Longitudinal profile of antibodies against SARS‐coronavirus in SARS patients and their clinical significance
Bibliographic record
Abstract
BACKGROUND: Severe acute respiratory syndrome (SARS) is a newly discovered disease caused by a novel coronavirus. The present study studied the longitudinal profile of antibodies against SARS-coronavirus (SARS-CoV) in SARS patients and evaluated the clinical significance of these antibodies. METHODS: Two methods, ELISA and indirect immunofluorescent assay, were used for the detection of the anti-SARS-CoV IgG and IgM in 335 serial sera from 98 SARS patients. In 18 patients, serum antibody profiles were investigated and antibody neutralization tests were performed from 7 to 720 days after the onset of symptoms. RESULTS: The ratios of positive IgG/IgM by ELISA were 0/0, 45.4/39.4, 88.6/71.4, 96/88, 100/48.6, 100/30.9, 100/17.1, 100/0 per cent, respectively, on 1-7, 8-14, 15-21, 22-28, 29-60, 61-90, 91-180 and 181-720 days after the onset of symptoms. Antibodies were not detected within the first 7 days of illness, but IgG titre increased dramatically on day 15, reaching a peak on day 60, and remained high until day 180 from when it declined gradually until day 720. IgM was detected on day 15 and rapidly reached a peak, then declined gradually until it was undetectable on day 180. Neutralizing viral antibodies were demonstrated in the convalescence sera from SARS patients. CONCLUSION: The persistence of detectable IgG antibodies and neutralizing viral antibodies for up to 720 days suggest that SARS patients may be protected from recurrent SARS-CoV infection for up to 2 years.
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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 | 0.002 |
| 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) | 0.001 | 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 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".