Low-Fat, High Fruit and Vegetable Diets and Weight Loss Do Not Affect Biomarkers of Cellular Proliferation in Barrett Esophagus
Bibliographic record
Abstract
Risk factors for esophageal adenocarcinoma include obesity, high fat intake, and low consumption of fruits and vegetables. This trial tested whether an intervention to reduce these risk factors in patients with Barrett esophagus, a preneoplastic condition for esophageal adenocarcinoma, could reduce biomarkers of cellular proliferation and, by inference, the risk of neoplastic progression. Eighty-seven men and women with Barrett esophagus were randomized to an intensive dietary intervention or control group. At baseline, 18 and 36 months after intervention, biopsies were obtained at 2-cm intervals throughout the length of the Barrett segment. Ki67/DNA content flow cytometry was used to assess (a) % Ki67-positive proliferating diploid G(1) cells, (b) % total Ki67-positive proliferating cells, (c) presence of aneuploidy, and (d) presence of >6% of cells in the 4N (G(2)/tetraploid) fraction of the cell cycle. We also assessed re-epithelialization and length of the Barrett segment, reflux symptoms, and medication use. The intervention effects for energy, fat, fruits and vegetables, and weight were, respectively, -314 kcal, -12.2% energy, 1.8 servings/d, and -4.0 kg at 18 months (all P < 0.005) and were smaller but remained significant at 36 months. There were no significant effects of the intervention on any biomarker of cellular proliferation. The intervention effects +/- SE for mean %G(1) Ki67+ cells were 0.98 +/- 1.58 at 18 months and 1.79 +/- 1.31 at 36 months; the relative risks (95% confidence interval) for developing >6% of cells in 4N were 0.5 (0.1-2.6) at 18 months and 0.75 (0.2-3.1) at 36 months. A single control participant developed aneuploidy. There were no significant effects on re-epithelialization, segment length, or reflux medication use. We conclude that substantial dietary change has no short-term effects on biomarkers of cellular proliferation in Barrett esophagus or on clinical observations of the Barrrett segment.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".