57 resultados para trace minerals


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Carbon and nitrogen stable isotope analysis (SIA) has identified the terrestrial subsidy of freshwater food-webs but relies on different 13C fractionation in aquatic and terrestrial primary producers. However dissolved inorganic carbon (DIC) is partly comprised of 13C depleted respiration of terrestrial C and ‘old’ C derived from weathering of catchment geology. SIA thus fails to differentiate between the contribution of old and recently fixed terrestrial C. DIC in alkaline lakes is partially derived from weathering of 14C-free carbonaceous bedrock This
yields an artificial age offset leading samples to appear significantly older than their actual age. As such, 14C can be used as a biomarker to identify the proportion of autochthonous C in the food-web. With terrestrial C inputs likely to increase, the origin and utilisation of ‘old’ or ‘recent’ allochthonous C in the food-web can also be determined. Stable isotopes and 14C were measured for biota, particulate organic matter (POM), DIC and dissolved organic carbon (DOC) from Lough Erne, Northern Ireland, a humic but alkaline lake. High winter δ15N values in calanoid zooplankton (δ15N =24‰) relative to phytoplankton and POM (δ15N =6‰ and 12‰ respectively) may reflect several microbial trophic levels between terrestrial C and calanoids. Furthermore winter calanoid 14C ages are consistent with DOC from inflowing rivers (87 and 75 years BP respectively) but not phytoplankton (355 years BP). Summer calanoid δ13N, δ15N and 14C (312 years BP) indicate greater reliance on phytoplankton. There is also temporal and spatial variation in DIC, DOC and POM C isotopes.

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Globally lakes bury and remineralise significant quantities of terrestrial C, and the associated flux of terrestrial C strongly influences their functioning. Changing deposition chemistry, land use and climate induced impacts on hydrology will affect soil biogeochemistry and terrestrial C export1 and hence lake ecology with potential feedbacks for regional and global C cycling. C and nitrogen stable isotope analysis (SIA) has identified the terrestrial subsidy of freshwater food webs. The approach relies on different 13C fractionation in aquatic and terrestrial primary producers, but also that inorganic C demands of aquatic primary producers are partly met by 13C depleted C from respiration of terrestrial C, and ‘old’ C derived from weathering of catchment geology. SIA thus fails to differentiate between the contributions of old and recently fixed terrestrial C. Natural abundance 14C can be used as an additional biomarker to untangle riverine food webs2 where aquatic and terrestrial δ 13C overlap, but may also be valuable for examining the age and origin of C in the lake. Primary production in lakes is based on dissolved inorganic C (DIC). DIC in alkaline lakes is partially derived from weathering of carbonaceous bedrock, a proportion of which is14C-free. The low 14C activity yields an artificial age offset leading samples to appear hundreds to thousands of years older than their actual age. As such, 14C can be used to identify the proportion of autochthonous C in the food-web. With terrestrial C inputs likely to increase, the origin and utilisation of ‘fossil’ or ‘recent’ allochthonous C in the food-web can also be determined. Stable isotopes and 14C were measured for biota, particulate organic matter (POM), DIC and dissolved organic carbon (DOC) from Lough Erne, Northern Ireland, a humic alkaline lake. Temporal and spatial variation was evident in DIC, DOC and POM C isotopes with implications for the fluctuation in terrestrial export processes. Ramped pyrolysis of lake surface sediment indicates the burial of two C components. 14C activity (507 ± 30 BP) of sediment combusted at 400˚C was consistent with algal values and younger than bulk sediment values (1097 ± 30 BP). The sample was subsequently combusted at 850˚C, yielding 14C values (1471 ± 30 BP) older than the bulk sediment age, suggesting that fossil terrestrial carbon is also buried in the sediment. Stable isotopes in the food web indicate that terrestrial organic C is also utilised by lake organisms. High winter δ 15N values in calanoid zooplankton (δ 15N = 24%¸) relative to phytoplankton and POM (δ 15N = 6h and 12h respectively) may reflect several microbial trophic levels between terrestrial C and calanoids. Furthermore winter calanoid 14C ages are consistent with DOC from an inflowing river (75 ± 24 BP), not phytoplankton (367 ± 70 BP). Summer calanoid δ 13C, δ 15N and 14C (345 ± 80 BP) indicate greater reliance on phytoplankton.

1 Monteith, D.T et al., (2007) Dissolved organic carbon trends resulting from changes in atmospheric deposition chemistry. Nature, 450:537-535

2 Caraco, N., et al.,(2010) Millennial-aged organic carbon subsidies to a modern river food web. Ecology,91: 2385-2393.

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The study assessed accessory minerals and metals in Tanzanian vermiculites with respect to their potential suitability for agricultural applications. Mineral and chemical analyses were involved. Pot experiments were also conducted to assess plant uptake of metals from soil with vermiculites. Fibrous sepiolite and amphiboles were minerals of health concern found in some samples. The sepiolite fibers had aspect ratios similar to those of asbestos minerals, which cause respiratory disorders and lung cancer when inhaled and thus pose a potential health risk to animals and humans. The amphibole fibers were thicker than 10 μm and are unlikely to be inhaled. Chromium (Cr) and nickel (Ni) concentrations in some samples were greater than the limits permitted in agricultural soils, but the elements are not highly plant available and do not inhibit the uptake of essential macronutrients. Heating vermiculites at 400-600° C enhanced extractability of Cr and Ni and should preferably be avoided. © Taylor & Francis Group, LLC.

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Sixty samples of milk, Halloumi cheese and local grazing plants (i.e. shrubs) were collected over a year from dairy farms located on three different locations of Cyprus. Major and trace elements were quantified using inductively coupled plasma-atomic emission spectroscopy (ICP-AES). Milk and Halloumi cheese produced in different geographical locations presented significant differences in the concentration of some of the elements analysed. Principal component analysis showed grouping of samples according to the region of production for both milk and cheese samples. These findings show that the assay of elements can provide useful fingerprints for the characterisation of dairy products.

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Preeclampsia (PE) affects approximately 5% of all pregnancies, but is increased several-fold in women with pre-gestational type 1 diabetes mellitus (T1DM). Increased oxidative stress and altered maternal plasma trace elements that modulate the antioxidant system have been implicated in PE. In non-diabetic women, increased plasma copper and iron and decreased manganese, selenium, and zinc have been associated with PE in cross-sectional studies. In a longitudinal study, we hypothesized that plasma levels of trace elements differ between T1DM women with vs. without subsequent PE. Samples were collected during the first (gestation 12.2 ± 1.9 weeks, [mean ± SD]), second (21.6 ± 1.5 weeks), and third (31.5 ± 1.7 weeks) trimesters of pregnancy, all before the onset of PE. We compared 23 T1DM women who subsequently developed PE with 24 T1DM women who remained normotensive; and we included 19 non-diabetic (non-DM) normotensive pregnant women as reference controls. Trace elements were measured using inductively coupled plasma mass spectroscopy. In T1DM women with subsequent PE vs normotensive, only plasma zinc was significantly higher at the first trimester, while copper:zinc and copper:high-density lipoprotein cholesterol ratios were higher throughout gestation (all P < .05). These findings persisted after adjustment for covariates. Higher copper:zinc ratios may contribute to oxidative stress in T1DM women who develop PE. Ratios of pro- to anti-oxidant factors may predict risk for PE in diabetic pregnancies more effectively than individual trace element levels.

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Structural and functional information encoded in DNA combined with unique properties of nanomaterials could be of use for the construction of novel biocomputational circuits and intelligent biomedical nanodevices. However, at present their practical applications are still limited by either low reproducibility of fabrication, modest sensitivity, or complicated handling procedures. Here, we demonstrate the construction of label-free and switchable molecular logic gates (AND, INHIBIT, and OR) that use specific conformation modulation of a guanine- and thymine-rich DNA, while the optical readout is enabled by the tunable metamaterials which serve as a substrate for surface enhanced Raman spectroscopy (MetaSERS). Our MetaSERS-based DNA logic is simple to operate, highly reproducible, and can be stimulated by ultra-low concentration of the external inputs, enabling an extremely sensitive detection of mercury ions down to 2×10-4 ppb, which is four orders of magnitude lower than the exposure limit allowed by United States Environmental Protection Agency

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The aim of this work was to study the possible deactivation effects of biogas trace ammonia concentrations on methanation catalysts. It was found that small amounts of ammonia led to a slight decrease in the catalyst activity. A decrease in the catalyst deactivation by carbon formation was also observed, with ammonia absorbed on the active catalyst sites. This was via a suppression of the carbon formation and deposition on the catalyst, since it requires a higher number of active sites than for the methanation of carbon oxides. From the paper findings, no special pretreatment for ammonia removal from the biogas fed to a methanation process is required.

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The research presented, investigates the optimal set of operational codes (opcodes) that create a robust indicator of malicious software (malware) and also determines a program’s execution duration for accurate classification of benign and malicious software. The features extracted from the dataset are opcode density histograms, extracted during the program execution. The classifier used is a support vector machine and is configured to select those features to produce the optimal classification of malware over different program run lengths. The findings demonstrate that malware can be detected using dynamic analysis with relatively few opcodes.