Protective Effect of Curcumin in an F1-Hybrid Model of Acute Graft-vs.-Host Disease.
Bibliographic record
Abstract
Abstract Curcumin (diferuloylmethane), a pigment from the rhizomes of Curcuma Longa, has anti-oxidant, anti-tumor and anti-inflammatory properties. It has been shown that curcumin can inhibit the development of experimental allergic encephalomyelitis, a Th1-mediated, autoimmune, demyelinating disease that affects the central nervous system in mice. Because acute GVHD involves the development of a Th1-mediated immune response, and is characterized by the development of a potent, systemic, inflammatory response, we wished to determine whether curcumin might also protect mice from developing acute GVHD in the C57BL/6→(C57BL/6 x DBA/2)F1-hybrid model. We found that ip injections of curcumin (100 micrograms dissolved in 25 microliters of DMSO), given once a day, every 2 days, protected recipients from developing acute, lethal GVHD. Two thirds of the treated group survived well past day 100 post-transplantation. Control GVH mice treated with DMSO alone became moribund within three weeks of transplantation, the time at which mice with acute GVHD typically succumb. To ensure that the protective effects of curcumin were not due to abortion of the graft, we analyzed T cell engraftment in some of the long-term survivors. In the surviving mice tested on days 135 and 275 post-transplantation, we were unable to detect any cells of recipient origin in the spleen. Furthermore, the percentage of donor-derived CD4+ cells ranged from 32–47% and the percentage of CD8+ T cells ranged from 25–42% in the non-adherent spleen cell fraction. Data from these experiments suggest that curcumin can protect mice from developing acute, lethal GVHD.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".