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Record W3000511596 · doi:10.1039/c9sc05248h

α-Glucuronosyl and α-glucosyl diacylglycerides, natural killer T cell-activating lipids from bacteria and fungi

2020· article· en· W3000511596 on OpenAlexaff
Satvika Burugupalli, Catarina F. Almeida, D. Smith, Sayali Shah, Onisha Patel, Jamie Rossjohn, Adam P. Uldrich, Dale I. Godfrey, Spencer J. Williams

Bibliographic record

VenueChemical Science · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsInstitute of Infection and Immunity
FundersNational Health and Medical Research CouncilAustralian Research CouncilMedical Research Council
KeywordsCD1DBacteriaReceptorCellBiologyMicrobiologyNatural killer cellNatural killer T cellChemistryBiochemistryT cellImmunologyImmune systemGeneticsCytotoxicityIn vitro

Abstract

fetched live from OpenAlex

-tuberculostearic acid) and unsaturated (oleic and vaccenic) acids. The TCR footprints on CD1d loaded with a mycobacterial α-glucuronosyl diacylglyceride were assessed using mutant CD1d molecules and, while similar to that for α-GalCer recognition by a type I NKT TCR, were more sensitive to mutations when α-glucuronosyl diacylglyceride was the antigen. In summary, we provide an efficient approach for synthesis of a broad class of bacterial and fungal α-glycosyl diacylglyceride antigens and demonstrate that they can be recognised by TCRs derived from type I and atypical NKT cells.

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: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.053
Threshold uncertainty score0.767

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.009
GPT teacher head0.210
Teacher spread0.201 · 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

Citations16
Published2020
Admission routes1
Has abstractyes

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