On Cotransmission & Neurotransmitter Phenotype Plasticity
Bibliographic record
Abstract
Most neurons in the nervous system appear to contain and release more than one chemical acting as a neurotransmitter or neuromodulator. Cotransmission can therefore be considered the rule rather than the exception. Indeed, cotransmission of a classical neurotransmitter and a peptide is a ubiquitous phenomenon, but several neuron types can also contain more than one classical neurotransmitter [glutamate, gamma-amino butyric acid (GABA), acetylcholine, dopamine, etc.]. Although the expression of peptide cotransmitters is known to be highly regulated in response to various physiological, chemical and pathological signals, new data now suggest that a similar situation prevails in neurons that co-release two classical transmitters. In this review we will consider a number of recently described examples of cotransmission implicating more than one classical neurotransmitter. We will also consider new data showing that during development and later in adulthood, as well as in the context of disease, the neurotransmitter phenotype of neurons can be highly plastic as revealed by changes in the expression of neurotransmitter synthesis enzymes and vesicular neurotransmitter transporters.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.005 |
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".