Vasoactive intestinal peptide 10-28 enhances natural killer cell cytotoxicity (134.84)
Bibliographic record
Abstract
Abstract Objective: Vasoactive intestinal peptide (VIP) and its synthetic analog VIP14-28 enhance NK cytotoxicity. This prompted us to study interaction of the naturally occurring peptide and orphan ligand VIP 10-28 with NK. Results: VIP10-28 stimulation (10-8-10-10 M, 30 min.) increased NK-92 cytotoxicity against K562 max. from 52% +/-2.6% SEM (control) to 68% +/-2.6% SEM (E:T 1:1), similar to long-term IL-2 stimulated NK from different donors (4/6), max. from 38% +/-4.2 SEM (control) to 51% +/-0.9% SEM (E:T 1:1). VIP10-28 did not seem to induce degranulation, since granzyme B levels remained unchanged in NK-92. However, stimulation with 10-8-10-10 M VIP10-28 for 5- 60 min. significantly induced tyrosine phosphorylation with ERK identified as one of the stimulated kinases. We used Informational Spectrum Method (ISM) to predict VIP10-28 NK receptor interactions. ISM results suggested potential binding of VIP10-28 to LFA-1α (F = 0.03, peptide residues 16-24) and with lower affinity to CD44 or MAC-1, but unlikely to NKG2D, -C, -A, NKp30, -44, -46, CD56, CD94, KIR2DL4, NKR-P1, CD45 or VIP receptors VPAC-1/ VPAC-2. Conclusion: The neuroendocrine peptide VIP10-28 induces increased NK cytotoxicity potentially through LFA-1 signaling pathways involving tyrosine kinase activation of ERK kinases.
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.
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) | 0.004 | 0.001 |
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".