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https://www.selleckchem.com/GSK-3.html Antibiotic resistance in bacterial pathogens is a growing problem for both human and veterinary medicine. Mobile genetic elements (MGEs) such as plasmids, transposons, and integrons enable the spread of antibiotic resistance genes (ARGs) among bacteria, and the overuse of antibiotics drives this process by providing the selection pressure for resistance genes to establish and persist in bacterial populations. Because bacteria, MGEs, and resistance genes can readily spread between different ecological compartments (e.g. soil, plants, animals, humans, wastewater), a "One Health" approach is needed to combat this problem. The equine hindgut is an understudied but potentially significant reservoir of ARGs and MGEs, since horses have close contact with humans, their manure is used in agriculture, they have a dense microbiome of both bacteria and fungi, and many antimicrobials used for equine treatment are also used in human medicine. Here, we collate information to date about resistance genes, plasmids, and class 1 integrons from equine-derived bacteria, we discuss why the equine hindgut deserves increased attention as a potential reservoir of ARGs, and we suggest ways to minimize the selection for ARGs in horses, in order to prevent their spread to the wider community. To compare the impact of Psoriasis Area and Severity Index (PASI) response on total work productivity impairment (TWPI) in patients with moderate-to-severe psoriasis; to compare TWPI and associated indirect costs among patients treated with risankizumab, adalimumab, ustekinumab, and placebo. Data from REVEAL (adalimumab phase III trial) were used to assess differences in trial-observed TWPI across PASI response cohorts. A machine learning model used REVEAL data to predict TWPI for patients in the risankizumab trials. These values were used to estimate work loss hours and work impairment-related indirect costs for each treatment cohort. Among REVEAL patients (  = 741)

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