Immune mechanisms underlying COVID-19 pathology and post-acute sequelae of SARS-CoV-2 infection (PASC)
Why this work is in the frame
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Bibliographic record
Abstract
With a global tally of more than 500 million cases of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infections to date, there are growing concerns about the post-acute sequelae of SARS-CoV-2 infection (PASC), also known as long COVID. Recent studies suggest that exaggerated immune responses are key determinants of the severity and outcomes of the initial SARS-CoV-2 infection as well as subsequent PASC. The complexity of the innate and adaptive immune responses in the acute and post-acute period requires in-depth mechanistic analyses to identify specific molecular signals as well as specific immune cell populations which promote PASC pathogenesis. In this review, we examine the current literature on mechanisms of immune dysregulation in severe COVID-19 and the limited emerging data on the immunopathology of PASC. While the acute and post-acute phases may share some parallel mechanisms of immunopathology, it is likely that PASC immunopathology is quite distinct and heterogeneous, thus requiring large-scale longitudinal analyses in patients with and without PASC after an acute SARS-CoV-2 infection. By outlining the knowledge gaps in the immunopathology of PASC, we hope to provide avenues for novel research directions that will ultimately lead to precision therapies which restore healthy immune function in PASC patients.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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