Fluid Restriction Dehydration Increase Core Temperature During Endurance Exercise Compared to Exercise Induced Dehydration

International Journal of Exercise Science 15(2): 166-176, 2022. This study aimed to evaluate the difference in heart rate and core temperature during aerobic exercise between two forms of dehydration: exercise-induced (EI) and fluid restricted (FR). Twenty-two subjects (N = 22; 83.35 ± 13.92 kg) completed the current study, performing a familiarization session, a pre-experimental exercise session, and two exercise testing sessions. The EI exercise trial (81.52 ± 13.72 kg) was conducted after performing exercise in a hot environment to lose three to four percent of body weight and partial rehydration. The FR exercise trial (81.53 ± 14.14 kg) was completed after 12 hours of fluid restriction. During both exercise sessions, subjects pedaled against a set resistance of 130 watts for 30 minutes. The main effect of hydration on Tc was significant, F(1, 18) = 4.474, p = .049, ηp2 = .199 (Figure 2) with core temperature being greater during the FR trial compared to the EI trial (FR = 37.58 ± .06°C vs. EI = 37.31 ± .11°C). No significant interaction was found between hydration and time for HR, F(2, 42) = 0.120, p = .887, ηp2 = .006. The main effect of time on HR was significant, F(2, 42) = 119.664, p \u3c .001, ηp2 = .851. Fluid restriction was associated with an increase in core temperature. An increased core temperature may negatively influence performance, and care should be taken to ensure proper hydration

The Ontology for Biomedical Investigations

The Ontology for Biomedical Investigations (OBI) is an ontology that provides terms with precisely defined meanings to describe all aspects of how investigations in the biological and medical domains are conducted. OBI re-uses ontologies that provide a representation of biomedical knowledge from the Open Biological and Biomedical Ontologies (OBO) project and adds the ability to describe how this knowledge was derived. We here describe the state of OBI and several applications that are using it, such as adding semantic expressivity to existing databases, building data entry forms, and enabling interoperability between knowledge resources. OBI covers all phases of the investigation process, such as planning, execution and reporting. It represents information and material entities that participate in these processes, as well as roles and functions. Prior to OBI, it was not possible to use a single internally consistent resource that could be applied to multiple types of experiments for these applications. OBI has made this possible by creating terms for entities involved in biological and medical investigations and by importing parts of other biomedical ontologies such as GO, Chemical Entities of Biological Interest (ChEBI) and Phenotype Attribute and Trait Ontology (PATO) without altering their meaning. OBI is being used in a wide range of projects covering genomics, multi-omics, immunology, and catalogs of services. OBI has also spawned other ontologies (Information Artifact Ontology) and methods for importing parts of ontologies (Minimum information to reference an external ontology term (MIREOT)). The OBI project is an open cross-disciplinary collaborative effort, encompassing multiple research communities from around the globe. To date, OBI has created 2366 classes and 40 relations along with textual and formal definitions. The OBI Consortium maintains a web resource (http://obi-ontology.org) providing details on the people, policies, and issues being addressed in association with OBI. The current release of OBI is available at http://purl.obolibrary.org/obo/obi.owl

“You Always End up Feeling Like You’re Some Hypochondriac”: Intimate Partner Violence Survivors’ Experiences Addressing Depression and Pain

Objective: Little is known regarding how providers should use information about intimate partner violence (IPV) to care for depressed patients. Our objective was to explore what depressed IPV survivors believe about the relationship between abuse, mental health, and physical symptoms and to elicit their recommendations for addressing depression. Design: Focus group study. Patients/Participants: Adult, English-speaking, female, Internal Medicine clinic patients with depressive symptoms and a history of IPV. Interventions: Thematic analysis using an inductive approach (consistent with grounded theory), at a semantic level, with an essentialist paradigm. Measurements and Main Results: Twenty three women participated in 5 focus groups. Although selected because of their depression, participants often felt their greatest concerns were physical. They acknowledged that their abuse history, depression, and physical complaints compound each other. They appreciated the need for health care workers to know about their depression and IPV history to get a “full picture” of their health, but they were often hesitant to discuss such issues with providers because of their fear that such information would make providers think their symptoms were “all in their head” or would encourage providers to discount their pain. Participants discussed difficulties related to trust and control in relationships with providers and gave recommendations as to how providers can earn their trust. Conclusions: Understanding a patient’s IPV history may allow providers to develop a better therapeutic relationship. To treat depression adequately, it is important for providers to reassure patients that they believe their physical symptoms; to communicate respect for patients’ intelligence, experience, and complexity; and to share control

Making Common Fund data more findable: catalyzing a data ecosystem

The Common Fund Data Ecosystem (CFDE) has created a flexible system of data federation that enables researchers to discover datasets from across the US National Institutes of Health Common Fund without requiring that data owners move, reformat, or rehost those data. This system is centered on a catalog that integrates detailed descriptions of biomedical datasets from individual Common Fund Programs’ Data Coordination Centers (DCCs) into a uniform metadata model that can then be indexed and searched from a centralized portal. This Crosscut Metadata Model (C2M2) supports the wide variety of data types and metadata terms used by individual DCCs and can readily describe nearly all forms of biomedical research data. We detail its use to ingest and index data from 11 DCCs

FAIR Principles for Research Software (FAIR4RS Principles)

Chue Hong NP, Katz DS, Barker M, et al. FAIR Principles for Research Software (FAIR4RS Principles). 2021.Research software is a fundamental and vital part of research worldwide, yet there remain significant challenges to software productivity, quality, reproducibility, and sustainability. Improving the practice of scholarship is a common goal of the open science, open source software and FAIR (Findable, Accessible, Interoperable and Reusable) communities, but improving the sharing of research software has not yet been a strong focus of the latter. To improve the FAIRness of research software, the FAIR for Research Software (FAIR4RS) Working Group has sought to understand how to apply the FAIR Guiding Principles for scientific data management and stewardship to research software, bringing together existing and new community efforts. Many of the FAIR Guiding Principles can be directly applied to research software by treating software and data as similar digital research objects. However, specific characteristics of software — such as its executability, composite nature, and continuous evolution and versioning — make it necessary to revise and extend the principles. This document presents the first version of the FAIR Principles for Research Software (FAIR4RS Principles). It is an outcome of the FAIR for Research Software Working Group (FAIR4RS WG). The FAIR for Research Software Working Group is jointly convened as an RDA Working Group, FORCE11 Working Group, and Research Software Alliance (ReSA) Task Force