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Record W2653991958 · doi:10.1039/c7ob00943g

Prodigiosenes conjugated to tamoxifen and estradiol

2017· article· en· W2653991958 on OpenAlexafffund
Estelle Marchal, Carlotta Figliola, Alison Thompson

Bibliographic record

VenueOrganic & Biomolecular Chemistry · 2017
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMicrobial Metabolism and Applications
Canadian institutionsDalhousie University
FundersCanadian Institutes of Health ResearchKillam TrustsTerry Fox FoundationNova Scotia Health Research FoundationBeatrice Hunter Cancer Research Institute
KeywordsChemistryConjugateConjugated systemEtherClick chemistryTamoxifenCombinatorial chemistryArylStereochemistryBreast cancerOrganic chemistryCancerAlkyl

Abstract

fetched live from OpenAlex

We report the synthesis of the first click-appended prodigiosene conjugates. Four prodigiosene conjugates of estradiol functionalised at the 7α-position were prepared, as were three prodigiosene conjugates of tamoxifen. The coupling between a prodigiosene and an 11-hydroxy estradiol derivative via an ether linkage was investigated, as was the 11- and 7-functionalisation of the estradiol core. The robustness of estradiol protecting groups was severely challenged by reactions typically used to equip such frameworks for 11- and 7-functionalisation. Specifically, and important to synthesis involving estradiol, TBS, TMS and THP are not useful protecting groups for the functionalisation of this core. When the chemical features of the therapeutic agent limit the choice of protecting group (in this case, prodigiosenes bearing aryl, NH, alkenyl and ester groups), click chemistry becomes an attractive synthetic strategy. The anti-cancer activity of the seven click prodigiosene conjugates was evaluated.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

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)0.0010.001

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 head0.006
GPT teacher head0.240
Teacher spread0.234 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations5
Published2017
Admission routes2
Has abstractyes

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