Circulating direct infusion MS and NMR metabolomic profiles of post-gonadectomy kittens with or without additional dietary choline supplementation
Bibliographic record
Abstract
Abstract Choline is beneficial for energy metabolism and growth in various species. Choline may work similarly in kittens at risk of obesity. Direct infusion MS (Di-MS) and NMR spectroscopy were used to investigate the metabolomic signatures of kittens supplemented with or without additional dietary choline for 12 weeks. Fifteen intact male kittens consumed a base diet (3310 mg choline/kg DM) to their daily metabolisable energy requirement (DER) over an 11-week acclimation. Kittens were gonadectomised and assigned, based on body weight, to the base diet (CONTROL,n7) or the base diet with 300 mg/kgBW0·75additional choline as choline chloride (CHOLINE,n8) and offered three times their individual energy requirement divided into three meals. At weeks −1 and 12, fasted blood was sampled and serum analysed for 130 metabolites via Di-MS and fifty-one metabolites via NMR spectroscopy. Changes in fasted metabolites were assessed using a repeated-measures GLIMMIX procedure with time and group as fixed effects, and time as a repeated measure. Metabolites of one-carbon metabolism and lipids increased, and medium-chain acyl carnitines decreased from week −1 to 12 for CHOLINE (P< 0·05), but not CONTROL (P> 0·05). Increases in amino acid, biogenic amine and organic compound concentrations were observed in both groups (P< 0·05). The results suggest impacts of dietary choline at greater intakes than currently recommended on one-carbon metabolism and fatty acid oxidation, and these may promote healthy growth in post-gonadectomy kittens.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".