Increasing cell membrane potential and GABAergic activity inhibits malignant hepatocyte growth
Bibliographic record
Abstract
Increasing hepatocyte membrane potentials by augmenting GABAergic activity inhibits nonmalignant hepatocyte proliferative activity. The objectives of this study were to document 1) potential differences (PDs) of four malignant hepatocyte cell lines, 2) GABAA receptor mRNA expression in the same cell lines, and 3) effects of restoring malignant hepatocyte PDs to levels approximating those of resting, nonmalignant hepatocytes. Hepatocyte PDs were documented in nonmalignant and malignant (Chang, HepG2, HuH-7, and PLC/PRF/5) hepatocytes with a fluorescent voltage-sensitive dye and GABAA receptor expression by RT-PCR and Western blot analyses. Compared with nonmalignant human hepatocytes, all four malignant cell lines were significantly depolarized (P < 0.0001, respectively). Only PLC/PRF/5 cells had detectable GABAA-beta3 receptor mRNA expression and all cell lines were negative for GABAA-beta3 receptor protein by Western blot analysis. Stable transfection of Chang cells with GABAA-beta3 receptor cDNA resulted in significant increases in PD and decreases in proliferative activity as manifest by decreased [3H]thymidine and bromodeoxyurieine incorporation rates, 4-[3-(4-lodophenyl)-2-(4-nitrophenyl)-2H-5-tetrazolio]-1,3-benzene disulfonate activity, a lower mitotic index, prolongation of cell-doubling times, and attenuated growth patterns compared with cells transfected with vector alone. Colony formation in soft agar and the number of abnormal mitoses were also significantly decreased in GABAA-beta3 receptor transfected cells. The results of this study indicate 1) relative to healthy hepatocytes, malignant hepatocytes are significantly depolarized, 2) GABAA-beta3 receptor expression is absent in malignant hepatocyte cell lines, and 3) increasing the PD of malignant hepatocytes is associated with less proliferative activity and a loss of malignant features.
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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".