From two to three dimensions: The importance of the third dimension for evaluating the limits to neuronal miniaturization in insects
Bibliographic record
Abstract
Abstract Most studies dealing with the limits to miniaturization in insect brains have until now relied on information based on data collected in two dimensions: either histological sections imaged by light microscopy, or electron micrographs of single ultrathin sections imaged by transmission electron microscopy (TEM). To test the validity of transferring information gained from two‐dimensional images to the third dimension, we examined a 3D image stack from serial‐section TEM (ssTEM) of the optic neuropiles of the miniature parasitic wasp Trichogramma brassicae (Bezdenko, 1968). We reinvestigated the proposed lower limit of 2 µm for the diameters of neuronal somata and found average volumes of 6.5 μm3 for lamina cells and 3.8 μm3 for medulla cells. We likewise found a limiting factor for the volume of nuclei, which averages 41.9% and 49.2% of the cell body volume, respectively, but that in turn the compactness of heterochromatin was not a limiting factor in the minimal volume of the nuclei. Finally, we also found a minimum axon diameter of 98 nm that could nevertheless accommodate axoplasmic mitochondria. Incorporating the third dimension thus proves critically important in avoiding volumetric misinterpretations of these values. We discuss the limitations of analyzing the effects of miniaturization from profile data of neurons and demonstrate that miniaturization within the nervous system can lie beyond previously described limits and in some cases is already present in the optic lobe neurons of T. brassicae.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".