Human Neutrophils as a Source of Nociceptin: A Novel Link between Pain and Inflammation<sup>,</sup>
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
Nociceptin is a neuropeptide sharing sequence homology with classical opioid peptides but with a distinct pharmacological profile. Through activation of its receptor, NociR, nociceptin has been linked with several physiological functions in the central nervous system including memory, locomotion, and processing of pain signals. Recently, peripheral blood neutrophils (PMNs) were demonstrated to express a functional NociR, a result suggesting that additional functions of the neuropeptide remain to be elucidated. The present study investigated the possibility that PMNs may be a source of nociceptin and whether the neuropeptide elicits PMN early responses. We observed the presence of nociceptin in the synovial fluids from arthritic patients, an inflammatory milieu typically containing high numbers of PMNs. In addition, freshly isolated PMNs were found to express and secrete nociceptin following degranulation, identifying these inflammatory cells as a novel source of the neuropeptide. Incubation of PMNs with nociceptin elicited a specific pattern of cellular protein phosphorylation on tyrosine residues in a rapid and transient fashion. Moreover, nociceptin prevented intracellular accumulation of cAMP in fMLP-stimulated PMNs, an effect mimicked by the specific NociR synthetic agonist, Ro 64-6198. Taken together, these results show that nociceptin/NociR is present and functional in human neutrophils, and the results identify a novel dialogue pathway between neural and immune tissues.
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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