Clinical performance of the ASAS health index in chinese patients with ankylosing spondylitis and its influencing factors.

OBJECTIVE: The aim of this study was to investigate the status of health-related quality of life in Chinese patients with ankylosing spondylitis (AS) and to analyze factors associated with the Assessment of SpondyloArthritis international Society Health Index (ASAS-HI) in AS and its relationship with disease activity and psychological status. METHODS: A cross-sectional study of 484 patients with AS attending 10 hospitals in China from March 2021 to September 2023 was recruited. The ASAS-HI assessed general health and functional status; the Depression Anxiety Stress Scales (DASS-21) assessed psychological disorders such as anxiety, depression, and stress; and the Functional Assessment of Chronic illness Therapy-Fatigue Scale (FACIT-F) assessed patients' fatigue symptoms; the Ankylosing Spondylitis Disease Activity Score-C-Reactive Protein (ASDAS-CRP), Bath Ankylosing Spondylitis Disease Activity Index (BASDAI), Bath Ankylosing Spondylitis Functional Index (BASFI), and Bath Ankylosing Spondylitis Measurement Index (BASMI) were used to assess patients' disease activity and functional impairment. The correlation between ASAS-HI and the ASDAS, poor psychological status, and fatigue symptoms was observed. Univariate and multivariate logistic regression analyses were used to explore the relevant influencing factors of ASAS-HI. RESULTS: A total of 484 patients were included in this study of whom 162 were in poor health, 139 in moderate health, and 183 in good health. On univariate analysis, disease activity is an important factor affecting ASAS-HI. People with extremely high disease activity (ASDAS ≥ 3.5) had a 12 times elevated risk of having poor health status (OR = 12.53; P < 0.001). Other significant covariates included age ≥ 36 (OR = 1.58; P = 0.015), BMI ≥ 24 kg/m2 (OR = 2.93; P = 0.013), smoke (OR = 1.96; P = 0.002), BASFI (OR = 1.49; P < 0.001), BASMI (OR = 1.22; P < 0.001), fatigue (OR = 6.28; P < 0.001), and bad psychological conditions such as depression (OR = 10.86; P < 0.001), anxiety (OR = 3.88; P < 0.001), and stress (OR = 4.65; P < 0.001). The use of bMARDs is inversely associated with the appearance of adverse health status (OR = 0.54; P = 0.012). There was no significant relationship between HLA-B27 and sex. Multivariable logistic regression showed that higher disease activity (ASDAS ≥ 3.5) (OR = 5.14; P = 0.005), higher scores of BASMI (OR = 1.10; P = 0.009), self-reported depression (OR = 3.68; P = 0.007), and fatigue (OR = 2.76; P < 0.001) were factors associated with adverse health status. CONCLUSION: The health status of AS patients is related to age, BMI, smoking, disease activity, poor psychological status, and fatigue and is influenced by a combination of multiple factors such as emotional state, economic level, pain, and dysfunction. Therefore, clinicians should pay attention to the early assessment of ASAS-HI in order to improve the prognosis of the disease. Key Points •Ankylosing spondylitis (AS) is a chronic inflammatory autoimmune disease with a long course and heavy disease burden, which greatly affects patients' quality of life. Therefore, this study aims to evaluate the health status of ankylosing spondylitis in the Chinese population and its influencing factors. •This is a multi-center cross-sectional study in China, which can better reflect the overall situation of the Chinese population.

Entry point of machine learning in axial spondyloarthritis.

Axial spondyloarthritis (axSpA) is a globally prevalent and challenging autoimmune disease. Characterised by insidious onset and slow progression, the absence of specific clinical manifestations and biomarkers often leads to misdiagnosis, thereby complicating early detection and diagnosis of axSpA. Furthermore, the high heterogeneity of axSpA, its complex pathogenesis and the lack of specific drugs means that traditional classification standards and treatment guidelines struggle to meet the demands of personalised treatment. Recently, machine learning (ML) has seen rapid advancements in the medical field. By integrating large-scale data with diverse algorithms and using multidimensional data, such as patient medical records, laboratory examinations, radiological data, drug usage and molecular biology information, ML can be modelled based on real-world clinical issues. This enables the diagnosis, stratification, therapeutic efficacy prediction and prognostic evaluation of axSpA, positioning it as an emerging research topic. This study explored the application and progression of ML in the diagnosis and therapy of axSpA from five perspectives: early diagnosis, stratification, disease monitoring, drug efficacy evaluation and comorbidity prediction. This study aimed to provide a novel direction for exploring rational diagnostic and therapeutic strategies for axSpA.

Integrating network pharmacology and experimental verification to explore the mechanism of Tripterygium wilfordii in ankylosing spondylitis.

OBJECTIVE: This study aimed to validate the mechanism of triptolide in treating ankylosing spondylitis (AS) through network pharmacology, molecular docking, and in vitro experiments. METHODS: We gathered AS-related genes using databases including DrugBank, OMIM, GeneCards, TTD and DisGeNET. TCMSP database was used to collect Tripterygium wilfordii (TWHF)-related data. Additionally, the potential targets of TWHF in treating AS were predicted by consulting databases such as Venny, String, Cytoscape, and Cytohubba. Subsequently, a protein-protein interaction network was created and the gene ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis were performed by metascape database. After selecting the most active ingredient of TWHF, molecular docking was performed to confirm the predicted results. Furthermore, we explore the potential mechanism of the most active ingredient of TWHF in the treatment of AS in vitro. RESULT: By integrating the results of network pharmacological analysis, 62 genes were found to be strongly associated with AS, such as STAT3, TNF, MMP9, VEGFA, CXCL8, PTGS2, etc. Triptolide (TP) is one of the most active ingredients in TWHF. The enrichment analysis indicated that 292 biological processes and 132 signaling pathways were involved, with the T helper 17 cells cell differentiation pathway as the key pathway. TP was selected for molecular docking and in vitro experiments. The molecular docking results indicated that TP had excellent affinity with 6 key targets. Further, flow cytometry, cell counting assay, and ELISA demonstrated that the serum level of IL-17 was higher in AS patients compared to XXX, and 25 µg/mL TP was the optimal intervention concentration. RT-qPCR and Western blotting further verified that TP could inhibit the activation of RORγt and the JAK2/STAT3 signaling pathway. CONCLUSION: In conclusion, based on network pharmacology, molecular docking, and experimental verification in vitro, we proposed that the TP can inhibit the activation of RORγt and the JAK2/STAT3 signaling pathway and inhibit the differentiation of T helper 17 cells cells. The article provide a theoretical basis for further development and utilization of TWHF in AS management.

Early transcriptomic adaptation to Na2CO3 stress altered the expression of a quarter of the total genes in the maize genome and exhibited shared and distinctive profiles with NaCl and high pH stresses.

Sodium carbonate (Na2CO3) presents a huge challenge to plants by the combined damaging effects of Na⁺, high pH, and CO3²â». Little is known about the cellular responses to Na2CO3 stress. In this study, the transcriptome of maize (Zea mays L. cv. B73) roots exposed to Na2CO3 stress for 5 h was compared with those of NaCl and NaOH stresses. The expression of 8,319 genes, representing over a quarter of the total number of genes in the maize genome, was altered by Na2CO3 stress, and the downregulated genes (5,232) outnumbered the upregulated genes (3,087). The effects of Na2CO3 differed from those of NaCl and NaOH, primarily by downregulating different categories of genes. Pathways commonly altered by Na2CO3, NaCl, and NaOH were enriched in phenylpropanoid biosynthesis, oxidation of unsaturated fatty acids, ATP-binding cassette (ABC) transporters, as well as the metabolism of secondary metabolites. Genes for brassinosteroid biosynthesis were specifically upregulated by Na2CO3, while genes involved in ascorbate and aldarate metabolism, protein processing in the endoplasmic reticulum and by N-glycosylation, fatty acid biosynthesis, and the circadian rhythm were downregulated. This work provides the first holistic picture of early transcriptomic adaptation to Na2CO3 stress, and highlights potential molecular pathways that could be manipulated to improve tolerance in maize.