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Record W2128857896 · doi:10.4049/jimmunol.165.7.3549

Cutting Edge: Defective NK Cell Activation in X-Linked Lymphoproliferative Disease

2000· article· en· W2128857896 on OpenAlexafffund
Loralyn A. Benoît, Henry F. Pabst, Jan Dutz, Rusung Tan

Bibliographic record

VenueThe Journal of Immunology · 2000
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsBC Children's HospitalUniversity of British ColumbiaUniversity of AlbertaVancouver Hospital and Health Sciences Centre
FundersUniversity of British ColumbiaFaculty of Medicine, University of British Columbia
KeywordsCytotoxicityBiologyImmunologyLymphocyteImmune systemLymphokineNatural killer cellAntibody-dependent cell-mediated cytotoxicityLytic cycleCancer researchCell biologyMolecular biologyBiochemistryVirusIn vitro

Abstract

fetched live from OpenAlex

X-linked lymphoproliferative disease (XLP) is characterized by a selective immune deficiency to EBV. The molecular basis of XLP has been attributed to mutations of signaling lymphocytic activation molecule-associated protein, an intracellular molecule known to associate with the lymphocyte-activating surface receptors SLAM and 2B4. We have identified a single nucleotide mutation in SLAM-associated protein that affects the NK cell function of males carrying the mutated gene. In contrast to normal controls, both NK and lymphokine-activated killer cell cytotoxicity was significantly reduced in two XLP patients. In addition to decreased baseline cytotoxicity, ligation of 2B4 significantly augmented NK lytic function in normal controls but failed to enhance the cytotoxicity of NK cells from XLP patients. These findings suggest that association of SAP with 2B4 is necessary for optimal NK/lymphokine-activated killer cytotoxicity and imply that alterations in SAP/2B4 signaling contribute to the immune dysfunction observed in XLP.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.206
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.001

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 head0.227
Teacher spread0.218 · 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.

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

Citations144
Published2000
Admission routes2
Has abstractyes

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