Novel image analysis tool for rapid screening of cell morphology in preclinical animal models of disease.

The field of cell biology has seen major advances in both cellular imaging modalities and the development of automated image analysis platforms that increase rigor, reproducibility, and throughput for large imaging data sets. However, there remains a need for tools that provide accurate morphometric analysis of single cells with complex, dynamic cytoarchitecture in a high-throughput and unbiased manner. We developed a fully automated image-analysis algorithm to rapidly detect and quantify changes in cellular morphology using microglia cells, an innate immune cell within the central nervous system, as representative of cells that exhibit dynamic and complex cytoarchitectural changes.

Analog Nanoscale Electro-Optical Synapses for Neuromorphic Computing Applications.

The typically nonlinear and asymmetric response of synaptic memristors to positive and negative electrical pulses makes the realization of accurate deep neural networks very challenging. Here, we integrate a two-terminal valence change memory (VCM) into a photonic/plasmonic circuit and show that the switching properties of this memristor become more gradual and symmetric under light irradiation. The added optical input acts on the VCM as a third, independent modulation channel.

Robust high-dimensional memory-augmented neural networks.

Traditional neural networks require enormous amounts of data to build their complex mappings during a slow training procedure that hinders their abilities for relearning and adapting to new data. Memory-augmented neural networks enhance neural networks with an explicit memory to overcome these issues. Access to this explicit memory, however, occurs via soft read and write operations involving every individual memory entry, resulting in a bottleneck when implemented using the conventional von Neumann computer architecture.

Testing a gamified Spider App to reduce spider fear and avoidance.

Mobile applications are increasingly part of mental health programs and various apps have been developed for treating anxiety disorders. Typically, they aim to improve anxiety symptoms via established CBT techniques, such as exposure principles, which are considered extremely unpleasant for fearful individuals. We combined in a mobile application exposure principles with gamification elements (e.

Interaction between magnesium and methylglyoxal in diabetic polyneuropathy and neuronal models.

Objective: The lack of effective treatments against diabetic sensorimotor polyneuropathy demands the search for new strategies to combat or prevent the condition. Because reduced magnesium and increased methylglyoxal levels have been implicated in the development of both type 2 diabetes and neuropathic pain, we aimed to assess the putative interplay of both molecules with diabetic sensorimotor polyneuropathy.

Methods: In a cross-sectional study, serum magnesium and plasma methylglyoxal levels were measured in recently diagnosed type 2 diabetes patients with (n = 51) and without (n = 184) diabetic sensorimotor polyneuropathy from the German Diabetes Study baseline cohort.