Influence of metabolic stress and metformin on synaptic protein profile in SH‐SY5Y‐derived neurons
Bibliographic record
Abstract
Insulin resistance (IR) is associated with reductions in neuronal proteins often observed with Alzheimer's disease (AD), however, the mechanisms through which IR promotes neurodegeneration/AD pathogenesis are poorly understood. Metformin (MET), a potent activator of the metabolic regulator AMPK is used to treat IR but its effectiveness for AD is unclear. We have previously shown that chronic AMPK activation impairs neurite growth and protein synthesis in SH-SY5Y neurons, however, AMPK activation in IR was not explored. Therefore, we examined the effects of MET-driven AMPK activation with and without IR. Retinoic acid-differentiated SH-SY5Y neurons were treated with: (1) Ctl: 24 h vehicle followed by 24 h Vehicle; (2) HI: 100 nM insulin (24 h HI followed by 24 h HI); or (3) MET: 24 h vehicle followed by 24 h 2 mM metformin; (4) HI/MET: 24 h 100 nM insulin followed by 24 h 100 nM INS+2 mM MET. INS and INS/MET groups saw impairments in markers of insulin signaling (Akt S473, mTOR S2448, p70s6k T389, and IRS-1S636) demonstrating IR was not recovered with MET treatment. All treatment groups showed reductions in neuronal markers (post-synaptic marker HOMER1 mRNA content and synapse marker synaptophysin protein content). INS and MET treatments showed a reduction in the content of the mature neuronal marker NeuN that was prevented by INS/MET. Similarly, increases in cell size/area, neurite length/area observed with INS and MET, were prevented with INS/MET. These findings indicate that IR and MET impair neuronal markers through distinct pathways and suggest that MET is ineffective in treating IR-driven impairments in neurons.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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) | 0.000 | 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 teacher head, 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".