Severity of COVID-19 in Pregnant Women: A Review on the PotentialRole of Regulatory T Cells
Bibliographic record
Abstract
As a physiological condition, pregnancy may cause temporary alterations in the hematological, cardiopulmonary, and immune responses, affecting the maternal susceptibility to viral infections. Pregnant women are vulnerable to infection with the influenza A virus, hepatitis E virus, MERS CoV, and SARS CoV. The agent of Coronavirus disease (COVID-19) is the SARS coronavirus (SARS CoV-2), which affects the cells upon binding to the angiotensin-converting enzyme-2 (ACE2). However, ACE2 expression is elevated in the placental tissue. However, surprisingly, COVID-19 infection in pregnant women tends to have a lower severity and mortality. Therefore, it is interesting to find the immunological mechanisms related to the severity of COVID-19 in pregnancy. Regulatory T cells (Tregs) are a subset of CD4+T cells that may play a central role in maintaining maternal tolerance by regulating immune responses. Pregnancy-induced Tregs are developed to control immune responses against paternal antigens expressed by the semi-allograft fetus. The role of uncontrolled immune responses in COVID-19 pathogenesis has already been identified. This review provides insight into whether pregnancy- induced regulatory T-cell functions could influence the severity of COVID-19 infection during pregnancy.
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How this classification was reachedexpand
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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".