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Record W1967367208 · doi:10.2174/138620706778249749

Modifications to Increase the Efficiency of the Fluorometric Cycling Assay for Cyclic ADP-Ribose

2006· article· en· W1967367208 on OpenAlexaff
Genevieve Young, James B. Kirkland

Bibliographic record

VenueCombinatorial Chemistry & High Throughput Screening · 2006
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicCalcium signaling and nucleotide metabolism
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsIntracellularCyclic ADP-riboseFluorescenceChemistryPerchloric acidReagentLysisChromatographyPlate readerBiophysicsBiochemistryBiologyOrganic chemistryCell biology

Abstract

fetched live from OpenAlex

Cyclic ADP-ribose (cADPR) is an intracellular messenger that triggers the release of calcium ions from intracellular stores in a variety of cell types. The fluorometric cycling assay has become the preferred method for measuring cADPR due to its high level of sensitivity (in the sub-nanomolar range) and its use of commercially available reagents. Additionally, the assay is performed in multiwell plates, making it suitable for high throughput screening using a fluorescence plate reader. The findings reported in this paper present several problems that may be encountered during various stages of the assay, and provide solutions to these problems. Modifications to the assay address reduced recovery of sample and cADPR with removal of perchloric acid (PCA) using organic solvent, reduction in diaphorase activity with heat treatment, and effects on resorufin fluorescence by pH range. Using these modifications, we report an increase of approximately 15% in recovery of brain cADPR, and show that between-subject variability is greatly reduced. We hope that these observations will encourage more widespread application of this valuable assay.

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)0.001
metaresearch head score (Gemma)0.001
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 score0.020
Threshold uncertainty score0.781

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
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 head0.011
GPT teacher head0.247
Teacher spread0.236 · 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

Citations6
Published2006
Admission routes1
Has abstractyes

Explore more

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