Cell identity revealed by precise cell cycle state mapping links data modalities.

Several methods for cell cycle inference from sequencing data exist and are widely adopted. In contrast, methods for classification of cell cycle state from imaging data are scarce. We have for the first time integrated sequencing and imaging derived cell cycle pseudo-times for assigning 449 imaged cells to 693 sequenced cells at an average resolution of 3.

A novel deep learning-based method for automatic stereology of microglia cells from low magnification images.

Microglial cells mediate diverse homeostatic, inflammatory, and immune processes during normal development and in response to cytotoxic challenges. During these functional activities, microglial cells undergo distinct numerical and morphological changes in different tissue volumes in both rodent and human brains. However, it remains unclear how these cytostructural changes in microglia correlate with region-specific neurochemical functions.

An estimation of physiochemical properties of bladder cancer drugs via degree-based chemical bonding topological descriptors.

The use of topological descriptors remains a significant approach due to numerous advances in the field of drug design. Descriptors provide numerical representations of a molecule's chemical characteristics when used with QSPR models. The QSPR analysis for bladder medications is the main focus of this study.

Mathematical Modeling of Clonal Interference by Density-Dependent Selection in Heterogeneous Cancer Cell Lines.

Many cancer cell lines are aneuploid and heterogeneous, with multiple karyotypes co-existing within the same cell line. Karyotype heterogeneity has been shown to manifest phenotypically, thus affecting how cells respond to drugs or to minor differences in culture media. Knowing how to interpret karyotype heterogeneity phenotypically would give insights into cellular phenotypes before they unfold temporally.

A Review of Nuclei Detection and Segmentation on Microscopy Images Using Deep Learning With Applications to Unbiased Stereology Counting.

The detection and segmentation of stained cells and nuclei are essential prerequisites for subsequent quantitative research for many diseases. Recently, deep learning has shown strong performance in many computer vision problems, including solutions for medical image analysis. Furthermore, accurate stereological quantification of microscopic structures in stained tissue sections plays a critical role in understanding human diseases and developing safe and effective treatments.

A disector-based framework for the automatic optical fractionator.

Stereology-based methods provide the current state-of-the-art approaches for accurate quantification of numbers and other morphometric parameters of biological objects in stained tissue sections. The advent of artificial intelligence (AI)-based deep learning (DL) offers the possibility of improving throughput by automating the collection of stereology data. We have recently shown that DL can effectively achieve comparable accuracy to manual stereology but with higher repeatability, improved throughput, and less variation due to human factors by quantifying the total number of immunostained cells at their maximal profile of focus in extended depth of field (EDF) images.

Risk of Bleeding after Transcatheter Aortic Valve Replacement: impact of Preoperative Antithrombotic Regimens.

Introduction: Bleeding after transcatheter aortic valve replacement (TAVR) has a negative impact on the outcome of the procedure. Risk factors for bleeding vary widely in the literature, and the impact of preoperative antithrombotic agents has not been fully established. The objectives of our study were to assess bleeding after TAVR as defined by the Valve Academic Research Consortium-2 (VARC-2), identify its risk factors, and correlate with antithrombotic treatment in addition to its effect on procedural mortality.

Outcomes After Transcatheter Aortic Valve Replacement in Patients with Severe Aortic Stenosis and Diastolic Dysfunction.

Objectives: Left ventricular diastolic dysfunction (LVDD) in patients undergoing transcatheter aortic valve replacement (TAVR) is associated with poor outcomes; however, the effect of its severity is controversial. We sought to assess the impact of diastolic dysfunction on hospital outcomes and survival after TAVR and identify prognostic factors.

Methods: We included patients who underwent TAVR for severe aortic stenosis with preexisting LVDD from 2009 to 2018 (n = 325).

An adaptive digital stain separation method for deep learning-based automatic cell profile counts.

Background: Quantifying cells in a defined region of biological tissue is critical for many clinical and preclinical studies, especially in the fields of pathology, toxicology, cancer and behavior. As part of a program to develop accurate, precise and more efficient automatic approaches for quantifying morphometric changes in biological tissue, we have shown that both deep learning-based and hand-crafted algorithms can estimate the total number of histologically stained cells at their maximal profile of focus in Extended Depth of Field (EDF) images. Deep learning-based approaches show accuracy comparable to manual counts on EDF images but significant enhancement in reproducibility, throughput efficiency and reduced error from human factors.

Cavity-Enhanced Raman and Helmholtz Resonator Photoacoustic Spectroscopy to Monitor the Mixed Sugar Metabolism of .

We introduce and compare two powerful new techniques for headspace gas analysis above bacterial batch cultures by spectroscopy, Raman spectroscopy enhanced in an optical cavity (CERS), and photoacoustic detection in a differential Helmholtz resonator (DHR). Both techniques are able to monitor O and CO and its isotopomers with excellent sensitivity and time resolution to characterize bacterial growth and metabolism. We discuss and show some of the shortcomings of more conventional optical density (OD) measurements if used on their own without more sophisticated complementary measurements.

Diode laser photoacoustic spectroscopy of CO, HS and O in a differential Helmholtz resonator for trace gas analysis in the biosciences and petrochemistry.

Photoacoustic spectroscopy in a differential Helmholtz resonator has been employed with near-IR and red diode lasers for the detection of CO, HS and O in 1 bar of air/N and natural gas, in static and flow cell measurements. With the red distributed feedback (DFB) diode laser, O can be detected at 764.3 nm with a noise equivalent detection limit of 0.

Delta Radiomics Improves Pulmonary Nodule Malignancy Prediction in Lung Cancer Screening.

Low-dose computed tomography (LDCT) plays a critical role in the early detection of lung cancer. Despite the life-saving benefit of early detection by LDCT, there are many limitations of this imaging modality including high rates of detection of indeterminate pulmonary nodules. Radiomics is the process of extracting and analyzing image-based, quantitative features from a region-of-interest which then can be analyzed to develop decision support tools that can improve lung cancer screening.

Automated Cell Counts on Tissue Sections by Deep Learning and Unbiased Stereology.

In recent decades stereology-based studies have played a significant role in understanding brain aging and developing novel drug discovery strategies for treatment of neurological disease and mental illness. A major obstacle to further progress in a wide range of neuroscience sub-disciplines remains the lack of high-throughput technology for stereology analyses. Though founded on methodologically unbiased principles, commercially available stereology systems still rely on well-trained humans to manually count hundreds of cells within each region of interest (ROI).

Severe aortic regurgitation complicating Takayasu's arteritis.

We present an uncommon case of a 48-year-old female patient with symptomatic presentation of a severe aortic regurgitation with aneurysm of the ascending aorta and progressive dyspnea. Detailed investigation of laboratory tests and imaging identified Takayasu's arteritis (TA) as the underlying etiology. Computed tomography scan revealed complete occlusion of the right carotid artery as well as stenosis at the origins of left subclavian and vertebral arteries.

Isolated partial anomalous pulmonary venous connection: Diagnostic value of suprasternal color flow imaging and contrast echocardiography.

Isolated partial anomalous pulmonary venous connection is frequently missed even when patients present with mild right ventricular enlargement. We describe the value of imaging from suprasternal window with color flow and ultrasound contrast echocardiography in aiding the diagnosis.