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Record W3014953259 · doi:10.1128/msphere.00195-20

Identification of the Neuroinvasive Pathogen Host Target, LamR, as an Endothelial Receptor for the Treponema pallidum Adhesin Tp0751

2020· article· en· W3014953259 on OpenAlexafffund
Karen Lithgow, Brigette Church, Alloysius Gomez, Emily Tsao, Simon Houston, Leigh Anne Swayne, Caroline E. Cameron

Bibliographic record

VenuemSphere · 2020
Typearticle
Languageen
FieldMedicine
TopicSyphilis Diagnosis and Treatment
Canadian institutionsUniversity of Victoria
FundersNational Institute of Allergy and Infectious DiseasesNational Institutes of HealthMichael Smith Health Research BCNatural Sciences and Engineering Research Council of CanadaGovernment of Canada
KeywordsTreponemaBacterial adhesinMicrobiologyBiologyNeisseriaPathogenNeisseria meningitidisVirologyNeisseria gonorrhoeaeHaemophilus influenzaeSyphilisStreptococcus pneumoniaeHuman pathogenImmunologyVirulenceBacteriaGeneAntibioticsGenetics

Abstract

fetched live from OpenAlex

Syphilis is a sexually transmitted infection caused by the spirochete bacterium Treponema pallidum subsp. pallidum. The continued incidence of syphilis demonstrates that screening and treatment strategies are not sufficient to curb this infectious disease, and there is currently no vaccine available. Herein we demonstrate that the T. pallidum adhesin Tp0751 interacts with endothelial cells that line the lumen of human blood vessels through the 67-kDa laminin receptor (LamR). Importantly, LamR is also a receptor for meningitis-causing neuroinvasive bacterial pathogens such as Neisseria meningitidis , Haemophilus influenzae , and Streptococcus pneumoniae . Our findings enhance understanding of the Tp0751 adhesin and present the intriguing possibility that the molecular events of Tp0751-mediated treponemal dissemination may mimic the endothelial interaction strategies of other invasive 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 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 score0.002
Threshold uncertainty score0.005

Distilled classifier scores by category (both heads)

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)0.0020.000

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 head0.032
GPT teacher head0.274
Teacher spread0.242 · 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

Citations40
Published2020
Admission routes2
Has abstractyes

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