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Record W4301042503 · doi:10.17615/smne-6m58

Regulation of T cell activation, anxiety, and male aggression by RGS2

2020· article· en· W4301042503 on OpenAlexfundno aff
C. A. Barnes, S. Mariathasan, J. C. Roder, Josef Penninger, I. Q. Whishaw, A. J. Oliveira-dos-Santos, B. E. Snow, T. Sasaki, David P. Siderovski, G. Matsumoto, P. S. Ohashi, A. Wakeham, D. Bai, F. P. Houston

Bibliographic record

VenueUNC Libraries · 2020
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsnot available
FundersMedical Research CouncilNational Institutes of HealthMedical Research Council Canada
KeywordsAggressionRGS2AnxietyPsychologyDevelopmental psychologyClinical psychologyPsychiatryBiologyGeneticsG proteinSignal transduction

Abstract

fetched live from OpenAlex

Regulators of G protein signaling (RGS) proteins accelerate the GTPase activity of Gα protein subunits in vitro, negatively regulating G protein-coupled receptor signaling. The physiological role of mammalian RGS proteins is largely unknown. The RGS family member rgs2 was cloned as an immediate early response gene up-regulated in T lymphocytes after activation. To investigate the role of RGS2 in vivo, we generated rgs2-deficient mice. We show that targeted mutation of rgs2 in mice leads to reduced T cell proliferation and IL-2 production, which translates in an impaired antiviral immunity in vivo. Interestingly, rgs2−/− mice also display increased anxiety responses and decreased male aggression in the absence of cognitive or motor deficits. RGS2 also controls synaptic development and basal electrical activity in hippocampal CA1 neurons. Thus, RGS2 plays an important role in T cell activation, synapse development in the hippocampus, and emotive behaviors.

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 score0.001
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0010.000
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 head0.186
Teacher spread0.177 · 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

Citations15
Published2020
Admission routes1
Has abstractyes

Explore more

Same venueUNC LibrariesSame topicImmune Cell Function and InteractionFrench-language works237,207