The pathogenesis and regulatory role of HIF-1 in rheumatoid arthritis.

Rheumatoid arthritis (RA) is a prevalent autoimmune disease that involves the overgrowth and inflammation of synovial tissue, leading to the degeneration and impairment of joints. In recent years, numerous studies have shown a close relationship between the hypoxic microenvironment in joints and the occurrence and progression of RA. The main cause of the pathological changes in RA is widely believed to be the abnormal expression of hypoxia-inducible factor-1 (HIF-1) in joints. This paper describes and illustrates the structure and primary functions of HIF-1 and explains the main regulatory methods of HIF-1, including the PHDs/HIF-1 α/pVHL pathway, factor-inhibiting HIF (FIH), regulation of inflammatory cytokines, and the NF-κB pathway. Furthermore, this paper discusses the mechanism of HIF-1 and its impact on inflammation, angiogenesis, and cartilage destruction in greater detail. We summarize previous research findings on the mechanism of HIF-1 and propose new potential treatments for RA based on the pathogenesis of HIF-1 in RA.

SKI knockdown suppresses apoptosis and extracellular matrix degradation of nucleus pulposus cells via inhibition of the Wnt/ß-catenin pathway and ameliorates disc degeneration.

This study aimed to determine the effects of SKI on interleukin (IL)-1ß-induced apoptosis of nucleus pulposus (NP) cells, intervertebral disc degeneration (IDD), and the Wnt signaling pathway. NP tissue specimens of different Pfirrmann grades (II-V) were collected from patients with different grades of IDD. Real-time polymerase chain reaction and western blotting were used to compare SKI mRNA and protein expression in NP tissues from patients. Using the IL-1ß-induced IDD model, NP cells were infected with lentivirus-coated si-SKI to downregulate the expression of SKI and treated with LiCl to evaluate the involvement of the Wnt/ß-catenin signaling pathway. Western blotting, immunofluorescence, and terminal deoxynucleotidyl transferase dUTP nick end labeling (TUNEL) staining were used to detect NP cell apoptosis, extracellular matrix (ECM) metabolism, and related protein expression changes in the Wnt/ß-catenin signaling pathway. To investigate the role of SKI in vivo, a rat IDD model was established by needle puncture of the intervertebral disc. Rats were injected with lentivirus-coated si-SKI and evaluated by magnetic resonance imaging (MRI), and hematoxylin and eosin (HE) and safranin O staining. SKI expression positively correlated with the severity of human IDD. In the IL-1ß-induced NP cell degeneration model, SKI expression increased significantly and reached a peak at 24 h. SKI knockdown protected against IL-1ß-induced NP cell apoptosis and ECM degradation. LiCl treatment reversed the protective effects of si-SKI on NP cells. Furthermore, lentivirus-coated si-SKI injection partially reversed the NP tissue damage in the IDD model in vivo. SKI knockdown reduced NP cell apoptosis and ECM degradation by inhibiting the Wnt/ß-catenin signaling pathway, ultimately protecting against IDD. Therefore, SKI may be an effective target for IDD treatment.

Rehabilitation care of patients with neurogenic bladder after spinal cord injury: A literature review.

This article reviews the research progress of rehabilitation treatment and nursing care of patients with neurogenic bladder after spinal cord injury, in order to provide reference for the rehabilitation treatment and nursing care of patients. We reviewed recent medical literature on patients with neurogenic bladder, focusing on neurogenic bladder caused by spinal cord injury. We analyzed 30 recent of publications in patients with neurogenic bladder after spinal cord injury, in addition to reviewing and evaluating the commonly used rehabilitation nursing methods for neurogenic bladder. Psychological counseling is a vital aspect which cannot be neglected in the process of neurogenic bladder rehabilitation. Hitherto, the commonly used drug and surgical treatments may have negatively impacted the mental health of patients in varying degrees. However, in clinical practice, applying intermittent catheterization in patients who have neurogenic bladder with spinal cord injury may help improve patients' life quality, mitigate psychological burden, and reduce negative emotions.

Glucose substrate in the hydrogen breath test for gut microbiota determination: A recommended noninvasive test.

Intestinal dysbiosis and small intestinal bacterial overgrowth (SIBO) are common in patients with liver cirrhosis. Existing studies have not explored the association between gut dysbiosis and SIBO. We propose some suggestions for the authors' experimental methods and concepts, and we hope these suggestions can be adopted. The hydrogen breath test is worthy of recommendation due to its high accuracy and convenient operation. We suggest changing the substrate of the hydrogen breath test from lactulose to glucose to improve the accuracy of each parameter. SIBO is a small subset of gut dysbiosis, and we propose clarifying the concept of both. SIBO may be caused by liver cirrhosis or one of the pathogeneses of gastrointestinal diseases. Therefore, interference from other gastrointestinal diseases should be excluded from this study.

An Immune-Related Long Non-Coding RNA Signature to Predict the Prognosis of Ewing's Sarcoma Based on a Machine Learning Iterative Lasso Regression.

The aim of this study was to construct a new immune-associated long non-coding RNA (lncRNA) signature to predict the prognosis of Ewing sarcoma (ES) and explore its molecular mechanisms. We downloaded transcriptome and clinical prognosis data from the Gene Expression Omnibus (GSE17679, which included 88 ES samples and 18 matched normal skeletal muscle samples), and used it as a training set to identify immune-related lncRNAs with different expression levels in ES. Univariable Cox regression was used to screen immune-related lncRNAs related to ES prognosis, and an immune-related lncRNA signature was constructed based on machine learning iterative lasso regression. An external verification set was used to confirm the predictive ability of the signature. Clinical feature subgroup analysis was used to explore whether the signature was an independent prognostic factor. In addition, CIBERSORT was used to explore immune cell infiltration in the high- and low-risk groups, and to analyze the correlations between the lncRNA signature and immune cell levels. Gene set enrichment and variation analyses were used to explore the possible regulatory mechanisms of the immune-related lncRNAs in ES. We also analyzed the expression of 17 common immunotherapy targets in the high- and low-risk groups to identify any that may be regulated by immune-related lncRNAs. We screened 35 immune-related lncRNAs by univariate Cox regression. Based on this, an immune-related 11-lncRNA signature was generated by machine learning iterative lasso regression. Analysis of the external validation set confirmed its high predictive ability. DPP10 antisense RNA 3 was negatively correlated with resting dendritic cell, neutrophil, and γδ T cell infiltration, and long intergenic non-protein coding RNA 1398 was positively correlated with resting dendritic cells and M2 macrophages. These lncRNAs may affect ES prognosis by regulating GSE17721_CTRL_VS_PAM3CSK4_12H_BMDC_UP, GSE2770_IL4_ACT_VS_ACT_CD4_TCELL_48H_UP, GSE29615_CTRL_VS_DAY3_ LAIV_IFLU_VACCINE_PBMC_UP, complement signaling, interleukin 2-signal transducer and activator of transcription 5 signaling, and protein secretion. The immune-related 11-lncRNA signature may also have regulatory effects on the immunotherapy targets CD40 molecule, CD70 molecule, and CD276 molecule. In conclusion, we constructed a new immune-related 11-lncRNA signature that can stratify the prognoses of patients with ES.

Role of the Wnt pathway in the formation, development, and degeneration of intervertebral discs.

Intervertebral disc degeneration (IVDD) is an age-related degenerative disease that is the main cause of low back pain. It seriously affects the quality of life of patients and places a heavy economic burden on families and society. The Wnt pathway plays an important role in the growth, development, and degeneration of intervertebral discs (IVDs). In the embryonic stage, the Wnt pathway participates in the growth and development of IVD by promoting the transformation of progenitor cells into notochord cells and the extension of the notochord. However, the activation of the Wnt pathway after birth promotes IVD cell senescence, apoptosis, and degradation of the extracellular matrix and induces the production of inflammatory factors, thereby accelerating the IVDD process. This article reviews the relationship between the Wnt pathway and IVD, emphasizing its influence on IVD growth, development, and degeneration. Targeting this pathway may become an effective strategy for the treatment of IVDD.

Development of a Machine Learning-Based Autophagy-Related lncRNA Signature to Improve Prognosis Prediction in Osteosarcoma Patients.

BACKGROUND: Osteosarcoma is a frequent bone malignancy in children and young adults. Despite the availability of some prognostic biomarkers, most of them fail to accurately predict prognosis in osteosarcoma patients. In this study, we used bioinformatics tools and machine learning algorithms to establish an autophagy-related long non-coding RNA (lncRNA) signature to predict the prognosis of osteosarcoma patients. METHODS: We obtained expression and clinical data from osteosarcoma patients in the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Gene Expression Omnibus (GEO) databases. We acquired an autophagy gene list from the Human Autophagy Database (HADb) and identified autophagy-related lncRNAs by co-expression analyses. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses of the autophagy-related lncRNAs were conducted. Univariate and multivariate Cox regression analyses were performed to assess the prognostic value of the autophagy-related lncRNA signature and validate the relationship between the signature and osteosarcoma patient survival in an independent cohort. We also investigated the relationship between the signature and immune cell infiltration. RESULTS: We initially identified 69 autophagy-related lncRNAs, 13 of which were significant predictors of overall survival in osteosarcoma patients. Kaplan-Meier analyses revealed that the 13 autophagy-related lncRNAs could stratify patients based on their outcomes. Receiver operating characteristic curve analyses confirmed the superior prognostic value of the lncRNA signature compared to clinically used prognostic biomarkers. Importantly, the autophagy-related lncRNA signature predicted patient prognosis independently of clinicopathological characteristics. Furthermore, we found that the expression levels of the autophagy-related lncRNA signature were significantly associated with the infiltration levels of different immune cell subsets, including T cells, NK cells, and dendritic cells. CONCLUSION: The autophagy-related lncRNA signature established here is an independent and robust predictor of osteosarcoma patient survival. Our findings also suggest that the expression of these 13 autophagy-related lncRNAs may promote osteosarcoma progression by regulating immune cell infiltration in the tumor microenvironment.

An immune-related gene signature for determining Ewing sarcoma prognosis based on machine learning.

PURPOSE: Ewing sarcoma (ES) is one of the most common malignant bone tumors in children and adolescents. The immune microenvironment plays an important role in the development of ES. Here, we developed an optimal signature for determining ES patient prognosis based on immune-related genes (IRGs). METHODS: We analyzed the ES gene expression profile dataset, GSE17679, from the GEO database and extracted differential expressed IRGs (DEIRGs). Then, we conducted functional correlation and protein-protein interaction (PPI) analyses of the DEIRGs and used the machine learning algorithm-iterative Lasso Cox regression analysis to build an optimal DEIRG signature. In addition, we applied ES samples from the ICGC database to test the optimal gene signature. We performed univariate and multivariate Cox regressions on clinicopathological characteristics and optimal gene signature to evaluate whether signature is an important prognostic factor. Finally, we calculated the infiltration of 24 immune cells in ES using the ssGSEA algorithm, and analyzed the correlation between the DEIRGs in the optimal gene signature and immune cells. RESULTS: A total of 249 DEIRGs were screened and an 11-gene signature with the strongest correlation with patient prognoses was analyzed using a machine learning algorithm. The 11-gene signature also had a high prognostic value in the ES external verification set. Univariate and multivariate Cox regression analyses showed that 11-gene signature is an independent prognostic factor. We found that macrophages and cytotoxic, CD8 T, NK, mast, B, NK CD56bright, TEM, TCM, and Th2 cells were significantly related to patient prognoses; the infiltration of cytotoxic and CD8 T cells in ES was significantly different. By correlating prognostic biomarkers with immune cell infiltration, we found that FABP4 and macrophages, and NDRG1 and Th2 cells had the strongest correlation. CONCLUSION: Overall, the IRG-related 11-gene signature can be used as a reliable ES prognostic biomarker and can provide guidance for personalized ES therapy.

Screening of osteoarthritis diagnostic markers based on immune-related genes and immune infiltration.

Osteoarthritis (OA) is a chronic degenerative disease of the bone and joints. Immune-related genes and immune cell infiltration are important in OA development. We analyzed immune-related genes and immune infiltrates to identify OA diagnostic markers. The datasets GSE51588, GSE55235, GSE55457, GSE82107, and GSE114007 were downloaded from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and differentially expressed immune-related genes (DEIRGs), and functional correlation analysis was conducted. Second, CIBERSORT was used to evaluate infiltration of immune cells in OA tissue. Finally, the least absolute shrinkage and selection operator logistic regression algorithm and support vector machine-recurrent feature elimination algorithm were used to screen and verify diagnostic markers of OA. A total of 711 DEGs and 270 DEIRGs were identified in this study. Functional enrichment analysis showed that the DEGs and DEIRGs are closely related to cellular calcium ion homeostasis, ion channel complexes, chemokine signaling pathways, and JAK-STAT signaling pathways. Differential analysis of immune cell infiltration showed that M1 macrophage infiltration was increased but that mast cell and neutrophil infiltration were decreased in OA samples. The machine learning algorithm cross-identified 15 biomarkers (BTC, PSMD8, TLR3, IL7, APOD, CIITA, IFIH1, CDC42, FGF9, TNFAIP3, CX3CR1, ERAP2, SEMA3D, MPO, and plasma cells). According to pass validation, all 15 biomarkers had high diagnostic efficacy (AUC > 0.7), and the diagnostic efficiency was higher when the 15 biomarkers were fitted into one variable (AUC = 0.758). We developed 15 biomarkers for OA diagnosis. The findings provide a new understanding of the molecular mechanism of OA from the perspective of immunology.

Development of a novel immune-related genes prognostic signature for osteosarcoma.

Immune-related genes (IRGs) are responsible for osteosarcoma (OS) initiation and development. We aimed to develop an optimal IRGs-based signature to assess of OS prognosis. Sample gene expression profiles and clinical information were downloaded from the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) and Genotype-Tissue Expression (GTEx) databases. IRGs were obtained from the ImmPort database. R software was used to screen differentially expressed IRGs (DEIRGs) and functional correlation analysis. DEIRGs were analyzed by univariate Cox regression and iterative LASSO Cox regression analysis to develop an optimal prognostic signature, and the signature was further verified by independent cohort (GSE39055) and clinical correlation analysis. The analyses yielded 604 DEIRGs and 10 hub IRGs. A prognostic signature consisting of 13 IRGs was constructed, which strikingly correlated with OS overall survival and distant metastasis (p < 0.05, p < 0.01), and clinical subgroup showed that the signature's prognostic ability was independent of clinicopathological factors. Univariate and multivariate Cox regression analyses also supported its prognostic value. In conclusion, we developed an IRGs signature that is a prognostic indicator in OS patients, and the signature might serve as potential prognostic indicator to identify outcome of OS and facilitate personalized management of the high-risk patients.

GRB10 and E2F3 as Diagnostic Markers of Osteoarthritis and Their Correlation with Immune Infiltration.

This study aimed to find potential diagnostic markers for osteoarthritis (OA) and analyze the role of immune cells infiltration in this pathology. We used OA datasets from the Gene Expression Omnibus database. First, R software was used to identify differentially expressed genes (DEGs) and perform functional correlation analysis. Then least absolute shrinkage and selection operator (LASSO) logistic regression and support vector machine-recursive feature elimination algorithms were used to screen and verify the diagnostic markers of OA. Finally, CIBERSORT was used to evaluate the infiltration of immune cells in OA tissues, and the correlation between diagnostic markers and infiltrating immune cells was analyzed. A total of 458 DEGs were screened in this study. GRB10 and E2F3 (AUC = 0.962) were identified as diagnostic markers of OA. Immune cell infiltration analysis found that resting mast cells, T regulatory cells, CD4 memory resting T cells, activated NK cells, and eosinophils may be involved in the OA process. In addition, GRB10 was correlated with NK resting cells, naive CD4 + T cells, and M1 macrophages, while E2F3 was correlated with resting mast cells. In conclusion, GRB10 and E2F3 can be used as diagnostic markers of osteoarthritis, and immune cell infiltration plays an important role in the occurrence and progression of OA.

Sirtuins and intervertebral disc degeneration: Roles in inflammation, oxidative stress, and mitochondrial function.

Intervertebral disc degeneration (IDD) is one of the main causes of low back pain, which seriously reduces the quality of life of patients and places a heavy economic burden on their families. Cellular senescence is considered to be an important factor leading to IDD, and inflammatory response, oxidative stress, and mitochondrial dysfunction are closely related to intervertebral disc (IVD) senescence. Therefore, inhibition of the inflammatory response and oxidative stress, along with maintaining mitochondrial function, may be useful in treating IDD. The sirtuins are a family of evolutionarily conserved nicotinamide adenine dinucleotide (NAD+)-dependent histone deacetylases, which are the major molecules mediating life extension or delay of aging-related diseases. The sirtuin protein family consist of seven members (SIRT1 - 7), which are mainly involved in various aging-related diseases by regulating inflammation, oxidative stress, and mitochondrial function. Among them, SIRT1, SIRT2, SIRT3, and SIRT6 are closely related to IDD. In addition, some activators of sirtuin proteins, such as resveratrol, melatonin, magnolol, 1,4-dihydropyridine (DHP), SRT1720, and nicotinamide mononucleotide (NMN), have been evaluated in preclinical studies for their effects in preventing IDD. This review described the biological functions of sirtuins and the important roles of SIRT1, SIRT2, SIRT3, and SIRT6 in IDD by regulating oxidative stress, inflammatory response, and mitochondrial function. In addition, we introduce the status of some sirtuin activators in IDD preclinical studies. This review will provide a background for further clarification of the molecular mechanism underlying IDD and the development of potential therapeutic drugs.

[Anterior versus posterior decompression for the treatment of thoracolumbar fractures with spinal cord injury:a Meta-analysis].

OBJECTIVE: To systematically evaluate the efficacy and safety of anterior decompression and posterior decompression in the treatment of thoracolumbar fractures with spinal cord injury, so as to provide a good scientific basis for more effective treatment of thoracolumbar fractures with spinal cord injury. METHODS: A clinical data about comparative study of anterior decompression and posterior decompression in the treatment of thoracolumbar fractures with spinal cord injury was searched and collected. The databases of Pubmed, Embase, Cochrane Library, CNKI, CBM, Wanfang Medical Network were searched by computer. Artificially collected journals included Spine, European Spine Journal, The Journal of Bone and Joint Surgery. Two spine surgeons independently screened the literature according to established inclusion and exclusion criteria and assessed the quality of the included studies. Meta-analysis was performed on the data using Review Manager 5.3 software, the indicators included operative time, intraoperative blood loss, postoperative tactile score, postoperative motor score, postoperative vertebral height, hospitalization time, neurological function recovery, efficiency of treatment, postoperative complications. RESULTS: Fifteen randomized controlled trials (RCTs) were enrolled in a total of 1 360 patients, including 680 anterior decompression and 680 posterior decompression. The results of Meta-analysis showed that the anterior decompression group had longer operation time [MD=80.09, 95% CI(36.83, 123.34), P=0.000 3], more intraoperative blood loss [MD=225.21, 95%CI(171.07, 279.35), P<0.000 01], longer hospitalization time [MD=2.31, 95% CI(0.32, 4.31), P=0.02]. And the postoperative tactile score [MD=13.39, 95% CI(9.86, 16.92), P<0.000 01], postoperative motor score [MD=13.15, 95% CI(7.02, 19.29), P<0.000 1], vertebral height [MD=1.36, 95% CI(0.79, 1.92), P<0.000 01] in anterior decompression were higher than that in posterior decompression. There was no statistically significant differences in the efficacy of treatment [OR=1.14, 95% CI(0.56, 2.31), P=0.72], neurological recovery [OR=0.87, 95% CI(0.57, 1.33), P=0.52] between two groups. CONCLUSIONS: Compared with posterior decompression, the anterior decompression has the advantages of longer operating time, more intraoperative blood loss, longer hospitalization time, higher postoperative tactile score, higher postoperative motor score, and higher injury vertebral height, But there was no significant difference in the treatment efficiency and nerve function recovery between two groups.