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Background: Rheumatoid arthritis (RA) is a chronic inflammatory disorder primarily targeting joints, significantly impacting patients' quality of life. The introduction of tumor necrosis factor-alpha (TNF-α) inhibitors has markedly improved RA management by reducing inflammation. However, these medications are associated with adverse skin reactions, which can vary greatly among patients due to genetic differences. Objectives: This study aimed to identify risk factors associated with skin adverse events by TNF-α in RA patients. Methods: A cohort study was conducted, encompassing patients with RA who were prescribed TNF-α inhibitors. This study utilized machine learning algorithms to analyze genetic data and identify markers associated with skin-related adverse events. Various machine learning algorithms were employed to predict skin and subcutaneous tissue-related outcomes, leading to the development of a risk-scoring system. Multivariable logistic regression analysis identified independent risk factors for skin and subcutaneous tissue-related complications. Results: After adjusting for covariates, individuals with the TT genotype of rs12551103, A allele carriers of rs13265933, and C allele carriers of rs73210737 exhibited approximately 20-, 14-, and 10-fold higher incidences of skin adverse events, respectively, compared to those with the C allele, GG genotype, and TT genotype. The machine learning algorithms used for risk prediction showed excellent performance. The risk of skin adverse events among patients receiving TNF-α inhibitors varied based on the risk score: 0 points, 0.6%; 2 points, 3.6%; 3 points, 8.5%; 4 points, 18.9%; 5 points, 36.7%; 6 points, 59.2%; 8 points, 90.0%; 9 points, 95.7%; and 10 points, 98.2%. Conclusions: These findings, emerging from this preliminary study, lay the groundwork for personalized intervention strategies to prevent TNF-α inhibitor-associated skin adverse events. This approach has the potential to improve patient outcomes by minimizing the risk of adverse effects while optimizing therapeutic efficacy. [ABSTRACT FROM AUTHOR]

Allergic contact dermatitis (ACD) is the most common chronic inflammatory skin disease (or immune-mediated disease), causing disruption to our psychological condition and life quality. In this study, the therapeutic properties of probiotic Bifidobacterium longum (B. longum) was investigated by using an ACD-induced animal model. For ACD induction, BALB/c mice ear and dorsal skin were sensitized with 240 µL of 1% (w/v) 2,4-dinitrochlorobenzene (DNCB) twice (3-day intervals). After a week of the first induction, the mice were re-sensitized by painting on their dorsal skin and ear with 0.4% (w/v) DNCB for a further three times (once per week). Before the ACD induction of 2 weeks and throughout the trial period, the BALB/c mice were supplemented daily with 1 mL of 1.0 × 109 CFU or 5.0 × 109 CFU B. longum using an intragastric gavage method. The ACD-induced mice without B. longum supplementation were used as a control. Results show that B. longum supplementation significantly alleviated ACD symptoms (e.g., ear swelling, epidermal damage) and immune response (e.g., reduced immune cell recruitment, serum IgE level, and cytokine production). The therapeutic efficiency of B. longum increased as the supplementation dose increased. Thus, daily supplementation with 5.0 × 109 CFU probiotic B. longum could be an effective method for the prevention and treatment of ACD. [ABSTRACT FROM AUTHOR]

Hydrogen (H2) gas is a green fuel, but its leakage during storage and transportation can lead to disasters due to its explosive nature. Here, a sensitive and selective H2 gas sensor is developed that can detect H2 in H2/CO and H2/NO2 gas mixtures. First, ZnO nanowires (NWs) are grown using vapor–liquid–solid growth. This is followed by atomic layer deposition‐mediated growth of Pd nanoparticles (NPs) on the ZnO NWs and uniform deposition of a thin NiO shell layer (12 nm in thickness) over the Pd‐decorated ZnO NWs. Characterization of the synthesized samples by different methods confirms the desired chemical composition, morphology, and phases. H2 gas sensing studies reveals the highly sensitive and selective response of the optimized gas sensor to H2 at 200 °C. In the presence of H2/CO and H2/NO2 gas mixtures, the NiO‐shelled Pd‐decorated ZnO NW sensor displays good selectivity for H2, but not the Pd‐decorated ZnO NW gas one. The NiO‐shelled Pd‐decorated ZnO NW gas sensor efficiently detected H2 also in the presence of 40% relative humidity and displays good stability even after 1 month. The present results can open the doors to the fabrication of highly selective H2 gas sensors using the described rationale design. [ABSTRACT FROM AUTHOR]

Arterial macrophage cholesterol accumulation and impaired cholesterol efflux lead to foam cell formation and the development of atherosclerosis. Modified lipoproteins interact with toll-like receptors (TLR), causing an increased inflammatory response and altered cholesterol homeostasis. We aimed to determine the effects of TLR antagonists on cholesterol efflux and foam cell formation in human macrophages. Stimulated monocytes were treated with TLR antagonists (MIP2), and the cholesterol efflux transporter expression and foam cell formation were analyzed. The administration of MIP2 attenuated the foam cell formation induced by lipopolysaccharides (LPS) and oxidized low-density lipoproteins (ox-LDL) in stimulated THP-1 cells (p < 0.001). The expression of ATP-binding cassette transporters A (ABCA)-1, ABCG-1, scavenger receptor (SR)-B1, liver X receptor (LXR)-α, and peroxisome proliferator-activated receptor (PPAR)-γ mRNA and proteins were increased (p < 0.001) following MIP2 administration. A concentration-dependent decrease in the phosphorylation of p65, p38, and JNK was also observed following MIP2 administration. Moreover, an inhibition of p65 phosphorylation enhanced the expression of ABCA1, ABCG1, SR-B1, and LXR-α. TLR inhibition promoted the cholesterol efflux pathway by increasing the expression of ABCA-1, ABCG-1, and SR-B1, thereby reducing foam cell formation. Our results suggest a potential role of the p65/NF-kB/LXR-α/ABCA1 axis in TLR-mediated cholesterol homeostasis. [ABSTRACT FROM AUTHOR]

This article discusses a study that examines the potential use of soluble programmed death 1 (sPD-1) as a biomarker for predicting mortality in patients with adult-onset Still's disease (AOSD). AOSD is a systemic inflammatory disease with a varied clinical course, and currently, there are no established biomarkers for predicting prognosis. The study included 69 patients with AOSD and found that higher levels of sPD-1 were associated with worse survival outcomes. The authors suggest that sPD-1 could be a valuable indicator for mortality in patients with AOSD. However, further research is needed to confirm the usefulness of sPD-1 levels as an indicator of diagnosis and disease activity in AOSD patients. [Extracted from the article]

With the advent of worldwide internet networks in the digital age, digital competence can play an important role in decreasing loneliness and social isolation in older adults. This study characterized different patterns of digital competence among older adults and examined their associations with loneliness and social isolation The sample included 315 older Korean adults (M = 68.79, range = 65–84) who completed an online survey. Latent profile analysis identified four different profiles of digital competence, including 1) low activity (28%) who did not choose digital participation despite advanced technical skills, 2) unskilled (13%) who had limited technical skills, 3) passive participation (25%) who was motivated for digital interactions even with insufficient technical skills, and 4) active participation (34%) who were involved in digital activities with the necessary skills. Additionally, the unskilled profile had relatively higher levels of loneliness than did the active participation profile. The passive participation and low activity profiles showed the highest level of social isolation, followed by the unskilled, and active participation profiles. The present findings suggest that understanding different profiles of digital competence and facilitating active digital participation related to specific profiles can be an effective strategy to reduce older adults' social isolation and loneliness. [ABSTRACT FROM AUTHOR]