2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) and early human pancreatic development
Bibliographic record
Abstract
Environmental factors such as pollutants are associated with diabetes incidence. Of particular interest is exposure to persistent organic pollutants (POPs) during critical stages of fetal development. TCDD (2,3,7, is a potent ligand of the aryl hydrocarbon receptor, which leads to induction of cytochrome P450 (CYP) 1A1 enzymes. We hypothesize that POPs such as TCDD accumulate in the pancreas, thereby eliciting stress on developing beta cells through induction of CYP1A1. Here, I exposed rodent alpha and beta cell lines to TCDD in vitro, but did not observe induction of Cyp1a1 gene expression or enzyme activity, meaning that this pathway is not activated in immortalized pancreatic endocrine cell lines. I also differentiated human embryonic stem cells toward pancreatic cell fate in vitro to study how TCDD exposure impacts human beta cell development. I concluded that TCDD might impede normal development of beta cells, potentially through induction of CYP1A1 and other embryonic lineages. I would firstly like to acknowledge my supervisor, Dr. Jenny Bruin, for her support and guidance throughout my project, on-going patience and understanding toward the struggles of stem cell culture, and encouragement through my endless troubleshooting. Thank you to the rest of the Bruin lab members, particularly Kayleigh Rick and Myriam Hoyeck, for occasional scientific support and frequent emotional support. This venture would have been much less enriching without you.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".