Osmotic regulation of hepatic betaine metabolism
Bibliographic record
Abstract
Betaine critically contributes to the control of hepatocellular hydration and provides protection of the liver from different kinds of stress. To investigate how the hepatocellular hydration state affects gene expression of enzymes involved in the metabolism of betaine and related organic osmolytes, we used quantitative RT-PCR gene expression studies in rat hepatoma cells as well as metabolic and gene expression profiling in primary hepatocytes of both wild-type and 5,10-methylenetetrahydrofolate reductase (MTHFR)-deficient mice. Anisotonic incubation caused coordinated adaptive changes in the expression of various genes involved in betaine metabolism, in particular of betaine homocysteine methyltransferase, dimethylglycine dehydrogenase, and sarcosine dehydrogenase. The expression of betaine-degrading enzymes was downregulated by cell shrinking and strongly induced by an increase in cell volume under hypotonic conditions. Metabolite concentrations in the culture system changed accordingly. Expression changes were mediated through tyrosine kinases, cyclic nucleotide-dependent protein kinases, and JNK-dependent signaling. Assessment of hepatic gene expression using a customized microarray chip showed that hepatic betaine depletion in MTHFR(-/-) mice was associated with alterations that were comparable to those induced by cell swelling in hepatocytes. In conclusion, the adaptation of hepatocytes to changes in cell volume involves the coordinated regulation of betaine synthesis and degradation and concomitant changes in intracellular osmolyte concentrations. The existence of such a well-orchestrated response underlines the importance of cell volume homeostasis for liver function and of methylamine osmolytes such as betaine as hepatic osmolytes.
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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".