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Record W2791421665 · doi:10.1002/iub.1737

The role of lipids in host–pathogen interactions

2018· review· en· W2791421665 on OpenAlex
Glenn F. W. Walpole, Sergio Grinstein, Johannes Westman

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

Bibliographic record

VenueIUBMB Life · 2018
Typereview
Languageen
FieldMedicine
TopicDrug Transport and Resistance Mechanisms
Canadian institutionsSt. Michael's HospitalHospital for Sick ChildrenUniversity of Toronto
FundersCanadian Institutes of Health ResearchHospital for Sick ChildrenUniversity of Toronto
KeywordsPhagosomeBiologyInnate immune systemCell biologyPathogenIntracellular parasiteIntracellularLipid metabolismImmune systemMicrobiologyImmunityYersinia pseudotuberculosisYersiniaHost (biology)SalmonellaBacteriaBiochemistryImmunologyVirulenceGeneGenetics

Abstract

fetched live from OpenAlex

Innate immunity relies on the effective recognition and elimination of pathogenic microorganisms. This entails sequestration of pathogens into phagosomes that promptly acquire microbicidal and degradative properties. This complex series of events, which involve cytoskeletal reorganization, membrane remodeling and the activation of multiple enzymes, is orchestrated by lipid signaling. To overcome this immune response, intracellular pathogens acquired mechanisms to subvert phosphoinositide-mediated signaling and use host lipids, notably cholesterol, as nutrients. We present brief overviews of the role of phosphoinositides in phagosome formation and maturation as well as of cholesterol handling by host cells, and selected Salmonella, Shigella, Chlamydia and Mycobacterium tuberculosis to exemplify the mechanisms whereby intracellular pathogens co-opt lipid metabolism in host cells. © 2018 IUBMB Life, 70(5):384-392, 2018.

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.986
Threshold uncertainty score0.520

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
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 head0.029
GPT teacher head0.330
Teacher spread0.301 · 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