The neuroendocrine phenotype, cellular plasticity, and the search for genetic switches: redefining the diffuse neuroendocrine system.
Bibliographic record
Abstract
The term neuroendocrine has been used to define cells that secrete their products in a regulated manner, in response to a specific stimulus. The neuroendocrine system includes neurons and endocrine cells sharing a common phenotypic program characterized by the expression of markers such as neuropeptides, chromogranins, neuropeptide processing enzymes SPC2 and SPC3 (subtilase-like pro-protein convertases) or dense core secretory granules. Various theories such as the APUD (amine precursor uptake decarboxylation) concept, the diffuse neuroendocrine system (DNES) or the paraneuron concept have been put forth to classify neuroendocrine cells as a cohesive group. Neuroendocrine characteristics have been used as evidence of a common embryological origin for normal and neoplastic cells. However, it is now recognized that neuroendocrine characteristics can be observed in various cell types, such as immunocytes, that are not of a common embryological origin with either neurons or endocrine cells. We propose to redefine previous "neuroendocrine" concepts to include the notion that activation of specific genetic switches can lead to the expression of a partial or full neuroendocrine phenotype in a variety of cell types, including immune cells.
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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 | 0.001 | 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 | 0.004 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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 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".