Two-step algorithm for the automated analysis of fluorescent microscopy data in biomedical applications

© 2017 IEEE. Measurement automation is essential in various biomedical and biotechnological applications become increasingly important with their intensification and wide utilization. Estimation of both pro- and eukaryotic cells subpopulations in different cultures, samples and tissues, including differentiation of live and dead bacterial cells, stem cells in eukaryotic cell culture and so on are essential in multiple biomedical and biotechnological applications. Fluorescent microscopy is a widely used methodology to obtain the above estimates. Wide utilization of biotechnologies increases the importance of automatic microscopic image processing tools design aiming at both qualitative and quantitative assessment of cells sub-populations. Existing methods are mostly based either on cell detection and counting or on the statistical analysis of image areas with similar staining. However, these methods exhibit known drawbacks including their inapplicability to the communities of cells adherent to each other and to external surfaces with biofilms being a prominent example. Another limitation of standard image processing tools in their high level of automation limiting the ability of the operator to adjust the algorithm parameters to particular microscopic imaging conditions as well as to specific features of the studied cells subpopulations. Here we present a two-step algorithm including preliminary adjustment of its parameters to the imaging conditions based on several representative images from the studied cohort in the first step and fully automated analysis of a large series of images with fixed algorithm parameters in the second step. Out results indicate that the suggested methodology is barely sensitive to the decision threshold value that allows to reduce the parameterization of the algorithm

Statistical Analysis of Local Extrema in Rough Sea Surfaces Based on Computer Simulation

Introduction. Generalized extreme value (GEV) distributions represent a universal description of the limiting distribution of the normalized local maxima statistics for independent and identically distributed data series. Extreme value distributions are commonly classified into three different types representing different functional forms and thus varying in shape, also known as types I, II, and III. Thus, attribution of some observational data series to a particular type of its local maxima distribution, as well as fitting of the distribution parameters, provides certain information about the laws governing the underlying natural or technogenic process. Radar-based remote sensing techniques represent a ubiquitous tool for analyzing large patterns of the sea surface and determining the parameters of the waves. In turn, understanding the laws governing the extreme values in the rough sea surface obtained from their radar images followed by evaluation of their distribution parameters, depending on the wind speed and direction, as well as the presence of surface currents and swells, can be useful for predicting wave height.   Aim. Analysis of the functional forms governing the local extreme value distributions in a rough sea surface for the given wind and swell parameters based on computer simulations.   Materials and methods. For the rough sea surface simulated by an additive harmonic synthesis procedure, the local extreme value distribution was fitted using the least-mean-squares technique. The fitted parameters were then used for their classification according to the three predetermined types.   Results. Computer simulations of a rough sea surface with combined wind and swell waves were performed. It is shown that the distribution of local maxima in the absence of swell waves could be well approximated by theWeibull (type III GEV) distribution, with the parameters explicitly depending on the wind speed. At the same time, no significant dependence on the sea depth was observed. On the contrary, in the presence of additional swell waves, the distribution of local extrema could be rather attributed to the Fréchet (type II GEV) distribution, with the parameters additionally depending on the angle between the wind and swell waves.   Conclusion. The laws governing the distributions of local wave extrema in rough seas are in a good agreement with the theoretical GEV approximations, with the distribution parameters being deductible from the key features of the waves. This indicates the predictability of wave height extrema from sea surface measurements, which can be performed based on remote radar observations

Robust Methods for Assessing the Characteristics of Locomotor Activity Based on Markerless Video Capture Data

Introduction. Analysis of locomotor activity is essential in a number of biomedical and pharmacological research designs, as well as environmental monitoring. The movement trajectories of biological objects can be represented by time series exhibiting a complex multicomponent structure and non-stationary dynamics, thus limiting the effectiveness of conventional correlation and spectral time series analysis methods. Recordings obtained using markerless technologies are typically characterized by enhanced noise levels, including both instrumental noise and anomalous errors associated with false estimates of the location of the points of interest, as well as gaps in the trajectories, promoting an urgent need in the development of robust methods to assess the characteristics of locomotor activity.Aim. Development of robust methods for assessing the characteristics of locomotor activity capable of efficient processing of noisy recordings obtained by markerless video-based motion capture systems.Materials and methods. In order to assess the characteristics of locomotor activity, the relative movements of body parts of laboratory animals were analyzed using the stability metrics of the mutual dynamics of their trajectories, their relative delays, as well as the relative duration of the recording fragments when relatively stable mutual dynamics could be observed. The local maxima of the cross-correlation function of two body fragments, the minima of the standard deviation of the difference between their Hilbert phases, as well as their relative delays, were used as the metrics of mutual dynamics.Results. The considered phase metrics were shown to explicitly reflect changes in locomotor activity, while the assessment of time delays using phase metric was shown to be prone to periodic error. The above limitation could be largely overcome using the correlation metrics, assuming that phase and correlation metrics could be combined.Conclusion. The proposed robust methods provide stable estimates of the characteristics of locomotor activity based on markerless video capture recordings, altogether increasing the efficiency of diagnostic procedures and assessment of the therapeutic effect during rehabilitation

Исследование методов оценивания стабильности взаимного поведения стохастических процессов

The sensitivity of some methods for estimating the mutual dynamic stability of stochastic processes with given correlative properties was studied in relation to the phase detuning between the processes. Two classes of normally distributed random stochastic processes are considered: the processes with short-term correlation and the processes with a long-term correlation, characterized by the specified Hurst coefficients.На примере тестовых процессов с заданными корреляционными свойствами исследована чувствительность методов оценивания стабильности взаимной динамики стохастических процессов к фазовой расстройке между ними. Рассмотрены два класса нормально распределенных стохастических случайных процессов: процессы с кратковременной зависимостью и процессы с долговременной зависимостью, характеризующиеся заданным показателем Херста

Исследование взаимной динамики стохастических нормально распределенных процессов при аддитивной амплитудной расстройке между ними

The joint analysis of several signals is essential for better understanding of the principles underlying the complex systems dynamics. We consider three methods for estimating the stability of the relative dynamics of two surrogate processes. The first one is based on calculation of the phase synchronization coefficient S and the second one on estimation of the cross-conditional entropy CE. The third approach uses the average value of the coherence function of the two processes - the coherence coefficient C. We study the sensitivity of these methods in relation to the amplitude randomization between test processes. All methods are applied to analyze two types of normally distributed random stochastic processes, with either short-term correlations characterized by finite correlation time or long-term correlations with theoretically infinite correlation time characterized by Hurst exponents. In our research, we generate two copies of the surrogate process with either short-term or long-term correlations. Then we attribute the additive white noise to one of these copies at first with the uniform distribution and then with the Gaussian distribution and the same variance. Next, we calculate the coefficients that characterize the mutual behavior of the two test processes and estimate their statistical characteristics. It is found that the sensitivity of all methods to Gaussian additive noise is higher than that of uniform one. We show that processes with long-term correlation react more actively to the additive amplitude noise then processes with short-term correlation. The influence of Hurst exponent value for the processes with long-term correlation is expressed for the coefficients S and C. The influence of correlation time is demonstrated for the coefficients S and СЕ. Our results may be useful in investigations of the mutual dynamics of two processes belonging to the considered types. Функционирование сложных систем возможно характеризовать совместными статистическими характеристиками порождаемых этими системами сигналов. Рассмотрены три подхода к оцениванию стабильности взаимного поведения двух тестовых процессов. Первый подход основан на расчете коэф­фициента фазовой синхронизации (КФС) между процессами. Второй метод базируется на определении взаимной условной энтропии (ВУЭ) процессов. Согласно третьему методу для оценивания стабильности взаимной динамики процессов используется среднее значение функции когерентности (ФК). Исследована чувствительность указанных методов к аддитивной амплитудной расстройке между процессами. Рас­ смотрены два типа процессов: с кратковременной зависимостью и заданным временем корреляции (ВК) и с долговременной зависимостью, определяемой значением показателя Херста. В исследованиях генерирова­лись две копии процесса с известными корреляционными свойствами. Затем в одну из копий вносилась ад­дитивная амплитудная помеха с независимыми отсчетами, подчиняющимися равномерному или нормаль­ ному распределению с одинаковой дисперсией. Для каждого типа помехи и каждого значения ее интенсив­ности оценивались статистические характеристики КФС, ВУЭ и ФК. Выявлено, что чувствительность рассмотренных методов к нормально распределенной расстройке выше, чем к равномерной. При этом процессы с долговременной зависимостью активнее реагируют на аддитивную амплитудную расстройку, чем процессы с кратковременной зависимостью. Влияние показателя Херста для процессов с долговременной зависимостью выражено для КФС и ФК. ВК процессов с кратковременной зависимостью влияет на КФС и ВУЭ. Полученные результаты позволяют обоснованно выбрать необходимый метод анализа взаимной динамики процессов, принадлежащий к рассмотренным в настоящей статье типам.

Исследование методов оценивания стабильности взаимного поведения стохастических процессов

The sensitivity of some methods for estimating the mutual dynamic stability of stochastic processes with given correlative properties was studied in relation to the phase detuning between the processes. Two classes of normally distributed random stochastic processes are considered: the processes with short-term correlation and the processes with a long-term correlation, characterized by the specified Hurst coefficients.На примере тестовых процессов с заданными корреляционными свойствами исследована чувствительность методов оценивания стабильности взаимной динамики стохастических процессов к фазовой расстройке между ними. Рассмотрены два класса нормально распределенных стохастических случайных процессов: процессы с кратковременной зависимостью и процессы с долговременной зависимостью, характеризующиеся заданным показателем Херста

The influence of polymorphic variants rs2305619 и rs3816527 of the PTX3 gene on clinical profile and outcomes in patients with hypertrophic cardiomyopathy: results of a 11-years follow-up

The objective of this study was to determine the association of polymorphic variants rs2305619 and rs3816527 of the PTX3 gene with clinical profile and outcomes in hypertrophic cardiomyopathy (HCM) patients.Methods and materials. The study population consisted of 153 patients ≥18 years old with a confirmed diagnosis of HCM. The control group included 200 healthy donors. Duration of follow-up was 11 years (2008–2019 yrs.). The study design included a new model for determining variants of the clinical profile and outcomes of HCM. Polymorphic variants rs2305619 and rs3816527 of the PTX3 gene were genotyped by polymerase chain reaction.Results. The mortality rate in patients ≥18 years old with 1, 2 and 3 adverse pathways of HCM progression was significantly higher, compared with those without adverse pathways (р<0.001). A combination of chronic heart failure (CHF) with midrange and reduced LVEF (<49 %) with 1, 2 and 3 adverse pathways in HCM patients occurred more frequently, compared with those who had CHF with preserved LVEF (≥50 %) (odds ratio (OR) = 0.168, 95 % confidence interval (CI) =0.068–0.412, р<0.001). The genetic testing showed no significant differences in genotype and allele frequencies of polymorphic variants rs2305619 and rs3816527 of the PTX3 gene in patients with HCM and control groups. It was found a tendency for increase in GG genotype frequency (p<0.068) and significant increase in G allele frequency of rs2305619 of the PTX3 gene in HCM patients ≥18 years old and CHF with mid-range and reduced LVEF (<49 %) (A:G, OR=0.521, 95 % CI=0.301–0.902, p<0.019). HCM patients (age – 63 [58; 75] years) and type 2 diabetes mellitus demonstrated high prevalence in AG and GG genotypes (p<0.008) and G allele frequencies of rs2305619 of the PTX3 gene (A:G, OR =1.952, 95 % CI=1.076–3.542, p<0.026).Conclusions. HCM progression along 1 and more adverse pathways in patients ≥18 years old has been characterized with adverse outcome. G allele of rs2305619 of the PTX3 gene is associated with CHF with mid-range and reduced LVEF (<49 %) in HCM patients ≥18 years old. The associations of G allele and AG and GG genotypes of rs2305619 of the PTX3 gene with diabetes type 2 are observed in elderly HCM patients

Сlinical features of hypertrophic cardiomyopathy depending on the age of onset of clinical manifestations and the presence of cardiometabolic risk factors

The objective was to study the clinical features of symptomatic hypertrophic cardiomyopathy (HCM) depending on the age of onset and the presence of cardiometabolic risk factors.Methods and materials. From 2014 to 2020, 250 patients were examined, 100 patients with symptomatic HCM aged 18 to 86 years were included in the study.Results. The incidence of arterial hypertension (AH), obesity, and angina syndrome was significantly higher in patients with HCM aged 45 years and older. The patients with HCM and associated obesity had greater left ventricular end-diastolic dimension and left antero-posterior size regardless of the age of onset of clinical manifestations. The young patients with HCM and associated obesity had more often AH. Patients with HCM with the disease onset ≥ 45 years of age and associated obesity had greater left ventricular posterior wall thickness, left ventricular end-diastolic dimension index. In this group of patients, pulmonary hypertension was more often diagnosed.Conclusion. Obesity and other cardiometabolic risk factors are predictors of the progressive course of HCM, which points the need for their prevention and timely correction

The impact of Grey Heron (Ardea cinerea L.) colony on soil biogeochemistry and vegetation: a natural long-term in situ experiment in a planted pine forest

Increased anthropogenic pressure including intensification of agricultural activities leads to long-term decline of natural biotopes, with planted forests often considered as promising compensatory response, although reduced biodiversity and ecosystem stability represent their common drawbacks. Here we present a complex investigation of the impact of a large Grey Heron (Ardea cinerea L.) colony on soil biogeochemistry and vegetation in a planted Scots pine forest representing a natural in situ experiment on an engineered ecosystem. After settling around 2006, the colony expanded for 15 years, leading to the intensive deposition of nutrients with feces, food remains and feather thereby considerably altering the local soil biogeochemistry. Thus, lower pH levels around 4.5, 10- and 2-fold higher concentrations of phosphorous and nitrogen, as well as 1.2-fold discrepancies in K, Li, Mn, Zn and Co., respectively, compared to the surrounding control forest area could be observed. Unaltered total organic carbon (Corg) suggests repressed vegetation, as also reflected in the vegetation indices obtained by remote sensing. Moreover, reduced soil microbial diversity with considerable alternations in the relative abundance of Proteobacteria, Firmicutes, Acidobacteriota, Actinobacteriota, Verrucomicrobiota, Gemmatimonadota, Chujaibacter, Rhodanobacter, and Bacillus has been detected. The above alterations to the ecosystem also affected climate stress resilience of the trees indicated by their limited recovery from the major 2010 drought stress, in marked contrast to the surrounding forest (p = 3∙10−5). The complex interplay between geographical, geochemical, microbiological and dendrological characteristics, as well as their manifestation in the vegetation indices is explicitly reflected in the Bayesian network model. Using the Bayesian inference approach, we have confirmed the predictability of biodiversity patterns and trees growth dynamics given the concentrations of keynote soil biogeochemical alternations with correlations R > 0.8 between observations and predictions, indicating the capability of risk assessment that could be further employed for an informed forest management