Michael Peitz

This study uses human oligodendrocyte spheroids to model leukodystrophies and identifies disease-specific transcriptional changes and lineage-specific vulnerabilities.

This study converts human blood cells into induced neural stem cells, showing prolonged epigenetic de-aging and delayed acquisition of neural stem cell identity over time.

The paper investigates the presynaptic mechanisms underlying epileptiform activities in human excitatory neuronal networks, finding that deceleration of rhythmic discharges is linked to vesicle translocation between pools.

The paper develops an imaging and analysis framework to map human microglial activation states using handcrafted and deep learning features, showing deep learning features achieve high classification accuracy and correlate with biological states.

This study shows that the PLCgamma2-P522R variant reduces beta-amyloid pathology and enhances microglial function in AD models, suggesting an anti-ageing mechanism.

This study identifies how GDAP1 loss of function disrupts actin signaling, leading to mitochondrial tubularity and metabolic changes in CMT4A.

The paper uses machine learning to classify Parkinson's disease patient-derived midbrain dopaminergic neurons based on multiple image-based phenotypes and identifies treatable targets.