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Introduction: The management of type II endoleak after EVAR continues to evolve. Most literature recommends intervention if aneurysm sac expansion is greater than 5 mm on surveillance imaging. Transcaval access has recently emerged as an effective technique to access the excluded aneurysm sac for endoleak embolization. One limitation of this approach may be direct visualization and cannulation of endoleak cavities within a large aneurysm sac as standard intravascular ultrasound (IVUS) has depth limitations. We present a series of patients in which an Intracardiac Echocardiography (ICE) catheter was used to assist in type II endoleak cavity cannulation, embolization, and confirmation of cessation of flow. Methods: From 2021 – 2022, patients who underwent transcaval embolization of type II endoleak after EVAR were included in our study. All patients were noted to have persistent endoleak with aneurysm sac expansion and failure or inability to perform sac endoleak embolization via conventional methods (transmesenteric, translumbar).ICE catheter was advanced into the IVC via the left common femoral vein. Real-time intra-sac ultrasound was performed via the ICE catheter and the radiopaque tip of the catheter was positioned directly over the endoleak cavity. The radio-opaque tip thus served as a marker for the point of sac entry. A TIPS catheter via the right common femoral vein was used to achieve transcaval access into the excluded aneurysm sac.Embolization was performed using coils or Onyx liquid embolic system (LES), at the discretion of the operating surgeon. Procedural success was defined by cessation of flow in endoleak cavity angiographically, via ICE catheter, and on post-op CT imaging. Results: A total of three patients had endoleaks treated using ICE catheter-assisted transcaval access from 2021 – 2022. Average patient age was 78 years old, average aneurysm sac size at the time of transcaval embolization was 6.75 cm, and average aneurysm sac growth following initial EVAR was 0.45 cm. The average fluoroscopy time for each procedure was 16.8 min, total radiation dose was 1010.06 mGy, and contrast used was 25 mL. Average EBL for the procedure was 7 mL. All procedures were performed in the outpatient setting and patients were discharged home the same day. There were no major adverse events (MAEs) within the first 30-days post-procedure.All three patients had successful embolization of the endoleak cavity, verified by both ICE catheter intra-procedurally and on post-op imaging. Aneurysm sac size was noted to be stable in one patient post-procedurally and was noted to be decreasing in size in two patients. Average patient follow-up time was approximately two weeks after endoleak embolization. Conclusion: The novel use of the ICE catheter allows for: (1) direct visualization of the endoleak cavity prior to transcaval access and (2) confirmation of cessation of blood flow into the sac at the termination of the procedure. The procedure proved to be safe for all three cases described, with the endpoint of endoleak embolization achieved without any ill-effects to the patients. Further study is warranted in the utility of this device in performing transcaval embolization procedures.

Selecting a wind farm layout optimization method is difficult. Comparisons between optimization methods in different papers can be uncertain due to the difficulty of exactly reproducing the objective function. Comparisons by just a few authors in one paper can be uncertain if the authors do not have experience using each algorithm. In this work we provide an algorithm comparison for a wind farm layout optimization case study between eight optimization methods applied, or directed, by researchers who developed those algorithms or who had other experience using them. We provided the objective function to each researcher to avoid ambiguity about relative performance due to a difference in objective function. While these comparisons are not perfect, we try to treat each algorithm more fairly by having researchers with experience using each algorithm apply each algorithm and by having a common objective function provided for analysis. The case study is from the International Energy Association (IEA) Wind Task 37, based on the Borssele III and IV wind farms with 81 turbines. Of particular interest in this case study is the presence of disconnected boundary regions and concave boundary features. The optimization methods studied represent a wide range of approaches, including gradient-free, gradient-based, and hybrid methods; discrete and continuous problem formulations; single-run and multi-start approaches; and mathematical and heuristic algorithms. We provide descriptions and references (where applicable) for each optimization method, as well as lists of pros and cons, to help readers determine an appropriate method for their use case. All the optimization methods perform similarly, with optimized wake loss values between 15.48 % and 15.70 % as compared to 17.28 % for the unoptimized provided layout. Each of the layouts found were different, but all layouts exhibited similar characteristics. Strong similarities across all the layouts include tightly packing wind turbines along the outer borders, loosely spacing turbines in the internal regions, and allocating similar numbers of turbines to each discrete boundary region. The best layout by annual energy production (AEP) was found using a new sequential allocation method, discrete exploration-based optimization (DEBO). Based on the results in this study, it appears that using an optimization algorithm can significantly improve wind farm performance, but there are many optimization methods that can perform well on the wind farm layout optimization problem, given that they are applied correctly.

Background: Vegetable consumption is known to reduce the risk of various chronic health conditions. Yet a small percentage of US adults consume enough vegetables to meet national dietary guidelines. The SouthEats community-led meal–kit service was developed in Washington DC to address known barriers to healthy eating and vegetable consumption among middle- and low-income households. Methods: Using a series of online surveys, we conducted a pilot study to provide preliminary information on the influence of SouthEats on vegetable consumption and factors known to influence vegetable consumption. Wilcoxon matched-pair sign ranked tests were used to examine changes in key outcomes between baseline, midpoint and endpoint surveys. Results: Among SouthEats customers who completed all pilot study surveys (n = 23) there was a significant decrease in the median amount of time spent on meal prep between baseline and midpoint. Between baseline and endpoint, participants also indicated increased feelings that they had enough time to meet their needs including cooking healthfully. Overall vegetable and fruit and vegetable consumption increased between the baseline and midpoint but then decreased between the midpoint and endpoint survey periods. However, there were no statistically significant changes in the outcomes of home eating behaviors, perceptions of neighborhood healthy food access, vegetable self-efficacy, or vegetable consumption. Conclusion: Our results provide some preliminary evidence suggesting that the SouthEats meal-kit service could help reduce the amount of time spent on cooking, reduce feelings of time scarcity, and increase vegetable consumption in the short-term. Further research exploring this topic will require a larger study sample.

Abstract Common data models solve many challenges of standardizing electronic health record (EHR) data but are unable to semantically integrate all of the resources needed for deep phenotyping. Open Biological and Biomedical Ontology (OBO) Foundry ontologies provide computable representations of biological knowledge and enable the integration of heterogeneous data. However, mapping EHR data to OBO ontologies requires significant manual curation and domain expertise. We introduce OMOP2OBO, an algorithm for mapping Observational Medical Outcomes Partnership (OMOP) vocabularies to OBO ontologies. Using OMOP2OBO, we produced mappings for 92,367 conditions, 8611 drug ingredients, and 10,673 measurement results, which covered 68–99% of concepts used in clinical practice when examined across 24 hospitals. When used to phenotype rare disease patients, the mappings helped systematically identify undiagnosed patients who might benefit from genetic testing. By aligning OMOP vocabularies to OBO ontologies our algorithm presents new opportunities to advance EHR-based deep phenotyping.

The recent breakthroughs of Large Language Models (LLMs) in the context of natural language processing have opened the way to significant advances in protein research. Indeed, the relationships between human natural language and the “language of proteins” invite the application and adaptation of LLMs to protein modelling and design. Considering the impressive results of GPT-4 and other recently developed LLMs in processing, generating and translating human languages, we anticipate analogous results with the language of proteins. Indeed, protein language models have been already trained to accurately predict protein properties, generate novel functionally characterized proteins, achieving state-of-the-art results. In this paper we discuss the promises and the open challenges raised by this novel and exciting research area, and we propose our perspective on how LLMs will affect protein modeling and design.

Summary: Background: The cause and symptoms of long COVID are poorly understood. It is challenging to predict whether a given COVID-19 patient will develop long COVID in the future. Methods: We used electronic health record (EHR) data from the National COVID Cohort Collaborative to predict the incidence of long COVID. We trained two machine learning (ML) models — logistic regression (LR) and random forest (RF). Features used to train predictors included symptoms and drugs ordered during acute infection, measures of COVID-19 treatment, pre-COVID comorbidities, and demographic information. We assigned the ‘long COVID’ label to patients diagnosed with the U09.9 ICD10-CM code. The cohorts included patients with (a) EHRs reported from data partners using U09.9 ICD10-CM code and (b) at least one EHR in each feature category. We analysed three cohorts: all patients (n = 2,190,579; diagnosed with long COVID = 17,036), inpatients (149,319; 3,295), and outpatients (2,041,260; 13,741). Findings: LR and RF models yielded median AUROC of 0.76 and 0.75, respectively. Ablation study revealed that drugs had the highest influence on the prediction task. The SHAP method identified age, gender, cough, fatigue, albuterol, obesity, diabetes, and chronic lung disease as explanatory features. Models trained on data from one N3C partner and tested on data from the other partners had average AUROC of 0.75. Interpretation: ML-based classification using EHR information from the acute infection period is effective in predicting long COVID. SHAP methods identified important features for prediction. Cross-site analysis demonstrated the generalizability of the proposed methodology. Funding: NCATS U24 TR002306, NCATS UL1 TR003015, Axle Informatics Subcontract: NCATS-P00438-B, NIH/NIDDK/OD, PSR2015-1720GVALE_01, G43C22001320007, and Director, Office of Science, Office of Basic Energy Sciences of the U.S. Department of Energy Contract No. DE-AC02-05CH11231.

Abstract Background Evaluating the impact of environmental exposures on organism health is a key goal of modern biomedicine and is critically important in an age of greater pollution and chemicals in our environment. Environmental health utilizes many different research methods and generates a variety of data types. However, to date, no comprehensive database represents the full spectrum of environmental health data. Due to a lack of interoperability between databases, tools for integrating these resources are needed. In this manuscript we present the Environmental Conditions, Treatments, and Exposures Ontology (ECTO), a species-agnostic ontology focused on exposure events that occur as a result of natural and experimental processes, such as diet, work, or research activities. ECTO is intended for use in harmonizing environmental health data resources to support cross-study integration and inference for mechanism discovery. Methods and findings ECTO is an ontology designed for describing organismal exposures such as toxicological research, environmental variables, dietary features, and patient-reported data from surveys. ECTO utilizes the base model established within the Exposure Ontology (ExO). ECTO is developed using a combination of manual curation and Dead Simple OWL Design Patterns (DOSDP), and contains over 2700 environmental exposure terms, and incorporates chemical and environmental ontologies. ECTO is an Open Biological and Biomedical Ontology (OBO) Foundry ontology that is designed for interoperability, reuse, and axiomatization with other ontologies. ECTO terms have been utilized in axioms within the Mondo Disease Ontology to represent diseases caused or influenced by environmental factors, as well as for survey encoding for the Personalized Environment and Genes Study (PEGS). Conclusions We constructed ECTO to meet Open Biological and Biomedical Ontology (OBO) Foundry principles to increase translation opportunities between environmental health and other areas of biology. ECTO has a growing community of contributors consisting of toxicologists, public health epidemiologists, and health care providers to provide the necessary expertise for areas that have been identified previously as gaps.

Abstract Background This review has been developed following a panel discussion with an international group of experts in the care of patients with obesity in the critical care setting and focuses on current best practices in malnutrition screening and assessment, estimation of energy needs for patients with obesity, the risks and management of sarcopenic obesity, the value of tailored nutrition recommendations, and the emerging role of immunonutrition. Patients admitted to the intensive care unit (ICU) increasingly present with overweight and obesity that require individualized nutrition considerations due to underlying comorbidities, immunological factors such as inflammation, and changes in energy expenditure and other aspects of metabolism. While research continues to accumulate, important knowledge gaps persist in recognizing and managing the complex nutritional needs in ICU patients with obesity. Available malnutrition screening and assessment tools are limited in patients with obesity due to a lack of validation and heterogeneous factors impacting nutrition status in this population. Estimations of energy and protein demands are also complex in patients with obesity and may include estimations based upon ideal, actual, or adjusted body weight. Evidence is still sparse on the role of immunonutrition in patients with obesity, but the presence of inflammation that impacts immune function may suggest a role for these nutrients in hemodynamically stable ICU patients. Educational efforts are needed for all clinicians who care for complex cases of critically ill patients with obesity, with a focus on strategies for optimal nutrition and the consideration of issues such as weight stigma and bias impacting the delivery of care. Conclusions Current nutritional strategies for these patients should be undertaken with a focus on individualized care that considers the whole person, including the possibility of preexisting comorbidities, altered metabolism, and chronic stigma, which may impact the provision of nutritional care. Additional research should focus on the applicability of current guidelines and evidence for nutrition therapy in populations with obesity, especially in the setting of critical illness.

IntroductionIncreasing calls have been made to decolonize global health education but there has been a lack of consensus and clarity on how this should be done. We conducted a qualitative study to understand current educational programs and curricula that aim to educate public health and allied health students to increase awareness of how colonialist structures of power influence current global health practice and provide students with tools to decolonize global health. Our goal is to inform related curriculum development and provide recommendations.MethodsWe conducted key-informant interviews with 14 study coordinators and faculty from institutions of higher learning with global health programs who are involved in developing educational approaches. All interviews were audio recorded, transcribed, and analyzed using an ‘up from the data’ approach.ResultsParticipants varied in their understanding of decolonizing global health and recognized that there is a lack of guidance in the field; this has an impact on how curriculum is developed and taught. Participants described a range of decolonizing global health educational activities in the classrooms and in applied learning activities. Most programming was situated in Diversity, Equity, and Inclusion Initiatives and participants did not always feel this was the best ‘home’ for such work; to some this reflected a lack of institutional support. Other institutional barriers included lack of protected time for faculty and limited budgets for speaker honoraria, co-creation, and related teaching expenses.DiscussionInstitutes of higher learning can play an important role, either positively or negatively, in decolonizing global health education. At a minimum such institutions should financially support faculty to incorporate decolonizing global health in their pedagogy and strengthen scholarship towards common understandings. More substantive institutional support is needed however to meaningfully transform institutional relationships that actively support equitable partnerships, co-creation, and responsiveness to local community priorities.

AimsDiabetic foot care is a significant burden on the NHS in England. We have conducted a nationwide survey to determine the current participation of orthopaedic surgeons in diabetic foot care in England.MethodsA questionnaire was sent to all 136 NHS trusts audited in the 2018 National Diabetic Foot Audit (NDFA). The questionnaire asked about the structure of diabetic foot care services.ResultsOverall, 123 trusts responded, of which 117 admitted patients with diabetic foot disease and 113 had an orthopaedic foot and ankle surgeon. A total of 90 trusts (77%) stated that the admission involved medicine, with 53 (45%) of these admissions being exclusively under medicine, and 37 (32%) as joint admissions. Of the joint admissions, 16 (14%) were combined with vascular and 12(10%) with orthopaedic surgery. Admission is solely under vascular surgery in 12 trusts (10%) and orthopaedic surgery in 7 (6%). Diabetic foot abscesses were drained by orthopaedic surgeons in 61 trusts (52%) and vascular surgeons in 47 (40%).ConclusionOrthopaedic surgeons make a significant contribution to both acute and elective diabetic foot care currently in the UK. This contribution is likely to increase with the movement of vascular surgery to a hub and spoke model, and measures should be put in place to increase the team based approach to the diabetic foot, for example with the introduction of a best practice tariff.Cite this article: Bone Jt Open 2022;3(8):618–622.

Abstract Background Subjective cognitive decline (SCD) is present in the early stage of preclinical Alzheimer’s disease (AD) and is associated with an increased risk of further cognitive decline and AD dementia later in life. Early detection of at-risk groups with subjective complaints is critical for targeted dementia prevention at the earliest. Accurate assessment of SCD is crucial. However, current measures lack important psychometric evaluations and or reporting. Objectives To systematically evaluate measurement properties of self-reported outcome measures (PROMs) used to assess SCD in the older adult population with or at risk of AD. Methods and analysis We used the Preferred Reporting Items for Systematic Reviews and Meta-Analysis Protocols 2015 Checklist for reporting. We conducted a literature search, screened, and included validation studies of SCD based on self-reported questionnaires from both population-based and clinical studies, conducted in older adults (≥ 55). We critically appraised the included primary studies using the Consensus-based Standards for the selection of health Measurement Instruments (COSMIN) guidelines. Results Sixteen studies met the inclusion criteria. The included studies reported psychometric properties of 17 SCD self-reported questionnaires. We extracted data on the structural validity, internal consistency, test-retest reliability, and cross-cultural validity and found a widespread proneness to bias across studies, and a marked heterogeneity is assessed and reported measurement properties that prevented the consolidation of results. Conclusion Our findings suggest that available SCD questionnaires lack content validity evaluation. Currently available measurements of SCD lack development and validation standards. Further work is needed to develop and validate SCD self-reported measurement with good quality measurement properties.

Single cell sequencing technologies have rapidly advanced in the last decade and are increasingly applied to gain unprecedented insights by deconstructing complex biology to its fundamental unit, the individual cell. First developed for measurement of gene expression, single cell sequencing approaches have evolved to allow simultaneous profiling of multiple additional features, including chromatin accessibility within the nucleus and protein expression at the cell surface. These multi-omic approaches can now further be applied to cells in situ, capturing the spatial context within which their biology occurs. To extract insights from these complex datasets, new computational tools have facilitated the integration of information across different data types and the use of machine learning approaches. Here, we summarize current experimental and computational methods for generation and integration of single cell multi-omic datasets. We focus on opportunities for multi-omic single cell sequencing to augment therapeutic development for kidney disease, including applications for biomarkers, disease stratification and target identification.

Abstract The Global Alliance for Genomics and Health (GA4GH) is developing a suite of coordinated standards for genomics for healthcare. The Phenopacket is a new GA4GH standard for sharing disease and phenotype information that characterizes an individual person, linking that individual to detailed phenotypic descriptions, genetic information, diagnoses, and treatments. A detailed example is presented that illustrates how to use the schema to represent the clinical course of a patient with retinoblastoma, including demographic information, the clinical diagnosis, phenotypic features and clinical measurements, an examination of the extirpated tumor, therapies, and the results of genomic analysis. The Phenopacket Schema, together with other GA4GH data and technical standards, will enable data exchange and provide a foundation for the computational analysis of disease and phenotype information to improve our ability to diagnose and conduct research on all types of disorders, including cancer and rare diseases.

Abstract Background Non-steroidal anti-inflammatory drugs (NSAIDs) are commonly used to reduce pain, fever, and inflammation but have been associated with complications in community-acquired pneumonia. Observations shortly after the start of the COVID-19 pandemic in 2020 suggested that ibuprofen was associated with an increased risk of adverse events in COVID-19 patients, but subsequent observational studies failed to demonstrate increased risk and in one case showed reduced risk associated with NSAID use. Methods A 38-center retrospective cohort study was performed that leveraged the harmonized, high-granularity electronic health record data of the National COVID Cohort Collaborative. A propensity-matched cohort of 19,746 COVID-19 inpatients was constructed by matching cases (treated with NSAIDs at the time of admission) and 19,746 controls (not treated) from 857,061 patients with COVID-19 available for analysis. The primary outcome of interest was COVID-19 severity in hospitalized patients, which was classified as: moderate, severe, or mortality/hospice. Secondary outcomes were acute kidney injury (AKI), extracorporeal membrane oxygenation (ECMO), invasive ventilation, and all-cause mortality at any time following COVID-19 diagnosis. Results Logistic regression showed that NSAID use was not associated with increased COVID-19 severity (OR: 0.57 95% CI: 0.53–0.61). Analysis of secondary outcomes using logistic regression showed that NSAID use was not associated with increased risk of all-cause mortality (OR 0.51 95% CI: 0.47–0.56), invasive ventilation (OR: 0.59 95% CI: 0.55–0.64), AKI (OR: 0.67 95% CI: 0.63–0.72), or ECMO (OR: 0.51 95% CI: 0.36–0.7). In contrast, the odds ratios indicate reduced risk of these outcomes, but our quantitative bias analysis showed E-values of between 1.9 and 3.3 for these associations, indicating that comparatively weak or moderate confounder associations could explain away the observed associations. Conclusions Study interpretation is limited by the observational design. Recording of NSAID use may have been incomplete. Our study demonstrates that NSAID use is not associated with increased COVID-19 severity, all-cause mortality, invasive ventilation, AKI, or ECMO in COVID-19 inpatients. A conservative interpretation in light of the quantitative bias analysis is that there is no evidence that NSAID use is associated with risk of increased severity or the other measured outcomes. Our results confirm and extend analogous findings in previous observational studies using a large cohort of patients drawn from 38 centers in a nationally representative multicenter database.

Abstract Structural variants (SVs) are implicated in the etiology of Mendelian diseases but have been systematically underascertained owing to sequencing technology limitations. Long-read sequencing enables comprehensive detection of SVs, but approaches for prioritization of candidate SVs are needed. Structural variant Annotation and analysis (SvAnna) assesses all classes of SVs and their intersection with transcripts and regulatory sequences, relating predicted effects on gene function with clinical phenotype data. SvAnna places 87% of deleterious SVs in the top ten ranks. The interpretable prioritizations offered by SvAnna will facilitate the widespread adoption of long-read sequencing in diagnostic genomics. SvAnna is available at https://github.com/TheJacksonLaboratory/SvAnn a .

Abstract Although certain individuals with HIV infection can stop antiretroviral therapy (ART) without viral load rebound, the mechanisms under-pinning ‘post-treatment control’ remain unclear. Using RNA-Seq we explored CD4 T cell gene expression to identify evidence of a mechanism that might underpin virological rebound and lead to discovery of associated biomarkers. Fourteen female participants who received 12 months of ART starting from primary HIV infection were sampled at the time of stopping therapy. Two analysis methods (Differential Gene Expression with Gene Set Enrichment Analysis, and Weighted Gene Co-expression Network Analysis) were employed to interrogate CD4+ T cell gene expression data and study pathways enriched in post-treatment controllers versus early rebounders. Using independent analysis tools, expression of genes associated with type I interferon responses were associated with a delayed time to viral rebound following treatment interruption (TI). Expression of four genes identified by Cox-Lasso (ISG15, XAF1, TRIM25 and USP18) was converted to a Risk Score, which associated with rebound (p

The Global Alliance for Genomics and Health (GA4GH) is a standards-setting organization that is developing a suite of coordinated standards for genomics. The GA4GH Phenopacket Schema is a standard for sharing disease and phenotype information that characterizes an individual person or biosample. The Phenopacket Schema is flexible and can represent clinical data for any kind of human disease including rare disease, complex disease, and cancer. It also allows consortia or databases to apply additional constraints to ensure uniform data collection for specific goals. We present phenopacket-tools, an open-source Java library and command-line application for construction, conversion, and validation of phenopackets. Phenopacket-tools simplifies construction of phenopackets by providing concise builders, programmatic shortcuts, and predefined building blocks (ontology classes) for concepts such as anatomical organs, age of onset, biospecimen type, and clinical modifiers. Phenopacket-tools can be used to validate the syntax and semantics of phenopackets as well as to assess adherence to additional user-defined requirements. The documentation includes examples showing how to use the Java library and the command-line tool to create and validate phenopackets. We demonstrate how to create, convert, and validate phenopackets using the library or the command-line application. Source code, API documentation, comprehensive user guide and a tutorial can be found at https://github.com/phenopackets/phenopacket-tools. The library can be installed from the public Maven Central artifact repository and the application is available as a standalone archive. The phenopacket-tools library helps developers implement and standardize the collection and exchange of phenotypic and other clinical data for use in phenotype-driven genomic diagnostics, translational research, and precision medicine applications.

Summary: Background: Stratification of patients with post-acute sequelae of SARS-CoV-2 infection (PASC, or long COVID) would allow precision clinical management strategies. However, long COVID is incompletely understood and characterised by a wide range of manifestations that are difficult to analyse computationally. Additionally, the generalisability of machine learning classification of COVID-19 clinical outcomes has rarely been tested. Methods: We present a method for computationally modelling PASC phenotype data based on electronic healthcare records (EHRs) and for assessing pairwise phenotypic similarity between patients using semantic similarity. Our approach defines a nonlinear similarity function that maps from a feature space of phenotypic abnormalities to a matrix of pairwise patient similarity that can be clustered using unsupervised machine learning. Findings: We found six clusters of PASC patients, each with distinct profiles of phenotypic abnormalities, including clusters with distinct pulmonary, neuropsychiatric, and cardiovascular abnormalities, and a cluster associated with broad, severe manifestations and increased mortality. There was significant association of cluster membership with a range of pre-existing conditions and measures of severity during acute COVID-19. We assigned new patients from other healthcare centres to clusters by maximum semantic similarity to the original patients, and showed that the clusters were generalisable across different hospital systems. The increased mortality rate originally identified in one cluster was consistently observed in patients assigned to that cluster in other hospital systems. Interpretation: Semantic phenotypic clustering provides a foundation for assigning patients to stratified subgroups for natural history or therapy studies on PASC. Funding: NIH (TR002306/OT2HL161847-01/OD011883/HG010860), U.S.D.O.E. (DE-AC02-05CH11231), Donald A. Roux Family Fund at Jackson Laboratory, Marsico Family at CU Anschutz.

Abstract Capillary endothelial cells of the human blood–brain barrier (BBB) express high levels of P-glycoprotein (P-gp, encoded by ABCB1) and ABCG2 (encoded by ABCG2). However, little information is available regarding ATP-binding cassette transporters expressed at the zebrafish BBB, which has emerged as a potential model system. We report the characterization and tissue localization of two genes that are similar to ABCB1, zebrafish abcb4 and abcb5. When stably expressed in HEK293 cells, both Abcb4 and Abcb5 conferred resistance to P-gp substrates; however, Abcb5 poorly transported doxorubicin and mitoxantrone compared to zebrafish Abcb4. Additionally, Abcb5 did not transport the fluorescent P-gp probes BODIPY-ethylenediamine or LDS 751, while they were transported by Abcb4. High-throughput screening of 90 human P-gp substrates confirmed that Abcb4 has an overlapping substrate specificity profile with P-gp. In the brain vasculature, RNAscope probes for abcb4 colocalized with staining by the P-gp antibody C219, while abcb5 was not detected. The abcb4 probe also colocalized with claudin-5 in brain endothelial cells. Abcb4 and Abcb5 had different tissue localizations in multiple zebrafish tissues, potentially indicating different functions. The data suggest that zebrafish Abcb4 functionally phenocopies P-gp and that the zebrafish may serve as a model to study the role of P-gp at the BBB.

DNA methylation targets CpG island promoters of germline genes to repress their expression in mouse somatic cells. Here the authors show that a transcription factor E2F6 is required to target CpG island DNA methylation and epigenetic silencing to germline genes during early mouse development.

ABSTRACT Obesity has been linked to higher morbidity and mortality in those that contract novel viruses, such as H1N1 and SARS-CoV-2. Loss of life and the high cost of obesity highlight the need to focus on preventative measures. The state of Maine (United States) is profiled as a rural state with high rates of obesity and low health literacy that benefits from programs to improve health. However, more multidirectional efforts are needed. Four recommendations for building a healthier, more resilient patient population are discussed here: (i) state incentives and subsidies, (ii) employers to incentivize healthy living, (iii) federal incentives and initiatives, and (iv) personal responsibility for health and wellness.

Abstract Background University students have limited opportunities to gain healthcare clinical exposure within an academic curriculum. Furthermore, traditional pre-medical clinical experiences like shadowing lack active learning components. This may make it difficult for students to make an informed decision about pursuing biomedical professions. An academic university level research course with bedside experience provides students direct clinical participation in the healthcare setting. Methods Described is a research immersion course for senior university students (3rd to 5th year) interested in healthcare and reported study enrollment with final course evaluations. The setting was an adult, academic, urban, level 1 trauma center emergency department (ED) within a tertiary-care, 1000-bed, medical center. Our course, “Immersion in Emergency Care Research”, was offered as a university senior level class delivered consecutively over 16-weeks for students interested in healthcare careers. Faculty and staff from the Department of Emergency Medicine provided a classroom lecture program and extensive bedside, hands-on clinical research experience. Students enrolled patients in a survey study requiring informed consent, interviews, data abstraction and data entry. Additionally, they were required to write and present a mock emergency care research proposal inspired by their clinical experience. The course evaluations from students’ ordinal rankings and blinded text responses report possible career impact. Results Thirty-two students, completed the 16-week, 6–9 h per week, course from August to December in 1 of 4 years (2016 to 2019). Collectively, students enrolled 759 ED patients in the 4 survey studies and reported increased confidence in the clinical research process as each week progressed. Ranked evaluations were extremely positive, with many students describing how the course significantly impacted their career pathways and addressed an unmet need in biomedical education. Six students continued the research experience from the course through independent study using the survey data to develop 3 manuscripts for submission to peer-reviewed journals. Conclusions A bedside emergency care research course for students with pre-healthcare career aspirations can successfully provide early exposure to patients and emergency care, allow direct experience with clinical bedside research, research data collection, and may impact biomedical science career choices.

Abstract We present Hierarchical Bayesian Analysis of Differential Expression and ALternative Splicing (HBA-DEALS), which simultaneously characterizes differential expression and splicing in cohorts. HBA-DEALS attains state of the art or better performance for both expression and splicing and allows genes to be characterized as having differential gene expression, differential alternative splicing, both, or neither. HBA-DEALS analysis of GTEx data demonstrated sets of genes that show predominant DGE or DAST across multiple tissue types. These sets have pervasive differences with respect to gene structure, function, membership in protein complexes, and promoter architecture.

Mutations in the TRPV4 channel cause inherited neurodegeneration syndromes, but the molecular mechanisms are unknown. Here the authors reveal that TRPV4 activation causes dose-dependent, CaMKII-mediated neuronal dysfunction and axonal degeneration via disruption of mitochondrial axonal transport.

Abstract Background Defects in the glycosylphosphatidylinositol (GPI) biosynthesis pathway can result in a group of congenital disorders of glycosylation known as the inherited GPI deficiencies (IGDs). To date, defects in 22 of the 29 genes in the GPI biosynthesis pathway have been identified in IGDs. The early phase of the biosynthetic pathway assembles the GPI anchor (Synthesis stage) and the late phase transfers the GPI anchor to a nascent peptide in the endoplasmic reticulum (ER) (Transamidase stage), stabilizes the anchor in the ER membrane using fatty acid remodeling and then traffics the GPI-anchored protein to the cell surface (Remodeling stage). Results We addressed the hypothesis that disease-associated variants in either the Synthesis stage or Transamidase+Remodeling-stage GPI pathway genes have distinct phenotypic spectra. We reviewed clinical data from 58 publications describing 152 individual patients and encoded the phenotypic information using the Human Phenotype Ontology (HPO). We showed statistically significant differences between the Synthesis and Transamidase+Remodeling Groups in the frequencies of phenotypes in the musculoskeletal system, cleft palate, nose phenotypes, and cognitive disability. Finally, we hypothesized that phenotypic defects in the IGDs are likely to be at least partially related to defective GPI anchoring of their target proteins. Twenty-two of one hundred forty-two proteins that receive a GPI anchor are associated with one or more Mendelian diseases and 12 show some phenotypic overlap with the IGDs, represented by 34 HPO terms. Interestingly, GPC3 and GPC6, members of the glypican family of heparan sulfate proteoglycans bound to the plasma membrane through a covalent GPI linkage, are associated with 25 of these phenotypic abnormalities. Conclusions IGDs associated with Synthesis and Transamidase+Remodeling stages of the GPI biosynthesis pathway have significantly different phenotypic spectra. GPC2 and GPC6 genes may represent a GPI target of general disruption to the GPI biosynthesis pathway that contributes to the phenotypes of some IGDs.

Abstract Background Reducing meat consumption may improve human health, curb environmental damage and greenhouse gas emissions, and limit the large-scale suffering of animals raised in factory farms. Previous work has begun to develop interventions to reduce individual meat consumption, often by appealing directly to individual health motivations. However, research on nutritional behavior change suggests that interventions additionally linking behavior to ethical values, identity formation, and existing social movements may be particularly effective and longer-lasting. Regarding meat consumption, preliminary evidence and psychological theory suggest that appeals related to animal welfare may have considerable potential to effectively leverage these elements of human psychology. We aim to conduct a systematic review and quantitative meta-analysis evaluating the effectiveness of animal welfare-related appeals on actual or intended meat consumption or purchasing. Our investigation will critically synthesize the current state of knowledge regarding psychological mechanisms of intervening on individual meat consumption and empirically identify the psychological characteristics underlying the most effective animal welfare-based interventions. Methods We will systematically search eight academic databases and extensively search unpublished grey literature. We will include studies that assess interventions intended to reduce meat consumption or purchase through the mention or portrayal of animal welfare, that measure outcomes related to meat consumption or purchase, and that have a control condition. Eligible studies may recruit from any human population, be written in any language, and be published or released any time. We will meta-analyze the studies, reporting the pooled point estimate and additional metrics that describe the distribution of potentially heterogeneous effects. We will assess studies’ risk of bias and conduct sensitivity analyses for publication bias. We describe possible follow-up analyses to investigate hypothesized moderators of intervention effectiveness. Discussion The findings of the proposed systematic review and meta-analysis, including any identified methodological limitations of the existing literature, could inform the design of successful evidence-based interventions with broad potential to improve human, animal, and environmental well-being. Systematic review registration The protocol was preregistered via the Open Science Framework (https://osf.io/d3y56/registrations).

Between January and October of 2020, the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has infected more than 34 million persons in a worldwide pandemic leading to over one million deaths worldwide (data from the Johns Hopkins University). Since the virus begun to spread, emergency departments were busy with COVID-19 patients for whom a quick decision regarding in- or outpatient care was required. The virus can cause characteristic abnormalities in chest radiographs (CXR), but, due to the low sensitivity of CXR, additional variables and criteria are needed to accurately predict risk. Here, we describe a computerized system primarily aimed at extracting the most relevant radiological, clinical, and laboratory variables for improving patient risk prediction, and secondarily at presenting an explainable machine learning system, which may provide simple decision criteria to be used by clinicians as a support for assessing patient risk. To achieve robust and reliable variable selection, Boruta and Random Forest (RF) are combined in a 10-fold cross-validation scheme to produce a variable importance estimate not biased by the presence of surrogates. The most important variables are then selected to train a RF classifier, whose rules may be extracted, simplified, and pruned to finally build an associative tree, particularly appealing for its simplicity. Results show that the radiological score automatically computed through a neural network is highly correlated with the score computed by radiologists, and that laboratory variables, together with the number of comorbidities, aid risk prediction. The prediction performance of our approach was compared to that that of generalized linear models and shown to be effective and robust. The proposed machine learning-based computational system can be easily deployed and used in emergency departments for rapid and accurate risk prediction in COVID-19 patients.

Summary:. Upper lip reconstruction represents a unique challenge for the reconstructive plastic surgeon. Given its prominent aesthetic role in addition to its functional role in facial expression, speech, and oral intake, preservation of this region’s natural form and function is paramount. In this report, we present a novel technique for the reconstruction of a complex central upper lip defect, restoring the natural aesthetic of this essential structure. We describe the case of a 51-year-old woman who presented with recurrence of a previously resected basal cell carcinoma center on the upper lip at the level of the white roll and philtral depression. Following surgical resection via Mohs micrographic surgery, a 1.8 × 1.6 cm partial-thickness defect centered around the Cupid bow involving both cutaneous and vermillion tissues remained. Reconstruction was achieved through a novel quadruple rhomboid flap primarily based on the preservation of the aesthetic subunits of the upper lip. A functional and aesthetic reconstruction was achieved through local tissue rearrangement, restoring the appearance of the white roll and red line. Native perfusion and innervation were preserved during the reconstruction of the Cupid bow, recreating this region’s natural appearance. The design of the flap resembles a jumping frog, which is the etiology of the “Frogger flap” moniker. The Frogger flap recreates the natural aesthetic of the central upper lip through the geometric transposition of tissue commensurate with native anatomy. Through the application of aesthetic subunit principles, it reliably reconstructs central upper lip defects while preserving function and providing an aesthetically pleasing outcome.

Pancreatic ductal adenocarcinoma (PDAC) remains one of the deadliest cancers due to low therapeutic response rates and poor prognoses. Majority of patients present with symptoms post metastatic spread, which contributes to its overall lethality as the 4th leading cause of cancer-related deaths. Therapeutic approaches thus far target only one or two of the cancer specific hallmarks, such as high proliferation rate, apoptotic evasion, or immune evasion. Recent genomic discoveries reveal that genetic heterogeneity, early micrometastases, and an immunosuppressive tumor microenvironment contribute to the inefficacy of current standard treatments and specific molecular-targeted therapies. To effectively combat cancers like PDAC, we need an innovative approach that can simultaneously impact the multiple hallmarks driving cancer progression. Here, we present the mechanical properties generated by the cell’s cortical cytoskeleton, with a spotlight on PDAC, as an ideal therapeutic target that can concurrently attack multiple systems driving cancer. We start with an introduction to cancer cell mechanics and PDAC followed by a compilation of studies connecting the cortical cytoskeleton and mechanical properties to proliferation, metastasis, immune cell interactions, cancer cell stemness, and/or metabolism. We further elaborate on the implications of these findings in disease progression, therapeutic resistance, and clinical relapse. Manipulation of the cancer cell’s mechanical system has already been shown to prevent metastasis in preclinical models, but it has greater potential for target exploration since it is a foundational property of the cell that regulates various oncogenic behaviors.

Disease heritability and genetic correlations between traits depend on genetics, the environment and their interaction. Here, Jia et al. compute disease prevalence curves and disease embeddings from electronic health records and impute heritability for hundreds of diseases and genetic correlations for thousands of disease pairs.

ABSTRACT: Background: Numerous publications describe the clinical manifestations of post-acute sequelae of SARS-CoV-2 (PASC or “long COVID”), but they are difficult to integrate because of heterogeneous methods and the lack of a standard for denoting the many phenotypic manifestations. Patient-led studies are of particular importance for understanding the natural history of COVID-19, but integration is hampered because they often use different terms to describe the same symptom or condition. This significant disparity in patient versus clinical characterization motivated the proposed ontological approach to specifying manifestations, which will improve capture and integration of future long COVID studies. Methods: The Human Phenotype Ontology (HPO) is a widely used standard for exchange and analysis of phenotypic abnormalities in human disease but has not yet been applied to the analysis of COVID-19. Funding: We identified 303 articles published before April 29, 2021, curated 59 relevant manuscripts that described clinical manifestations in 81 cohorts three weeks or more following acute COVID-19, and mapped 287 unique clinical findings to HPO terms. We present layperson synonyms and definitions that can be used to link patient self-report questionnaires to standard medical terminology. Long COVID clinical manifestations are not assessed consistently across studies, and most manifestations have been reported with a wide range of synonyms by different authors. Across at least 10 cohorts, authors reported 31 unique clinical features corresponding to HPO terms; the most commonly reported feature was Fatigue (median 45.1%) and the least commonly reported was Nausea (median 3.9%), but the reported percentages varied widely between studies. Interpretation: Translating long COVID manifestations into computable HPO terms will improve analysis, data capture, and classification of long COVID patients. If researchers, clinicians, and patients share a common language, then studies can be compared/pooled more effectively. Furthermore, mapping lay terminology to HPO will help patients assist clinicians and researchers in creating phenotypic characterizations that are computationally accessible, thereby improving the stratification, diagnosis, and treatment of long COVID. Funding: U24TR002306; UL1TR001439; P30AG024832; GBMF4552; R01HG010067; UL1TR002535; K23HL128909; UL1TR002389; K99GM145411.

Summary: Maximizing the personal, public, research, and clinical value of genomic information will require the reliable exchange of genetic variation data. We report here the Variation Representation Specification (VRS, pronounced “verse”), an extensible framework for the computable representation of variation that complements contemporary human-readable and flat file standards for genomic variation representation. VRS provides semantically precise representations of variation and leverages this design to enable federated identification of biomolecular variation with globally consistent and unique computed identifiers. The VRS framework includes a terminology and information model, machine-readable schema, data sharing conventions, and a reference implementation, each of which is intended to be broadly useful and freely available for community use. VRS was developed by a partnership among national information resource providers, public initiatives, and diagnostic testing laboratories under the auspices of the Global Alliance for Genomics and Health (GA4GH).

Summary: The Global Alliance for Genomics and Health (GA4GH) aims to accelerate biomedical advances by enabling the responsible sharing of clinical and genomic data through both harmonized data aggregation and federated approaches. The decreasing cost of genomic sequencing (along with other genome-wide molecular assays) and increasing evidence of its clinical utility will soon drive the generation of sequence data from tens of millions of humans, with increasing levels of diversity. In this perspective, we present the GA4GH strategies for addressing the major challenges of this data revolution. We describe the GA4GH organization, which is fueled by the development efforts of eight Work Streams and informed by the needs of 24 Driver Projects and other key stakeholders. We present the GA4GH suite of secure, interoperable technical standards and policy frameworks and review the current status of standards, their relevance to key domains of research and clinical care, and future plans of GA4GH. Broad international participation in building, adopting, and deploying GA4GH standards and frameworks will catalyze an unprecedented effort in data sharing that will be critical to advancing genomic medicine and ensuring that all populations can access its benefits.

The COVID-19 pandemic changed the way people acquired food, including increased use of meal-kit delivery services. Investigators analyzed data from a national survey of US adults collected between July 2020 and September 2020, to describe new users of meal-kit services during the pandemic and explore associations between new use of meal-kits and dietary behaviors. Bivariate and multivariate regression analyses were conducted to identify differences in demographic characteristics and reported dietary behaviors between new and never meal-kit users. Nearly all new meal-kit users were under the age of 55 years (92.5%), lived in urban areas (90.1%), and reported having children in their households (82%). A higher proportion of new users were current SNAP participants (32.8%) compared to never users (17.1%). Compared to never users, new users of meal-kit services reported eating more fruits and vegetables (PR: 1.95, 95% CI: 1.42, 2.68), and more red and processed meats (PR: 2.39, 95% CI: 1.49–3.85) since the pandemic began. Results suggest that meal-kit services may have been a useful resource for certain populations during the early months of COVID-19 and are potentially associated with increased consumption of certain foods. Further research examining the continued use and the influence of meal-kit services on diet is needed.

This article provides descriptive insights of the experiences of family caregivers of persons living with dementia during the COVID-19 pandemic. Data were generated as part of a qualitative cross-national project to explore the costs and consequences of providing unpaid dementia care. Participants in Jamaica, who were recruited using community gatekeepers, information booths at health fairs, conferences, and other outreach events, were contacted by telephone to discuss their experiences of the pandemic. When face-to-face in-depth interview data collection was suspended due to the pandemic, ethical approval was received to contact all research participants who were informal unpaid family caregivers, both those whose care recipients had died and those who were active caregivers ( N = 19). Participants in this study were the 10 active family caregivers ( n F = 8; aged 45+; 60% from high socio-economic status). Their updates and reflections during these calls were documented in fieldnotes and analyzed for key themes. Data showed that the pandemic has illustrated the direct costs, both financial and otherwise, that informal dementia carers bear in Jamaica. It also intensified pre-existing challenges faced by family carers. We provide recommendations for sustainable support for family carers.

Background:. Prosthetic vascular graft infection is a serious complication associated with significant morbidity and mortality often requiring graft excision and numerous additional operations. Pedicled flaps are often used for the coverage of exposed deep tissue or hardware for graft salvage. In the absence of pedicled options, the properties of omentum make it an excellent choice for free flap tissue coverage, particularly in cases involving implanted prostheses. Methods:. A 63-year-old woman developed a mycotic right subclavian arterial aneurysm requiring ligation and extra-anatomic bypass grafting to restore right-sided intracranial and right upper extremity arterial perfusion. Subsequent wound breakdown and poor healing left the grafts exposed, resulting in contamination. Given the profound risks associated with graft excision in this patient, salvage was attempted with IV antibiotics, serial wound/graft washouts, and graft coverage with an omental free flap. Results:. The patient tolerated the procedure well. The remainder of her hospital course was uneventful, and she was discharged home in good clinical condition. She will remain on long-term suppressive antibiotics per Infectious Disease recommendations. Conclusions:. Contemporary literature reporting novel and effective applications of omental free flap coverage is rare. This report demonstrates that omental free flap coverage is safe and can provide healthy tissue to protect implanted grafts and even aid in the salvage of infected extra-anatomic bypass grafts.

Abstract Background Natural killer (NK) cells are important anti-tumor cells of our innate immune system. Their anti-cancer activity is mediated through interaction of a wide array of activating and inhibitory receptors with their ligands on tumor cells. After activation, NK cells also secrete a variety of pro-inflammatory molecules that contribute to the final immune response by modulating other innate and adaptive immune cells. In this regard, external proteins from NK cell secretome and the mechanisms by which they mediate these responses are poorly defined. Methods TRANS-stable-isotope labeling of amino acids in cell culture (TRANS-SILAC) combined with proteomic was undertaken to identify early materials transferred between cord blood-derived NK cells (CB-NK) and multiple myeloma (MM) cells. Further in vitro and in vivo studies with knock-down of histones and CD138, overexpression of histones and addition of exogenous histones were undertaken to confirm TRANS-SILAC results and to determine functional roles of this material transferred. Results We describe a novel mechanism by which histones are actively released by NK cells early after contact with MM cells. We show that extracellular histones bind to the heparan sulfate proteoglycan CD138 on the surface of MM cells to promote the creation of immune-tumor cell clusters bringing immune and MM cells into close proximity, and thus facilitating not only NK but also T lymphocyte anti-MM activity. Conclusion This study demonstrates a novel immunoregulatory role of NK cells against MM cells mediated by histones, and an additional role of NK cells modulating T lymphocytes activity that will open up new avenues to design future immunotherapy clinical strategies.

Abstract Background The recruitment of participants into community-based randomized controlled trials studying childhood obesity is often challenging, especially from low-income racial/ethnical minorities and when long-term participant commitments are required. This paper describes strategies used to recruit and enroll predominately low-income racial/ethnic minority parents and children into the Childhood Obesity Prevention and Treatment Research (COPTR) consortium. Methods The COPTR consortium has run four independent 3-year, multi-level (individual, family, school, clinic, and community) community-based randomized controlled trials. Two were prevention trials in preschool children and the other two were treatment trials in pre-adolescents and adolescent youth. All trials reported monthly participant recruitment numbers using a standardized method over the projected 18–24 months of recruitment. After randomization of participants was completed, recruitment staff and investigators from each trial retrospectively completed a survey of recruitment strategies and their perceived top three recruitment strategies and barriers. Results Recruitment was completed in 15–21 months across trials, enrolling a total of 1745 parent-child dyads- out of 6314 screened. The number of children screened per randomized child was 4.6 and 3.5 in the two prevention trials, and 3.1 and 2.5 in the two treatment trials. Recruitment strategies reported included: (1) careful planning, (2) working with trusting community partners, (3) hiring recruitment staff who were culturally sensitive, personality appropriate, and willing to work flexible hours, (4) contacting potential participants actively and repeatedly, (5) recruiting at times and locations convenient for participants, (6) providing incentives to participants to complete baseline measures, (7) using a tracking database, (8) evaluating whether participants understand the activities and expectations of the study, and (9) assessing participants’ motivation for participating. Working with community partners, hiring culturally sensitive staff, and contacting potential participants repeatedly were cited by two trials among their top three strategies. The requirement of a 3-year commitment to the trial was cited by two trials to be among the top three recruitment barriers. Conclusions Comprehensive strategies that include community partnership support, culturally sensitive recruitment staff, and repeated contacts with potential participants can result in successful recruitment of low-income racial/ethnic minority families into obesity prevention and treatment trials. Trial registration NET-Works trial: ClinicalTrials.gov, NCT01606891. Registered on 28 May 2012. GROW trial: ClinicalTrials.gov, NCT01316653. Registered on 16 March 2011. GOALS trial: ClinicalTrials.gov, NCT01642836. Registered on 17 July 2012. IMPACT trial: ClinicalTrials.gov, NCT01514279. Registered on 23 January 2012.

Abstract Background Target enrichment combined with chromosome conformation capturing methodologies such as capture Hi-C (CHC) can be used to investigate spatial layouts of genomic regions with high resolution and at scalable costs. A common application of CHC is the investigation of regulatory elements that are in contact with promoters, but CHC can be used for a range of other applications. Therefore, probe design for CHC needs to be adapted to experimental needs, but no flexible tool is currently available for this purpose. Results We present a Java desktop application called GOPHER (Generator Of Probes for capture Hi-C Experiments at high Resolution) that implements three strategies for CHC probe design. GOPHER’s simple approach is similar to the probe design of previous approaches that employ CHC to investigate all promoters, with one probe being placed at each margin of a single digest that overlaps the transcription start site (TSS) of each promoter. GOPHER’s simple-patched approach extends this methodology with a heuristic that improves coverage of viewpoints in which the TSS is located near to one of the boundaries of the digest. GOPHER’s extended approach is intended mainly for focused investigations of smaller gene sets. GOPHER can also be used to design probes for regions other than TSS such as GWAS hits or large blocks of genomic sequence. GOPHER additionally provides a number of features that allow users to visualize and edit viewpoints, and outputs a range of files useful for documentation, ordering probes, and downstream analysis. Conclusion GOPHER is an easy-to-use and robust desktop application for CHC probe design. Source code and a precompiled executable can be downloaded from the GOPHER GitHub page at https://github.com/TheJacksonLaboratory/Gopher.