Tungsten-altered pre-B lymphocyte development correlates with downregulation of interleukin-7 receptor signaling
Bibliographic record
Abstract
Tungsten is a metal with desirable properties, including strength and flexibility. Increased use of tungsten has resulted in higher risk of human exposure. Recently, high levels of tungsten were identified in the drinking water near three pediatric leukemia clusters, yet the contribution of tungsten to the development of leukemia has not been defined. After an oral exposure of tungsten over 16 weeks, tungsten rapidly accumulated in the bones of mice in a dose-dependent manner. Tungsten exposure correlated with an accumulation of pre-B cells (fraction CC') and increased DNA damage within the bone marrow. In order to understand the underlying molecular changes caused by tungsten that result in altered B cell differentiation, we sorted this pre-B cell fraction by flow cytometry and profiled whole transcriptome gene expression by RNA-Seq from mice with and without a 4-week exposure to 15 ppm tungsten. Interestingly, tungsten down-regulated the expression of multiple genes known to be master regulators of B cell commitment and development. Tungsten suppressed both the IL-7R and preBCR receptor signaling. These pathways are critical for B cell differentiation at the pre-B cell differentiation checkpoint, suggesting that tungsten may be stalling B cell differentiation at this point. Down-regulation of IL-7R and preBCR signaling were validated in 2 independent RNA samples by qRT-PCR including IL-7R and PreBCR downstream targets: Jak1, Stat5, Ebf1, Pax5, Syk and Ikzf3 (Aiolos). In order to study these signaling pathways and their contribution to tungsten's effects on B cell differentiation, we developed an in vitro primary cell culture model of B cell differentiation. We isolated early B cells from murine bone marrow by Cell sorting and differentiated them in vitro. At the end of the experiment, B cell differentiation was monitored by flow cytometry, using a developed multi-parameter flow cytometry panel based on unique surface makers expressed at each stage of development. Tungsten halted B cell differentiation at the B to C transition check point. In addition, this shift in B cell differentiation was associated with decreased expression of IL-7 receptor on the cell surface and phosphorylated STAT5 levels. Based on our data, tungsten may not be an inert metal as previously described, but may alter B cell lymphopoiesis by downregulating B cell signaling and potentially, act as a tumor promoter by stalling B cells in an early stage of development, where cells are vulnerable to DNA damage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
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 teacher head, 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".