Flow Cytometry Assessment of In Vitro Generated CD138<b><sup>+</sup></b>Human Plasma Cells
Bibliographic record
Abstract
The in vitro CD40-CD154 interaction promotes human B lymphocytes differentiation into plasma cells. Currently, CD138 is the hallmark marker enabling the detection of human plasma cells, both in vitro and in vivo; its presence can be monitored by flow cytometry using a specific antibody. We have developed a culture system allowing for the differentiation of memory B lymphocytes. In order to detect the newly formed plasma cells, we have compared their staining using five anti-CD138 monoclonal antibodies (mAbs). As a reference, we also tested human cell lines, peripheral blood mononuclear cells, and bone marrow samples. The five anti-CD138 mAbs stained RPMI-8226 cells (>98%) with variable stain index (SI). The highest SI was obtained with B-A38 mAb while the lowest SI was obtained with DL-101 and 1D4 mAbs. However, the anti-CD138 mAbs were not showing equivalent CD138(+) cells frequencies within the generated plasma cells. B-A38, B-B4, and MI-15 were similar (15-25%) while DL-101 mAb stained a higher proportion of CD138-positive cells (38-42%). DL-101 and B-A38 mAbs stained similar populations in bone marrow samples but differed in their capacity to bind to CD138(high) and CD138(lo) cell lines. In conclusion, such cellular fluctuations suggest heterogeneity in human plasma cell populations and/or in CD138 molecules.
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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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".