Innovative approach for the qualitative-quantitative assessment of neurodevelopment biomarkers research in placenta tissue using immunohistochemistry digital image analysis.

利用免疫组织化学数字图像分析对胎盘组织中的神经发育生物标志物进行定性定量评估的创新方法

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作者:Camilo Caroline, Vieira Luana Martos, Gouveia Gisele Rodrigues, Torrezan Arleti Caramori, Peixoto Andrea, Euclydes Veronica, Francisco Rossana Pulcineli Vieira, Brentani Alexandra, Felipe-Silva Aloisio, Brentani Helena
We aimed to develop and validate a standardized, qualitative-quantitative protocol for digital IHC analysis to assess neurodevelopmental biomarkers in placental tissue. Placental tissues from 60 births were obtained from the Western Region Birth Cohort (ROC), and IHC staining was performed using Novolink(TM) Polymer System. The primary antibody against 11βHSD2 protein was used for protocol development, and ANXA1 was employed for validation. Slides were digitized using the Aperio ScanScope XT, and image analysis was conducted using the Positive Pixel Count V9 algorithm. Protein expression levels were calculated using the IHC Index formula. Protocol steps included combined optical and digital evaluation, representative fields per slide, intra- and interobserver validation, and assessment of reproducibility. Digital analysis of three random fields (scale bar: 300 µm) showed strong concordance with optical microscopy assessments for 11βHSD2 placental expression. Intraobserver validation showed a strong correlation (τ: 0.70, P < .001) and a substantial concordance (k(w): 0.67; P-value < .001), while interobserver comparisons also yielded substantial agreement (k(w): 0.61, P < .001), confirming the protocol's reliability. Validation using ANXA1 expression revealed moderate intra- and interobserver concordance (k(w): 0.50 and k(w): 0.48, respectively; both P < .001), reinforcing the protocol's applicability across different proteins. In conclusion, we established a reproducible digital IHC analysis protocol that enhances reliability in exploratory research. This approach optimizes image quantification, minimizes observer bias, and contributes to advances in developmental biology research and digital pathology focused on placental neurodevelopment biomarkers.

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