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Record W2904141410 · doi:10.1002/btpr.2764

Ready‐to‐use thermally stable mastermix pills for molecular biology applications

2018· article· en· W2904141410 on OpenAlexafffund
Vincent Leung, Meredith Brooks, Sophia Emerson, M. Monsur Ali, Carlos D. M. Filipe

Bibliographic record

VenueBiotechnology Progress · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicBacteriophages and microbial interactions
Canadian institutionsMcMaster University
FundersNatural Sciences and Engineering Research Council of CanadaGrand Challenges CanadaMcMaster University
KeywordsPullulanLoop-mediated isothermal amplificationReagentPolymerase chain reactionCombinatorial chemistryTrehaloseChemistryBiologyComputational biologyNanotechnologyMaterials scienceBiochemistryDNAGeneOrganic chemistryPolysaccharide

Abstract

fetched live from OpenAlex

Rolling circle amplification (RCA), polymerase chain reaction (PCR), and loop-mediated isothermal amplification (LAMP), are powerful tools that can be used for gene manipulation, pathogen detection, and infectious disease diagnostics. However, these techniques require trained personnel, as the pipetting steps involved can lead to contamination and, consequently, erroneous results. Furthermore, many of the reagents used in molecular biology are thermally labile and must be kept within a cold-chain. In this article, we present a simple and cost-effective method that allows molecular biology reagents to be thermally stabilized into ready-to-use mastermixes via drying in pullulan and trehalose films. Our experimental results demonstrate that this method is capable of preserving the activity of RCA, PCR, LAMP, ligase, polynucleotide kinase, and Klenow fragment mastermixes for at least 3 months at ambient conditions. Thus, stabilizing reagents via drying in pullulan and trehalose film may allow for a drastic reduction in the number of pipetting steps and the elimination of the need for a cold chain. © 2018 American Institute of Chemical Engineers Biotechnol. Prog., 35: e2764, 2019.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.651
Threshold uncertainty score1.000

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 studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.001

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 head0.014
GPT teacher head0.291
Teacher spread0.276 · 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

Citations4
Published2018
Admission routes2
Has abstractyes

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