47 research outputs found

    Simplified amino acid alphabets based on deviation of conditional probability from random background

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    The primitive data for deducing the Miyazawa-Jernigan contact energy or BLOSUM score matrix consists of pair frequency counts. Each amino acid corresponds to a conditional probability distribution. Based on the deviation of such conditional probability from random background, a scheme for reduction of amino acid alphabet is proposed. It is observed that evident discrepancy exists between reduced alphabets obtained from raw data of the Miyazawa-Jernigan's and BLOSUM's residue pair counts. Taking homologous sequence database SCOP40 as a test set, we detect homology with the obtained coarse-grained substitution matrices. It is verified that the reduced alphabets obtained well preserve information contained in the original 20-letter alphabet.Comment: 9 pages,3figure

    An Equation of State of a Carbon-Fibre Epoxy Composite under Shock Loading

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    An anisotropic equation of state (EOS) is proposed for the accurate extrapolation of high-pressure shock Hugoniot (anisotropic and isotropic) states to other thermodynamic (anisotropic and isotropic) states for a shocked carbon-fibre epoxy composite (CFC) of any symmetry. The proposed EOS, using a generalised decomposition of a stress tensor [Int. J. Plasticity \textbf{24}, 140 (2008)], represents a mathematical and physical generalisation of the Mie-Gr\"{u}neisen EOS for isotropic material and reduces to this equation in the limit of isotropy. Although a linear relation between the generalised anisotropic bulk shock velocity UsAU^{A}_{s} and particle velocity upu_{p} was adequate in the through-thickness orientation, damage softening process produces discontinuities both in value and slope in the UsAU^{A}_{s}-upu_{p} relation. Therefore, the two-wave structure (non-linear anisotropic and isotropic elastic waves) that accompanies damage softening process was proposed for describing CFC behaviour under shock loading. The linear relationship UsAU^{A}_{s}-upu_{p} over the range of measurements corresponding to non-linear anisotropic elastic wave shows a value of c0Ac^{A}_{0} (the intercept of the UsAU^{A}_{s}-upu_{p} curve) that is in the range between first and second generalised anisotropic bulk speed of sound [Eur. Phys. J. B \textbf{64}, 159 (2008)]. An analytical calculation showed that Hugoniot Stress Levels (HELs) in different directions for a CFC composite subject to the two-wave structure (non-linear anisotropic elastic and isotropic elastic waves) agree with experimental measurements at low and at high shock intensities. The results are presented, discussed and future studies are outlined.Comment: 12 pages, 9 figure

    Blended versus face-to-face: comparing student performance in a therapeutics class

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    Therapeutics is a very complex subject for every pharmacy student, since it requires the application of knowledge from several other disciplines. The study of therapeutics is often done in case-based learning in order to promote reflective thinking and give a scenario as real as possible. The objective of this study was to compare student performance between faceto-face (n = 54) and blended learning (n = 56) approaches to the teaching of therapeutics. They can confirm that there are statistically significant differences (p < 0.05) between the final exam scores from both groups, being that the b learning group achieved higher scores. Blended learning seems to be an effective way to teach therapeutics, following pre established teaching methods, and above all, does not negatively affect student performance. It also provides new learning environments and strategies, and promotes the development of new skills such as learning and collaborating online, which may be relevant in a networked knowledge society.info:eu-repo/semantics/publishedVersio

    Risk assessment in immunotoxicology. II. Relationships between immune and host resistance tests

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    We have reported on the design and content of a screening battery using a 'tier' approach for detecting potential immunotoxic compounds in mice (Luster et al., Fundam. Appl. Toxicol., 10, 2-19, 1988). The data base generated from these studies, which consists of over 50 selected compounds, has heen collected and analyzed in an attempt to improve future testing strategies and provide information to aid in developing future quantitative risk assessment for immunotoxicity. In a recent study it was shown that as few as two or three immune parameters were needed to predict immunotoxicants in mice (Luster et al., Fundam. Appl. Toxicol., 18, 200-210, 1992). In particular, enumeration of lymphocyte populations and quantitation of the T-dependent antibody response were particularly beneficial. Furthermore, commonly employed apical measures (e.g., leukocyte counts, lymphoid organ weights) were fairly insensitive. The present analyses focus on the use of this data base to develop statistical models that examine the qualitative and quantitative relationship(s) between the immune function and host resistance tests. The conclusion derived from these analyses are: (1) A good correlation exists between changes in the immune tests and altered host resistance in that there were no instances where host resistance was altered without affecting an immune test(s). However, in some instances immune changes occurred without corresponding changes in host resistance. (2) No single immune test could be identified which was fully predictive for altered host resistance, although most assays were relatively good indicators (i.e., >70%). Several others, such as proliferative response to lipopolysaccharide and leukocyte counts, were found to be relatively poor indicators for host resistance changes. (3) The ability to resist infectious agent challenge is dependent upon the degrees of immunosuppression and the quantity of infectious agent administered. (4) Logistic and standard regression modeling using one extensive chemical data set from the immunosuppressive agent, cyclophosphamide, indicated that most immune function-host resistance relationships followed linear rather than linear-quadratic (threshold-like) models. For most of the relationships this could not be confirmed using a large chemical data set and, thus, a more mechanistically based approach for modeling will need to be developed. (5) Using this limited data set, methods were developed for modeling the precise quantitative relationships between changes in selected immune tests and host resistance tests
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