The role of synovial fluid markers of catabolism and anabolism in osteoarthritis, rheumatoid arthritis and asymptomatic organ donors
Notice bibliographique
Résumé
INTRODUCTION: The purpose of this study was to correlate the level of anabolic and catabolic biomarkers in synovial fluid (SF) from patients with rheumatoid arthritis (RA), patients with osteoarthritis (OA) and asymptomatic organ donors. METHODS: SF was collected from the knees of 45 OA, 22 RA patients and 20 asymptomatic organ donors. Eight biomarkers were selected and analyzed by using an enzyme-linked immunosorbent assay: interleukin (IL)-1, IL-6, IL-8 and IL-11; leukemia-inhibitory factor (LIF); cartilage oligomeric protein (COMP); osteocalcin; and osteogenic protein 1 (OP-1). Data are expressed as medians (interquartile ranges). The effects of sex and disease activity were assessed on the basis of the Western Ontario and McMaster Universities index score for patients with OA and on the basis of white blood cell count, erythrocyte sedimentation rate and C-reactive protein level for patients with RA. RESULTS: The mean ages (± SD) of the patients were as follows: 53 ± 9 years for patients with OA, 54 ± 11 years for patients with RA and 52 ± 7 years for asymptomatic organ donors. No effect of participants' sex was identified. In the SF of patients with RA, four of five cytokines were higher than those in the SF of patients with OA and those of asymptomatic organ donors. The most significant differences were found for IL-6 and IL-8, where IL-6 concentration in SF of patients with RA was almost threefold higher than that in patients with OA and fourfold higher than that in asymptomatic donor controls: 354.7 pg/ml (1,851.6) vs. 119.4 pg/ml (193.2) vs. 86.97 pg/ml (82.0) (P < 0.05 and P < 0.05, respectively). IL-8 concentrations were higher in SF of patients with RA than that in patients with OA as well as that in asymptomatic donor controls: 583.6 pg/ml (1,086.4) vs. 429 pg/ml (87.3) vs. 451 pg/ml (170.1) (P < 0.05 and P < 0.05, respectively). No differences were found for IL-11 in the SF of patients with RA and that of patients with OA, while a 1.4-fold difference was detected in the SF of patients with OA and that of asymptomatic donor controls: 296.2 pg/ml (257.2) vs. 211.6 pg/ml (40.8) (P < 0.05). IL-1 concentrations were the highest in the SF of RA patients (9.26 pg/ml (11.1)); in the SF of asymptomatic donors, it was significantly higher than that in patients with OA (9.083 pg/ml (1.6) vs. 7.76 pg/ml (2.6); P < 0.05). Conversely, asymptomatic donor control samples had the highest LIF concentrations: 228.5 pg/ml (131.6) vs. 128.4 pg/ml (222.7) in the SF of patients with RA vs. 107.5 pg/ml (136.9) in the SF of patients with OA (P < 0.05). OP-1 concentrations were twofold higher in the SF of patients with RA than those in patients with OA and threefold higher than those in asymptomatic donor control samples (167.1 ng/ml (194.8) vs. 81.79 ng/ml (116.0) vs. 54.49 ng/ml (29.3), respectively; P < 0.05). The differences in COMP and osteocalcin were indistinguishable between the groups, as were the differences between active and inactive OA and RA. CONCLUSIONS: Activation of selected biomarkers corresponds to the mechanisms that drive each disease. IL-11, LIF and OP-1 may be viewed as a cluster of biomarkers significant for OA; while profiling of IL-1, IL-6, IL-8, LIF and OP-1 may be more significant in RA. Larger, better-defined patient cohorts are necessary to develop a biomarker algorithm for prognostic use.
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 | 0,001 | 0,003 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 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 ».