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Record W2804057239 · doi:10.1002/hlca.201800066

Fluorescent Nucleobase Analogues with Extended Pi Surfaces Stabilize <scp>DNA</scp> Duplexes Containing <i>O</i><sup>6</sup>‐Alkylguanine Adducts

2018· article· en· W2804057239 on OpenAlexafffund
Heidi A. Dahlmann, Florence D. Berger, Ryan W. Kung, Laura A. Wyss, Irina Gubler, Maureen McKeague, Stacey D. Wetmore, Shana J. Sturla

Bibliographic record

VenueHelvetica Chimica Acta · 2018
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicDNA and Nucleic Acid Chemistry
Canadian institutionsUniversity of Lethbridge
FundersEuropean Research CouncilNatural Sciences and Engineering Research Council of CanadaSchweizerischer Nationalfonds zur Förderung der Wissenschaftlichen Forschung
KeywordsChemistryNucleobaseDNANucleosideBase pairAdductAP siteStereochemistryAlkylationBiochemistryDNA damageOrganic chemistry

Abstract

fetched live from OpenAlex

Chemical alkylation of DNA produces potentially toxic and mutagenic damage such as O 6 ‐alkylguanine ( O 6 ‐alkylG) adducts. Non‐natural nucleoside analogues that pair with DNA adducts provide a potential basis for studying damaged DNA . Herein, we evaluated the base pairing properties of elongated nucleoside analogues containing napthalene‐derived tricyclic nucleobases as DNA adduct‐pairing nucleoside analogues in DNA hybridization probes. DNA duplex melting studies revealed that the elongated nucleoside analogs formed more stable base pairs opposite O 6 ‐alkylG than G and were better able to distinguish between G, O 6 ‐alkylG, and an abasic site than any previously described nucleoside analogue. DNA duplexes containing an elongated base analogue exhibited different fluorescence intensities when paired opposite O 6 ‐alkylG vs . G or abasic sites. Their selectivity for stabilizing alkylated DNA make the elongated hydrophobic base analogues improved candidates for incorporating into DNA hybridization probes targeting O 6 ‐alkylG.

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)0.000
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 score0.057
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.009
GPT teacher head0.225
Teacher spread0.216 · 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

Citations5
Published2018
Admission routes2
Has abstractyes

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