The short-term impact of the 2020 pandemic lockdown on employment in Greece.

This paper analyzes the short-term employment impact of the COVID-19 lockdown in Greece during the first few months following the pandemic onset. During the initial lockdown period, aggregate employment was lower by almost 9 percentage points than it would have been expected based on pre-pandemic employment trends. However, due to a government intervention that prohibited layoffs, this was not due to higher separation rates. The overall short-term employment impact was due to lower hiring rates. To uncover the mechanism behind this, we use a difference-in-differences framework, and show that tourism-related activities, which are exposed to seasonal variation, had significantly lower employment entry rates in the months following the pandemic onset compared to non-tourism activities. Our results highlight the relevance of the timing of unanticipated shocks in economies with strong seasonal patterns, and the relative effectiveness of policy interventions to partly absorb the consequences of such shocks.

ACTH vs steroids for the treatment of acute gout in hospitalized patients: a randomized, open label, comparative study.

The management of acute gout in the hospital setting may be challenging since most patients are elderly with multiple unstable comorbidities. However, there are no prospective clinical trials for hospitalized patients with gout to guide optimal management. Evidence indicates that steroids or adrenocorticotropic hormone (ACTH) may be effective and safe therapeutic options for these patients. This study aimed at directly comparing the efficacy and safety of ACTH vs betamethasone for the treatment of gout in hospitalized patients. This is the first prospective clinical trial for hospitalized patients with gout. We designed a randomized, open label study to assess the efficacy and safety of a single intramuscular injection of either ACTH or betamethasone in hospitalized patients with acute gout. Primary efficacy endpoints were the change in intensity of pain as recorded using a Visual Analogue Scale (VAS) at baseline compared to 24 h (ΔVAS24h), and 48 h. Moreover, we assessed safety and effects on the hypothalamic-pituitary-adrenal (HPA) axis, glucose and lipid homeostasis, bone metabolism, electrolytes and renal function. 38 patients were recruited. Both treatments were highly effective. The mean ± SE ΔVAS24h and ΔVAS48h for ACTH was 4.48 ± 0.29 and 5.58 ± 0.26, respectively. The mean ± SE ΔVAS24h and ΔVAS48h for betamethasone was 4.67 ± 0.32 and 5.67 ± 0.28, respectively. Direct comparison between the two groups at 24 h and 48 h did not show statistically significant differences. Both treatments were well tolerated and safe. The effects on all metabolic parameters were mostly minimal and transient for both treatments. However, ACTH may affect less the HPA axis and bone metabolism compared to betamethasone, thus leading to the conclusion that. ACTH and betamethasone are effective and safe for the management of acute gout in hospitalized patients but that ACTH may associate with less disturbance of the HPA axis and bone metabolism. Our data support the use of both drugs as first line treatments for hospitalized patients with gout.Clinical trial registration: ClinicalTrials.gov NCT04306653.

Blockchain for Mobile Health Applications Acceleration with GPU Computing.

Blockchain is a linearly linked, distributed, and very robust data structure. Originally proposed as part of the Bitcoin distributed stack, it can be applied in a number of fields, most notably in smart contracts, social media, secure IoT, and cryptocurrency mining. It ensures data integrity by distributing strongly encrypted data in widely redundant segments. Each new insertion requires verification and approval by the majority of the users of the blockchain. Both encryption and verification are computationally intensive tasks which cannot be solved with ordinary off-the-shelf CPUs. This has resulted in a renewed scientific interest in secure distributed communication and coordination protocols. Mobile health applications are growing progressively popular and have the enormous advantage of timely diagnosis of certain conditions. However, privacy concerns have been raised as mobile health applications by default have access to highly sensitive personal data. This chapter presents concisely how blockchain can be applied to mobile health applications in order to enhance privacy.

Expanded national database collection and data coverage in the FINDbase worldwide database for clinically relevant genomic variation allele frequencies.

FINDbase (http://www.findbase.org) is a comprehensive data repository that records the prevalence of clinically relevant genomic variants in various populations worldwide, such as pathogenic variants leading mostly to monogenic disorders and pharmacogenomics biomarkers. The database also records the incidence of rare genetic diseases in various populations, all in well-distinct data modules. Here, we report extensive data content updates in all data modules, with direct implications to clinical pharmacogenomics. Also, we report significant new developments in FINDbase, namely (i) the release of a new version of the ETHNOS software that catalyzes development curation of national/ethnic genetic databases, (ii) the migration of all FINDbase data content into 90 distinct national/ethnic mutation databases, all built around Microsoft's PivotViewer (http://www.getpivot.com) software (iii) new data visualization tools and (iv) the interrelation of FINDbase with DruGeVar database with direct implications in clinical pharmacogenomics. The abovementioned updates further enhance the impact of FINDbase, as a key resource for Genomic Medicine applications.

Introducing dAUTObase: a first step towards the global scale geoepidemiology of autoimmune syndromes and diseases.

MOTIVATION: An autoimmune disorder occurs when the immune system mistakenly attacks and destroys its own healthy body tissues. The initiation of a geoepidemiological database, for recording autoimmune incidents with a focus to clinical manifestations, demographic parameters and geographic background is crucial to detect correlations. RESULTS: The dAUTObase collects an ever increasing number of publications-currently counting 435-on autoimmune diseases' frequencies in various populations and ethnic groups. The respective data have been hosted by a web application developed for the task. It uses three data visualization tools: the PivotViewer, the Disease Treemap and the Disease World Map, to assist the effective data querying. AVAILABILITY AND IMPLEMENTATION: The dAUTObase 2.0 version (www.biodata.gr/dautobase) needs no registration for querying, but data entry and modification is reserved for registered users (curators-administrators). CONTACT: kpoulas@upatras.gr or tzimas@cti.gr.

Exploiting expert systems in cardiology: a comparative study.

An improved Adaptive Neuro-Fuzzy Inference System (ANFIS) in the field of critical cardiovascular diseases is presented. The system stems from an earlier application based only on a Sugeno-type Fuzzy Expert System (FES) with the addition of an Artificial Neural Network (ANN) computational structure. Thus, inherent characteristics of ANNs, along with the human-like knowledge representation of fuzzy systems are integrated. The ANFIS has been utilized into building five different sub-systems, distinctly covering Coronary Disease, Hypertension, Atrial Fibrillation, Heart Failure, and Diabetes, hence aiding doctors of medicine (MDs), guide trainees, and encourage medical experts in their diagnoses centering a wide range of Cardiology. The Fuzzy Rules have been trimmed down and the ANNs have been optimized in order to focus into each particular disease and produce results ready-to-be applied to real-world patients.

DruGeVar: an online resource triangulating drugs with genes and genomic biomarkers for clinical pharmacogenomics.

BACKGROUND/AIMS: Pharmacogenomics aims to rationalize drug use by minimizing drug toxicity and/or by increasing drug efficacy. A large number of genomic markers have been correlated with variable drug responses and severity of adverse drug reactions. Although a number of these drugs bear pharmacogenomic information in their labels--approved by regulatory agencies--and comprehensive drug/gene lists exist online, information related to the respective pharmacogenomic biomarkers is currently missing from such lists. METHODS: We extracted information from the published literature and online resources and developed DruGeVar (http://drugevar.genomicmedicinealliance.org), an online resource triangulating drugs with genes and pharmacogenomic biomarkers in an effort to build a comprehensive database that could serve clinical pharmacogenomics. RESULTS AND CONCLUSIONS: A user-friendly data querying and visualization interface allows users to formulate simple and complex queries. Such a database would be readily applicable as a stand-alone resource or a plug-in module for other databases.

Developments in FINDbase worldwide database for clinically relevant genomic variation allele frequencies.

FINDbase (http://www.findbase.org) aims to document frequencies of clinically relevant genomic variations, namely causative mutations and pharmacogenomic markers, worldwide. Each database record includes the population, ethnic group or geographical region, the disorder name and the related gene, accompanied by links to any related databases and the genetic variation together with its frequency in that population. Here, we report, in addition to the regular data content updates, significant developments in FINDbase, related to data visualization and querying, data submission, interrelation with other resources and a new module for genetic disease summaries. In particular, (i) we have developed new data visualization tools that facilitate data querying and comparison among different populations, (ii) we have generated a new FINDbase module, built around Microsoft's PivotViewer (http://www.getpivot.com) software, based on Microsoft Silverlight technology (http://www.silverlight.net), that includes 259 genetic disease summaries from five populations, systematically collected from the literature representing the documented genetic makeup of these populations and (iii) the implementation of a generic data submission tool for every module currently available in FINDbase.

Updates of the HbVar database of human hemoglobin variants and thalassemia mutations.

HbVar (http://globin.bx.psu.edu/hbvar) is one of the oldest and most appreciated locus-specific databases launched in 2001 by a multi-center academic effort to provide timely information on the genomic alterations leading to hemoglobin variants and all types of thalassemia and hemoglobinopathies. Database records include extensive phenotypic descriptions, biochemical and hematological effects, associated pathology and ethnic occurrence, accompanied by mutation frequencies and references. Here, we report updates to >600 HbVar entries, inclusion of population-specific data for 28 populations and 27 ethnic groups for α-, and ß-thalassemias and additional querying options in the HbVar query page. HbVar content was also inter-connected with two other established genetic databases, namely FINDbase (http://www.findbase.org) and Leiden Open-Access Variation database (http://www.lovd.nl), which allows comparative data querying and analysis. HbVar data content has contributed to the realization of two collaborative projects to identify genomic variants that lie on different globin paralogs. Most importantly, HbVar data content has contributed to demonstrate the microattribution concept in practice. These updates significantly enriched the database content and querying potential, enhanced the database profile and data quality and broadened the inter-relation of HbVar with other databases, which should increase the already high impact of this resource to the globin and genetic database community.

Microattribution and nanopublication as means to incentivize the placement of human genome variation data into the public domain.

The advances in bioinformatics required to annotate human genomic variants and to place them in public data repositories have not kept pace with their discovery. Moreover, a law of diminishing returns has begun to operate both in terms of data publication and submission. Although the continued deposition of such data in the public domain is essential to maximize both their scientific and clinical utility, rewards for data sharing are few, representing a serious practical impediment to data submission. To date, two main strategies have been adopted as a means to encourage the submission of human genomic variant data: (1) database journal linkups involving the affiliation of a scientific journal with a publicly available database and (2) microattribution, involving the unambiguous linkage of data to their contributors via a unique identifier. The latter could in principle lead to the establishment of a microcitation-tracking system that acknowledges individual endeavor and achievement. Both approaches could incentivize potential data contributors, thereby encouraging them to share their data with the scientific community. Here, we summarize and critically evaluate approaches that have been proposed to address current deficiencies in data attribution and discuss ways in which they could become more widely adopted as novel scientific publication modalities.

Population-ethnic group specific genome variation allele frequency data: a querying and visualization journey.

National/ethnic mutation databases aim to document the genetic heterogeneity in various populations and ethnic groups worldwide. We have previously reported the development and upgrade of FINDbase (www.findbase.org), a database recording causative mutations and pharmacogenomic marker allele frequencies in various populations around the globe. Although this database has recently been upgraded, we continuously try to enhance its functionality by providing more advanced visualization tools that would further assist effective data querying and comparisons. We are currently experimenting in various visualization techniques on the existing FINDbase causative mutation data collection aiming to provide a dynamic research tool for the worldwide scientific community. We have developed an interactive web-based application for population-based mutation data retrieval. It supports sophisticated data exploration allowing users to apply advanced filtering criteria upon a set of multiple views of the underlying data collection and enables browsing the relationships between individual datasets in a novel and meaningful way.

Institutional Profile: Golden Helix Institute of Biomedical Research: interdisciplinary research and educational activities in pharmacogenomics and personalized medicine.

The Golden Helix Institute of Biomedical Research is an international nonprofit scientific organization with interdisciplinary research and educational activities in the field of genome medicine in Europe, Asia and Latin America. These activities are supervised by an international scientific advisory council, consisting of world leaders in the field of genomics and translational medicine. Research activities include the regional coordination of the Pharmacogenomics for Every Nation Initiative in Europe, in an effort to integrate pharmacogenomics in developing countries, the development of several national/ethnic genetic databases and related web services and the critical assessment of the impact of genetics and genomic medicine on society in various countries. Educational activities also include the organization of the Golden Helix Symposia(®), which are high-profile scientific research symposia in the field of personalized medicine and the Golden Helix Pharmacogenomics Days, an international educational activity focused on pharmacogenomics, as part of its international pharmacogenomics education and outreach efforts.

Population-specific documentation of pharmacogenomic markers and their allelic frequencies in FINDbase.

AIMS: Population and ethnic group-specific allele frequencies of pharmacogenomic markers are poorly documented and not systematically collected in structured data repositories. We developed the Frequency of Inherited Disorders Pharmacogenomics database (FINDbase-PGx), a separate module of the FINDbase, aiming to systematically document pharmacogenomic allele frequencies in various populations and ethnic groups worldwide. MATERIALS & METHODS: We critically collected and curated 214 scientific articles reporting pharmacogenomic markers allele frequencies in various populations and ethnic groups worldwide. Subsequently, in order to host the curated data, support data visualization and data mining, we developed a website application, utilizing Microsoft™ PivotViewer software. RESULTS: Curated allelic frequency data pertaining to 144 pharmacogenomic markers across 14 genes, representing approximately 87,000 individuals from 150 populations worldwide, are currently included in FINDbase-PGx. A user-friendly query interface allows for easy data querying, based on numerous content criteria, such as population, ethnic group, geographical region, gene, drug and rare allele frequency. CONCLUSION: FINDbase-PGx is a comprehensive database, which, unlike other pharmacogenomic knowledgebases, fulfills the much needed requirement to systematically document pharmacogenomic allelic frequencies in various populations and ethnic groups worldwide.

FINDbase: a worldwide database for genetic variation allele frequencies updated.

Frequency of INherited Disorders database (FIND base; http://www.findbase.org) records frequencies of causative genetic variations worldwide. Database records include the population and ethnic group or geographical region, the disorder name and the related gene, accompanied by links to any related external resources and the genetic variation together with its frequency in that population. In addition to the regular data content updates, we report the following significant advances: (i) the systematic collection and thorough documentation of population/ethnic group-specific pharmacogenomic markers allele frequencies for 144 markers in 14 genes of pharmacogenomic interest from different classes of drug-metabolizing enzymes and transporters, representing 150 populations and ethnic groups worldwide; (ii) the development of new data querying and visualization tools in the expanded FINDbase data collection, built around Microsoft's PivotViewer software (http://www.getpivot.com), based on Microsoft Silverlight technology (http://www.silverlight.net) that facilitates querying of large data sets and visualizing the results; and (iii) the establishment of the first database journal, by affiliating FINDbase with Human Genomics and Proteomics, a new open-access scientific journal, which would serve as a prime example of a non-profit model for sustainable database funding.