Insights into the Impact of Gold Nanoclusters Au<sub>10</sub>SG<sub>10</sub> on Human Microglia
Bibliographic record
Abstract
The purpose of the current study is to uncover the impact of small liganded gold nanoclusters with 10 gold atoms and 10 glutathione ligands (Au 10 SG 10 ) on several biomarkers in human microglia. We established the links connecting the atomically precise structure of Au 10 SG 10 with their properties and changes in several biomolecules under oxidative stress. Au 10 SG 10 caused the loss of mitochondrial metabolic activity, increased lipid peroxidation and translocation of an alarmin molecule, high mobility group box 1 (HMGB1), from the nucleus to the cytosol. Molecular modeling provided an insight into the location of amino acid interaction sites with Au 10 SG 10 and the nature of bonds participating in these interactions. We show that Au 10 SG 10 can bind directly to the defined sites of reduced, oxidized, and acetylated HMGB1. Further studies with similar complementary approaches merging live-cell analyses, determination of biomarkers, and cell functions could lead to optimized gold nanoclusters best suited for diagnostic and bioimaging purposes in neuroscience.
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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 | 0.000 |
| 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".