Modulation of neutrophil function by the tripeptide feG
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: Neutrophils are critical in the defense against potentially harmful microorganisms, but their excessive and inappropriate activation can contribute significantly to tissue damage and a worsening pathology. Through the release of endocrine factors submandibular glands contribute to achieving a balance in neutrophil function by modulating the state of activation and migratory potential of circulating neutrophils. A putative hormonal candidate for these effects on neutrophils was identified as a heptapeptide named submandibular gland peptide T (SGP-T; sequence = TDIFEGG). Since the tripeptide FEG, derived from SGP-T, and its D-amino acid analogue feG had similar inhibitory effects on inflammatory reactions, we investigated the effects of feG on human and rat neutrophil function. RESULTS: With human neutrophils feG had no discernible effect on oxidative burst or phagocytosis, but in picomolar amounts it reduced PAF-induced neutrophil movement and adhesion, and the binding of CD11b by 34% and that of CD16b close to control values. In the rat feG (10-11M) reduced the binding of CD11b and CD16 antibodies to PAF-stimulated circulating neutrophils by 35% and 43%, respectively, and at 100 micrograms/kilograms intraperitoneally feG reduced neutrophil in vivo migration by 40%. With ovalbumin-sensitized rats that were challenged with antigen, feG inhibited binding of antibodies against CD16b but not CD11b, on peritoneal leukocytes. CONCLUSIONS: The inhibitory effect of feG on neutrophil movement may be mediated by alterations in the co-stimulatory molecules CD11b and CD16.
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 | 0.000 |
| 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 | 0.000 |
| 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