259 research outputs found
Sensitivity of plankton biomass and productivity to variations in physical forcing and biological parameters in Chesapeake Bay
A coupled three-dimensional hydrodynamic-biogeochemical model is used to simulate plankton dynamics in Chesapeake Bay and examine its sensitivity to variations in biological parameters and physical forcing. The coupled biophysical model captures observed seasonal cycle and regional distributions of plankton in Chesapeake Bay and predicts the phase lag between the spring chlorophyll maximum and the summer primary productivity maximum. This lag traces to the delivery of dissolved inorganic nutrients in the winter-spring freshet from the Susquehanna River that fuels the spring bloom, whereas regenerated nutrients support high primary productivity in summer. The model shows that episodic wind events commonly associated with frontal passages in summer inject nutrients into the euphotic layer, leading to short periods of elevated primary productivity. Quantitative comparisons between the predicted and observed annual time series of euphotic-layer chlorophyll and primary productivity show that the model possesses reasonable skill. Sensitivity analyses of model simulations for different biological parameter values and alternative formulations of biogeochemical processes suggest that model predictions are robust. To understand the impacts of climate variability and change on Chesapeake Bay, we examine how the plankton system responds to variations in river runoff, wind forcing, temperature and light level. Annual mean chlorophyll (AMC) and annual integrated production (AIP) increase by about 70% for a doubling of river runoff, but only reduce by 30% and 13% for 50% reduction of river runoff, suggesting a nonlinear response of plankton system to changes in river runoff and nutrient loading. Doubling of wind stress results in a small increase in AMC but 28% increase in AIP. For 2°C warming AMC increases from 25.4 to 30 mg m−2 and AIP increases from 180 to 246 g C m−2 yr−1
An Iron-Based Ecosystem Model of the Central Equatorial Pacific
The central and eastern equatorial Pacific region is characterized by lower than expected phytoplankton biomass and primary production given the relatively high ambient nitrate concentrations. These unusual conditions have spawned several field programs and laboratory experiments to determine why this high nitrate-low chlorophyll pattern persists in this region. To synthesize the results from these field programs, as well as providing additional evidence in support of the iron hypothesis, we developed a one-dimensional, nine-component ecosystem model of 0 degrees N 140 degrees W. The model components include two phytoplankton size fractions, two zooplankton size fractions, two detrital size fractions, dissolved iron, nitrate, and ammonium. The model was run for 5 years (1990-1994) and was forced using an atmospheric radiative transfer model, an ocean general circulation model (GCM), and in situ data. To our knowledge, this is the first ecosystem model at 0 degrees N 140 degrees W to synthesize the Joint Global Ocean Flux Study Equatorial Pacific Process Study (JGOFS EqPac) data set, as well as to use both in situ and modeled physical data to drive the model. Modeled phytoplankton, zooplankton, and iron all varied on interannual timescales due to El Nino events. Total phytoplankton biomass increased by as much as 40% from early 1992 (El Nino warm) to 1993 (normal). The results also indicate that the biomass increase during a cool period is not constant for each phytoplankton component, but instead the increase is most evident in the netphytoplankton (\u3e10 mu m). Netphytoplankton increase from a low of 0.1% of the total chlorophyll in 1992 to a high of 30% of the total in 1993. Microzooplankton grazing rates fluctuated in response to changes in nanophytoplankton growth rates, whereas mesozooplankton grazing was unrelated to netphytoplankton growth rates. The magnitude and temporal variability of phytoplankton chlorophyll agreed well with in situ data collected during 1992. Modeled primary production was lower than measured during El Nino but agreed with observations during normal conditions. The low primary productivity was probably a result of downwelling produced by the physical model. New production was calculated from total and recycled iron rather than nitrate-based production and was more variable in general and almost 3 times the nitrate-based new production during non-El Nino conditions
Variable climatic conditions dominate recent phytoplankton dynamics in Chesapeake Bay
Variable climatic conditions strongly influence phytoplankton dynamics in estuaries globally. Our study area is Chesapeake Bay, a highly productive ecosystem providing natural resources, transportation, and recreation for nearly 16 million people inhabiting a 165,000-km2 watershed. Since World War II, nutrient over-enrichment has led to multiple ecosystem impairments caused by increased phytoplankton biomass as chlorophyll-a (chl-a). Doubled nitrogen (N) loadings from 1945–1980 led to increased chl-a, reduced water clarity, and low dissolved oxygen (DO), while decreased N loadings from 1981–2012 suggest modest improvement. The recent 30+ years are characterized by high inter-annual variability of chl-a, coinciding with irregular dry and wet periods, complicating the detection of long-term trends. Here, we synthesize time-series data for historical and recent N loadings (TN, NO2 + NO3), chl-a, floral composition, and net primary productivity (NPP) to distinguish secular changes caused by nutrient over-enrichment from spatio-temporal variability imposed by climatic conditions. Wet years showed higher chl-a, higher diatom abundance, and increased NPP, while dry years showed lower chl-a, lower diatom abundance, and decreased NPP. Our findings support a conceptual model wherein variable climatic conditions dominate recent phytoplankton dynamics against a backdrop of nutrient over-enrichment, emphasizing the need to separate these effects to gauge progress toward improving water quality in estuaries
Remote Sensing Reflectance and Inherent Optical Properties in the Mid-mesohaline Chesapeake Bay
We used an extensive set of bio-optical data and radiative transfer (RT) model simulations of radiation fields to investigate relationships between inherent optical properties and remotely sensed quantities in the optically complex, mid-mesohaline Chesapeake Bay waters. Field observations showed that the chlorophyll algorithms used by the MODIS (MODerate resolution Imaging Spectroradiometer) ocean color sensor (i.e. Chlor_a, chlor_MODIS, chlor_a_3 products) do not perform accurately in these Case 2 waters. This is because, when applied to waters with high concentrations of chlorophyll, all MODIS algorithms are based on empirical relationships between chlorophyll concentration and blue-green wavelength remote sensing reflectance (Rrs) ratios that do not account for the typically strong blue-wavelength absorption by non-covarying, dissolved and non-algal particulate components. Stronger correlation was observed between chlorophyll concentration and Rrs ratios in the red (i.e. Rrs(677)/Rrs(554)) where dissolved and non-algal particulate absorption become exponentially smaller. Regionally-specific algorithms that are based on the phytoplankton optical properties in the red wavelength region provide a better basis for satellite monitoring of phytoplankton blooms in these Case 2 waters. Good optical closure was obtained between independently measured Rrs spectra and the optical properties of backscattering, b(sub b), and absorption, a, over the wide range of in-water conditions observed in the Chesapeake Bay. Observed variability in the quantity f/Q (proportionality factor in the relationship between Rrs and the water inherent optical properties ratio b(sub b)/(a+b(sub b)) was consistent with RT model calculations for the specific measurement geometry and water bio-optical characteristics. Data and model results showed that f/Q values in these Case 2 coastal waters are not considerably different from those estimated in previous studies for Case 1 waters. Variation in surface backscattering significantly affected Rrs magnitude across the visible spectrum and was most strongly correlated (R(sup 2)=0.88) with observed variability in Rrs at 670 nm. Surface values of particulate backscattering were strongly correlated with non-algal particulate absorption, a(sub nap), in the blue wavelengths (R(sup 2)=0.83). These results, along with the measured values of backscattering fraction magnitude and non-algal particulate absorption spectral slope, suggest that suspended non-algal particles with high inorganic content are the major water constituents regulating b(sub b) variability in the mid-mesohaline Chesapeake Bay. Remote retrieval of surface b(sub b) and (a(sub nap), from Rrs(670) can be used in regionally-specific satellite algorithms to separate contribution by non-algal particles and dissolved organic matter to total light absorption in the blue, and monitor non-algal suspended particle concentration and distribution in these Case 2 waters
Bio-Optics of the Chesapeake Bay from Measurements and Radiative Transfer Calculations
We combined detailed bio-optical measurements and radiative transfer (RT) modeling to perform an optical closure experiment for optically complex and biologically productive Chesapeake Bay waters. We used this experiment to evaluate certain assumptions commonly used when modeling bio-optical processes, and to investigate the relative importance of several optical characteristics needed to accurately model and interpret remote sensing ocean-color observations in these Case 2 waters. Direct measurements were made of the magnitude, variability, and spectral characteristics of backscattering and absorption that are critical for accurate parameterizations in satellite bio-optical algorithms and underwater RT simulations. We found that the ratio of backscattering to total scattering in the mid-mesohaline Chesapeake Bay varied considerably depending on particulate loading, distance from land, and mixing processes, and had an average value of 0.0128 at 530 nm. Incorporating information on the magnitude, variability, and spectral characteristics of particulate backscattering into the RT model, rather than using a volume scattering function commonly assumed for turbid waters, was critical to obtaining agreement between RT calculations and measured radiometric quantities. In situ measurements of absorption coefficients need to be corrected for systematic overestimation due to scattering errors, and this correction commonly employs the assumption that absorption by particulate matter at near infrared wavelengths is zero
Calcium modulates force sensing by the von Willebrand factor A2 domain
von Willebrand factor (VWF) multimers mediate primary adhesion and aggregation of platelets. VWF potency critically depends on multimer size, which is regulated by a feedback mechanism involving shear-induced unfolding of the VWF-A2 domain and cleavage by the metalloprotease ADAMTS-13. Here we report crystallographic and single-molecule optical tweezers data on VWF-A2 providing mechanistic insight into calcium-mediated stabilization of the native conformation that protects A2 from cleavage by ADAMTS-13. Unfolding of A2 requires higher forces when calcium is present and primarily proceeds through a mechanically stable intermediate with non-native calcium coordination. Calcium further accelerates refolding markedly, in particular, under applied load. We propose that calcium improves force sensing by allowing reversible force switching under physiologically relevant hydrodynamic conditions. Our data show for the first time the relevance of metal coordination for mechanical properties of a protein involved in mechanosensing
The Multi-Object, Fiber-Fed Spectrographs for SDSS and the Baryon Oscillation Spectroscopic Survey
We present the design and performance of the multi-object fiber spectrographs
for the Sloan Digital Sky Survey (SDSS) and their upgrade for the Baryon
Oscillation Spectroscopic Survey (BOSS). Originally commissioned in Fall 1999
on the 2.5-m aperture Sloan Telescope at Apache Point Observatory, the
spectrographs produced more than 1.5 million spectra for the SDSS and SDSS-II
surveys, enabling a wide variety of Galactic and extra-galactic science
including the first observation of baryon acoustic oscillations in 2005. The
spectrographs were upgraded in 2009 and are currently in use for BOSS, the
flagship survey of the third-generation SDSS-III project. BOSS will measure
redshifts of 1.35 million massive galaxies to redshift 0.7 and Lyman-alpha
absorption of 160,000 high redshift quasars over 10,000 square degrees of sky,
making percent level measurements of the absolute cosmic distance scale of the
Universe and placing tight constraints on the equation of state of dark energy.
The twin multi-object fiber spectrographs utilize a simple optical layout
with reflective collimators, gratings, all-refractive cameras, and
state-of-the-art CCD detectors to produce hundreds of spectra simultaneously in
two channels over a bandpass covering the near ultraviolet to the near
infrared, with a resolving power R = \lambda/FWHM ~ 2000. Building on proven
heritage, the spectrographs were upgraded for BOSS with volume-phase
holographic gratings and modern CCD detectors, improving the peak throughput by
nearly a factor of two, extending the bandpass to cover 360 < \lambda < 1000
nm, and increasing the number of fibers from 640 to 1000 per exposure. In this
paper we describe the original SDSS spectrograph design and the upgrades
implemented for BOSS, and document the predicted and measured performances.Comment: 43 pages, 42 figures, revised according to referee report and
accepted by AJ. Provides background for the instrument responsible for SDSS
and BOSS spectra. 4th in a series of survey technical papers released in
Summer 2012, including arXiv:1207.7137 (DR9), arXiv:1207.7326 (Spectral
Classification), and arXiv:1208.0022 (BOSS Overview
Advances in cholangiocarcinoma research:report from the third Cholangiocarcinoma Foundation Annual Conference
Anti-cancer effects and mechanism of actions of aspirin analogues in the treatment of glioma cancer
INTRODUCTION: In the past 25 years only modest advancements in glioma treatment have been made, with patient prognosis and median survival time following diagnosis only increasing from 3 to 7 months. A substantial body of clinical and preclinical evidence has suggested a role for aspirin in the treatment of cancer with multiple mechanisms of action proposed including COX 2 inhibition, down regulation of EGFR expression, and NF-κB signaling affecting Bcl-2 expression. However, with serious side effects such as stroke and gastrointestinal bleeding, aspirin analogues with improved potency and side effect profiles are being developed. METHOD: Effects on cell viability following 24 hr incubation of four aspirin derivatives (PN508, 517, 526 and 529) were compared to cisplatin, aspirin and di-aspirin in four glioma cell lines (U87 MG, SVG P12, GOS – 3, and 1321N1), using the PrestoBlue assay, establishing IC50 and examining the time course of drug effects. RESULTS: All compounds were found to decrease cell viability in a concentration and time dependant manner. Significantly, the analogue PN517 (IC50 2mM) showed approximately a twofold increase in potency when compared to aspirin (3.7mM) and cisplatin (4.3mM) in U87 cells, with similar increased potency in SVG P12 cells. Other analogues demonstrated similar potency to aspirin and cisplatin. CONCLUSION: These results support the further development and characterization of novel NSAID derivatives for the treatment of glioma
A comprehensive assessment of somatic mutation detection in cancer using whole-genome sequencing.
As whole-genome sequencing for cancer genome analysis becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Here using tumour-normal sample pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, we conduct a benchmarking exercise within the context of the International Cancer Genome Consortium. We compare sequencing methods, analysis pipelines and validation methods. We show that using PCR-free methods and increasing sequencing depth to ∼ 100 × shows benefits, as long as the tumour:control coverage ratio remains balanced. We observe widely varying mutation call rates and low concordance among analysis pipelines, reflecting the artefact-prone nature of the raw data and lack of standards for dealing with the artefacts. However, we show that, using the benchmark mutation set we have created, many issues are in fact easy to remedy and have an immediate positive impact on mutation detection accuracy.We thank the DKFZ Genomics and Proteomics Core Facility and the OICR Genome Technologies Platform for provision of sequencing services. Financial support was provided by the consortium projects READNA under grant agreement FP7 Health-F4-2008-201418, ESGI under grant agreement 262055, GEUVADIS under grant agreement 261123 of the European Commission Framework Programme 7, ICGC-CLL through the Spanish Ministry of Science and Innovation (MICINN), the Instituto de Salud Carlos III (ISCIII) and the Generalitat de Catalunya. Additional financial support was provided by the PedBrain Tumor Project contributing to the International Cancer Genome Consortium, funded by German Cancer Aid (109252) and by the German Federal Ministry of Education and Research (BMBF, grants #01KU1201A, MedSys #0315416C and NGFNplus #01GS0883; the Ontario Institute for Cancer Research to PCB and JDM through funding provided by the Government of Ontario, Ministry of Research and Innovation; Genome Canada; the Canada Foundation for Innovation and Prostate Cancer Canada with funding from the Movember Foundation (PCB). PCB was also supported by a Terry Fox Research Institute New Investigator Award, a CIHR New Investigator Award and a Genome Canada Large-Scale Applied Project Contract. The Synergie Lyon Cancer platform has received support from the French National Institute of Cancer (INCa) and from the ABS4NGS ANR project (ANR-11-BINF-0001-06). The ICGC RIKEN study was supported partially by RIKEN President’s Fund 2011, and the supercomputing resource for the RIKEN study was provided by the Human Genome Center, University of Tokyo. MDE, LB, AGL and CLA were supported by Cancer Research UK, the University of Cambridge and Hutchison-Whampoa Limited. SD is supported by the Torres Quevedo subprogram (MI CINN) under grant agreement PTQ-12-05391. EH is supported by the Research Council of Norway under grant agreements 221580 and 218241 and by the Norwegian Cancer Society under grant agreement 71220-PR-2006-0433. Very special thanks go to Jennifer Jennings for administrating the activity of the ICGC Verification Working Group and Anna Borrell for administrative support.This is the final version of the article. It first appeared from Nature Publishing Group via http://dx.doi.org/10.1038/ncomms1000
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