Using serum and plasma samples to assess failure of transfer of passive immunity in dairy calves
Notice bibliographique
Résumé
The objectives of this study were (1) to determine the differences in IgG and total protein (TP) content of serum and plasma samples collected from the same calves; (2) to evaluate the correlation between calf serum and plasma IgG levels, Brix scores, and TP concentrations; (3) to determine whether different cut-off values should be used for plasma and serum to assess failure of transfer of passive immunity (FTPI) in dairy calves; and (4) to evaluate the level of agreement between results obtained from using serum and plasma samples of the same calves to assess FTPI using optimal cut-off values. Blood samples (n = 217) were collected from Holstein calves at 3 to 10 d of age on 30 commercial dairy farms in Nova Scotia and Newfoundland, Canada. Paired serum and plasma samples were analyzed for IgG concentration by the reference radial immunodiffusion assay, transmission infrared (TIR) spectroscopy, digital and optical Brix refractometers, and optical TP refractometer. The IgG concentrations measured by RID and TIR spectroscopy in serum were similar to those in plasma. However, the Brix and TP refractometer readings were significantly higher in plasma than in serum. The prevalence of FTPI in serum and plasma samples based on a RID-IgG concentration <10 g/L was 43.3 and 46.5%, respectively. The RID-IgG concentration was correlated with TIR-IgG (r = 0.92 and 0.89), digital Brix (r = 0.80 and 0.80), optical Brix (r = 0.77 and 0.77), and optical TP (r = 0.75 and 0.77) refractometers in serum and plasma, respectively. The correlations between paired serum and plasma IgG content were 0.85 by TIR spectroscopy, 0.80 by digital Brix, 0.77 by optical Brix, and 0.79 by optical TP refractometer. The optimal cut-off values for TIR spectroscopy, digital Brix, optical Brix, and TP refractometers to assess FTPI using serum were 13.1 g/L, 8.7% Brix, 8.4% Brix and 5.1 g/dL, respectively; and the optimal cut-off values with plasma were 13.4 g/L, 9.4% Brix, 9.3% Brix and 5.8 g/dL, respectively. When using these optimal cut-off values, the level of agreement (88.1%) between results derived from testing serum and plasma by TIR spectroscopy was substantial, with a kappa (κ) value of 0.76. The results derived from testing serum and plasma by digital Brix refractometer showed substantial agreement (83.4%), with a κ value of 0.65, which is higher than the agreement and κ value (74.7% and 0.51) reported for the optical Brix refractometer. Substantial agreement (81.6%) between serum and plasma TP was also obtained when using the optical TP refractometer, with a κ value of 0.63. In conclusion, serum or plasma samples can be used interchangeably for measuring IgG concentrations and assessing FTPI in dairy calves. However, different cut-offs must be used to assess FTPI depending on the sample matrix. Furthermore, results obtained from serum samples showed higher agreement with the reference RID assay than those obtained from plasma samples.
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 | 0,002 | 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 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 ».