Gold Nanoparticles Impinge on Nucleoli and the Stress Response in MCF7 Breast Cancer Cells
Bibliographic record
Abstract
Cancer cells can take up gold nanoparticles of different morphologies. These particles interact with the plasma membrane and often travel to intracellular organelles. Among organelles, the nucleus is especially susceptible to the damage that is inflicted by gold nanoparticles. Located inside the nucleus, nucleoli are specialized compartments that transcribe ribosomal RNA genes, produce ribosomes and function as cellular stress sensors. Nucleoli are particularly prone to gold nanoparticle-induced injury. As such, small spherical gold nanoparticles and gold nanoflowers interfere with the transcription of ribosomal DNA. However, the underlying mechanisms are not fully understood. In this study, we examined the effects of gold nanoparticles on nucleolar proteins that are critical to ribosome biogenesis and other cellular functions. We show that B23/nucleophosmin, a nucleolar protein that is tightly linked to cancer, is significantly affected by gold nanoparticles. Furthermore, gold nanoparticles impinge on the cellular stress response, as they reduce the abundance of the molecular chaperone hsp70 and O-GlcNAc modified proteins in the nucleus and nucleoli. Together, our studies set the stage for the development of nanomedicines that target the nucleolus to eradicate proliferating cancer cells.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".