This study aimed to characterize and identify the non-volatile components in aqueous and ethanolic extracts of the stems and leaves of Rhododendron tomentosum by using sensitive and efficient ultra-performance liquid chromatography-quadrupole-time of flight mass spectrometry(UHPLC-Q-TOF-MS) combined with a self-built information database. By comparing with reference compounds, analyzing fragment ion information, searching relevant literature, and using a self-built information database, 118 compounds were identified from the aqueous and ethanolic extracts of R. tomentosum, including 35 flavonoid glycosides, 15 phenolic glycosides, 12 flavonoids, 7 phenolic acids, 7 phenylethanol glycosides, 6 tannins, 6 phospholipids, 5 coumarins, 5 monoterpene glycosides, 6 triterpenes, 3 fatty acids, and 11 other types of compounds. Among them, 102 compounds were reported in R. tomentosum for the first time, and 36 compounds were identified by comparing them with reference compounds. The chemical components in the ethanolic and aqueous extracts of R. tomentosum leaves and stems showed slight differences, with 84 common chemical components accounting for 71.2% of the total 118 compounds. This study systematically characterized and identified the non-volatile chemical components in the ethanolic and aqueous extracts of R. tomentosum for the first time. The findings provide a reference for active ingredient research, quality control, and product development of R. tomentosum.
Rhododendron/chemistry* ; Chromatography, High Pressure Liquid/methods* ; Drugs, Chinese Herbal/chemistry* ; Mass Spectrometry/methods* ; Plant Leaves/chemistry*

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OBJECTIVE: Baicalein has been reported to have wide therapeutic effects that act through its anti-inflammatory activity. This study examines the effect and mechanism of baicalein on sepsis-induced cardiomyopathy (SIC). METHODS: A thorough screening of a small library of natural products, comprising 100 diverse compounds, was conducted to identify the most effective drug against lipopolysaccharide (LPS)-treated H9C2 cardiomyocytes. The core target proteins and their associated signaling pathways involved in baicalein's efficacy against LPS-induced myocardial injury were predicted by network pharmacology. RESULTS: Baicalein was identified as the most potent protective agent in LPS-exposed H9C2 cardiomyocytes. It exhibited a dose-dependent inhibitory effect on cell injury and inflammation. In the LPS-induced septic mouse model, baicalein demonstrated a significant capacity to mitigate LPS-triggered myocardial deficits, inflammatory responses, and ferroptosis. Network pharmacological analysis and experimental confirmation suggested that hypoxia-inducible factor 1 subunit α (HIF1-α) is likely to be the crucial factor in mediating the impact of baicalein against LPS-induced myocardial ferroptosis and injury. By combining microRNA (miRNA) screening in LPS-treated myocardium with miRNA prediction targeting HIF1-α, we found that miR-299b-5p may serve as a regulator of HIF1-α. The reduction in miR-299b-5p levels in LPS-treated myocardium, compared to the control group, was reversed by baicalein treatment. The reverse transcription quantitative polymerase chain reaction, Western blotting, and dual-luciferase reporter gene analyses together identified HIF1-α as the target of miR-299b-5p in cardiomyocytes. CONCLUSION Baicalein mitigates SIC at the miRNA level, suggesting the therapeutic potential of it in treating SIC through the regulation of miR-299b-5p/HIF1-α/ferroptosis pathway. Please cite this article as: Zhou WY, Du JK, Liu HH, Deng L, Ma K, Xiao J, Zhang S, Wang CN. Baicalein attenuates lipopolysaccharide-induced myocardial injury by inhibiting ferroptosis via miR-299b-5p/HIF1-α pathway. J Integr Med. 2025; 23(5):560-575.
Flavanones/pharmacology* ; Animals ; MicroRNAs/genetics* ; Lipopolysaccharides ; Hypoxia-Inducible Factor 1, alpha Subunit/genetics* ; Ferroptosis/drug effects* ; Mice ; Myocytes, Cardiac/metabolism* ; Signal Transduction/drug effects* ; Rats ; Male ; Mice, Inbred C57BL ; Cardiomyopathies/etiology* ; Cell Line ; Sepsis/complications*

OBJECTIVE: This study aimed to explore the association between body mass index (BMI) and mortality based on the 10-year population-based multicenter prospective study. METHODS: A general population-based multicenter prospective study was conducted at four sites in rural China between 2013 and 2023. Multivariate Cox proportional hazards models and restricted cubic spline analyses were used to assess the association between BMI and mortality. Stratified analyses were performed based on the individual characteristics of the participants. RESULTS: Overall, 19,107 participants with a sum of 163,095 person-years were included and 1,910 participants died. The underweight (< 18.5 kg/m ²) presented an increase in all-cause mortality (adjusted hazards ratio [ aHR] = 2.00, 95% confidence interval [ CI]: 1.66-2.41), while overweight (≥ 24.0 to < 28.0 kg/m ²) and obesity (≥ 28.0 kg/m ²) presented a decrease with an aHR of 0.61 (95% CI: 0.52-0.73) and 0.51 (95% CI: 0.37-0.70), respectively. Overweight ( aHR = 0.76, 95% CI: 0.67-0.86) and mild obesity ( aHR = 0.72, 95% CI: 0.59-0.87) had a positive impact on mortality in people older than 60 years. All-cause mortality decreased rapidly until reaching a BMI of 25.7 kg/m ² ( aHR = 0.95, 95% CI: 0.92-0.98) and increased slightly above that value, indicating a U-shaped association. The beneficial impact of being overweight on mortality was robust in most subgroups and sensitivity analyses. CONCLUSION This study provides additional evidence that overweight and mild obesity may be inversely related to the risk of death in individuals older than 60 years. Therefore, it is essential to consider age differences when formulating health and weight management strategies.
Humans ; Body Mass Index ; China/epidemiology* ; Male ; Female ; Middle Aged ; Prospective Studies ; Rural Population/statistics & numerical data* ; Aged ; Follow-Up Studies ; Adult ; Mortality ; Cause of Death ; Obesity/mortality* ; Overweight/mortality*

Ankylosing spondylitis (AS) combined with lower cervical fracture is often categorized into unstable fracture, with a high incidence of neurological injury and a high rate of disability and morbidity. As factors such as shoulder occlusion may affect the accuracy of X-ray imaging diagnosis, it is often easily misdiagnosed at the primary diagnosis. Non-operative treatment has complications such as bone nonunion and the possibility of secondary neurological damage, while the timing, access and choice of surgical treatment are still controversial. Currently, there are no clinical practice guidelines for the treatment of AS combined with lower cervical fracture with or without dislocation. To this end, the Spinal Trauma Group of Orthopedics Branch of Chinese Medical Doctor Association organized experts to formulate Clinical guidelines for the treatment of ankylosing spondylitis combined with lower cervical fracture in adults ( version 2024) in accordance with the principles of evidence-based medicine, scientificity and practicality, in which 11 recommendations were put forward in terms of the diagnosis, imaging evaluation, typing and treatment, etc, to provide guidance for the diagnosis and treatment of AS combined with lower cervical fracture.

Deep vein thrombosis(DVT)is a common peripheral vascular disease in clinical practice.The lack of precise and efficient early diagnostic techniques renders it susceptible to being overlooked or misdiagnosed,and therefore,identifying trustworthy biomarkers is a major issue that has to be resolved.In this study,the endogenous metabolites in the urine of DVT rats were screened by metabolomics technology based on gas chromatograph-mass spectrometry(GC-MS)and the characteristic metabolites were identified by multiple feature selection algorithms and multivariate statistical analysis,for the development of a machine learning-based diagnostic model for DVT.The urine samples in metabolic cage in the thrombus development phase(between 48 and 72 h)of rats were collected,which was used as the models for inferior vena cava ligation.The metabolic profiles of the control group and DVT were obtained using the GC-MS method.A total of 176 kinds of endogenous metabolites were identified in rat urine through comparison with the FiehnLib database,26 kinds of differential metabolites associated with DVT were screened through a combination of the Mann-Whitney U test and orthogonal partial least squares discriminant analysis(OPLS-DA),and 13 kinds of significant metabolites strongly correlated with DVT were further evaluated in conjunction with various machine learning feature selection techniques.For DVT diagnosis,machine learning models such as Gaussian Naive Bayes(GNB),support vector machine(SVM),logistic regression(LR),and linear discriminant analysis(LDA)were developed.The diagnostic model constructed using 13 kinds of key metabolites demonstrated excellent accuracy and stability,and surpassed the predictive performance of the models utilizing 176 kinds of metabolites and 26 kinds of differential metabolites,as evidenced by examination and comparison of each model's efficacy.The study showed that the integration of multiple feature selection algorithms for analyzing metabolite information in DVT rat urine was capable of effectively identifying reliable potential markers of DVT.Furthermore,the developed machine learning model offered a novel technical approach for the automated diagnosis of DVT.

AIM:To investigate the mechanism of chronic stress-induced myocardial injury in atherosclerotic(AS)mice.METHODS:Eight-week-old SPF-grade male ApoE-/-mice and C57BL/6J mice used in this study.The mice received dietary intervention for 10 weeks followed by pathological examination to test the successful AS modeling.After AS establishment,the mice were exposed to chronic unpredictable mild stress(CUMS)for 6 weeks and then divided into five groups:control,CUMS,AS-regular diet(AS-r)+CUMS,AS-high-fat diet(AS-h),and AS-h+CUMS.During CUMS,open-field test and sucrose preference test were performed on mice in all groups.Blood lipids were characterized using an automatic biochemical analyzer.Hematoxylin-eosin(HE)and oil red O staining were performed to evaluate pathological changes in the aortic root.Cardiac function was assessed using echocardiography.The serum concentration of myocardial injury markers and ATP content was detected by ELISA.Transmission electron microscopy was employed to observe the ul-trastructure of myocardial mitochondria.Myocardial mitochondrial oxygen consumption rate was determined using the Oxy-graph-2k high-resolution respiratory energy metabolism analyzer.Western blot was conducted to quantify the expression of B-cell lymphoma-2(Bcl-2),Bcl-2-associated X protein(Bax),and cleaved caspase-3.RESULTS:compared with the Control group,the total distance traveled,the number of entries into the central area,and the sucrose preference rate were significantly decreased in all CUMS groups(P<0.05).All AS groups exhibited varying levels of lipid deposition and endo-thelial damage in the aortic root,along with a significant reduction in cardiac function(P<0.05)and varying degrees of myocardial injury(P<0.05).In the AS-h+CUMS and AS-r+CUMS groups,myocardial mitochondrial structure was signifi-cantly disrupted.ATP content was significantly reduced(P<0.05),and the rates of oxygen consumption associated with mitochondrial respiratory chain complex I,mitochondrial respiratory chain complexes I+II,and the maximum respiratory capacity of the electron transport system were all significantly decreased(P<0.05).Moreover,the protein levels of Bax and cleaved caspase-3 were significantly increased(P<0.05),while that of Bcl-2 protein was significantly decreased(P<0.05).CONCLUSION:Chronic stress triggers mitochondrial non-steady-state load by disrupting myocardial structure and energy metabolism in AS mice,promoting myocardial cell apoptosis and myocardial injury.

Objective To investigate the clinical characteristics and prognosis of pneumococcal meningitis(PM),and drug sensitivity of Streptococcus pneumoniae(SP)isolates in Chinese children.Methods A retrospective analysis was conducted on clinical information,laboratory data,and microbiological data of 160 hospitalized children under 15 years old with PM from January 2019 to December 2020 in 33 tertiary hospitals across the country.Results Among the 160 children with PM,there were 103 males and 57 females.The age ranged from 15 days to 15 years,with 109 cases(68.1% )aged 3 months to under 3 years.SP strains were isolated from 95 cases(59.4% )in cerebrospinal fluid cultures and from 57 cases(35.6% )in blood cultures.The positive rates of SP detection by cerebrospinal fluid metagenomic next-generation sequencing and cerebrospinal fluid SP antigen testing were 40% (35/87)and 27% (21/78),respectively.Fifty-five cases(34.4% )had one or more risk factors for purulent meningitis,113 cases(70.6% )had one or more extra-cranial infectious foci,and 18 cases(11.3% )had underlying diseases.The most common clinical symptoms were fever(147 cases,91.9% ),followed by lethargy(98 cases,61.3% )and vomiting(61 cases,38.1% ).Sixty-nine cases(43.1% )experienced intracranial complications during hospitalization,with subdural effusion and/or empyema being the most common complication[43 cases(26.9% )],followed by hydrocephalus in 24 cases(15.0% ),brain abscess in 23 cases(14.4% ),and cerebral hemorrhage in 8 cases(5.0% ).Subdural effusion and/or empyema and hydrocephalus mainly occurred in children under 1 year old,with rates of 91% (39/43)and 83% (20/24),respectively.SP strains exhibited complete sensitivity to vancomycin(100% ,75/75),linezolid(100% ,56/56),and meropenem(100% ,6/6).High sensitivity rates were also observed for levofloxacin(81% ,22/27),moxifloxacin(82% ,14/17),rifampicin(96% ,25/26),and chloramphenicol(91% ,21/23).However,low sensitivity rates were found for penicillin(16% ,11/68)and clindamycin(6% ,1/17),and SP strains were completely resistant to erythromycin(100% ,31/31).The rates of discharge with cure and improvement were 22.5% (36/160)and 66.2% (106/160),respectively,while 18 cases(11.3% )had adverse outcomes.Conclusions Pediatric PM is more common in children aged 3 months to under 3 years.Intracranial complications are more frequently observed in children under 1 year old.Fever is the most common clinical manifestation of PM,and subdural effusion/emphysema and hydrocephalus are the most frequent complications.Non-culture detection methods for cerebrospinal fluid can improve pathogen detection rates.Adverse outcomes can be noted in more than 10% of PM cases.SP strains are high sensitivity to vancomycin,linezolid,meropenem,levofloxacin,moxifloxacin,rifampicin,and chloramphenicol.[Chinese Journal of Contemporary Pediatrics,2024,26(2):131-138]

Objective To investigate factors influencing the occurrence of early haematoma expansion(HE)in patients with spontaneous intracerebral hemorrhage(sICH),to develop a predictive model and evaluate its predictive efficacy.Methods A retrospective cohort of 238 patients with sICH,admitted to General Hospital of Western Theater Command between January 2017 and December 2022,was analyzed.Patients were categorized into two groups based on the criteria of HE exceeding 33%in relative volume or 6 ml in absolute volume:HE group(n=62)and non-haematoma expansion(NHE)group(n=176).Clinical characteristics,laboratory findings,Non-contrast Computed Tomography(NCCT)imaging,and Glasgow Coma Scale(GCS)scores were compared between the two groups.Multifactorial logistic regression analysis was employed to identify risk factors for HE and to model the probability of its occurrence.The R language rms package was utilized to construct a nomogram model for predicting HE in sICH patients,Additionally,the related clinical,NCCT,and GCS models were constructed.The predictive efficacy of each model for HE in sICH patients was evaluated using area under Receive Operative Characteristic(ROC)curve(AUC),and the clinical application value of each model was assessed using accuracy,sensitivity,specificity,and Jordon's index.The Delong test was applied to analyze differences in the predictive values of the models.Results Significant differences in satellite sign,vortex sign,and history of anticoagulant treatment were observed between two groups(P<0.05).Multifactorial logistic regression analysis revealed independent risk factors for HE in sICH patients,including the first CT examination time,homogeneity,history of anticoagulant medication,volume,maximal diameter,hypodensity sign,island sign,satellite sign,and vortex sign(P<0.05).The AUCs for the constructed clinical model,NCCT model,GCS model and nomogram model in predicting the occurrence of HE in sICH patients were 0.672,0.706,0.518 and 0.754,respectively.The nomogram model demonstrated higher accuracy,sensitivity,Jordon's index and AUC compared with those in the clinical and NCTT models.Conclusions The first CT examination time,homogeneity,history of anticoagulant treatment,volume,maximum diameter,hypodensity sign,island sign,satellite sign,and vortex sign are independent predictors of early HE in sICH patients.The nomogram model,constructed with the above parameters,demonstrated high predictive efficacy for HE and holds potential for clinical application.

Objective To explore the influential factors and predictive value of early femoral head collapse progression following allogeneic fibula grafting(AFG)surgery.Methods Clinical and radiological data of 68 patients(75 hips)with osteonecrosis of the femoral head(ONFH)who underwent AFG between January 2008 and December 2022 at the Orthopedics and Traumatology Department,Affiliated Hospital of Nanjing University of Chinese Medicine were retrospectively analyzed.Seventy-five hips were divided into stable(n=40)and progressive(n=35)groups based on the presence or absence of postoperative collapse progression.Age,gender,etiology,location of the lesion,Association Research Circulation Osseous(ARCO)stage,Japanese Committee of Osteonecrosis Investigation(JIC)classification,China-Japan Friendship Hospital(CJFH)classification,and Hounsfield units(HU)value of anterolateral sclerosis rim(ⅠSHU)were collected.Univariate and multivariate logistic regression analyses were used to identify the factors influencing early collapse progression after AFG.Receiver operating characteristic(ROC)curve was used to analyze the predictive value of the identified factors influencing postoperative early collapse progression.Results Of the 75 hips,35(46.7%)had postoperative collapse progression.Univariate logistic regression analysis showed that age,ARCO stage,JIC classification,and ⅠSHU were in fluencing factors for early femoral head collapse progression after AFG(P<0.05).Multivariate logistic regression analysis showed that ARCO stage ⅢA and JIC classification C2 were independent risk factors for early femoral head collapse progression after AFG,while ⅠSHU was identified as an independent protective factor(P<0.05).The ROC curve analysis showed that the sensitivities of ARCO stage,JIC classification,ⅠSHU,and the combined predictive model were 0.850,0.725,0.800,and 0.775,the specificities were 0.486,0.657,0.743,and 0.914,and the area under the ROC curve(AUC)were 0.668,0.725,0.811,and 0.896,respectively.Conclusions ⅠSHU is associated with early collapse progression after AFG in patients with ONFH.ARCO stage ⅢA,JIC classification C2,and ⅠSHU are independent factors influencing postoperative early collapse progression and have a certain predictive value.