Supporting the Identification, Monitoring and Preservation of Government Data Resources: Findings from DataLumos Outreach Efforts

This report documents the findings of “Identification, Monitoring, and Preservation of Government Data Resources”, an 18-month project involving outreach to government data producers, users, and intermediaries. Through this project, the Inter-university Consortium for Political and Social Research (ICPSR) sought to identify stakeholders’ most-used government datasets that they perceive to be potentially less accessible in the future, among other goals. Interviews and less formal interactions with data advocates and intermediaries, government data producers, and a variety of data users provided insights into the use of government data and perceptions of these data’s future accessibility. The most important source of data to these stakeholders is the Census Bureau, and several of its products were identified as being critical to stakeholders’ work. Data from other major statistical agencies, non-statistical federal agencies, and state and local data sources were also cited. The federal government data most used by stakeholders—and specifically the data of greatest importance to AECF-funded work—are perceived as accessible for future use. All of the federal datasets that stakeholders perceived to be potentially at risk were assessed and added to the DataLumos archive. A noteworthy finding from these interactions is that data created or collected by KIDS COUNT grantees, National Neighborhood Indicators Partnership (NNIP) participants, and other data intermediaries may not have a long-term data archiving or sharing plan. The analysts at these organizations spend significant effort gathering, aggregating, and analyzing data for their products, but they generally have no mechanism to archive or share these data. Given the investment in this work and the potential value of these data to community organizations, researchers, and even local and regional government agencies, there is a real opportunity for data intermediaries to store and share these data in a secure manner for the long term. Recommendations based on the project’s findings can be grouped into two major categories: advocacy and data sharing. Data users, intermediaries, and funders should continue to advocate that the Census Bureau and other principal statistical agencies provide access to the data products needed to successfully complete their work. Advocacy is also needed at the state and local levels, with the goals of targeting the creation of transparency laws and sunshine clauses, budget line items for data sharing, and infrastructural investments like open data portals and data application programming interfaces (APIs). Beyond traditional advocacy work, sustained and increased collaboration between government data producers and data users, intermediaries, and advocates is needed. As for data sharing, we recommend that data creators and intermediaries like KIDS COUNT grantees and NNIP partners work with data repositories like ICPSR to make their data available to others now and in the future. The archiving of these data would require both the infrastructure of a secure data repository as well as specialized curation and technical assistance related to sharing these types of data. The creation of an archive for data intermediaries’ data would extend the value of intermediaries’ important work, creating new resources for community members, institutions, and researchers.Annie E. Casey Foundationhttps://deepblue.lib.umich.edu/bitstream/2027.42/148837/1/Supporting the Identification, Monitoring and Preservation of Government Data Resources.pdfDescription of Supporting the Identification, Monitoring and Preservation of Government Data Resources.pdf : Repor

CAFA-evaluator: A Python Tool for Benchmarking Ontological Classification Methods

We present CAFA-evaluator, a powerful Python program designed to evaluate the performance of prediction methods on targets with hierarchical concept dependencies. It generalizes multi-label evaluation to modern ontologies where the prediction targets are drawn from a directed acyclic graph and achieves high efficiency by leveraging matrix computation and topological sorting. The program requirements include a small number of standard Python libraries, making CAFA-evaluator easy to maintain. The code replicates the Critical Assessment of protein Function Annotation (CAFA) benchmarking, which evaluates predictions of the consistent subgraphs in Gene Ontology. Owing to its reliability and accuracy, the organizers have selected CAFA-evaluator as the official CAFA evaluation software.Comment: 5 page

Spin injection and spin accumulation in all-metal mesoscopic spin valves

We study the electrical injection and detection of spin accumulation in lateral ferromagnetic metal-nonmagnetic metal-ferromagnetic metal (F/N/F) spin valve devices with transparent interfaces. Different ferromagnetic metals, permalloy (Py), cobalt (Co) and nickel (Ni), are used as electrical spin injectors and detectors. For the nonmagnetic metal both aluminium (Al) and copper (Cu) are used. Our multi-terminal geometry allows us to experimentally separate the spin valve effect from other magneto resistance signals such as the anomalous magneto resistance (AMR) and Hall effects. We find that the AMR contribution of the ferromagnetic contacts can dominate the amplitude of the spin valve effect, making it impossible to observe the spin valve effect in a 'conventional' measurement geometry. In a 'non local' spin valve measurement we are able to completely isolate the spin valve signal and observe clear spin accumulation signals at T=4.2 K as well as at room temperature (RT). For aluminum we obtain spin relaxation lengths (lambda_{sf}) of 1.2 mu m and 600 nm at T=4.2 K and RT respectively, whereas for copper we obtain 1.0 mu m and 350 nm. The spin relaxation times tau_{sf} in Al and Cu are compared with theory and results obtained from giant magneto resistance (GMR), conduction electron spin resonance (CESR), anti-weak localization and superconducting tunneling experiments. The spin valve signals generated by the Py electrodes (alpha_F lambda_F=0.5 [1.2] nm at RT [T=4.2 K]) are larger than the Co electrodes (alpha_F lambda_F=0.3 [0.7] nm at RT [T=4.2 K]), whereas for Ni (alpha_F lambda_F<0.3 nm at RT and T=4.2 K) no spin signal is observed. These values are compared to the results obtained from GMR experiments.Comment: 16 pages, 12 figures, submitted to PR

DisProt

The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the 'dark' proteome

Differentially Expressed RNA from Public Microarray Data Identifies Serum Protein Biomarkers for Cross-Organ Transplant Rejection and Other Conditions

Serum proteins are routinely used to diagnose diseases, but are hard to find due to low sensitivity in screening the serum proteome. Public repositories of microarray data, such as the Gene Expression Omnibus (GEO), contain RNA expression profiles for more than 16,000 biological conditions, covering more than 30% of United States mortality. We hypothesized that genes coding for serum- and urine-detectable proteins, and showing differential expression of RNA in disease-damaged tissues would make ideal diagnostic protein biomarkers for those diseases. We showed that predicted protein biomarkers are significantly enriched for known diagnostic protein biomarkers in 22 diseases, with enrichment significantly higher in diseases for which at least three datasets are available. We then used this strategy to search for new biomarkers indicating acute rejection (AR) across different types of transplanted solid organs. We integrated three biopsy-based microarray studies of AR from pediatric renal, adult renal and adult cardiac transplantation and identified 45 genes upregulated in all three. From this set, we chose 10 proteins for serum ELISA assays in 39 renal transplant patients, and discovered three that were significantly higher in AR. Interestingly, all three proteins were also significantly higher during AR in the 63 cardiac transplant recipients studied. Our best marker, serum PECAM1, identified renal AR with 89% sensitivity and 75% specificity, and also showed increased expression in AR by immunohistochemistry in renal, hepatic and cardiac transplant biopsies. Our results demonstrate that integrating gene expression microarray measurements from disease samples and even publicly-available data sets can be a powerful, fast, and cost-effective strategy for the discovery of new diagnostic serum protein biomarkers

Limbic-thalamo-cortical projections and reward-related circuitry integrity affects eating behavior: A longitudinal DTI study in adolescents with restrictive eating disorders.

Few studies have used diffusion tensor imaging (DTI) to investigate the micro-structural alterations of WM in patients with restrictive eating disorders (rED), and longitudinal data are lacking. Twelve patients with rED were scanned at diagnosis and after one year of family-based treatment, and compared to twenty-four healthy controls (HCs) through DTI analysis. A tract-based spatial statistics procedure was used to investigate diffusivity parameters: fractional anisotropy (FA) and mean, radial and axial diffusivities (MD, RD and AD, respectively). Reduced FA and increased RD were found in patients at baseline in the corpus callosum, corona radiata and posterior thalamic radiation compared with controls. However, no differences were found between follow-up patients and controls, suggesting a partial normalization of the diffusivity parameters. In patients, trends for a negative correlation were found between the baseline FA of the right anterior corona radiata and the Eating Disorder Examination Questionnaire total score, while a positive trend was found between the baseline FA in the splenium of corpus callosum and the weight loss occurred between maximal documented weight and time of admission. A positive trend for correlation was also found between baseline FA in the right anterior corona radiata and the decrease in the Obsessive-Compulsive Inventory Revised total score over time. Our results suggest that the integrity of the limbic-thalamo-cortical projections and the reward-related circuitry are important for cognitive control processes and reward responsiveness in regulating eating behavior

DisProt: intrinsic protein disorder annotation in 2020

The Database of Protein Disorder (DisProt, URL: https://disprot.org) provides manually curated annotations of intrinsically disordered proteins from the literature. Here we report recent developments with DisProt (version 8), including the doubling of protein entries, a new disorder ontology, improvements of the annotation format and a completely new website. The website includes a redesigned graphical interface, a better search engine, a clearer API for programmatic access and a new annotation interface that integrates text mining technologies. The new entry format provides a greater flexibility, simplifies maintenance and allows the capture of more information from the literature. The new disorder ontology has been formalized and made interoperable by adopting the OWL format, as well as its structure and term definitions have been improved. The new annotation interface has made the curation process faster and more effective. We recently showed that new DisProt annotations can be effectively used to train and validate disorder predictors. We believe the growth of DisProt will accelerate, contributing to the improvement of function and disorder predictors and therefore to illuminate the ‘dark’ proteome

Early mobilisation in critically ill COVID-19 patients: a subanalysis of the ESICM-initiated UNITE-COVID observational study

Background Early mobilisation (EM) is an intervention that may improve the outcome of critically ill patients. There is limited data on EM in COVID-19 patients and its use during the first pandemic wave. Methods This is a pre-planned subanalysis of the ESICM UNITE-COVID, an international multicenter observational study involving critically ill COVID-19 patients in the ICU between February 15th and May 15th, 2020. We analysed variables associated with the initiation of EM (within 72 h of ICU admission) and explored the impact of EM on mortality, ICU and hospital length of stay, as well as discharge location. Statistical analyses were done using (generalised) linear mixed-effect models and ANOVAs. Results Mobilisation data from 4190 patients from 280 ICUs in 45 countries were analysed. 1114 (26.6%) of these patients received mobilisation within 72 h after ICU admission; 3076 (73.4%) did not. In our analysis of factors associated with EM, mechanical ventilation at admission (OR 0.29; 95% CI 0.25, 0.35; p = 0.001), higher age (OR 0.99; 95% CI 0.98, 1.00; p ≤ 0.001), pre-existing asthma (OR 0.84; 95% CI 0.73, 0.98; p = 0.028), and pre-existing kidney disease (OR 0.84; 95% CI 0.71, 0.99; p = 0.036) were negatively associated with the initiation of EM. EM was associated with a higher chance of being discharged home (OR 1.31; 95% CI 1.08, 1.58; p = 0.007) but was not associated with length of stay in ICU (adj. difference 0.91 days; 95% CI − 0.47, 1.37, p = 0.34) and hospital (adj. difference 1.4 days; 95% CI − 0.62, 2.35, p = 0.24) or mortality (OR 0.88; 95% CI 0.7, 1.09, p = 0.24) when adjusted for covariates. Conclusions Our findings demonstrate that a quarter of COVID-19 patients received EM. There was no association found between EM in COVID-19 patients' ICU and hospital length of stay or mortality. However, EM in COVID-19 patients was associated with increased odds of being discharged home rather than to a care facility. Trial registration ClinicalTrials.gov: NCT04836065 (retrospectively registered April 8th 2021)

Effect of angiotensin-converting enzyme inhibitor and angiotensin receptor blocker initiation on organ support-free days in patients hospitalized with COVID-19

IMPORTANCE Overactivation of the renin-angiotensin system (RAS) may contribute to poor clinical outcomes in patients with COVID-19. Objective To determine whether angiotensin-converting enzyme (ACE) inhibitor or angiotensin receptor blocker (ARB) initiation improves outcomes in patients hospitalized for COVID-19. DESIGN, SETTING, AND PARTICIPANTS In an ongoing, adaptive platform randomized clinical trial, 721 critically ill and 58 non–critically ill hospitalized adults were randomized to receive an RAS inhibitor or control between March 16, 2021, and February 25, 2022, at 69 sites in 7 countries (final follow-up on June 1, 2022). INTERVENTIONS Patients were randomized to receive open-label initiation of an ACE inhibitor (n = 257), ARB (n = 248), ARB in combination with DMX-200 (a chemokine receptor-2 inhibitor; n = 10), or no RAS inhibitor (control; n = 264) for up to 10 days. MAIN OUTCOMES AND MEASURES The primary outcome was organ support–free days, a composite of hospital survival and days alive without cardiovascular or respiratory organ support through 21 days. The primary analysis was a bayesian cumulative logistic model. Odds ratios (ORs) greater than 1 represent improved outcomes. RESULTS On February 25, 2022, enrollment was discontinued due to safety concerns. Among 679 critically ill patients with available primary outcome data, the median age was 56 years and 239 participants (35.2%) were women. Median (IQR) organ support–free days among critically ill patients was 10 (–1 to 16) in the ACE inhibitor group (n = 231), 8 (–1 to 17) in the ARB group (n = 217), and 12 (0 to 17) in the control group (n = 231) (median adjusted odds ratios of 0.77 [95% bayesian credible interval, 0.58-1.06] for improvement for ACE inhibitor and 0.76 [95% credible interval, 0.56-1.05] for ARB compared with control). The posterior probabilities that ACE inhibitors and ARBs worsened organ support–free days compared with control were 94.9% and 95.4%, respectively. Hospital survival occurred in 166 of 231 critically ill participants (71.9%) in the ACE inhibitor group, 152 of 217 (70.0%) in the ARB group, and 182 of 231 (78.8%) in the control group (posterior probabilities that ACE inhibitor and ARB worsened hospital survival compared with control were 95.3% and 98.1%, respectively). CONCLUSIONS AND RELEVANCE In this trial, among critically ill adults with COVID-19, initiation of an ACE inhibitor or ARB did not improve, and likely worsened, clinical outcomes. TRIAL REGISTRATION ClinicalTrials.gov Identifier: NCT0273570