Development and evaluation of a terrestial food web bioaccumulation model
Bibliographic record
Abstract
We previously showed that green tea polyphenols (GTPs) exert antiadipogenic effects on preadipocyte proliferation. Here, we investigated the regulatory effects of GTPs on osteogenesis and adipogenesis during early differentiation of human adipose tissue-derived stem cells (hADSC). Adipogenesis of hADSCs was determined by oil-red-O staining and triglycerides synthesis measurement. Osteoporosis of hADSC was measured using alkaline phosphatase assays and intracellular calcium levels. Immunofluorescence staining and qRT-PCR were used to detect PPARγ-CEBPA regulated adipogenic pathway regulated by PPAR-CEBPA and the osteogenic pathway mediated by RUNX2-BMP2. We found that GTPs treatment significantly decreased lipid accumulation and cellular triglyceride synthesis in mature adipocytes and attenuated pioglitazone-induced adipogenesis in a dose-dependent manner. GTPs downregulated protein and mRNA expression of <i>Pparγ</i> and attenuated pioglitazone-stimulated-<i>Cebpa</i> expression. GTPs treatment significantly enhanced hADSCs differentiation into osteoblasts compared to control and pioglitazone-treated cells. GTPs upregulated RunX2 and Bmp2 proteins and mRNA expression compared to control and significantly attenuated decreased RunX2 and Bmp2 mRNA expression by pioglitazone. In conclusion, our data demonstrates GTPs possesses great ability to facilitate osteogenesis and simultaneously inhibits hADSC differentiation into adipogenic lineage by upregulating the RUNX2-BMP2 mediated osteogenic pathway and suppressing PPARγ-induced signaling of adipogenesis. These findings highlight GTPs' potential to combat osteoporosis associated with obesity.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".