Secreted amyloid precursor protein alpha as a therapeutic for insulin signaling dysfunction in the nervous system
Bibliographic record
Abstract
Background: The amyloid precursor protein (APP) cleavage product secreted amyloid precursor protein alpha (sAPPα) is a neurotrophic factor demonstrated to be protective to neurons. Despite evidence that sAPPα activates the insulin signaling ,the effects of sAPPα on diabetes-induced pathology are unknown. Hypothesis: We hypothesized that sAPPα could inhibit neuronal dysfunction in an animal model of diabetes. This hypothesis was tested in 3 aims. AIM 1: To determine if sAPPα could inhibit the development of Alzheimer’s-like pathology in diabetic brain tissue. AIM 2: To examine if sAPPα could slow the development of diabetes-induced peripheral neuropathy. AIM 3: In our final aim, we examined the effects of sAPPα overexpressing neural stem cells (sAPPα-NSCs) engrafted into the hippocampi on Morris water maze (MWM) performance of healthy mice. Results: Analysis of brain tissue from diabetic sAPPα mice revealed that sAPPα blocked the development of Alzheimer’s-like pathology in the form of aberrant tau phosphorylation. Additionally, sAPPα decreased diabetes-induced activation of the unfolded protein response (UPR), a sign that diabetic sAPPα mice maintained better overall brain health compared to diabetic controls. We found that sAPPα slowed the development of diabetes-induced thermal hypoalgesia, an indicator of sensory neuropathy, in our model. Cell culture experiments demonstrated that the neurotrophic effects of sAPPα in the PNS are associated with up-regulation of the neuroprotective transcription factor NFκB and increased expression of the mitochondrial antioxidant MnSOD. In the final set of experiments, we found that hippocampal injections of sAPPα-NSCs altered Morris water maze (MWM) performance of healthy SAMR1 mice. Although future studies are required to determine the effects of sAPPα-NSCs on cognition, these preliminary results nevertheless warrant future studies investigating the therapeutic potential of sAPPα-NSCs. Conclusion: In total, the results presented in this thesis demonstrate that sAPPα can inhibit pathology in the diabetic nervous system. Therefore, the data generated from these studies has provided a foundation for the development of sAPPα based therapeutics, potentially in the form of sAPPα-NSCs, as a treatment option for diabetes and AD.
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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 | 0.001 |
| 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".