Objective To investigate the pathological damage to and inflammation of different intestinal segments in a rat model of severe hemorrhage,and to explore the effect of polarization of intestinal macrophage on the pathophysiology of intestinal inflammation.Methods Male Wistar rats were randomly divided into two groups:the sham operation group and hemorrhage group.In the hemorrhage group,40％of the total blood volume was lost in 25-30 minutes,while in the sham operation group,only the femoral artery and vein were intubated without bleeding.The rats were killed at 0,3,6,12 and 24 hours.The entire intestine was isolated quickly,and sections of the intestine were cut at the duodenum,jejunum,ileocecal junction,colon and rectum for histopathological evaluation.ELISA was adopted to determine related inflammation factors while multi-color immunohistochemistry was used to calculate macrophage surface markers.The data was statistically analyzed.Results(1)Compared with the sham group,there was no significant difference in colon histology at 3 h and 6 h,but significant difference was detected in rectum scores only at 24 h.The scores of other intestinal segments were significantly different at each time point.The severity of ileocecal and colonic lesions after bleeding increased with time.The duodenum,jejunum and ileocecum were more critically injured at 3 h than the rectum at 6 h.The injury to the duodenum,jejunum,ileum and colon was much more pronounced than to the rectum at 12 h.(2)The expressions of TNF-α and IL-1β in the rectum were increased significantly at 12 h post operation.The expressions of IL-1β,TNF-α in the jejunum increased obviously at 3 h and 6 h,respectively.(3)Three hours after severe bleeding,the level of macrophages in the jejunum and ileocececal area increased significantly,and the percentage of M1 macrophages was higher.After 6 hours,the proportion of M2 macrophages in the jejunum and M1 macrophages decreased significantly.After 3 hours,the percentage of M1 macrophages in the colon decreased,but that of M2 macrophages increased.The proportion of M2 polarized macrophages in the duodenum and rectum increased at 3 h after severe bleeding but decreased at 6 h.Conclusion Pathological damage to intestinal sections after bleeding varies depending on the time,and is correlated with the inflammatory level of macrophages.

Objective To propose strategies for developing clinical predictive models,aiming to assist researchers in conducting standardized clinical prediction model studies.Methods Literature review was conducted to summarize the operational steps and content for developing clinical predictive models.Then,a methodological framework was summarized and refined through expert consultation.Results The 11-step methodological framework for developing clinical predictive models was obtained by synthesizing the experience of 456 clinical predictive modeling studies and expert consultation,and the details were analyzed and elaborated.Conclusions This study presents methodological strategies and recommendations for the development of clinical predictive models,intended to serve as a guide for researchers.

In order to understand the prevalence of Akabane disease(AKAD)in Guizhou Province and the molecular characteristics of the isolates,the whole-genome sequence of a strain of Akabane virus(AKAV)from a bovine AKAD-positive sample was determined and analyzed.The genotype and genetic variation of the strain were also explored.Based on the conserved S sequence,a fluores-cence quantitative PCR(qPCR)detection method was established and applied for the investigation of AKAV infection status in four large-scale beef cattle farms of Guizhou.Results showed that the S,M and L fragments of the bovine strain were highly homologous to the Tianjin strain(TJ2016/China/2016)and the Australian strain(JaLAB39/Australia/1959),where they were in the same evolutionary branch and belonged to genotype Ⅱ.Sensitivity assay found that the lowest detection limit was 2.5 X 101 copies/μL.Specificity assay showed the established method detected only AKAV with no amplification on bovine bluetongue virus(BLUV),Pasteurella multocida(PM),bovine infectious rhinotracheitis virus(IBRV)and bovine Mycoplasma bovis.The variation coefficients of inter-and intra batches in the repeatability test were both lower than 2.26％.These findings illus-trated that the established qPCR method had high sensitivity,good specificity and repeatability.A total of 298 serum samples from 4 large-scale beef cattle farms in Qianxi City and Huangping County of Guizhou Province were collected and tested for AKAV by the method.Out of 298 sam-ples,25 positive samples(25/298)were detected as positive with a positive rate of 8.39％.In sum-mary,this work provided the reference data for a deep understanding of the molecular prevalence of AKAV in Guizhou Province and laid foundation for the prevention and control of AKAD.

Objective:To evaluate the predictive value of a risk prediction model guided by the ratio of respiratory rate to diaphragm thickening fraction (RR/DTF) for noninvasive-invasive mechanical ventilation transition timing in patients with acute exacerbation of chronic obstructive pulmonary disease (AECOPD), through ultrasound evaluation of diaphragm movement indicators.Methods:Sixty-four patients diagnosed with AECOPD and undergoing non-invasive ventilation (NIV), who were admitted to the department of critical care medicine of the First Affiliated Hospital of Jinzhou Medical University from January 2022 to July 2023 were enrolled. They were divided into NIV successful group and NIV failure group based on the outcome of NIV within 24 hours. Clinical indicators such as RR/DTF, diaphragmatic excursion (DE), tidal volume (VT), respiratory rate (RR), pH value, partial pressure of carbon dioxide (PaCO 2), and sputum excretion disorder were compared between the two groups after 2 hours of NIV. The factors influencing NIV failure were included in binary Logistic regression analysis, and an RR/DTF oriented risk prediction model was established. Receiver operator characteristic curve (ROC curve) analysis was used to assess the predictive value of this model for the timing of noninvasive-invasive mechanical ventilation transition in AECOPD patients. Results:Among 64 patients with AECOPD, with 43 in the NIV successful group and 21 in the NIV failure group. There were no statistically significant differences in baseline data such as age, gender, body mass index (BMI), oxygenation index (P/F), smoking history, and acute physiological and chronic health evaluation Ⅱ (APACHEⅡ) between the two groups of patients, indicating comparability. Compared to the NIV successful group, the NIV failure group showed a significantly increase in RR/DTF, RR, PaCO 2, and sputum retention, while VT and DE were significantly decreased [RR/DTF (%): 1.00±0.18 vs. 0.89±0.22, RR (bpm): 21.64±3.13 vs. 19.62±2.98, PaCO 2 (mmHg, 1 mmHg≈0.133 kPa): 70.82±8.82 vs. 65.29±9.47, sputum retention: 57.1% vs. 30.2%, VT (mL): 308.09±14.89 vs. 324.48±23.82, DE (mm): 19.91±2.94 vs. 22.05±3.30, all P < 0.05]. Binary Logistic regression analysis showed that RR/DTF [odds ratio ( OR) = 147.989, 95% confidence interval (95% CI) was 3.321-595.412, P = 0.010], RR ( OR = 1.296, 95% CI was 1.006-1.670, P = 0.045), VT ( OR = 0.966, 95% CI was 0.935-0.999, P = 0.044), PaCO 2 ( OR = 1.086, 95% CI was 1.006~1.173, P = 0.035), and sputum retention ( OR = 4.533, 95% CI was 1.025-20.049, P = 0.046) were independent risk factors for predicting NIV failure in AECOPD patients. ROC curve analysis showed that the area under the curve (AUC) of 0.713 with a 95% CI of 0.587-0.839 ( P = 0.005). The sensitivity was 72.73%, the specificity was 88.10%, the Youden index was 0.394, and the optimal cut-off value was 0.87. Conclusion:The RR/DTF risk prediction model has good predictive value for the timing of noninvasive-invasive mechanical ventilation transition in AECOPD patients.

OBJECTIVE To investigate the distribution and regulation of G-quadruplex(G4)in enzymes related to glycolysis.METHODS The sequences of the transcription start site(TSS)region upstream of 1500 bp to the 5'-Untranslated region in 200 enzymes and their subtypes in glycolysis were selected for bioinformatics analysis.Related enzymes in glycolysis containing putative G-quadru-plex-forming sequences(PQSs)were identified.Circular Dichroism and Native polyacrylamide gel elec-trophoresis were used to verify the formation of G4.The ExonucleaseⅠhydrolysis assay was used to validate the stability of the formed G4 under 0,0.5,2,8,16,and 32 min.A reporter gene plasmid was constructed by inserting specific fragments of the related enzymes before the luciferase expression sequence.The dual-luciferase reporter assay system validate the expression level of luciferase to assess the impact of G4 on promoter activity.Real-time quantitative PCR was performed to validate the transcriptional regulatory role of G4 by detecting the mRNA levels of luciferase.RESULTS ①Bioin-formatics analysis showed that out of the 200 glycolysis-related enzymes,12 contained PQSs.Based on the analysis of the length and structure of PQSs,aldolase A(ALDOA)and phosphoglycerate mutase 2(PGAM2)proved to be able to form stable G4.② ALDOA and PGAM2 had the maximum positive absorption peak at 260 nm and maximum negative absorption peak at 240 nm.Both of them could form a G4 at the same time.③After digestion with ExonucleaseⅠ,ALDOA and PGAM2 showed no significant hydrolysis and demonstrated the stability of G4 structures.However,both of them could be gradually hydrolyzed after mutations in their PQSs.④ After PQS mutation of ALDOA and PGAM2,the mRNA levels and expression of downstream luciferase of ALDOA were significantly increased(P<0.05,P<0.01),while PGAM2 was significantly decreased(P<0.05,P<0.01).CONCLUSION The gene sequences of glycolysis-related enzymes and their subtypes contain a large number of PQSs.ALDOA and PGAM2 can form stable G4 and perform transcriptional regulatory functions.

Objective:To discuss the clinical efficacy of treating lumbar muscle strain(LMS)with Tuina(Chinese therapeutic massage)plus Chinese medication hot compress. Methods:A total of 147 LMS patients were randomized into a Tuina group,a Chinese medication hot compress group,and a combined group,each consisting of 49 cases.The Tuina group received Tuina treatment;the Chinese medication hot compress group received Chinese medication hot compress treatment;and the combined group received the forementioned two therapies alternately.The three groups of patients were assessed using the visual analog scale(VAS)and Oswestry disability index(ODI)before treatment and after 2 weeks of treatment.A 2-month follow-up was also conducted to observe the relapse rate. Results:The VAS and ODI scores dropped significantly after treatment in all three groups compared with their baseline(P<0.05),and the combined group surpassed the other two groups in comparing the ODI score(P<0.05).The 2-month follow-up showed that the combined group had the lowest relapse rate among the three groups(P<0.05). Conclusion:Compared to each therapy used alone,Tuina plus Chinese medication hot compress can relieve pain,improve daily living function,and reduce the short-term relapse rate better in treating LMS patients.

Itaconate is a pivotal intermediate metabolite in the tricarboxylic acid (TCA) cycle of immune cells. It is produced by decarboxylation of cis-aconitic acid under the catalysis of aconitate decarboxylase 1 (ACOD1), which is encoded by the immune response gene 1 (IRG1). Itaconate has become a focal point of research on immunometabolism. Studies have demonstrated that itaconate plays a crucial role in diseases by regulating inflammation, remodeling cell metabolism, and participating in epigenetic regulation. This paper reviewed the research progress in itaconnate from its chemical structure, regulatory effects on different diseases, and mechanisms, proposes the future research directions, aiming to provide a theoretical basis for the development of itaconate-related drugs.
Humans ; Succinates/metabolism* ; Carboxy-Lyases/genetics* ; Inflammation/metabolism* ; Citric Acid Cycle ; Animals ; Epigenesis, Genetic ; Neoplasms/immunology*

Objective:To investigate clinical and imaging parameters to predict blood loss and cranial nerve injury (CNI) following carotid body paraganglioma (CBP) resection.Methods:A retrospective examination of clinical and imaging data was conducted on 63 patients who underwent CBP resection at Xiangya Hospital of Central South University from January 2016 to December 2022, including 23 males and 40 females, aged 26-87 years old. Three imaging parameters including tumor volume, the angle of contact with the internal carotid artery (ICA), and the distance to the base of skull (DTBOS) were gauged using the IMEDPACS software on CTA and MR imaging. The predictive efficacies of age, gender, Shamblin classification, and three imaging parameters for blood loss and CNI following surgery were analysed. Logistic composite parameter models were constructed and their predictive validity was assessed.Results:Multivariate logistic regression analysis underscored that only tumor volume ( OR=1.381,95% CI:1.167-1.507, P=0.001) showed significant statistical correlations with blood loss following surgery. Area under curve (AUC) values of 0.910 for receiver operating characteristic (ROC) curves showed a sensitivity of 1.000 and a specificity of 0.694. Tumor volume ( OR=1.126,95% CI:1.030-1.231, P=0.002) and DTBOS ( OR=0.225,95% CI:0.081-0.630, P=0.005) were significantly associated with postoperative CNI. The analysis of logistic composite model showed AUC values for tumor volume, DTBOS and combination of the two parameters were 0.858, 0.788, and 0.872, respectively. The model for combination of tumor volume and DTBOS also proved superior in predicting postoperative CNI ( Z=3.106, P<0.001), with a sensitivity of 0.833 and a specificity of 0.769. Conclusions:Tumor volume and DTBOS emerged as effective predictors for blood loss and/or CNI in patients with CBP resection. Moreover, the logistic composite parameter model outclassed single-parameter models in terms of their predictive clinical value.

Objective Based on the gene expression omnibus(GEO)database,bioinformatics methods were employed to analyze the expression characteristics of hypoxia-related differentially expressed genes(HRDEGs)in ischemic stroke,and key genes were screened,to provide important support for a deeper understanding of ischemic stroke.Methods The GSE16561 and GSE58294 datasets were downloaded from the GEO database,and Python software was used for data integration.The Combat method was employed to eliminate batch effects while retaining disease grouping characteristics.Principal component analysis was conducted to reduce dimensionality of the data before and after batch effect removal,and intraclass correlation coefficient(ICC)testing was performed on the ischemic stroke and normal control groups.Gene set enrichment analysis(GSEA)and single-sample GSEA were conducted on the merged and batch effects eliminated dataset,with a nominal P-value(NOM P-val)＜0.05 and false discovery rate P-value(FDR P-val)＜0.25 used as criteria to select significantly different gene sets.Differential expression genes between the ischemic stroke samples and normal control samples after merging and eliminating batch effects of the GSE16561 and GSE58294 datasets were identified using R software,with an absolute value of log2 gene expression fold change(FC)≥0.58 and adjusted P-value(Padj)＜0.05 as selection criteria.Intersection with hypoxia-related genes obtained from the National Center for Biotechnology Information(NCBI)in the United States yielded the HRDEGs.Gene ontology(GO)and Kyoto encyclopedia of genes and genomes(KEGG)enrichment analyses were performed on the HRDEGs,and the STRING database was used to construct a protein-protein interaction network of differentially expressed genes.The top 10 key genes were filtered using Cytoscape 3.8 software.Results The ICC analysis results showed excellent consistency in the ischemic stroke and normal control samples after batch effect removal,with ICC values of 0.94 and 0.98 for the GSE16561 and GSE58294datasets,respectively.GSEA results demonstrated significant enrichment of 34 gene sets in the stroke samples in the newly merged and batch effects removed dataset from GSE16561 and GSE58294,leading to the identification of 404 differentially expressed genes(all with Padj＜0.05),including 354 upregulated genes and 50 downregulated genes.Intersection with hypoxia-related genes yielded 64 HRDEGs.GO enrichment analysis indicated significant enrichment of HRDEGs in vesicle lumen,cytoplasmic vesicle lumen,secretory granule lumen,with molecular functions such as amide binding,peptide binding,phospholipid binding,and enzyme inhibitor activity.These genes are primarily involved in the positive regulation of cytokine production,regulation of immune response,response to bacterium-derived molecules,and response to lipopolysaccharide,among other biological processes.KEGG enrichment analysis revealed enrichment of HRDEGs in pathways related to lipid and atherosclerosis,Salmonella infection,neutrophil extracellular trap formation,nucleotide-binding oligomerization domain-like receptor signaling pathway,protein glycosylation in cancer,tuberculosis,and necroptosis.Based on the protein-protein interaction network,10 key genes were identified,including arginase1(ARG1),caspase1(CASP1),interleukin1 receptor type 1(IL-1R1),integrin subunit alpha M(ITGAM),matrix metalloproteinase9(MMP9),prostaglandin-endoperoxide synthase 2(PTGS2),signal transducer and activator of transcription 3(STAT3),Toll-like receptor2(TLR2),TLR4,and TLR8.Conclusion This study has identified 10 key genes associated with ischemic stroke and hypoxia through bioinformatics mining,which maybe provid potential targets for subsequent research and diagnostic and therapeutic interventions.