Cryopreserved Interleukin-4-Treated Macrophages Attenuate Murine Colitis in an Integrin β7-Dependent Manner
Bibliographic record
Abstract
The adoptive transfer of alternatively activated macrophages (AAMs) has proven to attenuate inflammation in multiple mouse models of colitis; however, the effect of cryopreservation on AAMs, the ability of previously frozen AAMs to block dinitrobenzene sulfonic acid (DNBS) (Th1) and oxazolone (Th2) colitis and their migration postinjection remains unknown. Here we have found that while cryopreservation reduced mRNA expression of canonical markers of interleukin (IL)-4-treated macrophages [M(IL-4)], this step did not translate to reduced protein or activity, and the cells retained their capacity to drive the suppression of colitis. The anticolitic effect of M(IL-4) adoptive transfer required neither T or B cell nor peritoneal macrophages in the recipient. After injection into the peritoneal cavity, M(IL-4)s migrated to the spleen, mesenteric lymph nodes and colon of DNBS-treated mice. The chemokines CCL2, CCL4 and CX3CL1 were expressed in the colon during the course of DNBS-induced colitis. The expression of integrin β7 on transferred M(IL-4)s was required for their anticolitic effect, whereas the presence of the chemokine receptors CCR2 and CX3CR1 were dispensable in this model. Collectively, the data show that M(IL-4)s can be cryopreserved M(IL-4)s and subsequently used to suppress colitis in an integrin β7-dependent manner, and we suggest that these proof-of-concept studies may lead to new cellular therapies for human inflammatory bowel disease.
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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) | 0.001 | 0.000 |
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".