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Record W2224256314 · doi:10.1039/c5sc04184h

Simple and ultrastable all-inclusive pullulan tablets for challenging bioassays

2016· article· en· W2224256314 on OpenAlexafffund
Sana Jahanshahi‐Anbuhi, Balamurali Kannan, Vincent Leung, Kevin Pennings, Meng Liu, Carmen Carrasquilla, Dawn White, Yingfu Li, Robert Pelton, John D. Brennan, Carlos D. M. Filipe

Bibliographic record

VenueChemical Science · 2016
Typearticle
Languageen
FieldEngineering
TopicBiosensors and Analytical Detection
Canadian institutionsMcMaster University
FundersOntario Ministry of Research and InnovationNatural Sciences and Engineering Research Council of CanadaOntario Ministry of Research, Innovation and ScienceCanada Research Chairs
KeywordsPullulanBioassayLuciferaseSimple (philosophy)ChemistryCombinatorial chemistryLuciferinChromatographyNanotechnologyBiochemistryMaterials scienceBiologyPolysaccharide

Abstract

fetched live from OpenAlex

Many biodetection systems employ labile enzymes and substrates that need special care, making it hard to routinely use them for point-of-care or field applications. In this work we provide a simple solution to this challenging problem through the creation of all-inclusive pullulan assay tablets. The proposed tablet system not only enhances the long-term stability of both enzymes and organic substrates, but also simplifies the assay procedure. The enhanced stability is attributed to two factors: the restriction of the molecular motion of proteins and impermeability to molecular oxygen afforded by the tables. These tablets dissolve rapidly upon addition to testing samples, making the test very easy to perform. Using the ATP-detecting luciferase-luciferin system as an example, we show that the tablet-based assay can achieve highly sensitive detection of ATP in biological samples and that the activity of the assay tablets remains unchanged for over a month at room temperature.

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 score0.049
Threshold uncertainty score0.201

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 head0.010
GPT teacher head0.231
Teacher spread0.222 · 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

Citations45
Published2016
Admission routes2
Has abstractyes

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