265 research outputs found

    Phenotypic Signatures Arising from Unbalanced Bacterial Growth

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    Fluctuations in the growth rate of a bacterial culture during unbalanced growth are generally considered undesirable in quantitative studies of bacterial physiology. Under well-controlled experimental conditions, however, these fluctuations are not random but instead reflect the interplay between intra-cellular networks underlying bacterial growth and the growth environment. Therefore, these fluctuations could be considered quantitative phenotypes of the bacteria under a specific growth condition. Here, we present a method to identify “phenotypic signatures” by time-frequency analysis of unbalanced growth curves measured with high temporal resolution. The signatures are then applied to differentiate amongst different bacterial strains or the same strain under different growth conditions, and to identify the essential architecture of the gene network underlying the observed growth dynamics. Our method has implications for both basic understanding of bacterial physiology and for the classification of bacterial strains

    Thermal Properties of Graphene, Carbon Nanotubes and Nanostructured Carbon Materials

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    Recent years witnessed a rapid growth of interest of scientific and engineering communities to thermal properties of materials. Carbon allotropes and derivatives occupy a unique place in terms of their ability to conduct heat. The room-temperature thermal conductivity of carbon materials span an extraordinary large range - of over five orders of magnitude - from the lowest in amorphous carbons to the highest in graphene and carbon nanotubes. I review thermal and thermoelectric properties of carbon materials focusing on recent results for graphene, carbon nanotubes and nanostructured carbon materials with different degrees of disorder. A special attention is given to the unusual size dependence of heat conduction in two-dimensional crystals and, specifically, in graphene. I also describe prospects of applications of graphene and carbon materials for thermal management of electronics.Comment: Review Paper; 37 manuscript pages; 4 figures and 2 boxe

    Efficacies of carbon-based adsorbents for carbon dioxide capture

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    © 2020 by the authors. Carbon dioxide (CO2), a major greenhouse gas, capture has recently become a crucial technological solution to reduce atmospheric emissions from fossil fuel burning. Thereafter, many efforts have been put forwarded to reduce the burden on climate change by capturing and separating CO2, especially from larger power plants and from the air through the utilization of different technologies (e.g., membrane, absorption, microbial, cryogenic, chemical looping, and so on). Those technologies have often suffered from high operating costs and huge energy consumption. On the right side, physical process, such as adsorption, is a cost-effective process, which has been widely used to adsorb different contaminants, including CO2. Henceforth, this review covered the overall efficacies of CO2 adsorption from air at 196 K to 343 K and different pressures by the carbon-based materials (CBMs). Subsequently, we also addressed the associated challenges and future opportunities for CBMs. According to this review, the efficacies of various CBMs for CO2 adsorption have followed the order of carbon nanomaterials (i.e., graphene, graphene oxides, carbon nanotubes, and their composites) < mesoporous -microporous or hierarchical porous carbons < biochar and activated biochar < activated carbons

    Approaches in biotechnological applications of natural polymers

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    Natural polymers, such as gums and mucilage, are biocompatible, cheap, easily available and non-toxic materials of native origin. These polymers are increasingly preferred over synthetic materials for industrial applications due to their intrinsic properties, as well as they are considered alternative sources of raw materials since they present characteristics of sustainability, biodegradability and biosafety. As definition, gums and mucilages are polysaccharides or complex carbohydrates consisting of one or more monosaccharides or their derivatives linked in bewildering variety of linkages and structures. Natural gums are considered polysaccharides naturally occurring in varieties of plant seeds and exudates, tree or shrub exudates, seaweed extracts, fungi, bacteria, and animal sources. Water-soluble gums, also known as hydrocolloids, are considered exudates and are pathological products; therefore, they do not form a part of cell wall. On the other hand, mucilages are part of cell and physiological products. It is important to highlight that gums represent the largest amounts of polymer materials derived from plants. Gums have enormously large and broad applications in both food and non-food industries, being commonly used as thickening, binding, emulsifying, suspending, stabilizing agents and matrices for drug release in pharmaceutical and cosmetic industries. In the food industry, their gelling properties and the ability to mold edible films and coatings are extensively studied. The use of gums depends on the intrinsic properties that they provide, often at costs below those of synthetic polymers. For upgrading the value of gums, they are being processed into various forms, including the most recent nanomaterials, for various biotechnological applications. Thus, the main natural polymers including galactomannans, cellulose, chitin, agar, carrageenan, alginate, cashew gum, pectin and starch, in addition to the current researches about them are reviewed in this article.. }To the Conselho Nacional de Desenvolvimento Cientfíico e Tecnológico (CNPq) for fellowships (LCBBC and MGCC) and the Coordenação de Aperfeiçoamento de Pessoal de Nvíel Superior (CAPES) (PBSA). This study was supported by the Portuguese Foundation for Science and Technology (FCT) under the scope of the strategic funding of UID/BIO/04469/2013 unit, the Project RECI/BBB-EBI/0179/2012 (FCOMP-01-0124-FEDER-027462) and COMPETE 2020 (POCI-01-0145-FEDER-006684) (JAT)

    Laws of biology: why so few?

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    Finding fundamental organizing principles is the current intellectual front end of systems biology. From a hydrogen atom to the whole cell level, organisms manage massively parallel and massively interactive processes over several orders of magnitude of size. To manage this scale of informational complexity it is natural to expect organizing principles that determine higher order behavior. Currently, there are only hints of such organizing principles but no absolute evidences. Here, we present an approach as old as Mendel that could help uncover fundamental organizing principles in biology. Our approach essentially consists of identifying constants at various levels and weaving them into a hierarchical chassis. As we identify and organize constants, from pair-wise interactions to networks, our understanding of the fundamental principles in biology will improve, leading to a theory in biology

    Will systems biology offer new holistic paradigms to life sciences?

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    A biological system, like any complex system, blends stochastic and deterministic features, displaying properties of both. In a certain sense, this blend is exactly what we perceive as the “essence of complexity” given we tend to consider as non-complex both an ideal gas (fully stochastic and understandable at the statistical level in the thermodynamic limit of a huge number of particles) and a frictionless pendulum (fully deterministic relative to its motion). In this commentary we make the statement that systems biology will have a relevant impact on nowadays biology if (and only if) will be able to capture the essential character of this blend that in our opinion is the generation of globally ordered collective modes supported by locally stochastic atomisms

    Detection of PIGO-Deficient Cells Using Proaerolysin: A Valuable Tool to Investigate Mechanisms of Mutagenesis in the DT40 Cell System

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    While isogenic DT40 cell lines deficient in DNA repair pathways are a great tool to understand the DNA damage response to genotoxic agents by a comparison of cell toxicity in mutants and parental DT40 cells, no convenient mutation assay for mutagens currently exists for this reverse-genetic system. Here we establish a proaerolysin (PA) selection-based mutation assay in DT40 cells to identify glycosylphosphatidylinositol (GPI)-anchor deficient cells. Using PA, we detected an increase in the number of PA-resistant DT40 cells exposed to MMS for 24 hours followed by a 5-day period of phenotype expression. GPI anchor synthesis is catalyzed by a series of phosphatidylinositol glycan complementation groups (PIGs). The PIG-O gene is on the sex chromosome (Chromosome Z) in chicken cells and is critical for GPI anchor synthesis at the intermediate step. Among all the mutations detected in the sequence levels observed in DT40 cells exposed to MMS at 100 µM, we identified that ∼55% of the mutations are located at A:T sites with a high frequency of A to T transversion mutations. In contrast, we observed no transition mutations out of 18 mutations. This novel assay for DT40 cells provides a valuable tool to investigate the mode of action of mutations caused by reactive agents using a series of isogenic mutant DT40 cells

    Cdc45 Limits Replicon Usage from a Low Density of preRCs in Mammalian Cells

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    Little is known about mammalian preRC stoichiometry, the number of preRCs on chromosomes, and how this relates to replicon size and usage. We show here that, on average, each 100-kb of the mammalian genome contains a preRC composed of approximately one ORC hexamer, 4–5 MCM hexamers, and 2 Cdc6. Relative to these subunits, ∼0.35 total molecules of the pre-Initiation Complex factor Cdc45 are present. Thus, based on ORC availability, somatic cells contain ∼70,000 preRCs of this average total stoichiometry, although subunits may not be juxtaposed with each other. Except for ORC, the chromatin-bound complement of preRC subunits is even lower. Cdc45 is present at very low levels relative to the preRC subunits, but is highly stable, and the same limited number of stable Cdc45 molecules are present from the beginning of S-phase to its completion. Efforts to artificially increase Cdc45 levels through ectopic expression block cell growth. However, microinjection of excess purified Cdc45 into S-phase nuclei activates additional replication foci by three-fold, indicating that Cdc45 functions to activate dormant preRCs and is rate-limiting for somatic replicon usage. Paradoxically, although Cdc45 colocalizes in vivo with some MCM sites and is rate-limiting for DNA replication to occur, neither Cdc45 nor MCMs colocalize with active replication sites. Embryonic metazoan chromatin consists of small replicons that are used efficiently via an excess of preRC subunits. In contrast, somatic mammalian cells contain a low density of preRCs, each containing only a few MCMs that compete for limiting amounts of Cdc45. This provides a molecular explanation why, relative to embryonic replicon dynamics, somatic replicons are, on average, larger and origin efficiency tends to be lower. The stable, continuous, and rate-limiting nature of Cdc45 suggests that Cdc45 contributes to the staggering of replicon usage throughout S-phase, and that replicon activation requires reutilization of existing Cdc45 during S-phase

    A novel framework for intelligent surveillance system based on abnormal human activity detection in academic environments

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    Abnormal activity detection plays a crucial role in surveillance applications, and a surveillance system thatcan perform robustly in an academic environment has become an urgent need. In this paper, we propose a novel framework for an automatic real-time video-based surveillance system which can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment. To develop our system, we have divided the work into three phases: preprocessing phase, abnormal human activity detection phase, and content-based image retrieval phase. For motion object detection, we used the temporal-differencing algorithm and then located the motions region using the Gaussian function.Furthermore, the shape model based on OMEGA equation was used as a filter for the detected objects (i.e.,human and non-human). For object activities analysis, we evaluated and analyzed the human activities of the detected objects. We classified the human activities into two groups:normal activities and abnormal activities based on the support vector machine. The machine then provides an automatic warning in case of abnormal human activities. It also embeds a method to retrieve the detected object from the database for object recognition and identification using content-based image retrieval.Finally,a software-based simulation using MATLAB was performed and the results of the conducted experiments showed an excellent surveillance system that can simultaneously perform the tracking, semantic scene learning, and abnormality detection in an academic environment with no human intervention
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