Technical note: Validation of an in-house bovine serum enzyme immunoassay for progesterone measurement
Notice bibliographique
Résumé
Measuring circulating progesterone (P4) of dairy cows is a key component of many research studies dealing with basic and applied reproduction physiology. The gold standard in dairy cows for the measurement of P4 in serum is radioimmunoassay (RIA), but it generates radioactive waste and requires licensed facilities. The purpose of this study was to develop and validate an in-house competitive enzyme immunoassay (EIA) to measure the P4 concentration in serum of dairy cattle. The secondary objective was to validate a commercial EIA. In the present study, a competitive EIA was developed using commercially available antibodies and conjugates. Ninety-six well microtiter plates were coated with the secondary antibody and incubated overnight. Following a washing step, the wells were blocked using the primary antibody. Serum samples were prepared by first extracting P4 using petroleum ether, then diluted in working conjugate solution. Samples were pipetted into the coated and blocked plates, then the matching HRP conjugate label (P4-3-HRP, East Coast Bio, North Berwick, ME) was added. The plates were incubated for 2 h, then washed. The substrate solution was added, and the plate was incubated up to 1 h at room temperature in the dark until a blue color had developed. A stop solution was added, and the optical density measured on a microplate reader was set at 450 nm. The binding proportion was calculated by a visible spectrum absorbance reader, and the amount of P4 was calculated using a log-logit regression line. The commercial EIA was executed as suggested by the manufacturer. The validation of the in-house EIA was done by calculating the inter- and intraassay coefficients of variation (CV) and evaluating the parallelism of diluted samples. The results from the in-house and commercial EIA were also compared with the ones from the RIA graphically (scatterplots and Bland-Altman plots) and statistically, using the Spearman correlation coefficient (r) and the Cohen's kappa statistics using a threshold of 1.0 ng/mL (κ). For the in-house EIA, the intraassay CV were all <10%, but the interassay for samples with small and large P4 concentration had CV of 12.5 and 11.0%, respectively. The correlations between the results from the EIA and the RIA were strong (in-house: r = 0.90; commercial: r = 0.83). At small concentrations (<1.0 ng/mL), however, the correlation with the gold standard was weak (in-house: r = 0.27; commercial: r = 0.14). This was likely due to the lack of accuracy at small concentrations, also shown by the absence of parallelism in samples ≤0.4 ng/mL. In conclusion, results from both the in-house and commercial EIA strongly correlated with the gold standard, but less so at smaller concentrations. The in-house EIA offers good accuracy to measure P4 in samples with a concentration >0.4 ng/mL, and a perfect agreement with RIA using a threshold of 1.0 ng/mL.
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 | 0,023 | 0,024 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,003 | 0,002 |
| Intégrité de la recherche | 0,002 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,005 | 0,009 |
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 ».