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Record W4378232370 · doi:10.3389/fmicb.2023.1181034

Lipid A structural diversity among members of the genus Leptospira

2023· article· en· W4378232370 on OpenAlexafffund
Helena Pětrošová, Abanoub Mikhael, Sophie Culos, Alexandre Giraud-Gatineau, Alloysius M. Gomez, Matthew E. Sherman, Robert K. Ernst, Caroline E. Cameron, Mathieu Picardeau, David R. Goodlett

Bibliographic record

VenueFrontiers in Microbiology · 2023
Typearticle
Languageen
FieldImmunology and Microbiology
TopicLeptospirosis research and findings
Canadian institutionsGenome British ColumbiaUniversity of Victoria
FundersNational Institute of Allergy and Infectious DiseasesNatural Sciences and Engineering Research Council of CanadaGenome CanadaCanadian Institutes of Health ResearchGenome British ColumbiaNational Institutes of HealthUniversity of Victoria
KeywordsLeptospiraLipid ABiologyImmune systemMicrobiologyLipopolysaccharideLeptospirosisInnate immune systemImmunologyVirology

Abstract

fetched live from OpenAlex

Lipid A is the hydrophobic component of bacterial lipopolysaccharide and an activator of the host immune system. Bacteria modify their lipid A structure to adapt to the surrounding environment and, in some cases, to evade recognition by host immune cells. In this study, lipid A structural diversity within the Leptospira genus was explored. The individual Leptospira species have dramatically different pathogenic potential that ranges from non-infectious to life-threatening disease (leptospirosis). Ten distinct lipid A profiles, denoted L1-L10, were discovered across 31 Leptospira reference species, laying a foundation for lipid A-based molecular typing. Tandem MS analysis revealed structural features of Leptospira membrane lipids that might alter recognition of its lipid A by the host innate immune receptors. Results of this study will aid development of strategies to improve diagnosis and surveillance of leptospirosis, as well as guide functional studies on Leptospira lipid A activity.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.523

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.001
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 head0.010
GPT teacher head0.220
Teacher spread0.210 · 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 designObservational
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

Citations14
Published2023
Admission routes2
Has abstractyes

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