Transient temperature rise in a mouse due to low-frequency regional hyperthermia

A refined nonlinear heat transfer model of a mouse has been developed to simulate the transient temperature rise in a neoplastic tumour and neighbouring tissue during regional hyperthermia using a 150 kHz inductive coil. In this study, we incorporate various bio-energetic enhancements to the heat transfer equation and numerical validations based on experimental findings for the mouse, in terms of nonlinear metabolic heat production, homeothermy, blood perfusion parameters, thermoregulation, psychological and physiological effects. The discretized bio-heat transfer equation has been validated with the commercial software FEMLAB on a canonical multi-sphere object before applying the scheme to the inhomogeneous mouse voxel phantom. The time-dependent numerical results of regional hyperthermia of mouse thigh have been compared with the available experimental temperature results with only a few small disparities. During the first 20 min of local unfocused heating, the temperature in the tumour and the surrounding tissue increased by around 7.5 degrees C. The objective of this preliminary study was to develop a validated electrothermal numerical scheme for inductive hyperthermia of a small mammal with the intention of expanding the model into a complete numerical solution involving ferromagnetic nanoparticles for targeted heating of tumours at low frequencies. In addition, the numerical scheme herein could assist in optimizing and tailoring of focused electromagnetic fields for hyperthermia.

Electrical impedance tomography in extremely prematurely born infants and during high frequency oscillatory ventilation analyzed in the frequency domain

Functional electrical impedance tomography (EIT) measures relative impedance change that occurs in the chest during a distinct observation period and an EIT image describing regional relative impedance change is generated. Analysis of such an EIT image may be erroneous because it is based on an impedance signal that has several components. Most of the change in relative impedance in the chest is caused by air movement but other physiological events such as cardiac activity change in end expiratory level or pressure swings originating from a ventilator circuit can influence the impedance signal. We obtained EIT images and signals in spontaneously breathing healthy adults, in extremely prematurely born infants on continuous positive airway pressure and in ventilated sheep on conventional mechanical or high frequency oscillatory ventilation (HFOV). Data were analyzed in the frequency domain and results presented after band pass filtering within the frequency range of the physiological event of interest. Band pass filtering of EIT data is necessary in premature infants and on HFOV to differentiate and eliminate relative impedance changes caused by physiological events other than the one of interest.

Mean sea surface modelling from multi-satellite altimetry utilising frequency domain techniques

A technique is presented for the development of a high precision and resolution Mean Sea Surface (MSS) model. The model utilises Radar altimetric sea surface heights extracted from the geodetic phase of the ESA ERS-1 mission. The methodology uses a modified Le Traon et al. (1995) cubic-spline fit of dual ERS-1 and TOPEX/Poseidon crossovers for the minimisation of radial orbit error. The procedure then uses Fourier domain processing techniques for spectral optimal interpolation of the mean sea surface in order to reduce residual errors within the model. Additionally, a multi-satellite mean sea surface integration technique is investigated to supplement the first model with additional enhanced data from the GEOSAT geodetic mission.The methodology employs a novel technique that combines the Stokes' and Vening-Meinsz' transformations, again in the spectral domain. This allows the presentation of a new enhanced GEOSAT gravity anomaly field.

Sparse time-frequency data analysis : a multi-scale approach

In this work, we further extend the recently developed adaptive data analysis method, the Sparse Time-Frequency Representation (STFR) method. This method is based on the assumption that many physical signals inherently contain AM-FM representations. We propose a sparse optimization method to extract the AM-FM representations of such signals. We prove the convergence of the method for periodic signals under certain assumptions and provide practical algorithms specifically for the non-periodic STFR, which extends the method to tackle problems that former STFR methods could not handle, including stability to noise and non-periodic data analysis. This is a significant improvement since many adaptive and non-adaptive signal processing methods are not fully capable of handling non-periodic signals. Moreover, we propose a new STFR algorithm to study intrawave signals with strong frequency modulation and analyze the convergence of this new algorithm for periodic signals. Such signals have previously remained a bottleneck for all signal processing methods. Furthermore, we propose a modified version of STFR that facilitates the extraction of intrawaves that have overlaping frequency content. We show that the STFR methods can be applied to the realm of dynamical systems and cardiovascular signals. In particular, we present a simplified and modified version of the STFR algorithm that is potentially useful for the diagnosis of some cardiovascular diseases. We further explain some preliminary work on the nature of Intrinsic Mode Functions (IMFs) and how they can have different representations in different phase coordinates. This analysis shows that the uncertainty principle is fundamental to all oscillating signals.

The influence of adsorption phenomena on the impedance spectroscopy of an electrolytic cell

In this work we investigate the influence of the adsorption of ions on the impedance spectroscopy of an electrolytic cell. We consider that the positive and negative ions present in a dielectric liquid are adsorbed in the electrode surfaces with different adsorption energies. This difference in adsorption energies causes an additional plateaux in the limit of the low-frequency range of the real part of the impedance Z. In the same frequency range, a second minimum in the imaginary part of Z is predicted. The theory is illustrated with measurements of the impedance of an electrolytic solution in the frequency range from 10(-2) Hz to 1 KHz. A comparison between the present model and others from the literature to describe the experimental results is also made.

Complex kinetics, high frequency oscillations and temperature compensation in the electro-oxidation of ethylene glycol on platinum

Despite the fact that the majority of the catalytic electro-oxidation of small organic molecules presents oscillatory kinetics under certain conditions, there are few systematic studies concerning the influence of experimental parameters on the oscillatory dynamics. Of the studies available, most are devoted to C1 molecules and just some scattered data are available for C2 molecules. We present in this work a comprehensive study of the electro-oxidation of ethylene glycol on polycrystalline platinum surfaces and in alkaline media. The system was studied by means of electrochemical impedance spectroscopy, cyclic voltammetry, and chronoamperometry, and the impact of parameters such as applied current, ethylene glycol concentration, and temperature were investigated. As in the case of other parent systems, the instabilities in this system were associated with a hidden negative differential resistance, as identified by impedance data. Very rich and robust dynamics were observed, including the presence of harmonic and mixed mode oscillations and chaotic states, in some parameter region. Oscillation frequencies of about 16 Hz characterized the fastest oscillations ever reported for the electro-oxidation of small organic molecules. Those high frequencies were strongly influenced by the electrolyte pH and far less affected by the EG concentration. The system was regularly dependent on temperature under voltammetric conditions but rather independent within the oscillatory regime.

Assessment of intracellular water by whole body bioelectrical impedance and total body potassium in HIV-positive patients

.:Abstract-Objective: Bioelectrical impedance analysis (BIA) is widely used as bedside assessment of body composition. Body cell mass (BCM) and intracellular water (ICW) are clinically important body compartments. Estimates of ICW obtained from BIA by different calculation approaches were compared to a reference method in male HIV-infected patients. Patients: Representative subsample of clinically stable HIV-infected outpatients, consisting of 42 men with a body mass index of 22.4 +/- 3.8 kg/m(2) (range, 13-31 kg/m(2)). Methods: Total body potassium was assessed in a whole body counter, and compared to 50 kHz mono-frequency BIA and multifrequency bioelectrical impedance spectroscopy. Six different prediction equations for ICW from BIA data were applied. Methods were compared by the Bland-Altman method. Results: BIA-derived ICW estimates explained 58% to 73% of the observed variance in ICW (TBK), but limits of confidence were wide (-16.6 to +18.2% for the best method). BIA overestimated low ICW (TBK) and underestimated high ICW (TBK) when normalized for weight or height. Mono- and multifrequency BIA were not different in precision but population-specific equations tended to narrower confidence limits. Conclusion: BIA is an unreliable method to estimate ICW in this population, in contrast to the better established estimation of total body water and extracellular water. Potassium depletion in severe malnutrition may contribute to this finding but a major part of the residual between methods remains unexplained. (C) 2000 Harcourt Publishers Ltd.

Real-time detection of pneumothorax using electrical impedance tomogyaphy

Objectives: Pneumothorax is a frequent complication during mechanical ventilation. Electrical impedance tomography (EIT) is a noninvasive tool that allows real-time imaging of regional ventilation. The purpose of this study was to 1) identify characteristic changes in the EIT signals associated with pneumothoraces; 2) develop and fine-tune an algorithm for their automatic detection; and 3) prospectively evaluate this algorithm for its sensitivity and specificity in detecting pneumothoraces in real time. Design: Prospective controlled laboratory animal investigation. Setting: Experimental Pulmonology Laboratory of the University of Sao Paulo. Subjects: Thirty-nine anesthetized mechanically ventilated supine pigs (31.0 +/- 3.2 kg, mean +/- SD). Interventions. In a first group of 18 animals monitored by EIT, we either injected progressive amounts of air (from 20 to 500 mL) through chest tubes or applied large positive end-expiratory pressure (PEEP) increments to simulate extreme lung overdistension. This first data set was used to calibrate an EIT-based pneumothorax detection algorithm. Subsequently, we evaluated the real-time performance of the detection algorithm in 21 additional animals (with normal or preinjured lungs), submitted to multiple ventilatory interventions or traumatic punctures of the lung. Measurements and Main Results: Primary EIT relative images were acquired online (50 images/sec) and processed according to a few imaging-analysis routines running automatically and in parallel. Pneumothoraces as small as 20 mL could be detected with a sensitivity of 100% and specificity 95% and could be easily distinguished from parenchymal overdistension induced by PEEP or recruiting maneuvers, Their location was correctly identified in all cases, with a total delay of only three respiratory cycles. Conclusions. We created an EIT-based algorithm capable of detecting early signs of pneumothoraces in high-risk situations, which also identifies its location. It requires that the pneumothorax occurs or enlarges at least minimally during the monitoring period. Such detection was operator-free and in quasi real-time, opening opportunities for improving patient safety during mechanical ventilation.

Toxoplasma gondii isolates: Multi locus RFLP-PCR genotyping from human patients in Sao Paulo State, Brazil identified distinct genotypes

This study investigated the genetic characteristics of Toxoplasma gondii samples collected from 62 patients with toxoplasmosis in Sao Paulo State, Brazil. DNA samples were isolated from blood, cerebrospinal fluid and amniotic fluids of 25 patients with cerebral toxoplasmosis and AIDS, two patients with acute toxoplasmosis, 12 patients with ocular toxoplasmosis, six newborns with congenital toxoplasmosis and 17 pregnant women with acute infection. Diagnosis of toxoplasmosis was based in clinical, radiological and laboratory features. Genotyping was performed using multilocus PCR-RFLP genetic markers including SAG1, SAG2, 5`- and 3`-SAG2, alt.SAG2, SAG3, BTUB, GRA6, C22-8, c29-2, L358, PK1 and Apico. Among the 62 clinical samples, 20 (32%) were successfully genotyped at eight or more genetic loci and were grouped to three distinct genotypes. Eighteen samples belonged to ToxoDB Genotype #65 and the other two samples were identified as ToxoDB Genotypes #6 and #71, respectively (http://toxodb.org/toxo/). Patients presenting Genotypes #6 and #71 had severe and atypical cerebral toxoplasmosis, characterized by diffuse encephalitis without extensive brain lesions. These results indicate that T. gondii Genotype #65 may have a high frequency in causing human toxoplasmosis in Sao Paulo State, Brazil. This unusual finding highlights the need to investigate the possible association of parasite genotypes with human toxoplasmosis. (C) 2011 Elsevier Inc. All rights reserved.

In vivo electrochemical characterization and inflammatory response of multiwalled carbon nanotube-based electrodes in rat hippocampus

Stimulating neural electrodes are required to deliver charge to an environment that presents itself as hostile. The electrodes need to maintain their electrical characteristics (charge and impedance) in vivo for a proper functioning of neural prostheses. Here we design implantable multi-walled carbon nanotubes coating for stainless steel substrate electrodes, targeted at wide frequency stimulation of deep brain structures. In well-controlled, low-frequency stimulation acute experiments, we show that multi-walled carbon nanotube electrodes maintain their charge storage capacity (CSC) and impedance in vivo. The difference in average CSCs (n = 4) between the in vivo (1.111 mC cm(-2)) and in vitro (1.008 mC cm(-2)) model was statistically insignificant (p > 0.05 or P-value = 0.715, two tailed). We also report on the transcription levels of the pro-inflammatory cytokine IL-1 beta and TLR2 receptor as an immediate response to low-frequency stimulation using RT-PCR. We show here that the IL-1 beta is part of the inflammatory response to low-frequency stimulation, but TLR2 is not significantly increased in stimulated tissue when compared to controls. The early stages of neuroinflammation due to mechanical and electrical trauma induced by implants can be better understood by detection of pro-inflammatory molecules rather than by histological studies. Tracking of such quantitative response profits from better analysis methods over several temporal and spatial scales. Our results concerning the evaluation of such inflammatory molecules revealed that transcripts for the cytokine IL-1 beta are upregulated in response to low-frequency stimulation, whereas no modulation was observed for TLR2. This result indicates that the early response of the brain to mechanical trauma and low-frequency stimulation activates the IL-1 beta signaling cascade but not that of TLR2.