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Record W2291667497 · doi:10.1042/bst20150231

A cautionary (spectral) tail: red-shifted fluorescence by DAPI–DAPI interactions

2016· review· en· W2291667497 on OpenAlexaff
Sidney Omelon, John Georgiou, Wouter J. E. M. Habraken

Bibliographic record

VenueBiochemical Society Transactions · 2016
Typereview
Languageen
FieldMaterials Science
TopicPolymer Surface Interaction Studies
Canadian institutionsLunenfeld-Tanenbaum Research InstituteMount Sinai HospitalUniversity of Ottawa
Fundersnot available
KeywordsDAPIFluorescenceChemistryPolyphosphateBiophysicsBiochemistryPhosphateBiologyOptics

Abstract

fetched live from OpenAlex

The fluorescent dye DAPI is useful for its association with and consequent amplification of an ∼460 nm emission maximum upon binding to dsDNA. Labelling with higher DAPI concentrations is a technique used to reveal Pi polymers [polyphosphate (polyP)], with a red-shift to ∼520-550 nm fluorescence emission. DAPI-polyP emissions of ∼580 nm are also generated upon 415 nm excitation. Red-shifted DAPI emission has been associated with polyP and RNA and has more recently been reported with polyadenylic acid (polyA), specific inositol phosphates (IPs) and heparin. We find that amorphous calcium phosphate (ACP) also demonstrates red-shifted DAPI emission at high DAPI concentrations. This DAPI spectral shift has been attributed to DAPI-DAPI electrostatic interactions enabled by molecules with high negative charge density that increase the local DAPI concentration and favour DAPI molecular proximity, as observed by increasing the dye/phosphate ratio. Excitation of dry DAPI (∼360 nm) confirmed a red-shifted DAPI emission. Whereas enzymatic approaches to modify substrates can help define the nature of DAPI fluorescence signals, multiple approaches beyond red-shifted DAPI excitation/emission are advised before conclusions are drawn about DAPI substrate identification.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0070.006

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 head0.029
GPT teacher head0.318
Teacher spread0.289 · 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
GenreReview

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

Citations52
Published2016
Admission routes1
Has abstractyes

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