Development of Multicellularity: Social/Economic Aspects

This article describes a philosophy of an arising multicellularity on the basis of division of functions between cells. Laws of the division are discussed in elementary multicellularity units, called histions. There is a variety of the histions that have different social structures. Several parameters have been proposed to describe them quantitatively and to systematize them by means of a periodic table. Consideration is given to the rules that govern polymerization of histions as well as the formation of regular cellular networks using them. It is shown that these types of networks could serve as biological tissue models that enable one to predict the tissue development. It has been found that arising multicellularity can result in a drastically decreased metabolites production per cell and thus creates the need in their economically justified unequal distribution

Culture of modern TV reporter’s discourse: the question of rhetorical skills in the profession of a TV reporter

В своей статье известный российский ученый-педагог, специалист в области риторического мастерства, культуры и техники речи профессор А. И. Савостьянов раскрывает законы современной риторики, важные в профессиональной деятельности тележурналиста.In this article a famous Russian scientist, pedagogue, an expert in the field of rhetorical skill, culture and technology of speech Professor A. I. Savostyanov reveals the laws of modern rhetoric, important in the professional activity of a TV reporter

Superfast solution of linear convolutional Volterra equations using QTT approximation

NOTICE: this is the author’s version of a work that was accepted for publication in Journal of Computational and Applied Mathematics. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Journal of Applied and Computational Mathematics, 260, 2014, doi: 10.1016/j.cam.2013.10.025This article address a linear fractional differential equation and develop effective solution methods using algorithms for the inversion of triangular Toeplitz matrices and the recently proposed QTT format. The inverses of such matrices can be computed by the divide and conquer and modified Bini’s algorithms, for which we present the versions with the QTT approximation. We also present an efficient formula for the shift of vectors given in QTT format, which is used in the divide and conquer algorithm. As a result, we reduce the complexity of inversion from the fast Fourier level O(nlogn) to the speed of superfast Fourier transform, i.e., O(log^2n). The results of the paper are illustrated by numerical examples.During this work D. V. Savostyanov and E. E. Tyrtyshnikov were supported by the Leverhulme Trust to visit, stay and work at the University of Chester, as the Visiting Research Fellow and the Visiting Professor, respectively. Their work was also supported in part by RFBR grants 11-01-00549, 12-01-91333-nnio-a, 13-01-12061, and Russian Federation Government Contracts 14.740.11.0345, 14.740.11.1067, 16.740.12.0727

Validation of a face image assessment technology to study the dynamics of human functional states in the EEG resting-state paradigm

The article presents the results of a study aimed at finding covariates to account for the activity of implicit cognitive processes in conditions of functional rest of the subjects and during them being presented their own or someone else’s face in a joint analysis of EEG experiment data. The proposed approach is based on the analysis of the dynamics of the facial muscles of the subject recorded on video. The pilot study involved 18 healthy volunteers. In the experiment, the subjects were sitting in front of a computer screen and performed the following task: sequentially closed their eyes (three trials of 2 minutes each) and opened them (three trials of the same duration between periods of closed eyes) when the screen was either empty or when it was showing a video recording of their own face or the face of an unfamiliar person of the same gender as the participant. EEG, ECG and a video of the face were recorded for all subjects. In the work a separate subtask of the study was also addressed: validating a technique for assessing the dynamics of the subjects’ facial muscle activity using the recorded videos of the “eyes open” trials to obtain covariates that can be included in subsequent processing along with EEG correlates in neurocognitive experiments with a paradigm that does not involve the performance of active cognitive tasks (“resting-state conditions”). It was shown that the subject’s gender, stimulus type (screen empty or showing own/other face), trial number are accompanied by differences in facial activity and can be used as study-specific covariates. It was concluded that the analysis of the dynamics of facial activity based on video recording of “eyes open” trials can be used as an additional method in neurocognitive research to study implicit cognitive processes associated with the perception of oneself and other, in the functional rest paradigm

Effect of Cultural Priming on Social Behavior and EEG Correlates of Self-Processing

Humans are social beings and the self is inevitably conceptualized in terms of social environment. The degree to which the self is perceived as fundamentally similar or fundamentally different from other people is modulated by cultural stereotypes, such as collectivism and individualism. These stereotypes are not hardwired in our brains and individuals differ in the degree to which they adopt the attitudes that define their culture. Moreover, individuals can acquire multiple sets of cultural knowledge and, depending on the context, either individualistic or collectivistic cultural mindset could be activated. In this study, we used cultural priming techniques to activate either individualistic or collectivistic mindset and investigated the association between source-level EEG connectivity in the default mode network (DMN) and spontaneous self-related thoughts in the subsequent resting state. Afterward, participants performed a social interaction task, in which they were allowed to choose between friendly, avoidant, or aggressive behavior. After collectivism priming, self-related thoughts were associated with increased connectivity of DMN with the right temporoparietal junction (TPJ), which is involved in taking the perspective of others and is more active in representatives of collectivistic cultures, whereas after individualism priming they were associated with increased connectivity with the temporal pole, which is involved in self/other discrimination and is more active in representatives of individualistic cultures. Individual differences in the intensity of post-priming self-related thoughts and the strength of DMN-temporal pole connectivity predicted individual differences in behavior during the social interaction task, with individualistic mindset predisposing to more friendly and trustful social behavior

Development of a neural network for diagnosing the risk of depression according to the experimental data of the stop signal paradigm

These days, the ability to predict the result of the development of the system is the guarantee of the successful functioning of the system. Improving the quality and volume of information, complicating its presentation, the need to detect hidden connections makes it ineffective, and most often impossible, to use classical statistical forecasting methods. Among the various forecasting methods, methods based on the use of artificial neural networks occupy a special place. The main objective of our work is to create a neural network that predicts the risk of depression in a person using data obtained using a motor control performance testing system. The stop-signal paradigm (SSP) is an experimental technique to assess a person’s ability to activate deliberate movements or inhibit movements that have become inadequate to external conditions. In modern medicine, the SSP is most commonly used to diagnose movement disorders such as Parkinson’s disease or the effects of stroke. We hypothesized that SSP could serve as a basis for detecting the risk of affective diseases, including depression. The neural network we are developing is supposed to combine such behavioral indicators as: the amount of missed responses, amount of correct responses, average time, the amount of correct inhibition of movements after stopsignal onset. Such a combination of indicators will provide increased accuracy in predicting the presence of depression in a person. The artificial neural network implemented in the work allows diagnosing the risk of depression on the basis of the data obtained in the stop-signal task. An architecture was developed and a system was implemented for testing motor control indicators in humans, then it was tested in real experiments. A comparison of neural network technologies and methods of mathematical statistics was carried out. A neural network was implemented to diagnose the risk of depression using stop-signal paradigm data. The efficiency of the neural network (in terms of accuracy) was demonstrated on data with an expert assessment for the presence of depression and data from the motor control testing system

НОВЫЕ ВАРИАНТЫ ГЕНОМА РОССИЙСКИХ ДЕТЕЙ С ГЕНЕТИЧЕСКИ ОБУСЛОВЛЕННЫМИ КАРДИОМИОПАТИЯМИ, ВЫЯВЛЕННЫЕ МЕТОДОМ МАССОВОГО ПАРАЛЛЕЛЬНОГО СЕКВЕНИРОВАНИЯ

Background: Cardiomyopathies in children are serious, continuously progressing myocardium diseases which are characterized by a variety of the causes, symptoms, implications, and high lethality. More than 400 genes that can cause hereditary heart and vessels diseases are described in scientific literature. The application of a high-performance method of massive parallel sequencing allows to conduct the investigation of genome extended targeted areas revealing the variants and analyzing them (bioinformatics) for pathogenicity.Aims: Identification of a genetic etiology of hereditary cardiomyopathies development in children’s population of the Russian Federation.Materials and methods: The research included 103 patients with various phenotypes of cardiomyopathies aged from 3 months up to 17 years 9 months who at the moment of examination were observed in the cardiology department and the department of recovery treatment with cardiovascular diseases in the NMRCCH. All patients were performed massive parallel sequencing analyzing the targeted areas of 404 genes which mutations lead to the development of heart and vessels hereditary diseases.Results: The diagnostic algorithm based on the method of a massive parallel sequencing was developed. 176 258 minor options were identified in the explored target areas of genome of 103 patients. An average number of the revealed nucleotide replacements different from the reference sequence was 1711. We observed that about 40% of all variants founded by our means were found in MYH7, MYBPC3, TTN, MYH6, SCN5A, DSC2 and TPM1 genes. Bioinformatics analysis allowed revealing 68 novel genome variants associated with cardiomyopathy development. The reliable association of carriage of pathogenic option in MYBPC3 gene with development of hypertrophic cardiomyopathy in the Russian children was found.Conclusions: The application of the offered algorithm allowed establishing laboratory diagnoses to 99 (96.1%) patients out from 103 investigated subjects including the syndromal and non-syndromal forms of heart and vessels hereditary diseases which showed a cardiomyopathy phenotype.Обоснование. Кардиомиопатии у детей относятся к тяжелым, непрерывно прогрессирующим заболеваниям миокарда, характеризующимся разнообразием причин, симптомов и проявлений, высокой летальностью. В мировой литературе описано более 400 генов, мутации которых приводят к развитию генетически обусловленных болезней сердца и сосудов. Применение высокопроизводительного метода массового параллельного секвенирования позволяет проводить исследование протяженных таргетных областей генома для обнаружения вариантов и их дальнейшего биоинформатического анализа на предмет патогенности.Цель исследования — выявление генетической этиологии развития наследственных кардиомиопатий среди детского населения России.Методы. В исследование были включены 103 пациента с различными фенотипами кардиомиопатий в возрасте от 3 мес до 17 лет 9 мес на момент обследования, наблюдавшиеся в кардиологическом отделении и отделении восстановительного лечения детей с болезнями сердечно-сосудистой системы ФГАУ «НМИЦ здоровья детей». Всем пациентам методом массового параллельного секвенирования проведен анализ таргетных областей 404 генов, мутации в которых приводят к развитию наследственных болезней сердца и сосудов.Результаты. Разработан диагностический алгоритм на основе метода массового параллельного секвенирования. Идентифицировано 176 258 минорных вариантов у 103 пациентов в исследуемых целевых регионах генома. В среднем у каждого пациента выявлено 1711 нуклеотидных замен, отличающихся от референсной последовательности. Установлено, что около 40% обнаруженных нами вариантов приходится на гены MYH7, MYBPC3, TTN, MYH6, SCN5A, DSC2 и TPM1. Биоинформатический анализ позволил выявить 68 новых вариантов генома, ассоциированных с развитием кардиомиопатий. Обнаружена достоверная ассоциация носительства патогенного варианта гена MYBPC3 с развитием гипертрофической кардиомиопатии у российских детей — OR 3,17 (1,36–11,72; p=0,009).Заключение. Применение предложенного алгоритма позволило установить лабораторные диагнозы 99 (96,1%) пациентам из 103 обследованных, в том числе с синдромальными и несиндромальными формами наследственных болезней сердца и сосудов, проявляющимися фенотипом кардиомиопатии