At present, the mouse is the most used animal model to study retinoblastoma and it would be beneficial to establish other reliable models that could confirm and complement these studies.
By using this model we could confirm that as the basal activation of Lyn increased, due to reduced activity of SHP-1, the sensitivity of this kinase to the BCR also diminished.
This undesirable property also applies to the main effects of the bivariate logistic model as we could confirm in simulation studies (only in the case of internal correlation in the gene sets, which is the case of gene expression but not of the rest of the measurements used in this study).
Co-morbid anxiety develops in this model and future studies could confirm other co-morbid symptoms like depression, fatigue, or sleep disturbances.
Subsequent validation experiments could confirm the models with an accuracy>95%.
Although it is impossible to eliminate potential confounding factors like isolation protocols, mouse strain, age, CNS regions used, and different expression profiling methodologies, we could confirm the model-specific differences in gene expression in App-Ps1 and Ercc1 mice with quantitative RT-PCR.
When we grouped the samples based on TMS, we could confirm our linear modeling results.
Hence, we investigated whether the age-related change of PQC observed in the cellular aging models could be confirmed in models of CNS aging.
Another study could confirm elevated expression of miR146a in five different mouse models for amyloid deposition (Li et al, 2011b).
After calibration, we could confirm that the resulting algorithm infers the correct noise model in synthetic data.
