Histamine Compartments of the<i>Drosophila</i>Brain With an Estimate of the Quantum Content at the Photoreceptor Synapse
Bibliographic record
Abstract
Reliable estimates of the quantum size in histaminergic neurons are not available. We have exploited two unusual opportunities in the fly's (Drosophila melanogaster) visual system to make such determinations for histaminergic photoreceptor synapses: 1) the possibility to microdissect successively from whole fly heads freeze-dried in acetone: the compound eyes; the first optic neuropils, or lamina; and the rest of the brain; and 2) the uniform sheaves of lamina synaptic terminals of photoreceptors R1-R6. We used this organization to count scrupulously the numbers of 30-nm synaptic vesicles from electron micrographs of R1-R6 profiles, and from microdissections we determined the regional contents of histamine in the compound eye, lamina, and central brain. Total head histamine averages 1.98 ng of which 9% was lost after freeze-drying in acetone and a further 28% after the brain was microdissected. Of the remainder, 71% was in the eye and lamina. Assuming that histamine loss from the tissue occurred mostly by diffusion evenly distributed among all regions, the overall lamina content of the head would be 0.1935 ng before dissection. From published values for the volumes of the brain's compartments, the computed regional concentrations of histamine are highest in the lamina (4.35 mM) because of the terminals of R1-R6. The concentration in the retina is approximately 13% that in the lamina, suggesting that most histamine is vesicular. There are approximately 43,500 +/- 7,400 (SD) synaptic vesicles per terminal and, if all histamine is allocated equally and exclusively among these, the vesicle contents would be 858 +/- 304 x 10(-21) moles or approximately 5,000 +/- 1,800 (SD) molecules at an approximate concentration of 670 mM. These values are compared with the vesicle contents at synapses using acetylcholine and catecholamines.
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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 | 0.000 | 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) | 0.001 | 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".