Late Simian virus 40 transcription factor is a target of the phosphoinositide 3-kinase/Akt pathway in anti-apoptotic Alzheimers amyloid precursor protein signalling
Bibliographic record
Abstract
The association of familial Alzheimer's disease (FAD) with mutations in Alzheimer's amyloid precursor protein (APP) suggests important functions for APP in the central nervous system. Mutations in APP impair its function to confer resistance to apoptosis in cells under stress, and this may contribute to neurodegeneration in Alzheimer's disease (AD) brain, but the mechanisms involved are unknown. We examined the role of the late Simian virus 40 transcription factor (LSF), in anti-apoptotic APP pathways. We show that in APP-deficient B103 cells, expression of wild-type human APP (hAPPwt), but not of FAD-mutant APP, inhibited staurosporine (STS)-induced apoptosis. This inhibition was further enhanced by expression of LSFwt, although LSFwt alone was not sufficient to inhibit STS-induced apoptosis. In contrast, expression of dominant-negative LSF led to a marked increase in STS-induced cell death that was significantly blocked by hAPPwt. These effects of APP were accompanied by LSF nuclear translocation and dependent gene transcription. The activation of LSF is dependent on the expression of hAPPwt and is inhibited by the expression of dominant-negative forms of either phosphoinositide 3-kinase or Akt. These results demonstrate that LSF activation is required for the neuroprotective effects of APP via phosphoinositide 3-kinase/Akt signalling. Alterations in this pathway by aberrations in APP and/or LSF could promote neuronal loss in AD brain, due to secondary insults. Thus a link is established between APP and LSF and AD.
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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 | 0.001 |
| 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".