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Multisystem inflammatory syndrome in children (MIS-C) is a severe, post-infectious sequela of SARS-CoV-2 infection1,2, yet the pathophysiological mechanism connecting the infection to the broad inflammatory syndrome remains unknown. Here we leveraged a large set of samples from patients with MIS-C to identify a distinct set of host proteins targeted by patient autoantibodies including a particular autoreactive epitope within SNX8, a protein involved in regulating an antiviral pathway associated with MIS-C pathogenesis. In parallel, we also probed antibody responses from patients with MIS-C to the complete SARS-CoV-2 proteome and found enriched reactivity against a distinct domain of the SARS-CoV-2 nucleocapsid protein. The immunogenic regions of the viral nucleocapsid and host SNX8 proteins bear remarkable sequence similarity. Consequently, we found that many children with anti-SNX8 autoantibodies also have cross-reactive T cells engaging both the SNX8 and the SARS-CoV-2 nucleocapsid protein epitopes. Together, these findings suggest that patients with MIS-C develop a characteristic immune response to the SARS-CoV-2 nucleocapsid protein that is associated with cross-reactivity to the self-protein SNX8, demonstrating a mechanistic link between the infection and the inflammatory syndrome, with implications for better understanding a range of post-infectious autoinflammatory diseases.

In this study, we drew on the m(ai)cro framework, which centers racism as a macrosystem, to examine how college-going emerging adults made meaning about society and themselves during the 2020 U.S. presidential election and 2021 inauguration. This period was marked by racial justice protests, a global pandemic, anti-Asian violence, and the storming of the U.S. Capitol by predominantly white Trump supporters. Using the constructs of critical consciousness and racial identity meaning making, we analyzed participants' reports of recent race related conversations. Our sample included 47 students (M[subscript age] = 19.71, SD = 1.72; 81% female, 17% male, 2% other; 45% Asian/Asian American, 30% white, 13% Latinx/Hispanic, 4% Black/African American, 4% Multiracial, 2% Middle Eastern/Arab) at a private, predominantly white university in the U.S. Midwest. Hybrid inductive-deductive analysis showed that a majority reported conversations with peers, focused primarily on racial inequity and justice. For many participants of color, conversations about topics including protests and anti-Asian violence were woven into their racial identities. In contrast, although many white participants discussed events such as the Capitol insurrection, none made links to their racial identities. Our findings highlight connections between critical consciousness and racial identity, and the importance of context and participant positionality in developmental research.

Best practice for the assessment of autism spectrum disorder (ASD) symptom severity relies on clinician ratings of the Autism Diagnostic Observation Schedule, 2nd Edition (ADOS-2), but the association of these ratings with objective measures of children's social gaze and smiling is unknown. Sixty-six preschool-age children (49 boys, M = 39.97 months, SD = 10.58) with suspected ASD (61 confirmed ASD) were administered the ADOS-2 and provided social affect calibrated severity scores (SA CSS). Children's social gaze and smiling during the ADOS-2, captured with a camera contained in eyeglasses worn by the examiner and parent, were obtained via a computer vision processing pipeline. Children who gazed more at their parents (p = 0.04) and whose gaze at their parents involved more smiling (p = 0.02) received lower social affect severity scores, indicating fewer social affect symptoms, adjusted R[superscript 2] = 0.15, p = 0.003.

This article examines the phenomenon whereby ‘professionalism’ is used as a concept in higher education (HE), specifically regarding HE’s relationships with professions in science, technology, engineering and mathematics (STEM). We examine the implications for human development arising from the influence of professionalism in HE, presenting the qualitative interpretations of second-career academics, a term we use to describe university teaching staff recruited for their prior industrial experience in STEM professions. Using a phenomenographic approach, we examine the conception of second-career academics and how professionalism influences educational policy and practice in HE. We present four successively inclusive conceptions of experiences, with professionalism expressed as making normative judgements of students’ interactions and behaviours, negotiating those interactions and behaviours with students, critiquing the professional applicability of curricula and activities, and changing those curricula and activities to suit the needs of STEM professions. These conceptions expose challenges related to policy and practice and the roles undertaken by second-career academics, including their enculturation of students into the normative expectations of STEM professions, their influence on the apparent correspondence between HE and work in STEM, and their marketing of STEM professions inside HE.

Abstract Background Malaria is the leading cause of hospitalizations and death in Uganda, particularly in children under the age of five. Studies have shown that adherence to the World Health Organization (WHO) guidelines for the management of severe malaria reduces mortality in hospitalized children. This study aimed to determine the impact of targeted interventions on adherence to the WHO severe malaria treatment guidelines in children at a Ugandan hospital as part of a quality improvement initiative. Methods Interventions included workflow changes, such as obtaining patient blood samples for diagnostic testing by the admitting healthcare provider as well as utilizing patient caregivers to assist nursing staff in timing medications. An additional intervention was the use of an admission checklist sticker. The post-intervention sample was compared to the baseline assessment. The primary outcome was the proportion of patients receiving care consistent with all aspects of the WHO guidelines. Secondary outcomes included the proportion of patients receiving malaria diagnostic testing, those receiving at least 3 doses of artesunate, the timely administration of artesunate, and adherence to other guideline components. Statistical analyses were conducted using GraphPad PRISM 9.0. Comparisons between groups were analysed using Chi-square or Fisher’s exact test for categorical variables and Mann–Whitney test for continuous variables. Results The post-intervention group included 230 patients with a median age of 5 years [4–8], and 58% of patients were male. Adherence to all aspects of the WHO guidelines was achieved in 10% of patients in the post-intervention group compared to 3% of patients in the baseline (P = 0.007). Appropriate malaria diagnostic testing was performed in 85% of patients post-intervention compared to 66% of patients in the baseline (P

Learner agency, often understood in terms of self-direction and negotiated engagement, is considered important in technical and vocational education and training (TVET). Yet nurturing and supporting agency is resource-intensive and difficult. In this paper, we consider learner agency for online TVET--a setting where content delivery models can be experienced as stultifying. We document the design and evaluation of specific task designs using the method and principle of double-stimulation, where prompts help participants to reconceptualise problematic situations and break out of conflicting motives. We draw on data from a research-intervention with adult learners undertaking a facilities management diploma online, while working. We explore how, across nine online workshops, task designs engendered transformative agency: the ability to collaboratively diverge from instructional intent, question dilemmatic conditions, and propose and enact change. We claim (1) that specific double-stimulation tasks encouraged participants to engage in understanding institutional practice, exposing conflict, and enacting change; (2) that participants came to view their own problematic conditions as stimuli for resistance, criticism, and development; and (3) that online resources were crucial for highlighting evidence of failure and learners' potential roles in change. Our findings are of importance to help learners set and evaluate their own learning agendas.

Abstract Background Although the COVID-19 pandemic has persisted for over 3 years, reinfections with SARS-CoV-2 are not well understood. We aim to characterize reinfection, understand development of Long COVID after reinfection, and compare severity of reinfection with initial infection. Methods We use an electronic health record study cohort of over 3 million patients from the National COVID Cohort Collaborative as part of the NIH Researching COVID to Enhance Recovery Initiative. We calculate summary statistics, effect sizes, and Kaplan–Meier curves to better understand COVID-19 reinfections. Results Here we validate previous findings of reinfection incidence (6.9%), the occurrence of most reinfections during the Omicron epoch, and evidence of multiple reinfections. We present findings that the proportion of Long COVID diagnoses is higher following initial infection than reinfection for infections in the same epoch. We report lower albumin levels leading up to reinfection and a statistically significant association of severity between initial infection and reinfection (chi-squared value: 25,697, p-value:

A randomized controlled trial established initial efficacy of a novel parent training (PT) intervention for improving oral hygiene and oral health in underserved children with ASD (Fenning et al., 2022), a population at risk for unmet dental needs. The present study describes our emic approach to PT development alongside treatment outcome data examining feasibility, acceptability, and engagement. Families with Medicaid-eligible children with ASD ages 3 to 13 years (85% male, 62% with intellectual disability) were assigned to receive PT (n = 60) or a psychoeducational toolkit (n = 59). Results indicate strong retention, fidelity, and adherence, with quantitative and qualitative metrics revealing high treatment satisfaction and utilization. Discussion focuses on implications for individualizing treatment to optimize engagement of underrepresented families.

Background and hypothesisChildren exposed to socioenvironmental adversities (eg, urbanicity, pollution, neighborhood deprivation, crime, and family disadvantage) are more likely to subsequently develop subclinical psychotic experiences during adolescence (eg, hearing voices, paranoia). However, the pathways through which this occurs have not been previously investigated. We hypothesized that cognitive ability and inflammation would partly explain this association.Study designData were utilized from the Environmental-Risk Longitudinal Twin Study, a cohort of 2232 children born in 1994-1995 in England and Wales and followed to age 18. Socioenvironmental adversities were measured from birth to age 10 and classified into physical risk (defined by high urbanicity and air pollution) and socioeconomic risk (defined by high neighborhood deprivation, neighborhood disorder, and family disadvantage). Cognitive abilities (overall, crystallized, fluid, and working memory) were assessed at age 12; and inflammatory markers (C-reactive protein, interleukin-6, soluble urokinase plasminogen activator receptor) were measured at age 18 from blood samples. Participants were interviewed at age 18 regarding psychotic experiences.Study resultsHigher physical risk and socioeconomic risk were associated with increased odds of psychotic experiences in adolescence. The largest mediation pathways were from socioeconomic risk via overall cognitive ability and crystallized ability, which accounted for ~11% and ~19% of the association with psychotic experiences, respectively. No statistically significant pathways were found via inflammatory markers in exploratory (partially cross-sectional) analyses.ConclusionsCognitive ability, especially crystallized ability, may partly explain the association between childhood socioenvironmental adversity and adolescent psychotic experiences. Interventions to support cognitive development among children living in disadvantaged settings could buffer them against developing subclinical psychotic phenomena.

Summary: Background: While many patients seem to recover from SARS-CoV-2 infections, many patients report experiencing SARS-CoV-2 symptoms for weeks or months after their acute COVID-19 ends, even developing new symptoms weeks after infection. These long-term effects are called post-acute sequelae of SARS-CoV-2 (PASC) or, more commonly, Long COVID. The overall prevalence of Long COVID is currently unknown, and tools are needed to help identify patients at risk for developing long COVID. Methods: A working group of the Rapid Acceleration of Diagnostics-radical (RADx-rad) program, comprised of individuals from various NIH institutes and centers, in collaboration with REsearching COVID to Enhance Recovery (RECOVER) developed and organized the Long COVID Computational Challenge (L3C), a community challenge aimed at incentivizing the broader scientific community to develop interpretable and accurate methods for identifying patients at risk of developing Long COVID. From August 2022 to December 2022, participants developed Long COVID risk prediction algorithms using the National COVID Cohort Collaborative (N3C) data enclave, a harmonized data repository from over 75 healthcare institutions from across the United States (U.S.). Findings: Over the course of the challenge, 74 teams designed and built 35 Long COVID prediction models using the N3C data enclave. The top 10 teams all scored above a 0.80 Area Under the Receiver Operator Curve (AUROC) with the highest scoring model achieving a mean AUROC of 0.895. Included in the top submission was a visualization dashboard that built timelines for each patient, updating the risk of a patient developing Long COVID in response to clinical events. Interpretation: As a result of L3C, federal reviewers identified multiple machine learning models that can be used to identify patients at risk for developing Long COVID. Many of the teams used approaches in their submissions which can be applied to future clinical prediction questions. Funding: Research reported in this RADx® Rad publication was supported by the National Institutes of Health. Timothy Bergquist, Johanna Loomba, and Emily Pfaff were supported by Axle Subcontract: NCATS-STSS-P00438.

Data centralization is increasingly non-viable in the changing landscape of data privacy and data governance. New models of data sharing are needed, in particular when privacy-preserving record linkages (PPRL) are being used to connect data within restricted data enclaves and public open enclaves. We share a privacy-preserving data-sharing infrastructure that employs a linkage honest broker implementation of PPRL connecting structured electronic health record data between the National Center for Advancing Translational Science (NCATS) National Clinical Cohort Collaborative (N3C), a restricted data enclave, with the National Cancer Institute (NCI) Cancer Imaging Archive (TCIA), a public open enclave. In particular we will address: • Data governance models needed when linking data from restricted vs. public enclaves • Specific privacy-preserving consideration when linking to imaging data which contain specific structured data and imaging considerations • Privacy-preserving data aggregation when combining multi-modal data from restricted data enclaves with publicly discoverable imaging data