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Mast cells play a key role in autoinflammatory disease development in PSTPIP2-deficient cmo mice (BA7P.141)

2015· article· en· W2749492988 on OpenAlexaff
Andrew W. Craig, J.H. Lee, Namit Sharma, Violeta Chiţu, E. Richard Stanley

Bibliographic record

VenueThe Journal of Immunology · 2015
Typearticle
Languageen
FieldMedicine
TopicOsteomyelitis and Bone Disorders Research
Canadian institutionsQueen's University
Fundersnot available
KeywordsMedicinePathologyImmune systemInflammationLymphImmunologyInfiltration (HVAC)

Abstract

fetched live from OpenAlex

Abstract Chronic recurrent multifocal osteomyelitis (CRMO) is an autoinflammatory disease characterized by fevers, bone lesions, and skin lesions. A CRMO-like disease develops in cmo mice, which harbor a mutation in proline serine threonine phosphatase-interacting protein 2 (PSTPIP2). Loss of PSTPIP2 in cmo mice has been linked to elevated macrophage and osteoclast activation, and IL-1β-dependent disease progression. Since mast cells were detected in cmo lesions, we have tested the role of mast cells in cmo disease. In diseased cmo mice, increased connective tissue mast cells were observed in both normal skin and within skin lesions. Crossing cmo mice with a transgenic model of mast cell deficiency (Mcpt5-Cre:Rosa26-Stopfl/fl-DTa) resulted in mice (cmo/MC-) that were protected from developing cmo disease, including skin lesions and joint swelling. Fewer osteolytic lesions were also observed in cmo/MC- mice by micro-computed tomography. Within these tissues, cmo/MC- mice had reduced levels of IL-1β, and less activated immune cells in popliteal lymph nodes compared to cmo. Intravital microscopy experiments on young cmo mice revealed increased leukocyte recruitment in response to lipopolysaccharide compared to cmo/MC- and wild-type mice. Together, these results implicate mast cells in promoting leukocyte recruitment to inflamed tissues during autoinflammatory disease progession, and suggest that therapies targeting mast cells or their mediators may benefit CRMO patients.

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)0.002
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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.688
Threshold uncertainty score0.358

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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)0.0000.000

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 head0.019
GPT teacher head0.264
Teacher spread0.245 · 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 designObservational
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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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