151 research outputs found

    Phycomyces

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    This monographic review on a fungus is not addressed to mycologists. None of the authors has been trained or has otherwise acquired a general proficiency in mycology. They are motivated by a common interest in the performances of signal handling exhibited by the sense organs of all organisms and by the desire to attack these as yet totally obscure aspects of molecular biology by the study of a microorganism with certain desirable properties. The sporangiophore of the fungus Phycomyces is a gigantic, single-celled, erect, cylindrical, aerial hypha. It is sensitive to at least four distinct stimuli: light, gravity, stretch, and some unknown stimulus by which it avoids solid objects. These stimuli control a common output, the growth rate, producing either temporal changes in growth rate or tropic responses. We are interested in the output because it gives us information about the reception of the various signals. In the absence of external stimuli, the growth rate is controlled by internal signals keeping the network of biochemical processes in balance. The external stimuli interact with the internal signals. We wish to inquire into the early steps of this interaction. For light, for instance, the cell must have a receptor pigment as the first mediator. What kind of a molecule is this pigment? Which organelle contains it? What chemical reaction happens after a light quantum has been absorbed? And how is the information introduced by this primary photochemical event amplified in a controlled manner and processed in the next step? How do a few quanta or a few molecules trigger macroscopic responses? Will we find ourselves confronted with devices wholly distinct from anything now known in biology

    Fast and Accurate Retrieval of Methane Concentration From Imaging Spectrometer Data Using Sparsity Prior

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    The strong radiative forcing by atmospheric methane has stimulated interest in identifying natural and anthropogenic sources of this potent greenhouse gas. Point sources are important targets for quantification, and anthropogenic targets have the potential for emissions reduction. Methane point-source plume detection and concentration retrieval have been previously demonstrated using data from the Airborne Visible InfraRed Imaging Spectrometer-Next Generation (AVIRIS-NG). Current quantitative methods have tradeoffs between computational requirements and retrieval accuracy, creating obstacles for processing real-time data or large data sets from flight campaigns. We present a new computationally efficient algorithm that applies sparsity and an albedo correction to matched the filter retrieval of trace gas concentration path length. The new algorithm was tested using the AVIRIS-NG data acquired over several point-source plumes in Ahmedabad, India. The algorithm was validated using the simulated AVIRIS-NG data, including synthetic plumes of known methane concentration. Sparsity and albedo correction together reduced the root-mean-squared error of retrieved methane concentration-path length enhancement by 60.7% compared with a previous robust matched filter method. Background noise was reduced by a factor of 2.64. The new algorithm was able to process the entire 300 flight line 2016 AVIRIS-NG India campaign in just over 8 h on a desktop computer with GPU acceleration

    Fast and Accurate Retrieval of Methane Concentration from Imaging Spectrometer Data Using Sparsity Prior

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    The strong radiative forcing by atmospheric methane has stimulated interest in identifying natural and anthropogenic sources of this potent greenhouse gas. Point sources are important targets for quantification, and anthropogenic targets have potential for emissions reduction. Methane point source plume detection and concentration retrieval have been previously demonstrated using data from the Airborne Visible InfraRed Imaging Spectrometer Next Generation (AVIRIS-NG). Current quantitative methods have tradeoffs between computational requirements and retrieval accuracy, creating obstacles for processing real-time data or large datasets from flight campaigns. We present a new computationally efficient algorithm that applies sparsity and an albedo correction to matched filter retrieval of trace gas concentration-pathlength. The new algorithm was tested using AVIRIS-NG data acquired over several point source plumes in Ahmedabad, India. The algorithm was validated using simulated AVIRIS-NG data including synthetic plumes of known methane concentration. Sparsity and albedo correction together reduced the root mean squared error of retrieved methane concentration-pathlength enhancement by 60.7% compared with a previous robust matched filter method. Background noise was reduced by a factor of 2.64. The new algorithm was able to process the entire 300 flightline 2016 AVIRIS-NG India campaign in just over 8 hours on a desktop computer with GPU acceleration.Comment: 13 pages, 11 figure

    Comparison of Methods for Modeling Fractional Cover Using Simulated Satellite Hyperspectral Imager Spectra

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    Remotely sensed data can be used to model the fractional cover of green vegetation (GV), non-photosynthetic vegetation (NPV), and soil in natural and agricultural ecosystems. NPV and soil cover are difficult to estimate accurately since absorption by lignin, cellulose, and other organic molecules cannot be resolved by broadband multispectral data. A new generation of satellite hyperspectral imagers will provide contiguous narrowband coverage, enabling new, more accurate, and potentially global fractional cover products. We used six field spectroscopy datasets collected in prior experiments from sites with partial crop, grass, shrub, and low-stature resprouting tree cover to simulate satellite hyperspectral data, including sensor noise and atmospheric correction artifacts. The combined dataset was used to compare hyperspectral index-based and spectroscopic methods for estimating GV, NPV, and soil fractional cover. GV fractional cover was estimated most accurately. NPV and soil fractions were more difficult to estimate, with spectroscopic methods like partial least squares (PLS) regression, spectral feature analysis (SFA), and multiple endmember spectral mixture analysis (MESMA) typically outperforming hyperspectral indices. Using an independent validation dataset, the lowest root mean squared error (RMSE) values were 0.115 for GV using either normalized difference vegetation index (NDVI) or SFA, 0.164 for NPV using PLS, and 0.126 for soil using PLS. PLS also had the lowest RMSE averaged across all three cover types. This work highlights the need for more extensive and diverse fine spatial scale measurements of fractional cover, to improve methodologies for estimating cover in preparation for future hyperspectral global monitoring missions

    Spectroscopic and Mechanistic Studies of Heterodimetallic Forms of Metallo-β-lactamase NDM-1

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    In an effort to characterize the roles of each metal ion in metallo-β-lactamase NDM-1, heterodimetallic analogues (CoCo-, ZnCo-, and CoCd-) of the enzyme were generated and characterized. UV–vis, 1H NMR, EPR, and EXAFS spectroscopies were used to confirm the fidelity of the metal substitutions, including the presence of a homogeneous, heterodimetallic cluster, with a single-atom bridge. This marks the first preparation of a metallo-β-lactamase selectively substituted with a paramagnetic metal ion, Co(II), either in the Zn1 (CoCd-NDM-1) or in the Zn2 site (ZnCo-NDM-1), as well as both (CoCo-NDM-1). We then used these metal-substituted forms of the enzyme to probe the reaction mechanism, using steady-state and stopped-flow kinetics, stopped-flow fluorescence, and rapid-freeze-quench EPR. Both metal sites show significant effects on the kinetic constants, and both paramagnetic variants (CoCd- and ZnCo-NDM-1) showed significant structural changes on reaction with substrate. These changes are discussed in terms of a minimal kinetic mechanism that incorporates all of the data

    Deadly diving? Physiological and behavioural management of decompression stress in diving mammals

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    © The Author(s), 2011. This article is distributed under the terms of the Creative Commons Attribution License. The definitive version was published in Proceedings of the Royal Society B Biological Sciences 279 (2012): 1041-1050, doi:10.1098/rspb.2011.2088.Decompression sickness (DCS; ‘the bends’) is a disease associated with gas uptake at pressure. The basic pathology and cause are relatively well known to human divers. Breath-hold diving marine mammals were thought to be relatively immune to DCS owing to multiple anatomical, physiological and behavioural adaptations that reduce nitrogen gas (N2) loading during dives. However, recent observations have shown that gas bubbles may form and tissue injury may occur in marine mammals under certain circumstances. Gas kinetic models based on measured time-depth profiles further suggest the potential occurrence of high blood and tissue N2 tensions. We review evidence for gas-bubble incidence in marine mammal tissues and discuss the theory behind gas loading and bubble formation. We suggest that diving mammals vary their physiological responses according to multiple stressors, and that the perspective on marine mammal diving physiology should change from simply minimizing N2 loading to management of the N2 load. This suggests several avenues for further study, ranging from the effects of gas bubbles at molecular, cellular and organ function levels, to comparative studies relating the presence/absence of gas bubbles to diving behaviour. Technological advances in imaging and remote instrumentation are likely to advance this field in coming years.This paper and the workshop it stemmed from were funded by the Woods Hole Oceanographic Institution Marine Mammal Centre

    Barnegat Bay-Little Egg Harbor Estuary : case study of a highly eutrophic coastal bay system

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    Author Posting. © The Author(s), 2007. This is the author's version of the work. It is posted here by permission of Ecological Society of America for personal use, not for redistribution. The definitive version was published in Ecological Applications 17 (2007): S3–S16, doi:10.1890/05-0800.1.The Barnegat Bay-Little Egg Harbor Estuary is classified here as a highly eutrophic estuary based on application of NOAA’s National Estuarine Eutrophication Assessment model. Because it is shallow, poorly flushed, and bordered by highly developed watershed areas, the estuary is particularly susceptible to the effects of nutrient loading. Most of this load (~50%) is from surface water inflow, but substantial fractions also originate from atmospheric deposition (~39%), and direct groundwater discharges (~11%). No point source inputs of nutrients exist in the Barnegat Bay watershed. Since 1980, all treated wastewater from the Ocean County Utilities Authority's regional wastewater treatment system has been discharged 1.6 km offshore in the Atlantic Ocean. Eutrophy causes problems in this system, including excessive micro- and macroalgal growth, harmful algal blooms (HABs), altered benthic invertebrate communities, impacted harvestable fisheries, and loss of essential habitat (i.e., seagrass and shellfish beds). Similar problems are evident in other shallow lagoonal estuaries of the Mid-Atlantic and South Atlantic regions. To effectively address nutrient enrichment problems in the Barnegat Bay-Little Egg Harbor Estuary, it is important to determine the nutrient loading levels that produce observable impacts in the system. It is also vital to continually monitor and assess priority indicators of water quality change and estuarine health. In addition, the application of a new generation of innovative models using web-based tools (e.g., NLOAD) will enable researchers and decision-makers to more successfully manage nutrient loads from the watershed. Finally, the implementation of stormwater retrofit projects should have beneficial effects on the system.Financial support of the Barnegat Bay National Estuary Program and Jacques Cousteau National Estuarine Research Reserve is gratefully acknowledged

    Novel therapies in breast cancer: what is new from ASCO 2008

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    <p>Abstract</p> <p>Introduction</p> <p>Breast cancer is the most common female cancer and the second most common cause of female cancer-related deaths in the United States. World-wide, more than one million women will be diagnosed with breast cancer annually. In 2007, more than 175,000 women were diagnosed with breast cancer in the United States. However, deaths due to breast cancer have decreased in the recent years in part because of improved screening techniques, surgical interventions, understanding of the pathogenesis of the disease, and utilization of traditional chemotherapies in a more efficacious manner. One of the more exciting areas of improvement in the treatment of breast cancer is the entrance of novel therapies now available to oncologists. In the field of cancer therapeutics, the area of targeted and biologic therapies has been progressing at a rapid rate, particularly in the treatment of breast cancer.</p> <p>Since the advent of imatinib for the successful treatment of chronic myelogenous leukemia in the 2001, clinicians have been searching for comparable therapies that could be as efficacious and as tolerable. In order for targeted therapies to be effective, the agent must be able to inhibit critical regulatory pathways which promote tumor cell growth and proliferation. The targets must be identifiable, quantifiable and capable of being interrupted.</p> <p>In the field of breast cancer, two advances in targeted therapy have led to great strides in the understanding and treatment of breast cancer, namely hormonal therapy for estrogen positive receptor breast cancer and antibodies directed towards the inhibition of human epidermal growth factor receptor (HER)2. These advances have revolutionized the understanding and the treatment strategies for breast cancer. Building upon these successes, a host of novel agents are currently being investigated and used in clinical trials that will hopefully prove to be as fruitful. This review will focus on novel therapies in the field of breast cancer with a focus on metastatic breast cancer (MBC) and updates from the recent annual ASCO meeting and contains a summary of the results.</p
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