HUMAN BONE MARROW AND ADIPOSE TISSUE DERIVED MESENCHYMAL STROMAL CELL INFLUENCE ON NEUROLOGICAL DEFICIT RECOVERY IN A MODEL OF SEVERE TRAUMATIC BRAIN INJURY IN RATS

In the present study we characterized the effect of transplantation of bone marrow and adipose tissue MSCs in the model of brain injury in rats. This study was performed on Wistar rats (males and females in equal proportions with body weight of 250—270 g; n = 50). Traumatic brain injury was produced, by original spring-loaded, mechanism to precise dosing of impact force. Neurological disorders were assessed by Chen scale, a vertical grid test and a Morris water maze. MSC injections on day 1 were accompanied by a significant reduction in neurological deficit in compare with the control group. Adipose tissue derived MSCs were found to have a more pronounced effectiveness than MSCs obtained from bone marrow

Атаки на глобальные навигационные спутниковые системы и обнаружение спуфинга беспилотных кораблей, базирующееся на облачных технологиях

Статья поступила 11.06.2018. Принята в печать 17.07.2018.Receiver: 11.06.2018. Accepted: 17.07.2018.Satellite navigation systems are widely used in navigation for precise trajectory determination of transport equipment. In this article mathematical models and algorithms have been developed to solve the problems of satellite navigation safety. One of the problems is spoofing (substitution) — a situation in which a system (hardware, software, etc.) successfully masquerades as another by falsifying data system and performs illegal actions. What is considered in the paper is the spoofing detection algorithm based on the analysis of a civil satellite signal generated by the mobile GNSS-singleantenna receivers or dual-antenna. The article also serves to refine the civilian spoofing threat assessment by demonstrating the challenges involved in mounting a spoofing attack. The widespread deployment of GNSS is pushing the current receiver technology to its limits due to the stringent demands for providing seamless, ubiquitous and secure/reliable positioning. This fact is further aggravated by the advent of new applications where the miniaturized size, low power consumption and limited computational capabilities of user terminals pose serious concerns to the implementation of even the most basic GNSS signal processing tasks. This article presents the advantage of Cloud-Based GNSS Navigation, which facilitates the possibility of developing innovative applications where their particularities (e. g. massive processing of data, cooperation among users, security-related applications, etc.) make them suitable for implementation using a cloud-based infrastructure.Спутниковые навигационные системы широко используются для точного определения траектории транспортных средств. В этой статье разработаны математические модели и алгоритмы для решения проблем безопасности спутниковой навигации. Одной из проблем является спуфинг (подстановка) — ситуация, когда система (аппаратное обеспечение, программное обеспечение и т. п.) успешно маскируется как другая, фальсифицируя систему данных, и выполняет незаконные действия. В статье рассматривается алгоритм обнаружения спуфинга на основе анализа гражданского спутникового сигнала, принимаемого мобильными одноантенными или двухантенными приемниками ГНСС. Эта работа также служит для уточнения оценки угроз среди гражданского населения путем демонстрации проблем, связанных с обнаружением спуфинга. Широкое распространение ГНСС подталкивает текущую технологию приемника к ее пределам из-за строгих требований к обеспечению бесшовного, повсеместного, безопасного и надежного позиционирования. Этот факт еще более усугубляется появлением новых приложений: миниатюрный размер, низкое энергопотребление и ограниченные вычислительные возможности пользовательских терминалов создают серьезную проблему для реализации даже самых основных задач обработки сигналов ГНСС. Эта работа иллюстрирует преимущество спутниковой навигации с использованием облачных технологий, которая облегчает возможность разработки инновационных приложений, таких как, например, массированная обработка данных, сотрудничество между пользователями, приложения, защищенные безопасностью и т. п

Polymorphism of ITS sequences in 35S rRNA genes in Elymus dahuricus aggregate species: two cryptic species?

Nuclear ribosomal internal transcribed spacer (ITS) sequences were sequenced for 23 species and subspecies of Elymus sensu lato collected in Russia. The Neighbor-Net analysis of ITS sequences suggested that there are four ribotypes called Core Northern St-rDNA, Core Southern St-rDNA, Northern dahuricus St-rDNA and Southern dahuricus St-rDNA. The Core Southern variant of St-rDNA is closely related to rDNA of diploid Pseudoroegneria stipifolia (PI 313960) and P. spicata (PI 547161). The Core Northern St-rDNA is closely related to rDNA of P. cognata (PI 531720), a diploid species of Kyrgyzstan carrying StY variant of the St genome. The Core Northern St-rDNA is widespread among the Elymus species of Siberia and the Far East, including Yakutia and Chukotka. The Core Southern St-ribotype is typical of southern Elymus and Pseudoroegneria of the South Caucasus, Primorye, Pakistan, and South Korea. The Northern dahuricus St-ribotype and Southern dahuricus St-ribotype are derivatives of the Core Northern and Core Southern St-ribotypes, correspondingly. Both of them were found in all four studied species of the E. dahuricus aggregate: E. dahuricus Turcz. ex Griseb., E. franchetii Kitag., E. excelsus Turcz. ex Griseb. and Himalayan E. tangutorum (Nevski) Hand.-Mazz. In other words, there are at least two population groups (two races) of the Elymus dahuricus aggregate species that consistently differ in their ITS-sequences in Siberia, the Far East and Northern China. Each contains all morphological forms, which taxonomists now attribute either to different species of E. dahuricus aggr. (E. dahuricus sensu stricto, E. franchetii, E. tangutorum, E. excelsus) or subspecies of Campeiostachys dahurica (Turcz. ex Griseb.) B.R. Baum, J.L. Yang et C.C. Yen. At the moment it is unknown if there are any morphological differences between plants carrying either Northern or Southern dahuricus rDNA. Probably, they are cryptic species, but it is certain that if differences in morphology between the two races exist, they are not associated with signs that are now considered taxonomically significant and are used to separate E. dahuricus s. s., E. franchetii, E. tangutorum, and E. excelsus

Basal ganglia correlates of fatigue in young adults

Although the prevalence of chronic fatigue is approximately 20% in healthy individuals, there are no studies of brain structure that elucidate the neural correlates of fatigue outside of clinical subjects. We hypothesized that fatigue without evidence of disease might be related to changes in the basal ganglia and prefrontal cortex and be implicated in fatigue with disease. We aimed to identify the white matter structures of fatigue in young subjects without disease using magnetic resonance imaging (MRI). Healthy young adults (n = 883; 489 males and 394 females) were recruited. As expected, the degrees of fatigue and motivation were associated with larger mean diffusivity (MD) in the right putamen, pallidus and caudate. Furthermore, the degree of physical activity was associated with a larger MD only in the right putamen. Accordingly, motivation was the best candidate for widespread basal ganglia, whereas physical activity might be the best candidate for the putamen. A plausible mechanism of fatigue may involve abnormal function of the motor system, as well as areas of the dopaminergic system in the basal ganglia that are associated with motivation and reward

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed

Variability in the analysis of a single neuroimaging dataset by many teams

Data analysis workflows in many scientific domains have become increasingly complex and flexible. To assess the impact of this flexibility on functional magnetic resonance imaging (fMRI) results, the same dataset was independently analyzed by 70 teams, testing nine ex-ante hypotheses. The flexibility of analytic approaches is exemplified by the fact that no two teams chose identical workflows to analyze the data. This flexibility resulted in sizeable variation in hypothesis test results, even for teams whose statistical maps were highly correlated at intermediate stages of their analysis pipeline. Variation in reported results was related to several aspects of analysis methodology. Importantly, meta-analytic approaches that aggregated information across teams yielded significant consensus in activated regions across teams. Furthermore, prediction markets of researchers in the field revealed an overestimation of the likelihood of significant findings, even by researchers with direct knowledge of the dataset. Our findings show that analytic flexibility can have substantial effects on scientific conclusions, and demonstrate factors related to variability in fMRI. The results emphasize the importance of validating and sharing complex analysis workflows, and demonstrate the need for multiple analyses of the same data. Potential approaches to mitigate issues related to analytical variability are discussed

Linking Symptom Inventories using Semantic Textual Similarity

An extensive library of symptom inventories has been developed over time to measure clinical symptoms, but this variety has led to several long standing issues. Most notably, results drawn from different settings and studies are not comparable, which limits reproducibility. Here, we present an artificial intelligence (AI) approach using semantic textual similarity (STS) to link symptoms and scores across previously incongruous symptom inventories. We tested the ability of four pre-trained STS models to screen thousands of symptom description pairs for related content - a challenging task typically requiring expert panels. Models were tasked to predict symptom severity across four different inventories for 6,607 participants drawn from 16 international data sources. The STS approach achieved 74.8% accuracy across five tasks, outperforming other models tested. This work suggests that incorporating contextual, semantic information can assist expert decision-making processes, yielding gains for both general and disease-specific clinical assessment