The Gene Dose-Dependently Controls Hippocampal Neurogenesis and the Expression of Autism-Like Behaviors.

Mutations in the activity-dependent transcription factor have been associated with several neuropsychiatric disorders. Among these, autism spectrum disorder (ASD)-related behavioral deficits are manifested. Multiple animal models that harbor mutations in have provided compelling evidence that is indeed an ASD gene.

Sex-Specific Neural Networks of Cued Threat Conditioning: A Pilot Study.

Cued threat conditioning is the most common preclinical model for emotional memory, which is dysregulated in anxiety disorders and post-traumatic stress disorder. Though women are twice as likely as men to develop these disorders, current knowledge of threat conditioning networks was established by studies that excluded female subjects. For unbiased investigation of sex differences in these networks, we quantified the neural activity marker c-fos across 112 brain regions in adult male and female mice after cued threat conditioning compared to naïve controls.

Predicting disease activity in patients with multiple sclerosis: An explainable machine-learning approach in the Mavenclad trials.

Multiple sclerosis (MS) is among the most common autoimmune disabling neurological conditions of young adults and affects more than 2.3 million people worldwide. Predicting future disease activity in patients with MS based on their pathophysiology and current treatment is pivotal to orientate future treatment.

Role of Hippocampal Neurogenesis in Alcohol Withdrawal Seizures.

Chronic alcohol consumption results in alcohol use disorder (AUD). Interestingly, however, sudden alcohol withdrawal (AW) after chronic alcohol exposure also leads to a devastating series of symptoms, referred to as alcohol withdrawal syndromes. One key feature of AW syndromes is to produce phenotypes that are opposite to AUD.

Predicting direct hepatocyte toxicity in humans by combining high-throughput imaging of HepaRG cells and machine learning-based phenotypic profiling.

Accurate prediction of drug- and chemical-induced hepatotoxicity remains to be a problem for pharmaceutical companies as well as other industries and regulators. The goal of the current study was to develop an in vitro/in silico method for the rapid and accurate prediction of drug- and chemical-induced hepatocyte injury in humans. HepaRG cells were employed for high-throughput imaging in combination with phenotypic profiling.

Long-term memory is maintained by continuous activity of Arp2/3 in lateral amygdala.

Evidence indicates that long-term memory formation involves alterations in synaptic efficacy produced by modifications in neural transmission and morphology. However, it is not clear how such changes induced by learning, that encode memory, are maintained over long period of time to preserve long-term memory. It has been shown that the actin nucleating protein Arp2/3 is essential for supporting neuronal morphology and synaptic transmission.

The Role of Actin Cytoskeleton in Dendritic Spines in the Maintenance of Long-Term Memory.

Evidence indicates that long-term memory formation involves alterations in synaptic efficacy produced by modifications in neural transmission and morphology. However, it is not clear how such alterations induced by learning, that encode memory, are maintained over long period of time to preserve long-term memory. This is especially intriguing as the half-life of most of the proteins that underlie such changes is usually in the range of hours to days and these proteins may change their location over time.

Building predictive in vitro pulmonary toxicity assays using high-throughput imaging and artificial intelligence.

Human lungs are susceptible to the toxicity induced by soluble xenobiotics. However, the direct cellular effects of many pulmonotoxic chemicals are not always clear, and thus, a general in vitro assay for testing pulmonotoxicity applicable to a wide variety of chemicals is not currently available. Here, we report a study that uses high-throughput imaging and artificial intelligence to build an in vitro pulmonotoxicity assay by automatically comparing and selecting human lung-cell lines and their associated quantitative phenotypic features most predictive of in vivo pulmonotoxicity.

Compound Functional Prediction Using Multiple Unrelated Morphological Profiling Assays.

Phenotypic cell-based assays have proven to be efficient at discovering first-in-class therapeutic drugs mainly because they allow for scanning a wide spectrum of possible targets at once. However, despite compelling methodological advances, posterior identification of a compound's mechanism of action (MOA) has remained difficult and highly refractory to automated analyses. Methods such as the cell painting assay and multiplexing fluorescent dyes to reveal broadly relevant cellular components were recently suggested for MOA prediction.

Smooth 2D manifold extraction from 3D image stack.

Three-dimensional fluorescence microscopy followed by image processing is routinely used to study biological objects at various scales such as cells and tissue. However, maximum intensity projection, the most broadly used rendering tool, extracts a discontinuous layer of voxels, obliviously creating important artifacts and possibly misleading interpretation. Here we propose smooth manifold extraction, an algorithm that produces a continuous focused 2D extraction from a 3D volume, hence preserving local spatial relationships.

Arp2/3 and VASP Are Essential for Fear Memory Formation in Lateral Amygdala.

The actin cytoskeleton is involved in key neuronal functions such as synaptic transmission and morphogenesis. However, the roles and regulation of actin cytoskeleton in memory formation remain to be clarified. In this study, we unveil the mechanism whereby actin cytoskeleton is regulated to form memory by exploring the roles of the major actin-regulatory proteins Arp2/3, VASP, and formins in long-term memory formation.

Neurite Tracing With Object Process.

In this paper we present a pipeline for automatic analysis of neuronal morphology: from detection, modeling to digital reconstruction. First, we present an automatic, unsupervised object detection framework using stochastic marked point process. It extracts connected neuronal networks by fitting special configuration of marked objects to the centreline of the neurite branches in the image volume giving us position, local width and orientation information.

The Membrane Proximal Region of AMPA Receptors in Lateral Amygdala is Essential for Fear Memory Formation.

The membrane proximal region (MPR) of AMPA receptor (AMPAR) is needed for receptor trafficking and synaptic plasticity. However, its roles in long-term memory formation are not known. To assess the possible roles of AMPAR-MPR in rat lateral amygdala (LA) in short- and long-term fear memory formation, we used glutamate receptors (GluAs)-MPR competitive peptides MPR(DD) and MPR(AA).

Mutant huntingtin replaces Gab1 and interacts with C-terminal SH3 domain of growth factor receptor binding protein 2 (Grb2).

Huntington's disease (HD) is caused due to expansion of CAG repeats in the gene huntingtin (Htt). Adaptor protein Grb2, involved in Ras-MAP kinase pathway, is a known interactor of Htt. Mutant Htt-Grb2 interaction reduces Ras-MAPK signaling in HD models.

Inhibition of amyloid fibril growth and dissolution of amyloid fibrils by curcumin-gold nanoparticles.

Inhibition of amyloid fibrillation and clearance of amyloid fibrils/plaques are essential for the prevention and treatment of various neurodegenerative disorders involving protein aggregation. Herein, we report curcumin-functionalized gold nanoparticles (Au-curcumin) of hydrodynamic diameter 10-25 nm, which serve to inhibit amyloid fibrillation and disintegrate/dissolve amyloid fibrils. In nanoparticle form, curcumin is water-soluble and can efficiently interact with amyloid protein/peptide, offering enhanced performance in inhibiting amyloid fibrillation and dissolving amyloid fibrils.

A stochastic model for automatic extraction of 3D neuronal morphology.

Tubular structures are frequently encountered in bio-medical images. The center-lines of these tubules provide an accurate representation of the topology of the structures. We introduce a stochastic Marked Point Process framework for fully automatic extraction of tubular structures requiring no user interaction or seed points for initialization.