Novel diterpenes with potent conidiation inducing activity

The isolation and structure determination of conidiogenol and conidiogenone, tetracyclic diterpenes with a novel carbon skeleton, from extracts of the fermentation broth of Penicillium cyclopium is reported. Conidiogenol and conidiogenone are potent and selective inducers of conidiogenesis in P. cyclopium in liquid culture, and relay information about the environmental conditions to the producing organism. (C) 2002 Elsevier Science Ltd. All rights reserved

Computing Scalable Multivariate Glocal Invariants of Large (Brain-) Graphs

Graphs are quickly emerging as a leading abstraction for the representation of data. One important application domain originates from an emerging discipline called "connectomics". Connectomics studies the brain as a graph; vertices correspond to neurons (or collections thereof) and edges correspond to structural or functional connections between them. To explore the variability of connectomes---to address both basic science questions regarding the structure of the brain, and medical health questions about psychiatry and neurology---one can study the topological properties of these brain-graphs. We define multivariate glocal graph invariants: these are features of the graph that capture various local and global topological properties of the graphs. We show that the collection of features can collectively be computed via a combination of daisy-chaining, sparse matrix representation and computations, and efficient approximations. Our custom open-source Python package serves as a back-end to a Web-service that we have created to enable researchers to upload graphs, and download the corresponding invariants in a number of different formats. Moreover, we built this package to support distributed processing on multicore machines. This is therefore an enabling technology for network science, lowering the barrier of entry by providing tools to biologists and analysts who otherwise lack these capabilities. As a demonstration, we run our code on 120 brain-graphs, each with approximately 16M vertices and up to 90M edges.Comment: Published as part of 2013 IEEE GlobalSIP conferenc

An Automated Images-to-Graphs Framework for High Resolution Connectomics

Reconstructing a map of neuronal connectivity is a critical challenge in contemporary neuroscience. Recent advances in high-throughput serial section electron microscopy (EM) have produced massive 3D image volumes of nanoscale brain tissue for the first time. The resolution of EM allows for individual neurons and their synaptic connections to be directly observed. Recovering neuronal networks by manually tracing each neuronal process at this scale is unmanageable, and therefore researchers are developing automated image processing modules. Thus far, state-of-the-art algorithms focus only on the solution to a particular task (e.g., neuron segmentation or synapse identification). In this manuscript we present the first fully automated images-to-graphs pipeline (i.e., a pipeline that begins with an imaged volume of neural tissue and produces a brain graph without any human interaction). To evaluate overall performance and select the best parameters and methods, we also develop a metric to assess the quality of the output graphs. We evaluate a set of algorithms and parameters, searching possible operating points to identify the best available brain graph for our assessment metric. Finally, we deploy a reference end-to-end version of the pipeline on a large, publicly available data set. This provides a baseline result and framework for community analysis and future algorithm development and testing. All code and data derivatives have been made publicly available toward eventually unlocking new biofidelic computational primitives and understanding of neuropathologies.Comment: 13 pages, first two authors contributed equally V2: Added additional experiments and clarifications; added information on infrastructure and pipeline environmen

Reaction pathways and textural aspects of the replacement of anhydrite by calcite at 25 °C

The replacement of sulfate minerals by calcium carbonate polymorphs (carbonation) has important implications in various geological processes occurring in Earth surface environments. In this paper we report the results of an experimental study of the interaction between anhydrite (100), (010), and (001) surfaces and Na₂CO₃ aqueous solutions under ambient conditions. Carbonation progress was monitored by glancing incidence X-ray diffraction (GIXRD) and scanning electron microscopy (SEM). We show that the reaction progresses through the dissolution of anhydrite and the simultaneous growth of calcite. The growth of calcite occurs oriented on the three anhydrite cleavage surfaces and its formation is accompanied by minor vaterite. The progress of the carbonation always occurs from the outer-ward to the inner-ward surfaces and its rate depends on the anhydrite surface considered, with the (001) surface being much more reactive than the (010) and (100) surfaces. The thickness of the formed carbonate layer grows linearly with time. The original external shape of the anhydrite crystals and their surface details (e.g., cleavage steps) are preserved during the carbonation reaction. Textural characteristics of the transformed regions, such as the gradation in the size of calcite crystals, from ~2 μm in the outer region to ~17 μm at the calcite-anhydrite interface, the local preservation of calcite crystalographic orientation with respect to anhydrite and the distribution of the microporosity mainly within the carbonate layer without development of any significant gap at the calcite-anhydrite interface. Finally, we compare these results on anhydrite carbonation with those on gypsum carbonation and can explain the differences on the basis of four parameters: (1) the molar volume change involved in the replacement process in each case, (2) the lack/existence of epitactic growth between parent and product phases, (3) the kinetics of dissolution of the different surfaces, and (4) the chemical composition (amount of structural water) of the parent phases

Synergistic Biomineralization Phenomena Created by a Combinatorial Nacre Protein Model System

In the nacre or aragonite layer of the mollusk shell, proteomes that regulate both the early stages of nucleation and nano-to-mesoscale assembly of nacre tablets from mineral nanoparticle precursors exist. Several approaches have been developed to understand protein-associated mechanisms of nacre formation, yet we still lack insight into how protein ensembles or proteomes manage nucleation and crystal growth. To provide additional insights, we have created a proportionally defined combinatorial model consisting of two nacre-associated proteins, C-RING AP7 (shell nacre, Haliotis rufescens) and pseudo-EF hand PFMG1 (oyster pearl nacre, Pinctada fucata), whose individual in vitro mineralization functionalities are well-documented and distinct from one another. Using scanning electron microscopy, flow cell scanning transmission electron microscopy, atomic force microscopy, Ca(II) potentiometric titrations, and quartz crystal microbalance with dissipation monitoring quantitative analyses, we find that both nacre proteins are functionally active within the same mineralization environments and, at 1:1 molar ratios, synergistically create calcium carbonate mesoscale structures with ordered intracrystalline nanoporosities, extensively prolong nucleation times, and introduce an additional nucleation event. Further, these two proteins jointly create nanoscale protein aggregates or phases that under mineralization conditions further assemble into protein–mineral polymer-induced liquid precursor-like phases with enhanced ACC stabilization capabilities, and there is evidence of intermolecular interactions between AP7 and PFMG1 under these conditions. Thus, a combinatorial model system consisting of more than one defined biomineralization protein dramatically changes the outcome of the in vitro biomineralization process