Intra- vs intermolecular photoinduced electron transfer reactions of a macrocyclic donor-acceptor dyad

The synthesis, structural characterization, and photophysical behavior of a 14-membered tetraazamacrocycle with pendant 4-dimethylaminobenzyl (DMAB) and 9-anthracenylmethyl groups is reported (L-3, 6-((9-anthracenylmethyl)amino)-trans-6,13-dimethyl-13-((4-dimethylaminobenzyl)amino)-1,4,8,11-tetraaza-cyclotetradecane). In its free base form, this compound displays rapid intramolecular photoinduced electron transfer (PET) quenching of the anthracene emission, with both the secondary amines and the DMAB group capable of acting as electron donors. When complexed with Zn(II), the characteristic fluorescence of the anthracene chromophore is restored as the former of these pathways is deactivated by coordination. Importantly, it is shown that the DMAB group, which remains uncoordinated and PET active, acts only very weakly to quench emission, by comparison to the behavior of a model Zn complex lacking the pendant DMAB group, [ZnL2](2+) (Chart 1). By contrast, Stern-Volmer analysis of intermolecular quenching of [ZnL2](2+) by N,N-dimethylaniline (DMA) has shown that this reaction is diffusion limited. Hence, the pivotal role of the bridge in influencing intramolecular PET is highlighted.

Variation talk: Articulating meaning in statistics

Little is known about the way that teachers articulate notions of variation in their own words. The study reported here was conducted with 17 prospective secondary math and science teachers enrolled in a preservice teacher education course which engaged them in statistical inquiry of testing data. This qualitative study examines how these preservice teachers articulated notions of variation as they compared two distributions. Although the teachers made use of tandard statistical language, they also expressed rich views of variation through nonstandard terminology. This paper details the statistical language used by the rospective teachers, categorizing both standard and nonstandard expressions. Their nonstandard language revealed strong relationships between expressions of variation and expressions of distribution. Implications and the benefits of nonstandard language in statistics are outlined.

Towards structure-property-function relationships for eumelanin

We discuss recent progress towards the establishment of important structure-property-function relationships in eumelanins-key functional bio-macromolecular systems responsible for photoprotection and immune response in humans, and implicated in the development of melanoma skin cancer. We focus on the link between eumelanin's secondary structure and optical properties such as broad band UV-visible absorption and strong non-radiative relaxation; both key features of the photo-protective function. We emphasise the insights gained through a holistic approach combining optical spectroscopy with first principles quantum chemical calculations, and advance the hypothesis that the robust functionality characteristic of eumelanin is related to extreme chemical and structural disorder at the secondary level. This inherent disorder is a low cost natural resource, and it is interesting to speculate as to whether it may play a role in other functional bio-macromolecular systems.

Predicting residue-wise contact orders in proteins by support vector regression

Background: The residue-wise contact order (RWCO) describes the sequence separations between the residues of interest and its contacting residues in a protein sequence. It is a new kind of one-dimensional protein structure that represents the extent of long-range contacts and is considered as a generalization of contact order. Together with secondary structure, accessible surface area, the B factor, and contact number, RWCO provides comprehensive and indispensable important information to reconstructing the protein three-dimensional structure from a set of one-dimensional structural properties. Accurately predicting RWCO values could have many important applications in protein three-dimensional structure prediction and protein folding rate prediction, and give deep insights into protein sequence-structure relationships. Results: We developed a novel approach to predict residue-wise contact order values in proteins based on support vector regression (SVR), starting from primary amino acid sequences. We explored seven different sequence encoding schemes to examine their effects on the prediction performance, including local sequence in the form of PSI-BLAST profiles, local sequence plus amino acid composition, local sequence plus molecular weight, local sequence plus secondary structure predicted by PSIPRED, local sequence plus molecular weight and amino acid composition, local sequence plus molecular weight and predicted secondary structure, and local sequence plus molecular weight, amino acid composition and predicted secondary structure. When using local sequences with multiple sequence alignments in the form of PSI-BLAST profiles, we could predict the RWCO distribution with a Pearson correlation coefficient (CC) between the predicted and observed RWCO values of 0.55, and root mean square error (RMSE) of 0.82, based on a well-defined dataset with 680 protein sequences. Moreover, by incorporating global features such as molecular weight and amino acid composition we could further improve the prediction performance with the CC to 0.57 and an RMSE of 0.79. In addition, combining the predicted secondary structure by PSIPRED was found to significantly improve the prediction performance and could yield the best prediction accuracy with a CC of 0.60 and RMSE of 0.78, which provided at least comparable performance compared with the other existing methods. Conclusion: The SVR method shows a prediction performance competitive with or at least comparable to the previously developed linear regression-based methods for predicting RWCO values. In contrast to support vector classification (SVC), SVR is very good at estimating the raw value profiles of the samples. The successful application of the SVR approach in this study reinforces the fact that support vector regression is a powerful tool in extracting the protein sequence-structure relationship and in estimating the protein structural profiles from amino acid sequences.

Simulation of a complete reflected shock tunnel showing a vortex mechanism for flow contamination

Simulations of a complete reflected shock tunnel facility have been performed with the aim of providing a better understanding of the flow through these facilities. In particular, the analysis is focused on the premature contamination of the test flow with the driver gas. The axisymmetric simulations model the full geometry of the shock tunnel and incorporate an iris-based model of the primary diaphragm rupture mechanics, an ideal secondary diaphragm and account for turbulence in the shock tube boundary layer with the Baldwin-Lomax eddy viscosity model. Two operating conditions were examined: one resulting in an over-tailored mode of operation and the other resulting in approximately tailored operation. The accuracy of the simulations is assessed through comparison with experimental measurements of static pressure, pitot pressure and stagnation temperature. It is shown that the widely-accepted driver gas contamination mechanism in which driver gas 'jets' along the walls through action of the bifurcated foot of the reflected shock, does not directly transport the driver gas to the nozzle at these conditions. Instead, driver gas laden vortices are generated by the bifurcated reflected shock. These vortices prevent jetting of the driver gas along the walls and convect driver gas away from the shock tube wall and downstream into the nozzle. Additional vorticity generated by the interaction of the reflected shock and the contact surface enhances the process in the over-tailored case. However, the basic mechanism appears to operate in a similar way for both the over-tailored and the approximately tailored conditions.

Diagnosis of canine bleeding disorders

Canine bleeding disorders arise due to a multitude of conditions and require detailed clinical and laboratory investigation. A productive diagnostic approach depends on a thorough patient history, physical examination, haemostatic screening tests and an array of specific diagnostic tests. Patient history is necessary to assist determination of the onset, severity and possible aetiologies of a bleeding disorder. Similarly, a complete physical examination should ideally allow differentiation between disorders of primary and secondary haemostasis. Following this distinction, a variety of laboratory tests are indicated to further define the nature of the bleeding episode. These tests may be broadly categorised as screening tests of primary haemostasis, secondary haemostasis and fibrinolysis, and specific tests directed at identifying particular disorders. Appropriate utilisation of these tests and interpretation of their results in conjunction with patient signalment, history and clinical signs affords the greatest chance of a successful diagnosis.

GFAP analysis in aluminium chloride-treated rat brain regions

The neurotoxicity of aluminium chloride was assessed in maleWistar albino rats. Rats were treated with aluminium chloride dissolved in distilled water at a dose of 300 mg/kg body weight daily by oral gavage (1 ml) for 45 days. Controls were treated with distilled water only. Animals were sacrificed and different brain regions were dissected. GFAP analysis was carried out by Western blotting using mouse anti-GFAP monoclonal antibody (Pharmingen: 60311D) at 1:1000. Blots were developed with HRP-linked goat anti-mouse secondary antibody and quantified by densitometry.