MétaCan
Menu
Back to cohort
Record W2059504312 · doi:10.1089/hyb.2010.0066

Monoclonal Antibodies to Lipopolysaccharide Antigens of <i>Salmonella enterica</i> serotype Typhimurium DT104

2011· article· en· W2059504312 on OpenAlexafffund
Jennifer Ronholm, Zhiyi Zhang, Xundong Cao, Min Lin

Bibliographic record

VenueHybridoma · 2011
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicSalmonella and Campylobacter epidemiology
Canadian institutionsNational Research Council CanadaInstitute for Microstructural SciencesUniversity of OttawaCanadian Food Inspection Agency
FundersCanadian Food Inspection Agency
KeywordsSalmonella entericaMonoclonal antibodySerotypeSalmonellaAntigenicityMicrobiologyEpitopeLipopolysaccharideAntigenBiologyBacteriaAntibodyVirologyEnterobacteriaceaeEscherichia coliImmunologyGene

Abstract

fetched live from OpenAlex

Salmonella enterica subsp. enterica serotype Typhimurium is one of the major causative agents of human gastroenteritis. Here we raised a panel of 45 monoclonal antibodies (MAbs) against ser. Typhimurium DT104 by immunizing mice with formalin-killed bacteria and demonstrated that all the MAbs recognized the bacterial lipopolysaccharide (LPS) antigen. These MAbs were specific for group O:4 Salmonella with very little or no cross-reactivity with other closely related bacteria and were able to bind to the cell surface of live bacterial cells, making them potential candidates for capture and concentration of the pathogen in food and water samples. Epitope characterization revealed that the O:5 antigen present in the LPS of some serogroup 4 Salmonella is the critical factor for the binding of these MAbs to LPS. This study has provided some insights into the structure of the Salmonella LPS and its influence on the antigenicity of LPS.

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)0.000
metaresearch head score (Gemma)0.000
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: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.010

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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)0.0030.001

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 head0.055
GPT teacher head0.222
Teacher spread0.167 · 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
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

Citations20
Published2011
Admission routes2
Has abstractyes

Explore more

Same venueHybridomaSame topicSalmonella and Campylobacter epidemiologyFrench-language works237,207