Third COVID-19 vaccine dose boosts antibody function in Rwandans with high HIV viral load
Bibliographic record
Abstract
SARS-CoV-2 (severe acute respiratory syndrome coronavirus 2) causing COVID-19 (coronavirus disease 2019) poses a greater health risk to immunocompromized individuals including people living with HIV (PLWH). However, most studies on PLWH have been conducted in higher-income countries. We investigated the post-vaccination antibody responses of PLWH in Rwanda by collecting peripheral blood from participants after receiving a second or third COVID-19 vaccine. Virus-binding antibodies as well as antibody neutralization ability against all major SARS-CoV-2 variants of concern were analyzed. We found that people with high HIV viral loads and two COVID-19 vaccine doses had lower levels of binding antibodies that were less virus neutralizing and less cross-reactive compared to control groups. A third vaccination increased neutralizing antibody titers. Our data suggest that people with high HIV viral loads require a third dose of vaccine to neutralize SARS-CoV-2 virus and new variants as they emerge.
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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 | 0.001 |
| 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".