The present study employed UPLC-MS/MS to analyze and identify compounds in the raw powder of Tongluo Shenggu capsules. An HPLC method for the determination of vitexin content was established. The analysis of this drug was performed on a 30 ℃ thermostatic Acquity UPLC® BEH C18 (2.1 mm×100 mm,1.7 μm) column, with the mobile phase comprising 0.2% formic acid-methanol flowing at 0.3 mL /min in a gradient elution manner. Mass spectrometry was detected by ESI sources in both positive and negative ion modes for qualitative identification of chemical constituents. 12 flavonoid and 3 stilbenes compounds in the raw powder of Tongluo Shenggu capsules were successfully identified. Additionally, an HPLC method for the determination of vitexin content was established using a XBridge C18 column (4.6 mm × 250 mm, 5 µm) with a mobile phase of 0.05% glacial acetic acid in methanol for gradient elution, at a column temperature of 30 °C, a flow rate of 1.0 mL/min, and an injection volume of 20 μL. The method demonstrated good linearity in the concentration range of 10 µg/mL to 40 µg/mL (R=1.000) with an average recovery rate of 96.7%. The establishment of these methods provides a scientific basis for the quality control and development of the raw powder of Tongluo Shenggu capsules.

Objective:To evaluate the efficacy and safety of nebulized inhalation of recombinant human interferon (IFN) α1b injection in the treatment of respiratory syncytial virus (RSV) associated lower respiratory tract infections (pneumonia and bronchiolitis) in children.Methods:A randomized, double-blind, parallel, placebo-controlled add-on design was used.Children with pneumonia or bronchiolitis aged 2 months to 5 years who tested positive for RSV antigen within 72 hours of onset from 30 clinical trial sites including Beijing Children′s Hospital, Capital Medical University between February 2021 and December 2022 were included in this study and randomly divided into 2 groups at a ratio of 1∶1 based on a stratified-block method.Both groups received basic treatments such as cough control, asthma relieving, expectorant treatment, fever reduction, oxygen therapy, etc.The experimental group received additional nebulized inhalation of IFN α1b injection at a dose of 2.0 μg/(kg·time), twice a day.The control group received nebulized inhalation of placebo twice a day.Clinical efficacy was evaluated based on indicators such as the duration of clinical symptoms and signs, and the Kaplan-Meier method was used to calculate the median and 95% CI of the duration of clinical symptoms and signs.The Log-rank test was used to compared data between groups.Safety was assessed through the incidence of adverse reactions and laboratory tests, and the Chi-square test was used to analyze the difference between groups. Results:There were 123 children in the experimental group and 122 children in the control group.The median durations of all the 5 clinical symptoms and signs [including shortness of breath, wheezing, dyspnea (visible retractions), decreased transcutaneous oxygen saturation, and abnormal mental state] in the experimental group after treatment were slightly shortened than those in the control group [2.7 d(95% CI: 1.9-3.0 d)] vs.[2.9 d(95% CI: 2.6-3.6 d), P=0.027].The improvement in dyspnea (retractions) was especially pronounced in the experimental group, with a relief rate of 50.0% (0, 100%) on the first day of administration[compared with 0 (0, 50.0%) in the control group ( Z=2.002, P=0.025)].The median duration of dyspnea in the experimental group was nearly 1 day shorter than that in the control group [1.0 d(95% CI: 0.7-1.7 d) vs.1.8 d(95% CI: 1.0-2.5 d), P=0.046].There were no significant difference in hospital stay [6.0(5.0, 8.0) d vs.6.5(5.0, 8.0) d, Z=0.675, P=0.500], oxygen therapy duration [32.0(14.0, 96.3) h vs.39.0 (24.0, 83.2) h, Z=0.094, P=0.925], the recovery rate from clinical symptoms during treatment [(105/106, 99.1%) vs.(96/101, 95.0%)], and recurrence rate [(0/106, 0) vs.(2/101, 2.0%)] between the 2 groups (all P>0.05).However, the above-mentioned four indicators in the experimental group showed a trend of clinical benefits.The quantitative virus detection results showed that the RSV viral load in both groups decreased after treatment compared to before treatment.After 2 days of treatment, the decline rate of RSV viral load from the baseline was 0.90 lg copies/(mL·d) in the experimental group and 0.25 lg copies/(mL·d)in the control group, with a statistically significant difference ( P<0.05).Furthermore, there was no statistically significant difference in the incidence of adverse reactions between the 2 groups ( P>0.05).Importantly, no drug-related serious adverse reactions occurred in both groups. Conclusions:The nebulized inhalation therapy of IFN α1b demonstrates efficacy and safety in treating pediatric RSV associated lower respiratory tract infections.It particularly offers outstanding clinical therapeutic value for severe children.

Objective:To develop an artificial intelligence (AI)-based platelet review strategy to identify abnormal platelet histograms with no significant difference between initial impedance platelet count (PLT-I) and PLT-F results.Methods:This study included 5 119 routine blood analysis in Nanfang Hospital of Southern Medical University and its Ganzhou branch from July 2023 and March 2024. Specimens exhibiting abnormal platelet histograms and an initial platelet count >40×10?/L underwent review using the fluorescent platelet count (PLT-F) channel. Consistency of the results was defined as a difference between impedance platelet count (PLT-I) and PLT-F less than ±20% of the PLT-F results. A deep learning model was developed using platelet and red blood cell histogram data from a training set of 3 807 specimens. The model′s diagnostic performance was evaluated on an independent external validation set ( n=805) using receiver operating characteristic (ROC) curve analysis. Changes in the number of reviewed samples and sample turnaround time were analyzed to assess its clinical utility. Results:The deep learning model based on platelet and red blood cell histograms achieved an area under the ROC curve (AUC) of 0.854 in the training set. At a cutoff value of 0.1, the sensitivity was 0.954 and specificity was 0.358. The model could reduce review by 16.80% (190/1 131). In the validation set, the AUC was 0.805, with a sensitivity of 0.955 and specificity of 0.307, corresponding to a reduction of 17.41% (47/270) in reviewed specimens.Conclusion:The platelet review prediction model developed based on deep learning technology can efficiently identify samples with consistent results before and after review, reducing unnecessary reviews and shortening specimen testing time, thereby improving the efficiency of platelet test.

This paper presents an automatic acquisition and analytic procedure of acupuncture manipulation based on optical navigation, aiming at solving the shortcomings of existing acquisition methods of acupuncture manipulation. An acquisition holder installed at the handle tail of filiform needle was designed to display the movement trajectory of the needle during acupuncture delivery by collecting the movement trajectory of holder. The 3-month old male Bama miniature pig was selected as the experimental subject, and 6 points, "Bojian" "Qiangfeng" "Housanli" "Xiaokua" "Huiyang" (BL35) and "Baihui" (GV20), were selected during acupuncture manipulation. The optical navigation system was used to collect the real-time data, and these data were per-processed and analyzed using mean filtering and Fourier transform. The acupuncture procedure was divided into 3 stages, inserting, lifting-thrusting, and twisting. The results showed that the accuracy was 96.3% at lifting-thrusting stage, and that was 100.0% at twisting stage. The decomposition effect of the entire procedure was satisfactory. This study provides a new approach to the quantitative analysis of acupuncture manipulation. In the future, it needs to further optimize the algorithm and expand the sample size so as to improve the accuracy of this analytic technique.
Acupuncture Therapy/methods* ; Male ; Animals ; Swine ; Acupuncture Points ; Humans ; Swine, Miniature ; Needles

BACKGROUND: Valvular heart disease (VHD) has become increasingly common with the aging in China. This study aimed to evaluate regional differences in the clinical features, management strategies, and outcomes of patients with VHD across different regions in China. METHODS: Data were collected from the China-VHD Study. From April 2018 to June 2018, 12,347 patients who presented with moderate or severe native VHD with a median of 2 years of follow-up from 46 centers at certified tertiary hospitals across 31 provinces, autonomous regions, and municipalities in Chinese mainland were included in this study. According to the locations of the research centers, patients were divided into five regional groups: eastern, southern, western, northern, and central China. The clinical features of VHD patients were compared among the five geographical regions. The primary outcome was all-cause mortality or rehospitalization for heart failure. Kaplan-Meier survival analysis was used to compare the cumulative incidence rate. RESULTS: Among the enrolled patients (mean age, 61.96 years; 6877 [55.70%] male), multiple VHD was the most frequent type (4042, 32.74%), which was mainly found in eastern China, followed by isolated mitral regurgitation (3044, 24.65%), which was mainly found in northern China. The etiology of VHD varied significantly across different regions of China. The overall rate of valve interventions was 32.67% (4008/12,268), with the highest rate in southern China at 48.46% (205/423). In terms of procedure, the proportion of transcatheter valve intervention was relatively low compared to that of surgical treatment. Patients with VHD in western China had the highest incidence of all-cause mortality or rehospitalization for heart failure. Valve intervention significantly improved the outcome of patients with VHD in all five regions (all P  <0.05). CONCLUSIONS: This study revealed that patients with VHD in China are characterized by significant geographic disparities in clinical features, treatment, and clinical outcomes. Targeted efforts are needed to improve the management and prognosis of patients with VHD in China according to differences in geographical characteristics. REGISTRATION ClinicalTrials.gov , NCT03484806.
Aged ; Female ; Humans ; Male ; Middle Aged ; China/epidemiology* ; Heart Valve Diseases/therapy* ; Kaplan-Meier Estimate ; Tertiary Care Centers ; Treatment Outcome

The risk prediction of paroxysmal atrial fibrillation (PAF) is a challenge in the field of biomedical engineering. This study integrated the advantages of machine learning feature engineering and end-to-end modeling of deep learning to propose a PAF risk prediction method based on multimodal feature fusion. Additionally, the study utilized four different feature selection methods and Pearson correlation analysis to determine the optimal multimodal feature set, and employed random forest for PAF risk assessment. The proposed method achieved accuracy of (92.3 ± 2.1)% and F1 score of (91.6 ± 2.9)% in a public dataset. In a clinical dataset, it achieved accuracy of (91.4 ± 2.0)% and F1 score of (90.8 ± 2.4)%. The method demonstrates generalization across multi-center datasets and holds promising clinical application prospects.
Humans ; Atrial Fibrillation/diagnosis* ; Machine Learning ; Deep Learning ; Risk Assessment/methods*

OBJECTIVES: To create a mixed valvular heart disease (MVHD)-related age-adjusted comorbidity index (MVACI) model for predicting mortality risk of patients with MVHD. METHODS: A total of 4080 patients with moderate or severe MVHD in the China-VHD study were included. The primary endpoint was 2-year all-cause mortality. A MVACI model prediction model was constructed based on the mortality risk factors identified by univariate and multivariate Cox regression analysis. Restricted cubic splines were used to assess the relationship between MVACI scores and 2-year all-cause mortality. The optimal threshold, determined by the maximum Youden index from receiver operator characteristic (ROC) curve analysis, was used to stratify patients. Kaplan-Meier method was used to calculate 2-year all-cause mortality and compared using the Log-rank test. Univariate and multivariate Cox proportional hazards models were employed to calculate hazard ratios (HR) and 95% confidence intervals (CI), evaluating the association between MVACI scores and mortality. Paired ROC curves were used to compare the discriminative ability of MVACI scores with the European System for Cardiac Operative Risk Evaluation Ⅱ(EuroSCORE Ⅱ) or the age-adjusted Charlson comorbidity index (ACCI) in predicting 2-year clinical outcomes, while calibration curves assessed the calibration of these models. Internal validation was performed using the Bootstrap method. Subgroup analyses were conducted based on etiology, treatment strategies, and disease severity. RESULTS: Multivariate analysis identified the following variables independently associated with 2-year all-cause mortality in patients: pulmonary hypertension, myocardiopathy, heart failure, low body weight (body mass index <18.5 kg/m²), anaemia, hypoalbuminemia, renal insufficiency, cancer, New York Heart Association (NYHA) class and age. The score was independently associated with the risk of all-cause mortality, and exhibited good discrimination (AUC=0.777, 95%CI: 0.755-0.799) and calibration (Brier score 0.062), with significantly better predictive performance than EuroSCORE Ⅱ or ACCI (both adjusted P<0.01). The internal validation showed that the MVACI model's predicted probability of 2-year all-cause mortality was generally consistent with the actual probability. The AUCs for predicting all-cause mortality risk were all above 0.750, and those for predicting adverse events were all above 0.630. The prognostic value of the score remained consistent in patients regardless of their etiology, therapeutic option, and disease severity. CONCLUSIONS The MVACI was constructed in this study based on age and comorbidities, and can be used for mortality risk prediction and risk stratification of MVHD patients. It is a simple algorithmic index and easy to use.
Humans ; Prognosis ; Comorbidity ; Heart Valve Diseases/epidemiology* ; Female ; Male ; Middle Aged ; Aged ; Proportional Hazards Models ; Risk Factors ; China/epidemiology* ; Age Factors ; Risk Assessment ; Adult ; ROC Curve

OBJECTIVES: To investigate the mechanism of DDX17 for regulating proliferation and migration of pulmonary arterial smooth muscle cells (PASMCs) during the development of pulmonary hypertension (PH). METHODS: In murine PASMCs cultured under normoxic or hypoxic conditions, the effects of transfection with si-Ddx17 and insulin treatment, alone or in combination, on cell proliferation and migration were evaluated using Ki-67 immunofluorescence staining, scratch assay and Transwell assay. Western Blotting was performed to detect the changes in protein expression levels of DDX17, 4EBP1, S6, p-4EBP1, and p-S6. In a mouse model of PH induced by intraperitoneal injection of monocrotaline (MCT), the changes in pulmonary vasculature were examined using HE staining following tail vein injection of AD-Ddx17i. RESULTS: The PASMCs in hypoxic culture exhibited significantly enhanced cell proliferation and migration and protein expressions of p-4EBP1 and p-S6, and these changes were obviously reversed by transfection with si-Ddx17. Treatment with insulin significantly attenuated the effect of si-Ddx17 against hypoxic exposure-induced changes in PASMCs. In the mouse model of MCT-induced PH, transfection with AD-Ddx17i obviously alleviated pulmonary vascular stenosis and intimal hyperplasia. CONCLUSIONS The expression of DDX17 is elevated in hypoxia-induced PASMCs and PH mice, and silencing DDX17 significantly inhibits PASMC proliferation and migration in vitro and pulmonary vascular remodeling in PH mice by reducing mTORC1 activity.
Animals ; Cell Proliferation ; Cell Movement ; DEAD-box RNA Helicases/metabolism* ; Myocytes, Smooth Muscle/metabolism* ; Mice ; Pulmonary Artery/cytology* ; Hypertension, Pulmonary/metabolism* ; Mechanistic Target of Rapamycin Complex 1 ; Cells, Cultured ; Muscle, Smooth, Vascular/cytology*

In order to study the pathogenesis of meningitis in lambs caused by Enterococcus faecalis(E.faecalis),and to elucidate the pathogenesis of meningitis from the circRNA level,E.faecalis(named XJ6)was reintroduced into the host to construct a lamb brain tissue injury model,and then the lamb brain tissues were selected for whole genome transcript sequencing at four time in-tervals(24,48,60 and 72 h).Based on the transcriptomics sequencing results,the differential cir-cRNAs were preliminarily screened,and the accuracy of the transcriptomics data was verified by real-time fluorescence quantification.The results showed that the experiments successfully con-structed the brain tissue injury model of E.faecalis infected lambs,and the GO enrichment analy-sis results showed the most significant 10 cellular components,10 biological processes,and 10 mo-lecular functions.KEGG pathway enrichment results revealed that the genes targeted by differenti-al circRNAs were mainly focused on signaling pathways regulating the neuronal cells,the MAPK signaling pathway,the Rap1 signaling pathway,VDEF signaling pathway,Apelin signaling path-way,vascular smooth muscle contraction,and cancer development.The differentially expressed cir-cRNAs validated by real-time quantitative PCR were completely consistent with the transcriptomic results.Among them,novel_circ_0004872 was identified as a candidate circRNA potentially involved in altering the permeability of the blood-brain barrier in lambs,providing a theoretical ref-erence for exploring the regulatory role of circRNAs in blood-brain barrier function.

Objectives:Utilizing an advanced and high-capacity data acquisition system tailored for elderly patients with valvular heart disease,we aimed to establish standardized data acquisition protocols and define variable sets for a clinical research big data platform dedicated to this condition.Guided by clinical treatment decisions,we implemented a standardized and uniform evaluation process for valvular heart disease.This initiative might culminate in the creation of the first comprehensive database for elderly valvular heart disease,encompassing clinical information,functional assessments,multimodal imaging,treatment modalities,and follow-up data.Methods:Variables were selected based on past clinical studies and literature,both domestic and international,and considering key guidelines,advancements in valvular heart disease,and China's clinical practices.Standards for data variables,imaging techniques,data acquisition,multi-channel verification,and quality control were established.Variables are then classified by their properties and generation time.Results:This comprehensive set of variables encompassed a total of 567 relevant variables,which were generated throughout the entire diagnosis and treatment process of patients with valvular heart disease,starting from admission and extending to those required for clinical research.The variable set was divided into six distinct parts:clinical information(encompassing demographics,admission details,clinical manifestations,comorbidities,medical history,physical examination,auxiliary examinations,and comprehensive assessment of frailty in the elderly),echocardiography,cardiac computed tomography(CT),treatment(including surgery,valve intervention therapy,non-valve intervention therapy,and medication therapy),clinical outcomes,and follow-up.Specifically,it included 14 variables related to demographic and admission information;22 variables encompassing clinical manifestations and physical examination;63 variables concerning medical history and comorbidities;49 variables for inspection and examination;15 variables for the comprehensive evaluation of frail elderly individuals;55 variables of echocardiography,including complete dynamic images at 4 time points,6 cross-sections per point,and corresponding Doppler spectra);131 variables for cardiac CT,including baseline and postoperative raw image uploads(encompassing non-enhanced electrocardiography[ECG]-gated cardiac CT scans,ECG-gated full-phase CT angiography(CTA)scans,and large-scale non-ECG-gated spiral CTA scans);51 variables for surgical diagnosis and treatment;72 variables for valve intervention therapy;33 variables for non-valvular interventional therapy;27 variables for medication information;and 35 variables for clinical outcomes.The follow-up integration comprises 140 variables,along with the upload of raw echocardiography and CT images.Conclusions:Through the establishment of data collection standards and variable standards for the big data platform of valvular heart disease,the standardization and normalization of comprehensive evaluation,diagnosis and treatment,and clinical research of patients with valvular heart disease can be achieved.As a national level big data research platform that can be sustainably used for clinical research and innovative development of valvular heart disease,it will provide support for long-term monitoring of valvular heart disease,real-world data analysis,clinical research(observational and randomized controlled trials),technological innovation,drug and device development,and post market evaluation.