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The percentage of White residents in the urban core increased during the last three decades. Meanwhile, urban school choice policies have changed school enrollment processes. Scholars must examine how White residents navigate school choice in this context to understand why racial segregation persists. We study White parents in a city with changing demographics and system-wide school choice. We use an exit, voice, and loyalty (EVL) framework to understand White parents' values and procedures. We find White parents weigh exit more than voice, and disloyalty is the norm. These findings suggest the enrollment ecosystem's norms perpetuate school racial segregation.

Although more is known about how general parenting practices predict social-emotional strengths in children, less research has looked at parent involvement in education and children's social-emotional strengths. This study examined the extent to which parent involvement, specifically home-based involvement, parent-teacher trust, and home-school communication, predicted children's social-emotional strengths in kindergarten. The study featured both parent (n = 120) and teacher ratings (n = 156) of children's social-emotional strengths. We examined the association between parent involvement and social emotional strengths while controlling for child age and gender, socioeconomic status, and general parenting (positive verbal discipline and harsh/inconsistent discipline). Parents' reports of home-based involvement were a moderate to strong positive predictor of their child's social-emotional strengths over the kindergarten year. For teacher ratings of social-emotional strengths, parents' trust of the teacher was associated with higher social-emotional strengths. The findings may inform essential components in parenting or school-based interventions for social-emotional development, as well as differences in what parents and teachers perceive as related to social-emotional development in young children.

The specific focus of this study is how a team of four preservice teachers experienced a collaborative practicum model to support the development of cogenerative dialogue and foster professional growth. Data sources included individual video club annotations and the associated group discussions facilitated by comparison of groups members selected annotations. The analysis found that participation in peer collaboration provided multiple viewpoints of shared teaching experiences that enabled preservice teachers' different ways to notice student thinking. Providing a structured framework for reflection, namely the individual video club annotations, served as the genesis for cogenerative dialogues centered on instructional change for the preservice teachers. This work's implications showcase the importance of allowing for the iterative enactment and reflection on pedagogical choices by preservice teachers early in their professional development.

In October 2022, New Brunswick Minister of Education and Early Childhood Development Dominic Cardy publicly resigned and widely disclosed his disappointment with Premier Blaine Higgs' leadership. Using Cardy's unprecedented public resignation letter as a primary source, this paper explores the inner workings of neoliberal governance and privatization in public education and critically analyzes data manipulation, governance shifts, and problematic conservative "hands-offism." Applying a rhizomatic methodological framing and theoretically drawing from Bourdieu and Passeron's (1977) conceptualization of symbolic violence and Gilmore's (2008) notion of "organized abandonment," we argue that neoliberal governance and privatization disproportionately affect vulnerable communities and weaken democratic processes. To understand these complexities, we utilize a rhizomatic analysis, simultaneously considering historical and geographical contexts, governance structures, and political narratives. We conclude that neoliberal governance and privatization are inherently symbolically violent, as they are used in tandem to perpetually defund and dismantle public institutions.

BACKGROUND: Infection with the COVID-19-causing pathogen SARS-CoV-2 is associated with disruption in the human gut microbiome. The gut microbiome enables protection against diverse pathogens and exhibits dysbiosis during infectious and autoimmune disease. Studies based in the United States and China have found that severe COVID-19 cases have altered gut microbiome composition when compared to mild COVID-19 cases. We present the first study to investigate the gut microbiome composition of COVID-19 cases in a population from Sub-Saharan Africa. Given the impact of geography and cultural traditions on microbiome composition, it is important to investigate the microbiome globally and not draw broad conclusions from homogenous populations. RESULTS: We used stool samples in a Ugandan biobank collected from COVID-19 cases during 2020-2022. We profiled the gut microbiomes of 83 symptomatic individuals who tested positive for SARS-CoV-2 along with 43 household contacts who did not present any symptoms of COVID-19. The inclusion of healthy controls enables us to generate hypotheses about bacterial strains potentially related to susceptibility to COVID-19 disease, which is highly heterogeneous. Comparison of the COVID-19 patients and their household contacts revealed decreased alpha diversity and blooms of Enterococcus and Eggerthella in COVID-19 cases. CONCLUSIONS: Our study finds that the microbiome of COVID-19 individuals is more likely to be disrupted, as indicated by decreased diversity and increased pathobiont levels. This is either a consequence of the disease or may indicate that certain microbiome states increase susceptibility to COVID-19 disease. Our findings enable comparison with cohorts previously published in the Global North, as well as support new hypotheses about the interaction between the gut microbiome and SARS-CoV-2 infection.

Introduction: Emergency cricothyrotomy is a rare but potentially life-saving procedure performed by emergency physicians. A comprehensive, dichotomous procedural checklist for emergency cricothyrotomy for emergency medicine (EM) resident education does not exist.Objectives: We aimed to develop a checklist containing the critical steps for performing an open emergency cricothyrotomy, to assess performance of EM residents performing an open emergency cricothyrotomy using the checklist on a simulator, and to evaluate the reliability and validity of the checklist for performing the procedure.Curricular Design: We developed a preliminary checklist based on literature review and sent it to experts in EM and trauma surgery. A modified Delphi approach was used to revise the checklist and reach consensus on a final version of the checklist. To assess usability of the checklist, we assessed EM residents using a cricothyrotomy task trainer. Scores were determined by the number of correctly performed items. We calculated inter-rater reliability using the Cohen kappa coefficient. Validity was assessed using the Welch t-test to compare the performance of residents who had and had not performed an open emergency cricothyrotomy, and we used analysis of variance to compare performance of postgraduate year (PGY) cohorts.Impact/Effectiveness: The final 27-item checklist was developed after three rounds of revisions. Inter-rater reliability was strong overall (κ = 0.812) with individual checklist items ranging from slight to nearly perfect agreement. A total of 56 residents participated, with an average score of 14.3 (52.9%). Performance varied significantly among PGY groups (P < 0.001). Residents who had performed an emergency cricothyrotomy previously performed significantly better than those who had not (P = 0.005). The developed checklist, which can be used in procedural training for open emergency cricothyrotomy, suggests that improved training approaches to teaching and assessing emergency cricothyrotomy are needed given the overall poor performance of this cohort.

Hemodialysis for chronic kidney disease (CKD) relies on vascular access (VA) devices, such as arteriovenous fistulas (AVF), grafts (AVG), or catheters, to maintain blood flow. Nonetheless, unpredictable progressive vascular stenosis due to neointimal formation or complete occlusion from acute thrombosis remains the primary cause of mature VA failure. Despite emergent surgical intervention efforts, the lack of a reliable early detection tool significantly reduces patient outcomes and survival rates. This study introduces a soft, wearable device that continuously monitors blood flow for early detection of VA failure. Using thermal anemometry, integrated sensors noninvasively measure flow changes in large vessels. Bench testing with AVF and AVG models shows agreement with finite element analysis (FEA) simulations, while human and preclinical swine trials demonstrate the devices sensitivity. Wireless adaptation could enable at-home monitoring, improving detection of VA-related complications and survival in CKD patients.

We conduct a harmonized lifecycle greenhouse gas assessment to compare the carbon removal efficiency and total energy required for twelve engineered carbon removal technologies.

A significant challenge on an exascale computer is the speed at which we compute results exceeds by many orders of magnitude the speed at which we save these results. Therefore the Exascale Computing Project (ECP) ALPINE project focuses on providing exascale-ready visualization solutions including in situ processing. In situ visualization and analysis runs as the simulation is run, on simulations results are they are generated avoiding the need to save entire simulations to storage for later analysis. The ALPINE project made post hoc visualization tools, ParaView and VisIt, exascale ready and developed in situ algorithms and infrastructures. The suite of ALPINE algorithms developed under ECP includes novel approaches to enable automated data analysis and visualization to focus on the most important aspects of the simulation. Many of the algorithms also provide data reduction benefits to meet the I/O challenges at exascale. ALPINE developed a new lightweight in situ infrastructure, Ascent.

The study explored the impact of proficiency, frequency, L1-L2 congruency, and semantic transparency on the knowledge of multi-word units (MWUs) among Iranian L2 learners (N = 256). A gap-filling test was used to assess learners' productive knowledge, employing a high-frequency MWU list created with the lemmatised concgramming method. The list, which included 11,212 MWUs across four frequency levels, was ranked by L1-L2 congruency and semantic transparency. As revealed by regression models with bootstrapping, the results showed a significant positive correlation between MWU knowledge and proficiency (IELTS scores). It was observed that knowledge of MWUs decreased with lower frequency, and participants scored higher on congruent and transparent items. The study also found that frequency and semantic transparency influenced IELTS scores, with a significant interaction between congruency and incongruent items. These findings underscore the crucial role of L1-L2 congruency in learning MWUs and provide hope for educators, as they offer insights to enhance learning by prioritising L1-L2 congruency in English MWU resources. This study's findings can potentially lead to improved language teaching methodologies and curriculum design, offering a pathway to optimise learning outcomes.

LaGuardia Community College in Queens, New York is known for its leadership in assessment practices aimed at improving teaching and learning. Its practices to improve student outcomes include remedial math and composition pathways reforms and establishing signature general education core competencies and communication abilities. Combined together, such practices have helped double the graduation rate over a decade. Until recently, however, assessment data had not been disaggregated for different student demographics. In this article, we describe how we transformed our traditional means of analyzing outcomes data toward one that utilized an equity-driven index for two cohorts of students across major racial and ethnic populations. We examined the data for representational equity and equitable performance. In a key finding, we discovered our ongoing assessment practices do not reflect our student population on both counts, especially as a designated Hispanic Serving Institution. Further, we found other under- and over-representation of racial populations in our general education assessment samples. We conclude by suggesting further areas of inquiry with equity-based assessment and note ongoing challenges to systematizing this approach.

Human Anatomy and Physiology courses are "gateway" courses that students must pass with high grades in order to proceed through their program of study. However, student pass rates are often low, resulting in students attempting the course multiple times and delaying their graduation. Supplemental instruction performed by peer leaders is one mechanism that has been used to increase student success. The goal of this study was to evaluate the effectiveness of peer-led supplemental instruction by comparing predicted and actual course grades. We learned that students predicted to earn a C achieved higher grades when they utilized supplemental instruction. While those students performed better than predicted, supplemental instruction did not improve ABC rates for the class. We conclude that supplemental instruction can be of benefit for some students.

Standardized patient encounters are being utilized more often in occupational therapy education as a replacement for traditional fieldwork. While there is a growing body of research to support the use of this model in developing student skillsets and confidence, there remains limited information on the topic, and no studies which look at its use with occupational therapy assistant students. Twenty-four occupational therapy assistant students participated in standardized patient encounters which served as a replacement for traditional Level I fieldwork. All students completed an anonymous supplementary course evaluation regarding their experiences. A secondary analysis of the data looked at their perceptions of a standardized patient encounter model for fieldwork and how it did or did not prepare them for future Level II clinicals. Quantitative and qualitative data exposed aspects of these experiences which students found to be most and least effective. Overall, data showed moderate support for use of standardized patient encounters to support student confidence and skills in anticipation of Level II fieldwork. The student perception of these types of experiences is influenced by environmental (e.g., structure) and personal (e.g., student personality) factors. Success requires adequate preparation of all involved parties. Use of standardized patient encounters should be researched further to determine its impact on fieldwork performance evaluation scores and future employment.

The recent expansion in Black suburbanization is the most substantial shift in Black American residential patterns since the Great Migration. It has left Blacks more sorted between urban and suburban neighborhoods across metropolitan areas. This study explores whether this increasing residential stratification is associated with differentiation in Blacks' political views on racialized issues. I first lay out a theory of Black political sorting by place, specifying processes inherent in suburbanization that could lead to opinion stratification between suburban and urban Blacks. This is followed by a descriptive analysis of American Voices Project interviews with suburban and urban Black respondents. The data show Black suburbanization is neither as economically transformative nor politically differentiating as might be expected. Despite subtle opinion differences between suburban and urban respondents, they mostly converge in their bleak assessments of racialized issues.

Climate change is expected to increase short-run shocks and extreme events in oceanic conditions. Fishery managers are considering how to design climate-ready systems that enable fishers and fishing communities to adapt to these events without jeopardizing the long-run sustainability of the ocean ecosystem. This paper highlights a suite of potential policy options already employed by fishery managers worldwide. Although these options have been designed to address unique conditions in particular settings, it is valuable to understand whether and how they might be extrapolated to other settings to increase fishers’ adaptive capacity. We demonstrate that adaptive capacity depends on what constitutes a fishery and discuss how managers can increase adaptive capacity across internal and external margins conditional on a fishery's definition. We contribute to the literature on climate-ready fisheries by expanding the discussion on adaptive capacity to include both internal and external margins, whereas the literature has focused on external margins for reducing barriers to entry. We also discuss the scientific and political economy challenges and trade-offs of introducing adaptive capacity into the US fishery management system. Ultimately, the benefits of doing so must be weighed against the risks of compromising a highly prescriptive system critical for achieving fishery sustainability.

This chapter argues for the centrality of spirituality in lifelong and adult learning theory and practice. As embedded in human experience, the spirituality of learning, including exploring awe and wonder, is vital. We introduce the processes and outcomes of lifelong spiritual formation, profound learning, and human flourishing as underpinnings for a theoretical, spirituality-based framework.

Data visualization literacy is "the ability and skill to read and interpret visually represented data in and to extract information from data visualizations" and is an emerging literacy type. Even though support exists for data literacy and data visualization use within the academic professions, limited research assessing data visualization literacy skills has been published. This study surveys participants recruited from the 56 institutions with ALA-accredited information programs using Visualization Literacy Assessment Tool (VLAT) content directly from the original test instrument. The results of this study indicate that information science students may possess data visualization literacy skills but have gaps in relation to specific types of data visualizations.

Despite increasing recognition of the importance of high-quality school leadership, we know remarkably little about principal skill development. Using administrative data from Tennessee, Oregon, and New York City, we estimate the returns to principal experience as measured by student outcomes, teacher hiring and retention patterns, and teacher and supervisor ratings of principals. The typical principal leads a school for only 3 to 5 years and leaves the principalship after 6 to 7 years. We find little evidence that school performance improves as principals gain experience, despite substantial improvement in supervisor ratings. Our results suggest that strategies intended to increase principal retention are unlikely to improve school outcomes absent more comprehensive efforts to strengthen the link between principal skill development and student and school outcomes.

Educational researchers have pointed to socioemotional dimensions of learning as important in gaining a more nuanced description of student engagement and learning. However, to date, research focused on the analysis of emotions has been narrow in its focus, centering on affect and sentiment analysis in isolation while neglecting how emotions potentially interact with social elements and course objectives in learning environments. In this paper, we present a case study analysis of seven asynchronous online discussions delivered as part of a blended-learning bachelor level course; we demonstrate the utility of a novel analysis workflow and visualization method which we refer to as SSEEN (social sentiment embedded epistemic networks) to uncover insights into the connection between social networks, course content, and detected student sentiment. The findings show that negative sentiment was most often associated with course content, but contrary to insights from prior research, negative sentiment served as a marker of engagement as students connected content to their own personal experiences. By simultaneously considering the social network alongside the sentiment-colored edges, we note that negative sentiment is not consistent within the discourse of particular students or between pairs indicating that sentiment did not appear to be an indicator of peer conflict or breaches in social contracts. The findings demonstrate how the proposed approach (SSEEN) can support educational researchers to gain a more nuanced understanding of the social, emotional, and epistemic dimensions of learning in asynchronous online discussions.

Background and aimsTropical forests exchange more carbon dioxide (CO2) with the atmosphere than any other terrestrial biome. Yet, uncertainty in the projected carbon balance over the next century is roughly three-times greater for the tropics than other ecosystems. Our limited knowledge of tropical plant physiological responses, including photosynthetic, to climate change is a substantial source of uncertainty in our ability to forecast the global terrestrial carbon sink.MethodsWe used a meta-analytic approach, focusing on tropical photosynthetic temperature responses, to address this knowledge gap. Our dataset, gleaned from 18 independent studies, included leaf-level light saturated photosynthetic (Asat) temperature responses from 108 woody species, with additional temperature parameters (35 species) and rates (250 species) of both maximum rates of electron transport (Jmax) and Rubisco carboxylation (Vcmax). We investigated how these parameters responded to mean annual temperature (MAT), temperature variability, aridity, and elevation, as well as also how responses differed among successional strategy, leaf habit, and light environment.Key resultsOptimum temperatures for Asat (ToptA) and Jmax (ToptJ) increased with MAT but not for Vcmax (ToptV). Although photosynthetic rates were higher for "light" than "shaded" leaves, light conditions did not generate differences in temperature response parameters. ToptA did not differ with successional strategy, but early successional species had ~4 °C wider thermal niches than mid/late species. Semi-deciduous species had ~1 °C higher ToptA than broadleaf evergreen. Most global modeling efforts consider all tropical forests as a single "broadleaf evergreen" functional type, but our data show that tropical species with different leaf habits display distinct temperature responses that should be included in modeling efforts.ConclusionsThis novel research will inform modeling efforts to quantify tropical ecosystem carbon cycling and provide more accurate representations of how these key ecosystems will respond to altered temperature patterns in the face of climate warming.

PurposeThe California National Primate Research Center contains a colony of rhesus macaques with a homozygous missense mutation in PDE6C (R565Q) which causes a cone disorder similar to PDE6C achromatopsia in humans. The purposes of this study are to characterize the phenotype in PDE6C macaques in detail to determine the onset of the cone phenotype, the degree to which the phenotype progresses, if heterozygote animals have an intermediate phenotype, and if rod photoreceptor function declines over time.MethodsWe analyzed spectral-domain optical coherence tomography (SD-OCT), fundus autofluorescence (FAF), and electroretinography (ERG) data from 102 eyes of 51 macaques (aged 0.25 to 16 years). Measurements of retinal layers as well as cone and rod function over time were quantitatively compared.ResultsHomozygotes as young as 3 months postnatal showed absent cone responses on electroretinogram. Infant homozygotes had reduced foveal outer nuclear layer (ONL) thickness compared with wildtype infants (P < 0.0001). Over 4 years of study, no consistent changes in retinal layer thicknesses were found within 5 adult homozygotes. However, comparisons between infants and adults revealed reductions in foveal ONL thickness suggesting that cone cells slowly degenerate as homozygotes age. The oldest homozygote (11 years) had reduced rod responses. Heterozygotes could not be distinguished from wildtypes in any parameters.ConclusionsThese data suggest that, like humans, macaque PDE6C heterozygotes are normal, and homozygote primates have absent cone function and reduced foveal ONL thickness from infancy. Cone photoreceptors probably degenerate over time and macular atrophy can occur. Rod photoreceptor function may wane in late stages.

With the increasing availability of large-scale multimodal neuroimaging datasets, it is necessary to develop data fusion methods which can extract cross-modal features. A general framework, multidataset independent subspace analysis (MISA), has been developed to encompass multiple blind source separation approaches and identify linked cross-modal sources in multiple datasets. In this work, we utilized the multimodal independent vector analysis (MMIVA) model in MISA to directly identify meaningful linked features across three neuroimaging modalities-structural magnetic resonance imaging (MRI), resting state functional MRI and diffusion MRI-in two large independent datasets, one comprising of control subjects and the other including patients with schizophrenia. Results show several linked subject profiles (sources) that capture age-associated decline, schizophrenia-related biomarkers, sex effects, and cognitive performance. For sources associated with age, both shared and modality-specific brain-age deltas were evaluated for association with non-imaging variables. In addition, each set of linked sources reveals a corresponding set of cross-modal spatial patterns that can be studied jointly. We demonstrate that the MMIVA fusion model can identify linked sources across multiple modalities, and that at least one set of linked, age-related sources replicates across two independent and separately analyzed datasets. The same set also presented age-adjusted group differences, with schizophrenia patients indicating lower multimodal source levels. Linked sets associated with sex and cognition are also reported for the UK Biobank dataset.

Leaf dark respiration (Rdark), an important yet rarely quantified component of carbon cycling in forest ecosystems, is often simulated from leaf traits such as the maximum carboxylation capacity (Vcmax), leaf mass per area (LMA), nitrogen (N) and phosphorus (P) concentrations, in terrestrial biosphere models. However, the validity of these relationships across forest types remains to be thoroughly assessed. Here, we analyzed Rdark variability and its associations with Vcmax and other leaf traits across three temperate, subtropical and tropical forests in China, evaluating the effectiveness of leaf spectroscopy as a superior monitoring alternative. We found that leaf magnesium and calcium concentrations were more significant in explaining cross-site Rdark than commonly used traits like LMA, N and P concentrations, but univariate trait-Rdark relationships were always weak (r2 ≤ 0.15) and forest-specific. Although multivariate relationships of leaf traits improved the model performance, leaf spectroscopy outperformed trait-Rdark relationships, accurately predicted cross-site Rdark (r2 = 0.65) and pinpointed the factors contributing to Rdark variability. Our findings reveal a few novel traits with greater cross-site scalability regarding Rdark, challenging the use of empirical trait-Rdark relationships in process models and emphasize the potential of leaf spectroscopy as a promising alternative for estimating Rdark, which could ultimately improve process modeling of terrestrial plant respiration.

The gut microbiota produces high concentrations of antimicrobial short-chain fatty acids (SCFAs) that restrict the growth of invading microorganisms. The enteric pathogen Salmonella enterica serovar (S.) Typhimurium triggers inflammation in the large intestine to ultimately reduce microbiota density and bloom, but it is unclear how the pathogen gains a foothold in the homeostatic gut when SCFA-producing commensals are abundant. Here, we show that S. Typhimurium invasion of the ileal mucosa triggers malabsorption of dietary amino acids to produce downstream changes in nutrient availability in the large intestine. In gnotobiotic mice engrafted with a community of 17 human Clostridia isolates, S. Typhimurium virulence factors triggered marked changes in the cecal metabolome, including an elevated abundance of amino acids. In an ex vivo fecal culture model, we found that two of these amino acids, lysine and ornithine, countered SCFA-mediated growth inhibition by restoring S. Typhimurium pH homeostasis through the inducible amino acid decarboxylases CadA and SpeF, respectively. In a mouse model of gastrointestinal infection, S. Typhimurium CadA activity depleted dietary lysine to promote cecal ecosystem invasion in the presence of an intact microbiota. From these findings, we conclude that virulence factor-induced malabsorption of dietary amino acids in the small intestine changes the nutritional environment of the large intestine to provide S. Typhimurium with resources needed to counter growth inhibition by microbiota-derived SCFAs.

Healthcare facilities produce millions of tons of waste annually, with a significant portion consisting of diagnostic plasticware. Here, we introduce a new detection platform that completely replaces traditional assay plates with a piece of membrane, offering a much greener and more sustainable alternative. The membrane, integrated within the portable vortex fluidic device (P-VFD), enables rapid detection of a clinically relevant protein biomarker, urinary p75ECD. This biomarker is utilized to evaluate the prognosis, disease severity, and progression of amyotrophic lateral sclerosis (ALS). This assay has a limit-of-detection (LOD) of 4.03 pg, which is comparable to the plate-based assay (2.24 pg) and has been optimised through a full factorial design of experiments (DOE) and response surface methodology (RSM). P-VFD has great potential in quantifying p75ECD in human biofluids and can significantly reduce the assay time to 5 min compared to the current plate-based p75ECD ELISA assay (3 days), with at least a 4.4-fold reduction in the usage of the detection antibody.

Treatment of the tumor and dural margin with surgery and sometimes radiation are cornerstones of therapy for meningioma. Molecular classifications have provided insights into the biology of disease; however, response to treatment remains heterogeneous. In this study, we used retrospective data on 2,824 meningiomas, including molecular data on 1,686 tumors and 100 prospective meningiomas, from the RTOG-0539 phase 2 trial to define molecular biomarkers of treatment response. Using propensity score matching, we found that gross tumor resection was associated with longer progression-free survival (PFS) across all molecular groups and longer overall survival in proliferative meningiomas. Dural margin treatment (Simpson grade 1/2) prolonged PFS compared to no treatment (Simpson grade 3). Molecular group classification predicted response to radiotherapy, including in the RTOG-0539 cohort. We subsequently developed a molecular model to predict response to radiotherapy that discriminates outcome better than standard-of-care classification. This study highlights the potential for molecular profiling to refine surgical and radiotherapy decision-making.

Previous studies have reported alterations in cortical thickness in autism. However, few have included enough autistic females to determine if there are sex specific differences in cortical structure in autism. This longitudinal study aimed to investigate autistic sex differences in cortical thickness and trajectory of cortical thinning across childhood. Participants included 290 autistic (88 females) and 139 nonautistic (60 females) individuals assessed at up to 4 timepoints spanning ~2-13 years of age (918 total MRI timepoints). Estimates of cortical thickness in early and late childhood as well as the trajectory of cortical thinning were modeled using spatiotemporal linear mixed effects models of age-by-sex-by-diagnosis. Additionally, the spatial correspondence between cortical maps of sex-by-diagnosis differences and neurotypical sex differences were evaluated. Relative to their nonautistic peers, autistic females had more extensive cortical differences than autistic males. These differences involved multiple functional networks, and were mainly characterized by thicker cortex at ~3 years of age and faster cortical thinning in autistic females. Cortical regions in which autistic alterations were different between the sexes significantly overlapped with regions that differed by sex in neurotypical development. Autistic females and males demonstrated some shared differences in cortical thickness and rate of cortical thinning across childhood relative to their nonautistic peers, however these areas were relatively small compared to the widespread differences observed across the sexes. These results support evidence of sex-specific neurobiology in autism and suggest that processes that regulate sex differentiation in the neurotypical brain contribute to sex differences in the etiology of autism.

Milk oligosaccharides are complex carbohydrates composed of various monosaccharide units linked together by glycosidic bonds. They play an essential role in promoting gut health by fostering beneficial bacteria, supporting the development of the immune system, and protecting against infections and diseases. This work compared the oligosaccharide profiles in widely utilized breeds such as Holstein and Ayrshire (Nordic Red), with the native Northern Finncattle, which is considered an endangered breed. Oligosaccharides were extracted from milk and analyzed by liquid chromatography-mass spectrometry. The composition and relative abundance of the identified oligosaccharides were characterized and compared. The statistical analyses showed that neutral, sialylated, and fucosylated oligosaccharides vary among the breeds. Ayrshire and Northern Finncattle oligosaccharides formed a cluster, while Holsteins profile shared features with both Ayrshire and Northern Finncattle. Holstein had the lowest abundance of fucosylated OS among the three breeds, with Ayrshire having the highest content followed by Northern Finncattle. The relatively higher sialylated over neutral content of Northern Finncattle is an important feature that should be preserved. Ayrshire is a good candidate to recover more diverse oligosaccharides with potential gut health implications for consumers.

The COVID-19 pandemic has challenged the current paradigm of clinical and community-based disease detection. We present a multimodal wearable sensor system paired with a two-minute, movement-based activity sequence that successfully captures a snapshot of physiological data (including cardiac, respiratory, temperature, and percent oxygen saturation). We conducted a large, multi-site trial of this technology across India from June 2021 to April 2022 amidst the COVID-19 pandemic (Clinical trial registry name: International Validation of Wearable Sensor to Monitor COVID-19 Like Signs and Symptoms; NCT05334680; initial release: 04/15/2022). An Extreme Gradient Boosting algorithm was trained to discriminate between COVID-19 infected individuals (n = 295) and COVID-19 negative healthy controls (n = 172) and achieved an F1-Score of 0.80 (95% CI = [0.79, 0.81]). SHAP values were mapped to visualize feature importance and directionality, yielding engineered features from core temperature, cough, and lung sounds as highly important. The results demonstrated potential for data-driven wearable sensor technology for remote preliminary screening, highlighting a fundamental pivot from continuous to snapshot monitoring of cardiorespiratory illnesses.

Autism spectrum disorder (ASD) is a neurodevelopmental disorder (NDD) that affects approximately 4% of males and 1% of females in the United States. While causes of ASD are multi-factorial, single rare genetic variants contribute to around 20% of cases. Here, we report a case series of seven unrelated probands (6 males, 1 female) with ASD or another variable NDD phenotype attributed to de novo heterozygous loss of function or missense variants in the gene LARP1 (La ribonucleoprotein 1). LARP1 encodes an RNA-binding protein that post-transcriptionally regulates the stability and translation of thousands of mRNAs, including those regulating cellular metabolism and metabolic plasticity. Using lymphocytes collected and immortalized from an index proband who carries a truncating variant in one allele of LARP1, we demonstrated that lower cellular levels of LARP1 protein cause reduced rates of aerobic respiration and glycolysis. As expression of LARP1 increases during neurodevelopment, with higher levels in neurons and astrocytes, we propose that LARP1 haploinsufficiency contributes to ASD or related NDDs through attenuated metabolic activity in the developing fetal brain.

Despite showing the greatest primate diversity on the planet, genomic studies on Amazonian primates show very little representation in the literature. With 48 geolocalized high coverage whole genomes from wild uakari monkeys, we present the first population-level study on platyrrhines using whole genome data. In a very restricted range of the Amazon rainforest, eight uakari species (Cacajao genus) have been described and categorized into the bald and black uakari groups, based on phenotypic and ecological differences. Despite a slight habitat overlap, we show that posterior to their split 0.92 Mya, bald and black uakaris have remained independent, without gene flow. Nowadays, these two groups present distinct genetic diversity and group-specific variation linked to pathogens. We propose differing hydrology patterns and effectiveness of geographic barriers have modulated the intra-group connectivity and structure of bald and black uakari populations. With this work we have explored the effects of the Amazon rainforests dynamism on wild primates genetics and increased the representation of platyrrhine genomes, thus opening the door to future research on the complexity and diversity of primate genomics.

Large stocks of soil carbon (C) and nitrogen (N) in northern permafrost soils are vulnerable to remobilization under climate change. However, there are large uncertainties in present-day greenhouse gas (GHG) budgets. We compare bottom-up (data-driven upscaling and process-based models) and top-down (atmospheric inversion models) budgets of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) as well as lateral fluxes of C and N across the region over 2000–2020. Bottom-up approaches estimate higher land-to-atmosphere fluxes for all GHGs. Both bottom-up and top-down approaches show a sink of CO2 in natural ecosystems (bottom-up: −29 (−709, 455), top-down: −587 (−862, −312) Tg CO2-C yr−1) and sources of CH4 (bottom-up: 38 (22, 53), top-down: 15 (11, 18) Tg CH4-C yr−1) and N2O (bottom-up: 0.7 (0.1, 1.3), top-down: 0.09 (−0.19, 0.37) Tg N2O-N yr−1). The combined global warming potential of all three gases (GWP-100) cannot be distinguished from neutral. Over shorter timescales (GWP-20), the region is a net GHG source because CH4 dominates the total forcing. The net CO2 sink in Boreal forests and wetlands is largely offset by fires and inland water CO2 emissions as well as CH4 emissions from wetlands and inland waters, with a smaller contribution from N2O emissions. Priorities for future research include the representation of inland waters in process-based models and the compilation of process-model ensembles for CH4 and N2O. Discrepancies between bottom-up and top-down methods call for analyses of how prior flux ensembles impact inversion budgets, more and well-distributed in situ GHG measurements and improved resolution in upscaling techniques.

Cough is an important symptom in children with acute and chronic respiratory disease. Daily cough is common in Cystic Fibrosis (CF) and increased cough is a symptom of pulmonary exacerbation. To date, cough assessment is primarily subjective in clinical practice and research. Attempts to develop objective, automatic cough counting tools have faced reliability issues in noisy environments and practical barriers limiting long-term use. This single-center pilot study evaluated usability, acceptability and performance of a mechanoacoustic sensor (MAS), previously used for cough classification in adults, in 36 children with CF over brief and multi-day periods in four cohorts. Children whose health was at baseline and who had symptoms of pulmonary exacerbation were included. We trained, validated, and deployed custom deep learning algorithms for accurate cough detection and classification from other vocalization or artifacts with an overall area under the receiver-operator characteristic curve (AUROC) of 0.96 and average precision (AP) of 0.93. Child and parent feedback led to a redesign of the MAS towards a smaller, more discreet device acceptable for daily use in children. Additional improvements optimized power efficiency and data management. The MASs ability to objectively measure cough and other physiologic signals across clinic, hospital, and home settings is demonstrated, particularly aided by an AUROC of 0.97 and AP of 0.96 for motion artifact rejection. Examples of cough frequency and physiologic parameter correlations with participant-reported outcomes and clinical measurements for individual patients are presented. The MAS is a promising tool in objective longitudinal evaluation of cough in children with CF.

Manufacturing workers face prolonged strenuous physical activities, impacting both financial aspects and their health due to work-related fatigue. Continuously monitoring physical fatigue and providing meaningful feedback is crucial to mitigating human and monetary losses in manufacturing workplaces. This study introduces a novel application of multimodal wearable sensors and machine learning techniques to quantify physical fatigue and tackle the challenges of real-time monitoring on the factory floor. Unlike past studies that view fatigue as a dichotomous variable, our central formulation revolves around the ability to predict multilevel fatigue, providing a more nuanced understanding of the subjects physical state. Our multimodal sensing framework is designed for continuous monitoring of vital signs, including heart rate, heart rate variability, skin temperature, and more, as well as locomotive signs by employing inertial motion units strategically placed at six locations on the upper body. This comprehensive sensor placement allows us to capture detailed data from both the torso and arms, surpassing the capabilities of single-point data collection methods. We developed an innovative asymmetric loss function for our machine learning model, which enhances prediction accuracy for numerical fatigue levels and supports real-time inference. We collected data on 43 subjects following an authentic manufacturing protocol and logged their self-reported fatigue. Based on the analysis, we provide insights into our multilevel fatigue monitoring system and discuss results from an in-the-wild evaluation of actual operators on the factory floor. This study demonstrates our systems practical applicability and contributes a valuable open-access database for future research.