No evidence of a link between influenza vaccines and Guillain–Barre syndrome–associated antiganglioside antibodies
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: Guillain-Barre syndrome (GBS) is a rare autoimmune disease characterized by acute, progressive peripheral neuropathy and is commonly associated with the presence of antiganglioside antibodies. Previously, influenza vaccination was linked with the increased incidence of GBS; however, whether antiganglioside antibodies are subsequently induced remains unresolved. METHODS: Sera from human subjects vaccinated with seasonal influenza vaccines from the 2007-2008, 2008-2009, or 1976-1977 influenza seasons were screened for the induction of immunity to influenza and the presence of antiganglioside antibodies pre- and post-vaccination. Likewise, sera from mice vaccinated with seasonal influenza vaccines (1988-1989, 2007-2008) or "swine flu" pandemic vaccines (1976, 2009) were assessed in the same manner. Viruses were also screened for cross-reacting ganglioside epitopes. RESULTS: Antiganglioside antibodies were found to recognize influenza viruses; this reactivity correlated with virus glycosylation. Antibodies to influenza viruses were detected in human and mouse sera, but the prevalence of antiganglioside antibodies was extremely low. CONCLUSIONS: Although the correlation between antiganglioside antibody cross-reactivity and glycosylation of viruses suggests the role of shared carbohydrate epitopes, no correlation was observed between hemagglutinin-inhibition titers and the induction of antiganglioside antibodies after influenza vaccination.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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) | 0.000 | 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 it