 0.207,a root mean square error(RMSE)of 0.454,a mean absolute error(MAE)of 0.361,a median absolute deviation(MAD)of 0.243,an explained variance score(EVS)of 0.814 and a R2of 0.823,which also outperformed the five models in fitting performance,convergence and final loss.In random sample testing,the MR-VAE model exhibited high consistency between predicted and actual values.Conclusion The MR-VAE model proposed can accurately predict IAP,which has great potential in reducing the repeated measurements of IAP in critically ill patients and providing new ideas for the early diagnosis and treatment of IAH.

This study analyzed the demographic characteristics and clinically significant inflammatory index changes in listeriosis cases in China from 2010 to 2023.The aim was to understand Listeria monocytogenes susceptibility,to provide a reference for listeriosis prevention and control.Records in three Chinese databases—the China Knowledge Network,Wanfang Database,and VIP Database—from January 1,2010,to December 31,2023,were searched.Statistical analysis was conducted on the clinical features and epidemiological information for all identified cases.A total of 693 cases of listeriosis were included:482 occurring during the perinatal period and 211 occurring outside the perinatal period.The average mortality rate was 17.2%(119/693).The predominant clinical manifestations of listeriosis in neonatal patients during the perinatal period were sepsis(75.5%,241/319)and meningitis(41.1%,131/319).The mortality rate among neonatal patients was 27.1%(76/280).In patients in the non-perinatal period,meningitis(70.1%,148/211)and sepsis(43.6%,92/211)were the main clinical manifestations,and the average patient age was 47.2 years.Among patients of known age,the highest prevalence was observed in the 40-64 year age group,which accounted for 44.9%(44/98).Sixty-one cases had no other underlying diseases before infection.Reported cases of listeriosis occurred in 27 provinces(municipalities,and autonomous region)in China,and Beijing reported the most cases,accounting for 23.7%(164/693).L.monocytogenes was sensitive to β-lactam drug treatment but showed differing degrees of drug resistance.Among 145 cases,12 were resistant to penicillin,and 16 were resistant to oxacillin.Listeriosis is a foodborne disease with a high mortality rate,particularly among neonates.With the continuing emergence of drug-resistant strains,standardizing and strengthening prevention and treatment measures for this disease as early as possible are essential.

Purpose: The aim of this study was to investigate the feasibility of an intelligent handheld ultrasound (US) device for assisting non-expert general practitioners (GPs) in detecting carotid plaques (CPs) in community populations. Methods: This prospective parallel controlled trial recruited 111 consecutive community residents. All of them underwent examinations by non-expert GPs and specialist doctors using handheld US devices (setting A, setting B, and setting C). The results of setting C with specialist doctors were considered the gold standard. Carotid intima-media thickness (CIMT) and the features of CPs were measured and recorded. The diagnostic performance of GPs in distinguishing CPs was evaluated using a receiver operating characteristic curve. Inter-observer agreement was compared using the intragroup correlation coefficient (ICC). Questionnaires were completed to evaluate clinical benefits. Results: Among the 111 community residents, 80, 96, and 112 CPs were detected in settings A, B, and C, respectively. Setting B exhibited better diagnostic performance than setting A for detecting CPs (area under the curve, 0.856 vs. 0.749; P<0.01). Setting B had better consistency with setting C than setting A in CIMT measurement and the assessment of CPs (ICC, 0.731 to 0.923). Moreover, measurements in setting B required less time than the other two settings (44.59 seconds vs. 108.87 seconds vs. 126.13 seconds, both P<0.01). Conclusion Using an intelligent handheld US device, GPs can perform CP screening and achieve a diagnostic capability comparable to that of specialist doctors.

Aromatic immunity in traditional Chinese medicine(TCM) is the medical knowledge accumulated in the process of people's struggling with diseases. It plays an important role in plague prevention, disease treatment, health preservation, and rehabilitation, and has profound TCM basic theoretical support and abundant modern scientific evidence. With the in-depth promotion of the Healthy China initiative and the succession of health needs in the post-COVID-19 era, how to practice the health concept of aromatic immunity in TCM and develop its health service resources with high quality has become an important proposition to be discussed urgently. This paper summarizes the cognitive process, puts forward the basic concept, discusses the scientific connotation and clinical application value, and looks forward to the future development trend of aromatic immunity in TCM, aiming to provide guidance for the development of great health products and promote the application of aromatic immunity in TCM in serving people's health.
Medicine, Chinese Traditional/methods* ; Humans ; COVID-19/immunology* ; China ; Drugs, Chinese Herbal/therapeutic use* ; SARS-CoV-2

Atractylodes lancea is a perennial herbaceous plant of Asteraceae, with rhizomes for medical use. However, A. lancea plants from different habitats have great variability, and the germplasm resources of A. lancea are unclear and mixed during production. Therefore, it is urgent to protect new varieties of A. lancea. The distinctness, uniformity, and stability(DUS) testing of new plant varieties is the foundation of plant variety protection, and the DUS testing guidelines are the technical basis for variety approval agencies to conduct DUS testing. In this study, the phenotypic traits of 94 germplasm accessions of A. lancea were investigated considering the breeding and variety characteristics of A. lancea in China. The traits were classified and described, and 24 traits were preliminarily determined, including 20 basic traits that must be tested and four traits selected to be tested. The 20 basic traits included 3 quality traits, 5 false quality traits, and 12 quantitative traits, corresponding to 1 plant traits, 2 stem traits, 8 leaf traits, 6 flower traits, and 3 seed traits. The measurement ranges and coefficients of variation of eight quantitative traits were determined, on the basis of which the grading criteria and codes of the traits were determined and assigned. The guidelines has guiding significance for the trait evaluation, utilization, and breeding of new varieties of A. lancea.
Atractylodes/growth & development* ; China ; Phenotype ; Guidelines as Topic ; Plant Breeding