Glutamate formation via the leucine-to-glutamate pathway of rat pancreas
Bibliographic record
Abstract
The leucine-to-glutamate (Leu→Glu) pathway, which metabolizes the carbon atoms of l-leucine to form l-glutamate, was studied by incubation of rat tissue segments with l-[U-(14)C]leucine and estimation of the [(14)C]glutamate formed. Metabolism of the leucine carbon chain occurs in most rat tissues, but maximal activity of the Leu→Glu pathway for glutamate formation is limited to the thoracic aorta and pancreas. In rat aorta, the Leu→Glu pathway functions to relax the underlying smooth muscle; its functions in the pancreas are unknown. This report characterizes the Leu→Glu pathway of rat pancreas and develops methods to examine its functions. Pancreatic segments effect net formation of glutamate on incubation with l-leucine, l-glutamine, or a mix of 18 other plasma amino acids at their concentrations in normal rat plasma. Glutamate formed from leucine remains mainly in the tissue, whereas that from glutamine enters the medium. The pancreatic Leu→Glu pathway uses the leucine carbons for net glutamate formation; the α-amino group is not used; the stoichiometry is as follows: 1 mol of leucine yields 2 mol of glutamate (2 leucine carbons per glutamate) plus 2 mol of CO2. Comparison of the Leu→Glu pathway in preparations of whole pancreatic segments, isolated acini, and islets of Langerhans localizes it in the acini; relatively high activity is found in cultures of the AR42J cell line and very little in the INS-1 832/13 cell line. Pancreatic tissue glutamate concentration is homeostatically regulated in the range of ∼1-3 μmol/g wet wt. l-Valine and leucine ethyl, benzyl, and tert-butyl esters inhibit the Leu→Glu pathway without decreasing tissue total glutamate.
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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".