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Adult learners are a significant proportion of distance learners and many of these students are working mothers. Several instructional design models center the learner, and this requires understanding the learner needs, strengths, and context. There is a gap in the literature describing the experience of modern working mother students in distance education. To understand this experience, the researchers interviewed and observed six academically high-achieving working mother students as they participated in their distance education courses during the pandemic. A discourse analysis approach was utilized to analyze the data. This extreme sample revealed several strategies that these students used to be successful despite their challenges. The findings suggest that understanding the experiences of distance learners as they study in the home are important for effective course design. More specifically, working mothers face significant distractions in their study environments, but the cognitive load can be reduced by making use of their prior knowledge, scaffolding instruction, and encouraging social presence. Additional strategies from the literature that address these constructs are provided for instructors and instructional designers.

Positive transition to adulthood of youth with disabilities is influenced by the type of support they receive. This study aims to analyse current transition to adulthood practices in the province of Quebec to map them to recommended practices and present an overview of the situation and needs. A multiple case study methodology included focus groups in six schools with 65 participants as well as internet searches and interviews with experts. A thematic analysis within and across cases was used. Results underscore the best practices in place concerning student-focused planning, student development, interagency collaboration and family engagement. They also highlight youths' and parents' opinions about strategies to better support transition. While inspiring practices are present, further efforts with regards to programme structures are required to ensure adequate support for transition to adulthood.

This paper advocates reading philosophy and using its concepts in educational and social science research. The lengthy engagement with the various concepts and conceptual orders of poststructuralism required for post qualitative inquiry exceeds the scope of reading required for a conventional literature review at the beginning of a typical empirical research project. Reading that spans many years of an academic career does not serve the epistemological project of stabilizing what is known through recognition, representation, and summary but attends to an ontological project of re-orienting thought through experimentation, invention, and creation to enable what does not yet exist but might.

Adults are skilled at using language to construct/negotiate identity and to signal affiliation with others, but little is known about how these abilities develop in children. Clearly, children mirror statistical patterns in their local environment (e.g., Canadian children using "zed" instead of "zee"), but do they flexibly adapt their linguistic choices on the fly in response to the choices of different peers? To address this question, we examined the effect of group membership on 7- to 9-year-olds' labeling of objects in a trivia game, exploring whether they were more likely to use a particular label (e.g., "sofa" vs. "couch") if members of their "team" also used that label. In a preregistered study, children (N = 72) were assigned to a team (red or green) and were asked during experimental trials to answer questions--which had multiple possible answers (e.g., "blackboard" or "chalkboard")--after hearing two teammates and two opponents respond to the same question. Results showed that children were significantly more likely to produce labels less commonly used by the community (i.e., dispreferred labels) when their teammates had produced those labels. Crucially, this effect was tied to group membership, and could not be explained by children simply repeating the most recently used label. These findings demonstrate how social processes (i.e., group membership) can guide linguistic variation in children.

OBJECTIVE: To estimate direct and indirect costs associated with neuropsychiatric (NP) events in the Systemic Lupus International Collaborating Clinics inception cohort. METHODS: NP events were documented annually using American College of Rheumatology definitions for NP events and attributed to systemic lupus erythematosus (SLE) or non-SLE causes. Patients were stratified into 1 of 3 NP states (no, resolved, or new/ongoing NP event). Change in NP status was characterized by interstate transition rates using multistate modeling. Annual direct costs and indirect costs were based on health care use and impaired productivity over the preceding year. Annual costs associated with NP states and NP events were calculated by averaging all observations in each state and adjusted through random-effects regressions. Five- and 10-year costs for NP states were predicted by multiplying adjusted annual costs per state by expected state duration, forecasted using multistate modeling. RESULTS: A total of 1,697 patients (49% White race/ethnicity) were followed for a mean of 9.6 years. NP events (n = 1,971) occurred in 956 patients, 32% attributed to SLE. For SLE and non-SLE NP events, predicted annual, 5-, and 10-year direct costs and indirect costs were higher in new/ongoing versus no events. Direct costs were 1.5-fold higher and indirect costs 1.3-fold higher in new/ongoing versus no events. Indirect costs exceeded direct costs 3.0 to 5.2 fold. Among frequent SLE NP events, new/ongoing seizure disorder and cerebrovascular disease accounted for the largest increases in annual direct costs. For non-SLE NP events, new/ongoing polyneuropathy accounted for the largest increase in annual direct costs, and new/ongoing headache and mood disorder for the largest increases in indirect costs. CONCLUSION: Patients with new/ongoing SLE or non-SLE NP events incurred higher direct and indirect costs.

Type 2 cytokines like IL-4 are hallmarks of helminth infection and activate macrophages to limit immunopathology and mediate helminth clearance. In addition to cytokines, nutrients and metabolites critically influence macrophage polarization. Choline is an essential nutrient known to support normal macrophage responses to lipopolysaccharide; however, its function in macrophages polarized by type 2 cytokines is unknown. Using murine IL-4-polarized macrophages, targeted lipidomics revealed significantly elevated levels of phosphatidylcholine, with select changes to other choline-containing lipid species. These changes were supported by the coordinated up-regulation of choline transport compared to naïve macrophages. Pharmacological inhibition of choline metabolism significantly suppressed several mitochondrial transcripts and dramatically inhibited select IL-4-responsive transcripts, most notably, Retnla. We further confirmed that blocking choline metabolism diminished IL-4-induced RELMα (encoded by Retnla) protein content and secretion and caused a dramatic reprogramming toward glycolytic metabolism. To better understand the physiological implications of these observations, naïve or mice infected with the intestinal helminth Heligmosomoides polygyrus were treated with the choline kinase α inhibitor, RSM-932A, to limit choline metabolism in vivo. Pharmacological inhibition of choline metabolism lowered RELMα expression across cell-types and tissues and led to the disappearance of peritoneal macrophages and B-1 lymphocytes and an influx of infiltrating monocytes. The impaired macrophage activation was associated with some loss in optimal immunity to H. polygyrus, with increased egg burden. Together, these data demonstrate that choline metabolism is required for macrophage RELMα induction, metabolic programming, and peritoneal immune homeostasis, which could have important implications in the context of other models of infection or cancer immunity.

A vexing observation in genome-wide association studies (GWASs) is that parallel analyses in different species may not identify orthologous genes. Here, we demonstrate that cross-species translation of GWASs can be greatly improved by an analysis of co-localization within molecular networks. Using body mass index (BMI) as an example, we show that the genes associated with BMI in humans lack significant agreement with those identified in rats. However, the networks interconnecting these genes show substantial overlap, highlighting common mechanisms including synaptic signaling, epigenetic modification, and hormonal regulation. Genetic perturbations within these networks cause abnormal BMI phenotypes in mice, too, supporting their broad conservation across mammals. Other mechanisms appear species specific, including carbohydrate biosynthesis (humans) and glycerolipid metabolism (rodents). Finally, network co-localization also identifies cross-species convergence for height/body length. This study advances a general paradigm for determining whether and how phenotypes measured in model species recapitulate human biology.

OBJECTIVES: A novel longitudinal clustering technique was applied to comprehensive autoantibody data from a large, well-characterised, multinational inception systemic lupus erythematosus (SLE) cohort to determine profiles predictive of clinical outcomes. METHODS: Demographic, clinical and serological data from 805 patients with SLE obtained within 15 months of diagnosis and at 3-year and 5-year follow-up were included. For each visit, sera were assessed for 29 antinuclear antibodies (ANA) immunofluorescence patterns and 20 autoantibodies. K-means clustering on principal component analysis-transformed longitudinal autoantibody profiles identified discrete phenotypic clusters. One-way analysis of variance compared cluster enrolment demographics and clinical outcomes at 10-year follow-up. Cox proportional hazards model estimated the HR for survival adjusting for age of disease onset. RESULTS: Cluster 1 (n=137, high frequency of anti-Smith, anti-U1RNP, AC-5 (large nuclear speckled pattern) and high ANA titres) had the highest cumulative disease activity and immunosuppressants/biologics use at year 10. Cluster 2 (n=376, low anti-double stranded DNA (dsDNA) and ANA titres) had the lowest disease activity, frequency of lupus nephritis and immunosuppressants/biologics use. Cluster 3 (n=80, highest frequency of all five antiphospholipid antibodies) had the highest frequency of seizures and hypocomplementaemia. Cluster 4 (n=212) also had high disease activity and was characterised by multiple autoantibody reactivity including to antihistone, anti-dsDNA, antiribosomal P, anti-Sjögren syndrome antigen A or Ro60, anti-Sjögren syndrome antigen B or La, anti-Ro52/Tripartite Motif Protein 21, antiproliferating cell nuclear antigen and anticentromere B). Clusters 1 (adjusted HR 2.60 (95% CI 1.12 to 6.05), p=0.03) and 3 (adjusted HR 2.87 (95% CI 1.22 to 6.74), p=0.02) had lower survival compared with cluster 2. CONCLUSION: Four discrete SLE patient longitudinal autoantibody clusters were predictive of long-term disease activity, organ involvement, treatment requirements and mortality risk.

BackgroundQuantitative Trait Locus (QTL) analysis and Genome-Wide Association Studies (GWAS) have the power to identify variants that capture significant levels of phenotypic variance in complex traits. However, effort and time are required to select the best methods and optimize parameters and pre-processing steps. Although machine learning approaches have been shown to greatly assist in optimization and data processing, applying them to QTL analysis and GWAS is challenging due to the complexity of large, heterogenous datasets. Here, we describe proof-of-concept for an automated machine learning approach, AutoQTL, with the ability to automate many complicated decisions related to analysis of complex traits and generate solutions to describe relationships that exist in genetic data.ResultsUsing a publicly available dataset of 18 putative QTL from a large-scale GWAS of body mass index in the laboratory rat, Rattus norvegicus, AutoQTL captures the phenotypic variance explained under a standard additive model. AutoQTL also detects evidence of non-additive effects including deviations from additivity and 2-way epistatic interactions in simulated data via multiple optimal solutions. Additionally, feature importance metrics provide different insights into the inheritance models and predictive power of multiple GWAS-derived putative QTL.ConclusionsThis proof-of-concept illustrates that automated machine learning techniques can complement standard approaches and have the potential to detect both additive and non-additive effects via various optimal solutions and feature importance metrics. In the future, we aim to expand AutoQTL to accommodate omics-level datasets with intelligent feature selection and feature engineering strategies.

Villains are disproportionately voiced with foreign accents in children’s media (Lippi-Green, 1997), and previous work has shown that children do indeed associate foreign accents with villains (St. Pierre & Johnson, 2022). Here, we investigate whether short-term exposure to foreign-accented heroes can mitigate this association. First, 7- to 9-year-old children (current n=112) watched a series of cartoon clips featuring either foreign-accented heroes or foreign-accented villains. Then, participants watched new clips in which foreign- and native-accented voice actors each performed both a hero and villain, and selected which character they thought each voice was best suited for. Preliminary results show that children were less likely to associate foreign accents with villains after exposure to foreign-accented heroes (compared to foreign-accented villains). These findings demonstrate how strongly language biases in children’s media can impact children’s attitudes, and suggest that more mindful programming might help reduce the development of negative social views towards foreign accents.

The acquisition of variation is a fundamental -- but poorly understood -- part of child language acquisition. We fully endorse Shin and Miller's call for us to recognize the importance of this core issue, and argue that our understanding could be further enriched by greater reliance on convergent methods. As such, we implore researchers to consider perception as well as production data, and to consider acquisition across different domains and different populations of children.

ObjectivesA perception derived from cross-sectional studies of small systemic lupus erythematosus (SLE) cohorts is that there is a marked discrepancy between antinuclear antibody (ANA) assays, which impacts on clinicians' approach to diagnosis and follow-up. We compared three ANA assays in a longitudinal analysis of a large international incident SLE cohort retested regularly and followed for 5 years.MethodsDemographic, clinical and serological data was from 805 SLE patients at enrolment, year 3 and 5. Two HEp-2 indirect immunofluorescence assays (IFA1, IFA2), an ANA ELISA, and SLE-related autoantibodies were performed in one laboratory. Frequencies of positivity, titres or absorbance units (AU), and IFA patterns were compared using McNemar, Wilcoxon and kappa statistics, respectively.ResultsAt enrolment, ANA positivity (≥1:80) was 96.1% by IFA1 (median titre 1:1280 (IQR 1:640-1:5120)), 98.3% by IFA2 (1:2560 (IQR 1:640-1:5120)) and 96.6% by ELISA (176.3 AU (IQR 106.4 AU-203.5 AU)). At least one ANA assay was positive for 99.6% of patients at enrolment. At year 5, ANA positivity by IFAs (IFA1 95.2%; IFA2 98.9%) remained high, while there was a decrease in ELISA positivity (91.3%, p91% agreement in ANA positivity at all time points and ≥71% agreement in IFA patterns between IFA1 and IFA2.ConclusionIn recent-onset SLE, three ANA assays demonstrated commutability with a high proportion of positivity and titres or AU. However, over 5 years follow-up, there was modest variation in ANA assay performance. In clinical situations where the SLE diagnosis is being considered, a negative test by either the ELISA or HEp-2 IFA may require reflex testing.

School-to-work transition is a challenging period for youth with learning difficulties (LD). Based on self-determination theory (SDT), we tested the role of autonomy support and motivation in predicting transition status and well-being among this population. This prospective study included 218 students with LD in their last year of a work-study program. They were surveyed at the end of the school year and 1 year later. Two structural equation models were tested: one with the transition status as the outcome and one with well-being. Analyses revealed that autonomy support from fathers was positively associated with autonomous motivation in both models, as was autonomy support from friends in the transition status model. Autonomous motivation positively predicted both outcomes, while controlled motivation negatively predicted them. In sum, the psychological resources proposed by SDT seem to matter for youth with LD, thereby providing support for the generalizability of SDT.

Background & aims: Youth with developmental language disorder (DLD) are at risk of experiencing challenges during their job search. It is thus crucial to promote efficient job search behaviors in terms of effort, intensity, and self-regulation. Based on self-determination theory (SDT), we verified the role of autonomous and controlled motivations in enhancing these behaviors. Methods: Study 1 included 37 young adults with DLD who have finished school, and Study 2 included 52 youth with DLD transitioning from school to work. They completed a questionnaire examining their job search behaviors and their motivation toward their job search. Results: Autonomous motivation positively predicted job search effort, intensity, and self-regulation. Small to moderate relations were observed in Study 1, and moderate to strong ones in Study 2. Controlled motivation was unrelated to the three behaviors. Conclusions: In line with SDT, autonomous motivation is an important foundation for positive job search behaviors among youth with DLD. Implications: Supporting the development of autonomous motivation is thus encouraged in transition services for this population.

The development of science writing and presentation skills is necessary for a successful science career. Too often these skills are not included in pre- or postsecondary science, technology, engineering, and mathematics (STEM) education, leading to a disconnect between high schoolers' expectations for college preparedness and the skills needed to succeed in college. The Young Scientist Program Summer Focus recruits high school students from historically marginalized backgrounds to participate in 8-week summer internships at Washington University in St. Louis. Students conduct hands-on biomedical research projects under the mentorship of Washington University scientists (graduate students, postdoctorates, lab staff). Here, we present the curriculum for a science communication course that accompanies this early research experience. The course is designed to strengthen students' communication skills (critical reading, writing, presenting, and peer review) through a combination of weekly lectures and active learning methods. It prepares students for the capstone of their summer internship: writing a scientific paper and presenting their results at a closing symposium. We administered pre- and postprogram surveys to four Summer Focus cohorts to determine whether the course met its learning objectives. We found significant improvements in students' self-confidence in reading, interpreting, and communicating scientific data. Thus, this course provides a successful model for introducing science literacy and communication skills that are necessary for any career in STEM. We provide a detailed outline of the course structure and content so that this training can be incorporated into any undergraduate and graduate research programs.

Resilience is often invoked to address systemic marginalization (e.g. racism) in academia but inadvertently maintains harmful systems. We argue that the ability to transform systems, as opposed to persevering within them, must be prioritized to make real, lasting change.

Listeners interpret spoken language differently, depending on the perceived identity of the speaker. Within increasingly diverse societies, it is important to understand how speaker characteristics such as accent may impact simple linguistic exchanges. In the current study, children are being tested on their ability to recall factual information provided by native and non-native accented English speakers. Preliminary results demonstrate that children tend to remember neutral facts better if they heard them from a native accented speaker. Interestingly, children understood the native and non-native accented talkers equally well, indicating that comprehension difficulties could not account for the results. To date, there have been no studies examining how a speaker’s accent affects children’s memory, and only preliminary, mixed results in adults have been found. This gap in the literature underscores the need to understand how linguistic biases might impact information transfer across diverse language communities.