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Research at the intersection of social science and genomics, 'sociogenomics', is transforming our understanding of the interplay between genomics, individual outcomes and society. It has interesting and maybe unexpected implications for education research and policy. Here we review the growing sociogenomics literature and discuss its implications for educational researchers and policymakers. We cover key concepts and methods in genomic research into educational outcomes, how genomic data can be used to investigate social or environmental effects, the methodological strengths and limitations of genomic data relative to other observational social data, the role of intergenerational transmission and potential policy implications. The increasing availability of genomic data in studies can produce a wealth of new evidence for education research. This may provide opportunities for disentangling the environmental and genomic factors that influence educational outcomes and identifying potential mechanisms for intervention.

PurposeModels to study metastatic disease in rare cancers are needed to advance preclinical therapeutics and to gain insight into disease biology. Osteosarcoma is a rare cancer with a complex genomic landscape in which outcomes for patients with metastatic disease are poor. As osteosarcoma genomes are highly heterogeneous, multiple models are needed to fully elucidate key aspects of disease biology and to recapitulate clinically relevant phenotypes.Experimental designMatched patient samples, patient-derived xenografts (PDX), and PDX-derived cell lines were comprehensively evaluated using whole-genome sequencing and RNA sequencing. The in vivo metastatic phenotype of the PDX-derived cell lines was characterized in both an intravenous and an orthotopic murine model. As a proof-of-concept study, we tested the preclinical effectiveness of a cyclin-dependent kinase inhibitor on the growth of metastatic tumors in an orthotopic amputation model.ResultsPDXs and PDX-derived cell lines largely maintained the expression profiles of the patient from which they were derived despite the emergence of whole-genome duplication in a subset of cell lines. The cell lines were heterogeneous in their metastatic capacity, and heterogeneous tissue tropism was observed in both intravenous and orthotopic models. Single-agent dinaciclib was effective at dramatically reducing the metastatic burden.ConclusionsThe variation in metastasis predilection sites between osteosarcoma PDX-derived cell lines demonstrates their ability to recapitulate the spectrum of the disease observed in patients. We describe here a panel of new osteosarcoma PDX-derived cell lines that we believe will be of wide use to the osteosarcoma research community.

The few examples of structures containing the 2-chloro-N,N-dimethylethan-1-aminium or 3-chloro-N,N-dimethylpropan-1-aminium cations show a competition between gauche and anti conformations for the chloroalkyl chain. To explore further the conformational landscape of these cations, and their possible use as molecular switches, the title salts, (C4H11ClN)2[CoCl4] and (C4H11ClN)2[ZnCl4], were prepared and structurally characterized. Details of both structures are in close agreement. The inorganic complex exhibits a slightly flattened tetrahedral geometry that likely arises from bifurcated N—H hydrogen bonds from the organic cations. The alkyl chain of the cation is disordered between gauche and anti conformations with the gauche conformation occupancy refined to 0.707 (2) for the cobaltate. The gauche conformation places the terminal Cl atom at a tetrahedral face of the inorganic complex with a contact distance of 3.7576 (9) Å to the Co2+ center. The anti conformation places the terminal Cl atom at a contact distance to a neighboring anti conformation terminal Cl atom that is ∼1 Å less than the sum of the van der Waals radii. Thus, if the anti conformation is present at a site, then the nearest neighbor must be gauche. DFT geometry optimizations indicate the gauche conformation is more stable in vacuo by 0.226 eV, which reduces to 0.0584 eV when calculated in a uniform dielectric. DFT geometry optimizations for the unprotonated molecule indicate the anti conformation is stabilized by 0.0428 eV in vacuo, with no strongly preferred conformation in uniform dielectric, to provide support to the notion that this cation could function as a molecular switch via deprotonation.

Abstract Background Although electronic cigarettes (e-cigarettes) appear to be effective in helping people who smoke to stop smoking, concerns about use of e-cigarettes among young people have led to restrictions on non-tobacco flavoured e-liquids in some countries and some US states. These restrictions could reduce the appeal of these products to non-smoking youth but could have negative consequences for people who smoke or use e-cigarettes. Methods In this mixed methods study, we recruited UK adults who smoked or used to smoke and subsequently vaped to explore their opinions of unflavoured e-liquids and their beliefs about how they would be impacted by hypothetical e-liquid flavour restrictions. Participants trialled an unflavoured e-liquid instead of their usual nicotine product for four hours and completed a survey and an online interview. Results Using Interpretive Phenomenological Analysis and graphically presented data, we found differences in participants’ opinions of unflavoured e-liquid. If only unflavoured, tobacco flavoured, and menthol flavoured e-liquids remained on the UK market, some people who smoke or vape may be unaffected, but some may relapse to smoking or continue smoking. Despite most wanting to prevent young people from initiating vaping, participants had varying opinions on whether flavour restrictions would be an effective method. Conclusions The findings highlight that people who smoke and vape could be impacted by flavour restrictions in a range of ways, some of which could have a potential adverse impact on harm reduction efforts in the UK (e.g., by making smoking more appealing than vaping).

Abstract Background Nowadays, there is no method to quantitatively characterize the material composition of acute ischemic stroke thrombi prior to intervention, but dual-energy CT (DE-CT) offers imaging-based multimaterial decomposition. We retrospectively investigated the material composition of thrombi ex vivo using DE-CT with histological analysis as a reference. Methods Clots of 70 patients with acute ischemic stroke were extracted by mechanical thrombectomy and scanned ex vivo in formalin-filled tubes with DE-CT. Multimaterial decomposition in the three components, i.e., red blood cells (RBC), white blood cells (WBC), and fibrin/platelets (F/P), was performed and compared to histology (hematoxylin/eosin staining) as reference. Attenuation and effective Z values were assessed, and histological composition was compared to stroke etiology according to the Trial of ORG 10172 in Acute Stroke Treatment (TOAST) criteria. Results Histological and imaging analysis showed the following correlation coefficients for RBC (r = 0.527, p

BackgroundThe extent to which interventions are perceived as acceptable to users impacts engagement and efficacy. ObjectiveIn this study, we evaluated the acceptability of (1) the smartphone app Drink Less (intervention) and (2) the National Health Service (NHS) alcohol advice web page (usual digital care and comparator) among adult drinkers in the United Kingdom participating in a randomized controlled trial evaluating the effectiveness of the Drink Less app. MethodsA subsample of 26 increasing- and higher-risk drinkers (Alcohol Use Disorders Identification Test score≥8) assigned to the intervention group (Drink Less; n=14, 54%; female: n=10, 71%; age: 22-72 years; White: n=9, 64%) or usual digital care group (NHS alcohol advice web page; n=12, 46%; female: n=5, 42%; age: 23-68 years: White: n=9, 75%) took part in semistructured interviews. The interview questions were mapped on to the 7 facets of acceptability according to the Theoretical Framework of Acceptability: affective attitude, burden, perceived effectiveness, ethicality, intervention coherence, opportunity costs, and self-efficacy. Alongside these constructs, we also included a question on perceived personal relevance, which previous research has linked to acceptability and engagement. Framework and thematic analysis of data was undertaken. ResultsThe Drink Less app was perceived as being ethical, easy, user-friendly, and effective for the period the app was used. Participants reported particularly liking the tracking and feedback sections of the app, which they reported increased personal relevance and which resulted in positive affect when achieving their goals. They reported no opportunity cost. Factors such as negative affect when not meeting goals and boredom led to disengagement in the longer term for some participants. The NHS alcohol advice web page was rated as being easy and user-friendly with no opportunity costs. However, the information presented was not perceived as being personally relevant or effective in changing drinking behavior. Most participants reported neutral or negative affect, most participants thought the alcohol advice web page was accessible, and some participants reported ethical concerns around the availability of suggested resources. Some participants reported that it had acted as a starting point or a signpost to other resources. Participants in both groups discussed motivation to change and contextual factors such as COVID-19 lockdowns, which influenced their perceived self-efficacy regardless of their assigned intervention. ConclusionsDrink Less appears to be an acceptable digital intervention among the recruited sample. The NHS alcohol advice web page was generally considered unacceptable as a stand-alone intervention among the recruited sample, although it may signpost and help people access other resources and interventions.

This study demonstrates that GPT-4V outperforms GPT-4 across radiology subspecialties in analyzing 207 cases with 1312 images from the Radiological Society of North America Case Collection.

KRAS is a frequent driver in lung cancer. To identify KRAS-specific vulnerabilities in lung cancer, we performed RNAi screens in primary spheroids derived from a Kras mutant mouse lung cancer model and discovered an epigenetic regulator Ubiquitin-like containing PHD and RING finger domains 1 (UHRF1). In human lung cancer models UHRF1 knock-out selectively impaired growth and induced apoptosis only in KRAS mutant cells. Genome-wide methylation and gene expression analysis of UHRF1-depleted KRAS mutant cells revealed global DNA hypomethylation leading to upregulation of tumor suppressor genes (TSGs). A focused CRISPR/Cas9 screen validated several of these TSGs as mediators of UHRF1-driven tumorigenesis. In vivo, UHRF1 knock-out inhibited tumor growth of KRAS-driven mouse lung cancer models. Finally, in lung cancer patients high UHRF1 expression is anti-correlated with TSG expression and predicts worse outcomes for patients with KRAS mutant tumors. These results nominate UHRF1 as a KRAS-specific vulnerability and potential target for therapeutic intervention.

Abstract Two-sample MR is an increasingly popular method for strengthening causal inference in epidemiological studies. For the effect estimates to be meaningful, variant-exposure and variant-outcome associations must come from comparable populations. A recent systematic review of two-sample MR studies found that, if assessed at all, MR studies evaluated this assumption by checking that the genetic association studies had similar demographics. However, it is unclear if this is sufficient because less easily accessible factors may also be important. Here we propose an easy-to-implement falsification test. Since recent theoretical developments in causal inference suggest that a causal effect estimate can generalise from one study to another if there is exchangeability of effect modifiers, we suggest testing the homogeneity of variant-phenotype associations for a phenotype which has been measured in both genetic association studies as a method of exploring the ‘same-population’ test. This test could be used to facilitate designing MR studies with diverse populations. We developed a simple R package to facilitate the implementation of our proposed test. We hope that this research note will result in increased attention to the same-population assumption, and the development of better sensitivity analyses.

Abstract When dealing with a newly emerging disease such as COVID-19, the impact of patient- and disease-specific factors (e.g., body weight or known co-morbidities) on the immediate course of the disease is largely unknown. An accurate prediction of the most likely individual disease progression can improve the planning of limited resources and finding the optimal treatment for patients. In the case of COVID-19, the need for intensive care unit (ICU) admission of pneumonia patients can often only be determined on short notice by acute indicators such as vital signs (e.g., breathing rate, blood oxygen levels), whereas statistical analysis and decision support systems that integrate all of the available data could enable an earlier prognosis. To this end, we propose a holistic, multimodal graph-based approach combining imaging and non-imaging information. Specifically, we introduce a multimodal similarity metric to build a population graph that shows a clustering of patients. For each patient in the graph, we extract radiomic features from a segmentation network that also serves as a latent image feature encoder. Together with clinical patient data like vital signs, demographics, and lab results, these modalities are combined into a multimodal representation of each patient. This feature extraction is trained end-to-end with an image-based Graph Attention Network to process the population graph and predict the COVID-19 patient outcomes: admission to ICU, need for ventilation, and mortality. To combine multiple modalities, radiomic features are extracted from chest CTs using a segmentation neural network. Results on a dataset collected in Klinikum rechts der Isar in Munich, Germany and the publicly available iCTCF dataset show that our approach outperforms single modality and non-graph baselines. Moreover, our clustering and graph attention increases understanding of the patient relationships within the population graph and provides insight into the network’s decision-making process.

The landscape of clinical research is continuously evolving, focusing now on the scientific assessment of efficacy balanced with patient safety, along with advancements in technology and informatics. These considerations necessitate the acquisition and retention of experienced staff that will be able to meet the demands associated with these new focus areas and can provide support for administrative duties, regulatory duties, study participant management, and data collection at individual research sites. Furthermore, the identification of Clinical Trials Administrators that can function independently and collaboratively within a large, integrated healthcare system clinical research consortium can be a challenging task. Currently, there is a limited amount of publicly available information on strategies that have been employed to identify these types of candidates in this type of setting. The primary aim of this project was to determine if the development of a virtual interview panel, or Manager Interview Panel (MIP), would be effective in screening, interviewing, and ranking applicants for a vacant Associate Director-- Operations (ADO) position at one of the Node sites in our clinical research consortium. The findings may inform individuals or groups in research administration and leadership roles seeking to improve the candidate selection component of their respective hiring processes, particularly for those groups that are a part of clinical research consortiums and have study sites that are geographically dispersed and not in close proximity to one another.

Work engagement is defined as a positive work-related state of mind that is characterized by vigor, dedication, and absorption. The engagement of staff has been associated with their performance and efficiency, productivity, safety, attendance and retention, customer service and satisfaction, and several other organizational success factors. The Coronavirus Disease 2019 (COVID-19) is an infectious disease caused by the most recently discovered coronavirus and is now a pandemic that is affecting many countries globally. The literature surrounding the employment of measures and strategies to increase work engagement amongst clinical research staff during pandemics is scarce, and to date, focuses primarily on health care and community health workers. The Cooperative Studies Program (CSP) Network of Dedicated Enrollment Sites (NODES) is a clinical research consortium of ten medical centers that are embedded within the Department of Veterans Affairs (VA) Health Care System. The consortium developed and implemented strategies during the pandemic that were intended to maintain work engagement amongst clinical research staff at each of the sites within the consortium. In this manuscript, we describe the development and deployment of these strategies to clinical research study teams in our clinical research consortium. It is our hope that the opportunities, successes, and challenges described here will serve as a useful resource for other clinical research consortia that are working to identify approaches to keep their staff members engaged during the current pandemic, as well as in other potential future situations in which their primary operations may be altered during other times of crises.

Abstract Comparative anatomy is an important tool for investigating evolutionary relationships among species, but the lack of scalable imaging tools and stains for rapidly mapping the microscale anatomies of related species poses a major impediment to using comparative anatomy approaches for identifying evolutionary adaptations. We describe a method using synchrotron source micro‐x‐ray computed tomography (syn‐μXCT) combined with machine learning algorithms for high‐throughput imaging of Lepidoptera (i.e., butterfly and moth) eyes. Our pipeline allows for imaging at rates of ~15 min/mm3 at 600 nm3 resolution. Image contrast is generated using standard electron microscopy labeling approaches (e.g., osmium tetroxide) that unbiasedly labels all cellular membranes in a species‐independent manner thus removing any barrier to imaging any species of interest. To demonstrate the power of the method, we analyzed the 3D morphologies of butterfly crystalline cones, a part of the visual system associated with acuity and sensitivity and found significant variation within six butterfly individuals. Despite this variation, a classic measure of optimization, the ratio of interommatidial angle to resolving power of ommatidia, largely agrees with early work on eye geometry across species. We show that this method can successfully be used to determine compound eye organization and crystalline cone morphology. Our novel pipeline provides for fast, scalable visualization and analysis of eye anatomies that can be applied to any arthropod species, enabling new questions about evolutionary adaptations of compound eyes and beyond.

The detrimental health effects of smoking are well-known, but the impact of regular nicotine use without exposure to the other constituents of tobacco is less clear. Given the increasing daily use of alternative nicotine delivery systems, such as e-cigarettes, it is increasingly important to understand and separate the effects of nicotine use from the impact of tobacco smoke exposure. Using a multivariable Mendelian randomisation framework, we explored the direct effects of nicotine compared with the non-nicotine constituents of tobacco smoke on health outcomes (lung cancer, chronic obstructive pulmonary disease [COPD], forced expiratory volume in one second [FEV-1], forced vital capacity [FVC], coronary heart disease [CHD], and heart rate [HR]). We used Genome-Wide Association Study (GWAS) summary statistics from Buchwald and colleagues, the GWAS and Sequencing Consortium of Alcohol and Nicotine, the International Lung Cancer Consortium, and UK Biobank. Increased nicotine metabolism increased the risk of COPD, lung cancer, and lung function in the univariable analysis. However, when accounting for smoking heaviness in the multivariable analysis, we found that increased nicotine metabolite ratio (indicative of decreased nicotine exposure per cigarette smoked) decreases heart rate (b = -0.30, 95% CI -0.50 to -0.10) and lung function (b = -33.33, 95% CI -41.76 to -24.90). There was no clear evidence of an effect on the remaining outcomes. The results suggest that these smoking-related outcomes are not due to nicotine exposure but are caused by the other components of tobacco smoke; however, there are multiple potential sources of bias, and the results should be triangulated using evidence from a range of methodologies.

ObjectiveTo investigate the genetic architecture of internalizing symptoms in childhood and adolescence.MethodIn 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument.ResultsThe meta-analysis of overall internalizing symptoms (INToverall) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, neffective = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|rg| > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |rg| = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa.ConclusionGenetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success.

BackgroundOrgan transplantation from donors with human immunodeficiency virus (HIV) to recipients with HIV (HIV D+/R+) presents risks of donor-derived infections. Understanding clinical, immunologic, and virologic characteristics of HIV-positive donors is critical for safety.MethodsWe performed a prospective study of donors with HIV-positive and HIV false-positive (FP) test results within the HIV Organ Policy Equity (HOPE) Act in Action studies of HIV D+/R+ transplantation (ClinicalTrials.gov NCT02602262, NCT03500315, and NCT03734393). We compared clinical characteristics in HIV-positive versus FP donors. We measured CD4 T cells, HIV viral load (VL), drug resistance mutations (DRMs), coreceptor tropism, and serum antiretroviral therapy (ART) detection, using mass spectrometry in HIV-positive donors.ResultsBetween March 2016 and March 2020, 92 donors (58 HIV positive, 34 FP), representing 98.9% of all US HOPE donors during this period, donated 177 organs (131 kidneys and 46 livers). Each year the number of donors increased. The prevalence of hepatitis B (16% vs 0%), syphilis (16% vs 0%), and cytomegalovirus (CMV; 91% vs 58%) was higher in HIV-positive versus FP donors; the prevalences of hepatitis C viremia were similar (2% vs 6%). Most HIV-positive donors (71%) had a known HIV diagnosis, of whom 90% were prescribed ART and 68% had a VL

Cardiac motion causes unpredictable signal loss in respiratory-triggered diffusion-weighted magnetic resonance imaging (DWI) of the liver, especially inside the left lobe. The left liver lobe may thus be frequently neglected in the clinical evaluation of liver DWI. In this work, a data-driven algorithm that relies on the statistics of the signal in the left liver lobe to mitigate the motion-induced signal loss is presented. The proposed data-driven algorithm utilizes the exclusion of severely corrupted images with subsequent spatially dependent image scaling based on a signal-loss model to correctly combine the multi-average diffusion-weighted images. The signal in the left liver lobe is restored and the liver signal is more homogeneous after applying the proposed algorithm. Furthermore, overestimation of the apparent diffusion coefficient (ADC) in the left liver lobe is reduced. The proposed algorithm can therefore contribute to reduce the motion-induced bias in DWI of the liver and help to increase the diagnostic value of DWI in the left liver lobe.

Abstract Background To determine whether denoised areal bone mineral density (BMD) measurements from scout scans in spectral detector computed tomography (CT) correlate with volumetric trabecular BMD for opportunistic osteoporosis screening. Methods A 64-slice single-source dual-layer spectral CT scanner was used to acquire scout scan data of 228 lumbar vertebral bodies within 57 patients. Scout scans in anterior–posterior (AP) view were performed with a dose of