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Abstract Background Healthcare workers (HCWs) including community health extension workers (CHEWs) in the Federal Capital Territory, Nigeria participated in a hypertension training series following the Extension for Community Healthcare Outcomes (ECHO) model which leverages technology and a practical peer-to-peer learning framework to virtually train healthcare practitioners. We sought to evaluate the patient-level effects of the hypertension ECHO series. Methods HCWs from 12 of 33 eligible primary healthcare centers (PHCs) in the Hypertension Treatment in Nigeria Program (NCT04158154) were selected to participate in a seven-part hypertension ECHO series from August 2022 to April 2023. Concurrent Hypertension Treatment in Nigeria Program patient data were used to evaluate changes in hypertension treatment and control rates, and adherence to Nigeria’s hypertension treatment protocol. Outcomes were compared between the 12 PHCs in the ECHO program and the 21 which were not. Results Between July 2022 and June 2023, 16,691 PHC visits were documented among 4340 individuals (ECHO: n = 1428 [33%], non-ECHO: n = 2912 [67%]). Patients were on average (SD) 51.5 (12.0) years old, and one-third were male (n = 1372, 32%) with no differences between cohorts in either characteristic (p ≥ 0.05 for both). Blood pressures at enrollment were higher in the ECHO cohort compared to the non-ECHO cohort (systolic p

A recently published molecular phylogenetic analysis, focusing on selected Western Atlantic subspecies of Acetes americanus Ortmann, 1893 and allies, was inconclusive about relationships among these members. This previous study found three groups that split into two distinct lineages: Acetes americanus (Brazil 1) (= A. americanus sensu stricto) and Acetes americanus (Brazil 2) + A. americanus (USA). Combined morphometry and molecular analyses applied to members of the group Acetes americanus (Brazil 2) revealed a new unidentified species genetically related to the A. americanus representatives. However, at that time, no conclusive morphological characters were found to identify it. In the present study, following an in-depth morphological analysis of specimens from the three groups, including data on the type series and consideration of the subtle distinctions of members of each lineage, morphological features of the reproductive structures (petasma and genital sternite) were found to characterize the new species, which is formally described and named herein.

Abstract Ceramics and single crystals of LaPO4 monazite doped with Eu(III) were irradiated with 14 MeV Au5+ ions at three different fluences. Changes to crystallinity, local coordination environments, and topography were probed using grazing-incidence X-ray diffraction (GIXRD), vertical scanning interferometry (VSI), scanning electron microscopy (SEM), Raman, and luminescence spectroscopy. GIXRD data of the ceramics revealed fluence dependent amorphization. A similar level of amorphization was detected for samples irradiated with 5 × 1013 ions/cm2 and 1 × 1014 ions/cm2, whereas the sample irradiated with the highest fluence of 1 × 1015 ions/cm2 appeared slightly less amorphous. VSI showed clear swelling of entire grains at the highest ion fluence, while more localized damage to grain boundaries was detected for ceramic samples irradiated at the lowest fluence. Single crystal specimens showed no pronounced topography changes following irradiation. SEM images of the ceramic irradiated at the highest fluence showed topological features indicative of grain surface melting. Raman and luminescence data showed a different degree of disorder in polycrystalline vs. single crystal samples. While changes to PO4 vibrational modes were observed in the ceramics, changes were more subtle or not present in the single crystals. The opposite was observed when probing the local Ln-O environment using Eu(III) luminescence, where the larger changes in terms of an elongation of the Eu-O (or La-O) bond and an increasing relative disorder with increasing fluence were observed only for the single crystals. The dissimilar trends observed in irradiated single crystals and ceramics indicate that grain boundary chemistry likely plays a significant role in the radiation response.

Abstract Background Mosquito-borne diseases, such as malaria, dengue, Zika and chikungunya, pose significant public health threats in tropical and subtropical regions worldwide. To mitigate the impact of these diseases on human health, effective vector surveillance and control strategies are necessary. Traditional vector control methods, which rely on chemical agents such as insecticides and larvicides, face challenges such as resistance and environmental concerns. Consequently, there has been a push to explore novel surveillance and control tools. Mass trapping interventions have emerged as a promising and environmentally friendly approach to reducing the burden of mosquito-borne diseases. This study assessed mass-trapping interventions using autocidal gravid ovitraps (AGOs) on Aedes aegypti populations in Reynosa, Tamaulipas, Mexico. Methods Four neighborhoods were selected to evaluate the effects of three treatments: AGO mass-trapping, integrated vector control (IVC), which included source reduction and the application of chemical larvicide and adulticide, and AGO + IVC on Ae. aegypti populations. A control area with no interventions was also included. The effectiveness of the interventions was evaluated by comparing Ae. aegypti abundance between the pre-treatment period (9 weeks) and the post-treatment period (11 weeks) for each treatment. Results Only treatment using AGO mass trapping with an 84% coverage significantly reduced Ae. aegypti female populations by 47%, from 3.75 ± 0.32 to 1.96 ± 0.15 females/trap/week. As expected, the abundance of Ae. aegypti in the control area did not differ from the pre- and post-treatment period (range of 4.97 ± 0.59 to 5.78 ± 0.53); Ae. aegypti abundance in the IVC treatment was 3.47 ± 0.30 before and 4.13 ± 0.35 after, which was not significantly different. However, Ae. aegypti abundance in the AGO + IVC treatment increased from 1.43 ± 0.21 before to 2.11 ± 0.20 after interventions; this increase may be explained in part by the low AGO (56%) coverage. Conclusions This is the first report to our knowledge on the effectiveness of mass-trapping interventions with AGOs in Mexico, establishing AGOs as a potential tool for controlling Ae. aegypti in Northeastern Mexico when deployed with sufficient coverage. Graphical Abstract

Abstract The Ediacaran-Cambrian transition documents a critical stage in the diversification of animals. The global fossil record documents the appearance of cloudinomorphs and other shelled tubular organisms followed by non-biomineralized small carbonaceous fossils and by the highly diversified small shelly fossils between ~ 550 and 530 Ma. Here, we report diverse microfossils in thin sections and hand samples from the Ediacaran Bocaina Formation, Brazil, separated into five descriptive categories: elongate solid structures (ES); elongate filled structures (EF); two types of equidimensional structures (EQ 1 and 2) and elongate hollow structures with coiled ends (CE). These specimens, interpreted as diversified candidate metazoans, predate the latest Ediacaran biomineralized index macrofossils of the Cloudina-Corumbella-Namacalathus biozone in the overlying Tamengo Formation. Our new carbonate U–Pb ages for the Bocaina Formation, position this novel fossil record at 571 ± 9 Ma (weighted mean age). Thus, our data point to diversification of metazoans, including biomineralized specimens reminiscent of sections of cloudinids, protoconodonts, anabaritids, and hyolithids, in addition to organo-phosphatic surficial coverings of animals, demonstrably earlier than the record of the earliest known skeletonized metazoan fossils.

Abstract Background Brain-derived neurotrophic factor (BDNF) is essential for antidepressant treatment of major depressive disorder (MDD). Our repeated studies suggest that DNA methylation of a specific CpG site in the promoter region of exon IV of the BDNF gene (CpG -87) might be predictive of the efficacy of monoaminergic antidepressants such as selective serotonin reuptake inhibitors (SSRIs), serotonin-norepinephrine reuptake inhibitors (SNRIs), and others. This trial aims to evaluate whether knowing the biomarker is non-inferior to treatment-as-usual (TAU) regarding remission rates while exhibiting significantly fewer adverse events (AE). Methods The BDNF trial is a prospective, randomized, rater-blinded diagnostic study conducted at five university hospitals in Germany. The study’s main hypothesis is that {1} knowing the methylation status of CpG -87 is non-inferior to not knowing it with respect to the remission rate while it significantly reduces the AE rate in patients experiencing at least one AE. The baseline assessment will occur upon hospitalization and a follow-up assessment on day 49 (± 3). A telephone follow-up will be conducted on day 70 (± 3). A total of 256 patients will be recruited, and methylation will be evaluated in all participants. They will be randomly assigned to either the marker or the TAU group. In the marker group, the methylation results will be shared with both the patient and their treating physician. In the TAU group, neither the patients nor their treating physicians will receive the marker status. The primary endpoints include the rate of patients achieving remission on day 49 (± 3), defined as a score of ≤ 10 on the Hamilton Depression Rating Scale (HDRS-24), and the occurrence of AE. Ethics and dissemination The trial protocol has received approval from the Institutional Review Boards at the five participating universities. This trial holds significance in generating valuable data on a predictive biomarker for antidepressant treatment in patients with MDD. The findings will be shared with study participants, disseminated through professional society meetings, and published in peer-reviewed journals. Trial registration German Clinical Trial Register DRKS00032503. Registered on 17 August 2023.

Abstract Background Police violence is increasingly recognized as an urgent public health problem. Basic questions about police violence, however, remain unanswered, including which types of law enforcement agency are responsible for fatal police violence deaths. Methods We estimated the proportion of police violence deaths in the U.S. (2013–2022) that were attributable to local, county, state, federal, or tribal police agencies, using mapping police violence data. We examined proportions overall, by decedent race/ethnicity, and by state. Results Nationally, 60% of decedents were killed by municipal, 29% by county, 8% by state, and 3% by federal, police, with 40% of deaths. Conclusions We identify wide geographic & racial/ethnic variation in the agencies responsible for fatal police violence. Findings suggest that the budgetary and infrastructural shifts required to prevent fatal police violence need to occur at multiple levels of government.

Abstract Counting animal populations is fundamental to understand ecological processes. Counts make it possible to estimate the size of an animal population at specific points in time, which is essential information for understanding demographic change. However, in the case of large populations, counts are time‐consuming, particularly if carried out manually. Here, we took advantage of convolutional neural networks (CNN) to count the total number of nest‐entrances in 222 photographs covering the largest known Psittaciformes (Aves) colony in the world. We conducted our study at the largest Burrowing Parrot Cyanoliseus patagonus colony, located on a cliff facing the Atlantic Ocean in the vicinity of El Cóndor village, in north‐eastern Patagonia, Argentina. We also aimed to investigate the distribution of nest‐entrances along the cliff with the colony. For this, we used three CNN architectures, U‐Net, ResUnet, and DeepLabv3. The U‐Net architecture showed the best performance, counting a mean of 59,842 Burrowing Parrot nest‐entrances across the colony, with a mean absolute error of 2.7 nest‐entrances over the testing patches, measured as the difference between actual and predicted counts per patch. Compared to a previous study conducted at El Cóndor colony more than 20 years ago, the CNN architectures also detected noteworthy differences in the distribution of the nest‐entrances along the cliff. We show that the strong changes observed in the distribution of nest‐entrances are a measurable effect of a long record of human‐induced disturbance to the Burrowing Parrot colony at El Cóndor. Given the paramount importance of the Burrowing Parrot colony at El Cóndor, which concentrates 71% of the world's population of this species, we advocate that it is imperative to reduce such a degree of disturbance before the parrots reach the limit of their capacity of adaptation.

ABSTRACT The limited temporal completeness and taxonomic accuracy of species lists, made available in a traditional manner in scientific publications, has always represented a problem. These lists are invariably limited to a few taxonomic groups and do not represent up-to-date knowledge of all species and classifications. In this context, the Brazilian megadiverse fauna is no exception, and the Catálogo Taxonômico da Fauna do Brasil (CTFB) (http://fauna.jbrj.gov.br/), made public in 2015, represents a database on biodiversity anchored on a list of valid and expertly recognized scientific names of animals in Brazil. The CTFB is updated in near real time by a team of more than 800 specialists. By January 1, 2024, the CTFB compiled 133,691 nominal species, with 125,138 that were considered valid. Most of the valid species were arthropods (82.3%, with more than 102,000 species) and chordates (7.69%, with over 11,000 species). These taxa were followed by a cluster composed of Mollusca (3,567 species), Platyhelminthes (2,292 species), Annelida (1,833 species), and Nematoda (1,447 species). All remaining groups had less than 1,000 species reported in Brazil, with Cnidaria (831 species), Porifera (628 species), Rotifera (606 species), and Bryozoa (520 species) representing those with more than 500 species. Analysis of the CTFB database can facilitate and direct efforts towards the discovery of new species in Brazil, but it is also fundamental in providing the best available list of valid nominal species to users, including those in science, health, conservation efforts, and any initiative involving animals. The importance of the CTFB is evidenced by the elevated number of citations in the scientific literature in diverse areas of biology, law, anthropology, education, forensic science, and veterinary science, among others.

Abstract The spatial organization of eukaryotic genomes is linked to their biological functions, although it is not clear how this impacts the overall evolution of a genome. Here, we uncover the three-dimensional (3D) genome organization of the phytopathogen Verticillium dahliae, known to possess distinct genomic regions, designated adaptive genomic regions (AGRs), enriched in transposable elements and genes that mediate host infection. Short-range DNA interactions form clear topologically associating domains (TADs) with gene-rich boundaries that show reduced levels of gene expression and reduced genomic variation. Intriguingly, TADs are less clearly insulated in AGRs than in the core genome. At a global scale, the genome contains bipartite long-range interactions, particularly enriched for AGRs and more generally containing segmental duplications. Notably, the patterns observed for V. dahliae are also present in other Verticillium species. Thus, our analysis links 3D genome organization to evolutionary features conserved throughout the Verticillium genus.

Abstract Moose (Alces alces) in the boreal forest habitats of Alaska are unlike other northern ungulates because they tolerate high densities of flies (Diptera) even though flies cause wounds and infections during the warm summer months. Moose move to find food and to find relief from overheating (hyperthermia) but do they avoid flies? We used GPS collars to measure the rate of movement (m⋅h−1) and the time spent (min⋅day−1) by enclosed moose in four habitats: wetlands, black spruce, early seral boreal forest, and late seral boreal forest. Fly traps were used in each habitat to quantify spatio‐temporal abundance. Average daily air temperatures increased into July when peak biomass of forage for moose was greatest in early seral boreal forest habitats (424.46 vs. 25.15 kg⋅ha−1 on average in the other habitats). Average daily air temperatures were 1.7°C cooler in black spruce than other habitats, but fly abundance was greatest in black spruce (approximately 4‐fold greater on average than the other habitats). Moose increased their movement rate with counts of biting flies (mosquitoes, black flies, horse and deer flies), but not non‐biting flies (coprophagous flies). However, as air temperature increased (above 14.7°C) moose spent more time in fly‐abundant black spruce, than early seral boreal forest, showing great tolerance for mosquitoes. Warm summer temperatures appear to cause moose to trade‐off foraging in fly‐sparse habitats for resting and dissipating heat in shady, wet habitats with abundant flies that adversely affect the fitness of moose.

Abstract The need for the identification of risk factors associated to COVID-19 disease severity remains urgent. Patients’ care and resource allocation can be potentially different and are defined based on the current classification of disease severity. This classification is based on the analysis of clinical parameters and routine blood tests, which are not standardized across the globe. Some laboratory test alterations have been associated to COVID-19 severity, although these data are conflicting partly due to the different methodologies used across different studies. This study aimed to construct and validate a disease severity prediction model using machine learning (ML). Seventy-two patients admitted to a Brazilian hospital and diagnosed with COVID-19 through RT-PCR and/or ELISA, and with varying degrees of disease severity, were included in the study. Their electronic medical records and the results from daily blood tests were used to develop a ML model to predict disease severity. Using the above data set, a combination of five laboratorial biomarkers was identified as accurate predictors of COVID-19 severe disease with a ROC-AUC of 0.80 ± 0.13. Those biomarkers included prothrombin activity, ferritin, serum iron, ATTP and monocytes. The application of the devised ML model may help rationalize clinical decision and care.

ObjectiveTo evaluate the extent to which patient-users reporting symptoms of five severe/acute conditions requiring emergency care to an AI-based virtual triage (VT) engine had no intention to get such care, and whose acuity perception was misaligned or decoupled from actual risk of life-threatening symptoms.MethodsA dataset of 3,022,882 VT interviews conducted over 16 months was evaluated to quantify and describe patient-users reporting symptoms of five potentially life-threatening conditions whose pre-triage healthcare intention was other than seeking urgent care, including myocardial infarction, stroke, asthma exacerbation, pneumonia, and pulmonary embolism.ResultsHealthcare intent data was obtained for 12,101 VT patient-user interviews. Across all five conditions a weighted mean of 38.5% of individuals whose VT indicated a condition requiring emergency care had no pre-triage intent to consult a physician. Furthermore, 61.5% intending to possibly consult a physician had no intent to seek emergency medical care. After adjustment for 13% VT safety over-triage/referral to ED, a weighted mean of 33.5% of patient-users had no intent to seek professional care, and 53.5% had no intent to seek emergency care.ConclusionAI-based VT may offer a vehicle for early detection and care acuity alignment of severe evolving pathology by engaging patients who believe their symptoms are not serious, and for accelerating care referral and delivery for life-threatening conditions where patient misunderstanding of risk, or indecision, causes care delay. A next step will be clinical confirmation that when decoupling of patient care intent from emergent care need occurs, VT can influence patient behavior to accelerate care engagement and/or emergency care dispatch and treatment to improve clinical outcomes.

Residential racial segregation in the U.S. has been hypothesized as a fundamental cause driving health disparities across racial groups. Potential mechanisms include economic and social marginalization, subsequent constrained opportunities, and high stress. Yet evidence on residential segregation's association with health among Black and White children-particularly longitudinally-is sparse. This study aims to address this gap. We used data from the Panel Study of Income Dynamics (PSID), a national longitudinal study of U.S. households, analyzing information on 1,251 Black and 1,427 White children who participated in the Child Development Supplement (CDS) at least twice (survey waves 1997, 2002, 2007, 2014). We fit individual fixed-effects models to estimate the within-person association of neighborhood-level residential segregation, measured with local Getis-Ord G* statistics, with three outcomes (general health, weight status, and behavioral problems). We examined heterogeneous effects by age and sex. We also examined associations between health and childhood segregation trajectories, i.e., the pattern of children's residential segregation exposures from birth through when their health outcomes were measured, providing additional insight on dynamic experiences of segregation. In fixed effects models, among Black children, higher segregation was associated with worse self-rated health, especially for Black children who were older (aged 11-17 years). In trajectory models, among White children, moving out of highly segregated neighborhoods was associated with a lower probability of poor self-rated health, while moving into those neighborhoods or back and forth between neighborhood types were both associated with increased behavioral problems. Our findings highlight the importance of early-life residential segregation in shaping persistent racial health disparities, as well as the costs of segregation for all children living in highly segregated neighborhoods.

Housing may be at once the most powerful and underused tool at our disposal to improve population health. Using examples from the USA, we argue that current levels of housing insecurity are the result of clear and inequitable policy choices, leading to the entrenchment of health inequities-particularly, across race and class. Solutions to housing insecurity must, therefore, be structural. The COVID-19 pandemic has opened a window of opportunity for these structural housing policy reforms. Through justice- and action-oriented research, health researchers can inform the development and implementation of housing policies that advance health equity. We offer a series of recommendations to better position our field to achieve this goal.

The hepatitis C virus (HCV) is responsible for approximately 50 million infections worldwide. Effective drug treatments while available face access barriers, and vaccine development is hampered by viral hypervariability and immune evasion mechanisms. The CD4+ and CD8+ T-cell responses targeting HCV non-structural (NS) proteins have shown a role in the viral clearance. In this paper, we reviewed the studies exploring the relationship between HCV structural and NS proteins and their effects in contributing to the elicitation of an effective T-cell immune response. The use of different vaccine platforms, such as viral vectors and virus-like particles, underscores their versability and efficacy for vaccine development. Diverse HCV antigens demonstrated immunogenicity, eliciting a robust immune response, positioning them as promising vaccine candidates for protein/peptide-, DNA-, or RNA-based vaccines. Moreover, adjuvant selection plays a pivotal role in modulating the immune response. This review emphasizes the importance of HCV proteins and vaccination strategies in vaccine development. In particular, the NS proteins are the main focus, given their pivotal role in T-cell-mediated immunity and their sequence conservation, making them valuable vaccine targets.

Quantum systems of infinite dimension, such as bosonic oscillators, provide vast resources for quantum sensing. Yet, a general theory on how to manipulate such bosonic modes for sensing beyond parameter estimation is unknown. We present a general algorithmic framework, quantum signal processing interferometry (QSPI), for quantum sensing at the fundamental limits of quantum mechanics by generalizing Ramsey-type interferometry. Our QSPI sensing protocol relies on performing nonlinear polynomial transformations on the oscillator's quadrature operators by generalizing quantum signal processing (QSP) from qubits to hybrid qubit-oscillator systems. We use our QSPI sensing framework to make efficient binary decisions on a displacement channel in the single-shot limit. Theoretical analysis suggests the sensing accuracy, given a single-shot qubit measurement, scales inversely with the sensing time or circuit depth of the algorithm. We further concatenate a series of such binary decisions to perform parameter estimation in a bit-by-bit fashion. Numerical simulations are performed to support these statements. Our QSPI protocol offers a unified framework for quantum sensing using continuous-variable bosonic systems beyond parameter estimation and establishes a promising avenue toward efficient and scalable quantum control and quantum sensing schemes beyond the NISQ era.

HER2-targeted therapies, such as Trastuzumab (Tz), have significantly improved the clinical outcomes for patients with HER2+ breast cancer (BC). However, treatment resistance remains a major obstacle. To elucidate functional and metabolic changes associated with acquired resistance, we characterized protein profiles of BC Tz-responder spheroids (RSs) and non-responder spheroids (nRSs) by a proteomic approach. Three-dimensional cultures were generated from the HER2+ human mammary adenocarcinoma cell line BT-474 and a derived resistant cell line. Before and after a 15-day Tz treatment, samples of each condition were collected and analyzed by liquid chromatography–mass spectrometry. The analysis of differentially expressed proteins exhibited the deregulation of energetic metabolism and mitochondrial pathways. A down-regulation of carbohydrate metabolism and up-regulation of mitochondria organization proteins, the tricarboxylic acid cycle, and oxidative phosphorylation, were observed in nRSs. Of note, Complex I-related proteins were increased in this condition and the inhibition by metformin highlighted that their activity is necessary for nRS survival. Furthermore, a correlation analysis showed that overexpression of Complex I proteins NDUFA10 and NDUFS2 was associated with high clinical risk and worse survival for HER2+ BC patients. In conclusion, the non-responder phenotype identified here provides a signature of proteins and related pathways that could lead to therapeutic biomarker investigation.

BackgroundCardiovascular disease (CVD) disproportionately affects Black adults in the United States. This is increasingly acknowledged to be due to inequitable distribution of health-promoting resources. One potential contributor is inequities in educational opportunities, although it is unclear what aspects of education are most salient. School racial segregation may affect cardiovascular health by increasing stress, constraining socioeconomic opportunities, and altering health behaviors. We investigated the association between school segregation and Black adults' CVD risk.Methods and findingsWe leveraged a natural experiment created by quasi-random (i.e., arbitrary) timing of local court decisions since 1991 that released school districts from court-ordered desegregation. We used the Panel Study of Income Dynamics (PSID) (1991 to 2017), linked with district-level school segregation measures and desegregation court order status. The sample included 1,053 Black participants who ever resided in school districts that were under a court desegregation order in 1991. The exposure was mean school segregation during observed schooling years. Outcomes included several adult CVD risk factors and outcomes. We fitted standard ordinary least squares (OLS) multivariable linear regression models, then conducted instrumental variables (IV) analysis, using the proportion of schooling years spent in districts that had been released from court-ordered desegregation as an instrument. We adjusted for individual- and district-level preexposure confounders, birth year, and state fixed effects. In standard linear models, school segregation was associated with a lower probability of good self-rated health (-0.05 percentage points per SD of the segregation index; 95% CI: -0.08, -0.03; p < 0.001) and a higher probability of binge drinking (0.04 percentage points; 95% CI: 0.002, 0.07; p = 0.04) and heart disease (0.01 percentage points; 95% CI: 0.002, 0.15; p = 0.007). IV analyses also found that school segregation was associated with a lower probability of good self-rated health (-0.09 percentage points; 95% CI: -0.17, -0.02, p = 0.02) and a higher probability of binge drinking (0.17 percentage points; 95% CI: 0.04, 0.30, p = 0.008). For IV estimates, only binge drinking was robust to adjustments for multiple hypothesis testing. Limitations included self-reported outcomes and potential residual confounding and exposure misclassification.ConclusionsSchool segregation exposure in childhood may have longstanding impacts on Black adults' cardiovascular health. Future research should replicate these analyses in larger samples and explore potential mechanisms. Given the recent rise in school segregation, this study has implications for policies and programs to address racial inequities in CVD.

ObjectivesFew researchers have evaluated whether school racial segregation, a key manifestation of structural racism, affects child health, despite its potential impacts on school quality, social networks, and stress from discrimination. We investigated whether school racial segregation affects Black children's health and health behaviors.MethodsWe estimated the association of school segregation with child health, leveraging a natural experiment in which school districts in recent years experienced increased school segregation. School segregation was operationalized as the Black-White dissimilarity index. We used ordinary least squares models as well as quasi-experimental instrumental variables analysis, which can reduce bias from unobserved confounders. Data from the Child Development Supplement of the Panel Study of Income Dynamics (1997-2014, n = 1248 Black children) were linked with district-level school segregation measures. Multivariable regressions were adjusted for individual-, neighborhood-, and district-level covariates. We also performed subgroup analyses by child sex and age.ResultsIn instrumental variables models, a one standard deviation increase in school segregation was associated with increased behavioral problems (2.53 points on a 27-point scale; 95% CI, 0.26 to 4.80), probability of having ever drunk alcohol (0.23; 95% CI, 0.049 to 0.42), and drinking at least monthly (0.20; 95% CI, 0.053 to 0.35). School segregation was more strongly associated with drinking behaviors among girls.ConclusionsSchool segregation was associated with worse outcomes on several measures of well-being among Black children, which may contribute to health inequities across the life span. These results highlight the need to promote school racial integration and support Black youth attending segregated schools.

Enhancers integrate transcription factor signaling pathways that drive cell fate specification in the developing brain. We paired enhancer labeling and single-cell RNA-sequencing (scRNA-seq) to delineate and distinguish specification of neuronal lineages in mouse medial, lateral, and caudal ganglionic eminences (MGE, LGE, and CGE) at embryonic day (E)11.5. We show that scRNA-seq clustering using transcription factors improves resolution of regional and developmental populations, and that enhancer activities identify specific and overlapping GE-derived neuronal populations. First, we mapped the activities of seven evolutionarily conserved brain enhancers at single-cell resolution in vivo, finding that the selected enhancers had diverse activities in specific progenitor and neuronal populations across the GEs. We then applied enhancer-based labeling, scRNA-seq, and analysis of in situ hybridization data to distinguish transcriptionally distinct and spatially defined subtypes of MGE-derived GABAergic and cholinergic projection neurons and interneurons. Our results map developmental origins and specification paths underlying neurogenesis in the embryonic basal ganglia and showcase the power of scRNA-seq combined with enhancer-based labeling to resolve the complex paths of neuronal specification underlying mouse brain development.