Children with KD have fewer of the previously described COVID-19-associated KD features with less prominent acute respiratory distress syndrome and shock than children with MIS-C. Conclusion COVID-19 in adults usually includes severe respiratory symptoms and pathology, with a high mortality. It has become apparent that children are infected as easily as adults but are more often asymptomatic and have milder disease because of their immature immune systems. Although children are largely spared from severe respiratory disease, they can present with a SARS-CoV-2-associated MIS-C similar to KD.Introduction.Moraxella bovoculi is frequently isolated from the eyes of cattle with infectious bovine keratoconjunctivitis (IBK; pinkeye). As with M. bovis, which has been causally linked to IBK, M. bovoculi expresses an RTX (repeats in the structural toxin) cytotoxin that is related to M. bovis cytotoxin. Pilin, another pathogenic factor in M. bovis, is required for corneal attachment. Seven antigenically distinct pilin serogroups have been described in M. bovis.Hypothesis/Gap Statement. Multiple different serogroups exist amongst type IV pilin encoded by M. bovis, however, it is not known whether M. bovoculi exhibits a similar degree of diversity in type IV pilin that it encodes.Aim. This study was done to characterize a structural pilin (PilA) encoded by M. bovoculi isolated from cases of IBK to determine if diversity exists amongst PilA sequences.Methodology. Ninety-four isolates of M. bovoculi collected between 2002 and 2017 from 23 counties throughout California and from five counties in four other Western states were evaluated.Results. DNA sequencing and determination of deduced amino acid sequences revealed ten (designated groups A through J) unique PilA sequences that were ~96.1-99.3 % identical. Pilin groups A and C matched previously reported putative PilA sequences from M. bovoculi isolated from IBK-affected cattle in the USA (Virginia, Nebraska, and Kansas) and Asia (Kazakhstan). The ten pilin sequences identified were only ~74-76 % identical to deduced amino acid sequences of putative pilin proteins identified from the previously reported whole-genome sequences of M. bovoculi derived from deep nasopharyngeal swabs of IBK-asymptomatic cattle.Conclusions. Compared to the diversity reported between structural pilin proteins amongst different serogroups of M. selleck inhibitor bovis, M. bovoculi PilA from geographically diverse isolates derived from IBK-affected cattle are more conserved.2020 was the year when microbiology burst onto the world stage, not just as the science of small living things, but as the prism through which we understood global events. Clinical logic suffered under pressure arising from an urgent need to confirm or exclude severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection. This is a generation's Hobbesian moment in which the public concern for safety and security from infection outweighs the pursuit of personal freedom. The strangeness of a world in which a minute particle wields superhuman power has generated its list of unlikely heroes and mendacious villains. As the year comes to an end, there are glimmers of light amid the gloom the prospect of an effective vaccine, and life after the pandemic.Discussions about the replicability of psychological studies have primarily focused on improving research methods and practices, with less attention paid to the role of well-specified theories in facilitating the production of reliable empirical results. The field is currently in need of clearly articulated steps to theory specification and development, particularly regarding frameworks that may generalize across different fields of psychology. Here we focus on two approaches to theory specification and development that are typically associated with distinct research traditions computational modeling and construct validation. We outline the points of convergence and divergence between them to illuminate the anatomy of a scientific theory in psychology-what a well-specified theory should contain and how it should be interrogated and revised through iterative theory-development processes. We propose how these two approaches can be used in complementary ways to increase the quality of explanations and the precision of predictions offered by psychological theories.State-sponsored disinformation campaigns increasingly use anti-vaccine comments to not only undermine public health but to also reduce confidence and participation in a democratic society. Despite these dangers, research has not fully explored whether anti-vaccine comments can achieve these effects. To address this gap, an online survey experiment was conducted using a national sample of 1010 U.S. adults. Participants read a mainstream news article discussing the flu vaccine that included random variations of user comments adapted from a documented state-sponsored disinformation campaign. While exposure to anti-vaccine comments did not affect participants' views of vaccines or their willingness to discuss vaccines, participants holding pro-vaccine views reported lower confidence in news organizations and viewed the journalist who authored their article as less credible. These results suggest that anti-vaccine comments may produce effects that align with the goals of state-sponsored disinformation campaigns.This study aimed to identify the predictive capacity of wellness questionnaires on measures of training load using machine learning methods. The distributions of, and dose-response between, wellness and other load measures were also examined, offering insights into response patterns. Data (n= 14,109) were collated from an athlete management systems platform (Catapult Sports, Melbourne, Australia) and were split across three sports (cricket, rugby league and football) with data analysis conducted in R (Version 3.4.3). Wellness (sleep quality, readiness to train, general muscular soreness, fatigue, stress, mood, recovery rating and motivation) as the dependent variable, and sRPE, sRPE-TL and markers of external load (total distance and m.min-1) as independent variables were included for analysis. Classification and regression tree models showed high cross-validated error rates across all sports (i.e., > 0.89) and low model accuracy (i.e., less then 5% of variance explained by each model) with similar results demonstrated using random forest models.