391 research outputs found
Performance related technique factors in Olympic sprint kayaking
A sprint kayaking specific deterministic model was used to identify key performance related technique factors using data from 12 international-level kayakers. There was large variability in the strength of the between-factor relationships across the group. The pull phase was split into 3 components with the 1st phase contributing the most to increases in boat velocity and the 3rd phase causing a decrease in velocity. The propulsive impulse had the largest influence on velocity, but the magnitude of the impact was moderated by blade slip. Large propulsive impulses in the 3rd phase of the pull were associated with larger decreases in velocity. The results show that the model can be used to identify key technique factors on an individual level, although the use of the model should be confirmed on additional kayakers before being used in an applied setting by practitioners
Elderly musculoskeletal disease burden in Karachi, Pakistan: Associations and implications for developing countries
Objective: The global rise in the older population has increased the rates of osteoporosis and osteoarthritis, conditions that impact mobility and functionality. There is limited data on musculoskeletal disease in older populations residing in developing countries.Methods: A community-based study using multistage cluster random sampling of older individuals was conducted in Karachi. Predefined criteria were used for osteoporosis and osteoarthritis. Gait assessment was performed.Results: More than half of the participants were females and 53% reported illiteracy. Around 30% had osteoporosis and two-thirds had osteoarthritis. Multivariate analysis showed associations of female sex, Pashtun ethnicity, illiteracy, and hypertension with the combined variable of osteoporosis and osteoarthritis.Conclusions: The prevalence of osteoarthritis was higher than in other regional studies. Presence of both osteoporosis and osteoarthritis increased the risk of certain geriatric syndromes. High rates of musculoskeletal morbidity are seen in the elderly in Pakistan. Measures at a health-system level are required for better outcomes in older adults
Construction and analysis of causally dynamic hybrid bond graphs
Engineering systems are frequently abstracted to models with discontinuous behaviour (such as a switch or contact),
and a hybrid model is one which contains continuous and discontinuous behaviours. Bond graphs are an established
physical modelling method, but there are several methods for constructing switched or âhybridâ bond graphs, developed
for either qualitative âstructuralâ analysis or efficient numerical simulation of engineering systems. This article proposes a
general hybrid bond graph suitable for both. The controlled junction is adopted as an intuitive way of modelling a discontinuity in the model structure. This element gives rise to âdynamic causalityâ that is facilitated by a new bond graph notation. From this model, the junction structure and state equations are derived and compared to those obtained by
existing methods. The proposed model includes all possible modes of operation and can be represented by a single set
of equations. The controlled junctions manifest as Boolean variables in the matrices of coefficients. The method is more
compact and intuitive than existing methods and dispenses with the need to derive various modes of operation from a
given reference representation. Hence, a method has been developed, which can reach common usage and form a platform for further study
RNA secondary structure prediction from multi-aligned sequences
It has been well accepted that the RNA secondary structures of most
functional non-coding RNAs (ncRNAs) are closely related to their functions and
are conserved during evolution. Hence, prediction of conserved secondary
structures from evolutionarily related sequences is one important task in RNA
bioinformatics; the methods are useful not only to further functional analyses
of ncRNAs but also to improve the accuracy of secondary structure predictions
and to find novel functional RNAs from the genome. In this review, I focus on
common secondary structure prediction from a given aligned RNA sequence, in
which one secondary structure whose length is equal to that of the input
alignment is predicted. I systematically review and classify existing tools and
algorithms for the problem, by utilizing the information employed in the tools
and by adopting a unified viewpoint based on maximum expected gain (MEG)
estimators. I believe that this classification will allow a deeper
understanding of each tool and provide users with useful information for
selecting tools for common secondary structure predictions.Comment: A preprint of an invited review manuscript that will be published in
a chapter of the book `Methods in Molecular Biology'. Note that this version
of the manuscript may differ from the published versio
The holographic principle
There is strong evidence that the area of any surface limits the information
content of adjacent spacetime regions, at 10^(69) bits per square meter. We
review the developments that have led to the recognition of this entropy bound,
placing special emphasis on the quantum properties of black holes. The
construction of light-sheets, which associate relevant spacetime regions to any
given surface, is discussed in detail. We explain how the bound is tested and
demonstrate its validity in a wide range of examples.
A universal relation between geometry and information is thus uncovered. It
has yet to be explained. The holographic principle asserts that its origin must
lie in the number of fundamental degrees of freedom involved in a unified
description of spacetime and matter. It must be manifest in an underlying
quantum theory of gravity. We survey some successes and challenges in
implementing the holographic principle.Comment: 52 pages, 10 figures, invited review for Rev. Mod. Phys; v2:
reference adde
Glycosaminoglycans and Sialylated Glycans Sequentially Facilitate Merkel Cell Polyomavirus Infectious Entry
Merkel cell polyomavirus (MCV or MCPyV) appears to be a causal factor in the development of Merkel cell carcinoma, a rare but highly lethal form of skin cancer. Although recent reports indicate that MCV virions are commonly shed from apparently healthy human skin, the precise cellular tropism of the virus in healthy subjects remains unclear. To begin to explore this question, we set out to identify the cellular receptors or co-receptors required for the infectious entry of MCV. Although several previously studied polyomavirus species have been shown to bind to cell surface sialic acid residues associated with glycolipids or glycoproteins, we found that sialylated glycans are not required for initial attachment of MCV virions to cultured human cell lines. Instead, glycosaminoglycans (GAGs), such as heparan sulfate (HS) and chondroitin sulfate (CS), serve as initial attachment receptors during the MCV infectious entry process. Using cell lines deficient in GAG biosynthesis, we found that N-sulfated and/or 6-O-sulfated forms of HS mediate infectious entry of MCV reporter vectors, while CS appears to be dispensable. Intriguingly, although cell lines deficient in sialylated glycans readily bind MCV capsids, the cells are highly resistant to MCV reporter vector-mediated gene transduction. This suggests that sialylated glycans play a post-attachment role in the infectious entry process. Results observed using MCV reporter vectors were confirmed using a novel system for infectious propagation of native MCV virions. Taken together, the findings suggest a model in which MCV infectious entry occurs via initial cell binding mediated primarily by HS, followed by secondary interactions with a sialylated entry co-factor. The study should facilitate the development of inhibitors of MCV infection and help shed light on the infectious entry pathways and cellular tropism of the virus
Study on Growth Kinetics of CdSe Nanocrystals with a New Model
A model which involves both bulk diffusion process and surface reaction process has been developed for describing the growth behaviour of nanoparticles. When the model is employed, hypothesising that either of the processes alone dominates the overall growth process is unnecessary. Conversely, the relative magnitude of contributions from both processes could be obtained from the model. Using this model in our system, the growth process of CdSe QDs demonstrated two different growth stages. During the first stage, the growth of CdSe QDs was dominated by bulk diffusion, whereas, neither the bulk diffusion process nor the surface reaction process could be neglected during the later stage. At last, we successfully modelled the Ostwald ripening of CdSe QDs with LSW theories
The stellar halo of the Galaxy
Stellar halos may hold some of the best preserved fossils of the formation
history of galaxies. They are a natural product of the merging processes that
probably take place during the assembly of a galaxy, and hence may well be the
most ubiquitous component of galaxies, independently of their Hubble type. This
review focuses on our current understanding of the spatial structure, the
kinematics and chemistry of halo stars in the Milky Way. In recent years, we
have experienced a change in paradigm thanks to the discovery of large amounts
of substructure, especially in the outer halo. I discuss the implications of
the currently available observational constraints and fold them into several
possible formation scenarios. Unraveling the formation of the Galactic halo
will be possible in the near future through a combination of large wide field
photometric and spectroscopic surveys, and especially in the era of Gaia.Comment: 46 pages, 16 figures. References updated and some minor changes.
Full-resolution version available at
http://www.astro.rug.nl/~ahelmi/stellar-halo-review.pd
Quantitative and Qualitative Analysis of the Antifungal Activity of Allicin Alone and in Combination with Antifungal Drugs
The antifungal activity of allicin and its synergistic effects with the antifungal agents flucytosine and amphotericin B (AmB) were investigated in Candida albicans (C. albicans). C. albicans was treated with different conditions of compounds alone and in combination (allicin, AmB, flucytosine, allicin + AmB, allicin + flucytosine, allicin + AmB + flucytosine). After a 24-hour treatment, cells were examined by scanning electron microscopy (SEM) and atomic force microscopy (AFM) to measure morphological and biophysical properties associated with cell death. The clearing assay was conducted to confirm the effects of allicin. The viability of C. albicans treated by allicin alone or with one antifungal drug (AmB, flucytosine) in addition was more than 40% after a 24-hr treatment, but the viability of groups treated with combinations of more than two drugs was less than 32%. When the cells were treated with allicin alone or one type of drug, the morphology of the cells did not change noticeably, but when cells were treated with combinations of drugs, there were noticeable morphological changes. In particular, cells treated with allicin + AmB had significant membrane damage (burst or collapsed membranes). Classification of cells according to their cell death phase (CDP) allowed us to determine the relationship between cell viability and treatment conditions in detail. The adhesive force was decreased by the treatment in all groups compare to the control. Cells treated with AmB + allicin had a greater adhesive force than cells treated with AmB alone because of the secretion of molecules due to collapsed membranes. All cells treated with allicin or drugs were softer than the control cells. These results suggest that allicin can reduce MIC of AmB while keeping the same efficacy
Accurate and efficient gp120 V3 loop structure based models for the determination of HIV-1 co-receptor usage
<p>Abstract</p> <p>Background</p> <p>HIV-1 targets human cells expressing both the CD4 receptor, which binds the viral envelope glycoprotein gp120, as well as either the CCR5 (R5) or CXCR4 (X4) co-receptors, which interact primarily with the third hypervariable loop (V3 loop) of gp120. Determination of HIV-1 affinity for either the R5 or X4 co-receptor on host cells facilitates the inclusion of co-receptor antagonists as a part of patient treatment strategies. A dataset of 1193 distinct gp120 V3 loop peptide sequences (989 R5-utilizing, 204 X4-capable) is utilized to train predictive classifiers based on implementations of random forest, support vector machine, boosted decision tree, and neural network machine learning algorithms. An <it>in silico </it>mutagenesis procedure employing multibody statistical potentials, computational geometry, and threading of variant V3 sequences onto an experimental structure, is used to generate a feature vector representation for each variant whose components measure environmental perturbations at corresponding structural positions.</p> <p>Results</p> <p>Classifier performance is evaluated based on stratified 10-fold cross-validation, stratified dataset splits (2/3 training, 1/3 validation), and leave-one-out cross-validation. Best reported values of sensitivity (85%), specificity (100%), and precision (98%) for predicting X4-capable HIV-1 virus, overall accuracy (97%), Matthew's correlation coefficient (89%), balanced error rate (0.08), and ROC area (0.97) all reach critical thresholds, suggesting that the models outperform six other state-of-the-art methods and come closer to competing with phenotype assays.</p> <p>Conclusions</p> <p>The trained classifiers provide instantaneous and reliable predictions regarding HIV-1 co-receptor usage, requiring only translated V3 loop genotypes as input. Furthermore, the novelty of these computational mutagenesis based predictor attributes distinguishes the models as orthogonal and complementary to previous methods that utilize sequence, structure, and/or evolutionary information. The classifiers are available online at <url>http://proteins.gmu.edu/automute</url>.</p
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