Three-Year Follow-up After Antiviral Treatment in New-Onset Type 1 Diabetes: Results From the Diabetes Virus Detection and Intervention Trial.

Objective: In the Diabetes Virus Detection and Intervention trial, antiviral treatment with pleconaril and ribavirin decreased the decline, compared with placebo, in endogenous C-peptide 1 year after diagnosis of type 1 diabetes (T1D) in children and adolescents. This article reports the results 2 and 3 years after diagnosis.

Research Design And Methods: This was a multicenter, randomized, placebo-controlled (1:1) trial of 96 children and adolescents aged 6-15.

Evolving alterations of structural organization and functional connectivity in feedforward neural networks after induced P301L tau mutation.

Reciprocal structure-function relationships underlie both healthy and pathological behaviours in complex neural networks. Thus, understanding neuropathology and network dysfunction requires a thorough investigation of the complex interactions between structural and functional network reconfigurations in response to perturbation. Such adaptations are often difficult to study in vivo.

Reverse engineering of feedforward cortical-Hippocampal microcircuits for modelling neural network function and dysfunction.

Engineered biological neural networks are indispensable models for investigation of neural function and dysfunction from the subcellular to the network level. Notably, advanced neuroengineering approaches are of significant interest for their potential to replicate the topological and functional organization of brain networks. In this study, we reverse engineered feedforward neural networks of primary cortical and hippocampal neurons, using a custom-designed multinodal microfluidic device with Tesla valve inspired microtunnels.

Generation of Orthotopic and Subcutaneous Patient-Derived Xenograft Models from Diverse Clinical Tissue Samples of Pediatric Extracranial Solid Tumors.

Realistic and renewable laboratory models that accurately reflect the distinct clinical features of childhood cancers have enormous potential to speed research progress. These models help us to understand disease biology, develop new research methods, advance new therapies to clinical trial, and implement personalized medicine. This chapter describes methods to generate patient-derived xenograft models of neuroblastoma and rhabdomyosarcoma, two tumor types for which children with high-risk disease have abysmal survival outcomes and survivors have lifelong-debilitating effects from treatment.