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College students' mental health concerns have dramatically increased in prevalence and severity over the past decade, overwhelming the capacity of counseling centers to meet demand for services. In response, institutions of higher education (IHEs) increasingly emphasize prevention, education, and outreach efforts aimed at improving well-being. Although this focus has prompted an increase in research on student well-being, few studies have investigated the unique contributions of malleable psychosocial factors on student outcomes. This study aims to address this gap in the literature by examining the relative impact of an array of psychosocial factors--adaptive and maladaptive perfectionism, coping self-efficacy, social connectedness, perceived burdensomeness, grit, resilience, and meaning in life--on academic performance and distress and suicidality in a sample of 7505 students from 15 U.S. IHEs. Controlling for institutional selectivity and non-malleable aspects of students' identities and pre-college experiences, facets of perfectionism, grit, and emotion-focused coping self-efficacy were the psychosocial factors most strongly associated with GPA, and perceived burdensomeness, social connectedness, emotion-focused coping self-efficacy, and resilience were most strongly associated with distress and suicidality. Among non-malleable factors, race/ethnicity explained the most variance in GPA and gender identity explained the most variance in distress and suicidality. Results are discussed in light of persistent, identity-based disparities in academic achievement and suicide risk and the potential of psychosocial factors as intervention targets to improve academic performance and reduce suicide risk.

Abstract CT is crucial for diagnosing chest diseases, with image quality affected by spatial resolution. Thick-slice CT remains prevalent in practice due to cost considerations, yet its coarse spatial resolution may hinder accurate diagnoses. Our multicenter study develops a deep learning synthetic model with Convolutional-Transformer hybrid encoder-decoder architecture for generating thin-slice CT from thick-slice CT on a single center (1576 participants) and access the synthetic CT on three cross-regional centers (1228 participants). The qualitative image quality of synthetic and real thin-slice CT is comparable (p = 0.16). Four radiologists’ accuracy in diagnosing community-acquired pneumonia using synthetic thin-slice CT surpasses thick-slice CT (p 0.99). For lung nodule detection, sensitivity with thin-slice CT outperforms thick-slice CT (p 0.05). These findings indicate the potential of our model to generate high-quality synthetic thin-slice CT as a practical alternative when real thin-slice CT is preferred but unavailable.

Abstract In tasks involving human health condition data, feature selection is heavily affected by data types, the complexity of the condition manifestation, and the variability in physiological presentation. One type of variability often overlooked or oversimplified is the effect of biological sex. As females have been chronically underrepresented in clinical research, we know less about how conditions manifest in females. Innovations in wearable technology have enabled individuals to generate high temporal resolution data for extended periods of time. With millions of days of data now available, additional feature selection pipelines should be developed to systematically identify sex-dependent variability in data, along with the effects of how many per-person data are included in analysis. Here we present a set of statistical approaches as a technique for identifying sex-dependent physiological and behavioral manifestations of complex diseases starting from longitudinal data, which are evaluated on diabetes, hypertension, and their comorbidity.

Abstract Acute myeloid leukemia (AML) is a deadly hematopoietic malignancy. Although many patients achieve complete remission with standard induction therapy, a combination of cytarabine and anthracycline, ~40% of patients have induction failure. These refractory patients pose a treatment challenge, as they do not respond to salvage therapy or allogeneic stem cell transplant. Herein, we show that AML patients who experience induction failure have elevated expression of the NF-κB target gene tumor necrosis factor alpha-induced protein-3 (TNFAIP3/A20) and impaired necroptotic cell death. A20High AML are resistant to anthracyclines, while A20Low AML are sensitive. Loss of A20 in AML restores sensitivity to anthracycline treatment by inducing necroptosis. Moreover, A20 prevents necroptosis in AML by targeting the necroptosis effector RIPK1, and anthracycline-induced necroptosis is abrogated in A20High AML. These findings suggest that NF-κB-driven A20 overexpression plays a role in failed chemotherapy induction and highlights the potential of targeting an alternative cell death pathway in AML.

Abstract The United States has seen increasing trends of maternal mortality in recent years. Within this health crisis there are large disparities whereby underserved and minoritized populations are bearing a larger burden of maternal morbidity and mortality. While new interventions to improve maternal health are being developed, there are opportunities for greater integration of existing evidence-based interventions into routine practice, especially for underserved populations, including those residing in maternity care deserts. In fact, over 80 percent of maternal deaths are preventable with currently available interventions. To spur equitable implementation of existing interventions, the National Heart, Lung, and Blood Institute launched the Maternal-Health Community Implementation Program (MH-CIP) in 2021. In 2023, the National Institutes of Health’s Implementing a Maternal health and PRegnancy Outcomes Vision for Everyone (IMPROVE) initiative partnered with the NHLBI to launch the IMPROVE Community Implementation Program (IMPROVE-CIP). By design, CIPs engage disproportionately impacted communities and partner with academic researchers to conduct implementation research. This commentary overviews the impetus for creating these programs, program goals, structure, and offers a high-level overview of the research currently supported. Lastly, the potential outcomes of these programs are contextualized within the landscape of maternal health initiatives in the United States.

Abstract Objective This study aimed to evaluate the association of dynamic contrast enhancement (DCE) with clinically significant prostate cancer (csPCa, Gleason Grade Group ≥2) and compare biparametric magnetic resonance imaging (bpMRI) and multiparametric MRI (mpMRI) nomograms. Subjects/patients and methods We identified a retrospective cohort of biopsy naïve patients who underwent pre‐biopsy MRI separated by individual MRI series from 2018 to 2022. csPCa detection rates were calculated for patients with peripheral zone (PZ) lesions scored 3–5 on diffusion weighted imaging (DWI) with available DCE (annotated as − or +). bpMRI Prostate Imaging Reporting and Data System (PIRADS) (3 = 3−, 3+; 4 = 4−, 4+; 5 = 5−, 5+) and mpMRI PIRADS (3 = 3−; 4 = 3+, 4−, 4+; 5 = 5−, 5+) approaches were compared in multivariable logistic regression models. Nomograms for detection of csPCa and ≥GG3 PCa incorporating all biopsy naïve patients who underwent prostate MRI were generated based on available serum biomarkers [PHI, % free prostate‐specific antigen (PSA), or total PSA] and validated with an independent cohort. Results Patients (n = 1010) with highest PIRADS lesion in PZ were included in initial analysis with 127 (12.6%) classified as PIRADS 3+ (PIRADS 3 on bpMRI but PIRADS 4 on mpMRI). On multivariable analysis, PIRADS 3+ lesions were associated with higher csPCa rates compared to PIRADS 3− (3+ vs. 3−: OR 1.86, p = 0.024), but lower csPCa rates compared to PIRADS DWI 4 lesions (4 vs. 3+: OR 2.39, p

Early differences in sensory responsiveness may contribute to difficulties with communication among autistic children; however, this theory has not been longitudinally assessed in infants at increased familial versus general population-level likelihood for autism (Sibs-autism vs. Sibs-NA) using a comprehensive battery of sensory responsiveness and communication. In a sample of 40 infants (20 Sibs-autism, of whom six were later diagnosed with autism; 20 Sibs-NA), we tested (a) associations between sensory responsiveness at 12-18 months and communication 9 months later and (b) evaluated whether such associations were moderated by sibling group, autism diagnosis, or age. We found negative zero-order correlations between sensory responsiveness (i.e., caregiver reported hyperresponsiveness and hyporesponsiveness; an observational measure of hyperresponsiveness) and later communication. Additionally, caregiver reported sensory seeking was negatively associated with later expressive communication only in Sibs-NA. Limitations include our relatively small sample size of infants diagnosed with autism. Implications for future research are discussed.

Analyzing three sets of video data collected in one Maya community, we examined apprenticeship and learning of backstrap loom weaving over three generations spanning the years 1970 to 2012. Like many cultural groups, the Maya of Chiapas are experiencing rapid sociodemographic shifts. Three generations of girls (N = 134) were observed at their looms: in the 1970 subsistence economy; in the transition to a commercial economy in the 1990s; and in 2012, when the commercial economy required formal education. Multilevel models showed that intergenerational sociodemographic change -- increased time in school, greater involvement in the money economy, and decreased family size -- changed weaving apprenticeship, which, in turn, was related to changes in characteristics of learners. In 2012, weaving learners received more explanations, praise, and body instruction from their teachers. Learners, in turn, asked more questions. However, these changes came at a cost -- the gradual loss of weaving as an everyday subsistence practice and art form. Tracing intergenerational change over three generations, this study makes a unique contribution to an understanding of cultural evolution.

We suggest that a healthy literacy diet for beginning readers consists of literacy experiences along a number of dimensions, including experiences with decodable text. As such, this article explores the role of decodable texts in a comprehensive early literacy curriculum that recognizes literacy as a complex, culturally mediated, and multifaceted set of skills. We provide five guidelines for practitioners to use when evaluating decodable texts to be used with beginning readers. As an example of the type of analysis we recommend for selecting quality decodable text, we examine one decodable text for its merit in fulfilling the guidelines described in this article.

A greater understanding of molecular, cellular, and immunological changes during the early stages of lung adenocarcinoma development could improve diagnostic and therapeutic approaches in patients with pulmonary nodules at risk for lung cancer. To elucidate the immunopathogenesis of early lung tumorigenesis, we evaluated surgically resected pulmonary nodules representing the spectrum of early lung adenocarcinoma as well as associated normal lung tissues using single-cell RNA sequencing and validated the results by flow cytometry and multiplex immunofluorescence (MIF). Single-cell transcriptomics revealed a significant decrease in gene expression associated with cytolytic activities of tumor-infiltrating natural killer and natural killer T cells. This was accompanied by a reduction in effector T cells and an increase of CD4+ regulatory T cells (Treg) in subsolid nodules. An independent set of resected pulmonary nodules consisting of both adenocarcinomas and associated premalignant lesions corroborated the early increment of Tregs in premalignant lesions compared with the associated normal lung tissues by MIF. Gene expression analysis indicated that cancer-associated alveolar type 2 cells and fibroblasts may contribute to the deregulation of the extracellular matrix, potentially affecting immune infiltration in subsolid nodules through ligand-receptor interactions. These findings suggest that there is a suppression of immune surveillance across the spectrum of early-stage lung adenocarcinoma.SignificanceAnalysis of a spectrum of subsolid pulmonary nodules by single-cell RNA sequencing provides insights into the immune regulation and cell-cell interactions in the tumor microenvironment during early lung tumor development.

ObjectiveTo examine the effectiveness of a workplace sugar-sweetened beverage (SSB) sales ban on reducing SSB consumption in employees, including those with cardiometabolic disease risk factors.DesignA controlled trial of ethnically diverse, full-time employees who consumed SSB heavily (sales ban n 315; control n 342). Outcomes included standardised measures of change in SSB consumption in the workplace (primary) and at home between baseline and 6 months post-sales ban.SettingSutter Health, a large non-profit healthcare delivery system in Northern California.ParticipantsFull-time employees at Sutter Health screened for heavy SSB consumption.ResultsParticipants were 66·1 % non-White. On average, participants consumed 34·7 ounces (about 1 litre) of SSB per d, and the majority had an elevated baseline BMI (mean = 29·5). In adjusted regression analyses, those exposed to a workplace SSB sales ban for 6 months consumed 2·7 (95 % CI -4·9, -0·5) fewer ounces of SSB per d while at work, and 4·3 (95 % CI -8·4, -0·2) fewer total ounces per d, compared to controls. Sales ban participants with an elevated BMI or waist circumference had greater post-intervention reductions in workplace SSB consumption.ConclusionsWorkplace sales bans can reduce SSB consumption in ethnically diverse employee populations, including those at higher risk for cardiometabolic disease.

What is the role of scholars in envisioning the continent and bearing witness to historic events? This paper is based on an interview with Professor Rene Lemarchand, renowned scholar of the former Belgian colonies of the African Great Lakes. His earliest book Political Awakening in the Belgian Congo is based on fieldwork conducted in 1960 as the country was undergoing decolonization and describes the political crises of early independence. In the 1970s, he explored the concept of clientelism and role of ethnicity in Central Africa. As events unfolded in Burundi and Rwanda, Lemarchand became an expert on genocide. His career an Africanist has been devoted to understanding political violence in Central Africa while envisioning a better future for its people. The piece will explore reflections not only on his long career, but also its contribution to our understanding of the history of ethnic violence and genocide in the Great Lakes and beyond. Keywords: Burundi, Congo, genocide, Great Lakes, Rwanda,, Introduction In 2005, I began my doctorate in political science at the University of Florida, which I had chosen because of its impressive Center for African Studies with over 100 [...]

Abstract Climate change alters the sources and age of carbon in Arctic food webs by fostering the release of older carbon from degrading permafrost. Radiocarbon (14C) traces carbon sources and age, but data before rapid warming are rare and limit assessments over time. We capitalized on 14C data collected ~ 40 years ago that used fish as natural samplers by resampling the same species today. Among resampled fish, those using freshwater food webs had the oldest 14C ages (> 1000 yr BP), while those using marine food webs had the youngest 14C ages (near modern). One migratory species encompassed the entire range of 14C ages because juveniles fed in freshwater streams and adults fed in offshore marine habitats. Over ~ 40 yr, average 14C ages of freshwater and marine feeding fish shifted closer to atmospheric values, suggesting a potential influence from “greening of the Arctic.”

Abstract Continued spread of chronic wasting disease (CWD) through wild cervid herds negatively impacts populations, erodes wildlife conservation, drains resource dollars, and challenges wildlife management agencies. Risk factors for CWD have been investigated at state scales, but a regional model to predict locations of new infections can guide increasingly efficient surveillance efforts. We predicted CWD incidence by county using CWD surveillance data depicting white-tailed deer (Odocoileus virginianus) in 16 eastern and midwestern US states. We predicted the binary outcome of CWD-status using four machine learning models, utilized five-fold cross-validation and grid search to pinpoint the best model, then compared model predictions against the subsequent year of surveillance data. Cross validation revealed that the Light Boosting Gradient model was the most reliable predictor given the regional data. The predictive model could be helpful for surveillance planning. Predictions of false positives emphasize areas that warrant targeted CWD surveillance because of similar conditions with counties known to harbor CWD. However, disagreements in positives and negatives between the CWD Prediction Web App predictions and the on-the-ground surveillance data one year later underscore the need for state wildlife agency professionals to use a layered modeling approach to ensure robust surveillance planning. The CWD Prediction Web App is at https://cwd-predict.streamlit.app/ .

Abstract Sleep monitoring has become widespread with the rise of affordable wearable devices. However, converting sleep data into actionable change remains challenging as diverse factors can cause combinations of sleep parameters to differ both between people and within people over time. Researchers have attempted to combine sleep parameters to improve detecting similarities between nights of sleep. The cluster of similar combinations of sleep parameters from a night of sleep defines that night’s sleep phenotype. To date, quantitative models of sleep phenotype made from data collected from large populations have used cross-sectional data, which preclude longitudinal analyses that could better quantify differences within individuals over time. In analyses reported here, we used five million nights of wearable sleep data to test (a) whether an individual’s sleep phenotype changes over time and (b) whether these changes elucidate new information about acute periods of illness (e.g., flu, fever, COVID-19). We found evidence for 13 sleep phenotypes associated with sleep quality and that individuals transition between these phenotypes over time. Patterns of transitions significantly differ (i) between individuals (with vs. without a chronic health condition; chi-square test; p-value

Abstract Mood disorders are an enigmatic class of debilitating illnesses that affect millions of individuals worldwide. While chronic stress clearly increases incidence levels of mood disorders, including major depressive disorder (MDD), stress-mediated disruptions in brain function that precipitate these illnesses remain largely elusive. Serotonin-associated antidepressants (ADs) remain the first line of therapy for many with depressive symptoms, yet low remission rates and delays between treatment and symptomatic alleviation have prompted skepticism regarding direct roles for serotonin in the precipitation and treatment of affective disorders. Our group recently demonstrated that serotonin epigenetically modifies histone proteins (H3K4me3Q5ser) to regulate transcriptional permissiveness in brain. However, this non-canonical phenomenon has not yet been explored following stress and/or AD exposures. Here, we employed a combination of genome-wide and biochemical analyses in dorsal raphe nucleus (DRN) of male and female mice exposed to chronic social defeat stress, as well as in DRN of human MDD patients, to examine the impact of stress exposures/MDD diagnosis on H3K4me3Q5ser dynamics, as well as associations between the mark and depression-related gene expression. We additionally assessed stress-induced/MDD-associated regulation of H3K4me3Q5ser following AD exposures, and employed viral-mediated gene therapy in mice to reduce H3K4me3Q5ser levels in DRN and examine its impact on stress-associated gene expression and behavior. We found that H3K4me3Q5ser plays important roles in stress-mediated transcriptional plasticity. Chronically stressed mice displayed dysregulated H3K4me3Q5ser dynamics in DRN, with both AD- and viral-mediated disruption of these dynamics proving sufficient to attenuate stress-mediated gene expression and behavior. Corresponding patterns of H3K4me3Q5ser regulation were observed in MDD subjects on vs. off ADs at their time of death. These findings thus establish a neurotransmission-independent role for serotonin in stress-/AD-associated transcriptional and behavioral plasticity, observations of which may be of clinical relevance to human MDD and its treatment.