A simple and fast method for the enrichment of lymphoid progenitors from mouse bone marrow (153.9)
Bibliographic record
Abstract
Abstract The expression of IL-7Rα in the common lymphoid progenitor (CLP) population marks initiation and/or commitment to the lymphoid lineage. CLPs hold potential for only B, T and NK cell lymphoid lineages and are defined as Lin−IL-7Rα+c-KitloSca-1lo. Study of lymphocyte development largely relies on access to CLPs or other IL-7Rα+ lymphoid progenitors. Fluorescence-activated cell sorting (FACS) commonly used to isolate lymphoid progenitors is costly, time-consuming and possibly detrimental to cell viability. We describe a fast and efficient method for the isolation of lymphoid progenitors from mouse bone marrow (BM). This method is based on immunomagnetic, column-free cell separation technology (EasySepTM). Using this method, lineage positive cells are first depleted by cross-linking them to magnetic particles using biotinylated antibodies. Next, IL-7Rα+ cells are positively selected from the Lin−/lo population. After enrichment, average purity of Lin−IL-7Rα+ lymphoid progenitors as assessed by flow cytometry is 32 ± 10% (n=18). Lin−IL-7Rα+c-KitloSca-1lo cells are enriched 60-fold from 0.08 ± 0.05% in start BM to 4.6 ± 2.5%. Limiting dilution analysis of enriched cells shows increased frequencies of B cell (1:73, n=12), T cell (1:16, n=5) and NK cell (1:65, n=6) progenitors as compared to non-depleted control BM. This system introduces an easy method for the enrichment of lymphoid progenitors with good viability that will enable study of developmental immunology.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.012 |
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".