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Multitarget Thiol-Activated Tetrapyridyl Gold(III) Complexes for Hypoxic Cancer Therapy

2023· article· en· W4387933721 on OpenAlex
Xue‐Quan Zhou, Selda Abyar, Imma Carbo‐Bague, Lan Wang, Sebastian Türck, Maxime A. Siegler, Uttara Basu, Ingo Ott, Rongfang Liu, Adriaan P. IJzerman, Sylvestre Bonnet

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

VenueCCS Chemistry · 2023
Typearticle
Languageen
FieldEngineering
TopicNanoplatforms for cancer theranostics
Canadian institutionsSimon Fraser University
Fundersnot available
KeywordsThiolCancer therapyChemistryCancerCancer researchMedicineInternal medicineBiochemistry

Abstract

fetched live from OpenAlex

Gold complexes have emerged as promising anticancer metallodrugs due to their efficient thioredoxin reductase (TrxR) inhibition, which disturbs the redox balance of cancer cells.However, in this model, the role of the ligand(s) coordinated to gold is often overlooked.In this work, we present a series of tetrapyridyl Au(III) complexes that exhibit thiol-induced release of a Au(I) ion and a tetrapyridyl ligand.The formation of a free Au(I) center is responsible for the expected TrxR inhibition.Additionally, the released ligand, which was visible in cells due to its intense blue fluorescence, showed excellent binding properties to the hERG potassium channel.Moreover, these ligands ended up in the lysosomes, resulting in significant lysosome damage.Altogether, the Au(III) complexes presented in this work showed broad-spectrum anticancer properties, both in hypoxic 2D monolayers and 3D tumor spheroids.We suggest that the interaction of the released Au(I) center and the tetrapyridyl ligand with two different protein targets may combine into prodrugs that overcome hypoxia-induced drug deactivation.

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 categoriesMeta-epidemiology (narrow)
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 score0.034
Threshold uncertainty score1.000

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 head0.026
GPT teacher head0.259
Teacher spread0.233 · 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