Tissue Distribution and Molecular Forms of a Novel Pituitary Protein in the Rat
Bibliographic record
Abstract
A sensitive and specific radioimmunoassay (RIA) was developed for a novel pituitary protein that we recently isolated from human and porcine pituitary gland and designated 7B2. By employing this RIA, we were able to detect and assay this novel protein in different rat tissue extracts. The concentrations of 7B2 in rat anterior pituitary lobe, neurointermediate lobe, hypothalamus, adrenal medulla and thyroid gland were 10,400 +/- 804; 6,190 +/- 908; 773 +/- 50; 697 +/- 83 and 1,368 +/- 116 pg/mg tissue (wet weight, n = 10, mean +/- SEM), respectively. However, the concentrations of 7B2 were lower than 30 pg/mg tissue in extracts of pancreas, ileum and colon, and were below the sensitivity of the RIA in extracts of liver, kidney, spleen, lung, adrenal cortex and testis. Gel permeation chromatography of extracts of anterior pituitary lobe, neurointermediate lobe, hypothalamus, adrenal medulla and thyroid gland on Sephadex G-100 revealed that most of the immunoreactive (Ir)-7B2 has an apparent molecular weight of 45,000-50,000. Subsequent dissociation of this Ir-7B2 by polyacrylamide gel electrophoresis containing sodium dodecyl sulfate (SDS) yielded an Ir-7B2 with an apparent molecular weight of around 19,000. In addition, high K+ concentration (50 mM) induced the release of Ir-7B2 from cultured cells of both rat anterior pituitary and neurointermediate lobe. Finally, Ir-7B2 was detected in the neurosecretory granule fraction prepared from porcine neurointermediate lobe. These results indicate that 7B2 may be a novel secretory protein in the pituitary gland.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".