Somatostatin peptide signaling dampens cortical circuits and promotes exploratory behavior.

We sought to characterize the unique role of somatostatin (SST) in the prelimbic (PL) cortex in mice. We performed slice electrophysiology in pyramidal and GABAergic neurons to characterize the pharmacological mechanism of SST signaling and fiber photometry of GCaMP6f fluorescent calcium signals from SST neurons to characterize the activity profile of SST neurons during exploration of an elevated plus maze (EPM) and open field test (OFT). We used local delivery of a broad SST receptor (SSTR) agonist and antagonist to test causal effects of SST signaling. SSTR activation hyperpolarizes layer 2/3 pyramidal neurons, an effect that is recapitulated with optogenetic stimulation of SST neurons. SST neurons in PL are activated during EPM and OFT exploration, and SSTR agonist administration directly into the PL enhances open arm exploration in the EPM. This work describes a broad ability for SST peptide signaling to modulate microcircuits within the prefrontal cortex and related exploratory behaviors.

Region of interest (ROI) selection using vision transformer for automatic analysis using whole slide images.

Selecting regions of interest (ROI) is a common step in medical image analysis across all imaging modalities. An ROI is a subset of an image appropriate for the intended analysis and identified manually by experts. In modern pathology, the analysis involves processing multidimensional and high resolution whole slide image (WSI) tiles automatically with an overwhelming quantity of structural and functional information. Despite recent improvements in computing capacity, analyzing such a plethora of data is challenging but vital to accurate analysis. Automatic ROI detection can significantly reduce the number of pixels to be processed, speed the analysis, improve accuracy and reduce dependency on pathologists. In this paper, we present an ROI detection method for WSI and demonstrated it for human epidermal growth factor receptor 2 (HER2) grading for breast cancer patients. Existing HER2 grading relies on manual ROI selection, which is tedious, time-consuming and suffers from inter-observer and intra-observer variability. This study found that the HER2 grade changes with ROI selection. We proposed an ROI detection method using Vision Transformer and investigated the role of image magnification for ROI detection. This method yielded an accuracy of 99% using 20 × WSI and 97% using 10 × WSI for the ROI detection. In the demonstration, the proposed method increased the diagnostic agreement to 99.3% with the clinical scores and reduced the time to 15 seconds for automated HER2 grading.

Thermal conductivity of polyurethane sheets containing beryllium oxide nanofibers.

Polyvinyl alcohol/beryllium sulfate/polyethyleneimine (PVA/BeSO4/PEI) precursor nanofibers (NFs) was first fabricated to obtain PVA/BeSO4/PEI electrospun NFs by electrospinning technology, finally manufactured beryllium oxide (BeO) NFs followed by various heat treatment methods. The minimum calcination temperature for pure BeO NFs was 1000 °C, and the minimum specific surface area (5.1 m2 g-1) and pore volumes (0.0128 cm3 g-1) were at 1300 °C. 46.18% Be and 53.82% O was measured in BeO NFs by X-ray photoelectron spectroscopy. BeO NFs were then impregnated with polyurethane (PU) aqueous solution to make PU/BeO NFs heat-dissipating sheet. This heat-dissipating sheet showed superior thermal conductivity (14.4 W m-1 K-1) at 41.4 vol% BeO NFs content. The electrical insulating properties of the heat-dissipating sheet were likewise excellent (1.6 × 1012 Ω â–¡-1). In this study, the author attempted to create a thermally conductive but electrically insulating PU/BeO NFs heat-dissipating sheet that could effectively eliminate generated heat from electric equipment.

Singular Nuclei Segmentation for Automatic HER2 Quantification Using CISH Whole Slide Images.

Human epidermal growth factor receptor 2 (HER2) quantification is performed routinely for all breast cancer patients to determine their suitability for HER2-targeted therapy. Fluorescence in situ hybridization (FISH) and chromogenic in situ hybridization (CISH) are the US Food and Drug Administration (FDA) approved tests for HER2 quantification in which at least 20 cancer-affected singular nuclei are quantified for HER2 grading. CISH is more advantageous than FISH for cost, time and practical usability. In clinical practice, nuclei suitable for HER2 quantification are selected manually by pathologists which is time-consuming and laborious. Previously, a method was proposed for automatic HER2 quantification using a support vector machine (SVM) to detect suitable singular nuclei from CISH slides. However, the SVM-based method occasionally failed to detect singular nuclei resulting in inaccurate results. Therefore, it is necessary to develop a robust nuclei detection method for reliable automatic HER2 quantification. In this paper, we propose a robust U-net-based singular nuclei detection method with complementary color correction and deconvolution adapted for accurate HER2 grading using CISH whole slide images (WSIs). The efficacy of the proposed method was demonstrated for automatic HER2 quantification during a comparison with the SVM-based approach.

Screening of novel alkaloid inhibitors for vascular endothelial growth factor in cancer cells: an integrated computational approach.

Vascular endothelial growth factor (VEGF) is expressed at elevated levels by most cancer cells, which can stimulate vascular endothelial cell growth, survival, proliferation as well as trigger angiogenesis modulated by VEGF and VEGFR (a tyrosine kinase receptor) signaling. The angiogenic effects of the VEGF family are thought to be primarily mediated through the interaction of VEGF with VEGFR-2. Targeting this signaling molecule and its receptor is a novel approach for blocking angiogenesis. In recent years virtual high throughput screening has emerged as a widely accepted powerful technique in the identification of novel and diverse leads. The high resolution X-ray structure of VEGF has paved the way to introduce new small molecular inhibitors by structure-based virtual screening. In this study using different alkaloid molecules as potential novel inhibitors of VEGF, we proposed three alkaloid candidates for inhibiting VEGF and VEGFR mediated angiogenesis. As these three alkaloid compounds exhibited high scoring functions, which also highlights their high binding ability, it is evident that these alkaloids can be taken to further drug development pipelines for use as novel lead compounds to design new and effective drugs against cancer.

Automatic quantification of HER2 gene amplification in invasive breast cancer from chromogenic in situ hybridization whole slide images.

Human epidermal growth factor receptor 2 (HER2), a transmembrane tyrosine kinase receptor encoded by the ERBB2 gene on chromosome 17q12, is a predictive and prognostic biomarker in invasive breast cancer (BC). Approximately 20% of BC are HER2-positive as a result of ERBB2 gene amplification and overexpression of the HER2 protein. Quantification of HER2 is performed routinely on all invasive BCs, to assist in clinical decision making for prognosis and treatment for HER2-positive BC patients by manually counting gene signals. We propose an automated system to quantify the HER2 gene status from chromogenic in situ hybridization (CISH) whole slide images (WSI) in invasive BC. The proposed method selects untruncated and nonoverlapped singular nuclei from the cancer regions using color unmixing and machine learning techniques. Then, HER2 and chromosome enumeration probe 17 (CEP17) signals are detected based on the RGB intensity and counted per nucleus. Finally, the HER2-to-CEP17 signal ratio is calculated to determine the HER2 amplification status following the ASCO/CAP 2018 guidelines. The proposed method reduced the labor and time for the quantification. In the experiment, the correlation coefficient between the proposed automatic CISH quantification method and pathologist manual enumeration was 0.98. The p -values larger than 0.05 from the one-sided paired t -test ensured that the proposed method yields statistically indifferent results to the reference method. The method was established on WSI scanned by two different scanners. Through the experiments, the capability of the proposed system has been demonstrated.

Characterization of the Spatial and Temporal Expression of Two Soybean miRNAs Identifies SCL6 as a Novel Regulator of Soybean Nodulation.

MicroRNAs (miRNAs) control expression of endogenous target genes through transcript cleavage or translational inhibition. Legume plants can form a specialized organ, the nodule, through interaction with nitrogen fixing soil bacteria. To understand the regulatory roles of miRNAs in the nodulation process, we functionally validated gma-miR171o and gma-miR171q and their target genes in soybean. These two miRNA sequences are identical in sequence but their miRNA genes are divergent and show unique, tissue-specific expression patterns. The expression levels of the two miRNAs are negatively correlated with that of their target genes. Ectopic expression of these miRNAs in transgenic hairy roots resulted in a significant reduction in nodule formation. Both gma-miR171o and gma-miR171q target members of the GRAS transcription factor superfamily, namely GmSCL-6 and GmNSP2. Transient interaction of miRNAs and their target genes in tobacco cells further confirmed their cleavage activity. The results suggest that gma-miR171o and gma-miR171q regulate GmSCL-6 and GmNSP2, which in turn, influence expression of the Nodule inception (NIN), Early Nodulin 40 (ENOD40), and Ethylene Response Factor Required for Nodulation (ERN) genes during the Bradyrhizobium japonicum-soybean nodulation process. Collectively, our data suggest a role for two miRNAs, gma-miR171o and gma-miR171q, in regulating the spatial and temporal aspects of soybean nodulation.