BACKGROUND:Rheumatoid arthritis is a chronic autoimmune disease.Early diagnosis is crucial for preventing disease progression and for effective treatment.Therefore,it is of significance to investigate the diagnostic characteristics and immune cell infiltration of rheumatoid arthritis. OBJECTIVE:Based on the Gene Expression Omnibus(GEO)database,to screen potential diagnostic markers of rheumatoid arthritis using machine learning algorithms and to investigate the relationship between the diagnostic characteristics of rheumatoid arthritis and immune cell infiltration in this pathology. METHODS:The gene expression datasets of synovial tissues related to rheumatoid arthritis were obtained from the GEO database.The data sets were merged using a batch effect removal method.Differential expression analysis and functional correlation analysis of genes were performed using R software.Bioinformatics analysis and three machine learning algorithms were used for the extraction of disease signature genes,and key genes related to rheumatoid arthritis were screened.Furthermore,we analyzed immune cell infiltration on all differentially expressed genes to examine the inflammatory state of rheumatoid arthritis and investigate the correlation between their diagnostic characteristics and infiltrating immune cells. RESULTS AND CONCLUSION:In both rheumatoid arthritis and normal synovial tissues,we identified 179 differentially expressed genes,with 124 genes up-regulated and 55 genes down-regulated.Enrichment analysis revealed a significant correlation between rheumatoid arthritis and immune response.Three machine learning algorithms identified LRRC15 and MICB as potential biomarkers of rheumatoid arthritis.LRRC15(area under the curve=0.964,95%confidence interval:0.924-0.992)and MICB(area under the curve=0.961,95%confidence interval:0.923-0.990)demonstrated strong diagnostic performance on the validation dataset.The infiltration of 13 types of immune cells was altered,with macrophages being the most affected.In rheumatoid arthritis,the majority of proinflammatory pathways in immune cell function were activated.Immunocorrelation analysis revealed that LRRC15 and MICB had the strongest correlation with M1 macrophages.To conclude,this study identified LRRC15 and MICB as potential diagnostic markers for rheumatoid arthritis,with strong diagnostic performance and significant correlation with immune cell infiltration.Machine learning and bioinformatics analysis deepened the understanding of immune infiltration in rheumatoid arthritis and provided new ideas for the diagnosis and treatment of rheumatoid arthritis.

Nonobstructive azoospermia (NOA), one of the most severe types of male infertility, etiology often remains unclear in most cases. Therefore, this study aimed to detect four biallelic detrimental variants (0.5%) in the minichromosome maintenance domain containing 2 ( MCMDC2 ) genes in 768 NOA patients by whole-exome sequencing (WES). Hematoxylin and eosin (H&E) demonstrated that MCMDC2 deleterious variants caused meiotic arrest in three patients (c.1360G>T, c.1956G>T, and c.685C>T) and hypospermatogenesis in one patient (c.94G>T), as further confirmed through immunofluorescence (IF) staining. The single-cell RNA sequencing data indicated that MCMDC2 was substantially expressed during spermatogenesis. The variants were confirmed as deleterious and responsible for patient infertility through bioinformatics and in vitro experimental analyses. The results revealed four MCMDC2 variants related to NOA, which contributes to the current perception of the function of MCMDC2 in male fertility and presents new perspectives on the genetic etiology of NOA.
Humans ; Male ; Azoospermia/genetics* ; Meiosis/genetics* ; Spermatogenesis/genetics* ; Adult ; Exome Sequencing ; Microtubule-Associated Proteins/genetics* ; Alleles ; Infertility, Male/genetics*

OBJECTIVE: To evaluate the dynamic changes of glucocorticoid (GC) dose and the feasibility of GC discontinuation in rheumatoid arthritis (RA) patients under the background of Chinese medicine (CM). METHODS: This multicenter retrospective cohort study included 1,196 RA patients enrolled in the China Rheumatoid Arthritis Registry of Patients with Chinese Medicine (CERTAIN) from September 1, 2019 to December 4, 2023, who initiated GC therapy. Participants were divided into the Western medicine (WM) and integrative medicine (IM, combination of CM and WM) groups based on medication regimen. Follow-up was performed at least every 3 months to assess dynamic changes in GC dose. Changes in GC dose were analyzed by generalized estimator equation, the probability of GC discontinuation was assessed using Kaplan-Meier curve, and predictors of GC discontinuation were analyzed by Cox regression. Patients with <12 months of follow-up were excluded for the sensitivity analysis. RESULTS: Among 1,196 patients (85.4% female; median age 56.4 years), 880 (73.6%) received IM. Over a median 12-month follow-up, 34.3% (410 cases) discontinued GC, with significantly higher rates in the IM group (40.8% vs. 16.1% in WM; P<0.05). GC dose declined progressively, with IM patients demonstrating faster reductions (median 3.75 mg vs. 5.00 mg in WM at 12 months; P<0.05). Multivariate Cox analysis identified age <60 years [P<0.001, hazard ratios (HR)=2.142, 95% confidence interval (CI): 1.523-3.012], IM therapy (P=0.001, HR=2.175, 95% CI: 1.369-3.456), baseline GC dose ⩽7.5 mg (P=0.003, HR=1.637, 95% CI: 1.177-2.275), and absence of non-steroidal anti-inflammatory drugs use (P=0.001, HR=2.546, 95% CI: 1.432-4.527) as significant predictors of GC discontinuation. Sensitivity analysis (545 cases) confirmed these findings. CONCLUSIONS RA patients receiving CM face difficulties in following guideline-recommended GC discontinuation protocols. IM can promote GC discontinuation and is a promising strategy to reduce GC dependency in RA management. (Trial registration: ClinicalTrials.gov, No. NCT05219214).
Adult ; Aged ; Female ; Humans ; Male ; Middle Aged ; Arthritis, Rheumatoid/drug therapy* ; Glucocorticoids/therapeutic use* ; Medicine, Chinese Traditional ; Retrospective Studies

Objective To analyze the interaction between PML protein and TAB1 protein using bioinformatic approaches and experimentally verify the results.Methods Using Rosetta software,a 3D model of TAB1 protein was constructed through a comparative modeling approach;the secondary structure of PML protein was retrieved in the PDB database and its crystal structure and 3D structure were resolved.Zdock 3.0.2 software was used to perform protein-protein docking of PML and TAB1,and the best conformation was extracted for molecular structure analysis of the docking model.The interaction between the two proteins was detected using immunoprecipitation in α-MMC-treated M1 inflammatory macrophages.Results When 6IMQ of PML was used as the docking site,PML protein formed 3 salt bridges,6 hydrogen bonds and 6 hydrophobic interactions with TAB1 proteins;when 5YUF of PML was used as the docking site,PML protein formed 1 hydrogen bond,3 electrostatic interactions and 9 hydrophobic interactions with TAB1 proteins,and both of the docking modes formed good molecular docking and interactions.In the M1 inflammatory macrophages treated with α-MMC for 4 h,positive protein bands of PML and TAB1 were detected in the cell lysates in PML-IP group.Conclusion PML protein can interact strongly with TAB1 protein.

Objective:To accurately ascertain the whole genome sequencing and the composition of open reading frames (ORFs) of non-replicating Tiantan strain of vaccinia virus (NTV) using next-generation long-read sequencing technology.Methods:NTV, obtained from our laboratory stock, was amplified and purified on chicken embryo fibroblast cells(CEFs), and the full-length genomic nucleic acid of NTV was extracted. The PacBio HiFi sequencing platform was utilized for de novo assembly to obtain the complete genomic sequence of NTV. Using a homology annotation strategy, we identified its ORF composition and compared it with known non-replicating vaccinia virus strains. Results:The total length of NTV′s genome was 171 729 bp, with a GC content of 33%. Its unique inverted terminal repeat (ITR) region comprised hairpin structures, two tandem repeat regions, and three non-repeat regions. NTV contained 166 ORFs, with major differences observed in the ITR and its surrounding regions when compared to MVA-BN and NYVAC. These three strains shared a common set of 138 ORFs. NTV encoded six unique ORFs related to virus evasion of host antiviral response.Conclusions:This study accurately determines the whole genome sequencing and ORFs composition of NTV, and reveals its similarities and differences with other replication-deficient vaccinia virus strains, which pave a way for the development and application of the next generation of monkeypox vaccines and novel viral vectors.

Healthy lifestyles and good living habits are effective strategies and important approaches to prevent chronic non-communicable diseases. With the development of evidence-based medicine, the evidence translation system has made some achievements in clinical practice. There is, however, no comprehensive, professional and efficient system for translating lifestyle evidence globally. Therefore, the Health Lifestyle Evidence (HLSE) Group of Lanzhou University constructed the HLSE Evidence Translation System (https://hlse.cn/), with the aim of synthesizing, evaluating, translating, and applying lifestyle-related evidence resources. This paper aims to introduce the functional module design of the evidence translation system, the system development process and testing, introduce the interface design and function demonstration, and explain the significance of constructing the HLSE.

To systematically construct a guideline to provide a methodological guide for researchers to develop patient decision aids.

Healthy lifestyles and good living habits are effective strategies and important approaches to prevent chronic non-communicable diseases. With the development of evidence-based medicine, the evidence translation system has made some achievements in clinical practice. There is, however, no comprehensive, professional and efficient system for translating lifestyle evidence globally. Therefore, the Health Lifestyle Evidence (HLSE) Group of Lanzhou University constructed the HLSE Evidence Translation System (https://hlse.cn/), with the aim of synthesizing, evaluating, translating, and applying lifestyle-related evidence resources. This paper aims to introduce the functional module design of the evidence translation system, the system development process and testing, introduce the interface design and function demonstration, and explain the significance of constructing the HLSE.

To systematically construct a guideline to provide a methodological guide for researchers to develop patient decision aids.