Linking Hypothermia and Altered Metabolism with TrkB Activation.

Many mechanisms have been proposed to explain acute antidepressant drug-induced activation of TrkB neurotrophin receptors, but several questions remain. In a series of pharmacological experiments, we observed that TrkB activation induced by antidepressants and several other drugs correlated with sedation, and most importantly, coinciding hypothermia. Untargeted metabolomics of pharmacologically dissimilar TrkB activating treatments revealed effects on shared bioenergetic targets involved in adenosine triphosphate (ATP) breakdown and synthesis, demonstrating a common perturbation in metabolic activity.

Ketamine reduces electrophysiological network activity in cortical neuron cultures already at sub-micromolar concentrations - Impact on TrkB-ERK1/2 signaling.

The dissociative anesthetic ketamine regulates cortical activity in a dose-dependent manner. Subanesthetic-dose ketamine has paradoxical excitatory effects which is proposed to facilitate brain-derived neurotrophic factor (BDNF) (a ligand of tropomyosin receptor kinase B, TrkB) signaling, and activation of extracellular signal-regulated kinase 1/2 (ERK1/2). Previous data suggests that ketamine, at sub-micromolar concentrations, induces glutamatergic activity, BDNF release, and activation of ERK1/2 also on primary cortical neurons.

Automated Quantification of Human Osteoclasts Using Object Detection.

A balanced skeletal remodeling process is paramount to staying healthy. The remodeling process can be studied by analyzing osteoclasts differentiated from mononuclear cells isolated from peripheral blood or from buffy coats. Osteoclasts are highly specialized, multinucleated cells that break down bone tissue.

Facing the FACS-Using AI to Evaluate and Control Facial Action Units in Humanoid Robot Face Development.

This paper presents a new approach for evaluating and controlling expressive humanoid robotic faces using open-source computer vision and machine learning methods. Existing research in Human-Robot Interaction lacks flexible and simple tools that are scalable for evaluating and controlling various robotic faces; thus, our goal is to demonstrate the use of readily available AI-based solutions to support the process. We use a newly developed humanoid robot prototype intended for medical training applications as a case example.