PEGylation of cationic liposomes encapsulating soluble Leishmania antigens reduces the adjuvant efficacy of liposomes in murine model.

Although there have been several attempts to develop a vaccine against leishmaniasis, no vaccine in human has been developed yet. Liposomes consisting of 1, 2-dioleoyl-3-trimethylammonium-propane (DOTAP) encapsulating soluble Leishmania antigens (SLA) enhance protective immunity of SLA against Leishmania major infection in mice. However, they immobilized at the injection site because of their positive charge. To overcome the problem, shielding the surface charge with polyethylene glycol (PEGylation) was chosen in this study. Liposomal SLA consisting different concentrations of PEG (1.9%-15% mol) were prepared. BALB/c mice were immunized three times in 3 weeks intervals with different formulations. Lesion development and parasite burden in footpad and spleen were evaluated to specify the type of generated immune response and extent of protection. Th1/Th2 cytokine profiles and IgG isotypes were also analysed. The maximum protection was observed in mice immunized with Lip-SLA or pLip-SLA (1.9%) due to smaller footpad swelling, reduction in parasite load, an increase in IgG2a and IFN-γ production. Our results showed that immunization of mice with a high level of PEG (>7.5%) did not improve protective immunity of liposomal SLA. The presence of PEG, particularly more than 3.75%, is not recommended for protection against leishmaniasis.

Doppler broadening thermometry of acetylene and accurate measurement of the Boltzmann constant.

In this paper, we present accurate measurements of the fundamental Boltzmann constant based on a line-shape analysis of acetylene spectra in the ν1 + ν3 band recorded using a tunable diode laser. Experimental spectra recorded at low pressures (0.25 - 9 Torr), have been analyzed using a Speed Dependent Voigt model that takes into account the molecular speed dependence effects. This line-shape model reproduces the experimental data with good accuracy and allows us to determine precise line-shape parameters for the P(25) transition of the ν1 + ν3 band. From the recorded spectra we obtained the Doppler-width and then determined the Boltzmann constant, k(B).

The effect of adipose tissue material properties on the lap belt-pelvis interaction: A global sensitivity analysis.

The lap belt-pelvis interaction is one of the main factors influencing the risk for abdominal and lower extremity injuries during vehicular crashes. To numerically study the lap belt-pelvis interaction, biofidelic representation of subcutaneous adipose tissue appears essential, especially for obese occupants with a thick layer of adipose tissue. Therefore, in this study, a finite element model is constructed and a newly developed material model for adipose tissue from the previous work is implemented to study the mechanism of lap belt-pelvis interaction and how subcutaneous adipose tissue affects this. Global Sensitivity Analysis (GSA) is used to determine which aspects of the mechanical properties of adipose tissue play a major role in the lap belt-pelvis interaction. It is found that, firstly, the incompressibility condition of adipose tissue is the most influential parameter. Secondly, the nonlinear elastic and viscoelastic properties are influential because of experiencing large deformation. The findings of this study are meaningful for vehicular injury-oriented characterization of adipose tissue as well as improving the biofidelity of finite element human body models for human safety.

Relativistic kinetic theory for spin-1/2 particles: Conservation laws, thermodynamics, and linear waves.

We study a recently derived fully relativistic kinetic model for spin-1/2 particles. First, the full set of conservation laws for energy, momentum, and angular momentum are given together with an expression for the (nonsymmetric) stress-energy tensor. Next, the thermodynamic equilibrium distribution is given in different limiting cases. Furthermore, we address the analytical complexity that arises when the spin and momentum eigenfunctions are coupled in linear theory by calculating the linear dispersion relation for such a case. Finally, we discuss the model and give some context by comparing with potentially relevant phenomena that are not included, such as radiation reaction and vacuum polarization.

Electrocardiogram signal quality assessment using an artificially reconstructed target lead.

In real applications, even the most accurate electrocardiogram (ECG) analysis algorithm, based on research databases, might breakdown completely if a quality measurement technique is not applied precisely before the analysis. The major concentration of this study is to describe and develop a reliable ECG signal quality assessment technique. The proposed algorithm includes three major stages: preprocessing, energy-concavity index (ECI) analysis and a correlation-based examination subroutine. The preprocessing step includes the removal of baseline wanders and high-frequency disturbances. The quality measurement based on ECI includes two separate stages according to the energy and concavity of the ECG signal. The correlation-based quality measurement step is mainly established by using the correlation between ECG leads estimated by applying a suitably trained neural network. The operating characteristics of the proposed ECI are sensitivity (Se) of 77.04% with a positive predictive value (PPV) of 90.53% for detecting high-energy noise. The correlation-based technique achieved the best scores (Se = 100%; PPV = 98.92%) for detecting high-energy noise and for recognising any other kind of disturbances (Se = 92.36%; PPV = 94.77%). Although ECI analysis acts effectively against high-energy disturbances, very poor performance is obtained in cases where the energy of the disturbances is not considerable. However, the correlation-based method is able to find all kinds of disturbances. For officially evaluating the proposed algorithm, an entry was sent to the Computing-in-Cardiology Challenge 2011 on 27 February 2012; a final score (accuracy) of 93.60% was achieved.

A correlation analysis-based detection and delineation of ECG characteristic events using template waveforms extracted by ensemble averaging of clustered heart cycles.

The goal of this study is to introduce a simple, standard and safe procedure to detect and to delineate P and T waves of the electrocardiogram (ECG) signal in real conditions. The proposed method consists of four major steps: (1) a secure QRS detection and delineation algorithm, (2) a pattern recognition algorithm designed for distinguishing various ECG clusters which take place between consecutive R-waves, (3) extracting template of the dominant events of each cluster waveform and (4) application of the correlation analysis in order to delineate automatically the P- and T-waves in noisy conditions. The performance characteristics of the proposed P and T detection-delineation algorithm are evaluated versus various ECG signals whose qualities are altered from the best to the worst cases based on the random-walk noise theory. Also, the method is applied to the MIT-BIH Arrhythmia and the QT databases for comparing some parts of its performance characteristics with a number of P and T detection-delineation algorithms. The conducted evaluations indicate that in a signal with low quality value of about 0.6, the proposed method detects the P and T events with sensitivity Se=85% and positive predictive value of P+=89%, respectively. In addition, at the same quality, the average delineation errors associated with those ECG events are 45 and 63ms, respectively. Stable delineation error, high detection accuracy and high noise tolerance were the most important aspects considered during development of the proposed method.

Detection and boundary identification of phonocardiogram sounds using an expert frequency-energy based metric.

This paper presents a new method to detect and to delineate phonocardiogram (PCG) sounds. Toward this objective, after preprocessing the PCG signal, two windows were moved on the preprocessed signal, and in each analysis window, two frequency-and amplitude-based features were calculated from the excerpted segment. Then, a synthetic decision making basis was devised by combining these two features for being used as an efficient detection-delineation decision statistic, (DS). Next, local extremums and locations of minimum slopes of the DS were determined by conducting forward-backward local investigations with the purpose of detecting sound incidences and their boundaries. In order to recognize the delineated PCG sounds, first, S1 and S2 were detected. Then, a new DS was regenerated from the signal whose S1 and S2 were eliminated to detect occasional S3 and S4 sounds. Finally, probable murmurs and souffles were spotted. The proposed algorithm was applied to 52 min PCG signals gathered from patients with different valve diseases. The provided database was annotated by some cardiology experts equipped by echocardiography and appropriate computer interfaces. The acquisition landmarks were in 2R (aortic), 2L (pulmonic), 4R (apex) and 4L (tricuspid) positions. The acquisition sensor was an electronic stethoscope (3 M Littmann® 3200, 4 kHz sampling frequency). The operating characteristics of the proposed method have an average sensitivity Se = 99.00% and positive predictive value PPV = 98.60% for sound type recognition (i.e., S1, S2, S3 or S4).

Noise/spike detection in phonocardiogram signal as a cyclic random process with non-stationary period interval.

The major aim of this study is to describe a unified procedure for detecting noisy segments and spikes in transduced signals with a cyclic but non-stationary periodic nature. According to this procedure, the cycles of the signal (onset and offset locations) are detected. Then, the cycles are clustered into a finite number of groups based on appropriate geometrical- and frequency-based time series. Next, the median template of each time series of each cluster is calculated. Afterwards, a correlation-based technique is devised for making a comparison between a test cycle feature and the associated time series of each cluster. Finally, by applying a suitably chosen threshold for the calculated correlation values, a segment is prescribed to be either clean or noisy. As a key merit of this research, the procedure can introduce a decision support for choosing accurately orthogonal-expansion-based filtering or to remove noisy segments. In this paper, the application procedure of the proposed method is comprehensively described by applying it to phonocardiogram (PCG) signals for finding noisy cycles. The database consists of 126 records from several patients of a domestic research station acquired by a 3M Littmann(®) 3200, 4KHz sampling frequency electronic stethoscope. By implementing the noisy segments detection algorithm with this database, a sensitivity of Se=91.41% and a positive predictive value, PPV=92.86% were obtained based on physicians assessments.

A unified procedure for detecting, quantifying, and validating electrocardiogram T-wave alternans.

The precision of T-wave alternans (TWA) quantification depends certainly upon the way we choose to align T-waves and to get feedbacks from the electrocardiogram (ECG) quality. Quantifying the ECG TWA based on assigning automatically the required number of T-waves along with applying a proper T-wave alignment approach is the purpose of this paper. The structure of the proposed method mainly consists of seven sections: preprocessing, ECG events detection-delineation, alignment of cycles, T-wave template extraction, T-wave delineation, T-wave left- and right-lobes synchronization, and T-wave alternans quantification-detection by getting feedback from ECG quality value. The proposed method is examined in two ways. First, some artificially generated ECGs with predefined TWA patterns and qualities are analyzed in order to regulate the parameters of the method to achieve the maximum performance. Finally, the method is applied to PhysioNet/Computing in Cardiology Challenge 2008 database. In this stage, the achieved accuracy is about 91.0 %, which shows marginal improvement in the area of TWA quantification.

An expert electrocardiogram quality evaluation algorithm based on signal mobility factors.

The major concentration of this study is to describe and to develop a new electrocardiogram (ECG) signal measurement binary quality assessment (accept-reject) technique. The proposed algorithm is composed of three major stages: pre-processing, signal mobility-based quality measurement and advanced post-evaluation. The pre-processing step includes baseline wander and high-frequency disturbances removal. The signal mobility-based quality measurement routine includes two separate stages based on energy and concavity of the ECG signal. The post-evaluation quality measurement step is mainly based on the six features inferenced from heuristic experiences and human thinking models. The proposed technique was applied to the test dataset provided by the PhysioNet Computing in Cardiology (CinC) challenge 2011 and accuracy 93.40% was achieved which shows the marginal improvement in this field.

An investigation of management effects on range functionality (case study: Karkaboud and Kouin, Taleghan).

Ecosystem function is affected by management activities in rangeland ecosystems. Hence, it is necessary to consider management effects on rangeland ecosystem to reduce its degradation. In order to determine the effects of management activities on rangeland ecosystem, four management treatments were chosen in Taleghan, Iran. Functionality characteristics including: stability, infiltration and nutrient cycling were calculated using Landscape Function Analysis (LFA). LFA calculates these parameters using 11 soil surface indicators. Results showed that stability, infiltration and nutrient cycle were higher in Karkaboud than the other locations because of low grazing pressure and non-accessibility conditions. As grazing pressure increased we witnessed less stability, infiltration and nutrient cycling in Karkaboud cascade, Kouin and Kouin-Marjan. Main causes of decline in stability, infiltration and nutrient cycling are perennial vegetation removal, soil trampling and decrease in soil organic matter and subsequent increase in erosion and soil instability.

Computerized quality assessment of phonocardiogram signal measurement-acquisition parameters.

The major focus of this study is to describe and develop a phonocardiogram (PCG) signal measurement binary quality assessment (accept-reject) technique. The proposed algorithm is composed of three major stages: preprocessing, numerical-based quality measurement and advanced measurement subroutines. The preprocessing step includes normalization, wavelet-based threshold denoising and baseline wander removal. The numerical-based quality measurement routine includes two separate stages based on energy and level of noise of the PCG signal. The advanced quality measurement step is mainly based on the interval of S1 and S2 sounds. The proposed technique was applied to 400 2-min PCG signals gathered by volunteers with range of skills in PCG data acquisition from patients with different types of valve diseases from their 2R (aortic), 2L (pulmonic), 4R (apex) and 4L (tricuspid) positions by implementing an electronic stethoscope (3M Littmann(®) 3200, 4 kHz sampling frequency). The dataset was firstly annotated manually and then, by applying the proposed algorithm, an accuracy of 95.25% was achieved.