French Africa

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I-127 and Pb-207 Solid-state NMR spectroscopy and nuclear spin relaxation in lead iodide: A preliminary study

Lead iodide is a layered structure that experiences polytypism. The 2H polytype contains high rates of iodine vacancies but retains its stoichiometry. This characteristic feature makes it potentially useful for many practical applications. The hopping of iodine ions among vacancies is the dominant motion in the 2H polytype. We present a preliminary 127I and 207Pb solid-state nuclear magnetic resonance (NMR) spectroscopy and spin–lattice relaxation study of the 2H polytype below 400 K. We present reasonable models for the solid-state NMR results in terms of the effects of iodine hopping and lattice vibrations

Pb-207 chemical shielding in lead molybdate and lead chloride: The effects of temperature and lattice expansion

The analysis of heavy-metal solids with NMR spectroscopy provides a means of investigating the electronic environment through the dependence of the chemical shift on structure. We have investigated the relation of the 207Pb NMR isotropic chemical shift, span, and skew of a series of solid Pb(II) compounds to lattice parameters. Complementary relativistic spin−orbit density functional calculations on clusters such as PbI64- that model the local environment in the dihalides show a dependence of NMR properties on the local structure in good agreement with experimental results

Framework Mobility in the Metal−Organic Framework Crystal IRMOF-3: Evidence for Aromatic Ring and Amine

a b s t r a c t The framework motions in IRMOF-3 (Zn 4 O(BDC-NH 2 ) 3 ), where BDC-NH 2 represents 2-amino-1,4-ben zenedicarboxylate, have been investigated with 1 H NMR relaxation measurements. Isotopic enrichment of the 2-amino group with 15 N was critical in elucidating the lattice dynamics and enhancing spectral resolution. These results indicate a low energy process associated with rotation of the amino group, with an activation energy of 1.8 ± 0.6 kcal/mol, and full 180°rotation of the phenylene group in the BDC-NH 2 moiety with an activation energy of 5.0 ± 0.2 kcal/mol. A relatively low pre-exponential factor for amine rotation (1.3 Â 10 7 s À1 ) is tentatively associated with the need to break a hydrogen bond as the rate-limiting step. Both amine rotation and the aromatic ring flip occur at frequencies that provide an effective relaxation mechanism for the 99.6% natural abundance quadrupola

Incorporating prior knowledge improves detection of differences in bacterial growth rate

BACKGROUND: Robust statistical detection of differences in the bacterial growth rate can be challenging, particularly when dealing with small differences or noisy data. The Bayesian approach provides a consistent framework for inferring model parameters and comparing hypotheses. The method captures the full uncertainty of parameter values, whilst making effective use of prior knowledge about a given system to improve estimation. RESULTS: We demonstrated the application of Bayesian analysis to bacterial growth curve comparison. Following extensive testing of the method, the analysis was applied to the large dataset of bacterial responses which are freely available at the web-resource, ComBase. Detection was found to be improved by using prior knowledge from clusters of previously analysed experimental results at similar environmental conditions. A comparison was also made to a more traditional statistical testing method, the F-test, and Bayesian analysis was found to perform more conclusively and to be capable of attributing significance to more subtle differences in growth rate. CONCLUSIONS: We have demonstrated that by making use of existing experimental knowledge, it is possible to significantly improve detection of differences in bacterial growth rate

電極界面を利用したマイクロチップの高機能化

指導教員: 北森, 武

Improved Bevirimat resistance prediction by combination of structural and sequence-based classifiers

<p>Abstract</p> <p>Background</p> <p>Maturation inhibitors such as Bevirimat are a new class of antiretroviral drugs that hamper the cleavage of HIV-1 proteins into their functional active forms. They bind to these preproteins and inhibit their cleavage by the HIV-1 protease, resulting in non-functional virus particles. Nevertheless, there exist mutations in this region leading to resistance against Bevirimat. Highly specific and accurate tools to predict resistance to maturation inhibitors can help to identify patients, who might benefit from the usage of these new drugs.</p> <p>Results</p> <p>We tested several methods to improve Bevirimat resistance prediction in HIV-1. It turned out that combining structural and sequence-based information in classifier ensembles led to accurate and reliable predictions. Moreover, we were able to identify the most crucial regions for Bevirimat resistance computationally, which are in line with experimental results from other studies.</p> <p>Conclusions</p> <p>Our analysis demonstrated the use of machine learning techniques to predict HIV-1 resistance against maturation inhibitors such as Bevirimat. New maturation inhibitors are already under development and might enlarge the arsenal of antiretroviral drugs in the future. Thus, accurate prediction tools are very useful to enable a personalized therapy.</p

Prediction of Co-Receptor Usage of HIV-1 from Genotype

Human Immunodeficiency Virus 1 uses for entry into host cells a receptor (CD4) and one of two co-receptors (CCR5 or CXCR4). Recently, a new class of antiretroviral drugs has entered clinical practice that specifically bind to the co-receptor CCR5, and thus inhibit virus entry. Accurate prediction of the co-receptor used by the virus in the patient is important as it allows for personalized selection of effective drugs and prognosis of disease progression. We have investigated whether it is possible to predict co-receptor usage accurately by analyzing the amino acid sequence of the main determinant of co-receptor usage, i.e., the third variable loop V3 of the gp120 protein. We developed a two-level machine learning approach that in the first level considers two different properties important for protein-protein binding derived from structural models of V3 and V3 sequences. The second level combines the two predictions of the first level. The two-level method predicts usage of CXCR4 co-receptor for new V3 sequences within seconds, with an area under the ROC curve of 0.937±0.004. Moreover, it is relatively robust against insertions and deletions, which frequently occur in V3. The approach could help clinicians to find optimal personalized treatments, and it offers new insights into the molecular basis of co-receptor usage. For instance, it quantifies the importance for co-receptor usage of a pocket that probably is responsible for binding sulfated tyrosine