Protocol for Exploring the Role of Irisin in the Enhancement of Spatial Learning Mediated by Aerobic Physical Exercise in Adult Mice
Bibliographic record
Abstract
Introduction: Age-related cognitive decline decreases with aerobic physical exercise in many animal models and humans. Irisin, a myokine and its’ precursor FNDC5, has increased hippocampal development to improve learning and memory. This study aims to determine the association between irisin, physical activity and enhancement of spatial learning in adult mice. Methods: Three experimental studies will be conducted to explore the role of FNDC5/irisin in spatial learning. Study 1 will test the spatial learning ability in C57BL/6 mice using Morris Water Maze (MWM) task in WT, FNDC5+/- and FNDC5-/- mice strains. Study 2 will test the changes in the MWM task due to exogenous administration of FNDC5/irisin in the hippocampus, specifically in the dentate gyrus region. Study 3 aims to test the effect of aerobic physical activity on irisin levels in the dentate gyrus region and the changes in the MWM task. Anticipated Results: Study 1 results are expected to show that WT mice perform better compared to the FNDC5+/- and FNDC5-/- in completing the MWM task. Study 2 is anticipated to show that hippocampal administration of FNDC5/irisin can rescue the spatial learning phenotype. Study 3 is expected to show that PE improves spatial learning in all mice strains by regulating FNDC5/irisin levels. Discussion: FNDC5/irisin play a role in enhancing neurogenesis and synaptic plasticity by regulating downstream signalling pathways that are involved in cognitive functions. Aerobic PE enhances this mechanism, resulting in improved spatial learning. Conclusion: Aerobic PE is expected to significantly regulates hippocampal FNDC5/irisin, which is associated with enhancing spatial learning and cognitive functions.
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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 | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.033 | 0.011 |
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".