Examination of BDNF Treatment on BACE1 Activity and Acute Exercise on Brain BDNF Signaling
Bibliographic record
Abstract
Perturbations in metabolism results in the accumulation of beta-amyloid peptides, which is a pathological feature of Alzheimer’s disease. Beta-site amyloid precursor protein cleaving enzyme 1 (BACE1) is the rate limiting enzyme responsible for beta-amyloid production. Obesogenic diets increase BACE1 while exercise reduces BACE1 activity, although the mechanisms are unknown. Brain-derived neurotropic factor (BDNF) is an exercise inducible neurotrophic factor, however, it is unknown if BDNF is related to the effects of exercise on BACE1. The purpose of this study was to determine the direct effect of BDNF on BACE1 activity and to examine neuronal pathways induced by exercise. C57BL/6J male mice were assigned to either a low ( n = 36) or high fat diet ( n = 36) for 10 weeks. To determine the direct effect of BDNF on BACE1, a subset of mice (low fat diet = 12 and high fat diet n = 12) were used for an explant experiment where the brain tissue was directly treated with BDNF (100 ng/ml) for 30 min. To examine neuronal pathways activated with exercise, mice remained sedentary ( n = 12) or underwent an acute bout of treadmill running at 15 m/min with a 5% incline for 120 min ( n = 12). The prefrontal cortex and hippocampus were collected 2-h post-exercise. Direct treatment with BDNF resulted in reductions in BACE1 activity in the prefrontal cortex ( p < 0.05), but not the hippocampus. The high fat diet reduced BDNF content in the hippocampus; however, the acute bout of exercise increased BDNF in the prefrontal cortex ( p < 0.05). These novel findings demonstrate the region specific differences in exercise induced BDNF in lean and obese mice and show that BDNF can reduce BACE1 activity, independent of other exercise-induced alterations. This work demonstrates a previously unknown link between BDNF and BACE1 regulation.
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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) | 0.001 | 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 | 0.002 |
| 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".