Effects of PCB126 on the Development of Non Alcoholic Fatty Liver Disease
Bibliographic record
Abstract
Persistent organic pollutants (POPs), are chemicals that were mostly used historically as pesticides, solvents, flame retardants, and other applications. Among POPs, polychlorinated biphenyls (PCB) have been recognized to be of environmental and potential toxicologic concerns. Specifically, PCB126 could act as endocrine disruptors and have recently been associated with hepatic fat accumulation. Fatty liver results from alteration in lipid synthesis and elimination mechanisms such as very low density lipoprotein (VLDL) production and de novo lipogenesis. The purpose of the study was to investigate the effects of PCB126 on the molecular development of non‐alcoholic fatty liver disease (NAFLD) in animals. Male sprague‐Dawley (275‐300g) were injected with a single dose of PCB126 (1 ug/kg) or Corn Oil (control group). Seven days later, liver triglyceride (TAG) content was measured along with protein quantification of microsomal triglyceride transfer protein (MTP) and sterol regulatory element binding protein 1c (SREBP1c). Results Exposure to PCB126 resulted in significant increases of hepatic TAG concentrations (64%, P <0.001) in rats compared to respective control groups. Rats with fatty livers depicted lower MTP (40%, P <0.02) and higher SREBP1c (27%, P < 0.05) protein content levels compared to Placebo group in rats. Conclusion It seems that exposure to PCB126 has an important emerging role in the pathophysiology of NAFLD by 1) altering elimination mechanisms such as VLDL synthesis and secretion, mainly through MTP; and 2) increasing hepatic TAG synthesis mechanisms through SREBP1c.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".