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Record W2143021230 · doi:10.1002/smll.200700794

Enhancement of Radiation Cytotoxicity in Breast‐Cancer Cells by Localized Attachment of Gold Nanoparticles

2008· article· en· W2143021230 on OpenAlex

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.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSmall · 2008
Typearticle
Languageen
FieldMaterials Science
TopicNanoparticles: synthesis and applications
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCytotoxicityColloidal goldCancer cellCysteamineMCF-7BiophysicsChemistryCellCell cultureIn vitroNanoparticleMaterials scienceNanotechnologyCancerBiochemistryHuman breastBiologyMedicineInternal medicine

Abstract

fetched live from OpenAlex

Gold nanoparticles (GNPs) and modified GNPs having two kinds of functional molecules, cysteamine (AET) and thioglucose (Glu), are synthesized. Cell uptake and radiation cytotoxicity enhancement in a breast-cancer cell line (MCF-7) versus a nonmalignant breast-cell line (MCF-10A) are studied. Transmission electron microscopy (TEM) results show that cancer cells take up functional Glu-GNPs significantly more than naked GNPs. The TEM results also indicate that AET-capped GNPs are mostly bound to the MCF-7 cell membrane, while Glu-GNPs enter the cells and are distributed in the cytoplasm. After MCF-7 cell uptake of Glu-GNPs, or binding of AET-GNPs, the in vitro cytotoxicity effects are observed at 24, 48, and 72 hours. The results show that these functional GNPs have little or no toxicity to these cells. To validate the enhanced killing effect on cancer cells, various forms of radiation are applied such as 200 kVp X-rays and gamma-rays, to the cells, both with and without functional GNPs. By comparison with irradiation alone, the results show that GNPs significantly enhance cancer killing.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.369

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.019
GPT teacher head0.254
Teacher spread0.235 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it