Performance of two-dimensional Doppler echocardiography for the assessment of infarct size and left ventricular function in rats

Although echocardiography has been used in rats, few studies have determined its efficacy for estimating myocardial infarct size. Our objective was to estimate the myocardial infarct size, and to evaluate anatomic and functional variables of the left ventricle. Myocardial infarction was produced in 43 female Wistar rats by ligature of the left coronary artery. Echocardiography was performed 5 weeks later to measure left ventricular diameter and transverse area (mean of 3 transverse planes), infarct size (percentage of the arc with infarct on 3 transverse planes), systolic function by the change in fractional area, and diastolic function by mitral inflow parameters. The histologic measurement of myocardial infarction size was similar to the echocardiographic method. Myocardial infarct size ranged from 4.8 to 66.6% when determined by histology and from 5 to 69.8% when determined by echocardiography, with good correlation (r = 0.88; P < 0.05; Pearson correlation coefficient). Left ventricular diameter and mean diastolic transverse area correlated with myocardial infarct size by histology (r = 0.57 and r = 0.78; P < 0.0005). The fractional area change ranged from 28.5 ± 5.6 (large-size myocardial infarction) to 53.1 ± 1.5% (control) and correlated with myocardial infarct size by echocardiography (r = -0.87; P < 0.00001) and histology (r = -0.78; P < 00001). The E/A wave ratio of mitral inflow velocity for animals with large-size myocardial infarction (5.6 ± 2.7) was significantly higher than for all others (control: 1.9 ± 0.1; small-size myocardial infarction: 1.9 ± 0.4; moderate-size myocardial infarction: 2.8 ± 2.3). There was good agreement between echocardiographic and histologic estimates of myocardial infarct size in rats.

Method for automatic detection of wheezing in lung sounds

The present report describes the development of a technique for automatic wheezing recognition in digitally recorded lung sounds. This method is based on the extraction and processing of spectral information from the respiratory cycle and the use of these data for user feedback and automatic recognition. The respiratory cycle is first pre-processed, in order to normalize its spectral information, and its spectrogram is then computed. After this procedure, the spectrogram image is processed by a two-dimensional convolution filter and a half-threshold in order to increase the contrast and isolate its highest amplitude components, respectively. Thus, in order to generate more compressed data to automatic recognition, the spectral projection from the processed spectrogram is computed and stored as an array. The higher magnitude values of the array and its respective spectral values are then located and used as inputs to a multi-layer perceptron artificial neural network, which results an automatic indication about the presence of wheezes. For validation of the methodology, lung sounds recorded from three different repositories were used. The results show that the proposed technique achieves 84.82% accuracy in the detection of wheezing for an isolated respiratory cycle and 92.86% accuracy for the detection of wheezes when detection is carried out using groups of respiratory cycles obtained from the same person. Also, the system presents the original recorded sound and the post-processed spectrogram image for the user to draw his own conclusions from the data.

Development of a rapid method for the determination of antibiotic residues in honey using UPLC-ESI-MS/MS

Abstract An accurate, reliable and fast multianalyte/multiclass ultra-performance liquid chromatography–tandem mass spectrometry (UPLC–MS/MS) method was developed and validated for the simultaneous analysis of 23 pharmaceuticals, belonging to different classes amphenicols, sulfonamides, tetracyclines, in honey samples. The method developed consists of ultrasonic extraction followed by UPLC–ESI–MS/MS with electrospray ionization in both positive mode and negative mode. The influence of the extraction solvents and mobile phase composition on the sensitivity of the method, and the optimum conditions for sample weight and extraction temperature in terms of analyte recovery were extensively studied. The identification of antibiotics is fulfilled by simultaneous use of chromatographic separation using an Acquity BEH C18 (100 mm x 2.1 mm, 1.7 µm) analytical column with a gradient elution of mobile phases and tandem mass spectrometry with an electrospray ionization. Finally, the method developed was applied to the determination of target analytes in honey samples obtained from the local markets and several beekeepers in Muğla, Turkey. Ultrasonic-extraction of pharmaceuticals from honey samples is a well-established technique by UPLC–ESI–MS/MS, the uniqueness of this study lies in the simultaneous determination of a remarkable number of compounds belonging to 23 drug at the sub-nanogram per kilogram level.