Biology subjects

Roeder, S.

Publications and source records attributed to Roeder, S..

2 recordsLinked to original sources

bioRxiv2025

Individual olfactory channels shape distinct parameters of sleep architecture

AbstractAcross the animal kingdom, olfactory dysfunction and anosmia have been associated with disruptions in sleep. In the fruit fly Drosophila melanogaster, various studies have demonstrated that broadly inhibiting olfactory receptor neurons (ORNs) similarly disrupts sleep/wake cycles, suggesting that baseline ORN signaling is an integral component of olfactory modulation of sleep. However, due to the diversity of ORNs and combinatorial nature of olfactory processing, many of the cellular and molecular mechanisms by which ORNs modulate sleep remain unclear. In this study, we addressed this gap of knowledge by characterizing the contributions of different ensembles of ORNs, individual ORN types, and a known modulator of ORNs on baseline sleep architecture. We find that the activity of distinct ORN types are important for day and nighttime sleep and heterogeneously shape parameters of sleep architecture. Importantly, the effects of ORN signaling on sleep are adjusted across mating status, suggesting that distinct ORN types are recruited within the context of sleep depending on the demands of the animal. Furthermore, the effects of ORN signaling on sleep are in part shaped by heterogeneous serotonin (5-HT) receptor expression. Together, this work identifies cellular and molecular pathways bridging olfaction and sleep, and helps establish a circuit model that can be used to further characterize the behavioral consequences of sensory dysfunction.

neuroscience↗

bioRxiv2019

Same same but different: a web-based deep learning application for the histopathologic distinction of cortical malformations

We trained a convolutional neural network (CNN) to classify H.E. stained microscopic images of focal cortical dysplasia type IIb (FCD IIb) and cortical tuber of tuberous sclerosis complex (TSC). Both entities are distinct subtypes of human malformations of cortical development that share histopathological features consisting of neuronal dyslamination with dysmorphic neurons and balloon cells. The microscopic review of routine stainings of such surgical specimens remains challenging. A digital processing pipeline was developed for a series of 56 FCD IIb and TSC cases to obtain 4000 regions of interest and 200.000 sub-samples with different zoom and rotation angles to train a CNN. Our best performing network achieved 91% accuracy and 0.88 AUCROC (area under the receiver operating characteristic curve) on a hold-out test-set. Guided gradient-weighted class activation maps visualized morphological features used by the CNN to distinguish both entities. We then developed a web application, which combined the visualization of whole slide images (WSI) with the possibility for classification between FCD IIb and TSC on demand by our pretrained and build-in CNN classifier. This approach might help to introduce deep learning applications for the histopathologic diagnosis of rare and difficult-to-classify brain lesions.

pathology↗