Modulation of three-dimensional structure and research of folding-analoges of AMB A 6 allergen of Ambrosia artemisiifolia

Amb A 6 allergen of Ambrosia artemisiifolia is a ragweed allergen (a principle cause of late summer hayfever in North America and Europe) (Hiller et al. 1998). The weed has recently become spreading as a neophyte in Europe, while climate change may also affect the growth of the plant and additionally may also influence pollen allergenicity (Kelish et al. 2014). In Ukraine, the number of diseases caused by this allergen has recently increases. The three-dimensional structure of Amb A 6 allergen is undescribed. The aim of our study was to modulate of three-dimensional structure and search of folding-analoges of AMB A 6 allergen of A. artemisiifolia

Hippocampal subfields and limbic white matter jointly predict learning rate in older adults

First published online: 04 December 2019Age-related memory impairments have been linked to differences in structural brain parameters, including cerebral white matter (WM) microstructure and hippocampal (HC) volume, but their combined influences are rarely investigated. In a population-based sample of 337 older participants aged 61-82 years (Mage = 69.66, SDage = 3.92 years), we modeled the independent and joint effects of limbic WM microstructure and HC subfield volumes on verbal learning. Participants completed a verbal learning task of recall over five repeated trials and underwent magnetic resonance imaging (MRI), including structural and diffusion scans. We segmented three HC subregions on high-resolution MRI data and sampled mean fractional anisotropy (FA) from bilateral limbic WM tracts identified via deterministic fiber tractography. Using structural equation modeling, we evaluated the associations between learning rate and latent factors representing FA sampled from limbic WM tracts, and HC subfield volumes, and their latent interaction. Results showed limbic WM and the interaction of HC and WM-but not HC volume alone-predicted verbal learning rates. Model decomposition revealed HC volume is only positively associated with learning rate in individuals with higher WM anisotropy. We conclude that the structural characteristics of limbic WM regions and HC volume jointly contribute to verbal learning in older adults

Interpersonal affect in groupwork: A comparative case study of two small groups with contrasting group dynamics outcomes

Teamwork capabilities are essential for 21st century life, with groupwork emerging as a fruitful context to develop these skills. Case studies that explore interpersonal affect dynamics in authentic higher education groupwork settings can highlight collaborative skills development needs. This comparative case-study traced the sociodynamic evolution of two groups of first-year university students to investigate the high collaborative variance outcomes of the two groups, which reported starkly contrasting group dynamics (negative and dysfunctional or positive and collaborative). Mixed-methods (video-recorded observations of five groupwork labs over one semester, and group interviews) provided interpersonal affect data as real-time visible behaviours, and the felt experiences and perceptions of participants. The study traced interpersonal affect dynamics in the natural fluctuation of not just task-focused (on-task), but also explicitly relational (off-task) interactions, which revealed their function in both task participation and group dynamics. Findings illustrate visible interpersonal affect behaviours that manifested and evolved over time as interactive patterns, and group dynamics outcomes. Fine-grained analysis of interactions unveiled interpersonal affect as a collective, evolving process, and the mechanism through which one group started and stayed highly positive and collaborative over the semester. The other group showed a tendency towards splitting to undertake tasks early, leading to low group-level interpersonal attentiveness, and over time, subgroups emerged through interactions both off-task and on-task. The study made visible the pervasive nature of interpersonal affect as enacted through seemingly inconsequential everyday behaviours that supported the relational and task-based needs of groupwork, and those behaviours which impeded collaboration

Magnetic Resonance Imaging Pilot Study of Intravenous Glyburide in Traumatic Brain Injury.

Pre-clinical studies of traumatic brain injury (TBI) show that glyburide reduces edema and hemorrhagic progression of contusions. We conducted a small Phase II, three-institution, randomized placebo-controlled trial of subjects with TBI to assess the safety and efficacy of intravenous (IV) glyburide. Twenty-eight subjects were randomized and underwent a 72-h infusion of IV glyburide or placebo, beginning within 10 h of trauma. Of the 28 subjects, 25 had Glasgow Coma Scale (GCS) scores of 6-10, and 14 had contusions. There were no differences in adverse events (AEs) or severe adverse events (ASEs) between groups. The magnetic resonance imaging (MRI) percent change at 72-168 h from screening/baseline was compared between the glyburide and placebo groups. Analysis of contusions (7 per group) showed that lesion volumes (hemorrhage plus edema) increased 1036% with placebo versus 136% with glyburide (p = 0.15), and that hemorrhage volumes increased 11.6% with placebo but decreased 29.6% with glyburide (p = 0.62). Three diffusion MRI measures of edema were quantified: mean diffusivity (MD), free water (FW), and tissue MD (MDt), corresponding to overall, extracellular, and intracellular water, respectively. The percent change with time for each measure was compared in lesions (n = 14) versus uninjured white matter (n = 24) in subjects receiving placebo (n = 20) or glyburide (n = 18). For placebo, the percent change in lesions for all three measures was significantly different compared with uninjured white matter (analysis of variance [ANOVA], p < 0.02), consistent with worsening of edema in untreated contusions. In contrast, for glyburide, the percent change in lesions for all three measures was not significantly different compared with uninjured white matter. Further study of IV glyburide in contusion TBI is warranted

High Current CD4+ T cell count predicts suboptimal adherence to antiretroviral therapy

Date of Acceptance: 30/09/2015 Funding: A.O.P. is financially supported by the Dutch AIDS Fonds (http://www.aidsfonds.nl/), grant nrs. 2011020 and 2012025. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.Peer reviewedPublisher PD

Estimation of Fiber Orientations Using Neighborhood Information

Data from diffusion magnetic resonance imaging (dMRI) can be used to reconstruct fiber tracts, for example, in muscle and white matter. Estimation of fiber orientations (FOs) is a crucial step in the reconstruction process and these estimates can be corrupted by noise. In this paper, a new method called Fiber Orientation Reconstruction using Neighborhood Information (FORNI) is described and shown to reduce the effects of noise and improve FO estimation performance by incorporating spatial consistency. FORNI uses a fixed tensor basis to model the diffusion weighted signals, which has the advantage of providing an explicit relationship between the basis vectors and the FOs. FO spatial coherence is encouraged using weighted l1-norm regularization terms, which contain the interaction of directional information between neighbor voxels. Data fidelity is encouraged using a squared error between the observed and reconstructed diffusion weighted signals. After appropriate weighting of these competing objectives, the resulting objective function is minimized using a block coordinate descent algorithm, and a straightforward parallelization strategy is used to speed up processing. Experiments were performed on a digital crossing phantom, ex vivo tongue dMRI data, and in vivo brain dMRI data for both qualitative and quantitative evaluation. The results demonstrate that FORNI improves the quality of FO estimation over other state of the art algorithms.Comment: Journal paper accepted in Medical Image Analysis. 35 pages and 16 figure

Probabilistic modeling of fatigue fracture using multiple cracking under thermal fatigue

Одним із фундаментальних чинників, що істотно впливає на міцність елементів конструкцій під час їхньої експлуатації, є термовтома матеріалів. Важливим завданням є прогнозування розвитку мережі поверхневих тріщин термовтоми, яка виникає на ранніх етапах експлуатації й значною мірою окреслює майбутню довговічність елемента конструкції. Аналітично розроблено метод інженерних розрахунків впливу теплової втоми на втомне руйнування матеріалу. Розвиток мікродефектів запропоновано моделювати на основі принципу механізмів зародження та розвитку тріщин з урахуванням в останньому залежності для коефіцієнтів інтенсивності напружень, отриманої в результаті розгляду подвійно періодичної задачі теорії пружності для нескінченної пластинки із подвійно періодичною мережею паралельних тріщин. Відстані між тріщинами визначено на основі ймовірнісних залежностей, отриманих за діаграмами термовтоми, а розміри дефектів розраховано за формулою Періса. Такий підхід дає змогу ефективно моделювати дію теплових напружень на втому й живучість матеріалів. Обчислено ймовірнісні залежності пошкодженості D, довжини мікротріщин і відстаней між ними від кількості термоциклів для сталі 25Х1М1Ф при розмаху внутрішніх температурних напружень S0 = 100...300 MПa.One of the fundamental factors that significantly affect the strength of structural elements during their operation is thermal fatigue of materials. It is important to predict the development of surface cracks network under thermal fatigue that emerges in the early stages of operation and largely determines the lifetime of structural elements. The microcracks growth rate depends on the thermomechanical properties of the material, its structure, temperature and force operation conditions (level, type, method of loading, other external influences), the relative position of microcracks and the distance between them and has a largely statistical nature. Modern design standards for the industry account for this uncertainty through empirical factor of safety. This makes the design conservative, not giving the proper ways to study and improve it. This approach makes it impossible to quantify the risks associated with the project design. So the critical task is the development and introduction into practice of design the probabilistic models, and the probabilistic methods on their basis, in addition to the existing standards. Analytical method is developed for engineering calculations of thermal fatigue effect on fatigue fracture of the material. The development of microdefects is proposed to be modeled on the basis of the mechanisms of nucleation and growth of cracks taking into consideration the dependency for stress intensity factors obtained as a result of the solution of doubly periodic problem of elasticity for an infinite plate with a doubly periodic network of parallel cracks. The distances between the cracks were determined based on probabilistic dependencies obtained from thermal fatigue diagrams and the size of defects was calculated by Paris law. This approach enables the efficient modeling of effects of thermal stresses on fatigue and durability of materials. The probabilistic dependencies of damage D, the average length of microcracks and the distances between them upon the number of thermal cycles were calculated for 25Cr1MoV steel under internal thermal stresses range S0 = 100 ... 300 MPa