MétaCan
Menu
Back to cohort
Record W6999430282

Contributions of mitogen-activated protein kinase signaling on mast cell differentiation and allergic phenotype

2021· other· en· W6999430282 on OpenAlexafffund

Bibliographic record

VenueBrock University Digital Repository (Brock University) · 2021
Typeother
Languageen
Field
Topic
Canadian institutionsNiagara Health System
FundersNatural Sciences and Engineering Research Council of CanadaBrock UniversityGovernment of Ontario
KeywordsMast cellMAPK/ERK pathwayInterleukin 33Protein kinase AImmunoglobulin ESignal transductionKinasep38 mitogen-activated protein kinasesCellular differentiationAllergic inflammation
DOInot available

Abstract

fetched live from OpenAlex

Introduction: Mast cells are large granulated immune cells, and major drivers of allergic inflammation. Increased inflammatory activity and numbers of mast cells contribute to allergic disease, which is of increasing concern worldwide. Mast cells are derived from hematopoietic stem cells, which are found in the bone marrow. Specifics regarding the molecular mechanisms that control mast cell differentiation remain largely undiscovered. The mitogen activated protein kinase (MAPK) pathway is a highly evolutionarily conserved intracellular signaling pathway that is active in all eukaryotic cells. We sought to evaluate the role of the three major nodes of the MAPK pathway—JNK, ERK, and p38—in IL-3-mediated mast cell differentiation. Methods: Bone marrow-derived mast cell (BMMC) cultures were initiated from the bone marrow of C57BL/6 mice and differentiated in the presence of MAPK inhibitors. One group received 1 µM of JNK inhibitor JNK-IN-8, another 1 µM of the ERK inhibitor SCH772984, another 10 µM of the p38 inhibitor Losmapimod. The control group received no inhibitor. The β-hexosaminidase release assay was used to assess mast cell degranulation; enzyme-linked immunosorbent assay (ELISA) was used to measure cytokine secretion; and flow cytometry was used to measure marker and receptor expression. Results: In the JNK group, cells exhibited a reduced capability to degranulate, a down-regulation in IL-13, CCL1, CCL2, and an up-regulation in basal CCL9 secretion. In the ERK group, mast cells secreted decreased amounts of CCL2, increased amounts of CCL3, and down-regulated c-kit expression on the cell surface. In the p38 group, mast cells exhibited an increased capability to degranulate, secreted lower amounts of CCL1 and CCL2, and exhibited increased c-kit expression on the cell surface. Conclusion: Overall, JNK inhibition negatively affects both the early and late phases of allergic inflammation, ultimately producing an impaired inflammatory phenotype. ERK inhibition affects the late phase of allergic inflammation and cell surface receptor expression. p38 inhibition affects both the early and late phases of allergic inflammation, as well as cell surface receptor expression. This research contributes to the fundamental biological understanding of mast cell differentiation and may drive the development of future therapeutics for allergic disease.

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 score0.004
Threshold uncertainty score0.013

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.001

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 head0.180
Teacher spread0.171 · 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

Citations0
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueBrock University Digital Repository (Brock University)French-language works237,207