Correlating the structure and in vitro digestion viscosities of different pectin fibers to in vivo human satiety
Bibliographic record
Abstract
The effects of a simulated in vitro digestion on the viscosity of orange juice with added high methoxyl (HM), low methoxyl (LM), and low methoxyl amidated (LMA) pectins were examined in conjunction with a human satiety study with healthy men (n=10) and women (n=15). Orange juice solutions were formulated to be either low (0.039±0.007 Pa s) or high viscosity (0.14±0.035 Pa s). The apparent viscosities after an in vitro digestion simulating the gastric and small intestinal phases in the presence of hydrolytic enzymes and bile salts were recorded at 10 and 50 s⁻¹. The viscosity induced by LM pectin increased considerably after the gastric phase whereas samples with all pectin types showed considerable reductions in viscosity, compared to initial apparent viscosity, after the small intestinal phase. For satiety testing, the orange juice solutions were consumed with a standardized breakfast meal after a 12 h overnight fast. Self-reported visual analogue scale (VAS) measurements of Hunger, Fullness, Satisfaction and Prospective Food Intake were obtained at fasting, after consumption of the breakfast and for the subsequent 3 h. The LM low and high viscosity pectin beverages were associated with the greatest effects on subjective ratings of satiety. The HM low and high viscosity pectin beverages had lower but significant effects on satiety, while LMA pectin had no effect. There was not a strong correlation between apparent viscosity of in vitro digested beverages and in vivo satiety scores. Thus, in this study, fiber-induced satiety could not be fully explained by digestate viscosity alone although gastric-phase viscosity may have played a significant role.
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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".