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Record W2165905855 · doi:10.4049/jimmunol.172.7.4225

Monocyte Surface-Bound IL-15 Can Function as an Activating Receptor and Participate in Reverse Signaling

2004· article· en· W2165905855 on OpenAlexaff
G. Gregory Neely, Slava Epelman, Ling Ling, Pina Colarusso, Christopher J. Howlett, Ernest K. Amankwah, Amanda C. McIntyre, Stephen M. Robbins, Christopher H. Mody

Bibliographic record

VenueThe Journal of Immunology · 2004
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsCalgary Laboratory ServicesUniversity of Calgary
Fundersnot available
KeywordsCell biologySignal transductionMonocyteExtracellularReceptorCytokineGTPaseCell adhesionChemistryCellBiologyImmunologyBiochemistry

Abstract

fetched live from OpenAlex

IL-15 is a short chain, four-alpha helix cytokine that shares some biological function with IL-2. One striking difference between IL-2 and IL-15 is the ability of monocytes to express IL-15 on their cell surface after activation. In the current study we have investigated the ability of human monocyte cell surface IL-15 to participate in reverse signaling. Cross-linking anti-IL-15 Abs were used as a surrogate ligand for surface IL-15 engagement. Ligation of cell surface-expressed IL-15 induced monocyte adhesion that required the activity of small m.w. GTPases. Reverse signals through surface IL-15 activated the Rho-GTPase Rac3. In addition, engagement of cell surface IL-15 was found to activate a number of signaling pathways, including both extracellular signal-regulated kinase 1/2 and p38, and resulted in the secretion of IL-8. IL-8 production required mitogen-activated protein kinase activity. Thus, the current study has established that cell surface IL-15 is more than just a ligand; it can function as a receptor and participate in reverse signaling that results in cellular adhesion and production of inflammatory cytokines.

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 score0.005

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 communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.022
GPT teacher head0.255
Teacher spread0.233 · 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

Citations62
Published2004
Admission routes1
Has abstractyes

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