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Over the last couple of decades, there has been a rapid growth in the number and scope of agricultural genetics, genomics and breeding databases and resources. The AgBioData Consortium (https://www.agbiodata.org/) currently represents 44 databases and resources (https://www.agbiodata.org/databases) covering model or crop plant and animal GGB data, ontologies, pathways, genetic variation and breeding platforms (referred to as 'databases' throughout). One of the goals of the Consortium is to facilitate FAIR (Findable, Accessible, Interoperable, and Reusable) data management and the integration of datasets which requires data sharing, along with structured vocabularies and/or ontologies. Two AgBioData working groups, focused on Data Sharing and Ontologies, respectively, conducted a Consortium-wide survey to assess the current status and future needs of the members in those areas. A total of 33 researchers responded to the survey, representing 37 databases. Results suggest that data-sharing practices by AgBioData databases are in a fairly healthy state, but it is not clear whether this is true for all metadata and data types across all databases; and that, ontology use has not substantially changed since a similar survey was conducted in 2017. Based on our evaluation of the survey results, we recommend (i) providing training for database personnel in a specific data-sharing techniques, as well as in ontology use; (ii) further study on what metadata is shared, and how well it is shared among databases; (iii) promoting an understanding of data sharing and ontologies in the stakeholder community; (iv) improving data sharing and ontologies for specific phenotypic data types and formats; and (v) lowering specific barriers to data sharing and ontology use, by identifying sustainability solutions, and the identification, promotion, or development of data standards. Combined, these improvements are likely to help AgBioData databases increase development efforts towards improved ontology use, and data sharing via programmatic means. Database URL  https://www.agbiodata.org/databases.

The Gene Ontology (GO) knowledgebase (http://geneontology.org) is a comprehensive resource concerning the functions of genes and gene products (proteins and noncoding RNAs). GO annotations cover genes from organisms across the tree of life as well as viruses, though most gene function knowledge currently derives from experiments carried out in a relatively small number of model organisms. Here, we provide an updated overview of the GO knowledgebase, as well as the efforts of the broad, international consortium of scientists that develops, maintains, and updates the GO knowledgebase. The GO knowledgebase consists of three components: (1) the GO-a computational knowledge structure describing the functional characteristics of genes; (2) GO annotations-evidence-supported statements asserting that a specific gene product has a particular functional characteristic; and (3) GO Causal Activity Models (GO-CAMs)-mechanistic models of molecular "pathways" (GO biological processes) created by linking multiple GO annotations using defined relations. Each of these components is continually expanded, revised, and updated in response to newly published discoveries and receives extensive QA checks, reviews, and user feedback. For each of these components, we provide a description of the current contents, recent developments to keep the knowledgebase up to date with new discoveries, and guidance on how users can best make use of the data that we provide. We conclude with future directions for the project.

Experimental data about gene functions curated from the primary literature have enormous value for research scientists in understanding biology. Using the Gene Ontology (GO), manual curation by experts has provided an important resource for studying gene function, especially within model organisms. Unprecedented expansion of the scientific literature and validation of the predicted proteins have increased both data value and the challenges of keeping pace. Capturing literature-based functional annotations is limited by the ability of biocurators to handle the massive and rapidly growing scientific literature. Within the community-oriented wiki framework for GO annotation called the Gene Ontology Normal Usage Tracking System (GONUTS), we describe an approach to expand biocuration through crowdsourcing with undergraduates. This multiplies the number of high-quality annotations in international databases, enriches our coverage of the literature on normal gene function, and pushes the field in new directions. From an intercollegiate competition judged by experienced biocurators, Community Assessment of Community Annotation with Ontologies (CACAO), we have contributed nearly 5,000 literature-based annotations. Many of those annotations are to organisms not currently well-represented within GO. Over a 10-year history, our community contributors have spurred changes to the ontology not traditionally covered by professional biocurators. The CACAO principle of relying on community members to participate in and shape the future of biocuration in GO is a powerful and scalable model used to promote the scientific enterprise. It also provides undergraduate students with a unique and enriching introduction to critical reading of primary literature and acquisition of marketable skills.

Throughout the twentieth century, Italian film criticism ran into various moments of crisis; three of these triggered the foundation of a union organization, a political instrument with little affinity for the intellectual elites and yet cyclically present in the history of our criticism. The years in question are 1916, 1925 and 1971, to which we owe, respectively, the Syndicate of the Film Press, the Syndicate of Intellectuals of Cinematography and the National Syndicate of Italian Film Critics. They are profoundly different moments and in any case in dialogue with each other, as phases of an identity repositioning in which the professional and ideological, political and social levels intersect. The aim of this essay is therefore to recover the studies that interpret the discursive practice of criticism as an entity ontologically connected to a state of crisis (de Man, Frey) to place them in a more accentuated historical framework. To do so, the three quoted periods will be reconstructed and analysed, using an archival corpus of period press as sources, and the cultural industry as an additional theoretical framework in the context of Italian literary theory of the sixties (Ferretti, Fortini), in order to restore facets and complexities of crisis that would otherwise not be resolved in purely endemic and ontological terms.

BackgroundElectrocardiogram (ECG) has proven to be useful for early detection of cardiac involvement in Anderson-Fabry disease (AFD); however, little evidence is available on the association between ECG alterations and the progression of the disease.Aim and MethodsTo perform a cross sectional comparison of ECG abnormalities throughout different left ventricular hypertrophy (LVH) severity subgroups, providing ECG patterns specific of the progressive AFD stages. 189 AFD patients from a multicenter cohort underwent comprehensive ECG analysis, echocardiography, and clinical evaluation.ResultsThe study cohort (39% males, median age 47 years, 68% classical AFD) was divided into 4 groups according to different degree of left ventricular (LV) thickness: group A ≤ 9 mm (n = 52, 28%); group B 10–14 mm (n = 76, 40%); group C 15–19 mm (n = 46, 24%); group D ≥ 20 mm (n = 15, 8%). The most frequent conduction delay was right bundle branch block (RBBB), incomplete in groups B and C (20%,22%) and complete RBBB in group D (54%, p

Young carers YCs) provide unpaid care for their family members due to several circumstances within the family. Caregiving can be time consuming and quite difficult for some adolescents. By meeting others' needs, their needs may be neglected, thereby potentially affecting their levels of self-compassion (SC) and subjective well-being (SWB). Due to a lack of studies in these areas, this descriptive, exploratory, quantitative, and comparative study aimed to fill in this gap. This study sampled 55 YCs and 107 non-YCs between the ages of 12-18 years. Multivariate analyses (MANOVA) were carried out. Results revealed that YCs and non-YCs had similar levels of SC and SWB. Implications for what it means for YCs and further support were discussed. Keywords: Young carers, self-compassion, subjective well-being, non-caregiving youth, comparative study, In Canada, young carers (YCs) represent around 28.2% of children and youth between the ages of 15-24 years, who provide unpaid care for family members due to specific circumstances in [...]

Background: Adherence and persistence to treatment with disease-modifying therapies (DMTs) is a predictor of the efficacy of treatment. Aims: The objectives of the study were the analysis of adherence, persistence, switches, and costs of the drugs used in MS. Methods: This is a retrospective non-interventional pharmacological observational study of 610 patients diagnosed with Relapsing-Remitting Multiple Sclerosis (RRMS) under therapy between January 2007 and September 2022. Results: Adherence values were greater than 0.75 for all the drugs in considered for the study. The mean persistence value was 2.5 years on the analysis performed on the first-line treatment. Conclusion: In a therapy in which adherence is predominant, but not exclusive to therapy efficacy, persistence to the drug is synonymous with drug efficacy. Plain Language Summary: Multiple Sclerosis (MS) is a chronic disease that often begins early in life. Like in many chronic diseases, consistent adherence to treatment is vital for the long-term effectiveness of therapies. In MS, most treatments—whether oral or parenteral—are self-administered at home, making long-term adherence crucial. Persistence in sticking with a single drug is also seen as an indicator of the treatment's effectiveness, as longer use generally means fewer therapy changes and greater drug efficacy. This article analyzes these key pharmacy utilization metrics—adherence, persistence, and therapy switches—to directly compare the real-world effectiveness of the most commonly used MS drugs. [ABSTRACT FROM AUTHOR]

One of the hallmarks of microgravity-induced effects in several cellular models is represented by the alteration of oxidative balance with the consequent accumulation of reactive oxygen species (ROS). It is well known that male germ cells are sensitive to oxidative stress and to changes in gravitational force, even though published data on germ cell models are scarce. We previously studied the effects of simulated microgravity (s-microgravity) on a 2D cultured TCam-2 seminoma-derived cell line, considered the only human cell line available to study in vitro mitotically active human male germ cells. In this study, we used a corresponding TCam-2 3D cell culture model that mimics cell–cell contacts in organ tissue to test the possible effects induced by s-microgravity exposure. TCam-2 cell spheroids were cultured for 24 h under unitary gravity (Ctr) or s-microgravity conditions, the latter obtained using a random positioning machine (RPM). A significant increase in intracellular ROS and mitochondria superoxide anion levels was observed after RPM exposure. In line with these results, a trend of protein and lipid oxidation increase and increased pCAMKII expression levels were observed after RPM exposure. The ultrastructural analysis via transmission electron microscopy revealed that RPM-exposed mitochondria appeared enlarged and, even if seldom, disrupted. Notably, even the expression of the main enzymes involved in the redox homeostasis appears modulated by RPM exposure in a compensatory way, with GPX1, NCF1, and CYBB being downregulated, whereas NOX4 and HMOX1 are upregulated. Interestingly, HMOX1 is involved in the heme catabolism of mitochondria cytochromes, and therefore the positive modulation of this marker can be associated with the observed mitochondria alteration. Altogether, these data demonstrate TCam-2 spheroid sensitivity to acute s-microgravity exposure and indicate the capability of these cells to trigger compensatory mechanisms that allow them to overcome the exposure to altered gravitational force.

The future of agricultural research depends on data. The sheer volume of agricultural biological data being produced today makes excellent data management essential. Governmental agencies, publishers and science funders require data management plans for publicly funded research. Furthermore, the value of data increases exponentially when they are properly stored, described, integrated and shared, so that they can be easily utilized in future analyses. AgBioData (https://www.agbiodata.org) is a consortium of people working at agricultural biological databases, data archives and knowledgbases who strive to identify common issues in database development, curation and management, with the goal of creating database products that are more Findable, Accessible, Interoperable and Reusable. We strive to promote authentic, detailed, accurate and explicit communication between all parties involved in scientific data. As a step toward this goal, we present the current state of biocuration, ontologies, metadata and persistence, database platforms, programmatic (machine) access to data, communication and sustainability with regard to data curation. Each section describes challenges and opportunities for these topics, along with recommendations and best practices.

Background: Accurate risk stratification of critically ill patients with coronavirus disease 2019 (COVID-19) is essential for optimizing resource allocation, delivering targeted interventions, and maximizing patient survival probability. Machine learning (ML) techniques are attracting increased interest for the development of prediction models as they excel in the analysis of complex signals in data-rich environments such as critical care. Methods: We retrieved data on patients with COVID-19 admitted to an intensive care unit (ICU) between March and October 2020 from the RIsk Stratification in COVID-19 patients in the Intensive Care Unit (RISC-19-ICU) registry. We applied the Extreme Gradient Boosting (XGBoost) algorithm to the data to predict as a binary outcome the increase or decrease in patients’ Sequential Organ Failure Assessment (SOFA) score on day 5 after ICU admission. The model was iteratively cross-validated in different subsets of the study cohort. Results: The final study population consisted of 675 patients. The XGBoost model correctly predicted a decrease in SOFA score in 320/385 (83%) critically ill COVID-19 patients, and an increase in the score in 210/290 (72%) patients. The area under the mean receiver operating characteristic curve for XGBoost was significantly higher than that for the logistic regression model (0.86 vs. 0.69, P