A Functional Assay to Assess Toxicity During Murine B Cell Development In Vitro
Bibliographic record
Abstract
B lymphocytes, or B cells, are important players in immunity that produce antigen-specific immunoglobulins. As a result, they are involved in various immune-linked pathologies. To better understand, prevent, or treat B cell-associated disease and immunotoxicity, we developed an in vitro assay to model early murine B cell differentiation within the bone marrow. This model uses sorted B cell precursors cultured on a supporting stromal cell layer, which over time acquire markers of further differentiated B cells, such as surface antigens and rearranged immunoglobulin light chain. Importantly, we utilized our in vitro model to validate our previous observations that xenobiotics, such as tungsten and organotins, alter B cell development in vivo. Furthermore, gene expression can be modulated in this model using retroviral transduction, making it amenable to investigating signaling pathways involved in disruption of B cell differentiation. © 2019 by John Wiley & Sons, Inc. Basic Protocol: Assessment of early B lymphocyte differentiation in vitro Support Protocol: Isolation of murine bone marrow Alternate Protocol 1: Addition of recombinant interleukin-7 Alternate Protocol 2: Genetic manipulation via retroviral transduction.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.004 |
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".