Column-free isolation of untouched mouse plasmacytoid dendritic cells (P4149)
Bibliographic record
Abstract
Abstract Plasmacytoid dendritic cells (pDC) are a DC subset distinct from conventional dendritic cells (cDC) in that they are able to produce large amounts of type I interferon (IFN) after challenge with pathogens. Viruses activate pDC mainly through Toll-like receptors (TLR). Unlike cDC, pDC are poor antigen-presenting cells. In line with the functional differences, pDC express lower levels of CD11c and MHCII as compared to cDC. Moreover, a number of markers expressed by pDC are absent on cDC including: PDCA-1, Siglec-H, B220 and Ly-6C. pDC are found in both lymphoid and non-lymphoid organs. Here, we describe a negative selection method to isolate untouched pDC from mouse spleen. This method uses an immunomagnetic, column-free cell separation technology (EasySepTM). Briefly, single cell suspensions of splenocytes are labeled with biotinylated antibodies against non-pDC. Bi-specific antibody complexes against biotin and dextran are used to cross-link non-pDC with dextran-coated magnetic particles. The unwanted cells are then removed using an EasySepTM magnet. The procedure can be automated using RoboSepTM. Starting with 0.4±0.2% CD11c+PDCA-1+ pDC in spleen, purities of 79±9% (n=21) are achieved. The isolated pDC are functional and produce IFN-α in response to TLR9 ligand, ODN-1585 as measured in ELISA. pDC play an important role in anti-viral immunity and autoimmunity, therefore the isolation of untouched pDC is critical in studies examining their role in these immune responses.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.003 |
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".