Rescue of Neurons from Ischemic Injury by Peroxisome Proliferator-Activated Receptor-γ Requires a Novel Essential Cofactor LMO4
Bibliographic record
Abstract
Activation of peroxisome proliferator-activated receptor-gamma (PPARgamma) signaling after stroke may reduce brain injury, but this effect will depend on the levels of receptor and cofactors. Here, we showed that the direct effect of PPARgamma signaling to protect neurons from ischemic injury requires a novel cofactor LMO4, because this effect was lost in LMO4-null cortical neurons. PPARgamma agonist also failed to reduce cerebral infarction after transient focal ischemia in CaMKIIalphaCre/LMO4loxP mice with LMO4 ablated in neurons of the forebrain. Expressing LMO4 in LMO4-null cortical neurons rescued the PPARgamma-protective effect. PPARgamma signaling activates the promoter of the antioxidant gene SOD2 and this process requires LMO4. Addition of a superoxide dismutase mimetic MnTBAP [manganese(III)tetrakis(4-benzoic acid)porphyrin] bypassed the deficiency in PPARgamma signaling and was able to directly rescue LMO4-null cortical neurons from ischemic injury. Like LMO4, PPARgamma and PGC1alpha (PPARgamma coactivator 1alpha) levels in neurons are elevated by hypoxic stress, and absence of LMO4 impairs their upregulation. Coimmunoprecipitation and mammalian two-hybrid assays revealed that LMO4 interacts in a ligand-dependent manner with PPARgamma. LMO4 augments PPARgamma-dependent gene activation, in part, by promoting RXRalpha (retinoid X receptor-alpha) binding to PPARgamma and by increasing PPARgamma binding to its target DNA sequence. Together, our results identify LMO4 as an essential hypoxia-inducible cofactor required for PPARgamma signaling in neurons. Thus, upregulation of LMO4 expression after stroke is likely to be an important determinant of neuron survival.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".