Differential effects of L‐ and D‐phenylalanine on pancreatic and gastrointestinal hormone release in humans: A randomized crossover study
Bibliographic record
Abstract
AIM: To investigate the effects of L-phenylalanine on gastroenteropancreatic hormone release, glucose levels, subjective appetite and energy intake in humans, and to determine whether these effects were stereoisomer-specific by comparing them with D-phenylalanine. MATERIALS AND METHODS: A dose-finding, non-randomized, unblinded, crossover study was conducted during October-December 2017 at the NIHR Imperial Clinical Research Facility in five participants, in which the tolerability of escalating doses of oral L-phenylalanine was assessed (0, 3, 6 and 10 g). Also, an acute, randomized, double-blind, placebo-controlled crossover study was conducted during January-May 2018 at the NIHR Imperial Clinical Research Facility in 11 participants, in which the effects of oral 10 g L-phenylalanine relative to D-phenylalanine and placebo on gastroenteropancreatic hormone (insulin, glucagon, glucose-dependent insulinotropic polypeptide [GIP], peptide tyrosine tyrosine [PYY], glucagon-like peptide-1) and glucose concentrations, visual analogue scales for subjective appetite and energy intake at an ad libitum meal served 70 minutes postingestion, were investigated. RESULTS: concentrations relative to placebo (P = .0002). CONCLUSIONS: Ingestion of L-phenylalanine, but not D-phenylalanine, increases insulin, glucagon and GIP concentrations without appearing to have a marked effect on appetite.
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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 | 0.007 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".