The general models for intermediates quality analysis in the production process of Yaobitong capsule were established by near infrared spectroscopy (NIRS) combined with chemometrics, realizing the rapid determination of notoginsenoside R1, ginsenoside Rg1, ginsenoside Re, ginsenoside Rb1, ginsenoside Rd and moisture. The spray-dried fine powder and total mixed granule were selected as research objects. The contents of five saponins were determined by high performance liquid chromatography and the moisture content was determined by drying method. The measured contents were used as reference values. Meanwhile, NIR spectra were collected. After removing abnormal samples by Monte Carlo cross validation (MCCV), Monte Carlo uninformative variables elimination (MC-UVE) and competitive adaptive reweighted sampling (CARS) were used to select feature variables respectively. Based on the feature variables, quantitative models were established by partial least squares regression (PLSR), extreme learning machine (ELM) and ant lion optimization least squares support vector machine (ALO-LSSVM). The results showed that CARS-ALO-LSSVM model had the optimum effect. The correlation coefficients of the six index components were greater than 0.93, and the relative standard errors were controlled within 6%. ALO-LSSVM was more suitable for a large number of samples with rich information, and the prediction effect and stability of the model were significantly improved. The general models with good predicting effect can be used for the rapid quality determination of Yaobitong capsule intermediates.

Objective To predict the lymph node metastasis status of patients with invasive pulmonary adenocarcinoma by constructing machine learning models based on primary tumor radiomics, peritumoral radiomics, and habitat radiomics, and to evaluate the predictive performance and generalization ability of different imaging features. Methods A retrospective analysis was performed on the clinical data of 1 263 patients with invasive pulmonary adenocarcinoma who underwent surgery at the Department of Thoracic Surgery, Jiangsu Province Hospital, from 2016 to 2019. Habitat regions were delineated by applying K-means clustering (average cluster number of 2) to the grayscale values of CT images. The peritumoral region was defined as a uniformly expanded area of 3 mm around the primary tumor. The primary tumor region was automatically segmented using V-net combined with manual correction and annotation. Subsequently, radiomics features were extracted based on these regions, and stacked machine learning models were constructed. Model performance was evaluated on the training, testing, and internal validation sets using the area under the receiver operating characteristic curve (AUC), F1 score, recall, and precision. Results After excluding patients who did not meet the screening criteria, a total of 651 patients were included. The training set consisted of 468 patients (181 males, 287 females) with an average age of (58.39±11.23) years, ranging from 29 to 78 years, the testing set included 140 patients (56 males, 84 females) with an average age of (58.81±10.70) years, ranging from 34 to 82 years, and the internal validation set comprised 43 patients (14 males, 29 females) with an average age of (60.16±10.68) years, ranging from 29 to 78 years. Although the habitat radiomics model did not show the optimal performance in the training set, it exhibited superior performance in the internal validation set, with an AUC of 0.952 [95%CI (0.87, 1.00)], an F1 score of 84.62%, and a precision-recall AUC of 0.892, outperforming the models based on the primary tumor and peritumoral regions. Conclusion The model constructed based on habitat radiomics demonstrated superior performance in the internal validation set, suggesting its potential for better generalization ability and clinical application in predicting lymph node metastasis status in pulmonary adenocarcinoma.

Peroxisome proliferator-activated receptor gamma(PPAR-γ)is a member of the ligand-activated nuclear tran-scription factor superfamily.Activated PPAR-γ is involved in the regulation of many central nervous system(CNS)events,and is involved in cholesterol metabolism by inducing or inhibi-ting a series of gene pathways,thereby inhibiting the deposition of β-amyloid protein(Aβ).It plays an important neuroprotec-tive role in Alzheimer's disease(AD),improves memory and cognition in AD,and is a potential target for AD.Drug develop-ment aimed at restoring cholesterol homeostasis may be a poten-tial strategy to counteract AD.By analyzing the distribution and structure of PPAR-γ,focusing on the biological correlation be-tween PPAR-γ-mediated cholesterol metabolism and AD,this paper describes the mechanism regulation of PPAR-γ on key proteins,genes and their corresponding molecules,providing a new reference for the treatment of AD.

Aim To explore the potential genes and mechanism of alisol B in the treatment of non-small cell lung cancer(NSCLC).Methods The proliferation and migration of NSCLC cells were detected by CCK-8 and Transwell.Genes of NSCLC and alisol B were col-lected through TCGA and compound gene prediction database,and their intersection genes were obtained.The network of protein-protein interaction(PPI)was constructed by using String database,and the top 20 key nodes were screened out,and the prognosis-related proteins related to the prognosis of NSCLC were screened out by using R language,and the intersection of them was obtained.The potential mechanism of ali-sol B on NSCLC was explored by KEGG and GO en-richment analysis and the relationship between related genes and immune cells,which was verified by cell-lev-el experiments.Results Alisol B inhibited the cell activity and migration ability of NSCLC cells.Five im-portant genes were identified by network pharmacologi-cal analysis:CCNE1,CDK1,COL1A1,COL1A2 and COL3A1.The results of cell experiment showed that al-isol B down-regulated the expression of Cyclin E1,CDK1 and COL1A2 in NSCLC cells.In addition,alisol B could inhibit the expression of COL1A2 and M2 macrophage marker CD206 in macrophages.Conclu-sions Alisol B may inhibit the proliferation of tumor cells by down-regulating CDK1 and Cyclin E1,and may affect the function of macrophages by inhibiting COL1A2,thus regulating the tumor immune microenvi-ronment and inhibiting NSCLC.

Objective To analyze the factors affecting the prognosis of patients with knee osteoarthritis,and to construct a nomogram prediction model in conjunction with multi-dimensional clinical indicators.Methods The clinical data of 234 pa-tients with knee osteoarthritis who were treated in our hospital from January 2015 to June 2021 were retrospectively analyzed,including 126 males and 108 females;age more than 60 years old for 135 cases,age less than 60 years old for 99 cases.Lysholm knee function score was used to evaluate the prognosis of the patients,and the patients were divided into good progno-sis group for 155 patients and poor prognosis group for 79 patients according to the prognosis.The clinical data of the subjects in the experimental cohort were analyzed by single factor and multiple factors.The patients were divided into experimental co-hort and verification cohort,the results of the multiple factor analysis were visualized to obtain a nomogram prediction model,the receiver operating characteristic curve(ROC),calibration curve and decision curve were used to evaluate the model's dis-crimination,accuracy and clinical benefit rate.Results The results of multivariate analysis showed that smoking,pre-treatment K-L grades of Ⅲto Ⅳ,and high levels of interleukin 6(IL-6)and matrix metallo proteinase-3(MMP-3)were risk factors for the prognosis of patients with knee osteoarthritis.ROC test results showed that the area under the curve of the nomogram model in the experimental cohort and validation cohort was 0.806[95％CI(0.742,0.866)]and 0.786[(95％CI(0.678,0.893)],re-spectively.The results of the calibration curve showed that the Brier values of the experimental cohort and verification cohort were 0.151 points and 0.134 points,respectively.When the threshold probability value in the decision curve was set to 31％,the clinical benefit rates of the experimental cohort and validation cohort were 51％and 56％,respectively.Conclusion The prognostic model of patients with knee osteoarthritis constructed based on multi-dimensional clinical data has both theoretical and practical significance,and can provide a reference for taking targeted measures to improve the prognosis of patients.

Heart failure with preserved ejection fraction(HFpEF)is a highly heterogeneous systemic condition and represents the predominant form of heart heart failure(HF)worldwide.Current pharmacotherapies for HFpEF are limited and lack specific targeted drugs.Recent studies suggest that non-pharmacological strategies serve as adjuncts to conventional pharmacological treatment,offering improvements in symptoms,quality of life,and reducing the risk of rehospitalization for HF in patients with HFpEF.These strategies include CD34 stem cell transplantation,the greater splanchnic nerve ablation,atrial septal shunting,atrial pacing,myocardial contractility modulation,left ventricular expander,baroreceptor stimulation,and others.This review comprehensively summarizes the latest clinical evidence on non-pharmacological treatments for HFpEF,with the aim of advancing the understanding of treatment strategies for this condition.

The effect of porcine SIRT5 on replication of foot and mouth disease virus type O(FMDV-O)and the underlying regulatory mechanism were investigated.Western blot and RT-qPCR analyses were employed to monitor expression of endoge-nous SIRT5 in PK-15 cells infected with FMDV-O.Three pairs of SIRT5-specific siRNAs were synthesized.Changes to SIRT5 and FMDV-O protein and transcript levels,in addition to virus copy numbers,were measured by western blot and RT-qPCR analyses.PK-15 cells were transfected with a eukaryotic SIRT5 expression plasmid.Western blot and RT-qPCR analyses were used to explore the impact of SIRT5 overexpression on FMDV-O replication.Meanwhile,RT-qPCR analysis was used to detect the effect of SIRT5 overexpression on the mRNA expression levels of type I interferon-stimulated genes induced by SeV and FMDV-O.The results showed that expression of SIRT5 was up-regulated in PK-15 cells infected with FMDV-O and siRNA interfered with SIRT5 to inhibit FMDV-O replication.SIRT5 overexpression promoted FMDV-O replication.SIRT5 over-expression decreased mRNA expression levels of interferon-stimulated genes induced by SeV and FMDV-O.These results suggest that FMDV-O infection stimulated expression of SIRT5 in PK-15 cells,while SIRT5 promoted FMDV-O rep-lication by inhibiting production of type I interferon-stimula-ted genes.These findings provide a reference to further ex-plore the mechanism underlying the ability of porcine SIRT5 to promote FMDV-O replication.

This study was aimed at understanding the trends in,and scope of,severe fever with thrombocytopenia syndrome(SFTS)in Nanjing,analyzing the spatial distribution pattern,detecting high incidence cluster areas and key popula-tions,and scientifically guiding prevention and control strategies and measures.We obtained data on SFTS cases from 2010 to 2023 in Nanjing from the China Disease Control and Prevention Information System,and described the time,popu-lation,and spatial distribution characteristics.We used joinpoint regression to calculate the annual percentage change(APC)in incidence,then used FleXScan spatial clustering scan analysis to explore spatial clustering areas at the street level.A total of 507 SFTS cases were reported from 2010 to 2023 in Nanjing.The APC was 31.8％(95％CI:22.5％-41.9％,P＜0.001),and the reported incidence in 2023 was 1.42/100 000(134 cases).The seasonal indices from May to August were 2.7,2.1,3.0,and 1.3,respectively,accounting for 76.1％of the total cases.The median age was 66(IQR:55,73)years,which gradually increased from 59 years in 2010-2011 to 68 in 2022-2023(P＜0.001);94.1％of cases were in individuals 45 years or older.Farmers,homemakers/unemployed individuals,and retirees accounted for 90.1％.The epidemic area increased from 11 streets in four districts in 2010-2011 to 58 streets in 11 dis-tricts in 2022-2023.Except for 2012-2013,global spatial autocorrelation analysis showed positive Moran's I values(0.224-0.526,P＜0.001),and FlexScan scan indicated that several streets in Lishui District and Jiangning District were the most likely clusters.Four streets in Pukou District were the secondary clusters from 2018 to 2023,and three streets in Luhe District in 2022-2023 were the secondary clusters(all P＜0.05).The reported incidence of SFTS in Nanjing showed a rapid upward trend,with spread of epidemic areas.The spatial distribution pattern was clustered.Strengthened training in diagnosis and treatment technology and detection ability of medical institutions,surveillance in high-incidence areas,tracing of case flow,and health education of tick and disease prevention knowledge are recommended.

Objective:To perform molecular diagnosis and pedigree analysis for one case with α-thalassemia who does not conform to the genetic laws,and explore the effects of a newly discovered rare mutation(HBA2:c.*12G＞A)on clinical phenotypes.Methods:Blood samples of the proband and her family members were collected for blood routine analysis,and the hemoglobin components were analyzed by capillary electrophoresis.The common α-and β-globin gene loci in Chinese population were detected by conventional techniques(Gap-PCR,RDB-PCR).The α-globin gene sequences(HBA1,HBA2)were analyzed by Sanger sequencing.Results:By analyzing the test results of proband and her family members,the genotype of the proband was-α3,7/HBA2:c.*12G＞A,her father was HBA2:c.*12G＞A heterozygous mutation carrier.Conclusion:This study identifies a rare α-globin gene mutation(HBA2:c.*12G＞A)that has not been reported before.It is found that heterozygous mutation carriers present with static α-thalassemia.

Objective:To analyze and compare the differences of expression profiles between RPL and normal adipose tissue by transcriptome sequencing(RNA-Seq),then identify the key genes related to prognosis and explore their potential mechanisms.Methods:Tumor tissues and normal adipose tissues of patients with RPL were collected for RNA-Seq,and then the differentially ex-pressed genes were analyzed by GO and KEGG enrichment analysis.Based on TCGA,the high-risk genes related to prognosis were screened and verified by Kaplan-Meier curve and receiver operat-ing characteristic(ROC)curve.Results:Compared with normal adipose tissue,279 differentially expressed genes were simultaneously up-regulated in RPL tissues,which were mainly enriched in immune response and PPAR signaling pathway.Combined with TCGA,7 stable prognostic high risk genes were identified and the overall survival rate of the high risk group was significantly lower than that of the low risk group(P＜0.05).Conclusion:KCNQ5,RBPJ and some other genes may be re-lated to the poor prognosis of RPL patients.The analysis of the mechanism of these genes in RPL is expected to provide new evidence for the formulation of diagnosis and treatment strategies for RPL patients.