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How phenotypic diversity originates and persists within populations are classic puzzles in evolutionary biology. While balanced polymorphisms segregate within many species, it remains rare for both the genetic basis and the selective forces to be known, leading to an incomplete understanding of many classes of traits under balancing selection. Here, we uncover the genetic architecture of a balanced sexual mimicry polymorphism and identify behavioral mechanisms that may be involved in its maintenance in the swordtail fish Xiphophorus birchmanni. We find that ∼40% of X. birchmanni males develop a "false gravid spot," a melanic pigmentation pattern that mimics the "pregnancy spot" associated with sexual maturity in female live-bearing fish. Using genome-wide association mapping, we detect a single intergenic region associated with variation in the false gravid spot phenotype, which is upstream of kitlga, a melanophore patterning gene. By performing long-read sequencing within and across populations, we identify complex structural rearrangements between alternate alleles at this locus. The false gravid spot haplotype drives increased allele-specific expression of kitlga, which provides a mechanistic explanation for the increased melanophore abundance that causes the spot. By studying social interactions in the laboratory and in nature, we find that males with the false gravid spot experience less aggression; however, they also receive increased attention from other males and are disdained by females. These behavioral interactions may contribute to the maintenance of this phenotypic polymorphism in natural populations. We speculate that structural variants affecting gene regulation may be an underappreciated driver of balanced polymorphisms across diverse species.

New school transitions can be challenging for students on the autism spectrum. No published, evidence-based interventions exist to support families and teachers of students transitioning to elementary and secondary school during this critical period. Using Community Partnered Participatory Research, we developed Building Better Bridges (BBB), a caregiver coaching intervention that includes training on effective school communication, educational rights, advocacy, and child preparation strategies. We compared BBB (n = 83) to a module/resources-only comparison (n = 87) in a four-site randomized controlled trial in racially and ethnically diverse, under-resourced communities. In our intent-to-treat analysis, caregivers and teachers in BBB rated students' transitions to the new classroom as more positive, relative to the comparison group. Results suggest this low-cost intervention can improve the transition process for families and students at high risk of poor transitions.

Preschool autistic children with significant global developmental delays and very limited language skills are at high risk for remaining minimally verbal at entry into primary school. This study compared two early intervention models for improving social communication and spoken language outcomes in 164 children who received intervention in their community preschool program for 6 months, with a six-month follow-up. The primary outcome measure was a standardized language assessment, and secondary measures focused on social communication. Results indicated children on average made 6 months gain in language development in the active 6 months of intervention with no difference between intervention models. Children who initiated joint attention more frequently, or who had higher receptive language at baseline made more progress if assigned to receive JASPER, a naturalistic developmental behavioral intervention. Children who received Discrete Trial Training made greater spoken language progress from exit to follow-up. These findings suggest that progress can be made in autistic children who have very little spoken language and who receive targeted early interventions. Individual trajectories vary and depend in part on initial abilities in social communication and receptive language. Future research might consider methods to systematically personalize approaches to fit child characteristics and family preference. LAY SUMMARY: This study compared two different early intervention approaches for teaching spoken language to minimally verbal, globally delayed autistic preschoolers. Children were given an hour of therapy daily for 6 months and then reassessed 6 months later. The majority of the 164 participants were from historically excluded populations (low income and minority), and therapy was delivered in school community settings by expert clinicians. Results indicated that the participants made significant progress regardless of intervention approach: 6 months gain in standardized language scores over 6 months, but slower progress during the period after therapy ended. Children who initiated joint attention more frequently, or who had higher language understanding at baseline made more progress if assigned to receive JASPER, a naturalistic developmental behavioral intervention. Children who received Discrete Trial Training made greater language progress during 6-month period after therapy ended. These findings suggest that progress can be made in children with ASD who have very little spoken language and who receive targeted early interventions.

The polarization of the cosmic microwave background (CMB) can be used to search for parity-violating processes like that predicted by a Chern-Simons coupling to a light pseudoscalar field. Such an interaction rotates E modes into E modes in the observed CMB signal through an effect known as cosmic birefringence. Even though isotropic birefringence can be confused with the rotation produced by a miscalibration of the detectors' polarization angles, the degeneracy between both effects is broken when Galactic foreground emission is used as a calibrator. In this work, we use realistic simulations of the High-Frequency Instrument of the Planck mission to test the impact that Galactic foreground emission and instrumental systematics have on the recent birefringence measurements obtained through this technique. Our results demonstrate the robustness of the methodology against the miscalibration of polarization angles and other systematic effects, like intensity-to-polarization leakage, beam leakage, or cross-polarization effects. However, our estimator is sensitive to the EB correlation of polarized foreground emission. Here we propose to correct the bias induced by dust EB by modeling the foreground signal with templates produced in Bayesian component-separation analyses that fit parametric models to CMB data. Acknowledging the limitations of currently available dust templates like that of the Commander sky model, high-precision CMB data and a characterization of dust beyond the modified blackbody paradigm are needed to obtain a definitive measurement of cosmic birefringence in the future.

We present constraints on the tensor-to-scalar ratio r using a combination of BICEP/Keck 2018 (BK18) and Planck PR4 data allowing us to fit for r consistently with the six parameters of the ΛCDM model. We discuss the sensitivity of constraints on r to uncertainties in the ΛCDM parameters as defined by the Planck data. In particular, we are able to derive a constraint on the reionization optical depth τ and thus propagate its uncertainty into the posterior distribution for r. While Planck sensitivity to r is slightly lower than the current ground-based measurements, the combination of Planck with BK18 and baryon-acoustic-oscillation data yields results consistent with r=0 and tightens the constraint to r

We search for the signature of parity-violating physics in the cosmic microwave background, called cosmic birefringence, using the Planck data release 4. We initially find a birefringence angle of β=0.30°±0.11° (68% C.L.) for nearly full-sky data. The values of β decrease as we enlarge the Galactic mask, which can be interpreted as the effect of polarized foreground emission. Two independent ways to model this effect are used to mitigate the systematic impact on β for different sky fractions. We choose not to assign cosmological significance to the measured value of β until we improve our knowledge of the foreground polarization.

We present a demonstration of the in-flight polarization angle calibration for the JAXA/ISAS second strategic large class mission, LiteBIRD, and estimate its impact on the measurement of the tensor-to-scalar ratio parameter, r, using simulated data. We generate a set of simulated sky maps with CMB and polarized foreground emission, and inject instrumental noise and polarization angle offsets to the 22 (partially overlapping) LiteBIRD frequency channels. Our in-flight angle calibration relies on nulling the EB cross correlation of the polarized signal in each channel. This calibration step has been carried out by two independent groups with a blind analysis, allowing an accuracy of the order of a few arc-minutes to be reached on the estimate of the angle offsets. Both the corrected and uncorrected multi-frequency maps are propagated through the foreground cleaning step, with the goal of computing clean CMB maps. We employ two component separation algorithms, the Bayesian-Separation of Components and Residuals Estimate Tool (B-SeCRET), and the Needlet Internal Linear Combination (NILC). We find that the recovered CMB maps obtained with algorithms that do not make any assumptions about the foreground properties, such as NILC, are only mildly affected by the angle miscalibration. However, polarization angle offsets strongly bias results obtained with the parametric fitting method. Once the miscalibration angles are corrected by EB nulling prior to the component separation, both component separation algorithms result in an unbiased estimation of the r parameter. While this work is motivated by the conceptual design study for LiteBIRD, its framework can be broadly applied to any CMB polarization experiment. In particular, the combination of simulation plus blind analysis provides a robust forecast by taking into account not only detector sensitivity but also systematic effects.

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored in a mega-analysis of previously published datasets from 2,034 AD and comparison participants spanning 27 sites curated by the ENIGMA Addiction Working Group. Data were grouped into a training set used for internal validation including 1,652 participants (692 AD, 24 sites), and a test set used for external validation with 382 participants (146 AD, 3 sites). An exploratory data analysis was first conducted, followed by an evolutionary search based feature selection to site generalizable and high performing subsets of brain measurements. Exploratory data analysis revealed that inclusion of case- and control-only sites led to the inadvertent learning of site-effects. Cross validation methods that do not properly account for site can drastically overestimate results. Evolutionary-based feature selection leveraging leave-one-site-out cross-validation, to combat unintentional learning, identified cortical thickness in the left superior frontal gyrus and right lateral orbitofrontal cortex, cortical surface area in the right transverse temporal gyrus, and left putamen volume as final features. Ridge regression restricted to these features yielded a test-set area under the receiver operating characteristic curve of 0.768. These findings evaluate strategies for handling multi-site data with varied underlying class distributions and identify potential biomarkers for individuals with current AD.

MRI-derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta-Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis-driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large-scale meta- and mega-analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large-scale, collaborative studies of mental illness.

Background: Numerous studies have shown that racial/ethnic minority and under-resourced families face barriers that delay timely access to autism services. These barriers include lack of resources and information about autism, financial hardship, mistrust in the service system, cultural and language mismatch, and other factors that have yet to be identified. Method: The current study aimed to examine additional caregiver and system-level factors that could be associated with early service access using a diverse sample from four study sites (Los Angeles, CA; Philadelphia, PA; Sacramento, CA; and Rochester, NY). Partnering with community agencies that serve traditionally underrepresented groups, the research team recruited 118 caregivers of young children with autism who were low-income, English, Spanish or Korean speaking and had not accessed autism-specific services. Results: Regression analyses revealed that the total number of services accessed were associated with caregiver social network size (p = 0.011) but not by race, autism knowledge and caregiver agency. Among families receiving at least one non-autism specific service, a marginally significant interaction effect of site and primary language on total services received was observed (p = 0.06). Conclusion: Findings suggest that caregivers’ social network connections are crucial in early service access, and future interventions could target increasing social networks to improve families’ service engagement. More attention for non-English speaking families, especially those living in areas with few supports in their native languages, is needed.

Parents of children with autism spectrum disorder (ASD) face higher levels of caregiver strain compared to parents of children with other disabilities. This study examined child clinical features that predict high levels of caregiver strain for 374 parents of children with ASD. Caregiver strain was measured using the Caregiver Strain Questionnaire (CGSQ) objective, subjective internalized, and subjective externalized subscales. Confirmatory factor analysis indicated an acceptable fit for the original CGSQ three-factor solution. The strongest child predictors across CGSQ subscales were: disruptive behavior for objective strain, autism severity and disruptive behavior for subjective internalized strain, and oppositional behavior and hyperactivity for subjective externalized strain. Individualized interventions that attend to specific elements of parental strain may reduce strain and improve family wellbeing.

Children with autism situated in lower income families often receive intensive educational interventions as their primary form of treatment, due to financial barriers for community interventions. However, the continuity of care can be disrupted by school transitions. The quality of social relationships during the transition to a new school among parents, school staff and community providers, called the team-around-the-child (TAC), can potentially buffer a child with autism from the adverse effects caused by care disruptions. Qualities of social relationships, including trust and collaborative problem solving, can be measured using social network analysis. This study investigates if two different types of TAC relationships, defined as (1) the level of trust among team members and (2) the degree of collaborative problem solving among team members, are associated with perceived successful transitions for children with autism from lower income families. Findings suggested that TAC trust is significantly associated with the outcome of transition success for children with autism immediately post-transition.

We present constraints on the tensor-to-scalar ratio r using Planck data. We use the latest release of Planck maps, processed with the NPIPE code, which produces calibrated frequency maps in temperature and polarisation for all Planck channels from 30 GHz to 857 GHz using the same pipeline. We computed constraints on r using the BB angular power spectrum, and we also discuss constraints coming from the TT spectrum. Given Planck's noise level, the TT spectrum gives constraints on r that are cosmic-variance limited (with σr = 0.093), but we show that the marginalised posterior peaks towards negative values of r at about the 1.2σ level. We derived Planck constraints using the BB power spectrum at both large angular scales (the 'reionisation bump') and intermediate angular scales (the 'recombination bump') from ℓ = 2 to 150 and find a stronger constraint than that from TT, with σr = 0.069. The Planck BB spectrum shows no systematic bias and is compatible with zero, given both the statistical noise and the systematic uncertainties. The likelihood analysis using B modes yields the constraint r < 0.158 at 95% confidence using more than 50% of the sky. This upper limit tightens to r < 0.069 when Planck EE, BB, and EB power spectra are combined consistently, and it tightens further to r < 0.056 when the Planck TT power spectrum is included in the combination. Finally, combining Planck with BICEP2/Keck 2015 data yields an upper limit of r < 0.044.

We present constraints on the tensor-to-scalar ratio r using Planck data. We use the latest release of Planck maps, processed with the NPIPE code, which produces calibrated frequency maps in temperature and polarisation for all Planck channels from 30 GHz to 857 GHz using the same pipeline. We computed constraints on r using the BB angular power spectrum, and we also discuss constraints coming from the TT spectrum. Given Planck's noise level, the TT spectrum gives constraints on r that are cosmic-variance limited (with σr = 0.093), but we show that the marginalised posterior peaks towards negative values of r at about the 1.2σ level. We derived Planck constraints using the BB power spectrum at both large angular scales (the 'reionisation bump') and intermediate angular scales (the 'recombination bump') from ℓ = 2 to 150 and find a stronger constraint than that from TT, with σr = 0.069. The Planck BB spectrum shows no systematic bias and is compatible with zero, given both the statistical noise and the systematic uncertainties. The likelihood analysis using B modes yields the constraint r < 0.158 at 95% confidence using more than 50% of the sky. This upper limit tightens to r < 0.069 when Planck EE, BB, and EB power spectra are combined consistently, and it tightens further to r < 0.056 when the Planck TT power spectrum is included in the combination. Finally, combining Planck with BICEP2/Keck 2015 data yields an upper limit of r < 0.044.

The cerebral cortex underlies our complex cognitive capabilities, yet little is known about the specific genetic loci that influence human cortical structure. To identify genetic variants that affect cortical structure, we conducted a genome-wide association meta-analysis of brain magnetic resonance imaging data from 51,665 individuals. We analyzed the surface area and average thickness of the whole cortex and 34 regions with known functional specializations. We identified 199 significant loci and found significant enrichment for loci influencing total surface area within regulatory elements that are active during prenatal cortical development, supporting the radial unit hypothesis. Loci that affect regional surface area cluster near genes in Wnt signaling pathways, which influence progenitor expansion and areal identity. Variation in cortical structure is genetically correlated with cognitive function, Parkinson's disease, insomnia, depression, neuroticism, and attention deficit hyperactivity disorder.

As Māori and tāngata whaikaha (Māori with lived experience of disability) of the nation-state known as New Zealand, we are deeply concerned about the impacts of the COVID-19 pandemic. In this commentary, we invoke intersectionality as an analytical tool for understanding critical issues tāngata whaikaha face in the context of the universal approach encompassing New Zealand’s pandemic response. We propose a “call to action” framework comprising four elements: (1) guaranteeing self-determination for tāngata whaikaha; (2) addressing all forms of racism, ableism, and other structural forms of oppression; (3) rectifying historical injustices; and (4) allocating resources for the pandemic and beyond in alignment with need.

IntroductionChildren with autism spectrum disorder (ASD) benefit when their caregivers can effectively advocate for appropriate services. Barriers to caregiver engagement such as provider mistrust, cultural differences, stigma, and lack of knowledge can interfere with timely service access. We describe Mind the Gap (MTG), an intervention that provides education about ASD, service navigation, and other topics relevant to families whose children have a new ASD diagnosis. MTG was developed via community partnerships and is explicitly structured to reduce engagement barriers (e.g., through peer matching, meeting flexibility, culturally-informed practices). We also present on the results of a pilot of MTG, conducted in preparation for a randomized controlled trial.MethodsMTG was evaluated using mixed methods that included qualitative analysis and pre/post-test without concurrent comparison group. Participants (n=9) were primary caregivers of children (ages 2-7 years) with a recent ASD diagnosis and whose annual income was at or below 185% of the federal poverty level. In order to facilitate trust and relationship building, peer coaches delivered MTG. The coaches were parents of children with ASD who we trained to deliver the intervention. MTG consisted of up to 12 meetings between coaches and caregivers over the course of 18 weeks. Coaches delivered the intervention in homes and other community locations. Coaches shared information about various "modules," which were topics identified as important for families with a new ASD diagnosis. Coaches worked with families to answer questions, set weekly goals, assess progress, and offer guidance. For the pilot, we focused on three primary outcomes: feasibility, engagement, and satisfaction. Feasibility was measured via enrollment and retention data, as well as coach fidelity (i.e., implementation of MTG procedures). Engagement was measured via number of sessions attended and percentage completion of the selected outcome measures. For completers (n=7), satisfaction was measured via a questionnaire (completed by caregivers) and open-ended interviews (completed by caregivers and coaches).ResultsWe enrolled 56% of referred caregivers and 100% of eligible families. Retention was high (78%). Coaches could deliver the intervention with fidelity, completing, on average, 83% of program components. Engagement also was high; caregivers attended an average of 85% of total possible sessions and completed 100% of their measures. Caregivers indicated moderately high satisfaction with MTG. Qualitative data indicated that caregivers and coaches were positive about intervention content, and the coach-caregiver relationship was important. They also had suggestions for changes.ConclusionMind the Gap demonstrates evidence of feasibility, and data from the pilot suggest that it addresses intervention engagement barriers for a population that is under-represented in research. The results and suggestions from participants were used to inform a large-scale RCT, which is currently underway. Overall, MTG shows promise as an intervention that can be feasibly implemented with under-resourced and ethnic minority families of children with ASD.Trial registrationThis study is registered with ClinicalTrials.gov: NCT03711799.

Decades of research have established that racial ethnic minority, low-income, and/or non-English speaking children with autism spectrum disorder (ASD) are diagnosed later than white children, and their families experience greater difficulty accessing services in the USA. Delayed access to timely diagnosis and early intervention may impact child outcomes and family quality of life. Despite their cognition of these disparities and their significant impact on the lives of those affected, explanations for the barriers experienced by underserved families are elusive, likely due to the complex interaction between structural and family factors. This study used qualitative methods to gather family and provider perspectives of perceived barriers and facilitators to obtaining an ASD diagnosis and accessing ASD-related services for underserved families. Themes from focus groups and interviews with families from three cultural groups (black, Hispanic/Latino, and Korean) and three primary languages (English, Korean, and Spanish) highlight specific barriers related to family, community, and systemic challenges as well as facilitators to accessing care for these populations. Family experiences are expanded upon with viewpoints from the providers who work with them. Recommendations are made for reducing disparities in the existing ASD service system including increasing professional, family, and community education; increasing culturally responsive care; improving provider-family partnerships; and addressing practical challenges to service access.

Decades of research have established that racial ethnic minority, low-income, and/or non-English speaking children with autism spectrum disorder (ASD) are diagnosed later than white children, and their families experience greater difficulty accessing services in the USA. Delayed access to timely diagnosis and early intervention may impact child outcomes and family quality of life. Despite their cognition of these disparities and their significant impact on the lives of those affected, explanations for the barriers experienced by underserved families are elusive, likely due to the complex interaction between structural and family factors. This study used qualitative methods to gather family and provider perspectives of perceived barriers and facilitators to obtaining an ASD diagnosis and accessing ASD-related services for underserved families. Themes from focus groups and interviews with families from three cultural groups (black, Hispanic/Latino, and Korean) and three primary languages (English, Korean, and Spanish) highlight specific barriers related to family, community, and systemic challenges as well as facilitators to accessing care for these populations. Family experiences are expanded upon with viewpoints from the providers who work with them. Recommendations are made for reducing disparities in the existing ASD service system including increasing professional, family, and community education; increasing culturally responsive care; improving provider-family partnerships; and addressing practical challenges to service access.

Transitioning to a new school is often challenging for students with autism spectrum disorder. Few studies have examined the transition needs of students with autism spectrum disorder or the benefits of specific supports. This review synthesizes research findings on the difficulties that school transitions pose for students with autism spectrum disorder and their parents and teachers, and the strategies used to support students and parents during school transition. The review included 27 studies (10 examining the transition to primary school, 17 the transition to secondary school), with data from 443 students with autism spectrum disorder, 453 parents, and 546 teachers, across four continents (North America, Europe, Africa, and Australia). Studies reported that children with autism spectrum disorder struggled with anxiety and increased social pressure, their parents felt overwhelmed with complex placement decisions and worried about the well-being of their children, and teachers strove to provide appropriate supports to their students with autism spectrum disorder, often with inadequate resources. Findings indicated that the most useful strategies involved helping the student adjust to the new school setting, individualizing transition supports, clarifying the transition process for parents, and fostering communication both between the sending and receiving schools, and school and home.

Transitioning to a new school is often challenging for students with autism spectrum disorder. Few studies have examined the transition needs of students with autism spectrum disorder or the benefits of specific supports. This review synthesizes research findings on the difficulties that school transitions pose for students with autism spectrum disorder and their parents and teachers, and the strategies used to support students and parents during school transition. The review included 27 studies (10 examining the transition to primary school, 17 the transition to secondary school), with data from 443 students with autism spectrum disorder, 453 parents, and 546 teachers, across four continents (North America, Europe, Africa, and Australia). Studies reported that children with autism spectrum disorder struggled with anxiety and increased social pressure, their parents felt overwhelmed with complex placement decisions and worried about the well-being of their children, and teachers strove to provide appropriate supports to their students with autism spectrum disorder, often with inadequate resources. Findings indicated that the most useful strategies involved helping the student adjust to the new school setting, individualizing transition supports, clarifying the transition process for parents, and fostering communication both between the sending and receiving schools, and school and home.

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.

ObjectiveWe explored patterns of concomitant psychiatric disorders in a large sample of treatment-seeking children and adolescents with autism spectrum disorder (ASD).MethodsParticipants were 658 children with ASD (age 3-17 years; mean = 7.2 years) in one of six federally-funded multisite randomized clinical trials (RCT) between 1999 and 2014. All children were referred for hyperactivity or irritability. Study designs varied, but all used the Child and Adolescent Symptom Inventory or Early Childhood Inventory to assess Attention Deficit Hyperactivity Disorder (ADHD), Oppositional-Defiant Disorder (ODD), Conduct Disorder (CD), Anxiety Disorders, and Mood Disorders. In addition, several measures in common were used to assess demographic and clinical characteristics.ResultsOf the 658 children, 73% were Caucasian and 59% had an IQ >70. The rates of concomitant disorders across studies were: ADHD 81%, ODD 46%, CD 12%, any anxiety disorder 42%, and any mood disorder 8%. Two or more psychiatric disorders were identified in 66% of the sample. Of those who met criteria for ADHD, 50% also met criteria for ODD and 46% for any anxiety disorder. Associations between types of concomitant disorders and a number of demographic and clinical characteristics are presented.ConclusionIn this well-characterized sample of treatment-seeking children with ASD, rates of concomitant psychiatric disorders were high and the presence of two or more co-occurring disorders was common. Findings highlight the importance of improving diagnostic practice in ASD and understanding possible mechanisms of comorbidity.

We organized 10Kin1day, a pop-up scientific event with the goal to bring together neuroimaging groups from around the world to jointly analyze 10,000+ existing MRI connectivity datasets during a 3-day workshop. In this report, we describe the motivation and principles of 10Kin1day, together with a public release of 8,000+ MRI connectome maps of the human brain.

The purpose of this review was to estimate the impact of parent engagement strategies tested with underrepresented families of young children with social, emotional, or behavioral disorders, and describe the combinations in which these strategies are commonly used together. We conducted a systematic review using the PracticeWise Engagement Coding System to identify which strategies had the strongest empirical support for engaging underrepresented (i.e., minority race or ethnicity, or low income) families receiving psychosocial services for their children. Social network analyses were used to identify the frequency of strategy use and how strategies were combined to engage underrepresented families. Linear regression was used to estimate the impact of each strategy on parent engagement, using attrition as a proxy for non-engagement. Thirty-five studies met inclusion criteria. Parent attrition was predicted by larger sample sizes, lower maternal education, interventions that were more community or home-based, less therapist monitoring, positive reinforcement from therapists, and more pairing families with peers. Social network analyses suggested that more effective strategies were more frequently implemented alone and less effective strategies were commonly combined with each other. Our findings suggest that researchers and practitioners require guidance in selecting engagement strategies to reduce attrition of underrepresented families in treatment. Although we identified promising strategies for improving parent engagement in treatment for underrepresented children with social, emotional, or behavioral disorders, the frequent combining of engagement strategies in research means that there is little data on the independent effects of interventions to increase parent engagement for this population.

We present an analysis of the main systematic effects that could impact the measurement of CMB polarization with the proposed CORE space mission. We employ timeline-to-map simulations to verify that the CORE instrumental set-up and scanning strategy allow us to measure sky polarization to a level of accuracy adequate to the mission science goals. We also show how the CORE observations can be processed to mitigate the level of contamination by potentially worrying systematics, including intensity-to-polarization leakage due to bandpass mismatch, asymmetric main beams, pointing errors and correlated noise. We use analysis techniques that are well validated on data from current missions such as Planck to demonstrate how the residual contamination of the measurements by these effects can be brought to a level low enough not to hamper the scientific capability of the mission, nor significantly increase the overall error budget. We also present a prototype of the CORE photometric calibration pipeline, based on that used for Planck, and discuss its robustness to systematics, showing how CORE can achieve its calibration requirements. While a fine-grained assessment of the impact of systematics requires a level of knowledge of the system that can only be achieved in a future study phase, the analysis presented here strongly suggests that the main areas of concern for the CORE mission can be addressed using existing knowledge, techniques and algorithms.

We present an analysis of the main systematic effects that could impact the measurement of CMB polarization with the proposed CORE space mission. We employ timeline-to-map simulations to verify that the CORE instrumental set-up and scanning strategy allow us to measure sky polarization to a level of accuracy adequate to the mission science goals. We also show how the CORE observations can be processed to mitigate the level of contamination by potentially worrying systematics, including intensity-to-polarization leakage due to bandpass mismatch, asymmetric main beams, pointing errors and correlated noise. We use analysis techniques that are well validated on data from current missions such as Planck to demonstrate how the residual contamination of the measurements by these effects can be brought to a level low enough not to hamper the scientific capability of the mission, nor significantly increase the overall error budget. We also present a prototype of the CORE photometric calibration pipeline, based on that used for Planck, and discuss its robustness to systematics, showing how CORE can achieve its calibration requirements. While a fine-grained assessment of the impact of systematics requires a level of knowledge of the system that can only be achieved in a future study phase, the analysis presented here strongly suggests that the main areas of concern for the CORE mission can be addressed using existing knowledge, techniques and algorithms.

Albedo-a primary control on surface melt-varies considerably across the Greenland Ice Sheet yet the specific surface types that comprise its dark zone remain unquantified. Here we use UAV imagery to attribute seven distinct surface types to observed albedo along a 25 km transect dissecting the western, ablating sector of the ice sheet. Our results demonstrate that distributed surface impurities-an admixture of dust, black carbon and pigmented algae-explain 73% of the observed spatial variability in albedo and are responsible for the dark zone itself. Crevassing and supraglacial water also drive albedo reduction but due to their limited extent, explain just 12 and 15% of the observed variability respectively. Cryoconite, concentrated in large holes or fluvial deposits, is the darkest surface type but accounts for

Soil carbon (C) is a critical component of Earth system models (ESMs), and its diverse representations are a major source of the large spread across models in the terrestrial C sink from the third to fifth assessment reports of the Intergovernmental Panel on Climate Change (IPCC). Improving soil C projections is of a high priority for Earth system modeling in the future IPCC and other assessments. To achieve this goal, we suggest that (1) model structures should reflect real-world processes, (2) parameters should be calibrated to match model outputs with observations, and (3) external forcing variables should accurately prescribe the environmental conditions that soils experience. First, most soil C cycle models simulate C input from litter production and C release through decomposition. The latter process has traditionally been represented by first-order decay functions, regulated primarily by temperature, moisture, litter quality, and soil texture. While this formulation well captures macroscopic soil organic C (SOC) dynamics, better understanding is needed of their underlying mechanisms as related to microbial processes, depth-dependent environmental controls, and other processes that strongly affect soil C dynamics. Second, incomplete use of observations in model parameterization is a major cause of bias in soil C projections from ESMs. Optimal parameter calibration with both pool- and flux-based data sets through data assimilation is among the highest priorities for near-term research to reduce biases among ESMs. Third, external variables are represented inconsistently among ESMs, leading to differences in modeled soil C dynamics. We recommend the implementation of traceability analyses to identify how external variables and model parameterizations influence SOC dynamics in different ESMs. Overall, projections of the terrestrial C sink can be substantially improved when reliable data sets are available to select the most representative model structure, constrain parameters, and prescribe forcing fields.

Carbon dioxide is taken up by agricultural crops and released soon after during the consumption of agricultural commodities. The global net impact of this process on carbon flux to the atmosphere is negligible, but impact on the spatial distribution of carbon dioxide uptake and release across regions and continents is significant. To estimate the consumption and release of carbon by humans over the landscape, we developed a carbon budget for humans in the United States. The budget was derived from food commodity intake data for the US and from algorithms representing the metabolic processing of carbon by humans. Data on consumption, respiration, and waste of carbon by humans were distributed over the US using geospatial population data with a resolution of ~450 × 450 m. The average adult in the US contains about 21 kg C and consumes about 67 kg C year−1 which is balanced by the annual release of about 59 kg C as expired CO2, 7 kg C as feces and urine, and less than 1 kg C as flatus, sweat, and aromatic compounds. In 2000, an estimated 17.2 Tg C were consumed by the US population and 15.2 Tg C were expired to the atmosphere as CO2. Historically, carbon stock in the US human population has increased between 1790 and 2006 from 0.06 Tg to 5.37 Tg. Displacement and release of total harvested carbon per capita in the US is nearly 12% of per capita fossil fuel emissions. Humans are using, storing, and transporting carbon about the Earth’s surface. Inclusion of these carbon dynamics in regional carbon budgets can improve our understanding of carbon sources and sinks.

Specific binding of HIV-1 viral protein NCp7 to a unique 35-base RNA stem-loop SL1 is critical for formation and packaging of the genomic RNA dimer found within HIV-1 virions. NCp7 binding stimulates refolding of SL1 from a metastable kissing dimer (KD) into thermodynamically stable linear dimer (LD). Using UV melting, gel electrophoresis and heteronuclear NMR, we investigated effects of various site-specific mutations within the full-length SL1 on temperature- or NCp7-induced refolding in vitro. Refolding involved intramolecular melting of SL1 stems but not dissociation of the intermolecular KD interface. Refolding required only two NCp7 molecules per KD but was limited by the amount of NCp7 present, implying that the protein does not catalytically promote refolding. Efficient refolding depended strictly on the presence and, to a lesser degree, on sequence of a highly conserved G-rich internal loop that normally limits thermal stability of the SL1 stem. Adding two base pairs to the lower stem created a hyperstable SL1 mutant that failed to refold, even when bound by NCp7 at high stoichiometries. NMR analysis of these kinetically trapped mutant RNA-protein complexes indicated that NCp7 initiates refolding by dissociating base pairs in the upper stem of SL1. This study illuminates structural transitions critical for HIV-1 assembly and replication.

Specific binding of HIV-1 viral protein NCp7 to a unique 35-base RNA stem-loop SL1 is critical for formation and packaging of the genomic RNA dimer found within HIV-1 virions. NCp7 binding stimulates refolding of SL1 from a metastable kissing dimer (KD) into thermodynamically stable linear dimer (LD). Using UV melting, gel electrophoresis and heteronuclear NMR, we investigated effects of various site-specific mutations within the full-length SL1 on temperature- or NCp7-induced refolding in vitro. Refolding involved intramolecular melting of SL1 stems but not dissociation of the intermolecular KD interface. Refolding required only two NCp7 molecules per KD but was limited by the amount of NCp7 present, implying that the protein does not catalytically promote refolding. Efficient refolding depended strictly on the presence and, to a lesser degree, on sequence of a highly conserved G-rich internal loop that normally limits thermal stability of the SL1 stem. Adding two base pairs to the lower stem created a hyperstable SL1 mutant that failed to refold, even when bound by NCp7 at high stoichiometries. NMR analysis of these kinetically trapped mutant RNA-protein complexes indicated that NCp7 initiates refolding by dissociating base pairs in the upper stem of SL1. This study illuminates structural transitions critical for HIV-1 assembly and replication.