Chromosome mis-segregation triggers cell cycle arrest through a mechanosensitive nuclear envelope checkpoint.

Errors during cell division lead to aneuploidy, which is associated with genomic instability and cell transformation. In response to aneuploidy, cells activate the tumour suppressor p53 to elicit a surveillance mechanism that halts proliferation and promotes senescence. The molecular sensors that trigger this checkpoint are unclear.

Mechano-osmotic signals control chromatin state and fate transitions in pluripotent stem cells.

Acquisition of specific cell shapes and morphologies is a central component of cell fate transitions. Although signaling circuits and gene regulatory networks that regulate pluripotent stem cell differentiation have been intensely studied, how these networks are integrated in space and time with morphological transitions and mechanical deformations to control state transitions remains a fundamental open question. Here, we focus on two distinct models of pluripotency, primed pluripotent stem cells and pre-implantation inner cell mass cells of human embryos to discover that cell fate transitions associate with rapid changes in nuclear shape and volume which collectively alter the nuclear mechanophenotype.

Multiphoton excited polymerized biomimetic models of collagen fiber morphology to study single cell and collective migration dynamics in pancreatic cancer.

The respective roles of aligned collagen fiber morphology found in the extracellular matrix (ECM) of pancreatic cancer patients and cellular migration dynamics have been gaining attention because of their connection with increased aggressive phenotypes and poor prognosis. To better understand how collagen fiber morphology influences cell-matrix interactions associated with metastasis, we used Second Harmonic Generation (SHG) images from patient biopsies with Pancreatic ductal adenocarcinoma (PDAC) as models to fabricate collagen scaffolds to investigate processes associated with motility. Using the PDAC BxPC-3 metastatic cell line, we investigated single and collective cell dynamics on scaffolds of varying collagen alignment.

Allele-level visualization of transcription and chromatin by high-throughput imaging.

The spatial arrangement of the genome within the nucleus is a pivotal aspect of cellular organization and function with implications for gene expression and regulation. While all genome organization features, such as loops, domains, and radial positioning, are nonrandom, they are characterized by a high degree of single-cell variability. Imaging approaches are ideally suited to visualize, measure, and study single-cell heterogeneity in genome organization.

Cell type- and transcription-independent spatial proximity between enhancers and promoters.

Cell type-specific enhancers are critically important for lineage specification. The mechanisms that determine cell-type specificity of enhancer activity, however, are not fully understood. Most current models for how enhancers function invoke physical proximity between enhancer elements and their target genes.

Allele-level visualization of transcription and chromatin by high-throughput imaging.

The spatial arrangement of the genome within the nucleus is a pivotal aspect of cellular organization and function with implications for gene expression and regulation. While all genome organization features, such as loops, domains, and radial positioning, are non-random, they are characterized by a high degree of single-cell variability. Imaging approaches are ideally suited to visualize, measure, and study single-cell heterogeneity in genome organization.

Allele-level visualization of transcription and chromatin by high-throughput imaging.

The spatial arrangement of the genome within the nucleus is a pivotal aspect of cellular organization and function with implications for gene expression and regulation. While all genome organization features, such as loops, domains, and radial positioning, are non-random, they are characterized by a high degree of single-cell variability. Imaging approaches are ideally suited to visualize, measure, and study single-cell heterogeneity in genome organization.

HiTIPS: High-Throughput Image Processing Software for the Study of Nuclear Architecture and Gene Expression.

High-throughput imaging (HTI) generates complex imaging datasets from a large number of experimental perturbations. Commercial HTI software for image analysis workflows does not allow full customization and adoption of new image processing algorithms in the analysis modules. While open-source HTI analysis platforms provide individual modules in the workflow, like nuclei segmentation, spot detection, or cell tracking, they are often limited in integrating novel analysis modules or algorithms.

Real-time polarization microscopy of fibrillar collagen in histopathology.

Over the past two decades, fibrillar collagen reorganization parameters such as the amount of collagen deposition, fiber angle and alignment have been widely explored in numerous studies. These parameters are now widely accepted as stromal biomarkers and linked to disease progression and survival time in several cancer types. Despite all these advances, there has not been a significant effort to make it possible for clinicians to explore these biomarkers without adding steps to the clinical workflow or by requiring high-cost imaging systems.

Single image super-resolution for whole slide image using convolutional neural networks and self-supervised color normalization.

High-quality whole slide scanners used for animal and human pathology scanning are expensive and can produce massive datasets, which limits the access to and adoption of this technique. As a potential solution to these challenges, we present a deep learning-based approach making use of single image super-resolution (SISR) to reconstruct high-resolution histology images from low-resolution inputs. Such low-resolution images can easily be shared, require less storage, and can be acquired quickly using widely available low-cost slide scanners.

Microstructure and resident cell-types of the feline optic nerve head resemble that of humans.

The lamina cribrosa (LC) region of the optic nerve head (ONH) is considered a primary site for glaucomatous damage. In humans, biology of this region reflects complex interactions between retinal ganglion cell (RGC) axons and other resident ONH cell-types including astrocytes, lamina cribrosa cells, microglia and oligodendrocytes, as well as ONH microvasculature and collagenous LC beams. However, species differences in the microanatomy of this region could profoundly impact efforts to model glaucoma pathobiology in a research setting.

Collagen Organization in Relation to Ductal Carcinoma Pathology and Outcomes.

Background: There is widespread interest in discriminating indolent from aggressive ductal carcinoma (DCIS). We sought to evaluate collagen organization in the DCIS tumor microenvironment in relation to pathologic characteristics and patient outcomes.

Methods: We retrieved fixed tissue specimens for 90 DCIS cases within the population-based Vermont DCIS Cohort.

Non-disruptive collagen characterization in clinical histopathology using cross-modality image synthesis.

The importance of fibrillar collagen topology and organization in disease progression and prognostication in different types of cancer has been characterized extensively in many research studies. These explorations have either used specialized imaging approaches, such as specific stains (e.g.

Fibrillar Collagen Quantification With Curvelet Transform Based Computational Methods.

Quantification of fibrillar collagen organization has given new insight into the possible role of collagen topology in many diseases and has also identified candidate image-based bio-markers in breast cancer and pancreatic cancer. We have been developing collagen quantification tools based on the curvelet transform (CT) algorithm and have demonstrated this to be a powerful multiscale image representation method due to its unique features in collagen image denoising and fiber edge enhancement. In this paper, we present our CT-based collagen quantification software platform with a focus on new features and also giving a detailed description of curvelet-based fiber representation.

Quantitative phase imaging of stromal prognostic markers in pancreatic ductal adenocarcinoma.

New quantitative prognostic markers are needed for improved pancreatic ductal adenocarcinoma (PDAC) prognosis. Second harmonic generation microscopy has been used to show that collagen fiber alignment in PDAC is a negative prognostic factor. In this work, a series of PDAC and normal adjacent tissue (NAT) biopsies were imaged with spatial light interference microscopy (SLIM).

Correction to: A multiscale Mueller polarimetry module for a stereo zoom microscope.

[This corrects the article DOI: 10.1007/s13534-019-00116-w.].

Intensity-based registration of bright-field and second-harmonic generation images of histopathology tissue sections.

The use of second-harmonic generation (SHG) microscopy in biomedical research is rapidly increasing. This is due in large part to the wide spread interest of using this imaging technique to examine the role of fibrillar collagen organization in diseases such as cancer. The co-examination of SHG images and traditional bright-field (BF) images of hematoxylin and eosin (H&E) stained tissue as a gold standard clinical validation is usually required.

Super-resolution recurrent convolutional neural networks for learning with multi-resolution whole slide images.

We study a problem scenario of super-resolution (SR) algorithms in the context of whole slide imaging (WSI), a popular imaging modality in digital pathology. Instead of just one pair of high- and low-resolution images, which is typically the setup in which SR algorithms are designed, we are given multiple intermediate resolutions of the same image as well. The question remains how to best utilize such data to make the transformation learning problem inherent to SR more tractable and address the unique challenges that arises in this biomedical application.

Quantitative Histopathology of Stained Tissues using Color Spatial Light Interference Microscopy (cSLIM).

Tissue biopsy evaluation in the clinic is in need of quantitative disease markers for diagnosis and, most importantly, prognosis. Among the new technologies, quantitative phase imaging (QPI) has demonstrated promise for histopathology because it reveals intrinsic tissue nanoarchitecture through the refractive index. However, a vast majority of past QPI investigations have relied on imaging unstained tissues, which disrupts the established specimen processing.

A multiscale Mueller polarimetry module for a stereo zoom microscope.

Mueller polarimetry is a quantitative polarized light imaging modality that is capable of label-free visualization of tissue pathology, does not require extensive sample preparation, and is suitable for wide-field tissue analysis. It holds promise for selected applications in biomedicine, but polarimetry systems are often constrained by limited end-user accessibility and/or long-imaging times. In order to address these needs, we designed a multiscale-polarimetry module that easily couples to a commercially available stereo zoom microscope.

Collagen organization of renal cell carcinoma differs between low and high grade tumors.

Background: The traditional pathologic grading for human renal cell carcinoma (RCC) has low concordance between biopsy and surgical specimen. There is a need to investigate adjunctive pathology technique that does not rely on the nuclear morphology that defines the traditional grading. Changes in collagen organization in the extracellular matrix have been linked to prognosis or grade in breast, ovarian, and pancreatic cancers, but collagen organization has never been correlated with RCC grade.

Quantitative second harmonic generation imaging of leporine, canine, and porcine vocal fold collagen.

Objectives/hypothesis: Vocal fold collagen composition is an important determinant of material properties and mucosal wave propagation. Collagen alignment and straightness are quantitatively characterized by second harmonic generation (SHG) imaging. We examined leporine, canined and porcine vocal folds showing collagen composition variation that is species, location, and strain specific.

Convolutional neural networks for whole slide image superresolution.

We present a computational approach for improving the quality of the resolution of images acquired from commonly available low magnification commercial slide scanners. Images from such scanners can be acquired cheaply and are efficient in terms of storage and data transfer. However, they are generally of poorer quality than images from high-resolution scanners and microscopes and do not have the necessary resolution needed in diagnostic or clinical environments, and hence are not used in such settings.