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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]

As(V)‐loaded granular activated carbon was regenerated through electrocoagulation assisted by elution with NaCl. Adsorption of As(V) by activated carbon was highest at pH 6, and subsequent desorption in water was highest at pH 11, followed by pH 3. Lower initial pH improved arsenic removal during electrocoagulation, NaCl concentration was insignificant, but removal increased with current density. Adding Fe(II) before electrocoagulation led to an improved removal efficiency up to a concentration of 30 mg/L. Regeneration of As(V)‐loaded activated carbon increased with current density and time up to a maximum of 85%. An increase in NaCl concentration to 6000 mg/L further improved regeneration to 92%. Regeneration at a lower current density only dropped slightly from 54% to 51% when doubling activated carbon concentration, demonstrating excellent scalability. Repeated adsorption–desorption tests were performed, where 81% and 69% regeneration were obtained after four regenerations with NaCl concentrations of 6000 and 750 mg/L, respectively. NaCl concentration in the tested range did not influence electrocoagulation but improved regeneration through elution. The combination of electrocoagulation and elution facilitated a higher regeneration efficiency, meanwhile removing As(V) from the solution through adsorption on iron hydroxide. Practitioner Points: As(V)‐loaded activated carbon was regenerated by electrocoagulation with elution.Regeneration increased with regeneration time and current density up to 85%.Addition of 6000 mg/L NaCl further increased regeneration to 93%.Regeneration of 82% was achieved after four regenerations.NaCl did not affect electrocoagulation but improved regeneration through elution. [ABSTRACT FROM AUTHOR]

BackgroundSleep is commonly assessed by recording the electroencephalogram (EEG) of the sleeping brain. As sleep assessments in a lab environment are cumbersome for both the participant and researcher, it would be highly desirable to record sleep EEG with a user-friendly and mobile device. Dry electrodes that are reusable, low-cost, and easy to apply would be an essential component of such a device. In this study, we developed a testing protocol to investigate the performance of novel flat-type dry electrodes for sleep EEG recordings in free-living conditions.MethodsOvernight sleep EEG, electrooculogram and electromyogram of four young and healthy participants were recorded at home. Two identical ambulatory recording devices, one using novel flat-type dry electrodes, the other using self-adhesive pre-gelled electrodes, simultaneously recorded sleep EEG. Between both electrode types, we then compared the signal quality, the incidence of artifacts, the sensitivity, specificity and inter-scoring reliability (Cohen’s kappa) of sleep staging, as well as the agreement of important characteristics of sleep-specific EEG microstructure features, such as slow waves (0.5–4 Hz) and sleep spindles (10–16 Hz).ResultsOur testing protocol comprehensively compared the two electrode types on a macro- and microstructure level of sleep. The dry and pre-gelled electrodes both had comparable signal quality and sleep staging was feasible with both electrodes. Also, slow-wave and spindle characteristics were similar. However, sweat artifacts were more prevalent in the flat-type dry electrodes.ConclusionWith a reliable testing protocol, the performance of dry electrodes can be compared to reference technologies and objectively assessed also in free-living conditions.

Objective This study was performed to determine effects of different curing salts on the quality of salamis and to assess feasibility of using NaCl-alternative salts. Methods Various types of curing salts (KCl or MgCl2) as well as NaCl (sun-dried or refined) were incorporated for processing of salamis. The proximate composition, fatty acids, nucleotide-related compounds, and free amino acids of the salamis were analyzed during 40 days of ripening. Results The substitution of NaCl by KCl caused higher fat and ash content, but lower moisture content of the salami after 20 days of ripening (p