Inhibition of Cell Division in Mouse B-Cell Hybridomas: An Overlooked Property of 2-Mercaptoethanol and Its Impact on <i>in vitro</i> Antibody Production
Bibliographic record
Abstract
Thiol 2-mercaptoethanol (2-ME) has been reported to enhance growth in lymphocytes by various investigators. Some have used 50 μM for growing hybridomas in vitro. Concentrations of 50 and 5 μM in 5% FBS supplemented D-MEM were tested to determine their effects on the growth of 5 monoclonal antibody secreting mouse B cell hybridomas and the myeloma Sp2/O-Ag14. Viability after 24 and 48 h exposure was determined by Trypan blue exclusion. Analysis by one-way ANOVA confirmed that 50 μM 2-ME has a significant negative impact (p<0.05) on hybridoma as well as on myeloma growth, whereas no significant difference (p>0.05) between the control and the 5 μM treatment group was observed after 48 h. Also, no significant difference (p>0.05) in the mortality rates between the control and the treatment groups was found. When combined with the observed protracted doubling time in the 50 μM treatment group, these results indicate that the impact of 2-ME is due to inhibition of cell division. The degree of inhibition was observed to vary between the different hybridomas as well as the myeloma. Although the impact of 2-ME on mitosis has been demonstrated in organisms such as the ciliated protozoan Tetrahymena pyriformis, the yeast Saccharomycess cerevisiae, and the egg of the echinoid the sand dollar Dendraster excentricus, this work demonstrates for the first time that 2-ME impedes the growth of mouse B cell hybridomas. We conclude that adding 2-ME to mouse B cell hybridoma growth media may not be beneficial.
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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) | 0.001 | 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 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".