Short-Term Supplementation of Sodium Nitrate vs. Sodium Chloride Increases Homoarginine Synthesis in Young Men Independent of Exercise

The aim of the study was to investigate the effects of short-term oral administration of inorganic nitrate (NaNO3; n = 8) or placebo (NaCl; n = 9) (each 0.1 mmol/kg body weight/d for 9 days) on plasma amino acids, creatinine, and oxidative stress in healthy young men. At baseline, the plasma concentrations of amino acids did not differ between the groups. At the end of the study, the plasma concentrations of homoarginine (hArg; by 24%, p = 0.0001), citrulline and ornithine (Cit/Orn; by 16%, p = 0.015), and glutamine/glutamate (Gln/Glu; by 6%, p = 0.0003) were higher in the NaNO3 group compared to the NaCl group. The plasma concentrations of sarcosine (Sarc; by 28%, p hArg + Orn, with equilibrium constant Kharg; (2) the formation of guanidinoacetate (GAA) and Orn from Arg and glycine (Gly): Arg + Gly GAA + Orn, with equilibrium constant Kgaa. The plasma Kgaa/KhArg ratio was lower in the NaNO3 group compared to the NaCl group (1.57 vs. 2.02, p = 0.0034). Our study suggests that supplementation of inorganic nitrate increases the AGAT-catalyzed synthesis of hArg and decreases the N-methyltransferase-catalyzed synthesis of GAA, the precursor of creatine. To our knowledge, this is the first study to demonstrate elevation of hArg synthesis by inorganic nitrate supplementation. Remarkably, an increase of 24% corresponds to the synthesis capacity of one kidney in healthy humans. Differences in the association between plasma concentrations of amino acids in the NaNO3 and NaCl groups suggest changes in amino-acid homeostasis. Plasma concentrations of the oxidative stress marker malondialdehyde (MDA) did not change after supplementation of NaNO3 or NaCl over the whole exercise time range. Plasma nitrite concentration turned out to be a more discriminant marker of NaNO3 ingestion than plasma nitrate (area under the receiver operating characteristic curve: 0.951 vs. 0.866, p < 0.0001 each)

Development of interoperable, domain-specific extensions for the German Corona Consensus (GECCO) COVID-19 research dataset using an interdisciplinary, consensus-based workflow

Background The COVID-19 pandemic has spurred large-scale, inter-institutional research efforts. To enable these efforts, researchers must agree on dataset definitions that not only cover all elements relevant to the respective medical specialty but that are also syntactically and semantically interoperable. Following such an effort, the German Corona Consensus (GECCO) dataset has been developed previously as a harmonized, interoperable collection of the most relevant data elements for COVID-19-related patient research. As GECCO has been developed as a compact core dataset across all medical fields, the focused research within particular medical domains demands the definition of extension modules that include those data elements that are most relevant to the research performed in these individual medical specialties. Objective To (i) specify a workflow for the development of interoperable dataset definitions that involves a close collaboration between medical experts and information scientists and to (ii) apply the workflow to develop dataset definitions that include data elements most relevant to COVID-19-related patient research in immunization, pediatrics, and cardiology. Methods We developed a workflow to create dataset definitions that are (i) content-wise as relevant as possible to a specific field of study and (ii) universally usable across computer systems, institutions, and countries, i.e., interoperable. We then gathered medical experts from three specialties (immunization, pediatrics, and cardiology) to the select data elements most relevant to COVID-19-related patient research in the respective specialty. We mapped the data elements to international standardized vocabularies and created data exchange specifications using HL7 FHIR. All steps were performed in close interdisciplinary collaboration between medical domain experts and medical information scientists. The profiles and vocabulary mappings were syntactically and semantically validated in a two-stage process. Results We created GECCO extension modules for the immunization, pediatrics, and cardiology domains with respect to the pandemic requests. The data elements included in each of these modules were selected according to the here developed consensus-based workflow by medical experts from the respective specialty to ensure that the contents are aligned with the respective research needs. We defined dataset specifications for a total number of 48 (immunization), 150 (pediatrics), and 52 (cardiology) data elements that complement the GECCO core dataset. We created and published implementation guides and example implementations as well as dataset annotations for each extension module. Conclusions These here presented GECCO extension modules, which contain data elements most relevant to COVID-19-related patient research in immunization, pediatrics and cardiology, were defined in an interdisciplinary, iterative, consensus-based workflow that may serve as a blueprint for the development of further dataset definitions. The GECCO extension modules provide a standardized and harmonized definition of specialty-related datasets that can help to enable inter-institutional and cross-country COVID-19 research in these specialties