Roadmap on Deep Learning for Microscopy.

Through digital imaging, microscopy has evolved from primarily being a means for visual observation of life at the micro- and nano-scale, to a quantitative tool with ever-increasing resolution and throughput. Artificial intelligence, deep neural networks, and machine learning are all niche terms describing computational methods that have gained a pivotal role in microscopy-based research over the past decade. This Roadmap is written collectively by prominent researchers and encompasses selected aspects of how machine learning is applied to microscopy image data, with the aim of gaining scientific knowledge by improved image quality, automated detection, segmentation, classification and tracking of objects, and efficient merging of information from multiple imaging modalities.

Predicting protein network topology clusters from chemical structure using deep learning.

Comparing chemical structures to infer protein targets and functions is a common approach, but basing comparisons on chemical similarity alone can be misleading. Here we present a methodology for predicting target protein clusters using deep neural networks. The model is trained on clusters of compounds based on similarities calculated from combined compound-protein and protein-protein interaction data using a network topology approach.

TEM virus images: Benchmark dataset and deep learning classification.

Background And Objective: To achieve the full potential of deep learning (DL) models, such as understanding the interplay between model (size), training strategy, and amount of training data, researchers and developers need access to new dedicated image datasets; i.e., annotated collections of images representing real-world problems with all their variations, complexity, limitations, and noise.

Reducing the U-Net size for practical scenarios: Virus recognition in electron microscopy images.

Background And Objective: Convolutional neural networks (CNNs) offer human experts-like performance and in the same time they are faster and more consistent in their prediction. However, most of the proposed CNNs require an expensive state-of-the-art hardware which substantially limits their use in practical scenarios and commercial systems, especially for clinical, biomedical and other applications that require on-the-fly analysis. In this paper, we investigate the possibility of making CNNs lighter by parametrizing the architecture and decreasing the number of trainable weights of a popular CNN: U-Net.

Image-Based Detection of Patient-Specific Drug-Induced Cell-Cycle Effects in Glioblastoma.

Image-based analysis is an increasingly important tool to characterize the effect of drugs in large-scale chemical screens. Herein, we present image and data analysis methods to investigate population cell-cycle dynamics in patient-derived brain tumor cells. Images of glioblastoma cells grown in multiwell plates were used to extract per-cell descriptors, including nuclear DNA content.

A short feature vector for image matching: The Log-Polar Magnitude feature descriptor.

The choice of an optimal feature detector-descriptor combination for image matching often depends on the application and the image type. In this paper, we propose the Log-Polar Magnitude feature descriptor-a rotation, scale, and illumination invariant descriptor that achieves comparable performance to SIFT on a large variety of image registration problems but with much shorter feature vectors. The descriptor is based on the Log-Polar Transform followed by a Fourier Transform and selection of the magnitude spectrum components.

A comprehensive structural, biochemical and biological profiling of the human NUDIX hydrolase family.

The NUDIX enzymes are involved in cellular metabolism and homeostasis, as well as mRNA processing. Although highly conserved throughout all organisms, their biological roles and biochemical redundancies remain largely unclear. To address this, we globally resolve their individual properties and inter-relationships.

Case-specific potentiation of glioblastoma drugs by pterostilbene.

Glioblastoma multiforme (GBM, astrocytoma grade IV) is the most common malignant primary brain tumor in adults. Addressing the shortage of effective treatment options for this cancer, we explored repurposing of existing drugs into combinations with potent activity against GBM cells. We report that the phytoalexin pterostilbene is a potentiator of two drugs with previously reported anti-GBM activity, the EGFR inhibitor gefitinib and the antidepressant sertraline.

PopulationProfiler: A Tool for Population Analysis and Visualization of Image-Based Cell Screening Data.

Image-based screening typically produces quantitative measurements of cell appearance. Large-scale screens involving tens of thousands of images, each containing hundreds of cells described by hundreds of measurements, result in overwhelming amounts of data. Reducing per-cell measurements to the averages across the image(s) for each treatment leads to loss of potentially valuable information on population variability.

Anthropocene streams and base-level controls from historic dams in the unglaciated mid-Atlantic region, USA.

Recently, widespread valley-bottom damming for water power was identified as a primary control on valley sedimentation in the mid-Atlantic US during the late seventeenth to early twentieth century. The timing of damming coincided with that of accelerated upland erosion during post-European settlement land-use change. In this paper, we examine the impact of local drops in base level on incision into historic reservoir sediment as thousands of ageing dams breach.

Inhibition of diphosphonate-blocked bone mineralization. Evidence that calcitonin promotes mineralization.

There is much experimental evidence which indicates that calcitonin in hibits bone mineral resorption, but there are few data available in support of the proposal that calcitonin may also promote mineralization. Ethane-1-hydroxy-1,1-diphosphonate (EHDP) administered to immature rats inhibited mineralization as evidenced by widened tibial epiphyseal plates and decreased bone ash to dry weight ratios. Concurrent dosing with salmon calcitonin (SCT) prevented or reversed the EHDP-blocked mineralization in a dose dependent manner.

Evidence for the promotion of bone mineralization by 1alpha,25-dihydroxycholecalciferol in the rat unrelated to the correction of deficiencies in serum calcium and phosphorus.

Concurrent administration of 1alpha,25-dihydroxycholecalciferol [1alpha,25-(OH)2-CC] to intact and thyroparathyroidectomized rats treated with ethane-1-hydroxy-1,1-diphosphonate (EHDP) prevented or reversed the EHDP-induced inhibition of bone mineralization as measured by changes in epiphyseal plate width and ash content of bone. An analog, 1alpha-droxycholecalciferol, was also effective. Recovery of bone after EHDP treatment was also significantly improved by administration of 1alpha,25-(OH)2-CC as evidenced by enhanced uptake of 45Ca by epiphyseal plates and decreased plate widths.