ObjectiveThis study aimed to establish a monocrotaline （MCT）-induced pulmonary arterial hypertension （PAH） rat model to systematically evaluate the protective effect of Xiao Qinglongtang （XQLT） on right cardiac function in model rats and further elucidate the underlying regulatory mechanism. MethodsSixty male SD rats were randomly assigned to the normal group， model group， XQLT low-， medium-， and high-dose groups （XQLT-L/M/H）， and the beraprost sodium tablet group （BST）. Except for the normal group， rats in all other groups were given a single subcutaneous injection of MCT （60 mg·kg^-1） to induce PAH. Three weeks after injection， rats in the XQLT-L/M/H groups were administered XQLT intragastrically at 3.07， 6.14， 12.28 g·kg^-1·d^-1， respectively. Rats in the BST group received beraprost sodium at 12.6 μg·kg^-1·d^-1， and rats in the model group received an equal volume of saline. All treatments lasted for 3 weeks. Right ventricular systolic pressure （RVSP） was measured by right ventricular catheterization. Cardiac function was assessed by echocardiography. The right ventricle was weighed to calculate the right ventricular hypertrophy index （RVHI）. Hematoxylin-eosin （HE） staining， Masson staining， and transmission electron microscopy were used to observe myocardial morphology. Serum metabolomic changes were analyzed using ultra-performance liquid chromatography-tandem mass spectrometry （UPLC-MS/MS）. Data-independent acquisition （DIA） proteomics was used to detect differentially expressed （DE） proteins in the right ventricle， and Western blot was used to measure the expression of uncoupling protein 3 （UCP3）， phosphatidylinositol 3-kinase catalytic subunit p110α （PIK3CA）， L1 cell adhesion molecule （L1CAM）， and quinone oxidoreductase （CRYZ）. UPLC-MS/MS was used to analyze the chemical components of XQLT. ResultsCompared with the normal group， the model group showed significantly increased RVSP and RVHI （P<0.05）， along with pathological changes in myocardial morphology. Compared with the model group， all XQLT-treated groups exhibited reductions in RVSP and RVHI as well as significant improvements in cardiac function and myocardial morphology. Among the XQLT groups， XQLT-M showed the most pronounced effects （P<0.05）， comparable to the BST group. Serum metabolomics revealed 105 differential metabolites in the XQLT groups versus the model group ［variable importance in projection （VIP） >1， P<0.05］， including 58 upregulated and 47 downregulated metabolites. KEGG enrichment analysis indicated that XQLT intervention downregulated phenylalanine metabolism （P<0.01） and upregulated unsaturated fatty acid biosynthesis （P<0.05）. Proteomics analysis showed that 982 DE proteins were identified in the MCT groups versus the normal group， including 455 upregulated and 527 downregulated proteins （|fold change （FC）| >1.3， P<0.05）. Compared with the model group， 237 DE proteins were identified in the XQLT groups， including 124 upregulated and 113 downregulated proteins （|FC| >1.3， P<0.05）， with 57 overlapping DE proteins. KEGG enrichment suggested that XQLT mainly modulated pathways related to mineral absorption， ribosomal biogenesis， peroxisomes， glycolysis/gluconeogenesis， spliceosomes， and thyroid hormone signaling. Western blot analysis showed that， compared with the model group， XQLT increased the expression of UCP3， PIK3CA， and L1CAM， while decreasing the expression of CRYZ （P<0.05）. ConclusionXQLT exerts a protective effect on right heart function in MCT-induced PAH rats， and its mechanism is associated with maintaining myocardial homeostasis and alleviating right ventricular remodeling.

Childhood simple obesity has become a significant public health issue in China. Modern medicine primarily relies on lifestyle interventions and often suffers from poor long-term compliance， while pharmacological options are limited and associated with potential adverse effects. Traditional Chinese Medicine （TCM） has a long history in the prevention and management of this condition， demonstrating eight distinct advantages， including systematic theoretical foundation， diversified therapeutic approaches， definite therapeutic efficacy， high safety profile， good patient compliance， comprehensive intervention strategies， emphasis on prevention， and stepwise treatment protocols. Additionally， TCM is characterized by six distinctive features： the use of natural medicinal substances， non-invasive external therapies， integration of medicinal dietetics， simple exercise regimens， precise syndrome differentiation， and diverse dosage forms. By combining internal and external treatments， TCM facilitates individualized regimen adjustment and holistic regulation， demonstrating remarkable effects in improving obesity-related metabolic indicators， regulating constitutional imbalance， and promoting healthy behaviors. However， challenges remain， such as inconsistent operational standards， insufficient high-quality clinical evidence， and a gap between basic research and clinical application. Future efforts should focus on accelerating the standardization of TCM diagnosis and treatment， conducting multicenter randomized controlled trials， and fostering interdisciplinary integration， so as to enhance the scientific validity and international recognition of TCM in the prevention and treatment of childhood obesity.

OBJECTIVE:Nowadays,machine learning algorithms are gradually being applied to predict stroke and cardiovascular disease.Compared with traditional regression models,machine learning can learn from data to achieve high prediction accuracy by exploring the flexible relationship between a large number of predictive features and outcome variables,providing a new method for the formulation of individualized treatment and rehabilitation programs.This study aims to systematically evaluate stroke functional recovery and prognosis prediction models based on machine learning,comprehensively assessing their predictive performance and clinical application potential to provide references for the development,application,and promotion of related predictive models.METHODS:This review was conducted following the PRISMA(Preferred Reporting Items for Systematic Reviews and Meta-Analyses)guidelines.Relevant literature on stroke prognosis prediction using machine learning methods was selected by searching PubMed,EMbase,Web of Science Core Collection,CNKI,WanFang,and the China Biomedical Literature Database,with the search period from January 1,2014,to July 1,2024.Two researchers independently screened the literature and extracted data based on inclusion and exclusion criteria,using the Prediction model Risk Of Bias ASsessment Tool(PROBAST)to assess model quality.RESULTS:(1)A total of 3 126 articles were obtained in the preliminary search.After screening and exclusion,18 articles were finally included.150 prediction models were constructed using 13 machine learning methods.The three most frequently used methods are Logistic Regression,Random Forest,and Extreme Gradient Boosting(XGBoost).Only one study was externally validated.Eight studies reported how the missing data were handled.(2)In terms of outcome indicators,8 studies used the combination of clinical data and imaging data to build models,9 studies only used clinical data to build models,and 1 study only used imaging data to build models.(3)Each of the 18 studies gave the most important characteristics of the study,with the most mentioned being the National Institute of Health Stroke Scale and age.All studies reported area under curve values ranging from 0.74 to 0.96,with the highest area under curve being 0.96.The overall risk of bias in all models was high.The high risk of bias in the field of model analysis was the main reason for the high risk of overall bias in all models.(4)The results of meta-analysis showed that age and National Institute of Health Stroke Scale score had significant influence on stroke prognosis,with age[MD=8.49,95％CI(6.24,10.75),P＜0.01]and National Institute of Health Stroke Scale score[MD=4.78,95％CI(2.56,7.00),P＜0.01].CONCLUSION:This study systematically evaluated the predictive model of functional recovery and prognosis of stroke based on machine learning,and all the models have good predictive potential.However,future studies should increase the sample size of the included model,adopt prospective studies,and add external validation of the model to improve the stability and prediction accuracy of the model,control the risk of bias,and contribute to the validation and promotion of the model in practical clinical applications.At the same time,the interpolation of missing values is more transparent and accurate.Although existing machine learning models show good predictive performance,it is also important to focus on the functionality and usability of the model,and the inclusion of features will reduce ease of use.We should develop easy to use model interfaces and user-friendly clinical tools to enable medical staff to better apply the model for clinical decision.

Objective To investigate the clinicopathological parameters and risk factors of the patients with connective tissue disease-associated interstitial lung disease(CTD-ILD)complicated with Epstein-Barr virus(EBV)viraemia.Methods The CTD-ILD pa-tients admitted to Department of Respiratory and Critical Care Medicine,Nanjing Drum Tower Hospital from January 2023 to April 2024 were collected.Based on the detection results of EBV DNA,the patients were divided into the EBV DNA(+)group and EBV DNA(-)group.The clinicopathological parameters of the two groups were analyzed.Results Out of 162 CTD-ILD patients who underwent EBV DNA testing,a total of 28 were found to have EBV viraemia.The levels of serum albumin([32.7±4.1]g/L vs[34.8±3.8]g/L,t=2.559,P＜0.05),oxygenation index([268.5±94.0]mmHg vs[323.2±120.9]mmHg,t=2.062,P＜0.05),and percentages of predicted diffusing capacity for carbon monoxide([30.9±15.3]% vs[44.9±18.8]%,t=2.127,P＜0.05])in the EBV DNA(+)group were significantly lower than those in the EBV DNA(-)group,while the levels of lactate dehydrogenase(LDH,[369.1±206.2]U/L vs[298.8±128.7]U/L,t=2.335,P＜0.05)were significantly higher than that in the EBV DNA(-)group.The acute exacerbation of ILD in the EBV DNA(+)group was more common than that in the EBV DNA(-)group(P＜0.05).Multivariate Lo-gistic analysis showed that honeycombing and low oxygenation index were independent risk factors of CTD-ILD patients complicated with EBV viraemia.Conclusion The CTD-ILD patients complicated with EBV viraemia have poorer oxygenation and are more prone to suf-fer from acute exacerbation of ILD.Honeycombing in chest HRCT and low oxygenation index are independent risk factors of CTD-ILD patients complicated with EBV viraemia.

This study was aimed at determining the molecular characteristics of Yersinia pestis in the natural plague foci around Qinghai Lake through single nucleotide polymorphism technology,to lay a foundation for molecular epidemiological and source-tracing analysis of Y.pestis in this area.Using the whole genome sequencing technology,we obtained the whole genome sequences of 84 representative Y.pestis strains.Using the sequences of Y.pestis and Yersinia pseudotuberculosis IP32953 from the NCBI database as references,we compared and analyzed the 2 298 SNP loci of these strains.From 1957 to 2020,84 representative strains of Y.pestis from the natural plague foci around Qinghai Lake were divided into two clades:1.IN2 and 3.ANT1.The 1.IN2 clade was the characteristic population of Y.pestis throughout all epidemic years in this area.Additionally,analysis of the SNP distribution and hosts in the region indicated that the 1.IN2 clade was located in five counties except Wulan,whereas the 3.ANT1 clade was isolated from Himalayan marmot and dog in two counties.In conclusion,the population structure of SNP of Y.pestis in the natural plague foci around Qinghai Lake is relatively simple,and SNP analysis of Y.pestis provided a scientific basis for tracing plague epidemic sources and formulating plague prevention and control measures in this area.

AIM To study the chemical constituents from Tylophora ovata(Lindl.)Hook.ex Steud.and their antibacterial activities.METHODS Ethanol extract was isolated and purified by MCI,silica gel,Sephadex LH-20 and semi-preparative HPLC,then the structures of obtained compounds were identified by spectral data.The inhibitory activities of each compound against Phomopsis sp.were determined by mycelial growth rate method.RESULTS Twenty-six compounds were identified as paeonol(1),stigmast-4-en-3-one(2),ergosta-4,6,8(14),22-tetraen-3-one(3),2,4-methoxyphenol(4),1,2,4-trimethoxybenzene(5),3-methoxyphenol(6),3,4-dimethoxyacetophenone(7),5α,8α-epidioxy-ergosta-6,22(E)-diene-3β-ol(8),kaempferol 3-O-β-D-galactopyranoside(9),glaucogenind C(10),glaucoge-nin A 3-O-β-D-cymaropyranoside(11),dibutyl phthalate(12),cynatratoside A(13),hirundigoside C(14),sublanceoside B2(15),cynanoside A(16),dipentyl phthalate(17),5-hydroxymethyl-2-furancarboxaldehyde(18),bis-(2-ethyl)hexylphthalate(19),p-hydroxybenzoic acid(20),syringic acid(21),β-hydroxypropiovanillone(22),3-hydroxy-l-(4-hydroxy-3,5-dimethoxyphenyl)-1-propanone(23),(+)-syringare sinol(24),(-)-syringare sinol(25),(+)-medioresinol(26).IC50 value of compound 12 was 37.27 μg/mL.CONCLUSION Compounds 1-26 are isolated from this plant for the first time.Compound 12 has inhibitory activity against Phomopsis sp.

This study was aimed at determining the molecular characteristics of Yersinia pestis in the natural plague foci around Qinghai Lake through single nucleotide polymorphism technology,to lay a foundation for molecular epidemiological and source-tracing analysis of Y.pestis in this area.Using the whole genome sequencing technology,we obtained the whole genome sequences of 84 representative Y.pestis strains.Using the sequences of Y.pestis and Yersinia pseudotuberculosis IP32953 from the NCBI database as references,we compared and analyzed the 2 298 SNP loci of these strains.From 1957 to 2020,84 representative strains of Y.pestis from the natural plague foci around Qinghai Lake were divided into two clades:1.IN2 and 3.ANT1.The 1.IN2 clade was the characteristic population of Y.pestis throughout all epidemic years in this area.Additionally,analysis of the SNP distribution and hosts in the region indicated that the 1.IN2 clade was located in five counties except Wulan,whereas the 3.ANT1 clade was isolated from Himalayan marmot and dog in two counties.In conclusion,the population structure of SNP of Y.pestis in the natural plague foci around Qinghai Lake is relatively simple,and SNP analysis of Y.pestis provided a scientific basis for tracing plague epidemic sources and formulating plague prevention and control measures in this area.

Neuropathic pain, often featuring allodynia, imposes significant physical and psychological burdens on patients, with limited treatments due to unclear central mechanisms. Addressing this challenge remains a crucial unsolved issue in pain medicine. Our previous study, using protein kinase C gamma (PKCγ)-tdTomato mice, highlights the spinal feedforward inhibitory circuit involving PKCγ neurons in gating neuropathic allodynia. However, the regulatory mechanisms governing this circuit necessitate further elucidation. We used diverse transgenic mice and advanced techniques to uncover the regulatory role of the descending serotonin (5-HT) facilitation system on spinal PKCγ neurons. Our findings revealed that 5-HT neurons from the rostral ventromedial medulla hyperpolarize spinal inhibitory interneurons via 5-HT_2C receptors, disinhibiting the feedforward inhibitory circuit involving PKCγ neurons and exacerbating allodynia. Inhibiting spinal 5-HT_2C receptors restored the feedforward inhibitory circuit, effectively preventing neuropathic allodynia. These insights offer promising therapeutic targets for neuropathic allodynia management, emphasizing the potential of spinal 5-HT_2C receptors as a novel avenue for intervention.
Animals ; Neuralgia/physiopathology* ; Protein Kinase C/metabolism* ; Receptor, Serotonin, 5-HT2C/metabolism* ; Hyperalgesia/physiopathology* ; Mice, Transgenic ; Mice ; Spinal Cord/metabolism* ; Serotonin/metabolism* ; Male ; Neurons/metabolism* ; Mice, Inbred C57BL

This study aimed to investigate the underlying mechanisms of Duhuo Jisheng Decoction(DJD) in the prevention and treatment of knee osteoarthritis(KOA). Forty SPF New Zealand rabbits were randomly divided using SPSS 26.0 software into five groups: blank group, model group, low-dose DJD group, high-dose DJD group, and high-dose DJD+phosphatidylinositol 3-kinase(PI3K)/protein kinase B(Akt)/mammalian target of rapamycin(mTOR) signaling pathway activator group(high-dose DJD+740Y-P group), with eight rabbits in each group. Except for the blank group, the KOA model was established in the other groups using papain injection into the knee joint cavity combined with forced flexion of the knee joint. The day after modeling, the blank group and model group were given normal saline at 10 mL·kg~(-1) by gavage, the low-dose DJD group received DJD at 8.8 g·kg~(-1) by gavage, the high-dose DJD group received DJD at 35.2 g·kg~(-1) by gavage, and the high-dose DJD+740Y-P group received DJD at 35.2 g·kg~(-1) by gavage along with 740Y-P at 0.15 μmoL·kg~(-1) injected via the auricular vein. All groups received treatment continuously for four weeks. After modeling and intervention, behavioral observations were performed for all groups, and after the intervention, imaging assessments of the knee joints were conducted. Cartilage from the knee joints was collected, and gross morphological changes were observed. Pathological changes in cartilage tissue were examined using hematoxylin-eosin(HE) staining. The results of these observations were quantitatively evaluated using the Lequesne MG score, Kellgren-Lawrence(K-L) grading, Pelletier score, and Mankin score. ELISA was used to measure the levels of interleukin-1β(IL-1β), interleukin-18(IL-18), and matrix metalloproteinase 13(MMP13) in cartilage tissue. Real-time RT-PCR was used to detect the mRNA expression levels of PI3K, Akt, mTOR, Nod-like receptor protein 3(NLRP3), cysteine protease 1(caspase-1), and gasdermin D(GSDMD) in cartilage tissue. Western blot was employed to measure the protein expression levels of PI3K, Akt, mTOR, NLRP3, caspase-1, and GSDMD. The results showed that compared with the blank group, the model group exhibited significant knee joint degeneration, increased Lequesne MG score, K-L grading, Pelletier score, and Mankin score, elevated levels of IL-1β, IL-18, and MMP13 in cartilage tissue, activation of PI3K, Akt, and mTOR phosphorylation along with increased mRNA expression levels, and elevated protein and mRNA expression levels of NLRP3, caspase-1, and GSDMD. Compared with the model group, these indicators were reversed in both the low-dose and high-dose DJD groups, with the high-dose group showing greater decline degree than the low-dose DJD group. However, compared with the high-dose DJD group, the improvements in knee joint degeneration were less pronounced in the high-dose DJD+740Y-P group, with increased Lequesne MG score, K-L grading, Pelletier score, Mankin score, elevated levels of IL-1β, IL-18, and MMP13, activation of PI3K, Akt, and mTOR phosphorylation along with increased mRNA expression, and increased protein and mRNA expression levels of NLRP3, caspase-1, and GSDMD. In conclusion, DJD is effective and safe in the treatment of KOA, and its mechanism may be related to the inhibition of PI3K/Akt/mTOR signaling pathway-mediated pyroptosis in cartilage tissue, thereby improving knee joint bone structure, reducing the inflammatory response, and preventing cartilage matrix degradation.
Animals ; Drugs, Chinese Herbal/administration & dosage* ; Rabbits ; TOR Serine-Threonine Kinases/genetics* ; Osteoarthritis, Knee/genetics* ; Proto-Oncogene Proteins c-akt/genetics* ; Signal Transduction/drug effects* ; Male ; Disease Models, Animal ; Pyroptosis/drug effects* ; Phosphatidylinositol 3-Kinases/genetics* ; Humans ; Female