Long-term docosahexaenoic acid therapy in a congenic murine model of cystic fibrosis
Bibliographic record
Abstract
We used a congenic C57Bl/6J cystic fibrosis transmembrane conductance regulator (Cftr)(-/-) mouse model, which develops cystic fibrosis (CF)-like pathology in all organs, to evaluate the short- and long-term therapeutic effects of dietary docosahexaenoic acid (DHA). Thirty-day-old Cftr(-/-) mice and wild-type littermates were randomized to receive a liquid diet with or without DHA (40 mg/day). Animals were killed for histological and lipid analysis after 7, 30, and 60 days of therapy. DHA had no significant therapeutic or harmful effect on the lung, pancreas, or ileum of the Cftr(-/-) mice or their wild-type littermates. In contrast, dietary DHA resulted in highly significant amelioration of the severity of liver disease in the Cftr(-/-) mice, primarily a reduction in the degree of peri-portal inflammation. Additionally, these detailed measurements confirm our previous findings that Cftr(-/-) mice have significant alterations in the pancreas (except external acinar diameter), ileum, liver, lung, and salivary (except sublingual) glands at all ages compared with their age-matched wild-type littermates. In conclusion, inhibition of cytokines and/or eicosanoid metabolism and release of endogenous inhibitors of inflammation by DHA may account for the anti-inflammatory effects in the liver of this congenic murine model of CF. The potential therapeutic benefits of DHA in severe CF-associated liver disease remain to be explored.
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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 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| 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".