Effects of development and iron status on ceruloplasmin expression in rat brain
Bibliographic record
Abstract
The increased iron content in the brain of subjects with aceruloplasminemia has implicated ceruloplasmin (CP) as a major factor in the regulation of regional brain iron content. In this study, we investigated the effects of age and iron on CP expression in rat brain. In all four regions, the iron concentrations increased with developmental age. There is a similar trend in age-induced changes in CP mRNA and protein. The CP mRNA and protein levels were both lowest at postnatal day (PND) 7. The expression increased gradually with age, reaching the highest at PND196 in the striatum and substantia nigra, and at PND21 and PND63 in the cortex and hippocampus, respectively. This suggests the existence of an age-dependent pre-transcriptional regulation and a regionally specific effect of age on CP expression in the brain. Although total iron in all four regions was significantly lower in the rats fed with a low-iron diet for 6 weeks and higher in the rats with a high-iron diet than those in the control animals, no significant between-group differences in CP mRNA and protein were found in these animals, except in the substantia nigra where a significant increase in CP protein in high-iron rats was observed, and the reverse in low-iron rats. These findings suggested that the effects of iron on CP expression in the brain may be region-specific, and that regulation of CP expression by iron in the substantia nigra was at the post-transcriptional level.
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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 | 0.001 | 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".