Technical Note: In vivo estimation of lipogenesis using a bolus injection of [U-13C]glucose in pigs
Bibliographic record
Abstract
The use of radioactive isotopes to measure de novo lipogenesis in pigs has been well established. Different from radioactive isotopes, stable isotopes present little or no risk to human and animal subjects. Therefore, the objective of this study was to adapt the method of bolus injection of radioactive glucose (14C) to use 13C-labeled glucose to estimate de novo lipogenesis in finishing pigs. Five vein-catheterized gilts received 3.0 kg/d of a commercial diet for 2 wk. On the last day, the pigs received a bolus injection of [U-13C]glucose (12 mg/kg body weight). A serial of blood samples was taken for 4 h to determine the glucose rate of disappearance (Rd) from plasma glucose isotopic enrichment (IE). The 13C IE of lipids was determined from adipose tissue biopsies collected at 1, 2, and 3 h after the bolus injection and from adipose tissue collected after pig euthanasia 4 h after the bolus. Lipogenesis was estimated from the incorporation of 13C from glucose into adipose tissue lipids. Glucose Rd, estimated using a double-exponential function, averaged 5.4 ± 1.4 mmol/min. The IE of lipids increased linearly during the 4 h following the bolus injection (P < 0.05). The rate of incorporation of glucose into lipids, estimating lipogenesis, averaged 9.0 µg glucose/(min × g of lipids) 4 h after the bolus injection. In conclusion, the in vivo method using a bolus injection of [U-13C]glucose allows a successful estimation of de novo lipogenesis in finishing pigs.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".