Acute exercise induced BDNF-TrkB signalling is intact in the prefrontal cortex of obese, glucose-intolerant male mice
Bibliographic record
Abstract
Obesity and glucose intolerance have been directly implicated in the pathology of Alzheimer's disease. It is thought that diet-induced obesity causes a reduction in neuronal plasticity through a reduction in the neurotrophin: brain-derived neurotrophic factor (BDNF). Previous work has demonstrated that acute exercise in healthy lean animals increases BDNF-TrkB signalling in the brain. However, if this effect is intact in a state of obesity remains unknown. The purpose of this study is to determine the effects of a single bout of exercise on BDNF-TrkB signalling in the prefrontal cortex and hippocampus from obese glucose intolerant mice. Male C57BL/6 mice were fed a low-fat diet (10% kcals from lard) or a high-fat diet (HFD, 60% kcals from lard) for 7 weeks. A subset of HFD mice underwent an acute bout of exercise (treadmill running: 15 m/min, 5% incline, 120 min) followed by a recovery period of 2 h, after which point the prefrontal cortex and hippocampus were collected. The HFD increased body mass and glucose intolerance (p < 0.05). Prefrontal cortex from HFD mice demonstrated lower BDNF protein content, reduced phosphorylation of the BDNF receptor (TrkB), and its downstream effector cAMP response element-binding protein (CREB), as well as PGC-1α and ERα) protein content (p < 0.05). Two hours following the acute exercise bout, TrkB and CREB phosphorylation as well as PGC-1α and ER-α protein content were recovered (p < 0.05). Our findings demonstrate for the first time that an acute bout of exercise can recover BDNF-TrkB signalling in the prefrontal cortex of obese mice.
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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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".