MiR-124 synergism with ELAVL3 enhances target gene expression to promote neuronal maturity.

Neuron-enriched microRNAs (miRNAs), miR-9/9* and miR-124 (miR-9/9*-124), direct cell fate switching of human fibroblasts to neurons when ectopically expressed by repressing antineurogenic genes. How these miRNAs function after the repression of fibroblast genes for neuronal fate remains unclear. Here, we identified targets of miR-9/9*-124 as reprogramming cells activate the neuronal program and reveal the role of miR-124 that directly promotes the expression of its target genes associated with neuronal development and function. The mode of miR-124 as a positive regulator is determined by the binding of both AGO and a neuron-enriched RNA-binding protein, ELAVL3, to target transcripts. Although existing literature indicates that miRNA-ELAVL family protein interaction can result in either target gene up-regulation or down-regulation in a context-dependent manner, we specifically identified neuronal ELAVL3 as the driver for miR-124 target gene up-regulation in neurons. In primary human neurons, repressing miR-124 and ELAVL3 led to the down-regulation of genes involved in neuronal function and process outgrowth and cellular phenotypes of reduced inward currents and neurite outgrowth. Our results highlight the synergistic role between miR-124 and RNA-binding proteins to promote target gene regulation and neuronal function.

3D Covalent Organic Framework as a Metastable Intermediate in the Formation of a Double-Stranded Helical Covalent Polymer.

The design and development of intricate artificial architectures have been pursued for decades. Helical covalent polymer (HCP) was recently reported as an unexpected topology that consists of chiral 1D polymers assembled through weak hydrogen bonds from achiral building blocks. However, many questions remained about the formation, driving force, and the single-handedness observed in each crystal. In this work, we reveal a metastable, racemic, fully covalently cross-linked, 3D covalent organic framework (COF) as an intermediate in the early stage of polymerization, which slowly converts into single-handed HCP double helices through partial fragmentation and self-sorting with the aid of a series of hydrogen bonding. Our work provides an intriguing example where weak noncovalent bonds serve as the determining factor of the overall product structure and facilitate the formation of a sophisticated polymeric architecture.

A Sanctioned Encampment as a Strategy for Increasing Homeless Veterans' Access to Housing and Healthcare During the COVID-19 Pandemic.

BACKGROUND: The COVID-19 pandemic intersected with a housing crisis for unsheltered Veterans experiencing homelessness (VEHs); congregate settings became high risk for viral spread. The VA Greater Los Angeles responded by creating the Care, Treatment, and Rehabilitation Service (CTRS), an outdoor, low-barrier-to-entry transitional housing program on VA grounds. This novel emergency initiative offered a protected outdoor environment ("sanctioned encampment") where VEHs lived in tents and had access to three meals a day, hygiene resources, and health and social services. OBJECTIVE: To identify contextual factors that supported and impeded CTRS participants' access to healthcare and housing services. DESIGN: Multi-method, ethnographic data collection. PARTICIPANTS: VEHs residing at CTRS, CTRS staff. APPROACH: Over 150 hours of participant observation were conducted at CTRS and at eight town hall meetings; semi-structured interviews were conducted with 21 VEHs and 11 staff. Rapid turn-around qualitative analysis was used to synthesize data, engaging stakeholders in iterative participant validation. Content analysis techniques were used to identify key factors that impacted access to housing and health services among VEHs residing in CTRS. KEY RESULTS: Staff varied in their interpretation of CTRS' mission. Some conceptualized access to health services as a central tenet, while others viewed CTRS as an emergency shelter only. Regardless, staff burnout was prevalent, which lead to low morale, high turnover, and worsened access to and quality of care. VEHs endorsed trusting, long-term relationships with CTRS staff as paramount for facilitating access to services. Though CTRS addressed basic priorities (food, shelter, etc.) that traditionally compete with access to healthcare, some VEHs needed on-site healthcare services, at their tents, to access care. CONCLUSIONS: CTRS provided VEHs access to basic needs and health and housing services. To improve access to healthcare services within encampments, our data suggest the value of longitudinal trusting relationships, adequate staff support, and on-site health services.

Software is Policy: Electronic Health Record Governance and the Implications of Clinical Standardization.

BACKGROUND: Electronic health record (EHR) implementations, whether replacing paper or electronic systems, are major social and organizational transformations. Yet studies of EHR-to-EHR transitions have largely neglected to elucidate accompanying social and organizational changes. One such underexplored change is the standardization of clinical practice in the context of EHR transitions. The Department of Veterans Affairs (VA) has begun a decade-long process of replacing the approximately 130 separate versions of its homegrown EHR with a single commercial EHR system. This provides an opportunity to explore the standardization of clinical practice amidst an EHR transition. OBJECTIVE: To identify, in the context of a large-scale EHR transition, (1) the scope and content of clinical standardization and (2) the anticipated implications of such standardization. DESIGN: Qualitative study. PARTICIPANTS: Twenty-nine members of VA councils established for the EHR transition. APPROACH: We conducted semi-structured interviews, which were professionally transcribed, and analyzed first using rapid analysis methods, followed by coding and content analysis. KEY RESULTS: Clinical standardization across facilities was a central goal of the EHR transition, encompassing computerized recommendations, order sets, professional roles/permissions, and clinical documentation. The anticipated implications of this standardization include (i) potential efficiency gains, with less duplicated effort across facilities; (ii) expanded bureaucracy; and (iii) increased uniformity, reducing both wanted and unwanted variation in care. CONCLUSIONS: EHR systems shape a wide range of clinical processes, particularly in a large organization like VA with a long history of EHR use. This makes standardization of EHR content a powerful mechanism for standardizing clinical practice itself, which can bring dramatic collateral consequences. Organizations undergoing EHR transitions need to recognize the important role that clinical standardization plays by treating EHR transitions as major organizational transformations in the governance of clinical practice.

Ethical Responsibilities for Companies That Process Personal Data.

It has become increasingly difficult for individuals to exercise meaningful control over the personal data they disclose to companies or to understand and track the ways in which that data is exchanged and used. These developments have led to an emerging consensus that existing privacy and data protection laws offer individuals insufficient protections against harms stemming from current data practices. However, an effective and ethically justified way forward remains elusive. To inform policy in this area, we propose the Ethical Data Practices framework. The framework outlines six principles relevant to the collection and use of personal data-minimizing harm, fairly distributing benefits and burdens, respecting autonomy, transparency, accountability, and inclusion-and translates these principles into action-guiding practical imperatives for companies that process personal data. In addition to informing policy, the practical imperatives can be voluntarily adopted by companies to promote ethical data practices.

Cadherin 11 Promotes Immunosuppression and Extracellular Matrix Deposition to Support Growth of Pancreatic Tumors and Resistance to Gemcitabine in Mice.

BACKGROUND & AIMS: Pancreatic ductal adenocarcinomas (PDACs) are characterized by fibrosis and an abundance of cancer-associated fibroblasts (CAFs). We investigated strategies to disrupt interactions among CAFs, the immune system, and cancer cells, focusing on adhesion molecule CDH11, which has been associated with other fibrotic disorders and is expressed by activated fibroblasts. METHODS: We compared levels of CDH11 messenger RNA in human pancreatitis and pancreatic cancer tissues and cells with normal pancreas, and measured levels of CDH11 protein in human and mouse pancreatic lesions and normal tissues. We crossed p48-Cre;LSL-KrasG12D/+;LSL-Trp53R172H/+ (KPC) mice with CDH11-knockout mice and measured survival times of offspring. Pancreata were collected and analyzed by histology, immunohistochemistry, and (single-cell) RNA sequencing; RNA and proteins were identified by imaging mass cytometry. Some mice were given injections of PD1 antibody or gemcitabine and survival was monitored. Pancreatic cancer cells from KPC mice were subcutaneously injected into Cdh11+/+ and Cdh11-/- mice and tumor growth was monitored. Pancreatic cancer cells (mT3) from KPC mice (C57BL/6), were subcutaneously injected into Cdh11+/+ (C57BL/6J) mice and mice were given injections of antibody against CDH11, gemcitabine, or small molecule inhibitor of CDH11 (SD133) and tumor growth was monitored. RESULTS: Levels of CDH11 messenger RNA and protein were significantly higher in CAFs than in pancreatic cancer epithelial cells, human or mouse pancreatic cancer cell lines, or immune cells. KPC/Cdh11+/- and KPC/Cdh11-/- mice survived significantly longer than KPC/Cdh11+/+ mice. Markers of stromal activation entirely surrounded pancreatic intraepithelial neoplasias in KPC/Cdh11+/+ mice and incompletely in KPC/Cdh11+/- and KPC/Cdh11-/- mice, whose lesions also contained fewer FOXP3+ cells in the tumor center. Compared with pancreatic tumors in KPC/Cdh11+/+ mice, tumors of KPC/Cdh11+/- mice had increased markers of antigen processing and presentation; more lymphocytes and associated cytokines; decreased extracellular matrix components; and reductions in markers and cytokines associated with immunosuppression. Administration of the PD1 antibody did not prolong survival of KPC mice with 0, 1, or 2 alleles of Cdh11. Gemcitabine extended survival of KPC/Cdh11+/- and KPC/Cdh11-/- mice only or reduced subcutaneous tumor growth in mT3 engrafted Cdh11+/+ mice when given in combination with the CDH11 antibody. A small molecule inhibitor of CDH11 reduced growth of pre-established mT3 subcutaneous tumors only if T and B cells were present in mice. CONCLUSIONS: Knockout or inhibition of CDH11, which is expressed by CAFs in the pancreatic tumor stroma, reduces growth of pancreatic tumors, increases their response to gemcitabine, and significantly extends survival of mice. CDH11 promotes immunosuppression and extracellular matrix deposition, and might be developed as a therapeutic target for pancreatic cancer.

Predicting Genetic Variation Severity Using Machine Learning to Interpret Molecular Simulations.

Distinct missense mutations in a specific gene have been associated with different diseases as well as differing severity of a disease. Current computational methods predict the potential pathogenicity of a missense variant but fail to differentiate between separate disease or severity phenotypes. We have developed a method to overcome this limitation by applying machine learning to features extracted from molecular dynamics simulations, creating a way to predict the effect of novel genetic variants in causing a disease, drug resistance, or another specific trait. As an example, we have applied this novel approach to variants in calmodulin associated with two distinct arrhythmias as well as two different neurodegenerative diseases caused by variants in amyloid-ß peptide. The new method successfully predicts the specific disease caused by a gene variant and ranks its severity with more accuracy than existing methods. We call this method molecular dynamics phenotype prediction model.

Intron and gene size expansion during nervous system evolution.

BACKGROUND: The evolutionary radiation of animals was accompanied by extensive expansion of gene and genome sizes, increased isoform diversity, and complexity of regulation. RESULTS: Here we show that the longest genes are enriched for expression in neuronal tissues of diverse vertebrates and of invertebrates. Additionally, we show that neuronal gene size expansion occurred predominantly through net gains in intron size, with a positional bias toward the 5' end of each gene. CONCLUSIONS: We find that intron and gene size expansion is a feature of many genes whose expression is enriched in nervous systems. We speculate that unique attributes of neurons may subject neuronal genes to evolutionary forces favoring net size expansion. This process could be associated with tissue-specific constraints on gene function and/or the evolution of increasingly complex gene regulation in nervous systems.

Public involvement in the governance of population-level biomedical research: unresolved questions and future directions.

Population-level biomedical research offers new opportunities to improve population health, but also raises new challenges to traditional systems of research governance and ethical oversight. Partly in response to these challenges, various models of public involvement in research are being introduced. Yet, the ways in which public involvement should meet governance challenges are not well understood. We conducted a qualitative study with 36 experts and stakeholders using the World Café method to identify key governance challenges and explore how public involvement can meet these challenges. This brief report discusses four cross-cutting themes from the study: the need to move beyond individual consent; issues in benefit and data sharing; the challenge of delineating and understanding publics; and the goal of clarifying justifications for public involvement. The report aims to provide a starting point for making sense of the relationship between public involvement and the governance of population-level biomedical research, showing connections, potential solutions and issues arising at their intersection. We suggest that, in population-level biomedical research, there is a pressing need for a shift away from conventional governance frameworks focused on the individual and towards a focus on collectives, as well as to foreground ethical issues around social justice and develop ways to address cultural diversity, value pluralism and competing stakeholder interests. There are many unresolved questions around how this shift could be realised, but these unresolved questions should form the basis for developing justificatory accounts and frameworks for suitable collective models of public involvement in population-level biomedical research governance.

Ethical Advocacy Across the Autism Spectrum: Beyond Partial Representation.

Recent debates within the autism advocacy community have raised difficult questions about who can credibly act as a representative of a particular population and what responsibilities that role entails. We attempt to answer these questions by defending a set of evaluative criteria that can be used to assess the legitimacy of advocacy organizations and other nonelectoral representatives. With these criteria in hand, we identify a form of misrepresentation common but not unique to autism advocacy, which we refer to as partial representation. Partial representation occurs when an actor claims to represent a particular group of people but appropriately engages with only a subset of that group. After highlighting symbolic and substantive harms associated with partial representation, we propose several strategies for overcoming it.

SNP2SIM: a modular workflow for standardizing molecular simulation and functional analysis of protein variants.

BACKGROUND: Molecular simulations are used to provide insight into protein structure and dynamics, and have the potential to provide important context when predicting the impact of sequence variation on protein function. In addition to understanding molecular mechanisms and interactions on the atomic scale, translational applications of those approaches include drug screening, development of novel molecular therapies, and targeted treatment planning. Supporting the continued development of these applications, we have developed the SNP2SIM workflow that generates reproducible molecular dynamics and molecular docking simulations for downstream functional variant analysis. The Python workflow utilizes molecular dynamics software (NAMD (Phillips et al., J Comput Chem 26(16):1781-802, 2005), VMD (Humphrey et al., J Mol Graph 14(1):33-8, 27-8, 1996)) to generate variant specific scaffolds for simulated small molecule docking (AutoDock Vina (Trott and Olson, J Comput Chem 31(2):455-61, 2010)). RESULTS: SNP2SIM is composed of three independent modules that can be used sequentially to generate the variant scaffolds of missense protein variants from the wildtype protein structure. The workflow first generates the mutant structure and configuration files required to execute molecular dynamics simulations of solvated protein variant structures. The resulting trajectories are clustered based on the structural diversity of residues involved in ligand binding to produce one or more variant scaffolds of the protein structure. Finally, these unique structural conformations are bound to small molecule ligand libraries to predict variant induced changes to drug binding relative to the wildtype protein structure. CONCLUSIONS: SNP2SIM provides a platform to apply molecular simulation based functional analysis of sequence variation in the protein targets of small molecule therapies. In addition to simplifying the simulation of variant specific drug interactions, the workflow enables large scale computational mutagenesis by controlling the parameterization of molecular simulations across multiple users or distributed computing infrastructures. This enables the parallelization of the computationally intensive molecular simulations to be aggregated for downstream functional analysis, and facilitates comparing various simulation options, such as the specific residues used to define structural variant clusters. The Python scripts that implement the SNP2SIM workflow are available (SNP2SIM Repository. https://github.com/mccoymd/SNP2SIM , Accessed 2019 February ), and individual SNP2SIM modules are available as apps on the Seven Bridges Cancer Genomics Cloud (Lau et al., Cancer Res 77(21):e3-e6, 2017; Cancer Genomics Cloud [ www.cancergenomicscloud.org ; Accessed 2018 November]).

LONGO: an R package for interactive gene length dependent analysis for neuronal identity.

Motivation: Reprogramming somatic cells into neurons holds great promise to model neuronal development and disease. The efficiency and success rate of neuronal reprogramming, however, may vary between different conversion platforms and cell types, thereby necessitating an unbiased, systematic approach to estimate neuronal identity of converted cells. Recent studies have demonstrated that long genes (>100 kb from transcription start to end) are highly enriched in neurons, which provides an opportunity to identify neurons based on the expression of these long genes. Results: We have developed a versatile R package, LONGO, to analyze gene expression based on gene length. We propose a systematic analysis of long gene expression (LGE) with a metric termed the long gene quotient (LQ) that quantifies LGE in RNA-seq or microarray data to validate neuronal identity at the single-cell and population levels. This unique feature of neurons provides an opportunity to utilize measurements of LGE in transcriptome data to quickly and easily distinguish neurons from non-neuronal cells. By combining this conceptual advancement and statistical tool in a user-friendly and interactive software package, we intend to encourage and simplify further investigation into LGE, particularly as it applies to validating and improving neuronal differentiation and reprogramming methodologies. Availability and implementation: LONGO is freely available for download at https://github.com/biohpc/longo. Supplementary information: Supplementary data are available at Bioinformatics online.

Patient and public involvement: Two sides of the same coin or different coins altogether?

Patient and public involvement (PPI) has gained widespread support in health research and health policy circles, but there is little consensus on the precise meaning or justifications of PPI. We argue that an important step towards clarifying the meaning and justification for PPI is to split apart the familiar acronym and draw a distinction between patient and public involvement. Specifically, we argue that patient involvement should refer to the practice of involving individuals in health research or policy on the basis of their experience with a particular condition, while public involvement should refer to the practice of involving individuals in health policy or research based on their status as members of a relevant population. Analyzing cases from the UK, Australia, and the USA, we show how our proposed distinction can deliver much needed clarity to conversations on PPI, while guiding the development and evaluation of future PPI-based policies.

Adapting crowdsourced clinical cancer curation in CIViC to the ClinGen minimum variant level data community-driven standards.

Harmonization of cancer variant representation, efficient communication, and free distribution of clinical variant-associated knowledge are central problems that arise with increased usage of clinical next-generation sequencing. The Clinical Genome Resource (ClinGen) Somatic Working Group (WG) developed a minimal variant level data (MVLD) representation of cancer variants, and has an ongoing collaboration with Clinical Interpretations of Variants in Cancer (CIViC), an open-source platform supporting crowdsourced and expert-moderated cancer variant curation. Harmonization between MVLD and CIViC variant formats was assessed by formal field-by-field analysis. Adjustments to the CIViC format were made to harmonize with MVLD and support ClinGen Somatic WG curation activities, including four new features in CIViC: (1) introduction of an assertions feature for clinical variant assessment following the Association of Molecular Pathologists (AMP) guidelines, (2) group-level curation tracking for organizations, enabling member transparency, and curation effort summaries, (3) introduction of ClinGen Allele Registry IDs to CIViC, and (4) mapping of CIViC assertions into ClinVar submission with automated submissions. A generalizable workflow utilizing MVLD and new CIViC features is outlined for use by ClinGen Somatic WG task teams for curation and submission to ClinVar, and provides a model for promoting harmonization of cancer variant representation and efficient distribution of this information.

Industry Support of Patient Advocacy Organizations: The Case for an Extension of the Sunshine Act Provisions of the Affordable Care Act.

Patient advocacy organizations (PAOs) have long been regarded as important representatives of patient and caregiver interests in health policy debates. Recently, however, PAOs have attracted increased scrutiny over their financial ties to drug and device companies. In the past year, researchers and policymakers have called for the creation of a "sunshine law" requiring mandatory public reporting of industry payments to PAOs. Others have suggested that increased transparency would do little to address, and may even exacerbate, underlying concerns about proindustry bias among industry-funded PAOs. To date, however, the benefits of a sunshine law have not been well articulated, nor have objections to the idea been carefully addressed. In particular, little attention has been paid to clarifying the merits of statutorily mandated disclosure relative to those of increased voluntary disclosure by PAOs. I examine arguments for and against a sunshine law and conclude that the balance of reasons supports the enactment of such a law.

National Standards for Public Involvement in Research: missing the forest for the trees.

Biomedical research funding bodies across Europe and North America increasingly encourage-and, in some cases, require-investigators to involve members of the public in funded research. Yet there remains a striking lack of clarity about what 'good' or 'successful' public involvement looks like. In an effort to provide guidance to investigators and research organisations, representatives of several key research funding bodies in the UK recently came together to develop the National Standards for Public Involvement in Research. The Standards have critical implications for the future of biomedical research in the UK and in other countries as researchers and funders abroad look to the Standards as a model for their own policy development. We assess the Standards and find that despite offering useful suggestions for dealing with practical challenges associated with public involvement, the Standards fail to address fundamental questions about when, why and with whom public involvement should be undertaken in the first place. We show that presented without this justificatory context, many of the recommendations in the Standards are, at best, fragments that require substantial elaboration by those looking to apply the Standards in their own work and, at worst, subject to potentially harmful misapplication by well-meaning investigators. As funding bodies increasingly push for public involvement in research, the key lesson of our analysis is that future recommendations about how public involvement should be conducted cannot be coherently formulated without a clear sense of the underlying goals and rationales for public involvement.