Inositol Stereoisomers Stabilize an Oligomeric Aggregate of Alzheimer Amyloid β Peptide and Inhibit Aβ-induced Toxicity
Bibliographic record
Abstract
Inositol has 8 stereoisomers, four of which are physiologically active. myo-Inositol is the most abundant isomer in the brain and more recently shown that epi- and scyllo-inositol are also present. myo-Inositol complexes with Abeta42 in vitro to form a small stable micelle. The ability of inositol stereoisomers to interact with and stabilize small Abeta complexes was addressed. Circular dichroism spectroscopy demonstrated that epi- and scyllo- but not chiro-inositol were able to induce a structural transition from random to beta-structure in Abeta42. Alternatively, none of the stereoisomers were able to induce a structural transition in Abeta40. Electron microscopy demonstrated that inositol stabilizes small aggregates of Abeta42. We demonstrate that inositol-Abeta interactions result in a complex that is non-toxic to nerve growth factor-differentiated PC-12 cells and primary human neuronal cultures. The attenuation of toxicity is the result of Abeta-inositol interaction, as inositol uptake inhibitors had no effect on neuronal survival. The use of inositol stereoisomers allowed us to elucidate an important structure-activity relationship between Abeta and inositol. Inositol stereoisomers are naturally occurring molecules that readily cross the blood-brain barrier and may represent a viable treatment for AD through the complexation of Abeta and attenuation of Abeta neurotoxic effects.
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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) | 0.001 | 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 | 0.000 |
| 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 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".