evoText: A new tool for analyzing the biological sciences

We introduce here evoText, a new tool for automated analysis of the literature in the biological sciences. evoText contains a database of hundreds of thousands of journal articles and an array of analysis tools for generating quantitative data on the nature and history of life science, especially ecology and evolutionary biology. This article describes the features of evoText, presents a variety of examples of the kinds of analyses that evoText can run, and offers a brief tutorial describing how to use it

Enhanced root-to-shoot translocation of cadmium in the hyperaccumulating ecotype of Sedum alfredii

Sedum alfredii (Crasulaceae) is the only known Cd-hyperaccumulating species that are not in the Brassica family; the mechanism of Cd hyperaccumulation in this plant is, however, little understood. Here, a combination of radioactive techniques, metabolic inhibitors, and fluorescence imaging was used to contrast Cd uptake and translocation between a hyperaccumulating ecotype (HE) and a non-hyperaccumulating ecotype (NHE) of S. alfredii. The Km of 109Cd influx into roots was similar in both ecotypes, while the Vmax was 2-fold higher in the HE. Significant inhibition of Cd uptake by low temperature or metabolic inhibitors was observed in the HE, whereas the effect was less pronounced in the NHE. 109Cd influx into roots was also significantly decreased by high Ca in both ecotypes. The rate of root-to-shoot translocation of 109Cd in the HE was >10 times higher when compared with the NHE, and shoots of the HE accumulated dramatically higher 109Cd concentrations those of the NHE. The addition of the metabolic inhibitor carbonyl cyanide m-chlorophenylhydrazone (CCCP) resulted in a significant reduction in Cd contents in the shoots of the HE, and in the roots of the NHE. Cd was distributed preferentially to the root cylinder of the HE but not the NHE, and there was a 3–5 times higher Cd concentration in xylem sap of the HE in contrast to the NHE. These results illustrate that a greatly enhanced rate of root-to-shoot translocation, possibly as a result of enhanced xylem loading, rather than differences in the rate of root uptake, was the pivotal process expressed in the Cd hyperaccumulator HE S. alfredii

The BioDICE Taverna plugin for clustering and visualization of biological data: a workflow for molecular compounds exploration

Background: In many experimental pipelines, clustering of multidimensional biological datasets is used to detect hidden structures in unlabelled input data. Taverna is a popular workflow management system that is used to design and execute scientific workflows and aid in silico experimentation. The availability of fast unsupervised methods for clustering and visualization in the Taverna platform is important to support a data-driven scientific discovery in complex and explorative bioinformatics applications. Results: This work presents a Taverna plugin, the Biological Data Interactive Clustering Explorer (BioDICE), that performs clustering of high-dimensional biological data and provides a nonlinear, topology preserving projection for the visualization of the input data and their similarities. The core algorithm in the BioDICE plugin is Fast Learning Self Organizing Map (FLSOM), which is an improved variant of the Self Organizing Map (SOM) algorithm. The plugin generates an interactive 2D map that allows the visual exploration of multidimensional data and the identification of groups of similar objects. The effectiveness of the plugin is demonstrated on a case study related to chemical compounds. Conclusions: The number and variety of available tools and its extensibility have made Taverna a popular choice for the development of scientific data workflows. This work presents a novel plugin, BioDICE, which adds a data-driven knowledge discovery component to Taverna. BioDICE provides an effective and powerful clustering tool, which can be adopted for the explorative analysis of biological datasets

Artificial intelligence in biological activity prediction

Artificial intelligence has become an indispensable resource in chemoinformatics. Numerous machine learning algorithms for activity prediction recently emerged, becoming an indispensable approach to mine chemical information from large compound datasets. These approaches enable the automation of compound discovery to find biologically active molecules with important properties. Here, we present a review of some of the main machine learning studies in biological activity prediction of compounds, in particular for sweetness prediction. We discuss some of the most used compound featurization techniques and the major databases of chemical compounds relevant to these tasks.This study was supported by the European Commission through project SHIKIFACTORY100 - Modular cell factories for the production of 100 compounds from the shikimate pathway (Reference 814408), and by the Portuguese FCT under the scope of the strategic funding of UID/BIO/04469/2019 unit and BioTecNorte operation (NORTE-01-0145-FEDER-000004) funded by the European Regional Development Fund under the scope of Norte2020.info:eu-repo/semantics/publishedVersio

The cognitive integration of scientific instruments: Information, situated cognition, and scientific practice

Researchers in the biological and biomedical sciences, particularly those working in laboratories, use a variety of artifacts to help them perform their cognitive tasks. This paper analyses the relationship between researchers and cognitive artifacts in terms of integration. It first distinguishes different categories of cognitive artifacts used in biological practice on the basis of their informational properties. This results in a novel classification of scientific instruments, conducive to an analysis of the cognitive interactions between researchers and artifacts. It then uses a multidimensional framework in line with complementarity-based extended and distributed cognition theory to conceptualize how deeply instruments in different informational categories are integrated into the cognitive systems of their users. The paper concludes that the degree of integration depends on various factors, including the amount of informational malleability, the intensity and kind of information flow between agent and artifact, the trustworthiness of the information, the procedural and informational transparency, and the degree of individualisation

Characterization and subtraction of luminescence background signals in high-wavenumber Raman spectra of human tissue

Raman spectroscopy in the high-wavenumber spectral region (HWR) is particularly suited for fiber-optic in vivo medical applications. The most-used fiber-optic materials have negligible Raman signal in the HWR. This enables the use of simple and cheap single-fiber-optic probes that can be fitted in endoscopes and needles. The HWR generally shows less tissue luminescence than the fingerprint region. However, the luminescence can still be stronger than the Raman signal. Hardware- and software-based strategies have been developed to correct for these luminescence signals. Typically, hardware-based strategies are more complex and expensive than software-based solutions. Effective software strategies have almost exclusively been developed for the fingerprint region. First-order polynomial baseline fitting (PBF) is the most common background/luminescence estimation employed for the HWR. The goal of this study was to characterize the luminescence background signals of HW spectra of human oral tissue and compare the performance of two algorithms for correction of these background signals: PBF and multiple regression fitting (MRF). In the MRF method, we introduce here, prior knowledge of the range of Raman signals that can be obtained from the tissues of interest is explicitly used. MRF is more robust than PBF because it does not require an a priori choice of the polynomial order for fitting the background signal. This is important because, as we show, no single polynomial order can optimally characterize all backgrounds that are encountered in HW tissue spectra. We conclude that MRF should be the preferred method for background subtraction in the HWR

DNA microarray revealed and RNAi plants confirmed key genes conferring low Cd accumulation in barley grains

List of genes down-regulated in both W6nk2 and Zhenong8 after 15 days exposure to 5 ΟM Cd. (DOC 130 kb

An Overview of Three Promising Mechanical, Optical, and Biochemical Engineering Approaches to Improve Selective Photothermolysis of Refractory Port Wine Stains

During the last three decades, several laser systems, ancillary technologies, and treatment modalities have been developed for the treatment of port wine stains (PWSs). However, approximately half of the PWS patient population responds suboptimally to laser treatment. Consequently, novel treatment modalities and therapeutic techniques/strategies are required to improve PWS treatment efficacy. This overview therefore focuses on three distinct experimental approaches for the optimization of PWS laser treatment. The approaches are addressed from the perspective of mechanical engineering (the use of local hypobaric pressure to induce vasodilation in the laser-irradiated dermal microcirculation), optical engineering (laser-speckle imaging of post-treatment flow in laser-treated PWS skin), and biochemical engineering (light- and heat-activatable liposomal drug delivery systems to enhance the extent of post-irradiation vascular occlusion)

The health care costs of childhood obesity in Australia : an instrumental variables approach

The effect of childhood obesity on medical costs incurred by the Australian Government is estimated using five waves of panel data from the Longitudinal Study of Australian Children, which is linked to public health insurance administrative records from Medicare Australia. Instrumental variables estimators are used to address concerns about measurement error and selection bias. The additional annual medical costs due to overweight and obesity among 6 to 13 year olds is about $43 million (in 2015 AUD). This is driven by a higher utilisation of general practitioner and specialist doctors. The results suggest that the economic consequences of childhood obesity are much larger than previously estimated