Daily variation in the distribution of glycogen phosphorylase in the suprachiasmatic nucleus of Syrian hamsters
Bibliographic record
Abstract
Dynamic changes in astrocytic processes in the Syrian hamster suprachiasmatic nucleus (SCN) have been reported with maximal process extension in the light phase and maximal process retraction in the dark phase of a daily light:dark cycle. In the present study, we asked whether dynamic changes occur in the distribution of an astrocytic metabolic marker, glycogen phosphorylase (GP), using a histochemical assay to reveal the distribution of both active and total GP, in the hamster SCN. Changes in glial acidic fibrillary protein (GFAP) immunoreactivity also were assessed using a relative optical density measure (ROD). We observed changes in the localization and distribution of GP both in the SCN and in the paraventricular nucleus of the hypothalamus (PVN) as a function of time of day. In the light phase, there were concentrated, large, dot-like deposits of GP throughout the SCN and PVN on an empty background. In the dark phase, diffuse, small, granular particles were seen throughout both nuclei. Selectively, in the dark-phase SCN, these granular particles formed a rim of intense GP reactivity on the lateral, ventral, posterior, and medial borders. Significantly higher levels of GP reactivity were seen in anterior sections of the medial optic chiasm in the light phase. GFAP-immunoreactive astrocytic processes had higher ROD levels in the dark phase. In conclusion, the astrocytic metabolic marker, GP, exhibits a significant daily variation in localization in both the SCN and the PVN that correlates with dynamic changes in the distribution of astrocytic processes in the SCN. Increased GP activity also occurs in astrocytes among optic fibers subjacent to the SCN during light input.
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) | 0.000 | 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 | 0.000 |
| 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".