Influenza virus H1N1 activates platelets through FcγRIIA signaling and thrombin generation
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
Platelets play crucial functions in hemostasis and the prevention of bleeding. During H1N1 influenza A virus infection, platelets display activation markers. The platelet activation triggers during H1N1 infection remain elusive. We observed that H1N1 induces surface receptor activation, lipid mediator synthesis, and release of microparticles from platelets. These activation processes require the presence of serum/plasma, pointing to the contribution of soluble factor(s). Considering that immune complexes in the H1N1 pandemic were reported to play a pathogenic role, we assessed their contribution in H1N1-induced platelet activation. In influenza-immunized subjects, we observed that the virus scaffolds with immunoglobulin G (IgG) to form immune complexes that promote platelet activation. Mechanistically, this activation occurs through stimulation of low-affinity type 2 receptor for Fc portion of IgG (FcγRIIA), a receptor for immune complexes, independently of thrombin. Using a combination of in vitro and in vivo approaches, we found that the antibodies from H3N2-immunized mice activate transgenic mouse platelets that express FcγRIIA when put in the presence of H1N1, suggesting that cross-reacting influenza antibodies suffice. Alternatively, H1N1 can activate platelets via thrombin formation, independently of complement and FcγRIIA. These observations identify both the adaptive immune response and the innate response against pathogens as 2 intertwined processes that activate platelets during influenza infections.
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) | 0.000 | 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) | 0.000 | 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