In this paper, we report in detail the studies of a different self-organized copper electrodeposition carried out in an ultrathin layer of CuSO4 electrolyte. On a macroscopic scale, the morphology of the electrodeposit is fingerlike. Microscopically, each fingering branch consists of long, straight copper filaments with periodic corrugated nanostructures. Branching rate of the electrodeposit is significantly decreased, compared with the patterns grown in conventional systems. Detailed information of the growth environment in the ultrathin electrodeposition system is provided, the formation mechanism of the periodic nanostructures on the deposit filaments is explored, and the origin of the significant descent of branching rate of the electrodeposit is discussed.
Motivation The location, timing, and abundance of gene expression (both mRNA and proteins) within a tissue define the molecular mechanisms of cell functions. Recent technology breakthroughs in spatial molecular profiling, including imaging-based technologies and sequencing-based technologies, have enabled the comprehensive molecular characterization of single cells while preserving their spatial and morphological contexts. This new bioinformatics scenario calls for effective and robust computational methods to identify genes with spatial patterns. Results We represent a novel Bayesian hierarchical model to analyze spatial transcriptomics data, with several unique characteristics. It models the zero-inflated and over-dispersed counts by deploying a zero-inflated negative binomial model that greatly increases model stability and robustness. Besides, the Bayesian inference framework allows us to borrow strength in parameter estimation in a de novo fashion. As a result, the proposed model shows competitive performances in accuracy and robustness over existing methods in both simulation studies and two real data applications. Availability The related R/C ++ source code is available at https://github.com/Minzhe/BOOST-GP. Supplementary information Supplementary data are available at Bioinformatics online.
Molecular profiling technologies, such as genome sequencing and proteomics, have transformed biomedical research, but most such technologies require tissue dissociation, which leads to loss of tissue morphology and spatial information. Recent developments in spatial molecular profiling technologies have enabled the comprehensive molecular characterization of cells while keeping their spatial and morphological contexts intact. Molecular profiling data generate deep characterizations of the genetic, transcriptional and proteomic events of cells, while tissue images capture the spatial locations, organizations and interactions of the cells together with their morphology features. These data, together with cell and tissue imaging data, provide unprecedented opportunities to study tissue heterogeneity and cell spatial organization. This review aims to provide an overview of these recent developments in spatial molecular profiling technologies and the corresponding computational methods developed for analyzing such data.
Enhancing nutrient uptake and the subsequent elemental transport from the sites of application to sites of utilization is of great importance to the science and practical field application of foliar fertilizers. The aim of this study was to investigate the mobility of various foliar applied zinc (Zn) formulations in sunflower (Helianthus annuus L.) and to evaluate the effects of the addition of an organic biostimulant on phloem loading and elemental mobility. This was achieved by application of foliar formulations to the blade of sunflower (H. annuus L.) and high-resolution elemental imaging with micro X-ray fluorescence (μ-XRF) to visualize Zn within the vascular system of the leaf petiole. Although no significant increase of total Zn in petioles was determined by inductively-coupled plasma mass-spectrometer, μ-XRF elemental imaging showed a clear enrichment of Zn in the vascular tissues within the sunflower petioles treated with foliar fertilizers containing Zn. The concentration of Zn in the vascular of sunflower petioles was increased when Zn was applied with other microelements with EDTA (commercial product Kick-Off) as compared with an equimolar concentration of ZnSO4 alone. The addition of macronutrients N, P, K (commercial product CleanStart) to the Kick-Off Zn fertilizer, further increased vascular system Zn concentrations while the addition of the microbially derived organic biostimulant “GroZyme” resulted in a remarkable enhancement of Zn concentrations in the petiole vascular system. The study provides direct visualized evidence for phloem transport of foliar applied Zn out of sites of application in plants by using μ-XRF technique, and suggests that the formulation of the foliar applied Zn and the addition of the organic biostimulant GroZyme increases the mobility of Zn following its absorption by the leaf of sunflower.
BackgroundReverse engineering approaches to infer gene regulatory networks using computational methods are of great importance to annotate gene functionality and identify hub genes. Although various statistical algorithms have been proposed, development of computational tools to integrate results from different methods and user-friendly online tools is still lagging.ResultsWe developed a web server that efficiently constructs gene networks from expression data. It allows the user to use ten different network construction methods (such as partial correlation-, likelihood-, Bayesian- and mutual information-based methods) and integrates the resulting networks from multiple methods. Hub gene information, if available, can be incorporated to enhance performance.ConclusionsGeNeCK is an efficient and easy-to-use web application for gene regulatory network construction. It can be accessed at http://lce.biohpc.swmed.edu/geneck.Electronic supplementary materialThe online version of this article (10.1186/s12859-018-2560-0) contains supplementary material, which is available to authorized users.
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