Mechanisms of Dysregulated Humoral and Cellular Immunity by SARS-CoV-2
Bibliographic record
Abstract
The current coronavirus disease 2019 (COVID-19) pandemic, a disease caused by severe acute respiratory syndrome corona virus 2 (SARS-CoV-2), was first identified in December 2019 in China, and has led to thousands of mortalities globally each day. While the innate immune response serves as the first line of defense, viral clearance requires activation of adaptive immunity, which employs B and T cells to provide sanitizing immunity. SARS-CoV-2 has a potent arsenal of mechanisms used to counter this adaptive immune response through processes, such as T cells depletion and T cell exhaustion. These phenomena are most often observed in severe SARS-CoV-2 patients, pointing towards a link between T cell function and disease severity. Moreover, neutralizing antibody titers and memory B cell responses may be short lived in many SARS-CoV-2 patients, potentially exposing these patients to re-infection. In this review, we discuss our current understanding of B and T cells immune responses and activity in SARS-CoV-2 pathogenesis.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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 source (direct Gemma or distilled Codex), 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".