An apple a day: pectin is an important source of formate in the rat.
Bibliographic record
Abstract
Since formate plays an important role in one‐carbon metabolism we examined the potential role of pectin as a source of formate. Rats were fed purified, AIN 93‐based diets in which the source of fibre was either 5% pectin (PF rats) or 5% cellulose (CF rats). The intestinal formate content was much higher in the PF rats than in the CF rats, with ileum>caecum> large intestine. Formate was primarily found in intestinal contents rather than in tissue. The gut output and the hepatic uptake of methanol were significantly elevated in the PF rats, as was the hepatic uptake of formate. Both plasma formate and methanol were markedly higher in PF rats. Chow‐fed rats, treated with a mixture of antibiotics (vancomycin, gentamycin, rifampin) for 7 days, had markedly decreased formate levels and a complete suppression of intestinal formate output compared to chow‐fed rats without antibiotics. Hepatic uptake of formate continued in the antibiotic‐treated animals. There is a requirement for the intestinal microbiome in the maintenance of normal circulating formate levels. Pectins are polysaccharides, rich in galacturonic acid of which approximately 80% of the carboxyl groups are esterified with methanol. These methyl groups may be removed during digestion by means of a methylesterase. We suggest that methanol, so produced, can give rise to substantial quantities of formate which becomes available to rat tissues as a source of one‐carbon groups. These findings are also relevant to experiments with cobalamin‐deficient animals in which pectin is commonly used as a cobalamin‐binding agent. Support or Funding Information Supported by CIHR This abstract is from the Experimental Biology 2018 Meeting. There is no full text article associated with this abstract published in The FASEB Journal .
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".