948 resultados para Impedance biosensor


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Determination of fat-free mass (FFM) and fat mass (FM) is of considerable interest in the evaluation of nutritional status. In recent years, bioelectrical impedance analysis (BIA) has emerged as a simple, reproducible method used for the evaluation of FFM and FM, but the lack of reference values reduces its utility to evaluate nutritional status. The aim of this study was to determine reference values for FFM, FM, and %FM by BIA in a white population of healthy subjects, to observe the changes in these values with age, and to develop percentile distributions for these parameters. Whole-body resistance of 1838 healthy white men and 1555 women, aged 15-64 y, was determined by using four skin electrodes on the right hand and foot. FFM and FM were calculated according to formulas validated for the subject groups and analyzed for age decades. This is the first study to present BIA-determined age- and sex-specific percentiles for FFM, FM, and %FM for healthy subjects, aged 15-64 y. Mean FM and %FM increased progressively in men and after age 45 y in women. The results suggest that any weight gain noted with age is due to a gain in FM. In conclusion, the data presented as percentiles can serve as reference to evaluate the normality of body composition of healthy and ill subject groups at a given age.

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Activated forms of jasmonic acid (JA) are central signals coordinating plant responses to stresses, yet tools to analyse their spatial and temporal distribution are lacking. Here we describe a JA perception biosensor termed Jas9-VENUS that allows the quantification of dynamic changes in JA distribution in response to stress with high spatiotemporal sensitivity. We show that Jas9-VENUS abundance is dependent on bioactive JA isoforms, the COI1 co-receptor, a functional Jas motif and proteasome activity. We demonstrate the utility of Jas9-VENUS to analyse responses to JA in planta at a cellular scale, both quantitatively and dynamically. This included using Jas9-VENUS to determine the cotyledon-to-root JA signal velocities on wounding, revealing two distinct phases of JA activity in the root. Our results demonstrate the value of developing quantitative sensors such as Jas9-VENUS to provide high-resolution spatiotemporal data about hormone distribution in response to plant abiotic and biotic stresses.

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Nutrition assessment is important during chronic respiratory insufficiency to evaluate the level of malnutrition or obesity and should include body composition measurements. The appreciation of fat-free and fat reserves in patients with chronic respiratory insufficiency can aid in designing an adapted nutritional support, e.g., nutritional support in malnutrition and food restriction in obesity. The purpose of the present study was to cross-validate fat-free and fat mass obtained by various bioelectric impedance (BIA) formulas with the fat-free and fat mass measured by dual-energy X-ray absorptiometry (DXA) and determine the formulas that are best suited to predict the fat-free and fat mass for a group of patients with severe chronic respiratory insufficiency. Seventy-five patients (15 women and 60 men) with chronic obstructive and restrictive respiratory insufficiency aged 45-86 y were included in this study. Body composition was calculated according to 13 different BIA formulas for women and 12 for men and compared with DXA. Because of the variability, calculated as 2 standard deviations, of +/- 5.0 kg fat-free mass for women and +/- 6.4 kg for men for the best predictive formula, the use of the various existing BIA formulas was considered not clinically relevant. Therefore disease-specific formulas for patients with chronic respiratory insufficiency should be developed to improve the prediction of fat-free and fat mass by BIA in these patients.

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Electrical Impedance Tomography (EIT) is an imaging method which enables a volume conductivity map of a subject to be produced from multiple impedance measurements. It has the potential to become a portable non-invasive imaging technique of particular use in imaging brain function. Accurate numerical forward models may be used to improve image reconstruction but, until now, have employed an assumption of isotropic tissue conductivity. This may be expected to introduce inaccuracy, as body tissues, especially those such as white matter and the skull in head imaging, are highly anisotropic. The purpose of this study was, for the first time, to develop a method for incorporating anisotropy in a forward numerical model for EIT of the head and assess the resulting improvement in image quality in the case of linear reconstruction of one example of the human head. A realistic Finite Element Model (FEM) of an adult human head with segments for the scalp, skull, CSF, and brain was produced from a structural MRI. Anisotropy of the brain was estimated from a diffusion tensor-MRI of the same subject and anisotropy of the skull was approximated from the structural information. A method for incorporation of anisotropy in the forward model and its use in image reconstruction was produced. The improvement in reconstructed image quality was assessed in computer simulation by producing forward data, and then linear reconstruction using a sensitivity matrix approach. The mean boundary data difference between anisotropic and isotropic forward models for a reference conductivity was 50%. Use of the correct anisotropic FEM in image reconstruction, as opposed to an isotropic one, corrected an error of 24 mm in imaging a 10% conductivity decrease located in the hippocampus, improved localisation for conductivity changes deep in the brain and due to epilepsy by 4-17 mm, and, overall, led to a substantial improvement on image quality. This suggests that incorporation of anisotropy in numerical models used for image reconstruction is likely to improve EIT image quality.

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We present a viscometric affinity biosensor that can potentially allow continuous multi-analyte monitoring in biological fluids like blood or plasma. The sensing principle is based on the detection of viscosity changes of a polymeric solution which has a selective affinity for the analyte of interest. The chemico-mechanical sensor incorporates an actuating piezoelectric diaphragm, a sensing piezoelectric diaphragm and a flow-resisting microchannel for viscosity detection. A free-standing Anodic Alumina Oxide (AAO) porous nano-membrane is used as selective interface. A glucose-sensitive sensor was fabricated and extensively assessed in buffer solution. The sensor reversibility, stability and sensitivity were excellent during at least 65 hours. Results showed also a good degree of stability for a long term measurement (25 days). The sensor behaviour was furthermore tested in fetal bovine serum (FBS). The obtained results for glucose sensing are very promising, indicating that the developed sensor is a candidate for continuous monitoring in biological fluids. Sensitive solutions for ionized calcium and pH are currently under development and should allow multi-analyte sensing in the near future.

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Combining bacterial bioreporters with microfluidics systems holds great promise for in-field detection of chemical or toxicity targets. Recently we showed how Escherichia coli cells engineered to produce a variant of green fluorescent protein after contact to arsenite and arsenate can be encapsulated in agarose beads and incorporated into a microfluidic chip to create a device for in-field detection of arsenic, a contaminant of well known toxicity and carcinogenicity in potable water both in industrialized and developing countries. Cell-beads stored in the microfluidics chip at -20°C retained inducibility up to one month and we were able to reproducibly discriminate concentrations of 10 and 50 μg arsenite per L (the drinking water standards for European countries and the United States, and for the developing countries, respectively) from the blank in less than 200 minutes. We discuss here the reasons for decreasing bioreporter signal development upon increased storage of cell beads but also show how this decrease can be reduced, leading to a faster detection and a longer lifetime of the device.

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Electrical impedance tomography (EIT) is a non-invasive imaging technique that can measure cardiac-related intra-thoracic impedance changes. EIT-based cardiac output estimation relies on the assumption that the amplitude of the impedance change in the ventricular region is representative of stroke volume (SV). However, other factors such as heart motion can significantly affect this ventricular impedance change. In the present case study, a magnetic resonance imaging-based dynamic bio-impedance model fitting the morphology of a single male subject was built. Simulations were performed to evaluate the contribution of heart motion and its influence on EIT-based SV estimation. Myocardial deformation was found to be the main contributor to the ventricular impedance change (56%). However, motion-induced impedance changes showed a strong correlation (r = 0.978) with left ventricular volume. We explained this by the quasi-incompressibility of blood and myocardium. As a result, EIT achieved excellent accuracy in estimating a wide range of simulated SV values (error distribution of 0.57 ± 2.19 ml (1.02 ± 2.62%) and correlation of r = 0.996 after a two-point calibration was applied to convert impedance values to millilitres). As the model was based on one single subject, the strong correlation found between motion-induced changes and ventricular volume remains to be verified in larger datasets.

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Living bacteria or yeast cells are frequently used as bioreporters for the detection of specific chemical analytes or conditions of sample toxicity. In particular, bacteria or yeast equipped with synthetic gene circuitry that allows the production of a reliable non-cognate signal (e.g., fluorescent protein or bioluminescence) in response to a defined target make robust and flexible analytical platforms. We report here how bacterial cells expressing a fluorescence reporter ("bactosensors"), which are mostly used for batch sample analysis, can be deployed for automated semi-continuous target analysis in a single concise biochip. Escherichia coli-based bactosensor cells were continuously grown in a 13 or 50 nanoliter-volume reactor on a two-layered polydimethylsiloxane-on-glass microfluidic chip. Physiologically active cells were directed from the nl-reactor to a dedicated sample exposure area, where they were concentrated and reacted in 40 minutes with the target chemical by localized emission of the fluorescent reporter signal. We demonstrate the functioning of the bactosensor-chip by the automated detection of 50 μgarsenite-As l(-1) in water on consecutive days and after a one-week constant operation. Best induction of the bactosensors of 6-9-fold to 50 μg l(-1) was found at an apparent dilution rate of 0.12 h(-1) in the 50 nl microreactor. The bactosensor chip principle could be widely applicable to construct automated monitoring devices for a variety of targets in different environments.

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We present an analytical procedure to perform the local noise analysis of a semiconductor junction when both the drift and diffusive parts of the current are important. The method takes into account space-inhomogeneous and hot-carriers conditions in the framework of the drift-diffusion model, and it can be effectively applied to the local noise analysis of different devices: n+nn+ diodes, Schottky barrier diodes, field-effect transistors, etc., operating under strongly inhomogeneous distributions of the electric field and charge concentration

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We present an analytical procedure to perform the local noise analysis of a semiconductor junction when both the drift and diffusive parts of the current are important. The method takes into account space-inhomogeneous and hot-carriers conditions in the framework of the drift-diffusion model, and it can be effectively applied to the local noise analysis of different devices: n+nn+ diodes, Schottky barrier diodes, field-effect transistors, etc., operating under strongly inhomogeneous distributions of the electric field and charge concentration

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A theoretical model for the noise properties of n+nn+ diodes in the drift-diffusion framework is presented. In contrast with previous approaches, our model incorporates both the drift and diffusive parts of the current under inhomogeneous and hot-carrier conditions. Closed analytical expressions describing the transport and noise characteristics of submicrometer n+nn+ diodes, in which the diode base (n part) and the contacts (n+ parts) are coupled in a self-consistent way, are obtained

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The present paper reports a bacteria autonomous controlled concentrator prototype with a user-friendly interface for bench-top applications. It is based on a micro-fluidic lab-on-a-chip and its associated custom instrumentation, which consists in a dielectrophoretic actuator, to pre-concentrate the sample, and an impedance analyser, to measure concentrated bacteria levels. The system is composed by a single micro-fluidic chamber with interdigitated electrodes and a instrumentation with custom electronics. The prototype is supported by a real-time platform connected to a remote computer, which automatically controls the system and displays impedance data used to monitor the status of bacteria accumulation on-chip. The system automates the whole concentrating operation. Performance has been studied for controlled volumes of Escherichia coli (E. coli) samples injected into the micro-fluidic chip at constant flow rate of 10 μL/min. A media conductivity correcting protocol has been developed, as the preliminary results showed distortion of the impedance analyser measurement produced by bacterial media conductivity variations through time. With the correcting protocol, the measured impedance values were related to the quantity of bacteria concentrated with a correlation of 0.988 and a coefficient of variation of 3.1%. Feasibility of E. coli on-chip automated concentration, using the miniaturized system, has been demonstrated. Furthermore, the impedance monitoring protocol had been adjusted and optimized, to handle changes in the electrical properties of the bacteria media over time.

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A L-ascorbic acid biosensor based on ascorbate oxidase has been developed. The enzyme was extracted from the mesocarp of cucumber (Cucumis sativus) by using 0.05 mol L-1 phosphate buffer, pH 5.8 containing 0.5 mol L-1 NaCl. After the dialysis versus phosphate buffer 0.05 mol L-1 pH 5.8, the enzyme was immobilized onto nylon net through glutaraldehyde covalent bond. The membrane was coupled to an O2 electrode and the yielding reaction monitored by oxygen depletion at -600 mV using flow injection analysis optimized to 0.1 mol L-1 phosphate buffer pH 5.8, as the carrier solution and flow-rate of 0.5 mL min-1. The ascorbic acid calibration curve was linear from 1.2x10-4 to 1.0x10-3 mol L-1. The evaluation of biosensor lifetime leads to 500 injections. Commercial pharmaceutical samples were analyzed with the proposed method and the results were compared with those obtained by high-performance liquid chromatography (HPLC).

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The assessment of fluid volume in neonates by a noninvasive, inexpensive, and fast method can contribute significantly to increase the quality of neonatal care. The objective of the present study was to calibrate an acquisition system and software to estimate the bioelectrical impedance parameters obtained by a method of bioelectrical impedance spectroscopy based on step response and to develop specific equations for the neonatal population to determine body fluid compartments. Bioelectric impedance measurements were performed by a laboratory homemade instrument. The volumes were estimated in a clinical study on 30 full-term neonates at four different times during the first month of life. During the first 24 hours of life the total body water, extracellular water and intracellular water were 2.09 ± 0.25, 1.20 ± 0.19, and 0.90 ± 0.25 liters, respectively. By the 48th hour they were 1.87 ± 0.27, 1.08 ± 0.17, and 0.79 ± 0.21 liters, respectively. On the 10th day they were 2.02 ± 0.25, 1.29 ± 0.21, and 0.72 ± 0.14 liters, respectively, and after 1 month they were 2.34 ± 0.27, 1.62 ± 0.20, and 0.72 ± 0.13 liters, respectively. The behavior of the estimated volume was correlated with neonatal body weight changes, leading to a better interpretation of such changes. In conclusion, this study indicates the feasibility of bioelectrical impedance spectroscopy as a method to help fluid administration in intensive care neonatal units, and also contribute to the development of new equations to estimate neonatal body fluid contents.

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The objectives of the present study were to describe and compare the body composition variables determined by bioelectrical impedance (BIA) and the deuterium dilution method (DDM), to identify possible correlations and agreement between the two methods, and to construct a linear regression model including anthropometric measures. Obese adolescents were evaluated by anthropometric measures, and body composition was assessed by BIA and DDM. Forty obese adolescents were included in the study. Comparison of the mean values for the following variables: fat body mass (FM; kg), fat-free mass (FFM; kg), and total body water (TBW; %) determined by DDM and by BIA revealed significant differences. BIA overestimated FFM and TBW and underestimated FM. When compared with data provided by DDM, the BIA data presented a significant correlation with FFM (r = 0.89; P < 0.001), FM (r = 0.93; P < 0.001) and TBW (r = 0.62; P < 0.001). The Bland-Altman plot showed no agreement for FFM, FM or TBW between data provided by BIA and DDM. The linear regression models proposed in our study with respect to FFM, FM, and TBW were well adjusted. FFM obtained by DDM = 0.842 x FFM obtained by BIA. FM obtained by DDM = 0.855 x FM obtained by BIA + 0.152 x weight (kg). TBW obtained by DDM = 0.813 x TBW obtained by BIA. The body composition results of obese adolescents determined by DDM can be predicted by using the measures provided by BIA through a regression equation.