Overexpression of the IGF-II/M6P Receptor in Mouse Fibroblast Cell Lines Differentially Alters Expression Profiles of Genes Involved in Alzheimer’s Disease-Related Pathology
Bibliographic record
Abstract
Alzheimer's disease (AD) is the most common type of senile dementia affecting elderly people. The processing of amyloid precursor protein (APP) leading to the generation of β-amyloid (Aβ) peptide contributes to neurodegeneration and development of AD pathology. The endocytic trafficking pathway, which comprises of the endosomes and lysosomes, acts as an important site for Aβ generation, and endocytic dysfunction has been linked to increased Aβ production and loss of neurons in AD brains. Since insulin-like growth factor-II (IGF-II) receptor plays a critical role in the transport of lysosomal enzymes from the trans-Golgi network to endosomes, it is likely that the receptor may have a role in regulating Aβ metabolism in AD pathology. However, very little is known on how altered levels of the IGF-II receptor can influence the expression/function of various molecules involved in AD pathology. To address this issue, we evaluated the expression profiles of 87 selected genes related to AD pathology in mouse fibroblast MS cells that are deficient in murine IGF-II receptor and corresponding MS9II cells overexpressing ∼ 500 times the human IGF-II receptors. Our results reveal that an elevation in IGF-II receptor levels alters the expression profiles of a number of genes including APP as well as enzymes regulating Aβ production, degradation and clearance mechanisms. Additionally, it influences the expression of various lysosomal enzymes and protein kinases that are involved in Aβ toxicity. IGF-II receptor overexpression also alters expression of several genes involved in intracellular signalling as well as cholesterol metabolism, which play a critical role in AD pathology. The altered gene profiles observed in this study closely match with the corresponding protein levels, with a few exceptions. These results, taken together, suggest that an elevation in IGF-II receptor levels can influence the expression profiles of transcripts as well as proteins that are involved in AD pathogenesis.
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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".