Precision Assessment of the HPLC Phytoplankton Pigment Dataset Analyzed by NASA to Quantify Global Variability in Support of Ocean Color Remote Sensing

The ability to generate chlorophyll a (Chl a) assessments from ocean color orbital sensors, such as VIIRS and MODIS, that satisfy the requirements to be climate-quality data record (CDR) quality is contingent in part on the quality of the in situ ground or sea truth observations that serve as datasets for vicarious calibration and algorithm validation activities. NASA has a mandate to collect, analyze, and distribute in situ data of the highest possible quality with documented uncertainties and in keeping with established performance metrics. Using a dataset of over 18,000 HPLC phytoplankton pigment samples representing water collected in all major ocean basins analyzed a central laboratory (Field Support Group (FSG) of the Ocean Ecology Laboratory (OEL) at NASA Goddard Space Flight Center (GSFC)), we performed an assessment of the global precision among sample replicates of Chl a as well as major accessory pigments. We investigated the impacts of filtration volume, water basin, collection technique, pigment concentration, and different filtration volumes for replicate filters on replicate filter precision, as well as investigating any pigment-specific differences. Our results quantify sample variability with the goal of understanding any systemic biases or biogeographic influences

Biases in the In Situ Measurement of Particulate Organic Carbon and Its Effect on the Calibration and Validation of Ocean Color Sensors

Particulate organic carbon (POC) plays an oversize role, relative to its standing stock in the global carbon (C) cycle. Accurate measurement of POC is central to understanding the ocean C flux and its sensitivity to climate forcing. POC is a standard NASA ocean color data product, which lacks a consensus, quality-assured measurement protocol for satellite validation. Thus, algorithms based on field measurements lacking verified uncertainties have limited applicability towards climate data records. Different sampling and filtration protocols, and blank corrections, introduce biases in the magnitude of POC measured from the field. A significant filter blank attributable to dissolved organic C (DOC) adsorption that, until recently has been seldom corrected for, likely has introduced biases in POC global datasets

Metabolomics-Based Profiling, Antioxidant Power, and Uropathogenic Bacterial Anti-Adhesion Activity of SP4™, a Formulation with a High Content of Type-A Proanthocyanidins

Flavonoids and proanthocyanidins (PACs) have been the subject of intense scientific investigations, both for their antioxidant properties and anti-adhesion activity against uropathogenic bacteria. We investigated the metabolomics and antioxidant capacity of SP4(TM), a patent-pending formulation based on a mixture of plant extracts with a high content of bioactive PACs and other polyphenols. The total content of polyphenols (885.51 ± 14.19 mg/g), flavonoids (135.52 ± 8.98 mg/g), anthocyanins (54.84 ± 2.97 mg/g), and PACs (379.43 ± 12.44 mg/g) was quantified using UV-Vis assays. Use of HPLC-ESI-MS/MS revealed the presence of 5 flavanols (100.77 ± 3.90 mg g(−1) d.wt), 11 flavonols (59.96 ± 1.83 mg g(−1) d.wt), and 8 anthocyanins (46.96 ± 1.59 mg g(−1) d.wt), whereas MALDI-TOF MS showed that SP4(TM) contains PACs with one or more type-A interflavan bonds at each degree of polymerization. Regarding antioxidant properties, LUCS technology on HepG2 cells evidenced the ability of SP4(TM) to neutralize intracellular free radicals, inhibit membrane lipid peroxidation, quench H(2)O(2), and reduce free radicals mainly through chelating mechanism, as demonstrated by a higher FRAP value (2643.28 ± 39.86 mmol/g) compared with ABTS (139.92 ± 6.16 mmol/g) and DPPH (89.51 ± 3.91 mmol/g). Finally, the SP4(TM) type-A PAC content strongly prevented bacterial adhesion of P-fimbriated uropathogenic Escherichia coli (0.23 mg/mL). In conclusion, SP4(TM) has a strong antioxidant capacity involving multitarget mechanisms and is a potential supplement to fight urinary tract infections due to its ability to inhibit uropathogenic E. coli adhesion

Insulin-like growth factor-1 is a negative modulator of glucagon secretion

Glucagon secretion involves a combination of paracrine, autocrine, hormonal, and autonomic neural mechanisms. Type 2 diabetes often presents impaired glucagon suppression by insulin and glucose. Insulin-like growth factor-I (IGF-1) has elevated homology with insulin, and regulates pancreatic β-cells insulin secretion. Insulin and IGF-1 receptors share considerable structure homology and function. We hypothesized the existence of a mechanism linking the inhibition of α-cells glucagon secretion to IGF-1. Herein, we evaluated the association between plasma IGF-1 and glucagon levels in 116 nondiabetic adults. After adjusting for age gender and BMI, fasting glucagon levels were positively correlated with 2-h post-load glycaemia, HOMA index and fasting insulin, and were negatively correlated with IGF-1 levels. In a multivariable regression, the variables independently associated to fasting glucagon were circulating IGF-1 levels, HOMA index and BMI, explaining 20.7% variation. To unravel the molecular mechanisms beneath IGF-1 and glucagon association, we investigated whether IGF-1 directly modulates glucagon expression and secretion in an in vitro model of α-cells. Our data showed that IGF-1 inhibits the ability of low glucose concentration to stimulate glucagon expression and secretion via activation of the phosphatidylinositol-3-kinase/Akt/FoxO1 pathway. Collectively, our results suggest a new regulatory role of IGF-1 on α-cells biological function

Algorithm Development and Validation for Satellite-Derived Distributions of DOC and CDOM in the US Middle Atlantic Bight

In coastal ocean waters, distributions of dissolved organic carbon (DOC) and chromophoric dissolved organic matter (CDOM) vary seasonally and interannually due to multiple source inputs and removal processes. We conducted several oceanographic cruises within the continental margin of the U.S. Middle Atlantic Bight (MAB) to collect field measurements in order to develop algorithms to retrieve CDOM and DOC from NASA's MODIS-Aqua and SeaWiFS satellite sensors. In order to develop empirical algorithms for CDOM and DOC, we correlated the CDOM absorption coefficient (a(sub cdom)) with in situ radiometry (remote sensing reflectance, Rrs, band ratios) and then correlated DOC to Rrs band ratios through the CDOM to DOC relationships. Our validation analyses demonstrate successful retrieval of DOC and CDOM from coastal ocean waters using the MODIS-Aqua and SeaWiFS satellite sensors with mean absolute percent differences from field measurements of < 9 %for DOC, 20% for a(sub cdom)(355)1,6 % for a(sub cdom)(443), and 12% for the CDOM spectral slope. To our knowledge, the algorithms presented here represent the first validated algorithms for satellite retrieval of a(sub cdom) DOC, and CDOM spectral slope in the coastal ocean. The satellite-derived DOC and a(sub cdom) products demonstrate the seasonal net ecosystem production of DOC and photooxidation of CDOM from spring to fall. With accurate satellite retrievals of CDOM and DOC, we will be able to apply satellite observations to investigate interannual and decadal-scale variability in surface CDOM and DOC within continental margins and monitor impacts of climate change and anthropogenic activities on coastal ecosystems

Impacts of Water Clarity Variability on Temperature and Biogeochemistry in the Chesapeake Bay

Estuarine water clarity depends on the concentrations of aquatic constituents, such as colored dissolved organic matter, phytoplankton, inorganic suspended solids, and detritus, which are influenced by variations in riverine inputs. These constituents directly affect temperature because when water is opaque, sunlight heats a shallower layer of the water compared to when it is clear. Despite the importance of accurately predicting temperature variability, many numerical modeling studies do not adequately account for this key process. In this study, we quantify the effect of water clarity on heating by comparing two simulations of a hydrodynamic-biogeochemical model of the Chesapeake Bay for the years 2001-2005, in which (1) water clarity is constant in space and time for the computation of solar heating, compared to (2) a simulation where water clarity varies with modeled concentrations of light-attenuating materials. In the variable water clarity simulation, the water is more opaque, particularly in the northern region of the Bay. This decrease in water clarity reduces the total heat, phytoplankton, and nitrate throughout the Bay. During the spring and summer months, surface temperatures in the northern Bay are warmer by 0.1 degrees C and bottom temperatures are colder by 0.2 degrees C in the variable light attenuation simulation. Warmer surface temperatures encourage phytoplankton growth and nutrient uptake near the head of the Bay, and fewer nutrients are transported downstream. These impacts are greater during higher river flow years, when differences in temperature, nutrients, phytoplankton, and zooplankton extend further seaward compared to other years. This study demonstrates the consequences of utilizing different light calculations for estuarine heating and biogeochemistry

The Adsorption of Dissolved Organic Carbon onto Glass Fiber Filters and Its Effect on the Measurement of Particulate Organic Carbon: A Laboratory and Modeling Exercise

Particulate organic carbon (POC) represents a small portion of total carbon in the ocean. However, it plays a large role in the turnover of organic matter through the biological pump and other processes. Early on since the development of the POC measurement technique in the 1960s, it was known that dissolved organic carbon (DOC) adsorbs and is retained both on and in the filter. That retained DOC is measured as if it was part of the particulate fraction, an artifact that can cause significant overestimates of POC concentration. We set out to address the long-standing question of whether the magnitude of the DOC adsorption is affected by the quantity and quality of the dissolved organic matter in the sample. However, our results precluded an unequivocal answer to that question; nevertheless, the experimental data generated did allow us to develop and test predictive models that relate the mass of carbon adsorbed to the volume of sample filtered. The results indicate that the uptake of DOC can be predicted using an exponential model and that a saturation point is approached when approximately a half-liter of water is filtered. This model can be a valuable tool for correcting existing POC data sets that did not account for DOC adsorption. Nonetheless, this approach should not be regarded as a substitute for collecting in situ filter blanks in parallel with POC samples to properly correct for this artifact