Dendritic Cells Derived from Murine Colonic Mucosa Have Unique Functional and Phenotypic Characteristics
Bibliographic record
Abstract
Dendritic cells (DCs) residing in different tissues and exposed to different organisms are likely to have different reactivities to their surrounding environment. Many studies use in vitro generated DCs to examine functions of these cells, but such cells may not truly reflect the nature of DCs and their in situ activities in vivo. We have used magnetic label-based technique to isolate colonic DCs to conduct derailed characterization of these cells. Colonic DCs comprise mainly CD11b+ DCs with few CD8alpha+ DCs or plasmacytoid DCs. Functionally, isolated colonic DCs are able to endocytose and process proteins, undergo maturation, and stimulate T cells to proliferate. Importantly, expression of TLRs by colonic DCs is significantly lower than that of their spleen counterparts; however, they appear to be as, or more, responsive to stimulation by oligodeoxynucleotides containing CpG motif based on their cytokine production. We speculate that colonic DCs have unique reactivities differing from DCs residing in other lymphoid tissues and are adapted for the unique microenvironment of the colonic mucosa and that these cells react uniquely to their environment.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".