Intracellular flow cytometry staining of antibody-secreting cells using phycoerythrin-conjugated antibodies: pitfalls and solutions
Bibliographic record
Abstract
Background: Antibody-secreting cells are terminally differentiated B cells that play a critical role in humoral immunity through immunoglobulin secretion along with possessing the potential to be long-lived. It is now appreciated that ASCs regulate multiple aspects of biology through the secretion of various cytokines. In this regard, ICFC is a key tool used to assess the presence of intracellular proteins such as cytokines and transcription factors. Methods: Paraformaldehyde plus saponin or the eBioscience Foxp3/Transcription Factor Staining Buffer Set were used to evaluate the non-specific intracellular retention of phycoerythrin-containing antibody conjugates by ASCs. Results: We showed that the use of phycoerythrin-containing antibody conjugates led to a false interpretation of ASC intracellular protein expression compared with other cell types. This was mainly due to the inappropriate retention of these antibodies specifically within ASCs. Furthermore, we demonstrated how to reduce this retention which allowed for a more accurate comparison of intracellular protein expression between ASCs and other cell types such as B lymphocytes. Using this methodology, our data revealed that spleen ASCs expressed toll-like receptor 7 as well as the pro-form of the inflammatory cytokine interleukin-1β. Conclusion: Increasing the number of centrifugation steps performed on ASCs post-fixation leads to inappropriate retention of phycoerythrin-containing antibody conjugates during ICFC.
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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 | 0.004 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".