Sudden cardiac death in young athletes: Literature review of molecular basis

Intense athletic training and competition can rarely result in sudden cardiac death (SCD). Despite the introduction of pre-participation cardiovascular screening, especially among young competitive athletes, sport-related SCD remains a debated issue among medical personnel, sports communities and laypersons alike, and generates significant media attention. The most frequent cause of SCD is a hidden inherited cardiomyopathy, the athletes may not even be aware of. Predictive medicine, by searching the presence of pathogenic alterations in cardiac genes, may be an integrative tool, besides the conventional ones used in cardiology (mainly electro and echocardiogram), to reach a definitive diagnosis in athletes showing signs/symptoms, even borderline, of inherited cardiomyopathy/ channelopathy, and in athletes presenting family history of SCD and/or of hereditary cardiac disease. In this review, we revised the molecular basis of the major cardiac diseases associated to sudden cardiac death and the clinical molecular biology approach that can be used to perform risk assessment at DNA level of sudden cardiac death, contributing to the early implementation of adequate therapy. Alterations can occur in ion channel genes, in genes encoding desmosomal and junctional proteins, sarcomeric and Z-disc proteins, proteins for the cytoskeleton and the nuclear envelope. The advent of next generation sequencing (NGS) technology has provided the means to search for mutations in all these genes, at the same time. Therefore, this molecular approach should be the preferred methodology for the aforementioned purpose

On the impact of cross-domain edge detection in biomedical event extraction

Biomedical event extraction is a crucial task to represent the increasingly growing body of biomedical literature. Despite recent advances in the methods, most prior work evaluate systems in-domain and on complete event structures only. Motivated by these limitations, we present a cross-domain study for the stage of edge detection towards the goal of domain adaptation for biomedical event extraction

Cross-Domain Evaluation of Edge Detection for Biomedical Event Extraction

Biomedical event extraction is a crucial task in order to automatically extract information from the increasingly growing body of biomedical literature. Despite advances in the methods in recent years, most event extraction systems are still evaluated in-domain and on complete event structures only. This makes it hard to determine the performance of intermediate stages of the task, such as edge detection, across different corpora. Motivated by these limitations, we present the first cross-domain study of edge detection for biomedical event extraction. We analyze differences between five existing gold standard corpora, create a standardized benchmark corpus, and provide a strong baseline model for edge detection. Experiments show a large drop in performance when the baseline is applied on out-of-domain data, confirming the need for domain adaptation methods for the task. To encourage research efforts in this direction, we make both the data and the baseline available to the research community: https://www.cosbi.eu/cfx/9985

Biomedical Event Extraction as Sequence Labeling

We introduce Biomedical Event Extraction as Sequence Labeling (BeeSL), a joint end-to-end neural information extraction model. BeeSL recasts the task as sequence labeling, taking advantage of a multi-label aware encoding strategy and jointly modeling the intermediate tasks via multi-task learning. BeeSL is fast, accurate, end-to-end, and unlike current methods does not require any external knowledge base or preprocessing tools. BeeSL outperforms the current best system (Li et al., 2019) on the Genia 2011 benchmark by 1.57% absolute F1 score reaching 60.22% F1, establishing a new state of the art for the task. Importantly, we also provide first results on biomedical event extraction without gold entity information. Empirical results show that BeeSL's speed and accuracy makes it a viable approach for large-scale real-world scenarios

Biomedical Event Extraction as Sequence Labeling

We introduce Biomedical Event Extraction as Sequence Labeling (BeeSL), a joint end-to-end neural information extraction model. BeeSL recasts the task as sequence labeling, taking advantage of a multi-label aware encoding strategy and jointly modeling the intermediate tasks via multi-task learning. BeeSL is fast, accurate, end-to-end, and unlike current methods does not require any external knowledge base or preprocessing tools. BeeSL outperforms the current best system (Li et al., 2019) on the Genia 2011 benchmark by 1.57% absolute F1 score reaching 60.22% F1, establishing a new state of the art for the task. Importantly, we also provide first results on biomedical event extraction without gold entity information. Empirical results show that BeeSL’s speed and accuracy makes it a viable approach for large-scale real-world scenarios

Demographic and epidemiological characteristics of Ukrainian refugees in an Italian local health authority

Background: The Russian invasion of Ukraine caused millions of Ukrainian refugees to flee to other nations. To provide the most appropriate assistance, host nations necessitate up-to-date information regarding Ukrainian refugee's demographic and epidemiological conditions. We aim to investigate the demographic composition, the COVID-19 vaccinations performed, specialist care provided and the prevalence of non-communicable diseases (NCDs) in refugees assisted by an Italian Local Health Authority (LHA). Methods: We conducted a retrospective cross-sectional analysis from March to June 2022, analyzing the demographic and epidemiological status of Ukrainians. Statistical analyses were carried out to assess possible associations between NCDs distribution, age and gender. Results: LHA Roma 1 assisted 9349 Ukrainian refugees. Of these, 2784 (29.8%) were males and 6565 (70.2%) were females, with a median age of 25 years. Two thousand four hundred and eighty-five Ukrainian refugees were vaccinated against COVID-19. Among them, 401 (16.1%) had at least one NCD. The most frequent groups of diseases were related to the circulatory system (50.6%), the endocrine system (24.9%), and mental and behavioral disorders (6.5%). Conclusion: Refugees need healthcare services targeted mainly towards minors and females. It is essential to analyze and monitor the demographic and epidemiological conditions to provide evidence about patient management and the best care integrated into the health service of host countries

Molecular Epidemiology of Mitochondrial Cardiomyopathy: A Search Among Mitochondrial and Nuclear Genes

Mitochondrial Cardiomyopathy (MCM) is a common manifestation of multi-organ Mitochondrial Diseases (MDs), occasionally present in non-syndromic cases. Diagnosis of MCM is complex because of wide clinical and genetic heterogeneity and requires medical, laboratory, and neuroimaging investigations. Currently, the molecular screening for MCM is fundamental part of MDs management and allows achieving the definitive diagnosis. In this article, we review the current genetic knowledge associated with MDs, focusing on diagnosis of MCM and MDs showing cardiac involvement. We searched for publications on mitochondrial and nuclear genes involved in MCM, mainly focusing on genetic screening based on targeted gene panels for the molecular diagnosis of the MCM, by using Next Generation Sequencing. Here we report twelve case reports, four case-control studies, eleven retrospective studies, and two prospective studies, for a total of twenty-nine papers concerning the evaluation of cardiac manifestations in mitochondrial diseases. From the analysis of published causal mutations, we identified 130 genes to be associated with mitochondrial heart diseases. A large proportion of these genes (34.3%) encode for key proteins involved in the oxidative phosphorylation system (OXPHOS), either as directly OXPHOS subunits (22.8%), and as OXPHOS assembly factors (11.5%). Mutations in several mitochondrial tRNA genes have been also reported in multi-organ or isolated MCM (15.3%). This review highlights the main disease-genes, identified by extensive genetic analysis, which could be included as target genes in next generation panels for the molecular diagnosis of patients with clinical suspect of mitochondrial cardiomyopathies

Earthquakes trigger the loss of groundwater biodiversity

Earthquakes are among the most destructive natural events. The 6 April 2009, 6.3-Mw earthquake in L\u27Aquila (Italy) markedly altered the karstic Gran Sasso Aquifer (GSA) hydrogeology and geochemistry. The GSA groundwater invertebrate community is mainly comprised of small-bodied, colourless, blind microcrustaceans. We compared abiotic and biotic data from two pre-earthquake and one post-earthquake complete but non-contiguous hydrological years to investigate the effects of the 2009 earthquake on the dominant copepod component of the obligate groundwater fauna. Our results suggest that the massive earthquake-induced aquifer strain biotriggered a flushing of groundwater fauna, with a dramatic decrease in subterranean species abundance. Population turnover rates appeared to have crashed, no longer replenishing the long-standing communities from aquifer fractures, and the aquifer became almost totally deprived of animal life. Groundwater communities are notorious for their low resilience. Therefore, any major disturbance that negatively impacts survival or reproduction may lead to local extinction of species, most of them being the only survivors of phylogenetic lineages extinct at the Earth surface. Given the ecological key role played by the subterranean fauna as decomposers of organic matter and "ecosystem engineers", we urge more detailed, long-term studies on the effect of major disturbances to groundwater ecosystems