We present a detailed description of the numerical implementation (for either MATLAB or GNU Octave) of a novel method for processing data with serial localized peaks intended to distinguish between individual components even when they form a mono-modal but complicatedly shaped structure [E.B. Postnikov et al. Mathematics 9 (2021) 2802]. The essence of the method consists of a cascade of local non-linear approximations by the Gaussian function at the vicinity of the zero-crossings for the signal’s Hilbert transform. At the first level, this procedure is applied to the processed signal directly; at the next level, it is applied to residuals between the signal and approximations on the previous levels. As a practical example, we consider the decomposition of Raman spectra recorded from different strains of Mycobacterium tuberculosis. Finally, we discuss other areas of applicability for the proposed method of signal processing.
Here we report the construction, results of testing, and methodology of data processing for a newly developed portable microbiological analyzer (patent application RU2021111818,24.04.2021). This Arduino-based setup allows for high-frequency temporal resolution of data recordings that reduces instant noises and provides detailed dynamical curves. It was tested with the culture of baker’s yeast Saccharomyces cerevisiae in a liquid medium with the usage of resazurin as a redox indicator changing its colour. Moreover, for such fast-growing culture, one should take into account the full chain of chemical transitions from resazurin to resarufin and further to dihydroresorufin. We argue that the respective model of such chemical cascade can be treated with the logletdecomposition of the recorded data into components of two Bertalanffy’s models and demonstrate the ability to define the required kinetic rates.
Lung tuberculosis caused by Micobacterium tuberculosis is still one of the leading killers today. Different computational models have been developed to find new clues to understand this mortal disease. Up until now these models lacked up-to-date visualization tools that allow dynamic exploratory data analysis. We have developed model based on the study of “manipulation" by immune signalling and biochemical metabolic pathways by M. tuberculosis that reveal key factors contributing either to the beginning of reparative changes or the transition of the disease to a chronic form. We have defined deploying the mathematical model and being based on published clinical observations, "key parameters" stimulating the restoration of the structure and functions of tissues, as well as analyzed the dynamics of cellular populations for the diagnosis of functional and pathological conditions of the host.
The discovery of meningeal lymphatic vessels [Louveau et al, 2015] is one of the most impressive breakthroughs of neurophysiology of last years, and the problem of its functioning is a hot topic far from the complete resolution. In addition, first video recordings in vivo, which allows revealing spatio-temporal dynamics potentially possible, are made available only recently [Castranova et al., 2020]. This talk comprises two main issues in this respect, both of which address the practical sides of computational biophysics and data analysis: i) the computational analysis of the mentioned video records by means of MATLAB's tools for video and image processing as well as a presentation of its quantitative results; ii) the methodology of numerical simulations of the proposed nonlinear partial differential equation that generalizes the Barenblatt-Pattle's solution for moving fronts spread in porous media on the case of distributed sources and channels with a finite width associated with lymphatic micro-vessels.
The rezazurin assay for screening of bacterial growth remains the most popular method for express diagnostic tests. It is based on the change of colour and uorescence properties of the respective dye due to bacterial breathing but its conventional quantitative practical implementation requires a relative expensive and cumbersome spectrophotometric equipment. As an alternative approach, we propose to shift a focus from hardware to software. Preliminary results announced in this work show that the processing RGB colour channels for simple photographic images of resazurin assay plates with mycobacterium tuberculosis provides an opportunity to reconstruct the target growth curve with an accuracy comparable with results obtained using the conventional photometric uorescence curves.
Laser Speckle Contrast Analysis (LASCA) is one of the most powerful modern methods for revealing blood dynamics. The experimental design and theory for this method are well established, and the computational recipie is often regarded to be trivial. However, the achieved performance and spatial resolution may considerable differ for different implementations. We comprise a minireview of known approaches to the spatial laser speckle contrast data processing and their realization in MATLAB code providing an explicit correspondence to the mathematical representation, a discussion of available implementations. We also present the algorithm based on the 2D Haar wavelet transform, also supplied with the program code. This new method provides an opportunity to introduce horizontal, vertical and diagonal speckle contrasts; it may be used for processing highly anisotropic images of vascular trees. We provide the comparative analysis of the accuracy of vascular pattern detection and the processing times with a special attention to details of the used MATLAB procedures.
Transparenchymal transport attracted the attention of many research groups after the discovery of glymphatic mechanism for the brain drainage in 2012. While the main facts of rapid transport of substances across the parenchyma are well established experimentally, specific mechanisms that drive this drainage are just hypothezised but not proved yed. Moreover, the number of modeling studies show that the pulse wave powered mechanism is unlikely able to perform pumping as suggested. Thus, the problem is still open. In addition, new data obtained under the conditions of intensionally opened blood brain barrier shows the presence of equally fast transport in opposite durection. In our study we investigate the possible physical mechanisms for rapid transport of substances after the opening of blood-brain barrier under the conditions of zero net flow.
A manual measurement of blood vessels diameter is a conventional component of routine visual assessment of microcirculation, say, during optical capillaroscopy. However, many modern optical methods for blood flow measurements demand the reliable procedure for a fully automated detection of vessels and estimation of their diameter that is a challenging task. Specifically, if one measure the velocity of red blood cells by means of laser speckle imaging, then visual measurements become impossible, while the velocity-based estimation has their own limitations. One of promising approaches is based on fast switching of illumination type, but it drastically reduces the observation time, and hence, the achievable quality of images. In the present work we address this problem proposing an alternative method for the processing of noisy images of vascular structure, which extracts the mask denoting locations of vessels, based on the application of the continuous wavelet transform with the Morlet wavelet having small central frequencies. Such a method combines a reasonable accuracy with the possibility of fast direct implementation to images. Discussing the latter, we describe in details a new MATLAB program code realization for the CWT with the Morlet wavelet, which does not use loops completely replaced with element-by-element operations that drastically reduces the computation time.
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