Human-centered Model of Interaction within the System “Individual – Higher Educational Establishment”

AbstractIn this article the peculiarities of the model of interaction within the system “individual – higher educational establishment” which is centered on the individual's integrity are considered. Statistic and dynamic characteristics are analyzed. The main principles, such asintegrity, decentration, excessiveness, multidimensional resources, cluster organization are discussed. The key concepts of the model and interaction methods are pointed out. The systematic regularities of this model are described. Various types of relations between an individual and the educational environment are characterized

Conhecimentos e opiniões de médicos e farmacêuticos acerca dos genéricos versus padrões de prescrição/dispensa

Objectivos (Objectives): Na actual situação da economia portuguesa, a política do medicamento assume uma importância primordial na prossecução de uma redução da despesa pública com medicamentos para 1,25% do PIB até final de 2012 e para cerca de 1% do PIB em 2013, conforme o acordo estabelecido com as entidades internacionais. No entanto, do ponto de vista do cidadão, a despesa privada em medicamentos é também uma temática na ordem do dia. Poucos temas são tão controversos na área da política do medicamento como a introdução de genéricos no mercado de medicamentos, contudo, estes podem desempenhar um papel fundamental na optimização da afectação de recursos. São muitas as questões levantadas contra e a favor da qualidade, segurança e eficácia dos genéricos. Se os médicos, através da prescrição, são o factor decisivo para o aumento da quota de genéricos; os farmacêuticos enquanto dispensadores assumem um papel preponderante na sensibilização dos utentes para a sua aceitação e adesão à terapêutica. Objectivo: O presente estudo pretende estudar os conhecimentos e opiniões de médicos e farmacêuticos face aos medicamentos genéricos e as suas relações com a prescrição/dispensa de genéricos. Metodologia (Methodology): Foi enviado, via postal, um inquérito por questionário a uma amostra de médicos e farmacêuticos. Responderam 261 indivíduos, 158 médicos e 103 farmacêuticos. O inquérito foi validado por um painel de juízes e demonstrou uma boa consistência interna. Para efectuar a comparação entre as respostas dos diferentes grupos, recorreu-se ao teste t para amostras independentes. Resultados (Results): 75,9% dos inquiridos, considerou que o medicamento genérico é bioequivalente ao de referência mas apenas 58,7% disse acreditar que um fármaco genérico, no processo de preparação, oferece as mesmas garantias de qualidade. Verificou-se que os médicos que têm mais conhecimentos e opinião mais favorável sobre os genéricos prescrevem genéricos com mais frequência (p <0.001). Constatou-se que os farmacêuticos têm mais conhecimentos (p <0.008) sobre os medicamentos genéricos que os médicos e que manifestaram respostas mais positivas (p <0.001). Conclusões (Conclusions): Médicos e farmacêuticos acreditam que a despesa em medicamentos é um factor a ter em atenção no momento da prescrição/dispensa de medicamentos. Subsistem, no entanto, algumas crenças erróneas sobre a qualidade do medicamento genérico. Tal facto reforça a necessidade de políticas activas de promoção dos medicamentos genéricos

Coping Responses During the COVID-19 Pandemic: A Cross-Cultural Comparison of Russia, Kyrgyzstan, and Peru

Background. The COVID-19 pandemic has subjected people around the world to severe stress, evoking a variety of coping responses. Coping responses can be broadly classified into four strategies: 1) problem-focused coping; 2) emotion-focused coping; 3) socially supported coping; and 4) avoidance. While there is a wide variability of individual coping responses, to some extent they are also culturally specific. Objective. This study aimed to compare the differences in the prevalence and factor structure of coping responses during COVID-19 pandemic in three countries: Russia, Kyrgyzstan, and Peru. Design. The sample included 501 participants from Russia, 456 participants from Kyrgyzstan, and 354 participants from Peru. The mean age of participants was 28 years in Russia (SD = 13.5); 24 years in Kyrgyzstan (SD = 10.0); and 30 years in Peru (SD = 12.3). In Russia and Kyrgyzstan, coping strategies were assessed with an abbreviated Russian adaptation of the COPE (Coping Orientations to Problems Experienced) questionnaire. In Peru, coping responses were assessed using the Spanish version of the Brief COPE questionnaire. The average scores from fifteen COPE scales were used as the input data for linear modelling and factor analysis. Results. The coping scores varied substantially within each country. Differences between countries accounted for 17.7% of the total variability in religious coping; 15.8% in acceptance; 13.9% in mental disengagement; and less than 7% in the other coping strategies. No difference in the prevalence of coping responses was found between Russian and Kyrgyz participants after accounting for age and gender. In all three countries the coping responses were associated with the same four coping domains: problem-focused coping, socially supported coping, avoidance, and emotion-focused coping. Four factors explained up to 44% of the total variation in the COPE scores. Religious coping and mental disengagement were classified into different coping domains in the three countries. Conclusion. The results suggest that during the COVID-19 pandemic, people from different countries apply the full range of coping responses within the four universal coping strategies. Religious coping and mental disengagement differed the most across the countries, suggesting that some coping behaviors can take on different roles within the system of coping responses to stressful events. We attribute these differences to differing cultural and socioeconomic characteristics, and the different measures taken by governments in response to COVID-19

Microglial amyloid beta clearance is driven by PIEZO1 channels

Background Microglia are the endogenous immune cells of the brain and act as sensors of pathology to maintain brain homeostasis and eliminate potential threats. In Alzheimer's disease (AD), toxic amyloid beta (A beta) accumulates in the brain and forms stiff plaques. In late-onset AD accounting for 95% of all cases, this is thought to be due to reduced clearance of A beta. Human genome-wide association studies and animal models suggest that reduced clearance results from aberrant function of microglia. While the impact of neurochemical pathways on microglia had been broadly studied, mechanical receptors regulating microglial functions remain largely unexplored. Methods Here we showed that a mechanotransduction ion channel, PIEZO1, is expressed and functional in human and mouse microglia. We used a small molecule agonist, Yoda1, to study how activation of PIEZO1 affects AD-related functions in human induced pluripotent stem cell (iPSC)-derived microglia-like cells (iMGL) under controlled laboratory experiments. Cell survival, metabolism, phagocytosis and lysosomal activity were assessed using real-time functional assays. To evaluate the effect of activation of PIEZO1 in vivo, 5-month-old 5xFAD male mice were infused daily with Yoda1 for two weeks through intracranial cannulas. Microglial Iba1 expression and A beta pathology were quantified with immunohistochemistry and confocal microscopy. Published human and mouse AD datasets were used for in-depth analysis of PIEZO1 gene expression and related pathways in microglial subpopulations. Results We show that PIEZO1 orchestrates A beta clearance by enhancing microglial survival, phagocytosis, and lysosomal activity. A beta inhibited PIEZO1-mediated calcium transients, whereas activation of PIEZO1 with a selective agonist, Yoda1, improved microglial phagocytosis resulting in A beta clearance both in human and mouse models of AD. Moreover, PIEZO1 expression was associated with a unique microglial transcriptional phenotype in AD as indicated by assessment of cellular metabolism, and human and mouse single-cell datasets. Conclusion These results indicate that the compromised function of microglia in AD could be improved by controlled activation of PIEZO1 channels resulting in alleviated A beta burden. Pharmacological regulation of these mechanoreceptors in microglia could represent a novel therapeutic paradigm for AD.Peer reviewe

Обзор методов искусственного интеллекта, применяемых в анализе данных функциональной спектроскопии в ближнем инфракрасном диапазоне

Introduction. Recently, machine learning methods, which are core components of artificial intelligence, have gained popularity in analyzing neurophysiological data. Functional near-infrared spectroscopy (fNIRS) is actively used to study neurocognitive mechanisms. This technology for recording hemodynamic data has a number of advantages, including spatial resolution, non-invasiveness, and the feasibility to conduct studies in natural settings, which has made the technology popular among researchers. Theoretical justification. The analysis of fNIRS results relies on the sequence and selected methods for preliminary processing of raw data, as well as on the classification models employed. This review evaluates various preprocessing methods and examines the approaches to classifying fNIRS data. An essential aspect of preprocessing involves detecting and eliminating physiological artifacts from raw data, utilizing algorithms such as filtering, signal whitening, principal component analysis (PCA) and independent component analysis (ICA), short-channels removal. Methods such as wavelet filtering, spline interpolation, and Kalman filtering are employed to address motion artifacts. Discussion. The review aims to provide an in-depth exploration of machine learning methods, specifically recurrent neural networks (RNN) and convolutional neural networks (CNN), which have been used in various studies for analyzing fNIRS data. The review highlights that leveraging deep learning neural networks can streamline signal preprocessing while achieving higher accuracy compared to traditional approaches in processing neurocognitive data.Введение. В последнее время все большую популярность для анализа нейрофизиологических данных набирают методы машинного обучения, являющиеся составной частью методов искусственного интеллекта. Для изучения нейрокогнитивных механизмов в настоящее время активно применяют функциональную спектроскопию в ближнем инфракрасном диапазоне (фБИК-спектроскопию). Данная технология регистрации гемодинамических данных обладает рядом преимуществ, таких как точная локализация сигнала, неинвазивность, возможность проводить исследования в естественных условиях, что объясняет растущую популярность технологии среди исследователей. Теоретическое обоснование. Анализ результатов фБИК-спектроскопии зависит от последовательности и выбранных методов предварительной очистки и обработки исходных данных, а также от применяемых моделей для классификации полученных зависимостей. В настоящем обзоре рассмотрены различные методы предварительной обработки и детально проанализированы подходы к классификации данных фБИК-спектроскопии. При предварительной обработке сигнала важным моментом является удаление из исходных данных физиологических артефактов, для чего используются следующие алгоритмы: фильтрация, отбеливание сигнала, метод главных компонент (PCA) и метод независимых компонент (ICA), метод регистрации коротковолновых каналов (short-channel). Для удаления артефактов движения применяются такие методы, как вейвлет-фильтрация (wavelet), сплайн-интерполяция (spline interpolation), фильтрация Калмана. Обсуждение результатов. Обзор направлен на детальное рассмотрение методов машинного обучения, таких как рекуррентные нейронные сети (RNN) и сверточные нейронные сети (CNN), которые применялись в различных исследованиях для анализа данных фБИК-спектроскопии. В обзоре показано, что применение нейронных сетей глубокого обучения позволяет при анализе сигнала фБИК-спектроскопии сократить длительность предварительной обработки сигнала и при этом получить точность, превосходящую точность классических подходов в обработке нейрокогнитивных данных

DsTau: Study of tau neutrino production with 400 GeV protons from the CERN-SPS

In the DsTau experiment at the CERN SPS, an independent and direct way to measure tau neutrino production following high energy proton interactions was proposed. As the main source of tau neutrinos is a decay of Ds mesons, produced in proton-nucleus interactions, the project aims at measuring a differential cross section of this reaction. The experimental method is based on a use of high resolution emulsion detectors for effective registration of events with short lived particle decays. Here we present the motivation of the study, details of the experimental technique, and the first results of the analysis of the data collected during test runs, which prove feasibility of the full scale study of the process in future

Phenological shifts of abiotic events, producers and consumers across a continent

Ongoing climate change can shift organism phenology in ways that vary depending on species, habitats and climate factors studied. To probe for large-scale patterns in associated phenological change, we use 70,709 observations from six decades of systematic monitoring across the former Union of Soviet Socialist Republics. Among 110 phenological events related to plants, birds, insects, amphibians and fungi, we find a mosaic of change, defying simple predictions of earlier springs, later autumns and stronger changes at higher latitudes and elevations. Site mean temperature emerged as a strong predictor of local phenology, but the magnitude and direction of change varied with trophic level and the relative timing of an event. Beyond temperature-associated variation, we uncover high variation among both sites and years, with some sites being characterized by disproportionately long seasons and others by short ones. Our findings emphasize concerns regarding ecosystem integrity and highlight the difficulty of predicting climate change outcomes. The authors use systematic monitoring across the former USSR to investigate phenological changes across taxa. The long-term mean temperature of a site emerged as a strong predictor of phenological change, with further imprints of trophic level, event timing, site, year and biotic interactions.Peer reviewe