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Record W2607213148 · doi:10.1073/pnas.1615007114

Plasma fibronectin stabilizes <i>Borrelia burgdorferi</i> –endothelial interactions under vascular shear stress by a catch-bond mechanism

2017· article· en· W2607213148 on OpenAlexafffund
Alexandra F. Niddam, Rhodaba Ebady, Anil K. Bansal, Anne B. Koehler, Boris Hinz, Tara J. Moriarty

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2017
Typearticle
Languageen
FieldImmunology and Microbiology
TopicVector-borne infectious diseases
Canadian institutionsUniversity of Toronto
FundersCanadian Institutes of Health ResearchFaculty of Dentistry, University of TorontoUniversity of TorontoCanada Foundation for InnovationNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsBorrelia burgdorferiMechanism (biology)FibronectinShear stressBorreliaShear (geology)MicrobiologyCell biologyChemistryBiologyMaterials scienceImmunologyComposite materialPhysicsAntibodyExtracellular matrix

Abstract

fetched live from OpenAlex

Significance Spread of bacteria via the bloodstream to vital organs causes most mortality due to bacterial infection. To exit the bloodstream and enter these organs, bacteria must be able to resist the forces generated by flowing blood so that they can adhere to the endothelial cells lining blood vessels without being washed away. This process is not yet understood for most disease-causing bacteria. Here, we show that the Lyme disease pathogen Borrelia burgdorferi exploits an abundant constituent of blood, plasma fibronectin, to form endothelial interactions that become stronger as forces due to blood-flow increase. The ability to recruit this highly conserved molecule may also be important for the vascular interaction mechanisms of other pathogens.

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 score0.022
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.001
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 head0.024
GPT teacher head0.289
Teacher spread0.265 · 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

Citations48
Published2017
Admission routes2
Has abstractyes

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