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Cytochrome P450 (CYP) gene expression exhibits large interindividual variation attributable to diverse regulatory factors including microRNAs (miRNAs) and hepatic transcription factors (TFs). We used real-time qPCR with 106 human liver samples to measure the expression and interindividual variation of seven miRNAs and four TFs that have been reported to regulate the expression of CYPs; we also identified factors that influence their expression. The results show that expression of the seven miRNAs and the four TFs exhibits a non-normal distribution and the expression variability is high (89- to 618-fold for miRNA and 12- to 85-fold for TFs). Age contributed to the interindividual variation for miR-148a, miR-27b and miR-34a, whereas cigarette smoking and alcohol consumption significantly reduced HNF4α mRNA levels. Association analysis showed significant correlations among the seven miRNAs as well as the four TFs. Furthermore, we systematically evaluated the impact of the seven miRNAs and four TFs on protein content, mRNA levels, translation efficiency and activity of 10 CYPs. The results show that numerous associations (positive and negative) are present between the seven miRNAs or the four TFs and the 10 CYP phenotypes (as indicated by mRNA, protein and activity); specifically, miR-27b, miR-34a and all four TFs played key roles in the interindividual variation of CYPs. Our results extend previous findings and suggest that miR-27b and miR-34a may be potential direct or indirect master regulators of CYP expression and thereby contribute to the interindividual variations in CYP-mediated drug metabolism.The coronavirus disease (COVID-19) has infected more than 79 million individuals, with 1.7 million deaths worldwide. Several countries have implemented social distancing and testing policies with contact tracing as a measure to flatten the curve of the ongoing pandemic. Optimizing these control measures is urgent given the substantial societal and economic impacts associated with infection and interventions. To determine the optimal social distancing and testing strategies, we developed a mathematical model of COVID-19 transmission and applied optimal control theory, identifying the best approach to reduce the epidemiological burden of COVID-19 at a minimal cost. The results demonstrate that testing as a standalone optimal strategy does not have a significant effect on the final size of an epidemic, but it would delay the peak of the pandemic. If social distancing is the sole control strategy, it would be optimal to gradually increase the level of social distancing as the incidence curve of COVID-19 grows, and relax the measures after the curve has reached its peak. Compared with a single strategy, combined social distancing and testing strategies are demonstrated to be more efficient at reducing the disease burden, and they can delay the peak of the disease. To optimize these strategies, testing should be maintained at a maximum level in the early phases and after the peak of the epidemic, whereas social distancing should be intensified when the prevalence of the disease is greater than 15%. Accordingly, public health agencies should implement early testing and switch to social distancing when the incidence level begins to increase. After the peak of the pandemic, it would be optimal to gradually relax social distancing and switch back to testing.COVID-19 testing has become a standard approach for estimating prevalence which then assist in public health decision making to contain and mitigate the spread of the disease. The sampling designs used are often biased in that they do not reflect the true underlying populations. For instance, individuals with strong symptoms are more likely to be tested than those with no symptoms. This results in biased estimates of prevalence (too high). Typical post-sampling corrections are not always possible. Here we present a simple bias correction methodology derived and adapted from a correction for publication bias in meta analysis studies. The methodology is general enough to allow a wide variety of customization making it more useful in practice. Implementation is easily done using already collected information. Via a simulation and two real datasets, we show that the bias corrections can provide dramatic reductions in estimation error.In this study, we performed comprehensive pathology examinations on 83 Tripneustes ventricosus from 11 locations on St. Kitts to build baseline data necessary for disease diagnosis in this species. Gross abnormalities were observed in 23/83 (28%) urchins and included spine loss, visceral hyperpigmentation, test discoloration, and test ulceration. Ciliates were the only protists identified in this study via examination of tissue wet mounts and histology, documented in 50/83 (60%) urchins. Microscopic observations associated with visibly abnormal status included muscle necrosis, test and appendage inflammation, appendage (tube feet, spines, and pedicellariae) degeneration, severe coelomocytosis, and generalized hypermelanosis. Enterocyte intranuclear inclusion bodies, microbial aggregates, nerve pigmentation, enteric pigmentation, integument-associated crustaceans, and encysted metazoan parasites were of uncertain pathological significance. The etiology for any lesion was not microscopically apparent, contrasting literature implicating common marine bacteria in urchin diseases. This study highlights the importance of histopathology in urchin disease investigations and facilitates the recognition of disease in T. ventricosus.Psoriasis and type 2 diabetes (T2D) are complex conditions with significant impacts on health. Patients with psoriasis have a higher risk of T2D (∼1.5 OR) and vice versa, controlling for body mass index; yet, there has been a limited study comparing their genetic architecture. [https://www.selleckchem.com/products/vy-3-135.html VY-3-135 inhibitor] We hypothesized that there are shared genetic components between psoriasis and T2D. Trans-disease meta-analysis was applied to 8,016,731 well-imputed genetic markers from large-scale meta-analyses of psoriasis (11,024 cases and 16,336 controls) and T2D (74,124 cases and 824,006 controls), adjusted for body mass index. We confirmed our findings in a hospital-based study (42,112 patients) and tested for causal relationships with multivariable Mendelian randomization. Mendelian randomization identified a causal relationship between psoriasis and T2D (P = 1.6 × 10‒4, OR = 1.01) and highlighted the impact of body mass index. Trans-disease meta-analysis further revealed four genome-wide significant loci (P less then 5 × 10‒8) with evidence of colocalization and shared directions of effect between psoriasis and T2D not present in body mass index.