SARS-CoV2 infection leads to severe lung damage due to pneumonia and, in more severe cases, leads to acute respiratory distress syndrome, or ARDS. This affects the viability of bronchoalveolar cells. An important role in the pathogenesis of these complications is the hyperactivation of the renin-angiotensin-aldosterone (RAA) pathway and induction of cytokine storm that occurs in an Nlrp3 inflammasome-dependent manner. To shed more light on the susceptibility of lung tissue to SARS-CoV2 infection, we evaluated murine bronchioalveolar stem cells (BASC), alveolar type II cells (AT2), and 3D-derived organoids expression of mRNA encoding genes involved in virus entry into cells, components of RAA, and genes that comprise elements of the Nlrp3 inflammasome pathway. We noticed that all these genes are expressed by lung alveolar stem cells and organoids-derived from these cells. Interestingly, all these cells express a high level of ACE2 that, on the one hand, serves as an entry receptor for SARS-CoV2 and, on the other, converts angiotensin II into its physiological antagonist, angiotensin 1–7 (Ang 1–7), which has been reported to have a protective role in lung damage. To shed more light on the role of Ang 1–7 on lung tissue, we exposed lung-derived BASC and AT2 cells to this mediator of RAA and noticed that it increases the proliferation of these cells. Based on this, Ang 1–7 could be employed to alleviate the damage to lung alveolar stem/progenitor cells during SARS-CoV2 infection.
(1) Background: Administrative data allows for time- and cost-efficient acquisition of large volumes of individual patient data invaluable for evaluation of the prevalence of diseases and clinical outcomes. The aim of the study was to evaluate the accuracy of data collected from the Polish National Health Fund (NHF), from a researcher’s perspective, in regard to a cohort of atrial fibrillation patients. (2) Methods: NHF data regarding atrial fibrillation and common cardiovascular comorbidities was compared with the data collected manually from the individual patients’ health records (IHR) collected in the retrospective CRAFT registry (NCT02987062). (3) Results: Data from the NHF underestimated the proportion of patients with AF (NHF = 83% vs. IHR = 100%) while overestimating the proportion of patients with other cardiovascular comorbidities in the cohort. Significantly higher CHA2DS2VASc (Median, [Q1–Q3]) (NHF: 1, [0–2]; vs. IHR: 1, [0–1]; p < 0.001) and HAS-BLED (Median, [Q1–Q3]) (NHF: 4, [2–6] vs. IHR: 3, [2–5]; p < 0.001) scores were calculated according to NHF in comparison to IHR data, respectively. (4) Conclusions: Clinical researchers should be aware that significant differences between IHR and billing data in cardiovascular research can be observed which should be acknowledged while drawing conclusions from administrative data-based cohorts. Natural Language Processing of IHR could further increase administrative data quality in the future.
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