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Comparison of ATP and in vivo bioluminescence for assessing the efficiency of immunomagnetic sorbents for live Escherichia coli O157:H7 cells

2002· article· en· W2005910778 on OpenAlexaff
Wenrong Sun, Firoozeh Khosravi, Hans‐Jørgen Albrechtsen, Lubov Brovko, Mansel W. Griffiths

Bibliographic record

VenueJournal of Applied Microbiology · 2002
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
Topicbioluminescence and chemiluminescence research
Canadian institutionsUniversity of Guelph
Fundersnot available
KeywordsBioluminescenceEscherichia coliIn vivoImmunomagnetic separationMicrobiologyBacteriaChemistryBiologyBiochemistryBiotechnologyGeneGenetics

Abstract

fetched live from OpenAlex

AIMS: To develop methods to assess the efficiency of immunomagnetic separation (IMS). METHODS AND RESULTS: The capturing efficiency of biosorbents for Escherichia coli O157:H7, constructed using streptavidin-coated magnetic beads and biotinylated antibodies, was tested using both in vivo and ATP bioluminescence. Both methods were suitable for the enumeration of bacteria captured by the biosorbents. The level of both ATP and in vivo bioluminescence depended on the media used, but was unaffected by the magnetic beads. The capture efficiency depended on time and sample volume, but did not depend on the length of spacer arm of the biotinylation agent. For cell concentrations of <or= 105 cfu ml-1, in a 1-ml sample volume, nearly 80-85% recovery of the pathogen was observed after 0.5 h of incubation. For an 11-ml sample containing 104 cfu ml-1, maximum recovery (50% of cells) was achieved only after 2 h incubation. CONCLUSIONS: The detection limit of an ATP-based bioluminescent assay for E. coli O157:H7 was reduced by 1 log cycle after optimization of IMS. The bioluminescent methods could be used for screening and testing the affinity of antibodies or other affinity elements of biosorbents towards live bacterial cells. SIGNIFICANCE AND IMPACT OF THE STUDY: Bioluminescent assays provide an easy way to optimize conditions for the capture of bacteria by biosorbents in real time.

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 score0.002
Threshold uncertainty score0.473

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 head0.019
GPT teacher head0.302
Teacher spread0.282 · 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

Citations19
Published2002
Admission routes1
Has abstractyes

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