Chromatin alternates between A and B compartments at kilobase scale for subgenic organization.

Nuclear compartments are prominent features of 3D chromatin organization, but sequencing depth limitations have impeded investigation at ultra fine-scale. CTCF loops are generally studied at a finer scale, but the impact of looping on proximal interactions remains enigmatic. Here, we critically examine nuclear compartments and CTCF loop-proximal interactions using a combination of in situ Hi-C at unparalleled depth, algorithm development, and biophysical modeling.

Genome-wide tracing to decipher nuclear organization.

Nuclear organization impacts gene expression activity and cell phenotype. Our current understanding is mainly derived from ensemble-level sequencing studies that reflect the 3D genome structure of millions of cells. These approaches have provided invaluable details on the 3D organizations of the genome and their relation to other nuclear landmarks.

The anti-immune dengue subgenomic flaviviral RNA is present in vesicles in mosquito saliva and is associated with increased infectivity.

Mosquito transmission of dengue viruses to humans starts with infection of skin resident cells at the biting site. There is great interest in identifying transmission-enhancing factors in mosquito saliva in order to counteract them. Here we report the discovery of high levels of the anti-immune subgenomic flaviviral RNA (sfRNA) in dengue virus 2-infected mosquito saliva.

A very luminous jet from the disruption of a star by a massive black hole.

Tidal disruption events (TDEs) are bursts of electromagnetic energy that are released when supermassive black holes at the centres of galaxies violently disrupt a star that passes too close. TDEs provide a window through which to study accretion onto supermassive black holes; in some rare cases, this accretion leads to launching of a relativistic jet, but the necessary conditions are not fully understood. The best-studied jetted TDE so far is Swift J1644+57, which was discovered in γ-rays, but was too obscured by dust to be seen at optical wavelengths.

Open Structural Data in Precision Medicine.

Three-dimensional protein structural data at the molecular level are pivotal for successful precision medicine. Such data are crucial not only for discovering drugs that act to block the active site of the target mutant protein but also for clarifying to the patient and the clinician how the mutations harbored by the patient work. The relative paucity of structural data reflects their cost, challenges in their interpretation, and lack of clinical guidelines for their utilization.

A new precision medicine initiative at the dawn of exascale computing.

Which signaling pathway and protein to select to mitigate the patient's expected drug resistance? The number of possibilities facing the physician is massive, and the drug combination should fit the patient status. Here, we briefly review current approaches and data and map an innovative patient-specific strategy to forecast drug resistance targets that centers on parallel (or redundant) proliferation pathways in specialized cells. It considers the availability of each protein in each pathway in the specific cell, its activating mutations, and the chromatin accessibility of its encoding gene.

Improving prostate cancer classification in H&E tissue micro arrays using Ki67 and P63 histopathology.

Histopathology of Hematoxylin and Eosin (H&E)-stained tissue obtained from biopsy is commonly used in prostate cancer (PCa) diagnosis. Automatic PCa classification of digitized H&E slides has been developed before, but no attempts have been made to classify PCa using additional tissue stains registered to H&E. In this paper, we demonstrate that using H&E, Ki67 and p63-stained (3-stain) tissue improves PCa classification relative to H&E alone.

3D mapping and accelerated super-resolution imaging of the human genome using in situ sequencing.

There is a need for methods that can image chromosomes with genome-wide coverage, as well as greater genomic and optical resolution. We introduce OligoFISSEQ, a suite of three methods that leverage fluorescence in situ sequencing (FISSEQ) of barcoded Oligopaint probes to enable the rapid visualization of many targeted genomic regions. Applying OligoFISSEQ to human diploid fibroblast cells, we show how four rounds of sequencing are sufficient to produce 3D maps of 36 genomic targets across six chromosomes in hundreds to thousands of cells, implying a potential to image thousands of targets in only five to eight rounds of sequencing.

The genome-wide multi-layered architecture of chromosome pairing in early Drosophila embryos.

Genome organization involves cis and trans chromosomal interactions, both implicated in gene regulation, development, and disease. Here, we focus on trans interactions in Drosophila, where homologous chromosomes are paired in somatic cells from embryogenesis through adulthood. We first address long-standing questions regarding the structure of embryonic homolog pairing and, to this end, develop a haplotype-resolved Hi-C approach to minimize homolog misassignment and thus robustly distinguish trans-homolog from cis contacts.

Deep Learning-Based Gleason Grading of Prostate Cancer From Histopathology Images-Role of Multiscale Decision Aggregation and Data Augmentation.

Visual inspection of histopathology images of stained biopsy tissue by expert pathologists is the standard method for grading of prostate cancer (PCa). However, this process is time-consuming and subject to high inter-observer variability. Machine learning-based methods have the potential to improve efficient throughput of large volumes of slides while decreasing variability, but they are not easy to develop because they require substantial amounts of labeled training data.

A new era: artificial intelligence and machine learning in prostate cancer.

Artificial intelligence (AI) - the ability of a machine to perform cognitive tasks to achieve a particular goal based on provided data - is revolutionizing and reshaping our health-care systems. The current availability of ever-increasing computational power, highly developed pattern recognition algorithms and advanced image processing software working at very high speeds has led to the emergence of computer-based systems that are trained to perform complex tasks in bioinformatics, medical imaging and medical robotics. Accessibility to 'big data' enables the 'cognitive' computer to scan billions of bits of unstructured information, extract the relevant information and recognize complex patterns with increasing confidence.

A multiplexed DNA FISH strategy for assessing genome architecture in .

Eukaryotic DNA is highly organized within nuclei and this organization is important for genome function. Fluorescent hybridization (FISH) approaches allow 3D architectures of genomes to be visualized. Scalable FISH technologies, which can be applied to whole animals, are needed to help unravel how genomic architecture regulates, or is regulated by, gene expression during development, growth, reproduction, and aging.

Comparison of Artificial Intelligence Techniques to Evaluate Performance of a Classifier for Automatic Grading of Prostate Cancer From Digitized Histopathologic Images.

Importance: Proper evaluation of the performance of artificial intelligence techniques in the analysis of digitized medical images is paramount for the adoption of such techniques by the medical community and regulatory agencies.

Objectives: To compare several cross-validation (CV) approaches to evaluate the performance of a classifier for automatic grading of prostate cancer in digitized histopathologic images and compare the performance of the classifier when trained using data from 1 expert and multiple experts.

Design, Setting, And Participants: This quality improvement study used tissue microarray data (333 cores) from 231 patients who underwent radical prostatectomy at the Vancouver General Hospital between June 27, 1997, and June 7, 2011.

Walking along chromosomes with super-resolution imaging, contact maps, and integrative modeling.

Chromosome organization is crucial for genome function. Here, we present a method for visualizing chromosomal DNA at super-resolution and then integrating Hi-C data to produce three-dimensional models of chromosome organization. Using the super-resolution microscopy methods of OligoSTORM and OligoDNA-PAINT, we trace 8 megabases of human chromosome 19, visualizing structures ranging in size from a few kilobases to over a megabase.

An End-to-end System for Automatic Characterization of Iba1 Immunopositive Microglia in Whole Slide Imaging.

Traumatic brain injury (TBI) is one of the leading causes of death and disability worldwide. Detailed studies of the microglial response after TBI require high throughput quantification of changes in microglial count and morphology in histological sections throughout the brain. In this paper, we present a fully automated end-to-end system that is capable of assessing microglial activation in white matter regions on whole slide images of Iba1 stained sections.

Automatic grading of prostate cancer in digitized histopathology images: Learning from multiple experts.

Prostate cancer (PCa) is a heterogeneous disease that is manifested in a diverse range of histologic patterns and its grading is therefore associated with an inter-observer variability among pathologists, which may lead to an under- or over-treatment of patients. In this work, we develop a computer aided diagnosis system for automatic grading of PCa in digitized histopathology images using supervised learning methods. Our pipeline comprises extraction of multi-scale features that include glandular, cellular, and image-based features.

Prostate segmentation in MRI using a convolutional neural network architecture and training strategy based on statistical shape models.

Purpose: Most of the existing convolutional neural network (CNN)-based medical image segmentation methods are based on methods that have originally been developed for segmentation of natural images. Therefore, they largely ignore the differences between the two domains, such as the smaller degree of variability in the shape and appearance of the target volume and the smaller amounts of training data in medical applications. We propose a CNN-based method for prostate segmentation in MRI that employs statistical shape models to address these issues.

Investigation of Physical Phenomena Underlying Temporal-Enhanced Ultrasound as a New Diagnostic Imaging Technique: Theory and Simulations.

Temporal-enhanced ultrasound (TeUS) is a novel noninvasive imaging paradigm that captures information from a temporal sequence of backscattered US radio frequency data obtained from a fixed tissue location. This technology has been shown to be effective for classification of various in vivo and ex vivo tissue types including prostate cancer from benign tissue. Our previous studies have indicated two primary phenomena that influence TeUS: 1) changes in tissue temperature due to acoustic absorption and 2) micro vibrations of tissue due to physiological vibration.

OligoMiner provides a rapid, flexible environment for the design of genome-scale oligonucleotide in situ hybridization probes.

Oligonucleotide (oligo)-based FISH has emerged as an important tool for the study of chromosome organization and gene expression and has been empowered by the commercial availability of highly complex pools of oligos. However, a dedicated bioinformatic design utility has yet to be created specifically for the purpose of identifying optimal oligo FISH probe sequences on the genome-wide scale. Here, we introduce OligoMiner, a rapid and robust computational pipeline for the genome-scale design of oligo FISH probes that affords the scientist exact control over the parameters of each probe.

The role of near-wall drag effects in the dynamics of tethered DNA under shear flow.

We utilized single-molecule tethered particle motion (TPM) tracking, optimized for studying the behavior of short (0.922 μm) dsDNA molecules under shear flow conditions, in the proximity of a wall (surface). These experiments track the individual trajectories through a gold nanobead (40 nm in radius), attached to the loose end of the DNA molecules.

In Situ Super-Resolution Imaging of Genomic DNA with OligoSTORM and OligoDNA-PAINT.

OligoSTORM and OligoDNA-PAINT meld the Oligopaint technology for fluorescent in situ hybridization (FISH) with, respectively, Stochastic Optical Reconstruction Microscopy (STORM) and DNA-based Point Accumulation for Imaging in Nanoscale Topography (DNA-PAINT) to enable in situ single-molecule super-resolution imaging of nucleic acids. Both strategies enable ≤20 nm resolution and are appropriate for imaging nanoscale features of the genomes of a wide range of species, including human, mouse, and fruit fly (Drosophila).

Focal application of low-dose-rate brachytherapy for prostate cancer: a pilot study.

Purpose: To evaluate the feasibility and to report the early outcomes of focal treatment of prostate cancer using low-dose-rate brachytherapy (LDR-PB).

Material And Methods: Seventeen patients were screened with multi-parametric magnetic resonance imaging (mpMRI), 14 of whom proceeded to receive trans-perineal template mapping biopsy (TTMB). Focal LDR-PB was performed on five eligible patients using dual air kerma strength treatment plans based on planning target volumes derived from cancer locations and determined by TTMB.

Detection and grading of prostate cancer using temporal enhanced ultrasound: combining deep neural networks and tissue mimicking simulations.

PURPOSE  : Temporal Enhanced Ultrasound (TeUS) has been proposed as a new paradigm for tissue characterization based on a sequence of ultrasound radio frequency (RF) data. We previously used TeUS to successfully address the problem of prostate cancer detection in the fusion biopsies. METHODS  : In this paper, we use TeUS to address the problem of grading prostate cancer in a clinical study of 197 biopsy cores from 132 patients.

MR elastography of prostate cancer: quantitative comparison with histopathology and repeatability of methods.

The purpose of this work was to assess trans-perineal prostate magnetic resonance elastography (MRE) for (1) repeatability in phantoms/volunteers and (2) diagnostic power as correlated with histopathology in prostate cancer patients. The three-dimensional (3D) displacement field was obtained using a fractionally encoded gradient echo sequence using a custom-made transducer. The repeatability of the method was assessed based on three repeat studies and by changing the driving frequency by 3% in studies on a phantom and six healthy volunteers.