Exposure to low doses of Dechlorane Plus promotes adipose tissue dysfunction and glucose intolerance in mice
Bibliographic record
Abstract
The prevalence of type 2 diabetes (T2D) continues to increase worldwide. It is well established that genetic susceptibility, obesity, overnutrition and a sedentary life style are risk factors for the development of T2D. However, more recently, studies have also proposed links between exposure to endocrine-disrupting chemicals (EDCs) and altered glucose metabolism. Human exposure to environmental pollutants suspected to have endocrine disruptor activity is ubiquitous. One such chemical is Dechlorane Plus, a flame retardant, that is now detected in humans and the environment. Here we show that exposure of mice to low, environmentally relevant doses of Dechlorane Plus (DP), promoted glucose intolerance in mice fed high fat diet independent of weight gain. Further, DP had pronounced effects on the adipose tissue, where it induced the development of hypertrophied white adipose tissue (WAT), and increased serum levels of resistin, leptin, and plasminogen activator inhibitor-1. Further, DP exposure induced “whitening” of brown adipose tissue (BAT), and reduced BAT uncoupling protein 1 expression. Importantly, some of these effects occurred even when the mice were fed regular, low fat, diet. Finally, WAT adipogenic markers were reduced with DP treatment in the WAT. We also show that, DP directly inhibited insulin signalling in murine adipocytes and human primary subcutaneous adipocytes in vitro. Taken together, our results show that the exposure to low and environmentally relevant levels of DP may contribute to the development of T2D.
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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 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".