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Record W2160659643 · doi:10.1109/iembs.2005.1616458

Quantum dots as phototoxic drugs and sensors of specific metabolic processes in living cells

2005· article· en· W2160659643 on OpenAlexaff
Samuel Clarke, Jay Nadeau, Daniel M. Bahcheli, Z. Zhang, Christiane Hollmann

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldMaterials Science
TopicQuantum Dots Synthesis And Properties
Canadian institutionsMcGill University
Fundersnot available
KeywordsPhototoxicityQuantum dotQuenching (fluorescence)ChemistryFluorescenceBiophysicsToxicityNanotechnologyBiochemistryMaterials scienceBiologyPhysicsIn vitro

Abstract

fetched live from OpenAlex

When conjugated to CdSe/ZnS nanocrystals (quantum dots), the nucleobase adenine and the neurotransmitter dopamine quench fluorescence emission from in a manner strongly dependent upon the size of the quantum dot. The degree of quenching serves to predict the efficiency with which the conjugates are able to enter living cells. Along with quenching, the presence of specific receptors on the cells is necessary for QD binding, entry, and phototoxicity. Toxicity is manifested by opening of large membrane pores and by oxidative DNA damage, and does not require the release of Cd <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">+2</sup> . In bacterial cells, light exposure is necessary for uptake, and procedures to reduce toxicity eliminate labeling. In mammalian cells, antioxidants prevent toxicity but not QD uptake, leading to QD-loaded cells that are nonfluorescent before light exposure. These findings provide a general procedure for rational design of nanoparticle-based photosensitizing drugs and for "off-on" fluorescent labels

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.

How this classification was reachedexpand

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.009
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0020.000

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 head0.016
GPT teacher head0.229
Teacher spread0.213 · 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

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations9
Published2005
Admission routes1
Has abstractyes

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