Persistence of SARS-CoV-2 in long COVID-19 patients
Bibliographic record
Abstract
Abstract The World Health Organization has defined long COVID-19 (LC) as a condition where patients exhibit persistent symptoms over time after its acute phase, which cannot be explained by alternative diagnosis. Since we have previously reported residual viral antigens in tissues of convalescent patients, we now aim to assess the presence of such antigens in post-convalescent tissues. Here, we established the presence of residual virus within the appendix and breast tissue of 2 patients who exhibited LC symptoms, 163 to 462 days upon positive diagnosis, using immunohistological techniques. We observed positive staining for viral nucleocapsid protein (NP) in the appendix, and tumour-adjacent region of the breast, but not within the tumour. Multiplex immunohistochemistry further detected colocalization of viral NP with macrophage marker CD68, in support of immune cells being direct targets. Notably, with RNA scope, both positive-sense and negative-sense (replicative intermediate) viral RNA were detected. As a single-stranded virus, SARS-CoV-2, have to produce a replicative intermediate as a template to synthesize new genomic RNAs. Thus, the detection of negative-sense viral RNA suggests ongoing viral replication. While viral RNA and antigen from gastrointestinal and stool samples of convalescent patients has been extensively reported, we believe this is the first study to detect viable virus. Furthermore, our positive finding in the breast tissue also corroborated with recent reports that immunocompromised patients had also experienced LC symptoms and persistent viral replication. Overall, our findings, along with emerging LC studies, question the possibility of the gastrointestinal tract functioning as a reservoir. Supported by A*STAR Career Development Award (C21112056)
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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".