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Although models have been developed for predicting severity of COVID-19 from the medical history of patients, simplified models with good accuracy could be more practical. In this study, we examined utility of simpler models for estimating risk of hospitalization of patients with COVID-19 and mortality of these patients based on demographic characteristics (sex, age, race, median household income based on zip code) and smoking status of 12,347 patients who tested positive at Mass General Brigham centers. The corresponding electronic records were queried (02/26–07/14/2020) to construct derivation and validation cohorts. The derivation cohort was used to fit generalized linear models for estimating risk of hospitalization within 30 days of COVID-19 diagnosis and mortality within approximately 3 months for the hospitalized patients. In the validation cohort, the model resulted in c-statistics of 0.77 [95% CI 0.73–0.80] for hospitalization, and 0.84 [95% CI 0.74–0.94] for mortality among hospitalized patients. Higher risk was associated with older age, male sex, Black ethnicity, lower socioeconomic status, and current/past smoking status. The models can be applied to predict the absolute risks of hospitalization and mortality, and could aid in individualizing the decision making when detailed medical history of patients is not readily available. [ABSTRACT FROM AUTHOR]

Trophic interactions of cave arthropods have been understudied. We used molecular methods (NGS) to decipher the food web in the subterranean ecosystem of the Ardovská Cave (Western Carpathians, Slovakia). We collected five arthropod predators of the species Parasitus loricatus (gamasid mites), Eukoenenia spelaea (palpigrades), Quedius mesomelinus (beetles), and Porrhomma profundum and Centromerus cavernarum (both spiders) and prey belonging to several orders. Various arthropod orders were exploited as prey, and trophic interactions differed among the predators. Linear models were used to compare absolute and relative prey body sizes among the predators. Quedius exploited relatively small prey, while Eukoenenia and Parasitus fed on relatively large prey. Exploitation of eggs or cadavers is discussed. In contrast to previous studies, Eukoenenia was found to be carnivorous. A high proportion of intraguild predation was found in all predators. Intraspecific consumption (most likely cannibalism) was detected only in mites and beetles. Using Pianka's index, the highest trophic niche overlaps were found between Porrhomma and Parasitus and between Centromerus and Eukoenenia, while the lowest niche overlap was found between Parasitus and Quedius. Contrary to what we expected, the high availability of Diptera and Isopoda as a potential prey in the studied system was not corroborated. Our work demonstrates that intraguild diet plays an important role in predators occupying subterranean ecosystems. [ABSTRACT FROM AUTHOR]

The husk—the leaf-like outer covering of maize ear—has multiple functions, including protecting the ear from diseases infection and dehydration. In previous studies, we genotyped an association panel of 508 inbred lines genotyped with a total of ~550,000 SNPs (Illumina 50 K SNP Chip and RNA-seq). Genome-Wide Association Studies (GWAS) were conducted on four husk traits: husk length (HL), husk layer number (HN), husk thickness (HT), and husk width (HW). Minimal associations were identified and none of them passed the P-value threshold after a Bonferroni multiple-test correction using a single locus test in framework of mixed linear model. In this study, we doubled the number of SNPs (~1,250,000 in total) by adding GBS and 600 K SNP Chip. GWAS, performed with the recently developed multiple loci model (BLINK), revealed six genetic loci associated with HN and HT above the Bonferroni multiple-test threshold. Five candidate genes were identified based on the linkage disequilibrium with these loci, including GRMZM2G381691 and GRMZM2G012416. These two genes were up-regulation and down-regulation in all husk related tissues, respectively. GRMZM2G381691 associated with HT encoded a CCT domain protein, which expressed higher in tropical than temperate maize. GRMZM2G012416 associated with HN encoded an Armadillo (ARM) repeat protein, which regulated GA signal pathway. These associated SNPs and candidate genes paved a path to understand the genetic architecture of husk in maize. [ABSTRACT FROM AUTHOR]

Computational models are crucial to studying the encoding of individual neurons. Static models are composed of a fixed set of parameters, thus resulting in static encoding properties that do not change under different inputs. Here, we challenge this basic concept which underlies these models. Using generalized linear models, we quantify the encoding and information processing properties of basal ganglia neurons recorded in-vitro. These properties are highly sensitive to the internal state of the neuron due to factors such as dependency on the baseline firing rate. Verification of these experimental results with simulations provides insights into the mechanisms underlying this input-dependent encoding. Thus, static models, which are not context dependent, represent only part of the neuronal encoding capabilities, and are not sufficient to represent the dynamics of a neuron over varying inputs. Input-dependent encoding is crucial for expanding our understanding of neuronal behavior in health and disease and underscores the need for a new generation of dynamic neuronal models. [ABSTRACT FROM AUTHOR]

Metabolic pathways that are corrupted at early stages of insulin resistance (IR) remain elusive. This study investigates changes in body metabolism in clinically healthy and otherwise asymptomatic subjects that may become apparent already under compromised insulin sensitivity (IS) and prior to IR. 47 clinically healthy Arab male subjects with a broad range of IS, determined by hyperinsulinemic-euglycemic clamp (HIEC), were investigated. Untargeted metabolomics and complex lipidomics were conducted on serum samples collected under fasting and HIEC conditions. Linear models were used to identify associations between metabolites concentrations and IS levels. Among 1896 identified metabolites, 551 showed significant differences between fasting and HIEC, reflecting the metabolic switch in energy utilization. At fasting, 336 metabolites, predominantly di- and tri-acylglycerols, showed significant differences between subjects with low and high levels of IS. Changes in amino acid, carbohydrate and fatty acid metabolism in response to insulin were impaired in subjects with low IS. Association of altered mannose and amino acids with IS was also replicated in an independent cohort of T2D patients. We identified metabolic phenotypes that characterize clinically healthy Arab subjects with low levels of IS at their fasting state. Our study is providing further insights into the metabolic pathways that precede IR. [ABSTRACT FROM AUTHOR]