The Roles of GPD1 in Maintaining Blood Glucose Levels under Fasting Conditions
Bibliographic record
Abstract
Glucose is used as one of the energy sources in many organs. Under feeding conditions, glucose can be obtained from dietary carbohydrate. On the other hand, when external supply of energy is interrupted, such as fasting, carbohydrate preserved in liver and glycogenic precursor derived from other organs are used to maintain blood glucose levels. Glycerol and glycogenic amino acid derived from adipocyte and skeletal muscle, respectively, are utilized as glycogenic precursor. But, it hasn't become clear which glycogenic precursor is more important in gluconeogenesis. The recent study revealed that Metformin, therapeutics for treating type 2 diabetes, depressed gluconeogenesis from glycerol by inhibition of glycerol‐3‐phosphate dehydrogenase (GPD) 2. This result suggests that glycerol have a potent impact on gluconeogenesis. In this study, we focused attention on GPD1, which is the enzyme that related gluconeogenesis using glycerol, and examined the roles of GPD1 in gluconeogenesis and importance of glycerol as glycogenic precursor. Using GPD1 null mutant model BALB/cHeA mice (HeA mice), we measured the change of blood glucose levels under fasting conditions and gene expressions related to gluconeogenesis in liver. BALB/cBy mice (By mice) were used as a control. In HeA mice, blood glucose levels at 1 to 4 hour after fasting were significantly higher than the By mice. The hepatic gene expressions involved in gluconeogenesis and aminotransferase such as glucose‐6‐phosphatase and alanine amino transferase were also higher than the By mice. Moreover, we examined availability of the glycogenic amino acid by alanine tolerance test. At 30 min after alanine administration, blood glucose level was significantly higher in the HeA mice. In short, these data suggests that lacking of GPD1 maintained blood glucose levels under fasting state by enhancing gluconeogenesis from glycogenic amino acid and release of glucose into the blood stream. Support or Funding Information This study was supported by the Council for Science, Technology and Innovation (CSTI), Cross‐ministerial Strategic Innovation Promotion Program (SIP, No.14533567), and “Technologies for creating next‐generation agriculture, forestry and fisheries” (funding agency: Bio‐oriented Technology Research Advancement Institution, NARO), Grants‐in‐Aid for Scientific Research (KAKENHI, No. 15J10165, 15K00827) from the Japanese Ministry of Education, Culture, Sports, Science and Technology (MEXT, Tokyo), and University of Shizuoka Grant for Scientific and Educational Research.
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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 | 0.001 |
| 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".