A simple and fast method for the isolation of mouse lymphoid progenitors from bone marrow (36.6)
Bibliographic record
Abstract
Abstract Lymphocytes are derived from hematopoietic stem cells through an important developmental intermediate called a common lymphoid progenitor (CLP). CLPs are defined as Lin−IL-7Rα+c-KitloSca-1lo. They can differentiate into T, B, and natural killer (NK) cells but lack myeloid and erythroid potential. Study of lymphocyte development largely relies on access to this rare cell population. Fluorescence-activated cell sorting (FACS) commonly used to isolate CLPs is costly, time-consuming and perhaps most importantly detrimental to the cell viability and function. We describe a fast and efficient method for the isolation of CLPs from mouse bone marrow (BM). This method is based on immunomagnetic, column-free cell separation technology (EasySep). Using this method, lineage positive cells were first depleted by cross-linking them to magnetic particles using biotinylated antibodies. Next, IL-7Rα+ cells were positively selected from the Lin−/lo population. Purity of Lin−IL-7Rα+c-Kit+ lymphoid progenitors as assessed by flow cytometry ranged from 18-41%. Limiting dilution analysis of the EasySep enriched cells showed increased frequencies of B cell (1:25), T cell (1:6) and NK cell (1:49) progenitors as compared to non-depleted control BM. This system introduces a rapid and easy method for the enrichment of rare CLPs with greater yield than cell sorting and good viability. This will enable research in the field of cellular, molecular and 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.008 |
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".