Intracellular amyloid formation in muscle cells of Aβ-transgenic Caenorhabditis elegans: determinants and physiological role in copper detoxification
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
BACKGROUND: The amyloid beta-peptide is a ubiquitous peptide, which is prone to aggregate forming soluble toxic oligomers and insoluble less-toxic aggregates. The intrinsic and external/environmental factors that determine Abeta aggregation in vivo are poorly understood, as well as the cellular meaning of this process itself. Genetic data as well as cell biological and biochemical evidence strongly support the hypothesis that Abeta is a major player in the onset and development of Alzheimer's disease. In addition, it is also known that Abeta is involved in Inclusion Body Myositis, a common myopathy of the elderly in which the peptide accumulates intracellularly. RESULTS: In the present work, we found that intracellular Abeta aggregation in muscle cells of Caenorhabditis elegans overexpressing Abeta peptide is affected by two single amino acid substitutions, E22G (Arctic) and V18A (NIC). Both variations show decrease intracellular amyloidogenesis compared to wild type Abeta. We show that intracellular amyloid aggregation of wild type Abeta is accelerated by Cu2+ and diminished by copper chelators. Moreover, we demonstrate through toxicity and behavioral assays that Abeta-transgenic worms display a higher tolerance to Cu2+ toxic effects and that this resistance may be linked to the formation of amyloid aggregates. CONCLUSION: Our data show that intracellular Abeta amyloid aggregates may trap excess of free Cu2+ buffering its cytotoxic effects and that accelerated intracellular Abeta aggregation may be part of a cell protective mechanism.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 it