Aerobic degradation by white‐rot fungi of trichloroethylene (TCE) and mixtures of TCE and perchloroethylene (PCE)

BACKGROUND: Trichloroethylene (TCE) and perchloroethylene (PCE) are considered among the most important groundwater pollutants around the world. These compounds are usually found together in polluted environments but little is known about the ability of microorganisms to simultaneously degrade TCE and PCE. RESULTS: Data showed that several species of white‐rot fungi, including Trametes versicolor, Ganoderma lucidum, and Irpex lacteus, degrade substantial levels of TCE in pure culture. T. versicolor was chosen for further study since it degraded higher levels of TCE than the other organisms. Initial glucose concentration and reoxygenation of samples increased the amount of TCE dechlorination, but no significant difference in percentage TCE degradation was observed. T. versicolor was able to degrade 34.1 and 47.7% of PCE and TCE added as mixtures (containing 5 and 10 mg L⁻¹, respectively). CONCLUSIONS: The degradation ability of TCE was extended to other species of white‐rot fungi. Percentage degradation as well as chloride release from mixtures of TCE and PCE showed that T. versicolor degrades mixtures of TCE and PCE almost as well as its ability to degrade individually added TCE or PCE. The results suggest the potential promise of T. versicolor for bioremediation of TCE and PCE in the environment. Copyright © 2008 Society of Chemical Industry     

Analyzing dynamic EMG and VMG signals of respiratory muscles

A promising technique is described for evaluating ventilatory disease by studying activity and fatigue in the sternocleidomastoid muscle. We analyze dynamic muscular function in time and frequency domains during two respiratory load tests at different levels of ventilation     

Analysis of abnormal signals within the QRS complex of thehigh-resolution electrocardiogram

Presents a new, quantitative approach to measuring abnormal intra-QRS signals, using the high-resolution electrocardiogram (HRECG). These signals are conventionally known as QRS “notches and slurs.” They are measured qualitatively and form the basis for the ECG identification of myocardial infarction. The HRECG is used for detection of ventricular late potentials (LP), which are linked with the presence of a reentry substrate for ventricular tachycardia (VT) after a myocardial infarction. LP's are defined as signals from areas of delayed conduction which outlast the normal QRS period. The authors' objective is to quantify very low-level abnormal signals that may not outlast the normal QRS period. In this work, abnormal intra-QRS potentials (AIQP) were characterized by removing the predictable, smooth part of the QRS from the original waveform. This was represented as the impulse response of an ARX parametric model, with model order selected empirically from a training data set. AIQP were estimated using the residual of the modeling procedure. Critical AIQP parameters to separate VT and non-VT subjects were obtained using discriminant functions. Results suggest that AIQP indexes are a new predictive index of the HRECG for VT. The concept of abnormal intra-QRS potentials permits the characterization of pathophysiological signals contained wholly within the normal QRS period, but related to arrhythmogenesis. The new method may have other applications, such as detection of myocardial ischemia and improved ECG identification of the site of myocardial infarction, particularly in the absence of Q waves     

Lipase‐catalysed synthesis of natural ethanol esters: effect of water removal on enzyme reutilisation

Lipase‐catalysed synthesis of ethanol esters using natural substrates is presented. Initial substrate concentrations, optimised through an experimental design, were 0.8 mol dm⁻³ lauric acid and 0.58 mol dm⁻³ ethanol, with an initial esterification rate (r₀) of 17.13 mmol dm⁻³ min⁻¹. Two different water removal systems were compared: a cooling exchanger in the reactor headspace and a vacuum‐based system. The best results were obtained with the second system. After six consecutive operations with the same enzyme, no loss of activity was observed. The yields obtained in all the runs were greater than 90%. Using the same approach three different natural esters (ethyl laureate, ethyl myristate and ethyl palmitate) were synthesised at 0.9 dm³ scale. Similar results were obtained in all three cases, with chemical yields always being greater than 90%. © 2000 Society of Chemical Industry     

Methods derived from nonlinear dynamics for analysing heart rate variability

Methods from nonlinear dynamics (NLD) have shown new insights into heart rate (HR) variability changes under various physiological and pathological conditions, providing additional prognostic information and complementing traditional time- and frequency-domain analyses. In this review, some of the most prominent indices of nonlinear and fractal dynamics are summarized and their algorithmic implementations and applications in clinical trials are discussed. Several of those indices have been proven to be of diagnostic relevance or have contributed to risk stratification. In particular, techniques based on mono- and multifractal analyses and symbolic dynamics have been successfully applied to clinical studies. Further advances in HR variability analysis are expected through multidimensional and multivariate assessments. Today, the question is no longer about whether or not methods from NLD should be applied; however, it is relevant to ask which of the methods should be selected and under which basic and standardized conditions should they be applied.     

Biodegradation of sulfamethazine by Trametes versicolor: Removal from sewage sludge and identification of intermediate products by UPLC-QqTOF-MS

Degradation of the sulfonamide sulfamethazine (SMZ) by the white-rot fungus Trametes versicolor was assessed. Elimination was achieved to nearly undetectable levels after 20 h in liquid medium when SMZ was added at 9 mg L^− 1. Experiments with purified laccase and laccase-mediators resulted in almost complete removal. On the other hand, inhibition of SMZ degradation was observed when piperonilbutoxide, a cytochrome P450-inhibitor, was added to the fungal cultures. UPLC-QqTOF-MS analysis allowed the identification and confirmation of 4 different SMZ degradation intermediates produced by fungal cultures or purified laccase: desulfo-SMZ, N⁴-formyl-SMZ, N⁴-hydroxy-SMZ and desamino-SMZ; nonetheless SMZ mineralization was not demonstrated with the isotopically labeled sulfamethazine-phenyl-¹³C₆ after 7 days. Inoculation of T. versicolor to sterilized sewage sludge in solid-phase systems showed complete elimination of SMZ and also of other sulfonamides (sulfapyridine, sulfathiazole) at real environmental concentrations, making this fungus an interesting candidate for further remediation research.     

Ventricular late potentials characterization in time-frequencydomain by means of a wavelet transform

The main transforms of Cohen's class allow signal representation simultaneously in time and frequency domains. Wavelet transforms make it possible to link the temporal window width to the analyzing frequency and leads to a “modified wavelet transform” which improves resolution both in time and frequency. A simulation study illustrates the artifacts of every time-frequency representation on pure sinusoids and gives performance evaluation of the different methods when searching a sinusoid embedded in a QRS complex. Analyses of real signals from healthy and pathological subjects confirm the simulation results and complete the characterization of ventricular late potentials yet detected by signal averaging     

DNA binding site characterization by means of Rényi entropy measures on nucleotide transitions.

In this work, parametric information-theory measures for the characterization of binding sites in DNA are extended with the use of transitional probabilities on the sequence. We propose the use of parametric uncertainty measures such as Rényi entropies obtained from the transition probabilities for the study of the binding sites, in addition to nucleotide frequency-based Rényi measures. Results are reported in this work comparing transition frequencies (i.e., dinucleotides) and base frequencies for Shannon and parametric Rényi entropies for a number of binding sites found in E. Coli, lambda and T7 organisms. We observe that the information provided by both approaches is not redundant. Furthermore, under the presence of noise in the binding site matrix we observe overall improved robustness of nucleotide transition-based algorithms when compared with nucleotide frequency-based method.     

Alignment methods for averaging of high-resolution cardiac signals:a comparative study of performance

Accurate signal estimation by means of coherent averaging techniques needs temporal alignment methods. A known low-pass filtering effect is yielded when alignment errors are present. This is very critical in the estimation of low-level high-frequency potentials in high-resolution ECG analysis. A comparative study of the performance of three alignment methods (the double-level method, a new time-delay estimation method based on normalized integrals, and matched filtering) is presented in this paper. A real signal and additive random noise for several signal-to-noise ratios (SNR's) are selected to make an ensemble of computer-simulated beats. The relation between the standard deviation of temporal misalignment versus SNR is discussed. A second study with real ECG signals is also presented. Several morphologies of QRS and P waves are tested. The results are in agreement with the computer simulation study. Nevertheless, the power spectrum of the noise process can affect the results. Matched filter estimation has been tested in the presence of power line interference (50 Hz), with poor results. An application of the three alignment methods as a function of the SNR is proposed. The new time-delay estimation method has been observed to be robust, even in the presence of nonwhite noise.     

Low-pass differentiators for biological signals with known spectra:application to ECG signal processing

Digital low-pass filtering and differentiation (LPD) are useful in real-time processing of many biomedical signals. A general method is presented for determining the coefficients of a differentiator that maximizes the signal-to-noise ratio or minimizes the error between actual and ideal LPD filters, when signal and noise spectra are known. Several examples of digital filters suitable for QRS complex and P-T wave processing in ECG are presented.