Oral (−)-Epicatechin Inhibits Progressive Tau Pathology in rTg4510 Mice Independent of Direct Actions at GSK3β
Bibliographic record
Abstract
but display poor bioavailability and low potency, challenging their therapeutic translation. We previously reported that oral administration of the flavonoid (-)-epicatechin (EC) reduced Amyloid-β (Aβ) plaque pathology in APP/PS1 transgenic mice. Here, we investigated whether EC impacts on tau pathology, independent of actions on Aβ, using rTg4510 mice expressing P301L mutant tau. 4 and 6.5 months old rTg4510 mice received EC (∼18 mg/day) or vehicle (ethanol) via drinking water for 21 days and the levels of total and phosphorylated tau were assessed. At 4 months, tau appeared as two bands of ∼55 kDa, phosphorylated at Ser262 and Ser396 and was unaffected by exposure to EC. At 6.5 months an additional higher molecular weight form of tau was detected at ∼64 kDa which was phosphorylated at Ser262, Ser396 and additionally at the AT8 sites, indicative of the presence of PHFs. EC consumption reduced the levels of the ∼64 kDa tau species and inhibited phosphorylation at Ser262 and AT8 phosphoepitopes. Regulation of the key tau kinase glycogen synthase kinase 3β (GSK3β) by phosphorylation at Ser9 was not altered by exposure to EC in mice or primary neurons. Furthermore, EC did not significantly inhibit GSK3β activity at physiologically-relevant concentrations in a cell free assay. Therefore, a 21-day intervention with EC inhibits or reverses the development of tau pathology in rTg4510 mice independently of direct inhibition of GSK3β.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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 | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".