Absence of the bile acid enzyme CYP8B1 increases brain chenodeoxycholic acid and reduces neuronal excitotoxicity in mice
Bibliographic record
Abstract
Abstract Background Bile acids (BAs), which act in the liver-brain axis, are liver-derived signaling molecules found in the brain. However, how they modulate neurological function remains largely unknown. Methods To assess the role of BAs in the brain, we generated mice with absent 12α-hydroxylase ( Cyp8b1 ), a BA synthesis enzyme, and determined if brain BA levels were altered in these mice, and if and how this may modulate neuronal function. Results The absence of CYP8B1 increased brain levels of the primary BA chenodeoxycholic acid (CDCA), and decreased ischemic stroke infarct area. Furthermore, CDCA administration reduced ischemic stroke lesion area in wild-type mice. Excitotoxicity due to elevated extra-cellular glutamate contributes to neuronal death in ischemic stroke. Neurons from Cyp8b1 -/- mice showed reduced susceptibility to glutamate-induced toxicity, and exogenous CDCA reduced glutamate-induced toxicity in neurons from wild-type mice. These data suggest that CDCA-mediated decreases in excitotoxic neuronal death contributes to the reduced stroke lesion area in Cyp8b1 -/- mice. Aberrant N-methyl-D-aspartate receptor (NMDAR) over-activation contributes to excitotoxicity. CDCA decreased NMDAR-mediated excitatory post-synaptic currents (EPSCs) in wild-type brain slices, by reducing over-activation of the NMDAR subunit GluN2B. In line with this, synaptic NMDAR activity was also decreased in Cyp8b1 -/- brain slices. Expression level and synaptic distribution of GluN2B were unaltered in Cyp8b1 -/- mice, suggesting that CDCA may directly antagonize GluN2B-containing NMDARs. Conclusions Our data suggests that CDCA acts in the liver-brain axis and decreases the aberrant over-activation of neuronal GluN2B-containing NMDARs, contributing to neuroprotection.
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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) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".