Signal enhancement of surface plasmon resonance immunoassay using enzyme precipitation-functionalized gold nanoparticles: A femto molar level measurement of anti-glutamic acid decarboxylase antibody

Colloidal gold nanoparticles (AuNPs) and precipitation of an insoluble product formed by HRP-biocatalyzed oxidation of 3,3'-diaminobenzidine (DAB) in the presence of H2O2 were used to enhance the signal obtained from the surface plasmon resonance (SPR) biosensor. The AuNPs were synthesized and functionalized with HS-OEG(3)-COOH by self assembling technique. Thereafter, the HS-OEG3-COOH functionalized nanoparticles were covalently conjugated with horseradish peroxidase (HRP) and anti IgG antibody to form an enzyme-immunogold complex. Characterizations were performed by several methods: UV-vis absorption, DLS, HR-TEM and Fr-IR. The Au-anti IgG-HRP complex has been applied in enhancement of SPR immunoassay using a sensor chip constructed by 1:9 molar ratio of HS-OEG(6)-COOH and HS-OEG(3)-OH for detection of anti-GAD antibody. As a result, AuNPs showed their enhancement as being consistent with other previous studies while the enzyme precipitation using DAB substrate was applied for the first time and greatly amplified the SPR detection. The limit of detection was found as low as 0.03 ng/ml of anti-GAD antibody (or 200 fM) which is much higher than that of previous reports. This study indicates another way to enhance SPR measurement, and it is generally applicable to other SPR-based immunoassays.

Effects of Gold Nanoparticle and Enzyme Precipitation on Enhancement of Surface Plasmon Resonance Immunoassay: A Super Sensitive Measurement of Anti- Glutamic Acid Decarboxylase Antibody

Introduction: In this study, colloidal gold nanoparticle and precipitation of an insoluble product formed by HRP-biocatalyzed oxidation of 3,3'-diaminobenzidine (DAB) in the presence of H2O2 were used to enhance the signal obtained from the surface plasmon resonance biosensor.

Methods: The colloidal gold nanoparticle was synthesized as described by Turkevitch et al., and their surface was firstly functionalized with HS(CH2)11(OCH2CH2)3COOH (OEG3¬-COOH) by self assembling technique. Thereafter, those OEG3-COOH functionalized nanoparticles were covalently conjugated with horseradish peroxidase (HRP) and anti-IgG antibody (specific to the Fc portion of all human IgG subclasses) to form an enzyme-immunogold complex. Characterization was performed by several methods: UV-Vis absorption, dynamic light scattering (DLS), transmission electron microscopy (TEM) and FTIR. The as-prepared enzyme-immunogold complex has been applied in enhancement of SPR immunoassay. A sensor chip used in the experiment was constructed by using 1:10 molar ratio of HS(CH2)11(OCH2CH2)6COOH and HS(CH2)11(OCH2CH2)3OH. The capture protein, GAD65 (autoantigen) which is recognized by anti-GAD antibody (autoantibody) in the sera of insulin-dependent diabetes mellitus patients, was immobilized onto the 1:10 surface via biotin-streptavidin interaction.

Results and conclusions: In the research, we reported the influences of gold nanoparticle and enzyme precipitation on the enhancement of SPR signal. Gold nanoparticle showed its enhancement as being consistent with other previous studies, while the enzyme precipitation using DAB substrate was applied for the first time and greatly amplified the SPR detection. As the results, anti-GAD antibody could be detected at pg/ml level which is far higher than that of commercial ELISA detection kit. This study indicates another way to enhance SPR measurement, and it is generally applicable to other SPR-based immunoassays.

Landfill cap models under simulated climate change precipitation::Impacts of cracks and root growth

Desiccation crack formation is a key process that needs to be understood in assessment of landfill cap performance under anticipated future climate change scenarios. The objectives of this study were to examine: (a) desiccation cracks and impacts that roots may have on their formation and resealing, and (b) their impacts on hydraulic conductivity under anticipated climate change precipitation scenarios. Visual observations, image analysis of thin sections and hydraulic conductivity tests were carried out on cores collected from two large-scale laboratory trial landfill cap models (∼80 × 80 × 90 cm) during a year of four simulated seasonal precipitation events. Extensive root growth in the topsoil increased percolation of water into the subsurface, and after droughts, roots grew deep into low-permeability layers through major cracks which impeded their resealing. At the end of 1 year, larger cracks had lost resealing ability and one single, large, vertical crack made the climate change precipitation model cap inefficient. Even though the normal precipitation model had developed desiccation cracks, its integrity was preserved better than the climate change precipitation model.

Validation of non‑stationary precipitation series for site‑specific impact assessment: comparison of two statistical downscaling techniques

Statistical downscaling (SD) methods have become a popular, low-cost and accessible means of bridging the gap between the coarse spatial resolution at which climate models output climate scenarios and the finer spatial scale at which impact modellers require these scenarios, with various different SD techniques used for a wide range of applications across the world. This paper compares the Generator for Point Climate Change (GPCC) model and the Statistical DownScaling Model (SDSM)—two contrasting SD methods—in terms of their ability to generate precipitation series under non-stationary conditions across ten contrasting global climates. The mean, maximum and a selection of distribution statistics as well as the cumulative frequencies of dry and wet spells for four different temporal resolutions were compared between the models and the observed series for a validation period. Results indicate that both methods can generate daily precipitation series that generally closely mirror observed series for a wide range of non-stationary climates. However, GPCC tends to overestimate higher precipitation amounts, whilst SDSM tends to underestimate these. This infers that GPCC is more likely to overestimate the effects of precipitation on a given impact sector, whilst SDSM is likely to underestimate the effects. GPCC performs better than SDSM in reproducing wet and dry day frequency, which is a key advantage for many impact sectors. Overall, the mixed performance of the two methods illustrates the importance of users performing a thorough validation in order to determine the influence of simulated precipitation on their chosen impact sector.

Building sandstone surface modification by biofilm and iron precipitation: emerging block-scale heterogeneity and system response

Stone surfaces are sensitive to their environment. This means that they will often respond to exposure conditions by manifesting a change in surface characteristics. Such changes can be more than simply aesthetic, creating surface/subsurface heterogeneity in stone at the block scale, promoting stress gradients to be set up as surface response to, for example, temperature fluctuations, can diverge from subsurface response. This paper reports preliminary experiments investigating the potential of biofilms and iron precipitation as surface-modifiers on stone, exploring the idea of block-scale surface-to-depth heterogeneity, and investigating how physical alteration in the surface and near-surface zone can have implications for subsurface response and potentially for long-term decay patterns. Salt weathering simulations on fresh and surface-modified stone suggest that even subtle surface modification can have significant implications for moisture uptake and retention, salt concentration and distribution from surface to depth, over the period of the experimental run. The accumulation of salt may increase the retention of moisture, by modifying vapour pressure differentials and the rate of evaporation.
Temperature fluctuation experiments suggest that the presence of a biofilm can have an impact on energy transfer processes that occur at the stone surface (for example, buffering against temperature fluctuation), affecting surface-to-depth stress gradients. Ultimately, fresh and surface-modified blocks mask different kinds of system, which respond to inputs differently because of different storage mechanisms, encouraging divergent behaviour between fresh and surface modified stone over time.

Assessment of NDVI, land surface temperature and precipitation anomalies for drought monitoring in Bayankhongor province, Mongolia

During the last decade Mongolia’s region was characterized by a rapid increase of both severity and frequency of drought events, leading to pasture reduction. Drought monitoring and assessment plays an important role in the region’s early warning systems as a way to mitigate the negative impacts in social, economic and environmental sectors. Nowadays it is possible to access information related to the hydrologic cycle through remote sensing, which provides a continuous monitoring of variables over very large areas where the weather stations are sparse. The present thesis aimed to explore the possibility of using NDVI as a potential drought indicator by studying anomaly patterns and correlations with other two climate variables, LST and precipitation. The study covered the growing season (March to September) of a fifteen year period, between 2000 and 2014, for Bayankhongor province in southwest Mongolia. The datasets used were MODIS NDVI, LST and TRMM Precipitation, which processing and analysis was supported by QGIS software and Python programming language. Monthly anomaly correlations between NDVI-LST and NDVI-Precipitation were generated as well as temporal correlations for the growing season for known drought years (2001, 2002 and 2009). The results show that the three variables follow a seasonal pattern expected for a northern hemisphere region, with occurrence of the rainy season in the summer months. The values of both NDVI and precipitation are remarkably low while LST values are high, which is explained by the region’s climate and ecosystems. The NDVI average, generally, reached higher values with high precipitation values and low LST values. The year of 2001 was the driest year of the time-series, while 2003 was the wet year with healthier vegetation. Monthly correlations registered weak results with low significance, with exception of NDVI-LST and NDVI-Precipitation correlations for June, July and August of 2002. The temporal correlations for the growing season also revealed weak results. The overall relationship between the variables anomalies showed weak correlation results with low significance, which suggests that an accurate answer for predicting drought using the relation between NDVI, LST and Precipitation cannot be given. Additional research should take place in order to achieve more conclusive results. However the NDVI anomaly images show that NDVI is a suitable drought index for Bayankhongor province.

Broad-scale adaptive genetic variation in alpine plants is driven by temperature and precipitation.

Identifying adaptive genetic variation is a challenging task, in particular in non-model species for which genomic information is still limited or absent. Here, we studied distribution patterns of amplified fragment length polymorphisms (AFLPs) in response to environmental variation, in 13 alpine plant species consistently sampled across the entire European Alps. Multiple linear regressions were performed between AFLP allele frequencies per site as dependent variables and two categories of independent variables, namely Moran's eigenvector map MEM variables (to account for spatial and unaccounted environmental variation, and historical demographic processes) and environmental variables. These associations allowed the identification of 153 loci of ecological relevance. Univariate regressions between allele frequency and each environmental factor further showed that loci of ecological relevance were mainly correlated with MEM variables. We found that precipitation and temperature were the best environmental predictors, whereas topographic factors were rarely involved in environmental associations. Climatic factors, subject to rapid variation as a result of the current global warming, are known to strongly influence the fate of alpine plants. Our study shows, for the first time for a large number of species, that the same environmental variables are drivers of plant adaptation at the scale of a whole biome, here the European Alps.

Atmospheric warming and the amplification of precipitation extremes

Climate models suggest that extreme precipitation events will become more common in an anthropogenically warmed climate. However, observational limitations have hindered a direct evaluation of model-projected changes in extreme precipitation. We used satellite observations and model simulations to examine the response of tropical precipitation events to naturally driven changes in surface temperature and atmospheric moisture content. These observations reveal a distinct link between rainfall extremes and temperature, with heavy rain events increasing during warm periods and decreasing during cold periods. Furthermore, the observed amplification of rainfall extremes is found to be larger than that predicted by models, implying that projections of future changes in rainfall extremes in response to anthropogenic global warming may be underestimated.

Temperature and moist-stability effects on midlatitude orographic precipitation

Idealized, convection-resolving simulations of moist orographic flows are conducted to investigate the influence of temperature and moist stability on the drying ratio (DR), defined as the fraction of the impinging water mass removed as orographic precipitation. In flow past a long ridge, where most of the air rises over the barrier rather than detouring around it, DR decreases as the surface temperature (Ts) increases, even as the orographic cap cloud becomes statically unstable at higher Ts and develops embedded convection. This behaviour is explained by a few physical principles: (1) the Clausius–Clapeyron equation dictates that the normalized condensation rate decreases as the flow gets warmer, (2) the replacement of ice-phase precipitation growth with warm-rain processes decreases the efficiency by which condensate is converted to precipitation, thereby lowering precipitation efficiency, and (3) embedded convection acts more to vertically redistribute moisture than to enhance precipitation. Over an isolated mountain, the effects of (1) and (2) are counteracted by moisture deflection around the barrier, which is stronger in the colder, more stable flows.