Irisin Exerts Neuroprotective Effects on Cultured Neurons by Regulating Astrocytes
Bibliographic record
Abstract
Neurons suffer detrimental effects from β-amyloid toxicity in Alzheimer’s disease. The exercise hormone, irisin, is found to induce a neuroprotective gene program and facilitates the beneficial effects on cognitive function. But no effort is made to test its direct protective effects on neurons against the Aβ-induced cell toxicity so far. In the present study, we investigated whether irisin could protect neurons against Aβ- (25–35) induced cell damage and explored the possible underlying mechanisms. Primary cell cultures of astrocytes and neurons were established. Conditioned medium from astrocyte was collected for the treatment and biochemistry assay study. To explore the protein expression changes, Western blot and ELISA assays were used in these in vitro cell culture models. Exposure of hippocampal neurons to 10 μM Aβ (25–35) caused significant reduction on cell viability, and the toxic effect was not significantly reduced by the coadministration of irisin. However, pretreated astrocyte-conditioned medium with irisin for 12 hours notably protected the neurons from the toxicity of Aβ. Also, we found that irisin could attenuate the release of IL-6 and IL-1β from cultured astrocytes and decrease the expression level of COX-2 and phosphorylation of AKT. Last, we found that irisin could reduce NFκB activation in astrocyte exposed to Aβ by preventing the phosphorylation and the loss of IκBα. Our finding may provide novel evidence for the future application of irisin in the treatment of Alzheimer’s disease and the memory dysfunction in diabetes mellitus.
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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) | 0.000 | 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 | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".