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Immunomodulatory effect of Tityus sp. in mononuclear cells extracted from the blood of rheumatoid arthritis patients

Background

Pathophysiological mechanisms of rheumatoid arthritis arise because of a proinflammatory environment, generated by the interaction of autoreactive lymphocytes and proinflammatory mediators. Current strategies to mitigate the progression of the disease produce adverse effects, so there is a need for new therapeutic strategies and molecular targets to treat this disease. In this context, evidence suggests that scorpion venoms could modulate the immune response and some important cellular mechanisms of pharmacological interest. To evaluate the immunomodulatory effect of the venom of Tityus sp. (a possible new species close to Tityus metuendus) peripheral blood mononuclear cells of women diagnosed with RA were compared to cells of a control group.

Methods

A case-control study was conducted with a sample of 10 women with a confirmed diagnosis of RA and controls matched by sex and age. The cytotoxicity of the venom was evaluated to find sublethal concentrations of the venom, and subsequently, their immunomodulatory capacity in terms of percentage of proliferation, cell activation, and cytokines production.

Results

the venom of Tityus sp. produced a decrease in the percentage of proliferation in the CD3+, CD3+CD4+, and CD3+CD8+ cell subpopulations of RA patients and healthy controls, at concentrations of 252 and 126 µg/mL. However, the venom did not induce significant differences in the percentage of cell activation markers. The venom caused a decrease in IL-10 at a concentration of 252 µg/mL compared to untreated cells from patients and controls. The remaining cytokines did not show significant differences.

Conclusion

the venom of Tityus sp. is a potential source of molecules with immunomodulatory ability in CD4 and CD8 T lymphocytes. This result directs venom characterization studies to identify pharmacological targets with immunomodulatory capacity in T lymphocytes to enhance research in the treatment of autoimmune disorders such as RA.

Arbutin attenuates CFA-induced arthritis by modulating expression levels of 5-LOX, NF‑κB, IL-17, PGE-2 and TNF-α

Arbutin, a naturally soluble glycosylated phenol has antioxidant, antimicrobial, antitumor and anti-inflammatory properties. The current exploration appraises the treatment of arthritis by use of Arbutin (25, 50 and 100 mg/kg) orally in CFA-induced rat arthritis model. Body weight changes, paw size, and joint diameter were recorded till the 28th day in the arthritic-induced rats. Hematological, biochemical, oxidative and inflammatory biomarkers were measured through the blood samples of anesthetized rats. Arbutin markedly decreased paw volume, PGE-2, anti-CCP and 5-LOX levels, however, maintained metabolic and hematological balance and prevented weight loss. Radiology and histology changes improved significantly in the ankle joints of rats. Moreover, Arbutin increased gene pointers such as IL-10 and IL-4 while significantly reducing the levels of CRP and WBCs, whereas Hb, platelets and RBCs count markedly raised in post-treatments. Antioxidant levels of SOD, CAT and GSH were improved and MDA level was reduced in treated groups. Rt-PCR investigation showed a significant reduction of the interleukin-1β, TNF-α, interleukin-6, cyclooxygenase-2, NF-κB and IL-17 and increased expression of gene pointers like IL-4, and IL-10 in treated groups. Assessment of molecular docking revealed a strong binding interaction of Arbutin against 5-LOX, IL-17, TNF-alpha and interleukin-6, cyclooxygenase-2, nuclear factor-κB, IL-4 and iNOS providing a strong association between experimental and theoretical results. As a result, Arbutin has significantly reduced CFA-induced arthritis by modulation of anti-inflammatory cytokines, i.e., IL-10 and IL-4, the pro-inflammatory cytokines panel such as NF-κB, TNF-alpha, IL-1β, IL-6, PGE-2, 5-LOX and COX-2 and oxidative biomarkers.

Predicting perinatal outcomes in women affected by COVID-19: An artificial intelligence (AI) approach

This study aimed to explore the role of artificial intelligence (AI) in predicting perinatal outcomes among women with COVID-19. Data was collected from hospitals in the Middle Euphrates and Southern regions of Iraq, with 152 pregnant patients included in the study. Patients were categorized into mild and severe infection groups, and their serum samples were analyzed for mineral levels (magnesium, copper, calcium, sodium, potassium, zinc, selenium, and iron) and immune factors (IL-6, IL-8, IL-32, IL-10, IL-18, IL-37, IL-38, IL-36, and IL-1). The findings revealed significant associations between specific mineral levels, immune factors, and perinatal outcomes. Mineral levels such as magnesium (75.5% mild infection, 80.9% severe infection), copper (68.2% mild infection, 64.3% severe infection), calcium ion (81.8% mild infection, 76.2% severe infection), sodium (70.9% mild infection, 69.0% severe infection), potassium (72.7% mild infection, 71.4% severe infection), zinc (61.8% mild infection, 54.8% severe infection), selenium (78.2% mild infection, 82.9% severe infection), and iron (74.5% mild infection, 68.3% severe infection) showed varying percentages associated with mild and severe infections. Immune factors such as IL-6 (32% mild infection, 21% severe infection), IL-8 (15% mild infection, 7% severe infection), IL-32 (24% mild infection, 9% severe infection), IL-10 (7% mild infection, no severe infection), IL-18 (13% mild infection, 11% severe infection) demonstrated varying percentages associated with perinatal outcomes, while other interleukins showed no changes in severe infections. These results highlight the potential of AI in predicting outcomes for pregnant women with COVID-19, which could aid in improving their management and care. Further research and validation of predictive models are recommended to enhance accuracy and applicability.

Protective effect of fustin against adjuvant-induced arthritis through the restoration of proinflammatory response and oxidative stress

Rheumatoid arthritis causes irreparable damage to joints. The present research sought to check fustin's anti-arthritic efficacy against the complete Freund's adjuvant-induced arthritis paradigm in animals by altering the inflammatory response. In the rats, complete Freund's adjuvant was used to trigger arthritis and they received fustin at 50 and 100 mg/kg for 21 days. At regular intervals, the hind paw volume and arthritic score were assessed. After the trial period, hematological, antioxidant, pro-inflammatory cytokines, and other biochemical parameters were estimated. Fustin-treated rats showed the down-regulation of hind paw volume, arthritic score, and altered hematological parameters (TLC, DLC (neutrophil, lymphocyte, monocyte, eosinophil, basophil)). Furthermore, fustin significantly mitigates proinflammatory cytokine (reduced interleukin, tumor necrosis factor-a (TNF-α), IL-6, IL-1β), oxidative stress (attenuated malondialdehyde (MDA), catalase (CAT), glutathione (GSH), superoxide dismutase (SOD)), attenuated production of prostaglandin E2 and myeloperoxidase (MPO) and improved nuclear factor erythroid 2-related factor (Nrf2) action. Fustin led to the benefit in arthritis-prone animals elicited by complete Freund's adjuvant via pro-inflammatory cytokine.

Identifying anti-TNF response biomarkers in ulcerative colitis using a diffusion-based signalling model

Motivation

Resistance to anti-TNF therapy in subgroups of ulcerative colitis (UC) patients is a major challenge and incurs significant treatment costs. Identification of patients at risk of nonresponse to anti-TNF is of major clinical importance. To date, no quantitative computational framework exists to develop a complex biomarker for the prognosis of UC treatment. Modelling patient-wise receptor to transcription factor (TF) network connectivity may enable personalized treatment.

Results

We present an approach for quantitative diffusion analysis between receptors and TFs using gene expression data. Key TFs were identified using pandaR. Network connectivities between immune-specific receptor-TF pairs were quantified using network diffusion in UC patients and controls. The patient-specific network could be considered a complex biomarker that separates anti-TNF treatment-resistant and responder patients both in the gene expression dataset used for model development and separate independent test datasets. The model was further validated in rheumatoid arthritis where it successfully discriminated resistant and responder patients to tocilizumab treatment. Our model may contribute to prognostic biomarkers that may identify treatment-resistant and responder subpopulations of UC patients.

Availability and implementation

Software is available at https://github.com/Amy3100/receptor2tfDiffusion.

Supplementary information

Supplementary data are available at Bioinformatics Advances online.

Molecular insights into phytochemicals exhibiting anti-arthritic activity: systematic review : John Di Battista

INTRODUCTION

Rheumatoid arthritis (RA) is a chronic inflammatory autoimmune disease with an unclear etiology causing severe inflammation, joint pain, and destruction that increases the chance of disability over time. Dysregulation of various immune signaling cascades regulates the formation of synovial hyperplasia and pannus formation. Imbalance in cytokine levels, predominantly proinflammatory cytokines like TNF-α, IL-1, IL-6, IL-17, and IL-12p70 profoundly influences the disease's pathogenesis. Even though various strategies are adopted to treat arthritis, their side effects and cost limit their usage. This review discusses the multiple pathways involved in the pathogenesis of rheumatoid arthritis, provides a systematic analysis of various phytochemicals, and discusses their potential molecular targets in RA treatment.

METHODS

The literature mining was done from scientific databases such as PubMed, Europe PMC, Web of Science, Scopus, etc. The terminologies used for literature mining were Rheumatoid arthritis, phytochemicals, cell signaling pathways, molecular mechanism, etc. RESULTS: NF-κB, MAPKs, and JAK-STAT are the key pathways potentially targeted for RA treatment. However, specific susceptible pathways and potential targets remain unexplored. Besides, the phytochemicals remain an immense source to be exploited for the effective treatment of RA, overcoming the demerits of the conventional strategies. Various in vitro and in vivo findings suggest that polyphenols and flavonoids effectively treat RA conditions overcoming the demerits, such as limitations in usage and toxicity. The phytochemicals should be explored in par with the pathological mechanisms with all the available targets to determine their therapeutic efficacy. Through the established therapeutic efficacy, phytochemicals can help developing therapeutics that are safe and efficacious for RA treatment.