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Biological Transport

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Schwann Cell and Axon: An Interlaced Unit-From Action Potential to Phenotype Expression.

Advances in experimental medicine and biology
Here we propose a model of a peripheral axon with a great deal of autonomy from its cell body-the autonomous axon-but with a substantial dependence on its ensheathing Schwann cell (SC), the axon-SC unit. We review evidence in several fields and show ...

Development of a Support Vector Machine-Based System to Predict Whether a Compound Is a Substrate of a Given Drug Transporter Using Its Chemical Structure.

Journal of pharmaceutical sciences
The aim of this study was to develop an in silico prediction system to assess which of 7 categories of drug transporters (organic anion transporting polypeptide [OATP] 1B1/1B3, multidrug resistance-associated protein [MRP] 2/3/4, organic anion transp...

OMPcontact: An Outer Membrane Protein Inter-Barrel Residue Contact Prediction Method.

Journal of computational biology : a journal of computational molecular cell biology
In the two transmembrane protein types, outer membrane proteins (OMPs) perform diverse important biochemical functions, including substrate transport and passive nutrient uptake and intake. Hence their 3D structures are expected to reveal these funct...

Dendritic trafficking faces physiologically critical speed-precision tradeoffs.

eLife
Nervous system function requires intracellular transport of channels, receptors, mRNAs, and other cargo throughout complex neuronal morphologies. Local signals such as synaptic input can regulate cargo trafficking, motivating the leading conceptual m...

Prediction of LncRNA Subcellular Localization with Deep Learning from Sequence Features.

Scientific reports
Long non-coding RNAs are involved in biological processes throughout the cell including the nucleus, chromatin and cytosol. However, most lncRNAs remain unannotated and functional annotation of lncRNAs is difficult due to their low conservation and t...

A 3D deep convolutional neural network approach for the automated measurement of cerebellum tracer uptake in FDG PET-CT scans.

Medical physics
PURPOSE: The purpose of this work was to assess the potential of deep convolutional neural networks in automated measurement of cerebellum tracer uptake in F-18 fluorodeoxyglucose (FDG) positron emission tomography (PET) scans.

GAN and dual-input two-compartment model-based training of a neural network for robust quantification of contrast uptake rate in gadoxetic acid-enhanced MRI.

Medical physics
PURPOSE: Gadoxetic acid uptake rate (k ) obtained from dynamic, contrast-enhanced (DCE) magnetic resonance imaging (MRI) is a promising measure of regional liver function. Clinical exams are typically poorly temporally characterized, as seen in a low...