Comparative fine structural distribution of endopeptidase 24.15 (EC3.4.24.15) and 24.16 (EC3.4.24.16) in rat brain
Bibliographic record
Abstract
Endopeptidase 24.15 (EP24.15) and 24.16 (EP24.16) are closely related metalloendopeptidases implicated in the metabolism of several neuropeptides and widely expressed in mammalian brain. To gain insight into the functional role of these two enzymes in the central nervous system, we examined their cellular and subcellular distribution in rat brain by using electron microscopic immunogold labeling. In all areas examined, EP24.15 and EP24.16 immunoreactivity were observed in selective subpopulations of neuronal and glial cells. Subcellular localization of EP24.15 in neurons revealed that this enzyme was predominantly concentrated in the nucleus, whereas EP24.16 was almost exclusively cytoplasmic. The amount of EP24.15 found in the nucleus was inversely correlated with that found in the cytoplasm, suggesting that the enzyme could be mobilized from one compartment to the other. Within the cytoplasm, EP24.15 and EP24.16 immunoreactivity showed comparable distributional patterns. Both enzymes were detected throughout perikarya and dendrites, as well as within axons and axon terminals. In all neuronal compartments, EP24.15 and EP24.16 showed a major association with membranes of neurosecretory elements, including Golgi cisternae, tubulovesicular organelles, synaptic vesicles, and endosomes. However, whereas EP24.15 always faced the cytoplasmic face of the membranes, EP24.16 was observed on both cytoplasmic and luminal sides, suggesting that the latter was more likely to contribute to the processing of peptides or to the degradation of internalized ligands. Taken together, the present results suggest that EP24.15 could play a major role in the hydrolysis of intranuclear substrates, whereas EP24.16 would be predominantly involved in the processing and inactivation of signaling peptides.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".