Roxadustat (FG-4592) abated lipopolysaccharides-induced depressive-like symptoms via PI3K signaling
Bibliographic record
Abstract
Background: Despite its role in inflammation and the redox system under hypoxia, the effects and molecular mechanisms of hypoxia-inducible factor (HIF) in neuroinflammation-associated depression are poorly explored. Furthermore, Prolyl hydroxylase domain-containing proteins (PHDs) regulate HIF-1; however, whether and how PHDs regulate depressive-like behaviors under Lipopolysaccharides (LPS)-induced stress conditions remain covered. Methods: To highlight the roles and underlying mechanisms of PHDs-HIF-1 in depression, we employed behavioral, pharmacological, and biochemical analyses using the LPS-induced depression model. Results: Lipopolysaccharides treatment induced depressive-like behaviors, as we found, increased immobility and decreased sucrose preference in the mice. Concurrently, we examined increased cytokine levels, HIF-1 expression, mRNA levels of PHD1/PHD2, and neuroinflammation upon LPS administration, which Roxadustat reduced. Furthermore, the PI3K inhibitor wortmannin reversed Roxadustat-induced changes. Additionally, Roxadustat treatment attenuated LPS-induced synaptic impairment and improved spine numbers, ameliorated by wortmannin. Conclusion: PI3K signaling.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".