Size and ligand effects of gold nanoclusters in alteration of organellar state and translocation of transcription factors in human primary astrocytes
Bibliographic record
Abstract
Ultra-small gold nanoclusters (AuNCs) with designed sizes and ligands are gaining popularity for biomedical purposes and ultimately for human imaging and therapeutic applications. Human non-tumor brain cells, astrocytes, are of particular interest because they are abundant and play a role in functional regulation of neurons under physiological and pathological conditions. Human primary astrocytes were treated with AuNCs of varying sizes (Au10, Au15, Au18, Au25) and ligand composition (glutathione, polyethylene glycol, N-acetyl cysteine). Concentration and time-dependent studies showed no significant cell loss with AuNC concentrations <10 μM. AuNC treatment caused marked differential astrocytic responses at the organellar and transcription factor level. The effects were exacerbated under severe oxidative stress induced by menadione. Size-dependent effects were most remarkable with the smallest and largest AuNCs (10, 15 Au atoms versus 25 Au atoms) and might be related to the accessibility of biological targets toward the AuNC core, as demonstrated by QM/MM simulations. In summary, these findings suggest that AuNCs are not inert in primary human astrocytes, and that their sizes play a critical role in modulation of organellar and redox-responsive transcription factor homeostasis.
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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 | 0.000 |
| 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 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".