Multiple chirality transfers in the enantioselective synthesis of 11-O-debenzoyltashironin. Chiroptical analysis of the key cascade

The mechanism of the cascade oxidative dearomatization-transannular Diels-Alder was investigated in the context of an asymmetric route to (−)-11-O-debenzoyltashironin. Although the oxidative dearomatization provides two acetal intermediates, the transannular Diels-Alder proceeds spontaneously from only one of the acetal isomers. Access to enantioenriched tetracyclic adduct was gained through the use of optically active allene.     

Matrix-assisted laser desorption/ionisation mass spectrometry imaging of lipids in rat brain tissue with integrated unsupervised and supervised multivariant statistical analysis

To date matrix-assisted laser desorption/ionisation mass spectrometry imaging (MALDI-MSI) analysis has been largely concerned with mapping the distribution of known analytes in tissues. An important step in the progression of its applications is the determination of unknown variants for metabolite and protein profiling in both clinical studies and studies of disease. Principal component analysis (PCA) is a statistical approach which can be used as a means of determining latent variables in multivariate data sets. In the work reported here, PCA, in both unsupervised and supervised modes, has been used to differentiate brain regions based on their lipid composition determined by MALDI-MSI. PCA has been shown to be useful in the determination of hidden variables between spectra taken from six regions of brain tissue. It is possible to identify ions of interest from the loadings plot which are likely to be more prominent in the different regions of the brain and thus differentiating between white and grey matter. It is also possible to distinguish between the grey Cerebellar Cortex and the Hippocampal formation, due to the grey Cerebellar Cortex having a positive PC2 and the Hippocampal formation having a negative PC2 score; this is only possible in supervised PCA with this data set because with unsupervised PCA the two regions overlap.     

Metal ion binding of photoactive poly-(arylene ethynylene) co-polymers

The metal ion binding properties of three photoactive poly-(arylene ethynylene) co-polymers with potentially complexing units have been described. Upon protonation or complexation, the intensity of the luminescence typical of these conjugated polymers is completely quenched, due to the extended electronic conjugation of the polymer backbones. In the case of the formation of complexes with Yb³⁺ and Er³⁺, one of the studied polymers gives rise to an efficient sensitization of their typical metal centred NIR emission. This feature is of particular interest for the preparation of new materials that are the subject of active research for their possible applications in optical imaging and in optical amplification for telecommunication purposes.     

Enantioselective Catalytic Addition of N-Acyl Radicals: In Batch and In Flow Organophotoredox α-Amination of Aldehydes

The organophotoredox catalytic enantioselective addition of N-acyl radicals to aldehydes, to afford enantioenriched N-acyl 1,2 aminoalcohols was studied. Under the best conditions, in batch, the product was isolated in up to 52 % yield and 85 % e.e., using a low cost and commercially available chiral imidazolidinone as organocatalyst. The reaction was then studied in flow, exploring different experimental setups and photoreactors. Although modest yields were obtained, the in-flow process afforded the product in higher productivities (up to 60 times higher) and improved space time yields (increased up to 113 times) compared to the batch reaction, with no loss of stereoselectivity.     

Regularized Quadratic Penalty Methods for Shape from Shading

Shape from shading (SFS) denotes the problem of reconstructing a 3D surface, starting from a single shaded image which represents the surface itself. Minimization techniques are commonly used for solving the SFS problem, where the objective function is a weighted combination of the brightness error, plus one or more terms aiming to obtain a valid solution. We present a regularized quadratic penalty method where quadratic penalization is used to adaptively adjust the smoothing weights, and regularization improves the robustness and reliability of the procedure. A nonmonotone Barzilai–Borwein method is employed to efficiently solve the arising subproblems. Numerical results are provided showing the reliability of the proposed approach.     

Variable selection in high‐dimensional regression: a nonparametric procedure for business failure prediction

Business failure prediction models are important in providing warning for preventing financial distress and giving stakeholders time to react in a timely manner to a crisis. The empirical approach to corporate distress analysis and forecasting has recently attracted new attention from financial institutions, academics, and practitioners. In fact, this field is as interesting today as it was in the 1930s, and over the last 80 years, a remarkable body of both theoretical and empirical studies on this topic has been published. Nevertheless, some issues are still under investigation, such as the selection of financial ratios to define business failure and the identification of an optimal subset of predictors. For this purpose, there exist a large number of methods that can be used, although their drawbacks are usually neglected in this context. Moreover, most variable selection procedures are based on some very strict assumptions (linearity and additivity) that make their application difficult in business failure prediction. This paper proposes to overcome these limits by selecting relevant variables using a nonparametric method named Rodeo that is consistent even when the aforementioned assumptions are not satisfied. We also compare Rodeo with two other variable selection methods (Lasso and Adaptive Lasso), and the empirical results demonstrate that our proposed procedure outperforms the others in terms of positive/negative predictive value and is able to capture the nonlinear effects of the selected variables. Copyright © 2017 John Wiley & Sons, Ltd.     

An Assessment of the Utility of Tissue Smears in Rapid Cancer Profiling with Desorption Electrospray Ionization Mass Spectrometry (DESI-MS)

Mass spectrometry imaging with desorption electrospray ionization mass spectrometry (DESI-MS) is used to characterize cancer from ex vivo slices of tissues. The process is time-consuming. The use of tissue smears for DESI-MS analysis has been proposed as it eliminates the time required to snap-freeze and section the tissue. To assess the utility of tissue smears for rapid cancer characterization, principal component analysis (PCA) was performed to evaluate the concordance between DESI-MS profiles of breast cancer from tissue slices and smears prepared on various surfaces. PCA suggested no statistical discrimination between DESI-MS profiles of tissue sections and tissue smears prepared on glass, polytetrafluoroethylene (PTFE), and porous PTFE. However, the abundances of cancer biomarker ions varied between sections and smears, with DESI-MS analysis of tissue sections yielding higher ion abundances of cancer biomarkers compared with smears. Coefficient of variance (CV) analysis suggests DESI-MS profiles from tissue smears are as reproducible as the ones from tissue sections. The limit of detection with smear samples from single pixel analysis is comparable to tissue sections that average the signal from a tissue area of 0.01 mm². The smears prepared on the PTFE surface possessed a higher degree of homogeneity compared with the smears prepared on the glass surface. This allowed single MS scans (~1 s) from random positions across the surface of the smear to be used in rapid cancer typing with good reproducibility, providing pathologic information for cancer typing at speeds suitable for clinical utility.

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Supramolecular Macrostructures of UPy‐Functionalized Carbon Nanotubes

Carbon nanotubes (CNTs) are considered excellent materials for the construction of flexible displays due to their nanoscale dimensions and unique physical and chemical properties. By using the recognition properties of 2‐ureido‐4[1H]pyrimidinone (UPy), a versatile and simple methodology was demonstrated for the construction of macroscopic structures based on UPy‐CNT/polymer composites prepared by a combination of two functionalization approaches: 1) covalent attachment of UPy pendants on the multiwalled CNT surface ( UPy‐MWCNTs ) and 2) directed self‐assembly of UPy‐MWCNTs within polymers bearing UPy pendants ( Bis‐UPy 1 and Bis‐UPy 2 ) by quadruple complementary DDAA–AADD hydrogen‐bond recognition (D=donor, A=acceptor).     

Electroanalytical Method for Determining Pyrogallol in Biodiesel in the Presence of a Surfactant

A sensitive, straightforward electroanalytical method for determining pyrogallol (PY) in biodiesel in the presence of a surfactant was developed using a voltammetric technique and screen‐printed electrodes. The influence of surfactant addition (sodium dodecyl sulfate (SDS), Triton X‐100 (TX‐100), cetyltrimethylammonium bromide (CTAB), tetrabutylammonium iodide (TBAI), tetrabutylammonium bromide (TBAB), or tetraethylammonium bromide (TEAB)) on the supporting electrolyte (0.04 mol L^?1 Britton? Robinson buffer) was evaluated. Only CTAB significantly increased the oxidation peak current. Under optimal conditions, the method demonstrated linearity over the concentration range of 0.8–9.0×10^?6 mol L^?1, with limits of detection and quantification of 4.9×10^?7 and 1.5×10^?6 mol L^?1, respectively. The results were satisfactory, relative to those obtained using high‐performance liquid chromatography (HPLC).