Effect of apoptotic proteins on function of rat vasopressin-and dopaminergic hypothalamic neurons
Bibliographic record
Abstract
To study character of effect of apoptosis signal proteins on activities of neurosecretory cells and neurons of rat hypothalamus, pharmacologic inhibitors of proapoptotic protein p53 Pifithrin-alpha and antiapoptotic protein Bcl-2 HA14-1 were injected into the hypothalamus. Activation of vasopressinergic neurosecretory cells at administration of the blocker Bcl-2 HA14-1 was shown: there were observed an increase of vasopressin mRNA in neurons of hypothalamus supraoptical and paraventricular nuclei, a decrease of the immunoreactive vasopressin content in posterior pituitary, and reduction of diuresis. Inactivation of p53 inhibited release of vasopressin from hypothalamus cell bodies, which is indicated by an elevated content of immunoreactive vasopressin in neurosecretory cell bodies with its unchanged synthesis, a decrease of the neurohormone content in the posterior pituitary, and an increase of diuresis rate. Activation of vasopressinergic neurons of the suprachiasmatic nucleus was also shown. Administration of the blocker Bcl-2 has been revealed to decrease functional activity both of dopaminergic neurons (Zona Incerta) and of dopaminergic neurosecretory cells (arcuate nucleus), in which a decrease of the tyrosine hydroxylase content was observed. The p53 inactivation also led to a decrease of activity of dopaminergic neurosecretory cells of arcuate nucleus, whereas activity of the proteins Zone Incerta did not change. Thus, it has been shown that a change of the apoptotic protein content in vasopressinergic and dopaminergic neurons and neurosecretory cells leads to a change of their functional activity, the character and possibly mechanisms of effects of apoptotic proteins on activities of vasopressin- and dopaminergic cells being different.
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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 | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".