Effect of dexamethasone, 2-bromopalmitate and clofibrate on L-FABP mediated hepatoma proliferation
Bibliographic record
Abstract
Cytosolic liver fatty acid binding protein (L-FABP) is involved in many intracellular functions including cellular mitogenesis. We investigated the role of L-FABP and the plasma membrane liver fatty acid binding proteins (L-FABP(pm)) in the modulation of hepatoma growth and proliferation, hypothesizing that agents that affect either the content of, or ligand binding to, L-FABP would affect hepatocellular mitogenesis. L-FABP expressing 1548-rat hepatoma cells were treated with 0.5 microM dexamethasone or 500 microM clofibrate for 4 days to downregulate and upregulate L-FABP expression, respectively. The competitive inhibitor 2-bromopalmitate (BrPA, 600 microM) was used to inhibit ligand binding to L-FABP. The peripherally present plasma membrane fatty acid transporter was inactivated by treating cells with 1:50 rabbit antisera (FABP-Ab) raised against L-FABP. Western blot analysis was used to monitor L-FABP levels while [(3)H]-thymidine incorporation and growth curves were used to monitor hepatocellular proliferation. [(3)H]-Palmitate clearance studies were performed using monolayer cultures. Palmitate clearance in dexamethasone-, BrPA- and FABP-Ab-treated cells was significantly reduced when compared with control (P < 0.05), while clofibrate treatment moderately increased the rate. [(3)H]-Thymidine incorporation by dexamethasone- and BrPA-treated cells was significantly lower than control (P < 0.05), suggesting that hepatocellular proliferation was inhibited. Clofibrate treatment did not statistically affect growth rate. Lowering L-FABP using dexamethasone or interfering with its activity using BrPA significantly affected hepatocellular proliferation. This may be due to the non-availability of long-chain fatty acids or other intracellular mediators that are transported by L-FABP to the nucleus.
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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 | 0.000 |
| 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) | 0.001 | 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".