Effect of pH and lipopolysaccharide on tight junction regulators and inflammatory markers in intestinal cells as an experimental model of weaning transition in dairy calves
Notice bibliographique
Résumé
Acidic conditions combined with the presence of lipopolysaccharide (LPS) may increase the permeability of gastrointestinal epithelium. Feeding starch-rich starter to dairy calves is associated with ruminal acidosis and decreases the pH of other segments of the gastrointestinal tract, and that affects the tight junction regulator. The objective was to evaluate the effect of the combination of different pH (7.4 vs. 6.0) and LPS concentrations (0, 0.5, 10 ng/mL) in intestinal cells on tight junction regulators, inflammatory markers, and permeability. The human colon carcinoma Caco-2 cell line was used with the main treatment of pH and LPS in a 2 × 3 factorial arrangement. The pH was acidic (pH 6.0) or physiologic (pH 7.4), whereas LPS was 0, 0.5, or 10 ng/mL. After cells reached 70%–80% of confluence, the media were replaced with each respective treatment medium. Cells were treated for 3 h for mRNA abundance analysis, 3 and 6 h for protein abundance determination, and 3, 6, 12, and 24 h for permeability determination. Protein abundance of the myosin light-chain kinase (MYLK) and toll-like receptor 4 (TLR4) were measured by western blot. The mRNA abundance of IL-8, MYLK, peroxisome proliferator activated receptor gamma, and nuclear factor kappa B (Nfkb1) was determined by real-time, quantitative PCR. Paracellular permeability was determined with Lucifer yellow after 21 d of incubation. Cell culture was performed in biological triplicate; each biological replicate for real-time, quantitative PCR had 2 technical replicates, and for protein abundance and permeability assay had one technical replicate. The MIXED procedure of SAS (SAS Institute Inc.) was used with LPS, pH, and pH × LPS as fixed effects. Significance was declared at P ≤ 0.05 and tendencies when 0.05 < P ≤ 0.10. Increasing LPS doses did not affect the protein abundance of MYLK and TLR4, nor mRNA abundance of MYLK and PPRG. The LPS tended to increase mRNA abundance of IL-8 while pH × LPS interactively increased mRNA abundance of Nfkb1, where mRNA abundance of Nfkb1 was lower in cells exposed to pH 6.0 when combined with 0 and 10 ng/mL of LPS. Contrary to expectations, LPS did not affect the permeability of Caco-2 cells. The mRNA abundance of MYLK was greater at pH 6.0 versus pH 7.4. Also, protein abundance of TLR4 was lower at pH 6.0 than pH 7.4, and it decreased when exposure increased to 6 h. In addition, mRNA abundance of IL-8 was lower at pH 6.0 versus pH 7.4. Permeability was greater at pH 6.0 versus 7.4 after 6, 12, and 24 h of treatment. In summary, the effect of LPS and its interaction with pH showed less impact than expected on dependent variables measured, which might be attributed to the adopted clinically achievable LPS doses likely not being high enough to draw a strong response as observed in the literature. On the other hand, pH was far more relevant, modulating mRNA abundance of inflammatory markers, tight junction regulators, and permeability in in vitro colon cell models.
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,001 | 0,001 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,000 |
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.
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 ».