Cross-talk between heme oxygenase and peroxisome proliferator-activated receptors in the regulation of physiological functions
Bibliographic record
Abstract
Peroxisome-proliferator-activated-receptors (PPARs) are transcription factors belonging to the superfamily of nuclear receptors. The isoforms of PPAR include PPAR alpha, PPAR gamma and PPAR delta (also known as PPAR beta). Generally, PPARs potentiate insulin sensitivity, improve glucose/lipid metabolism, suppress inflammation/oxidative stress, attenuate excessive immune responses, regulate cell-growth and differentiation. Interestingly, agonists of PPAR gamma and PPAR alpha have been shown to upregulate the heme-oxygenase (HO)-system. Conversely, the HO-system also enhances PPAR alpha, and potentiates the expression and activity of PPAR gamma. Moreover, the HO-system and related products including bilirubin, biliverdin, carbon monoxide and ferritin have been shown to increase insulin sensitivity, improve glucose/lipid metabolism, suppress inflammation/oxidative stress, abate immune response, and modulate cell-growth/differentiation. Therefore, an intimate, reciprocal, stimulatory and synergistic relationship between PPAR-signaling and the HO-system can be envisaged in the regulation of physiological functions. Thus, both the HO-system and PPARs-signaling participate in fine-tuning similar physiological functions, so novel pharmacological agents capable of optimizing this interaction should be sought. The coordinated regulation of PPAR-signaling and the HO-system may constitute the basis for future drug design.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".