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Record W1976735289 · doi:10.1021/bc100178z

Facile Synthesis of Advanced Photodynamic Molecular Beacon Architectures

2010· article· en· W1976735289 on OpenAlexafffund
Jonathan F. Lovell, Juan Chen, Elizabeth Huynh, Mark T. Jarvi, Brian C. Wilson, Gang Zheng

Bibliographic record

VenueBioconjugate Chemistry · 2010
Typearticle
Languageen
FieldMedicine
TopicPhotodynamic Therapy Research Studies
Canadian institutionsUniversity of TorontoOntario Institute for Cancer Research
FundersCanadian Institutes of Health Research
KeywordsChemistryPhotodynamic therapyMolecular beaconCombinatorial chemistryNanotechnologyOrganic chemistryBiochemistry

Abstract

fetched live from OpenAlex

Nucleic acid photodynamic molecular beacons (PMBs) are a class of activatable photosensitizers that increase singlet oxygen generation upon binding a specific target sequence. Normally, PMBs are functionalized with multiple solution-phase labeling and purification steps. Here, we make use of a flexible solid-phase approach for completely automated synthesis of PMBs. This enabled the creation of a new type of molecular beacon that uses a linear superquencher architecture. The 3' terminus was labeled with a photosensitizer by generating pyropheophorbide-labeled solid-phase support. The 5' terminus was labeled with up to three consecutive additions of a dark quencher phosphoramidite. These photosensitizing and quenching moieties were stable in the harsh DNA synthesis environment and their hydrophobicity facilitated PMB purification by HPLC. Linear superquenchers exhibited highly efficient quenching. This fully automated synthesis method simplifies not only the synthesis and purification of PMBs, but also the creation of new activatable photosensitizer designs.

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 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 score0.008
Threshold uncertainty score0.822

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 head0.005
GPT teacher head0.264
Teacher spread0.259 · 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.

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

Citations30
Published2010
Admission routes2
Has abstractyes

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