Altered processing of the neurotensin/neuromedin N precursor in PC2 knock down mice: a biochemical and immunohistochemical study
Bibliographic record
Abstract
Neurotensin (NT) and neuromedin N (NN) are generated by endoproteolytic cleavage of a common precursor molecule, pro-NT/NN. To gain insight into the role of prohormone convertases PC1, PC2, and PC7 in this process, we investigated the maturation of pro-NT/NN in the brain of PC7 (PC7-/-), PC2 (PC2-/-), and/or PC1 (PC1+/- and PC2-/-; PC1+/-) knock down mice. Inactivation of the PC7 gene was without effect, suggesting that this convertase is not involved in the processing of pro-NT/NN. By contrast, there was a 15% decrease in NT and a 50% decrease in NN levels, as measured by radioimmunoassay, in whole brain extracts from PC2 null as compared with wild type mice. Using immunohistochemistry, we found that this decrease in pro-NT/NN maturation products was uneven and that it was most pronounced in the medial preoptic area, lateral hypothalamus, and paraventricular hypothalamic nuclei. These results suggest that PC2 plays a critical role in the processing of pro-NT/NN in mouse brain and that its deficiency may be compensated to a regionally variable extent by other convertases. Previous data have suggested that PC1 might be subserving this role. However, there was no change in the maturation of pro-NT/NN in the brain of mice in which the PC1 gene had been partially inactivated, implying that complete PC1 knock down may be required for loss of function.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".