A rapid and bidirectional reporter of neural activity reveals neural correlates of social behaviors in Drosophila.

Neural activity is modulated over different timescales encompassing subseconds to hours, reflecting changes in external environment, internal state and behavior. Using Drosophila as a model, we developed a rapid and bidirectional reporter that provides a cellular readout of recent neural activity. This reporter uses nuclear versus cytoplasmic distribution of CREB-regulated transcriptional co-activator (CRTC).

Facial Nerve High-Resolution Microanatomy Analysis of the Distal Intratemporal to Extracranial Pes Segment: Reconstructive Implications.

Background: Current knowledge of facial nerve topography between the stylomastoid foramen to the pes anserinus is very limited. Elucidating this segment's intraneural microanatomy may be advantageous in certain clinical settings: the planning of nerve grafts for gaps extending from the proximal facial nerve trunk to distal branches or in determining coaptation sites for hypoglossal jump grafts to provide selective upper and lower facial tone. This study is the first to provide high-definition intraneural topography of the aforementioned segment to optimize reconstructive outcomes.

Heterozygous Mutation of Vegfr3 Reduces Renal Lymphatics without Renal Dysfunction.

Background: Lymphatic abnormalities are observed in several types of kidney disease, but the relationship between the renal lymphatic system and renal function is unclear. The discovery of lymphatic-specific proteins, advances in microscopy, and available genetic mouse models provide the tools to help elucidate the role of renal lymphatics in physiology and disease.

Methods: We utilized a mouse model containing a missense mutation in Vegfr3 (dubbed Chy ) that abrogates its kinase ability.

Rethinking Autonomous Surgery: Focusing on Enhancement over Autonomy.

Context: As robot-assisted surgery is increasingly used in surgical care, the engineering research effort towards surgical automation has also increased significantly. Automation promises to enhance surgical outcomes, offload mundane or repetitive tasks, and improve workflow. However, we must ask an important question: should autonomous surgery be our long-term goal?

Objective: To provide an overview of the engineering requirements for automating control systems, summarize technical challenges in automated robotic surgery, and review sensing and modeling techniques to capture real-time human behaviors for integration into the robotic control loop for enhanced shared or collaborative control.

Interpretable deep learning uncovers cellular properties in label-free live cell images that are predictive of highly metastatic melanoma.

Deep learning has emerged as the technique of choice for identifying hidden patterns in cell imaging data but is often criticized as "black box." Here, we employ a generative neural network in combination with supervised machine learning to classify patient-derived melanoma xenografts as "efficient" or "inefficient" metastatic, validate predictions regarding melanoma cell lines with unknown metastatic efficiency in mouse xenografts, and use the network to generate in silico cell images that amplify the critical predictive cell properties. These exaggerated images unveiled pseudopodial extensions and increased light scattering as hallmark properties of metastatic cells.

A Silver Lining? Fewer Non-Severe Acute Respiratory Syndrome Coronavirus 2 Respiratory Viruses During the Coronavirus Disease 2019 Pandemic.

Nonpharmaceutical interventions (NPIs) have "flattened the curve" of the coronavirus disease 2019 pandemic; however the effect of these interventions on other respiratory viruses is unknown. We used aggregate level case count data for 8 respiratory viruses and compared the institutional and statewide case counts before and during the period that NPIs were active. We observed a 61% decrease (incidence rate ratio, 0.

What the Coronavirus Disease 2019 (COVID-19) Pandemic Has Reinforced: The Need for Accurate Data.

The COVID-19 pandemic has challenged the United States’ existing national public health informatics infrastructure. This report details the factors that have contributed to COVID-19 data inaccuracies and reporting delays and their effect on the modeling and monitoring of the COVID-19 pandemic.

Robust and automated detection of subcellular morphological motifs in 3D microscopy images.

Rapid developments in live-cell three-dimensional (3D) microscopy enable imaging of cell morphology and signaling with unprecedented detail. However, tools to systematically measure and visualize the intricate relationships between intracellular signaling, cytoskeletal organization and downstream cell morphological outputs do not exist. Here, we introduce u-shape3D, a computer graphics and machine-learning pipeline to probe molecular mechanisms underlying 3D cell morphogenesis and to test the intriguing possibility that morphogenesis itself affects intracellular signaling.

Genomic ancestry estimation quantifies use of wild species in grape breeding.

Background: Grapes are one of the world's most valuable crops and most are made into wine. Grapes belong to the genus Vitis, which includes over 60 inter-fertile species. The most common grape cultivars derive their entire ancestry from the species Vitis vinifera, but wild relatives have also been exploited to create hybrid cultivars, often with increased disease resistance.

FaRXf1: a locus conferring resistance to angular leaf spot caused by Xanthomonas fragariae in octoploid strawberry.

Angular leaf spot is a devastating bacterial disease of strawberry. Resistance from two wild accessions is highly heritable and controlled by a major locus on linkage group 6D. Angular leaf spot caused by Xanthomonas fragariae is the only major bacterial disease of cultivated strawberry (Fragaria ×ananassa).

Anti-Inflammatory Activity of Haskap Cultivars is Polyphenols-Dependent.

Haskap (Lonicera caerulea L.) berries have long been used for their health promoting properties against chronic conditions. The current study investigated the effect of Canadian haskap berry extracts on pro-inflammatory cytokines using a human monocytic cell line THP-1 derived macrophages stimulated by lipopolysaccharide.

Pilot study demonstrating potential association between breast cancer image-based risk phenotypes and genomic biomarkers.

Purpose: In this pilot study, the authors examined associations between image-based phenotypes and genomic biomarkers. The potential genetic contribution of UGT2B genes to interindividual variation in breast density and mammographic parenchymal patterns is demonstrated by performing an association study between image-based phenotypes and genomic biomarkers [single-nucleotide polymorphism (SNP) genotypes].

Methods: This candidate-gene approach study included 179 subjects for whom both mammograms and blood DNA samples had been obtained.

Enhancement of breast CADx with unlabeled data.

Purpose: Unlabeled medical image data are abundant, yet the process of converting them into a labeled ("truth-known") database is time and resource expensive and fraught with ethical and logistics issues. The authors propose a dual-stage CADx scheme in which both labeled and unlabeled (truth-known and "truth-unknown") data are used. This study is an initial exploration of the potential for leveraging unlabeled data toward enhancing breast CADx.

Exploring nonlinear feature space dimension reduction and data representation in breast Cadx with Laplacian eigenmaps and t-SNE.

Purpose: In this preliminary study, recently developed unsupervised nonlinear dimension reduction (DR) and data representation techniques were applied to computer-extracted breast lesion feature spaces across three separate imaging modalities: Ultrasound (U.S.) with 1126 cases, dynamic contrast enhanced magnetic resonance imaging with 356 cases, and full-field digital mammography with 245 cases.

Evaluation of computer-aided diagnosis on a large clinical full-field digital mammographic dataset.

Rationale And Objectives: To convert and optimize our previously developed computerized analysis methods for use with images from full-field digital mammography (FFDM) for breast mass classification to aid in the diagnosis of breast cancer.

Materials And Methods: An institutional review board approved protocol was obtained, with waiver of consent for retrospective use of mammograms and pathology data. Seven hundred thirty-nine FFDM images, which contained 287 biopsy-proven breast mass lesions, of which 148 lesions were malignant and 139 lesions were benign, were retrospectively collected.