Ethnic differences in proximal and distal tubular sodium reabsorption are heritable in black and white populations.

BACKGROUND: Segmental handling of sodium along the proximal and distal nephron might be heritable and different between black and white participants. METHODS: We randomly recruited 95 nuclear families of black South African ancestry and 103 nuclear families of white Belgian ancestry. We measured the (FENa) and estimated the fractional renal sodium reabsorption in the proximal (RNaprox) and distal (RNadist) tubules from the clearances of endogenous lithium and creatinine. In multivariable analyses, we studied the relation of RNaprox and RNadist with FENa and estimated the heritability (h) of RNaprox and RNadist. RESULTS: Independent of urinary sodium excretion, South Africans (n = 240) had higher RNaprox (unadjusted median, 93.9% vs. 81.0%; P < 0.001) than Belgians (n = 737), but lower RNadist (91.2% vs. 95.1%; P < 0.001). The slope of RNaprox on FENa was steeper in Belgians than in South Africans (-5.40 +/- 0.58 vs. -0.78 +/- 0.58 units; P < 0.001), whereas the opposite was true for the slope of RNadist on FENa (-3.84 +/- 0.19 vs. -13.71 +/- 1.30 units; P < 0.001). h of RNaprox and RNadist was high and significant (P < 0.001) in both countries. h was higher in South Africans than in Belgians for RNaprox (0.82 vs. 0.56; P < 0.001), but was similar for RNadist (0.68 vs. 0.50; P = 0.17). Of the filtered sodium load, black participants reabsorb more than white participants in the proximal nephron and less postproximally. CONCLUSION: Segmental sodium reabsorption along the nephron is highly heritable, but the capacity for regulation in the proximal and postproximal tubules differs between whites and blacks.

Modifications in the Si valence band after ion-beam-induced oxidation

The changes undergone by the Si surface after oxygen bombardment have special interest for acquiring a good understanding of the Si+-ion emission during secondary ion mass spectrometry (SIMS) analysis. For this reason a detailed investigation on the stoichiometry of the builtup surface oxides has been carried out using in situ x-ray photoemission spectroscopy (XPS). The XPS analysis of the Si 2p core level indicates a strong presence of suboxide chemical states when bombarding at angles of incidence larger than 30°. In this work a special emphasis on the analysis and interpretation of the valence band region was made. Since the surface stoichiometry or degree of oxidation varies with the angle of incidence, the respective valence band structures also differ. A comparison with experimentally measured and theoretically derived Si valence band and SiO2 valence band suggests that the new valence bands are formed by a combination of these two. This arises from the fact that Si¿Si bonds are present on the Si¿suboxide molecules, and therefore the corresponding 3p-3p Si-like subband, which extends towards the Si Fermi level, forms the top of the respective new valence bands. Small variations in intensity and energy position for this subband have drastic implications on the intensity of the Si+-ion emission during sputtering in SIMS measurements. A model combining chemically enhanced emission and resonant tunneling effects is suggested for the variations observed in ion emission during O+2 bombardment for Si targets.

Avoiding sensor blindness in Geiger mode avalanche photodiode arrays fabricated in a conventional CMOS process

The need to move forward in the knowledge of the subatomic world has stimulated the development of new particle colliders. However, the objectives of the next generation of colliders sets unprecedented challenges to the detector performance. The purpose of this contribution is to present a bidimensional array based on avalanche photodiodes operated in the Geiger mode to track high energy particles in future linear colliders. The bidimensional array can function in a gated mode to reduce the probability to detect noise counts interfering with real events. Low reverse overvoltages are used to lessen the dark count rate. Experimental results demonstrate that the prototype fabricated with a standard HV-CMOS process presents an increased efficiency and avoids sensor blindness by applying the proposed techniques.

A reusable smart interface for gas sensor resistance measurement

The advances of the semiconductor industry enable microelectromechanical systems sensors, signal conditioning logic and network access to be integrated into a smart sensor node. In this framework, a mixed-mode interface circuit for monolithically integrated gas sensor arrays was developed with high-level design techniques. This interface system includes analog electronics for inspection of up to four sensor arrays and digital logic for smart control and data communication. Although different design methodologies were used in the conception of the complete circuit, high-level synthesis tools and methodologies were crucial in speeding up the whole design cycle, enhancing reusability for future applications and producing a flexible and robust component.

On-line event detection by recursive dynamic principal component analysis and gas sensor arrays under drift conditions

Leakage detection is an important issue in many chemical sensing applications. Leakage detection hy thresholds suffers from important drawbacks when sensors have serious drifts or they are affected by cross-sensitivities. Here we present an adaptive method based in a Dynamic Principal Component Analysis that models the relationships between the sensors in the may. In normal conditions a certain variance distribution characterizes sensor signals. However, in the presence of a new source of variance the PCA decomposition changes drastically. In order to prevent the influence of sensor drifts the model is adaptive and it is calculated in a recursive manner with minimum computational effort. The behavior of this technique is studied with synthetic signals and with real signals arising by oil vapor leakages in an air compressor. Results clearly demonstrate the efficiency of the proposed method.

Configurational statistical model for the damaged structure of silicon oxide after ion implantation

A configurational model for silicon oxide damaged after a high-dose ion implantation of a nonreactive species is presented. Based on statistics of silicon-centered tetrahedra, the model takes into account not only the closest environment of a given silicon atom, but also the second neighborhood, so it is specified whether the oxygen attached to one given silicon is bridging two tetrahedra or not. The frequencies and intensities of infrared vibrational bands have been calculated by averaging over the distributions and these results are in agreement with the ones obtained from infrared experimental spectra. Likewise, the chemical shifts obtained from x-ray photoelectron spectroscopy (XPS) analysis are similar to the reported values for the charge-transfer model of SiOx compounds.

A current-mode interface circuit for a piezoresistive pressure sensor

An interfacing circuit for piezoresistive pressure sensors based on CMOS current conveyors is presented. The main advantages of the proposed interfacing circuit include the use of a single piezoresistor, the capability of offset compensation, and a versatile current-mode configuration, with current output and current or voltage input. Experimental tests confirm linear relation of output voltage versus piezoresistance variation.

The unfolded protein response: integrating stress signals through the stress sensor IRE1α.

Stress induced by accumulation of unfolded proteins at the endoplasmic reticulum (ER) is a classic feature of secretory cells and is observed in many tissues in human diseases including cancer, diabetes, obesity, and neurodegeneration. Cellular adaptation to ER stress is achieved by the activation of the unfolded protein response (UPR), an integrated signal transduction pathway that transmits information about the protein folding status at the ER to the nucleus and cytosol to restore ER homeostasis. Inositol-requiring transmembrane kinase/endonuclease-1 (IRE1α), the most conserved UPR stress sensor, functions as an endoribonuclease that processes the mRNA of the transcription factor X-box binding protein-1 (XBP1). IRE1α signaling is a highly regulated process, controlled by the formation of a dynamic scaffold onto which many regulatory components assemble, here referred to as the UPRosome. Here we provide an overview of the signaling and regulatory mechanisms underlying IRE1α function and discuss the emerging role of the UPR in adaptation to protein folding stress in specialized secretory cells and in pathological conditions associated with alterations in ER homeostasis.

Gas identification with tin oxide sensor array and self-organizing maps: adaptive correction of sensor drifts

Low-cost tin oxide gas sensors are inherently nonspecific. In addition, they have several undesirable characteristics such as slow response, nonlinearities, and long-term drifts. This paper shows that the combination of a gas-sensor array together with self-organizing maps (SOM's) permit success in gas classification problems. The system is able to determine the gas present in an atmosphere with error rates lower than 3%. Correction of the sensor's drift with an adaptive SOM has also been investigated

Drift compensation of gas sensor array data by Orthogonal Signal Correction

Drift is an important issue that impairs the reliability of gas sensing systems. Sensor aging, memory effects and environmental disturbances produce shifts in sensor responses that make initial statistical models for gas or odor recognition useless after a relatively short period (typically few weeks). Frequent recalibrations are needed to preserve system accuracy. However, when recalibrations involve numerous samples they become expensive and laborious. An interesting and lower cost alternative is drift counteraction by signal processing techniques. Orthogonal Signal Correction (OSC) is proposed for drift compensation in chemical sensor arrays. The performance of OSC is also compared with Component Correction (CC). A simple classification algorithm has been employed for assessing the performance of the algorithms on a dataset composed by measurements of three analytes using an array of seventeen conductive polymer gas sensors over a ten month period.

Nonlinear inverse dynamic models of gas sensing systems based on chemical sensor arrays for quantitative measurements

Gas sensing systems based on low-cost chemical sensor arrays are gaining interest for the analysis of multicomponent gas mixtures. These sensors show different problems, e.g., nonlinearities and slow time-response, which can be partially solved by digital signal processing. Our approach is based on building a nonlinear inverse dynamic system. Results for different identification techniques, including artificial neural networks and Wiener series, are compared in terms of measurement accuracy.

Drift compensation of gas sensor array data by common principal component analysis

A new drift compensation method based on Common Principal Component Analysis (CPCA) is proposed. The drift variance in data is found as the principal components computed by CPCA. This method finds components that are common for all gasses in feature space. The method is compared in classification task with respect to the other approaches published where the drift direction is estimated through a Principal Component Analysis (PCA) of a reference gas. The proposed new method ¿ employing no specific reference gas, but information from all gases ¿has shown the same performance as the traditional approach with the best-fitted reference gas. Results are shown with data lasting 7-months including three gases at different concentrations for an array of 17 polymeric sensors.