Validating a Multibiomarker Panel for the Assessment of Quantity and Quality of Plant Foods in the Diet (PLAENTI): Protocol for a Parallel Group–Designed Randomized Controlled Trial
Notice bibliographique
Résumé
Background: Although a high intake of plant foods is often considered healthy, some plant foods can be detrimental to health. Reliable dietary assessment is crucial to examine the relationship between diet and disease. Current dietary assessment methods rely on self-reported intake data, which are subject to bias. Objective measurement using biomarkers of food intake could mitigate this problem. However, single biomarkers of food intake have limitations as well. Combining several biomarkers of food intake into a multibiomarker panel could attenuate these limitations and allow for an accurate, objective dietary assessment. Objective: The PLAENTI study aims to validate a multibiomarker panel for the assessment of quantity and quality of plant foods in the diet. Methods: PLAENTI is a randomized controlled trial with 4 arms in a parallel design. Metabolically healthy adults (≥18 years old) were enrolled in the study. The study consisted of 1 week of run-in, with a standardized diet low in healthful plant foods for all participants; 2 weeks of a dietary intervention according to the assigned arm; and 1 week of washout, during which participants returned to their habitual diet. During the intervention, the participants' diet consisted of either a low, medium, or high proportion of healthful plant foods or a high proportion of unhealthful plant foods in the diet according to the assigned arm. The arm that received a high proportion of healthful plant foods served as the control. All food was provided based on energy-adjusted menu plans. During the visits, anthropometry and body composition were assessed, and blood samples were collected. Throughout the study, participants collected multiple urine samples (24-hour urine, evening and morning spot urine) and stool samples. Blood and urine samples will be analyzed by liquid chromatography-mass spectrometry to determine biomarker levels for the validation of a multibiomarker panel. Results: After receiving approval from the ethics committee, recruitment began, and the first screening visit took place in November 2023. Between January and August 2024, of the 66 enrolled participants, 59 (31 female, 28 male) successfully completed the study, and their urine, blood, and stool samples are available for analysis. PLAENTI was conducted in 5 waves with a maximum of 16 participants enrolled in each wave. The mean age of the study population was 45.5 (SD 18.4) years, the mean BMI was 24.8 (SD-3.9) kg/m², and the mean total energy expenditure was 2464 (SD 440) kcal. Conclusions: PLAENTI was conducted in a highly controlled and standardized manner, yielding samples and data that will be used to examine whether the quantity and quality of plant foods in the diet can be assessed using a multibiomarker panel. Successful validation of the multibiomarker panel would enable its application for objective dietary assessment.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,049 | 0,049 |
| Méta-épidémiologie (sens strict) | 0,008 | 0,004 |
| Méta-épidémiologie (sens large) | 0,011 | 0,006 |
| Bibliométrie | 0,003 | 0,004 |
| Études des sciences et des technologies | 0,004 | 0,004 |
| Communication savante | 0,004 | 0,004 |
| Science ouverte | 0,004 | 0,003 |
| Intégrité de la recherche | 0,009 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,045 | 0,011 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».