Restrained memory CD8 <sup>+</sup> T cell responses favors viral persistence and elevated IgG responses in patients with severe Long COVID
Bibliographic record
Abstract
Abstract During the COVID-19 pandemic it was widely described that certain individuals infected by SARS-CoV-2 experience persistent disease signs and symptoms, Long COVID, which in some cases is very severe with life changing consequences. To maximize our chances of identifying the underpinnings of this illness, we have focused on 121 of the most severe cases from >1000 patients screened in specialized clinics in Sweden and Belgium. We restricted this study to subjects with objective measures of organ damage or dysfunction, >3 months following a verified, but mild-to-moderate SARS-CoV-2 infection. By performing systems-level immunological testing and comparisons to controls fully convalescent following a similar mild/moderate COVID-19 episode, we identify elevated serological responses to SARS-CoV-2 in severe Long COVID suggestive of chronic antigen stimulation. Persistent viral reservoirs have been proposed in Long COVID and using multiple orthogonal methods for detection of SARS-CoV-2 RNA and protein in plasma we identify a subset of patients with detectable antigens, but with minimal overlap across assays, and no correlation to symptoms or immune measurements. Elevated serologic responses to SARS-CoV-2 on the other hand were inversely correlated with clonally expanded memory CD8 + T cells, indicating that restrained clonal expansion enables viral persistence, chronic antigen exposure and elevated IgG responses, even if antigen-detection in blood is not universally possible.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".