Age and sex influence cultured rodent mast cell and basophil responses to antigen
Bibliographic record
Abstract
Abstract Mast cells initiate allergic inflammatory immune responses and play a role in disease by releasing various inflammatory and immunomodulatory mediators. Several mast cell-lines and primary cultured cells have been used as mast cell models with inconsistent results among research groups. Bone marrow-derived mast cells (BMMC) cultured from mouse bone marrow progenitor cells are often used as a representative model of mucosal mast cell behaviour, however their reported phenotype is variable due to inconsistent culture protocols. RBL-2H3 is a rat basophilic histamine-releasing cell line that has some characteristics of both mast cells and basophils but is not a true representation of either cell type. The murine mast cell line MC/9 is an IL-3-dependent mucosal mast cell model but has limited mast cell characteristics. In this study, we have compared the response of BMMC (derived from C57BL/6 male or female mice), two sources of RBL-2H3 (purchased directly from ATCC and a lab curated culture), and MC/9 (ATCC) at several critical stages to some common stimuli (IgE/Ag, A23187) and analyzed mast cell morphology, expression level of common mast cell surface markers (CD117 and FcɛRI), protease expression, and function (growth kinetics, viability, ROS production, degranulation, cytokine release and FcɛRI signaling). The objective of this study was to provide insight into the effects of culture conditions, biological sex, and age of the cells on variability among reported phenotypes and, to determine optimal conditions for activation of these cells. Factors that are often overlooked such as source, age and biological sex of mast cells play an integral role in phenotypic outcomes and may account for the reported variability in their function. National Research Council Canada
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".