Role of ACE2 in pregnancy and potential implications for COVID-19 susceptibility
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In times of coronavirus disease 2019 (COVID-19), the impact of severe acute respiratory syndrome (SARS)-coronavirus (CoV)-2 infection on pregnancy is still unclear. The presence of angiotensin-converting enzyme (ACE) 2 (ACE2), the main receptor for SARS-CoV-2, in human placentas indicates that this organ can be vulnerable for viral infection during pregnancy. However, for this to happen, additional molecular processes are critical to allow viral entry in cells, its replication and disease manifestation, particularly in the placenta and/or feto-maternal circulation. Beyond the risk of vertical transmission, COVID-19 is also proposed to deplete ACE2 protein and its biological actions in the placenta. It is postulated that such effects may impair essential processes during placentation and maternal hemodynamic adaptations in COVID-19 pregnancy, features also observed in several disorders of pregnancy. This review gathers information indicating risks and protective features related to ACE2 changes in COVID-19 pregnancies. First, we describe the mechanisms of SARS-CoV-2 infection having ACE2 as a main entry door and current evidence of viral infection in the placenta. Further, we discuss the central role of ACE2 in physiological systems such as the renin-angiotensin system (RAS) and the kallikrein-kinin system (KKS), both active during placentation and hemodynamic adaptations of pregnancy. Significant knowledge gaps are also identified and should be urgently filled to better understand the fate of ACE2 in COVID-19 pregnancies and the potential associated risks. Emerging knowledge will be able to improve the early stratification of high-risk pregnancies with COVID-19 exposure as well as to guide better management and follow-up of these mothers and their children.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.035 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it