ObjectiveTo systematically evaluate the content differences of 4 components in Leonuri Herba granules， reveal the quality fluctuation patterns of products from the same and different manufacturers， providing scientific basis for the optimization of production process and quality control. MethodsHigh performance liquid chromatography-diode array detector-charged aerosol detector（HPLC-DAD-CAD） was employed to determine the contents of 4 components（syringic acid， leonurine hydrochloride， ferulic acid， and stachydrine hydrochloride） in samples from 19 manufacturers（53 batches， 159 boxes）. Additionally， fingerprint profiles were constructed， and the fingerprint dissimilarity（P_S） and relative standard deviation（RSD） of different samples from the same manufacturer were calculated. A principal component analysis（PCA） model was established with P_S and the RSD values of the 4 components as variables to classify the manufacturers. Finally， samples from 5 manufacturers（M1-M5） covering three consistency groups were selected to calculate three quality consistency parameters， namely intra-batch consistency（P_A）， inter-batch consistency（P_B）， and P_S. Then， PCA was performed with P_A， P_B， and P_S of these 5 manufacturers as variables. ResultsThe average total content of the 4 index components per bag across the 19 manufacturers ranged from 41.10 mg to 97.54 mg. Among them， the content of stachydrine hydrochloride（a pharmacopoeial quality control component） was 32.46-72.70 mg per bag， all meeting the requirements of the 2025 edition of the Pharmacopoeia of the People's Republic of China， with RSD of 1.7%-17.1%. The content ranges of the other 3 components were as follows：syringic acid of 1.43-41.92 mg per bag， leonurine hydrochloride of 0.67-11.85 mg per bag， and ferulic acid of 0.11-3.81 mg per bag. Notably， leonurine hydrochloride exhibited the most significant content fluctuation among samples from the same manufacturer（RSD of 4.8%-59.2%）. PCA results showed that the 19 manufacturers could be classified into 3 categories. Samples from 8 manufacturers（M2， M6， M7， M8， M10， M15， M17， M18） demonstrated relatively high consistency， five manufacturers（M3， M9， M12， M13， M14） showed moderate consistency， six manufacturers（M1， M4， M5， M11， M16， M19） exhibited low consistency. The two methods yielded consistent classification results for the 5 representative manufacturers， verifying the reliability of the proposed method. Among these， manufacturer M2 showed the best quality consistency and the highest total content of indicator components among M1-M5. ConclusionThe HPLC-DAD-CAD multi-detector hyphenation technology established in this study enables the accurate detection of 4 components in Leonuri Herba granules. Significant differences in the total content of these four components are observed among products from 19 manufacturers. The application of 2 consistency evaluation methods combined with PCA can effectively classify their consistency into 3 categories， and the classification results of the 2 methods are highly consistent. This study provides scientific basis for the process optimization and quality standard improvement of Leonuri Herba granules.

ObjectiveTo systematically evaluate the content differences of 4 components in Leonuri Herba granules， reveal the quality fluctuation patterns of products from the same and different manufacturers， providing scientific basis for the optimization of production process and quality control. MethodsHigh performance liquid chromatography-diode array detector-charged aerosol detector（HPLC-DAD-CAD） was employed to determine the contents of 4 components（syringic acid， leonurine hydrochloride， ferulic acid， and stachydrine hydrochloride） in samples from 19 manufacturers（53 batches， 159 boxes）. Additionally， fingerprint profiles were constructed， and the fingerprint dissimilarity（P_S） and relative standard deviation（RSD） of different samples from the same manufacturer were calculated. A principal component analysis（PCA） model was established with P_S and the RSD values of the 4 components as variables to classify the manufacturers. Finally， samples from 5 manufacturers（M1-M5） covering three consistency groups were selected to calculate three quality consistency parameters， namely intra-batch consistency（P_A）， inter-batch consistency（P_B）， and P_S. Then， PCA was performed with P_A， P_B， and P_S of these 5 manufacturers as variables. ResultsThe average total content of the 4 index components per bag across the 19 manufacturers ranged from 41.10 mg to 97.54 mg. Among them， the content of stachydrine hydrochloride（a pharmacopoeial quality control component） was 32.46-72.70 mg per bag， all meeting the requirements of the 2025 edition of the Pharmacopoeia of the People's Republic of China， with RSD of 1.7%-17.1%. The content ranges of the other 3 components were as follows：syringic acid of 1.43-41.92 mg per bag， leonurine hydrochloride of 0.67-11.85 mg per bag， and ferulic acid of 0.11-3.81 mg per bag. Notably， leonurine hydrochloride exhibited the most significant content fluctuation among samples from the same manufacturer（RSD of 4.8%-59.2%）. PCA results showed that the 19 manufacturers could be classified into 3 categories. Samples from 8 manufacturers（M2， M6， M7， M8， M10， M15， M17， M18） demonstrated relatively high consistency， five manufacturers（M3， M9， M12， M13， M14） showed moderate consistency， six manufacturers（M1， M4， M5， M11， M16， M19） exhibited low consistency. The two methods yielded consistent classification results for the 5 representative manufacturers， verifying the reliability of the proposed method. Among these， manufacturer M2 showed the best quality consistency and the highest total content of indicator components among M1-M5. ConclusionThe HPLC-DAD-CAD multi-detector hyphenation technology established in this study enables the accurate detection of 4 components in Leonuri Herba granules. Significant differences in the total content of these four components are observed among products from 19 manufacturers. The application of 2 consistency evaluation methods combined with PCA can effectively classify their consistency into 3 categories， and the classification results of the 2 methods are highly consistent. This study provides scientific basis for the process optimization and quality standard improvement of Leonuri Herba granules.

Objective To propose a lightweight end-to-end neural network model for automated Korotkoff sound phase recognition and subsequent blood pressure (BP) measurement, aiming to improve measurement accuracy and population adaptability. Methods We developed a streamlined architecture integrating depthwise separable convolution (DSConv), multi-head attention (MHA), and bidirectional gated recurrent unit (BiGRU). The model directly processes Korotkoff sound time-series signals to identify auscultatory phases. Systolic BP (SBP) and diastolic BP (DBP) were determined using phase Ⅰ and phaseⅤdetections, respectively. Given the clinical relevance of phase Ⅳ for specific populations (e.g., children and pregnant women, denoted as DBPⅣ), BP values from this phase were also recorded.Results The study enrolled 106 volunteers with 70 males and 36 females at mean age of (40.0±12.0) years. The model achieved 94.25% phase recognition accuracy. Measurement errors were (0.1±2.5) mm Hg (SBP), (0.9±3.4) mm Hg (DBPⅣ), and (0.8±2.6) mm Hg (DBP). Conclusion Our method enables precise phase recognition and BP measurement, demonstrating potential for developing population-adaptive blood pressure monitoring systems.

Objective To analyze the epidemiological characteristics of newly diagnosed occupational coal workers' pneumoconiosis (CWP) in Gansu Province. Methods All newly diagnosed cases of CWP reported online in Gansu Province from 2005 to 2024 were collected as study subjects through the "Occupational Diseases and Health Hazard Factors Monitoring Information System". A descriptive epidemiological method was used to analyze the epidemiological characteristics. A total of 886 newly diagnosed CWP cases were reported in Gansu Province during 2005-2024. Results Among them, cases initially diagnosed as stageⅠ, stage Ⅱ, and stage Ⅲ accounted for 68.8%, 20.0%, and 11.2%, respectively. The cases were predominantly male, accounting for 99.0%. Age groups of 50-<60 years and ≥60 years accounted for 47.0% and 42.9%, respectively. In terms of regional distribution, Lanzhou City, Pingliang City, and Baiyin City were the main affected areas, accounting for 36.0%, 19.1%, and 16.4%, respectively. Regarding industry distribution, the coal mining and washing industry accounted for 91.3% of the cases. Enterprises of large and small sizes accounted for 46.0% and 29.7%, respectively. In terms of enterprise economic types, state-owned enterprises and private enterprises accounted for 54.2% and 21.6%, respectively. The median duration of dust exposure among newly diagnosed CWP cases was 18 years. As of 2024, 102 cases had progressed to a more advanced stage; among the progressed cases, stageⅠ, stage Ⅱ, and stage Ⅲ cases accounted for 58.1%, 28.3%, and 13.6%, respectively. Conclusion Cases of CWP in Gansu Province are mainly distributed in large state-owned coal mines in cities such as Lanzhou, Pingliang, and Baiyin, predominantly affecting older males with longer dust exposure durations. Therefore, occupational health supervision and management in coal dust-related enterprises in the province should be further strengthened, and the occupational health examination procedures for workers exposed to dust should be standardized.

Liver cancer is one of the most common malignant tumors worldwide. Currently, the available treatment methods cannot fully control its recurrence and mortality rate. Establishing appropriate animal models for liver cancer is crucial for developing new treatment technologies and strategies. The patient-derived xenograft (PDX) model preserves the tumor's microenvironment and heterogeneity, which makes it advantageous for biological research, drug evaluation, personalized medicine, and other purposes. This article reviews the development, preparation techniques, application fields, and challenges of PDX models in liver cancer, providing insights for the research and exploration of PDX models in diagnostic and therapeutic strategies of liver cancer.
Liver Neoplasms/drug therapy* ; Animals ; Humans ; Xenograft Model Antitumor Assays/methods* ; Mice ; Disease Models, Animal

OBJECTIVES: To investigate the relationship between the polygenic risks for various psychiatric disorders and clinical and neuropsychological characteristics in children with attention-deficit/hyperactivity disorder (ADHD). METHODS: Using a cross-sectional design, 285 children with ADHD and 107 healthy controls were assessed using the Child Behavior Checklist, the Behavior Rating Inventory of Executive Function for parents, the Wechsler Intelligence Scale for Children, Fourth Edition, and the Cambridge Neuropsychological Test Automated Battery. Blood samples were collected for genetic data. Polygenic risk scores (PRSs) for various psychiatric disorders were calculated using the PRSice-2 software. RESULTS: Compared with the healthy controls, the children with ADHD displayed significantly higher PRSs for ADHD, major depressive disorder, anxiety disorder, and obsessive-compulsive disorder (P<0.05). In terms of daily-life executive function, ADHD-related PRS was significantly correlated with the working memory factor; panic disorder-related PRS was significantly correlated with the initiation factor; bipolar disorder-related PRS was significantly correlated with the shift factor; schizophrenia-related PRS was significantly correlated with the inhibition, emotional control, initiation, working memory, planning, organization, and monitoring factors (P<0.05). The PRS related to anxiety disorders was negatively correlated with total IQ and processing speed index (P<0.05). The PRS related to obsessive-compulsive disorder was negatively correlated with the processing speed index and positively correlated with the stop-signal reaction time index of the stop-signal task (P<0.05). CONCLUSIONS PRSs for various psychiatric disorders are closely correlated with the behavioral and cognitive characteristics in children with ADHD, which provides more insights into the heterogeneity of ADHD.
Humans ; Attention Deficit Disorder with Hyperactivity/genetics* ; Child ; Male ; Female ; Cross-Sectional Studies ; Neuropsychological Tests ; Multifactorial Inheritance ; Adolescent ; Mental Disorders/etiology* ; Executive Function ; Genetic Risk Score

BACKGROUND: Despite some studies identifying a potential association between obesity and chronic obstructive pulmonary disease (COPD) risk, previous research had overlooked the dynamic nature of body weight over time, leading to inconsistent findings. The purpose of this study is to elucidate the relationship between adult weight change and COPD risk by adjusting for potential confounding factors. METHODS: We conducted a retrospective analysis using data from ten NHANES cycles (1999-2018), including adults aged 40-74 years. Weight change patterns were assessed using BMI at three time points and classified into five categories per period. Absolute weight change was also grouped into five levels. Multivariate logistic regression models, incorporating sampling weights, were used to examine associations between weight change and COPD, adjusting for demographic and lifestyle covariates. RESULTS: Compared with participants who maintained normal weight, stable obesity participants had increased risk of COPD from age 25 years to 10 years before the survey (OR = 1.45, 95% CI = 1.15 to 1.83), in the 10 years period before the survey (OR = 1.75, 95% CI = 1.47 to 2.08), and from age 25 years to survey (OR = 1.84, 95% CI = 1.46 to 2.31). Three periods indicate that weight gain in adulthood was associated with risk of COPD. In addition, substantial weight gain of more than 20 kg was associated with a higher risk of COPD. In stratified analyses, we also observed a more significant association between weight change and the risk of COPD in never smokers compared to former smokers. CONCLUSIONS Our study suggested that stable obesity and weight gain in adulthood were associated with an increased risk of COPD compared to those who maintain a normal weight, and that the association between weight gain and the incidence of COPD appears closer in patients who have never smoked.
Humans ; Pulmonary Disease, Chronic Obstructive/etiology* ; Middle Aged ; Male ; Female ; Adult ; Aged ; Retrospective Studies ; Weight Gain ; Obesity/complications* ; Risk Factors ; United States/epidemiology* ; Nutrition Surveys ; Body Mass Index

Objective To observe the value of MRI quantified uterine indictors in late pregnancy for predicting uterine inertia in delivery.Methods A total of 182 pregnant women were retrospectively collected and were divided into uterine inertia group(inertia group,n=67)and non-uterine inertia group(non-inertia group,n=115)based on delivery or cesarean section records.MRI quantified uterine indicators were compared between groups,and those being statistically different were included to build a multivariate logistic regression model for predicting uterine inertia in delivery.The predictive performance of this model was evaluated using receiver operating characteristic(ROC)curve and the area under the curve(AUC).Results The inertia group had more previous uterine surgeries,also higher proportion of in vitro fertilization and embryo transfer(IVF-ET)and cesarean sections compared to the non-inertia group(all P＜0.05).In late pregnancy,the longitudinal diameter of the uterus,cervical length and the thickness of the myometrium at the placental attachment site in inertia group were larger than those in non-inertia group(all P＜0.05).Increased times of previous uterine surgeries,undergoing IVF-ET,as well as increased longitudinal diameter of the uterus and cervical length in late pregnancy were all independent predictors of uterine inertia in delivery(all P＜0.05).AUC of the multivariate logistic regression model established based on the above factors for predicting uterine inertia in delivery was 0.733.Conclusion MRI quantified uterine indictors in late pregnancy could be used to predict uterine inertia in delivery.