Platelets: bridging hemostasis, inflammation, and immunity
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
Although the function of platelets in the maintenance of hemostasis has been studied in great detail, more recent evidence has highlighted a central role for platelets in the host inflammatory and immune responses. Platelets by virtue of their large numbers and their ability to rapidly release a broad spectrum of immunomodulatory cytokines, chemokines, and other mediators act as circulating sentinels. Upon detection of a pathogen, platelets quickly activate and begin to drive the ensuing inflammatory response. Platelets have the ability to directly modulate the activity of neutrophils (phagocytosis, oxidative burst), endothelium (adhesion molecule and chemokine expression), and lymphocytes. Due to their diverse array of adhesion molecules and preformed chemokines, platelets are able to adhere to leukocytes and facilitate their recruitment to sites of tissue damage or infection. Furthermore, platelets directly participate in the capture and sequestration of pathogens within the vasculature. Platelet-neutrophil interactions are known to induce the release of neutrophil extracellular traps (NETs) in response to either bacterial or viral infection, and platelets have been shown to internalize pathogens, sequestering them in engulfment vacuoles. Finally, emerging data indicate that platelets also participate in the host immune response by directly killing infected cells. This review will highlight the central role platelets play in the initiation and modulation of the host inflammatory and immune responses.
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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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 it