This study investigates the genetic diversity and evolutionary relationships of different Artemisia argyi germplasm resources to provide a basis for germplasm identification, variety selection, and resource protection. A total of 192 germplasm resources of A. argyi were studied, and EST-based simple sequence repeat(EST-SSR) primers were designed based on transcriptomic data of A. argyi. Polymerase chain reaction(PCR) amplification was performed on these resources, followed by fluorescence capillary electrophoresis to detect genetic diversity and construct DNA fingerprints. From 197 pairs of primers designed, 28 pairs with polymorphic and clear bands were selected. A total of 278 alleles were detected, with an average of 9.900 0 alleles per primer pair and an average effective number of alleles of 1.407 2. The Shannon's diversity index(I) for the A. argyi germplasm resources ranged from 0.148 1 to 0.418 0, with an average of 0.255 7. The polymorphism information content(PIC) ranged from 0.454 5 to 0.878 0, with an average of 0.766 9, showing high polymorphism. Cluster analysis divided the A. argyi germplasm resources into three major groups: Group Ⅰ contained 136 germplasm samples, Group Ⅱ contained 45, and Group Ⅲ contained 11. Principal component analysis also divided the resources into three groups, which was generally consistent with the clustering results. Mantel test results showed that the genetic variation in A. argyi populations was to some extent influenced by geographic distance, but the effect was minimal. Structure analysis showed that 190 germplasm materials had Q≥ 0.6, indicating that these germplasm materials had a relatively homogeneous genetic origin. Furthermore, 8 core primer pairs were selected from the 28 designed primers, which could distinguish various germplasm types. Using these 8 core primers, DNA fingerprints for the 192 A. argyi germplasm resources were successfully constructed. EST-SSR molecular markers can be used to study the genetic diversity and phylogenetic relationships of A. argyi, providing theoretical support for the identification and molecular-assisted breeding of A. argyi germplasm resources.
Artemisia/classification* ; Microsatellite Repeats ; Genetic Variation ; Expressed Sequence Tags ; DNA Fingerprinting ; Phylogeny ; Polymorphism, Genetic ; DNA, Plant/genetics* ; Genetic Markers

This study aims to explore the protective effect of Chaihu Jia Longgu Muli Decoction on rats with heart failure after myocardial infarction, and to clarify its possible mechanisms, providing a new basis for basic research on the mechanism of classic Chinese medicinal formula-mediated inflammatory response in preventing and treating heart failure induced by apoptosis after myocardial infarction. A heart failure model after myocardial infarction was established in rats by coronary artery ligation. The rats were divided into sham group, model group, and low, medium, and high-dose groups of Chaihu Jia Longgu Muli Decoction, with 10 rats in each group. The low-dose, medium-dose, and high-dose groups of Chaihu Jia Longgu Muli Decoction were given 6.3, 12.6, and 25.2 g·kg~(-1) doses by gavage, respectively. The sham group and model group were given an equal volume of distilled water by gavage once daily for four consecutive weeks. Cardiac function was assessed using color Doppler echocardiography. Myocardial pathology was detected by hematoxylin-eosin(HE) staining, apoptosis was measured by TUNEL assay, and mitophagy was observed by transmission electron microscopy. The levels of tumor necrosis factor-α(TNF-α), interleukin(IL)-1β, and N-terminal pro-B-type natriuretic peptide(NT-proBNP) in serum were detected by enzyme-linked immunosorbent assay(ELISA). The expression of apoptosis-related proteins B-cell lymphoma 2(Bcl-2), Bcl-2-associated X protein(Bax), and cleaved caspase-3 was detected by Western blot. Additionally, the expression of phosphorylated nuclear transcription factor-κB(NF-κB) p65(p-NF-κB p65)(upstream) and nuclear factor kappa B inhibitor alpha(IκBα)(downstream) in the NF-κB signaling pathway was assessed by Western blot. The results showed that compared with the sham group, left ventricular ejection fraction(LVEF) and left ventricular short axis shortening(LVFS) in the model group were significantly reduced, while left ventricular end diastolic diameter(LVEDD) and left ventricular end systolic diameter(LVESD) increased significantly. Myocardial tissue damage was severe, with widened intercellular spaces and disorganized cell arrangement. The apoptosis rate was increased, and mitochondria were enlarged with increased vacuoles. Levels of TNF-α, IL-1β, and NT-proBNP were elevated, indicating an obvious inflammatory response. The expression of pro-apoptotic factors Bax and cleaved caspase-3 increased, while the anti-apoptotic factor Bcl-2 decreased. The expression of p-NF-κB p65 was upregulated, and the expression of IκBα was downregulated. In contrast, the Chaihu Jia Longgu Muli Decoction groups showed significantly improved of LVEF, LVFS and decreased LVEDD, LVESD compared to the model group. Myocardial tissue damage was alleviated, and intercellular spaces were reduced. The apoptosis rate decreased, mitochondrial volume decreased, and the levels of TNF-α, IL-1β, and NT-proBNP were lower. The expression of pro-apoptotic factors Bax and cleaved caspase-3 decreased, while the expression of the anti-apoptotic factor Bcl-2 increased. Additionally, the expression of p-NF-κB p65 decreased, while IκBα expression increased. In summary, this experimental study shows that Chaihu Jia Longgu Muli Decoction can reduce the inflammatory response and apoptosis rate in rats with heart failure after myocardial infarction, which may be related to the regulation of the IκBα/NF-κB signaling pathway.
Animals ; Apoptosis/drug effects* ; Drugs, Chinese Herbal/administration & dosage* ; Rats ; Myocardial Infarction/physiopathology* ; Male ; NF-kappa B/genetics* ; Heart Failure/etiology* ; Rats, Sprague-Dawley ; Signal Transduction/drug effects* ; NF-KappaB Inhibitor alpha/genetics* ; Humans ; Tumor Necrosis Factor-alpha/genetics*

Allergic rhinitis (AR), a globally prevalent immune-mediated inflammatory condition, is still an incurable disease. In the present study, we have validated the impact of the Kelch-like ECH associated protein 1 (Keap1)-related oxidative stress and inflammatory response in clinical AR patient peripheral blood and nasal swab samples, emphasizing the biological relevance of Keap1 and AR. Targeting Keap1 -nuclear factor erythroid 2-related factor 2 (Nrf2) related anti-oxidative stress may be effective for AR intervention. Drawing inspiration from the Keap1 homodimerization and the E3 ligase characteristics, we herein present a design of novel bivalent molecules for chemical knockdown of Keap1. For the first time, we characterized ternary complexes of Keap1 dimer and one molecule of bivalent compounds. The best bivalent molecule 8 encompasses robust capacity to degrade Keap1 as a homoPROTAC^KEAP1. It efficaciously suppresses inflammatory cytokines in extensively different cells, including human nasal epithelial cells. Moreover, in an AR mouse model, we confirmed that the chemical degradation induced by homoPROTAC^KEAP1 led to therapeutic benefits in managing AR symptoms, oxidative stress and inflammation. In summary, our findings underscore the efficacy of targeting the Keap1 system through the homoPROTAC-ing technology as an innovative and promising treatment strategy for the incurable allergic disorders.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Background/Aims: Early detection and effective prognosis prediction in patients with hepatocellular carcinoma (HCC) provide an avenue for survival improvement, yet more effective approaches are greatly needed. We sought to develop the detection and prognosis models with ultra-sensitivity and low cost based on fragmentomic features of circulating cell free mtDNA (ccf-mtDNA). Methods: Capture-based mtDNA sequencing was carried out in plasma cell-free DNA samples from 1168 participants, including 571 patients with HCC, 301 patients with chronic hepatitis B or liver cirrhosis (CHB/LC) and 296 healthy controls (HC). Results: The systematic analysis revealed significantly aberrant fragmentomic features of ccf-mtDNA in HCC group when compared with CHB/LC and HC groups. Moreover, we constructed a random forest algorithm-based HCC detection model by utilizing ccf-mtDNA fragmentomic features. Both internal and two external validation cohorts demonstrated the excellent capacity of our model in distinguishing early HCC patients from HC and highrisk population with CHB/LC, with AUC exceeding 0.983 and 0.981, sensitivity over 89.6% and 89.61%, and specificity over 98.20% and 95.00%, respectively, greatly surpassing the performance of alpha-fetoprotein (AFP) and mtDNA copy number. We also developed an HCC prognosis prediction model by LASSO-Cox regression to select 20 fragmentomic features, which exhibited exceptional ability in predicting 1-year, 2-year and 3-year survival (AUC=0.8333, 0.8145 and 0.7958 for validation cohort, respectively). Conclusions We have developed and validated a high-performing and low-cost approach in a large clinical cohort based on aberrant ccf-mtDNA fragmentomic features with promising clinical translational application for the early detection and prognosis prediction of HCC patients.

Objective: To construct a hypertension risk prediction model for residents aged 18-79 years, so as to provide an assessment tool for early screening and prevention of hypertension in high-risk groups. Methods: The permanent residents aged 18-79 years from 6 townships (streets) in Fangshan District of Beijing Municipality were selected as the study subjects using a multi-stage stratified random sampling method from March to June 2023. Demographic information, lifestyle, body mass index (BMI), blood pressure, fasting blood glucose, and blood lipid were collected through questionnaire survey, physical examination, and laboratory tests. Subjects were randomly divided into training and validation sets at a 7∶3 ratio. The logistic regression model was used to screen the risk factors of hypertension, and a hypertension risk prediction nomogram was constructed. Receiver operating characteristic (ROC) curve, calibration curve, and decision curve analysis were used to verify the discrimination, fit, and clinical application value of the model. Results: A total of 4 438 subjects were included, including 2 365 males (53.29%) and 2 073 females (46.71%), with a mean age of (44.99±14.90) years. The prevalence of hypertension was 35.29% (1 566 cases), and the standardized prevalence was 24.74%. The logistic regression model screened out 9 influencing factors of hypertension. The nomogram was established as ln[p/ (1-p)]= -2.873 + 0.935×40-<50 years + 1.463×50-<60 years + 1.908×60-<70 years + 2.346×70-79 years + 0.298×male-0.675×college degree or above + 0.384×smoking + 0.227×drinking + 0.572×overweight + 1.449×obesity + 0.557×heart rate ≥80 beats/min + 0.428×diabetes + 0.484×dyslipidemia. The area under the ROC curve of the validation set was 0.821 (95%CI: 0.798-0.843), and the calibration curve results showed that the calibration curve fitted the actual curve well. Decision curve analysis showed that the threshold probability was in the range of 0.10 to 0.70, and the model had good predictive value and clinical application value. Conclusion The nomogram based on age, gender, educational level, smoking, drinking, body mass index, heart rate, diabetes, and dyslipidemia can be used to predict the risk of hypertension among residents aged 18-79 years.

OBJECTIVE: To investigate the clinical efficacy of Zhuangdan Yanshi Decoction combined with dapoxetine hydrochloride in the treatment of premature ejaculation with cholestasis and phlegm disturbance. METHODS: A total of 120 patients diagnosed with premature ejaculation and treated in the Andrology Outpatient Department of Shaanxi Provincial Hospital of Traditional Chinese Medicine from March to December in 2022 were selected and randomly divided into treatment group and control group, with 60 cases in each group. The incubation period of intravaginal ejaculation (IELT), the Diagnostic Scale of Premature Ejaculation (PEDT), the Premature Ejaculation Assessment Scale (PEP), the 5-item Sexual Function Evaluation of Chinese Premature Ejaculation Patients (CIPE-5) and the improvement of traditional Chinese medicine symptom scores were compared before and after the treatment. And the adverse reactions were recorded as well. RESULTS: A total of 105 cases were ultimately included, with 55 cases in the treatment group and 50 cases in the control group. Measurable improvements in IELT, PEDT scores, PEP scores, CIPE scores and TCM symptom scores had been found after treatment in both of two groups (P<0.05). Moreover, the improvement in the treatment group was superior to that in the control group (P<0.05). The total effective rate in the treatment group was 89.1%, which was higher than that(84%) in the control group, with no statistically significant difference between the two groups (P>0.05). The incidence of adverse reactions in the treatment group was 9.1%, which was 24% in the control group. There was significantly difference between two groups (P<0.05). CONCLUSION The combination therapy with Zhuangdan Yanshi Decoction and dapoxetine hydrochloride for premature ejaculation associated with cholestasis and phlegm disturbance syndrome is definite, and it can reduce the side effects of drugs, which is better than oral dapoxetine hydrochloride alone.
Humans ; Premature Ejaculation/drug therapy* ; Benzylamines/therapeutic use* ; Drugs, Chinese Herbal/therapeutic use* ; Male ; Naphthalenes/therapeutic use* ; Cholestasis/complications* ; Adult ; Benzyl Compounds/therapeutic use* ; Medicine, Chinese Traditional ; Treatment Outcome

The rapid development of artificial intelligence (AI), especially generative AI (GenAI), has already brought, and will continue to bring, revolutionary changes to our daily production and life, as well as create new opportunities and challenges for diagnostic and therapeutic practices in the medical field. Haihe Hospital of Tianjin University collaborates with the National Supercomputer Center in Tianjin, Tianjin University, and other institutions to carry out research in areas such as smart healthcare, smart services, and smart management. We have conducted research and development of a full-process disease diagnosis and treatment assistance system based on GenAI in the field of smart healthcare. The development of this project is of great significance. The first goal is to upgrade and transform the hospital's information center, organically integrate it with existing information systems, and provide the necessary computing power storage support for intelligent services within the hospital. We have implemented the localized deployment of three models: Tianhe "Tianyuan", WiNGPT, and DeepSeek. The second is to create a digital avatar of the chief physician/chief physician's voice and image by integrating multimodal intelligent interaction technology. With generative intelligence as the core, this solution provides patients with a visual medical interaction solution. The third is to achieve deep adaptation between generative intelligence and the entire process of patient medical treatment. In this project, we have developed assistant tools such as intelligent inquiry, intelligent diagnosis and recognition, intelligent treatment plan generation, and intelligent assisted medical record generation to improve the safety, quality, and efficiency of the diagnosis and treatment process. This study introduces the content of a full-process disease diagnosis and treatment assistance system, aiming to provide references and insights for the digital transformation of the healthcare industry.
Artificial Intelligence ; Humans ; Delivery of Health Care ; Generative Artificial Intelligence

Objective: To investigate the relationship between depressive symptoms and frailty among middle-aged and elderly populations, so as to provide insights into the early identification and prevention of frailty. Methods: Based on the 2018 database of China Health and Retirement Longitudinal Study (CHARLS), demographic information, lifestyle and self-rated health status were collected from people aged 50 years and older. Depression symptoms were evaluated using the Short Version of Center for Epidemiological Studies Depression Scales (CES-D-10), and the frailty status was evaluated using frailty index. The relationship between depressive symptoms and frailty among middle-aged and elderly populations were using a multivariable logistic regression model, and the dose-response relationship was analyzed using a restricted cubic spline model. Results: A total of 5 172 individuals were enrolled, including 2 495 males (48.24%) and 2 677 females (51.76%), with a median age of 63.00 (interquartile range, 12.00) years, a median CES-D-10 score of 7.00 (interquartile range, 9.00) scores. There were 1 560 participants (30.16%) detected with mild depressive symptoms, 360 participants (6.96%) detected with moderate to severe depressive symptoms. Multivariable logistic regression analysis showed that after adjusting for gender, age, educational level, marital status, smoking, alcohol consumption and self-rated health status, participants who had mild depressive symptoms (OR=4.226, 95%CI: 3.625-4.928) and moderate to severe depressive symptoms (OR=10.737, 95%CI: 8.259-13.958) had a higher risk of frailty. The restricted cubic spline model showed a nonlinear relationship between depressive symptoms and frailty among middle-aged and elderly populations. When the CES-D-10 scores were greater than 7, the risk of frailty increased with higher CES-D-10 scores. Conclusion The degree of depressive symptoms in middle-aged and elderly people is associated with frailty, and there is a nonlinear relationship between the two.