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Abstract Background Despite continued efforts to manage and control Tuberculosis (TB) in China, it remains a major health concern. Bone tuberculosis (Bone-TB), a common form of extrapulmonary tuberculosis, still adds considerably to the global TB case load. Diagnosing Bone-TB is often difficult as its symptoms can be similar to other bone or joint diseases, which leads to delayed detection and treatment. Currently, comprehensive reports on the epidemiological aspects of Bone-TB in China are scarce. Methods This retrospective study analyzed demographic and clinical data from 2,191 patients diagnosed with Bone-TB in Southwest China between January 2011 and September 2023.This study fully reveals the characteristics of Bone-TB in Southwest China. Results The overall trend of bone tuberculosis was a slow rise. Among 2191 patients, males, farmers, aged 42–68 years, and people with HIV and diabetes are the priority groups for the prevention and treatment of Bone-TB. The majority of the infected spines (1556/2191) were located in the thoracic vertebra (759/2191) and lumbar vertebra (715/2191). Forty-nine (2.24%) patients had drug-resistant TB (DR-TB). Forty-five (2.05%) died during the treatment. The total and actual hospitalization. Costs amounted to $3,837.10 and $1,914.35 (p

Abstract Spinal cord injury (SCI) is a prevalent and serious complication among patients with spinal tuberculosis (STB) that can lead to motor and sensory impairment and potentially paraplegia. This research aims to identify factors associated with SCI in STB patients and to develop a clinically significant predictive model. Clinical data from STB patients at a single hospital were collected and divided into training and validation sets. Univariate analysis was employed to screen clinical indicators in the training set. Multiple machine learning (ML) algorithms were utilized to establish predictive models. Model performance was evaluated and compared using receiver operating characteristic (ROC) curves, area under the curve (AUC), calibration curve analysis, decision curve analysis (DCA), and precision-recall (PR) curves. The optimal model was determined, and a prospective cohort from two other hospitals served as a testing set to assess its accuracy. Model interpretation and variable importance ranking were conducted using the DALEX R package. The model was deployed on the web by using the Shiny app. Ten clinical characteristics were utilized for the model. The random forest (RF) model emerged as the optimal choice based on the AUC, PRs, calibration curve analysis, and DCA, achieving a test set AUC of 0.816. Additionally, MONO was identified as the primary predictor of SCI in STB patients through variable importance ranking. The RF predictive model provides an efficient and swift approach for predicting SCI in STB patients.

Abstract The ossification of the posterior longitudinal ligament (OPLL) in the cervical spine is commonly observed in degenerative changes of the cervical spine. Early detection of cervical OPLL and prevention of postoperative complications are of utmost importance. We gathered data from 775 patients who underwent cervical spine surgery at the First Affiliated Hospital of Guangxi Medical University, collecting a total of 84 variables. Among these patients, 144 had cervical OPLL, while 631 did not. They were randomly divided into a training cohort and a validation cohort. Multiple machine learning (ML) methods were employed to screen the variables and ultimately develop a diagnostic model. Subsequently, we compared the postoperative outcomes of patients with positive and negative cervical OPLL. Initially, we compared the advantages and disadvantages of various ML methods. Seven variables, namely Age, Gender, OPLL, AST, UA, BMI, and CHD, exhibited significant differences and were used to construct a diagnostic nomogram model. The area under the curve (AUC) values of this model in the training and validation groups were 0.76 and 0.728, respectively. Our findings revealed that 69.2% of patients who underwent cervical OPLL surgery eventually required elective anterior surgery, in contrast to 86.8% of patients who did not have cervical OPLL. Patients with cervical OPLL had significantly longer operation times and higher postoperative drainage volumes compared to those without cervical OPLL. Interestingly, preoperative cervical OPLL patients demonstrated significant increases in mean UA, age, and BMI. Furthermore, 27.1% of patients with cervical anterior longitudinal ligament ossification (OALL) also exhibited cervical OPLL, whereas this occurrence was only observed in 6.9% of patients without cervical OALL. We developed a diagnostic model for cervical OPLL using the ML method. Our findings indicate that patients with cervical OPLL are more likely to undergo posterior cervical surgery, and they exhibit elevated UA levels, higher BMI, and increased age. The prevalence of cervical anterior longitudinal ligament ossification was also significantly higher among patients with cervical OPLL.

【Objective】The study aims to explore the composition, sequence number and diversity of microbial community in Zhuhai Wailingding Marine Ranch, analyze the sensitivity and reducing power of eDNA technology, with a view to providing references for the management and maintenance of ecosystem in Zhuhai Wailingding Marine Ranch.【Method】In September 2021, 9 stations were set up in Zhuhai Wailingding Marine Ranch to sample at 2 m below the surface water for pretreatment, DNA extraction, PCR amplification, and high-throughput sequencing to analyze the composition of microbial species, the density and abundance of microbial resources, and determine the dominant species.【Result】A total of 30 species of microorganisms in Zhuhai Wailingding Marine Ranch were detected by eDNA technology, and 5 phyla, 7 classes, 14 orders, 19 families and 26 genera were identified, and a total of 779 706 Operational Taxonomic Units (OTUS) were detected. The Proteobacteria was the absolute dominant phylum accounting for 75.06%, followed by Bacteroidetes (11.35%), Firmicutes (5.28%), Planctomycetes (1.91%), and Actinobacteria (1.06%). There were 7 dominant species, which were Pseudoalteromonas, Marinobacter, Moraxella, Psychrobacter, Vibrio alginolyticus, Halomonas and Sphingobacterium. The dominance of Vibrio alginolyticus reached 0.19, which was the absolute dominant species, followed by Moraxella and Pseudoalteromonas reaching 0.134 and 0.127, respectively, which were the main dominant species.【Conclusion】The study reveals the microbial community information of the Zhuhai Wailingding Marine Ranch, explores the application of eDNA technology in marine ranch, and verifies the efficiency and sensitivity of this technology, providing basic data and scientific reference for future research on marine ranching microorganisms.

AbstractBackground Cinnamomi ramulus (C. ramulus) is frequently employed in the treatment of ankylosing spondylitis (AS). However, the primary constituents, drug targets, and mechanisms of action remain unidentified.Methods In this study, various public databases and online tools were employed to gather information on the compounds of C. ramulus, drug targets, and disease targets associated with ankylosing spondylitis. The intersection of drug targets and disease targets was then determined to identify the common targets, which were subsequently used to construct a protein-protein interaction (PPI) network using the STRING database. Network analysis and the analysis of hub genes and major compounds were conducted using Cytoscape software. Furthermore, the Metascape platform was utilized for Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses. Molecular docking studies and immunohistochemical experiments were performed to validate the core targets.Results The network analysis identified 2-Methoxycinnamaldehyde, cinnamaldehyde, and 2-Hydroxycinnamaldehyde as the major effective compounds present in C. ramulus. The PPI network analysis revealed PTGS2, MMP9, and TLR4 as the most highly correlated targets. GO and KEGG analyses indicated that C. ramulus exerts its therapeutic effects in ankylosing spondylitis through various biological processes, including the response to hormones and peptides, oxidative stress response, and inflammatory response. The main signaling pathways involved were IL-17, TNF, NF-kappa B, and Toll-like receptor pathways. Molecular docking analysis confirmed the strong affinity between the key compounds and the core targets. Additionally, immunohistochemical analysis demonstrated an up-regulation of PTGS2, MMP9, and TLR4 levels in ankylosing spondylitis.Conclusions This study provides insights into the effective compounds, core targets, and potential mechanisms of action of C. ramulus in the treatment of ankylosing spondylitis. These findings establish a solid groundwork for future fundamental research in this field.

Abstract Background Asthma is a frequently occurring respiratory disease with an increasing incidence around the world. Airway inflammation and remodeling are important contributors to the occurrence of asthma. We conducted this study aiming at exploring the effect of Histone deacetylase 4 (HDAC4)-mediated Kruppel-like factor 5 (KLF5)/Slug/CXC chemokine ligand-12 (CXCL12) axis on the development of asthma in regulation of airway inflammation and remodeling. Methods An asthmatic rat model was induced by ovalbumin (OVA) irrigation, and determined HDAC4, KLF5, Slug, and CXCL12 expression in the lung tissues by RT-qPCR and Western blot assay. OVA was also used to induce a cell model of asthma in human BEAS-2B and HBE135-E6E7bronchial epithelial cells. The airway hyperresponsiveness (AHR), and expression of inflammatory cytokines in model mice were examined using methacholine challenge test and ELISA. The biological behaviors were measured in asthma model bronchial smooth muscle cells (BSMCs) following loss- and gain- function approaches. The interactions between HDAC4, KLF5, Slug, and CXCL12 were also detected by IP assay, dual luciferase gene reporter assay, and ChIP. Results HDAC4 was upregulated in lung tissues of OVA-induced asthmatic mice, and inhibition of HDAC4 alleviated the airway inflammation and remodeling. HDAC4 increased KLF5 transcriptional activity through deacetylation; deacetylated KLF5 bound to the promoter of Slug and transcriptionally upregulated Slug expression, which in turn increased the expression of CXCL12 to promote the inflammation in bronchial epithelial cells and thus induce the proliferation and migration of BSMCs. Conclusion Collectively, HDAC4 deacetylates KLF5 to upregulate Slug and CXCL12, thereby causing airway remodeling and facilitating progression of asthma.

The aims of the present study were to examine the influences of different push-off techniques on kinetic and kinematic parameters both in and out of the water. The two techniques were: (1) a push off that was characterized by rapid extension of knees and hips towards the wall, prior to contact (i.e., no countermovement), and, (2) where the swimmer glides into the wall, letting the wall flex the knees in an approximate countermovement or eccentric phase. Twenty trained male and female freestyle swimmers (age 26.1 ± 9.9 years, height 1.61 ± 0.04 m, and weight 65.6 ± 19.3 kg) participated. Data were analyzed by employing two (i.e., land and water) 3 (variables of interest) x 2 (push-off type) repeated measures ANOVAs with the alpha level set a priori at 05. Results indicated that there were significant main effects for peak perpendicular force (p < 0.001), perpendicular impulse (p = 0.018), and velocity at 2.5 m (p = 0.005) on land. However, no significant effects were found between techniques in the water trials. As many of the participants were master swimmers, it is possible that they were unable to approach the wall in the water at the requisite speed to elicit a benefit from the countermovement.