Antibody dependent disease enhancement (ADE) after COVID-19 vaccination and beta glucans as a safer strategy in management
Bibliographic record
Abstract
A potential risk associated with vaccines for COVID-19 is antibody-dependent disease enhancement (ADE) in which vaccine induced antibody mediated immune responses may lead to enhanced SARS CoV- 2 acquisition or increased disease severity. Though ADE has not been clinically demonstrated with any of the COVID-19 vaccines so far, when neutralizing antibodies are suboptimal, the severity of COVID-19 has been reported to be greater. ADE is presumed to occur via abnormal macrophages induced by the vaccine based immune response by antibody-mediated virus uptake into Fc gamma receptor IIa (FcγRIIa) or by the formation of Fc-mediated excessive antibody effector functions. Beta-glucans which are naturally occurring polysaccharides known for unique immunomodulation by capability to interact with macrophages, eliciting a specific beneficial immune-response and enhancing all arms of the immune system, importantly without over-activation are suggested as safer nutritional supplement-based vaccine adjuvants for COVID-19.
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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 | 0.000 |
| 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) | 0.002 | 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".