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Record W2102911374 · doi:10.4049/jimmunol.165.4.1771

Ly-49P Activates NK-Mediated Lysis by Recognizing H-2Dd 1

2000· article· en· W2102911374 on OpenAlexaff
Elizabeth T. Silver, Dong‐Er Gong, Chew Shun Chang, Abdelaziz Amrani, Pere Santamaría, Kevin P. Kane

Bibliographic record

VenueThe Journal of Immunology · 2000
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsUniversity of CalgaryUniversity of Alberta
Fundersnot available
KeywordsTransfectionLysisMolecular biologyEpitopeReceptorCytotoxicityMajor histocompatibility complexBiologyChemistryCell biologyAntibodyCell cultureAntigenImmunologyIn vitroBiochemistryGenetics

Abstract

fetched live from OpenAlex

Little is known regarding the ligand specificity of Ly-49 activating receptor subfamily members expressed by NK cells. A new Ly-49 activating receptor related to Ly-49A in its extracellular domain, designated Ly-49P, was recently cloned from 129 strain mice. We independently cloned an apparent allele of Ly-49P expressed by nonobese diabetic and nonobese diabetes-resistant mouse strain NK cells. We found it to be reactive with the A1 Ab thought to recognize a polymorphic epitope expressed only by the Ly-49A inhibitory receptor of the C57BL/6 strain. Rat RNK-16 cells transfected with Ly-49P mediated reverse Ab-dependent cellular cytotoxicity of FcR-positive target cells, indicating that Ly-49P can activate NK-mediated lysis. We determined that RNK-16 lysis of Con A blasts induced by Ly-49P was MHC dependent, resulting in efficient lysis of H-2Dd-bearing targets. We found that the Dd alpha1/alpha2 domain is required for Ly-49P-mediated RNK-16 activation, as determined by exon shuffling and transfection. Thus, Ly-49P is the second activating Ly-49 receptor demonstrated to induce NK cytotoxicity by recognizing a class I MHC molecule.

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 score0.006

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)0.0020.001

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 head0.214
Teacher spread0.205 · 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

Citations36
Published2000
Admission routes1
Has abstractyes

Explore more

Same venueThe Journal of ImmunologySame topicImmune Cell Function and InteractionFrench-language works237,207