Efficient isolation of highly purified tonsil B lymphocytes using RosetteSep with allogeneic human red blood cells
Bibliographic record
Abstract
BACKGROUND: Human tonsils are a rich source of B lymphocytes exhibiting a variety of phenotypes and activation states. Existing methods of purification are time consuming or costly. The aim of the present study was to optimize conditions to isolate large numbers of highly purified primary B lymphocytes from tonsils in a short and cost-effective single step, using a commercially available reagent designed for purifying cells from whole blood (RosetteSep). This technique relies on the presence of the large excess of red blood cells in whole blood for the formation of immunorosettes, whereas single cell suspensions from tonsils contain relatively few red blood cells. RESULTS: B cell enrichment from tonsils was achieved using RosetteSep with no modification to the whole blood procedure; however, the degree of purity depended on the extent of red blood cell contamination of the starting tonsil cell suspension. Addition of a 50-fold excess of allogeneic human red blood cells, but not sheep red blood cells, reproducibly resulted in high levels of purity. Depletion of mononuclear cells from the donor red blood cells eliminated potential contamination with allogeneic B cells. CONCLUSION: RosetteSep reagent can be used in combination with allogeneic human red blood cells to reproducibly isolate tonsil B lymphocytes to high levels of purity with no change in phenotype or loss of cells. This method provides considerable time and cost savings compared to other methods.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.002 |
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".