107 research outputs found

    Fluorescent analysis of photosynthetic microbes and Polycyclic Aromatic Hydrocarbons linked to optical remote sensing

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    Fluorescence analysis, being a non-invasive technique, has become one of the most powerful and widely used techniques for microbiologists and chemists to study various types of sample from photosynthetic microbes to hydrocarbons. The work reported here focuses on experimental results of fluorescent features of photosynthetic microbial species (cyanobacteria) and also five different crude oil samples. The cyanobacteria samples were collected from the Baltic Sea at the end of July 2011 and were associated with cyanobacterial bloom events, and the crude oil samples were from various oil spill events. The aim of the study was to find fluorescent biosignatures of cyanobacteria (initially a species specific to the Baltic Sea) and the fingerprints of crude oil; oil spills can be difficult to differentiate from biogenic films when using Synthetic Aperture Radar (SAR) or sunglint contaminated optical imagery. All samples were measured using a Perkin Elmer LS55 Luminescence spectrometer over a broad range of excitation and emission wavelength from ultraviolet (UV) to near infrared (NIR). The results are presented in Excitation Emission Matrices (EEMs) that exhibit the fluorescent features of each sample. In the EEM of the seawater sample containing cyanobacteria, there is an intense emission peak from tryptophan with fluorescent excitation and emission peaks at 285 and 345 nm respectively. In addition, fluorescent signatures of phycocyanin and chlorophyll-a are present with excitation and emission centre wavelengths at 555 nm, 645 nm and 390 nm, 685 nm, respectively. Additionally, the fluorescence signatures of Polycyclic Aromatic Hydrocarbons (PAHs) are present in the EEMs of crude oil samples with excitation and emission peaks at 285 nm and 425 nm. This study underpins further research on how to distinguish cyanobacteria species by their fluorescence signatures and the potential role that PAHs play in detection of cyanobacteria fluorescence features

    Conjugacy of one-dimensional one-sided cellular automata is undecidable

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    Two cellular automata are strongly conjugate if there exists a shift-commuting conjugacy between them. We prove that the following two sets of pairs (F,G)(F,G) of one-dimensional one-sided cellular automata over a full shift are recursively inseparable: (i) pairs where FF has strictly larger topological entropy than GG, and (ii) pairs that are strongly conjugate and have zero topological entropy. Because there is no factor map from a lower entropy system to a higher entropy one, and there is no embedding of a higher entropy system into a lower entropy system, we also get as corollaries that the following decision problems are undecidable: Given two one-dimensional one-sided cellular automata FF and GG over a full shift: Are FF and GG conjugate? Is FF a factor of GG? Is FF a subsystem of GG? All of these are undecidable in both strong and weak variants (whether the homomorphism is required to commute with the shift or not, respectively). It also immediately follows that these results hold for one-dimensional two-sided cellular automata.Comment: 12 pages, 2 figures, accepted for SOFSEM 201

    Fluorescence characterization of clinically-important bacteria

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    Healthcare-associated infections (HCAI/HAI) represent a substantial threat to patient health during hospitalization and incur billions of dollars additional cost for subsequent treatment. One promising method for the detection of bacterial contamination in a clinical setting before an HAI outbreak occurs is to exploit native fluorescence of cellular molecules for a hand-held, rapid-sweep surveillance instrument. Previous studies have shown fluorescence-based detection to be sensitive and effective for food-borne and environmental microorganisms, and even to be able to distinguish between cell types, but this powerful technique has not yet been deployed on the macroscale for the primary surveillance of contamination in healthcare facilities to prevent HAI. Here we report experimental data for the specification and design of such a fluorescence-based detection instrument. We have characterized the complete fluorescence response of eleven clinically-relevant bacteria by generating excitation-emission matrices (EEMs) over broad wavelength ranges. Furthermore, a number of surfaces and items of equipment commonly present on a ward, and potentially responsible for pathogen transfer, have been analyzed for potential issues of background fluorescence masking the signal from contaminant bacteria. These include bedside handrails, nurse call button, blood pressure cuff and ward computer keyboard, as well as disinfectant cleaning products and microfiber cloth. All examined bacterial strains exhibited a distinctive double-peak fluorescence feature associated with tryptophan with no other cellular fluorophore detected. Thus, this fluorescence survey found that an emission peak of 340nm, from an excitation source at 280nm, was the cellular fluorescence signal to target for detection of bacterial contamination. The majority of materials analysed offer a spectral window through which bacterial contamination could indeed be detected. A few instances were found of potential problems of background fluorescence masking that of bacteria, but in the case of the microfiber cleaning cloth, imaging techniques could morphologically distinguish between stray strands and bacterial contamination

    Limit laws of entrance times for low complexity Cantor minimal systems

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    This paper is devoted to the study of limit laws of entrance times to cylinder sets for Cantor minimal systems of zero entropy using their representation by means of ordered Bratteli diagrams. We study in detail substitution subshifts and we prove these limit laws are piecewise linear functions. The same kind of results is obtained for classical low complexity systems given by non stationary ordered Bratteli diagrams

    Transitory Microbial Habitat in the Hyperarid Atacama Desert

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    Traces of life are nearly ubiquitous on Earth. However, a central unresolved question is whether these traces always indicate an active microbial community or whether, in extreme environments, such as hyperarid deserts, they instead reflect just dormant or dead cells. Although microbial biomass and diversity decrease with increasing aridity in the Atacama Desert, we provide multiple lines of evidence for the presence of an at times metabolically active, microbial community in one of the driest places on Earth. We base this observation on four major lines of evidence: a physico-chemical characterization of the soil habitability after an exceptional rain event, identified biomolecules indicative of potentially active cells [e.g., presence of ATP, phospholipid fatty acids (PLFAs), metabolites, and enzymatic activity], measurements of in situ replication rates of genomes of uncultivated bacteria reconstructed from selected samples, and microbial community patterns specific to soil parameters and depths. We infer that the microbial populations have undergone selection and adaptation in response to their specific soil microenvironment and in particular to the degree of aridity. Collectively, our results highlight that even the hyperarid Atacama Desert can provide a habitable environment for microorganisms that allows them to become metabolically active following an episodic increase in moisture and that once it decreases, so does the activity of the microbiota. These results have implications for the prospect of life on other planets such as Mars, which has transitioned from an earlier wetter environment to today's extreme hyperaridity. [Abstract copyright: Copyright © 2018 the Author(s). Published by PNAS.

    Correlation versus Causation? Pharmacovigilance of the Analgesic Flupirtine Exemplifies the Need for Refined Spontaneous ADR Reporting

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    Annually, adverse drug reactions result in more than 2,000,000 hospitalizations and rank among the top 10 causes of death in the United States. Consequently, there is a need to continuously monitor and to improve the safety assessment of marketed drugs. Nonetheless, pharmacovigilance practice frequently lacks causality assessment. Here, we report the case of flupirtine, a centrally acting non-opioid analgesic. We re-evaluated the plausibility and causality of 226 unselected, spontaneously reported hepatobiliary adverse drug reactions according to the adapted Bradford-Hill criteria, CIOMS score and WHO-UMC scales. Thorough re-evaluation showed that only about 20% of the reported cases were probable or likely for flupirtine treatment, suggesting an incidence of flupirtine-related liver injury of 1∶ 100,000 when estimated prescription data are considered, or 0.8 in 10,000 on the basis of all 226 reported adverse drug reactions. Neither daily or cumulative dose nor duration of treatment correlated with markers of liver injury. In the majority of cases (151/226), an average of 3 co-medications with drugs known for their liver liability was observed that may well be causative for adverse drug reactions, but were reported under a suspected flupirtine ADR. Our study highlights the need to improve the quality and standards of ADR reporting. This should be done with utmost care taking into account contributing factors such as concomitant medications including over-the-counter drugs, the medical history and current health conditions, in order to avoid unjustified flagging and drug warnings that may erroneously cause uncertainty among healthcare professionals and patients, and may eventually lead to unjustified safety signals of useful drugs with a reasonable risk to benefit ratio

    A Computational Approach to Analyze the Mechanism of Action of the Kinase Inhibitor Bafetinib

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    Prediction of drug action in human cells is a major challenge in biomedical research. Additionally, there is strong interest in finding new applications for approved drugs and identifying potential side effects. We present a computational strategy to predict mechanisms, risks and potential new domains of drug treatment on the basis of target profiles acquired through chemical proteomics. Functional protein-protein interaction networks that share one biological function are constructed and their crosstalk with the drug is scored regarding function disruption. We apply this procedure to the target profile of the second-generation BCR-ABL inhibitor bafetinib which is in development for the treatment of imatinib-resistant chronic myeloid leukemia. Beside the well known effect on apoptosis, we propose potential treatment of lung cancer and IGF1R expressing blast crisis
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