Bioluminescence and ice-nucleation microbial biosensors for l-arabinose content analysis in arabinoxylans

Microbial biosensors are analytical devices converting a biochemical signal into a quantifiable response. Due to their molecular properties, they can be diversely designed in order to fulfill the needs of different fields, from food industry to environmental sciences. One of the possible applications of microbial biosensors concerns arabinoxylans, components of dietary fibers having potential as functional food ingredients, which are also used for biogas production. The aim of this study was to develop reporter strains capable to evaluate the content of l-arabinose monosaccharides in arabinoxylans. The bioluminescent strain DPDaraBAD contains a plasmid in which luxCDABE genes of Photorhabdus luminescens are inserted under the control of Escherichia coli arabinose operon promoter. The ice-nucleation-active strain NIaraBAD bears a similar fusion using the same promoter upstream of the inaZ gene of Pseudomonas syringae. Sufficient response of biosensor cells was obtained after NIaraBAD incubation at 29 °C for 3 h and DPDaraBAD for 6 h, followed by 30-min incubation with l-arabinose. Both reporter strains responded specifically and quantitatively in the presence of the inducer with a detection limit of 0.009 and 0.015 g l^?1, respectively. Validation of reporter strains was performed in comparison with the l-arabinose concentration values obtained by high-performance anion-exchange chromatography (HPAEC) and demonstrated mean divergence of 9.59 % for bioluminescent strain and 15.86 % for ice-nucleation strain, which for microbial sensors is an acceptable dissimilarity. These l-arabinose microbial biosensors can be used as an alternative tool to chromatographic methods in monosaccharide content analysis of arabinoxylans.     

Ocean wave extraction from RADARSAT synthetic aperture radarinter-look image cross-spectra

This study is concerned with the extraction of directional ocean wave spectra from synthetic aperture radar (SAR) image spectra. The statistical estimation problem underlying the wave-SAR inverse problem is examined in detail in order to properly quantify the wave information content of SAR. As a concrete focus, a data set is considered comprising six RADARSAT SAR images co-located with a directional wave buoy off the east coast of Canada. These SAR data are transformed into inter-look image cross-spectra based on two looks at the same ocean scene separated by 0.4 s. The general problem of wave extraction from SAR is cast in terms of a statistical estimation problem that includes the observed SAR spectra, the wave-SAR transform, and prior spectral wave information. The central role of the weighting functions (inverse of the error covariances) is demonstrated, as well as the consequence of approximate (based on the quasilinear wave-SAR transform) versus exact linearizations on the convergence properties of the algorithm. Error estimates are derived and discussed. This statistical framework is applied to the extraction of spectral wave information from observed RADARSAT SAR image cross-spectra. A modified wave-SAR transform is used to account for case-specific geophysical and imaging effects. Analysis of the residual error of simulated and observed SAR spectra motivates a canonical form for the SAR observation error covariance. Wave estimates are then extracted from the SAR spectra, including wavenumber dependent error estimates and explicit identification of spectral null spaces where the SAR contains no wave information. Band-limited SAR wave information is also combined with prior (buoy) spectral wave estimates through parameterization of the wave spectral shape and use of regularization     

A two-element antenna for suppression in multipath environments

The design of a two-element antenna for portable transceivers is considered. The antenna consists of a dipole terminated with a parallel loop-capacitor combination. The antenna has a single feed at a point on the loop opposite the junction and does not require external combining circuitry. The capacitor creates a phase shift between the dipole and loop currents, thereby greatly reducing the probability of deep s in the received signal when the antenna is deployed in free-space or in the vicinity of a fixed reflector, where standing wave patterns occur. Theoretical and simulation studies based on multiple incident/reflected plane wave fields typical of multipath environments are used to quantify the reduction in probability. Simulation results are presented for three antenna types: a dipole antenna, a loop-dipole antenna without a capacitor, and the loop-dipole antenna with capacitor. The results are verified by field measurements on an automated outdoor test range, where the incidence angle and distance from the reflector are varied. With a single incident plane wave, the loop-dipole-capacitor (LDC) design reduces the probability of deep s in the received signal by up to two orders of magnitude at low signal-to-noise ratios (SNRs) when compared with the standard dipole antenna and the loop-dipole antenna without the capacitor. The performance advantage of the new design decreases as the number of incident waves increases; however, it performs at least as well as the dipole antenna in all cases studied.     

A probabilistic approach for the construction of regional earthquake response spectra

Five scenario earthquakes plausible for the Los Angeles metropolitan region, and one numerical approximation of the 1994 Northridge M_w 6.7 event, provide the database of the proposed methodology that is applied for the construction of regional earthquake response spectra. The methodology involves two main stages of data compaction. In the first stage, the Karhunen–Loève (K–L) decomposition of the excitation temporal covariance matrix is performed. In the second stage, the dominant eigenvectors are analytically approximated with Chebyshev polynomials, thus being converted from eigenvectors to eigenfunctions. This compact analytical representation of the nonstationary excitation data provides an exact closed-form solution for the nonstationary response of linear multi-degree-of-freedom systems. Furthermore, statistical inference analysis for the response variables is conducted, which leads to the construction of regional probabilistic response spectra based on the Log-Normal probability model for the response variables.     

Quantifying inequality in health in the absence of a natural reference group

When quantifying inequality in health, the excess fraction (i.e. the proportional reduction in the outcome in question that would occur if all groups had the same, lowest, risk rate) is an appealing measure. If the population contains a natural, healthiest reference group, the excess fraction is straightforward to estimate. In the absence of an a priori reference group, calculating the excess fraction requires reflection, since using the group with the lowest observed risk rate as reference can lead to erroneous conclusions. This paper proposes a simple simulation procedure for calculating the excess fraction, without fixing a reference group.     

Oligodendrogliomas. Part II: A new grading system based on morphological and imaging criteria

Myocardial perfusion scintigraphy is a noninvasive diagnostic method for the evaluation of patients with suspected or proven coronary artery disease (CAD). We utilized case-based reasoning (CBR) methods to develop the computer-based image interpretation system SCINA which automatically derives from a scintigraphic image data set an assessment concerning the presence of CAD. We compiled a case library of 100 patients who underwent both perfusion scintigraphy and coronary angiography to document or exclude the presence of CAD. The angiographic diagnosis of the retrieved nearest neighbor match of a scintigraphic input case was selected as the CBR diagnosis. We examined the effects of input data granularity, case indexing, similarity metric, and adaptation on the diagnostic accuracy of the CBR application SCINA. For the final prototype, sensitivity and specificity for detection of coronary heart disease were 98% and 70% suggesting that CBR systems may achieve a diagnostic accuracy that appears feasible for clinical use.     

Sea-air flux of CO2 in the Caribbean Sea estimated using in situ and remote sensing data

Empirical relationships between sea surface carbon dioxide fugacity (fCO₂^sw) and sea surface temperature (SST) were applied to datasets of remotely sensed SST to create fCO₂^sw fields in the Caribbean Sea. SST datasets from different sensors were used, as well as the SST fields created by optimum interpolation of bias corrected AVHRR data. Empirical relationships were derived using shipboard fCO₂^sw data, in situ SST data, and SST data from the remote sensing platforms. The results show that the application of a relationship based on shipboard SST data, on fields of remotely sensed SST yields biased fCO₂^sw values. This bias is reduced if the fCO₂^sw-SST relationships are derived using the same SST data that are used to create the SST fields. The fCO₂^sw fields found to best reproduce observed fCO₂^sw are used in combination with wind speed data from QuikSCAT to create weekly maps of the sea-air CO₂ flux in the Caribbean Sea in 2002. The region to the SW of Cuba was a source of CO₂ to the atmosphere throughout 2002, and the region to the NE was a sink during winter and spring and a source during summer and fall. The net uptake of CO₂ in the region was doubled when potential skin layer effects on fCO₂^sw were taken into account.     

Initial scalar lithospheric magnetic anomaly map of China and surrounding regions derived from CSES satellite data

Science China Technological Sciences - The China Seismo-Electromagnetic Satellite (CSES), China’s first satellite to measure geophysical fields with scientific goals in both space and solid...     

Shot-noise limited,supercontinuum-based optical coherence tomography

We present the first demonstration of shot-noise limited supercontinuum-based spectral domain optical coherence tomography (SD-OCT) with an axial resolution of ...     

Pancreatic Islets Accumulate Cadmium in a Rodent Model of Cadmium-Induced Hyperglycemia

Cadmium (Cd) is an anthropogenic as well as a naturally occurring toxicant associated with prediabetes and T2DM in humans and experimental models of Cd exposure. However, relatively few studies have examined the mechanism(s) of Cd-induced hyperglycemia. The purpose of this study was to examine the role of pancreatic islets in Cd-induced hyperglycemia. Male Sprague–Dawley rats were given daily subcutaneous doses of Cd at 0.6 mg/kg over 12 weeks. There was a resulting time-dependent increase in fasting blood glucose and altered insulin release in vitro. Islets isolated from control (saline-treated) and Cd-treated animals were incubated in low (0.5 mg/mL) or high (3 mg/mL) glucose conditions. Islets from 12 week Cd-treated animals had significantly less glucose-stimulated insulin release compared to islets from saline-treated control animals. The actual Cd content of isolated islets was 5 fold higher than the whole pancreas (endocrine + exocrine) and roughly 70% of that present in the renal cortex. Interestingly, islets isolated from Cd-treated animals and incubated in high glucose conditions contained significantly less Cd and zinc than those incubated in low glucose. These results show that within whole pancreatic tissue, Cd selectively accumulates in pancreatic islets and causes altered islet function that likely contributes to dysglycemia.