ObjectiveTo analyze the adverse reactions associated with the clinical use of Banxia （Rhizoma Pinelliae）- Wutou （Aconitum） in the same formula， with the aim of providing a reference for the safety of their clinical application. MethodsLiterature on the clinical application of antagonistic herbs "Banxia-Wutou" used in the same formula， published from January 1st， 2014， to June 30th， 2023， was retrieved from databases including CNKI， VIP， Wanfang， SinoMed， PubMed， Cochrane Library， and Embase. A database was established， and information related to adverse reactions was extracted， including descriptions， classifications， specific manifestations， management and outcomes， patients' primary diseases （western medicine diseases and traditional Chinese medicine diagnoses and syndromes）， and medication information （dosage， ratio， administration routes， and dosage forms）. ResultsA total of 79 researches simultaneously used antagonistic herbs Banxia-Wutou in the same formula and reported associated advers reactions. Gastrointestinal adverse reactions were the most common， with 8 studies reporting management of adverse reactions and 3 studies reporting improvement with no intervention. Among the 11 researches， the adverse reaction relieved to extant， while other 69 researches didn't report the managment of adverse reaction and its prognosis. For the primary disease in western medicine system， chronic bronchitis and chronic obstructive pulmonary disease （COPD） were most common， while gastric pain was the most common symptom in traditional Chinese medicine with spleen and kidney deficiency and spleen stomach cold deficiency being the most frequent syndromes. The most common Banxia dosage was 10 g， while for the Wutou， Fuzi （Radix Aconiti Lateralis Praeparata） was predominant with the highest dose at 15 g. The most frequent herbal combination was Banxia-fuzi， with a 1∶1 ratio. The main administration route was oral， and the primary dosage form was decoction. ConclusionGastrointestinal adverse reactions are the most common in the clinical use of Banxia-Wutou antagonistic herb combinations. Research on the safety of "Banxia-Wutou" combinations should focus on respiratory system diseases and spleen-stomach related conditions.

PURPOSE: Septic shock is associated with high mortality and poor outcomes among sepsis patients with coagulopathy. Although traditional statistical methods or machine learning (ML) algorithms have been proposed to predict septic shock, these potential approaches have never been systematically compared. The present work aimed to develop and compare models to predict septic shock among patients with sepsis. METHODS: It is a retrospective cohort study based on 484 patients with sepsis who were admitted to our intensive care units between May 2018 and November 2022. Patients from the 908th Hospital of Chinese PLA Logistical Support Force and Nanchang Hongdu Hospital of Traditional Chinese Medicine were respectively allocated to training (n=311) and validation (n=173) sets. All clinical and laboratory data of sepsis patients characterized by comprehensive coagulation indexes were collected. We developed 5 models based on ML algorithms and 1 model based on a traditional statistical method to predict septic shock in the training cohort. The performance of all models was assessed using the area under the receiver operating characteristic curve and calibration plots. Decision curve analysis was used to evaluate the net benefit of the models. The validation set was applied to verify the predictive accuracy of the models. This study also used Shapley additive explanations method to assess variable importance and explain the prediction made by a ML algorithm. RESULTS: Among all patients, 37.2% experienced septic shock. The characteristic curves of the 6 models ranged from 0.833 to 0.962 and 0.630 to 0.744 in the training and validation sets, respectively. The model with the best prediction performance was based on the support vector machine (SVM) algorithm, which was constructed by age, tissue plasminogen activator-inhibitor complex, prothrombin time, international normalized ratio, white blood cells, and platelet counts. The SVM model showed good calibration and discrimination and a greater net benefit in decision curve analysis. CONCLUSION The SVM algorithm may be superior to other ML and traditional statistical algorithms for predicting septic shock. Physicians can better understand the reliability of the predictive model by Shapley additive explanations value analysis.
Humans ; Shock, Septic/blood* ; Machine Learning ; Male ; Female ; Retrospective Studies ; Middle Aged ; Aged ; Sepsis/complications* ; ROC Curve ; Cohort Studies ; Adult ; Intensive Care Units ; Algorithms ; Blood Coagulation ; Critical Illness

OBJECTIVE: To explore the accuracy of human-computer interaction software in identifying and locating type C1 distal radius fractures. METHODS: Based on relevant inclusion and exclusion criteria, 14 cases of type C1 distal radius fractures between September 2023 and March 2024 were retrospectively analyzed, comprising 3 males and 11 females(aged from 27 to 82 years). The data were assigned randomized identifiers. A senior orthopedic physician reviewed the films and measured the ulnar deviation angle, radial height, palmar inclination angle, intra-articular step, and intra-articular gap for each case on the hospital's imaging system. Based on the reduction standard for distal radius fractures, cases were divided into reduction group and non-reduction group. Then, the data were sequentially imported into a human-computer interaction intelligent software, where a junior orthopedic physician analyzed the same radiological parameters, categorized cases, and measured fracture details. The categorization results from the software were consistent with manual classifications (6 reduction cases and 8 non-reduction cases). For non-reduction cases, the software performed further analyses, including bone segmentation and fracture recognition, generating 8 diagnostic reports containing fracture recognition information. For the 6 reduction cases, the senior and junior orthopedic physicians independently analyzed the data on the hospital's imaging system and the AI software, respectively. Bone segments requiring reduction were identified, verified by two senior physicians, and measured for displacement and rotation along the X (inward and outward), Z (front and back), and Y (up and down) axes. The AI software generated comprehensive diagnostic reports for these cases, which included all measurements and fracture recognition details. RESULTS: Both the manual and AI software methods consistently categorized the 14 cases into 6 reduction and 8 non-reduction groups, with identical data distributions. A paired sample t-test revealed no statistically significant differences (P>0.05) between the manual and software-based measurements for ulnar deviation angle, radial ulnar bone height, palmar inclination angle, intra-articular step, and joint space. In fracture recognition, the AI software correctly identified 10 C-type fractures and 4 B-type fractures. For the 6 reduction cases, a total of 24 bone fragments were analyzed across both methods. After verification, it was found that the bone fragments identified by the two methods were consistent. A paired sample t-tests revealed that the identified bone fragments and measured displacement and rotation angles along the X, Y, and Z axes were consistent between the two methods. No statistically significant differences(P>0.05) were found between manual and software measurements for these parameters. CONCLUSION Human-computer interaction software employing AI technology demonstrated comparable accuracy to manual measurement in identifying and locating type C1 distal radius fractures on CT imaging.
Humans ; Male ; Female ; Radius Fractures/surgery* ; Middle Aged ; Adult ; Aged ; Aged, 80 and over ; Tomography, X-Ray Computed/methods* ; Retrospective Studies ; Software ; Wrist Fractures

Coronavirus disease 2019 (COVID-19) is an acute infectious respiratory disease that has been prevalent since December 2019. Chinese medicine (CM) has demonstrated its unique advantages in the fight against COVID-19 in the areas of disease prevention, improvement of clinical symptoms, and control of disease progression. This review summarized the relevant material components of CM in the treatment of COVID-19 by searching the relevant literature and reports on CM in the treatment of COVID-19 and combining with the physiological and pathological characteristics of the novel coronavirus. On the basis of sorting out experimental methods in vivo and in vitro, the mechanism of herb action was further clarified in terms of inhibiting virus invasion and replication and improving related complications. The aim of the article is to explore the strengths and characteristics of CM in the treatment of COVID-19, and to provide a basis for the research and scientific, standardized treatment of COVID-19 with CM.
Humans ; Drugs, Chinese Herbal/pharmacology* ; COVID-19 Drug Treatment ; SARS-CoV-2/drug effects* ; COVID-19/therapy* ; Medicine, Chinese Traditional/methods* ; Antiviral Agents/pharmacology* ; Animals

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Objective To investigate plasma protein expression changes in heatstroke patients using proteomics technology and to identify reliable prognostic biomarkers.Methods A retrospective analysis was conducted on 20 heatstroke patients hospitalized at the 908th Hospital of the Chinese PLA Joint Logistics Support Force from July 2022 to February 2024.Patients were divided into survival(n=16)and death groups(n=4)based on 28-day outcomes.Fasting venous blood samples were collected from both groups for proteomic analysis.Liquid chromatography-mass spectrometry(LC-MS/MS)was used to identify and screen differentially expressed proteins.Kyoto Encyclopedia of Genes and Genomes(KEGG)and Gene Ontology(GO)enrichment analyses were performed.LASSO regression was applied to screen key prognostic biomarkers,and receiver operating characteristic(ROC)curve analysis was used to evaluate their predictive value.Results A total of 27 upregulated and 90 downregulated proteins were identified between the two groups.These proteins were primarily involved in biological processes such as immune responses,complement activation,and metabolic processes.LASSO regression analysis indicated that actin-related protein 2(ARP2),cysteine-rich scavenger receptor type 1 M130(CD163),and catalase(CAT)could serve as effective biomarkers for evaluating heatstroke prognosis.ROC curve analysis demonstrated that ARP2 had higher diagnostic efficacy(AUC=0.98,sensitivity=0.80,specificity=1.00)compared to CD163(AUC=0.94,sensitivity=0.76,specificity=1.00),CAT(AUC=0.96,sensitivity=0.67,specificity=1.00),and acute physiology and chronic health evaluation Ⅱ(APACHE Ⅱ)score(AUC=0.79,sensitivity=0.44,specificity=1.00).Conclusion Elevated plasma ARP2 level has good clinical value for predicting poor prognosis in heatstroke patients.

Using the"structure-process-outcome-institution"framework,this article analyzes the conceptual connotation and manifestation of primary care resilience.The mechanism by which digital technologies embedding improve organizational resilience of primary healthcare institution was elucidated;From the resilience perspective,an action framework for reshaping the primary healthcare system by digital technologies was constructed.Research has found that:1)Organizational resilience is the core of primary healthcare resilience.2)Digital technologies mainly promote coupling coordination between resource and organization through promoting change perception,knowledge absorption,and knowledge integration,improve organizational resilience of primary healthcare institution.3)There is a bidirectional interaction between the improvement of organizational resilience and reshaping primary healthcare system;4)The relevant departments should unify instrumental rationality,institutional rationality,and value rationality to establish the embedding,governance,and evaluation framework for digital technologies to reshape the primary healthcare system.

Objective To investigate the role of high-mobility group AT-hook 2(HMGA2)in osteogenic differentiation of adipose-derived mesenchymal stem cells(ADSCs)and the effect of Hmga2 knockdown for promoting bone defect repair.Methods Bioinformatics studies using the GEO database and Rstudio software identified HMGA2 as a key factor in adipogenic-osteogenic differentiation balance of ADSCs.The protein-protein interaction network of HMGA2 in osteogenic differentiation was mapped using String and visualized with Cytoscape to predict the downstream targets of HMGA2.Primary mouse ADSCs(mADSCs)were transfected with Hmga2 siRNA,and the changes in osteogenic differentiation of the cells were evaluated using alkaline phosphatase staining and Alizarin red S staining.The expressions of osteogenic markers Runt-related transcription factor 2(RUNX2),osteopontin(OPN),and osteocalcein(OCN)in the transfected cells were detected using RT-qPCR and Western blotting.In a mouse model of critical-sized calvarial defects,mADSCs with Hmga2-knockdown were transplanted into the defect,and bone repair was evaluated 6 weeks later using micro-CT scanning and histological staining.Results GEO database analysis showed that HMGA2 expression was upregulated during adipogenic differentiation of ADSCs.Protein-protein interaction network analysis suggested that the potential HMGA2 targets in osteogenic differentiation of ADSCs included SMAD7,CDH1,CDH2,SNAI1,SMAD9,IGF2BP3,and ALDH1A1.In mADSCs,Hmga2 knockdown significantly upregulated the expressions of RUNX2,OPN,and OCN and increased cellular alkaline phosphatase activity and calcium deposition.In a critical-sized calvarial defect model,transplantation of mADSCs with Hmga2 knockdown significantly promoted new bone formation.Conclusion HMGA2 is a crucial regulator of osteogenic differentiation in ADSCs,and Hmga2 knockdown significantly promotes osteogenic differentiation of ADSCs and accelerates ADSCs-mediated bone defect repair in mice.

Objective To investigate the current situation and influencing factors of latent tuberculosis infection(LTBI)among close contacts of positive etiology pulmonary tuberculosis(PTB)patients,provide basis for formula-ting intervention measures for LTBI.Methods A multi-stage stratified cluster random sampling method was used to select close contacts of positive etiology PTB patients from 39 districts and counties in Chongqing City as the study objects.Demographic information was collected by questionnaire survey and the infection of Mycobacterium tuberculosis was detected by interferon gamma release assay(IGRA).The influencing factors of LTBI were analyzed by x2 test and binary logistic regression model.Results A total of 2 591 close contacts were included,the male to female ratio was 0.69∶1,with the mean age of(35.72±16.64)years.1 058 cases of LTBI were detected,Myco-bacterium tuberculosis latent infection rate was 40.83％.Univariate analysis showed that the infection rate was dif-ferent among peoples of different age,body mass index(BMI),occupation,education level,marital status,wheth-er they had chronic disease or major surgery history,whether they lived together with the indicator case,and whether the cumulative contact time with the indicator case ≥250 hours,difference were all statistically significant(all P＜0.05);infection rate presented increased trend with the increase of age and BMI(both P＜0.001),and decreased trend with the increase of education(P＜0.05).Logistic regression analysis showed that age 45-54 years old(OR=1.951,95％CI:1.031-3.693),age 55-64 years old(OR=2.473,95％CI:1.279-4.781),other occupations(OR=0.530,95％CI:0.292-0.964),teachers(OR=0.439,95％CI:0.242-0.794),students(OR=0.445,95％CI:0.233-0.851),junior high school education or below(OR=1.412,95％CI:1.025-1.944),BMI＜18.5 kg/m2(OR=0.762,95％CI:0.586-0.991),co-living with indicator cases(OR=1.621,95％CI1.316-1.997)and cumu-lative contact time with indicator cases ≥250 hours(OR=1.292,95％CI:1.083-1.540)were the influential fac-tors for LTBI(all P＜0.05).Conclusion The close contacts with positive etiology PTB have a high latent infection rate of Mycobacterium tuberculosis,and it is necessary to pay attention to close contacts of high age,farmers,and frequent contact with patients,and take timely targeted interventions to reduce the risk of occurrence of disease.

Objective:To understand the epidemiological characteristics of human respiratory syncytial virus (HRSV) among acute respiratory infection (ARI) cases in 16 provinces of China from 2009 to 2023.Methods:The data of this study were collected from the ARI surveillance data from 16 provinces in China from 2009 to 2023, with a total of 28 278 ARI cases included in the study. The clinical specimens from ARI cases were screened for HRSV nucleic acid from 2009 to 2023, and differences in virus detection rates among cases of different age groups, regions, and months were analyzed.Results:A total of 28 278 ARI cases were enrolled from January 2009 to September 2023. The age of the cases ranged from<1 month to 112 years, and the age M ( Q1, Q3) was 3 years (1 year, 9 years). Among them, 3 062 cases were positive for HRSV nucleic acid, with a total detection rate of 10.83%. From 2009 to 2019, the detection rate of HRSV was 9.33%, and the virus was mainly prevalent in winter and spring. During the Corona Virus Disease 2019 (COVID-19) pandemic, the detection rate of HRSV fluctuated between 6.32% and 18.67%. There was no traditional winter epidemic peak of HRSV from the end of 2022 to the beginning of 2023, and an anti-seasonal epidemic of HRSV occurred from April to May 2023. About 87.95% (2 693/3 062) of positive cases were children under 5 years old, and the difference in the detection rate of HRSV among different age groups was statistically significant ( P<0.001), showing a decreasing trend of HRSV detection rate with the increase of age ( P<0.001). Among them, the HRSV detection rate (25.69%) was highest in children under 6 months. Compared with 2009-2019, the ranking of HRSV detection rates in different age groups changed from high to low between 2020 and 2023, with the age M (Q1, Q3) of HRSV positive cases increasing from 1 year (6 months, 3 years) to 2 years (11 months, 3 years). Conclusion:Through 15 years of continuous HRSV surveillance analysis, children under 5 years old, especially infants under 6 months old, are the main high-risk population for HRSV infection. During the COVID-19 pandemic, the prevalence and patterns of HRSV in China have changed.