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Enregistrement W7028051785

THE EFFECT OF DIETARY FIBRE ON HUMAN LIPID METABOLISM

2023· dissertation· en· W7028051785 sur OpenAlexaboutno aff

Notice bibliographique

RevueUniversity Library (University of Saskatchewan) · 2023
Typedissertation
Langueen
DomaineMedicine
ThématiquePrenatal Screening and Diagnostics
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPropionateCholesterolGlucagonSerum cholesterolLipid metabolismFatty acidDietary fibreCarnitine
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Soluble fibre has been shown to lower serum cholesterol under experimental conditions. To date no survey has shown a relationship between soluble fibre and serum cholesterol.\n\nA survey was designed to establish if any relationship existed between the habitual intake of soluble fibre and serum cholesterol in 96 Saskatoon residents. Stepwise multiple regression\nanalysis showed that soluble fibre was inversely related and responsible for 10% of the variation in serum total cholesterol (TC). TC, LDL-cholesterol (LDL-C), VLDL-cholesterol (VLDL-C)\nand triglycerides (TG) were directly related to Age, and HDL-C was inversely related to Age. Body Mass Index (BMI) was inversely related to HDL-C and directly related to VLDL-C and TG.\n\nThe cholesterol lowering effect of soluble fibre may be mediated through propionate, a short chain fatty acid (SCFA) normally produced from the fermentation in the colon. Propionyl-CoA may compete with acetyl-CoA for binding sites on HMG-CoA synthase. Changes in serum glucagon have been reported when SCFA are infused rectally, and propionate is known to have a high affinity for carnitine. Increased glucagon secretion (which may inhibit cholesterol synthesis) has been reported as a response to decreased hepatic carnitine (CN) levels. To\nresearch one of possible mechanisms responsible for the cholesterol lowering of soluble fibre, a study was designed to determine if the SCFA propionate lowers serum cholesterol in human subjects, if acetate modifies the response, and to explore the mechanisms by which propionate, carnitine and glucagon interact.\n\nThe study was carried out using 9 healthy male volunteers (initial TC > 5.5 mmol/L), who where fed a controlled low CN diet ( < 200 µmol/d) for 45 days (d). For 15-day periods subjects were on control (CTRL) or given by mouth 75 mmol propionate (PR) or 75 mmol propionate + 180 mmol acetate (PR+ACET). Treatment order was randomized.\n\nFaecal samples were collected throughout the study, and radiopaque faecal markers were given daily to ensure complete collection and measure intestinal transit time. 24 hour urine was collected on the last five days of each period during which the PABACHECK markers were taken (3xd). Urine samples were analyzed for para-amino benzoic acid (PABA) recovery to\ndetermine completeness of collection. On the last 2 days of each period fasting blood was taken. \n\nStatistical analysis was carried out by paired t-test with level of significance established at p <0.017 (Bonferroni correction for multiple comparisons).\n\nFaecal output (marker corrected faecal dry weight) decreased with propionate but no change was seen when acetate was added: CTRL 40.3 ±2.9 g/d (Mean±SEM); PR 36.3 ±2.6 g/d (p =0.001); PR +ACET 38.7 ±2.1 g/d. Neither total bile acids nor non-starch polysaccharide (NSP) excretion changed with either treatment.\n\nNo ketones were found in any of the urine samples on either treatment and urinary urea nitrogen values were unchanged. Propionate significantly lowered serum total cholesterol when given alone, but when given together with acetate, no reduction was seen: CTRL 5.8 ±0.29 mmol/L; PR 5.5±0.30 mmol/L (p =0.005); PR + ACET 5.8 ±0.27 mmol/L. LDL-cholesterol was also significantly lowered by propionate with no change when acetate was added: CTRL 4.1 ±0.24 mmol/L; PR 3.8 ±0.29 mmol/L (p =0.013); PR + ACET 4.0 ±0.27 mmol/L. HDL-C, VLDL-C and TG were unchanged with both treatments. Serum SCFA showed no significant change with either treatment. Insulin was unchanged but glucagon increased with propionate, but not with added acetate: CTRL 93.8+2.7 pg/mL; PR 98.9±3.3 pg/mL (p=0.016); PR+ACET 98.3+4.2 pg/mL. Carnitine was measured in the plasma, urine and diet. No changes were found in plasma or urinary carnitines with either treatment. \nThis study shows that propionate supplementation, clearly interferes with lipid metabolism in humans. Propionate reduced serum TC by 5%, and LDL-C by 7%. However until specific human liver enzymes can be studied in relation to these metabolic pathways, there is not enough evidence to indicate the mechanisms responsible. Both the increase in glucagon or competitive inhibition of acetyl-CoA in the synthesis of HMG-CoA could have been responsible for the lowering of serum cholesterol.

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 distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,454
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,001
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0010,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,010
Tête enseignante GPT0,214
Écart entre enseignants0,204 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2023
Routes d'admission1
Résumé présentoui

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