Large‐depth‐of‐field full‐field optical angiography

A large‐depth‐of‐field full‐field optical angiography (LD‐FFOA) method is developed to expand the depth‐of‐field (DOF) using a contrast pyramid fusion algorithm (CPFA). The absorption intensity fluctuation modulation effect is utilized to obtain full‐field optical angiography (FFOA) images at different focus positions. The CPFA is used to process these FFOA images with different focuses. By selecting high‐contrast areas, the CPFA can highlight the characteristics and details of blood vessels to obtain LD‐FFOA images. In the optimal case of the proposed method, the DOF for FFOA is more than tripled using 10 differently focused FFOA images. Both the phantom and animal experimental results show that the LD‐FFOA resolves FFOA defocusing issues induced by surface and thickness inhomogeneities in biological samples. The proposed method can be potentially applied to practical biological experiments.      

Effect of one D‐Leu residue on right‐handed helical ‐L‐Leu‐Aib‐ peptides in the crystal state

Four diastereomeric‐Leu‐Leu‐Aib‐Leu‐Leu‐Aib‐peptides, Boc‐D ‐Leu‐L ‐Leu‐Aib‐L ‐Leu‐L ‐Leu‐Aib‐OMe (1), Boc‐L ‐Leu‐D ‐Leu‐Aib‐L ‐Leu‐L ‐Leu‐Aib‐OMe (2), Boc‐L ‐Leu‐L ‐Leu‐Aib‐D ‐Leu‐L ‐Leu‐Aib‐OMe (3), and Boc‐L ‐Leu‐L ‐Leu‐Aib‐L ‐Leu‐D ‐Leu‐Aib‐OMe (4), were synthesized. The crystals of the four hexapeptides were characterized by X‐ray crystallographic analysis. Two diastereomeric hexapeptides 1 and 2 having D ‐Leu(1) or D ‐Leu(2) were folded into right‐handed (P) 3 ₁₀ ‐helical structures, while peptide 3 having D ‐Leu(4) was folded into a turn structure nucleated by type III′ and I$' \bf{\beta}$ ‐turns, and peptide 4 having D ‐Leu(5) was folded into a left‐handed (M) 3 ₁₀ ‐helical structure. Copyright © 2011 European Peptide Society and John Wiley & Sons, Ltd.     

Efficient approximate k‐fold and leave‐one‐out cross‐validation for ridge regression

In model building and model evaluation, cross‐validation is a frequently used resampling method. Unfortunately, this method can be quite time consuming. In this article, we discuss an approximation method that is much faster and can be used in generalized linear models and Cox’ proportional hazards model with a ridge penalty term. Our approximation method is based on a Taylor expansion around the estimate of the full model. In this way, all cross‐validated estimates are approximated without refitting the model. The tuning parameter can now be chosen based on these approximations and can be optimized in less time. The method is most accurate when approximating leave‐one‐out cross‐validation results for large data sets which is originally the most computationally demanding situation. In order to demonstrate the method's performance, it will be applied to several microarray data sets. An R package penalized, which implements the method, is available on CRAN.     

The C‐terminal extension of human RTEL1, mutated in Hoyeraal‐Hreidarsson syndrome,contains Harmonin‐N‐like domains

Several studies have recently shown that germline mutations in RTEL1, an essential DNA helicase involved in telomere regulation and DNA repair, cause Hoyeraal‐Hreidarsson syndrome (HHS), a severe form of dyskeratosis congenita. Using original new softwares, facilitating the delineation of the different domains of the protein and the identification of remote relationships for orphan domains, we outline here that the C‐terminal extension of RTEL1, downstream of its catalytic domain and including several HHS‐associated mutations, contains a yet unidentified tandem of harmonin‐N‐like domains, which may serve as a hub for partner interaction. This finding highlights the potential critical role of this region for the function of RTEL1 and gives insights into the impact that the identified mutations would have on the structure and function of these domains. Proteins 2014; 82:897–903. © 2013 Wiley Periodicals, Inc.     

Channel‐like crystal structure of cinchoninium L‐O‐phosphoserine salt dihydrate

Studies on the interactions between L ‐O‐ phosphoserine, as one of the simplest fragments of membrane components, and the Cinchona alkaloid cinchonine, in the crystalline state were performed. Cinchoninium L ‐O‐phosposerine salt dihydrate (PhSerCin) crystallizes in a monoclinic crystal system, space group P2₁, with unit cell parameters: a = 8.45400(10) Å, b = 7.17100(10) Å, c = 20.7760(4) Å, α = 90°, β = 98.7830(10)°, γ = 90°, Z = 2. The asymmetric unit consists of the cinchoninium cation linked by hydrogen bonds to a phosphoserine anion and two water molecules. Intermolecular hydrogen bonds connecting phosphoserine anions via water molecules form chains extended along the b axis. Two such chains symmetrically related by twofold screw axis create a “channel.” On both sides of this channel cinchonine cations are attached by hydrogen bonds in which the atoms N1, O12, and water molecules participate. This arrangement mimics the system of bilayer biological membrane. Chirality 2010. © 2009 Wiley‐Liss, Inc.     

A note on pseudo‐observations and left‐truncation

Pseudo‐observations have been introduced as a way to perform regression analysis of a mean value parameter related to a right‐censored time‐to‐event outcome, such as the survival probability or the restricted mean survival time. Since the introduction of the approach there have been several extensions from the original setting. However, the proper definition and performance of pseudo‐observations under left‐truncation has not yet been addressed. Here, we look at two types of pseudo‐observations under right‐censoring and left‐truncation. We explored their performance in a simulation study and applied them to data on diabetes patients with left‐truncation.     

Comparison of l‐tyrosine containing dipeptides reveals maximum ATP availability for l‐prolyl‐l‐tyrosine in CHO cells

Increasing markets for biopharmaceuticals, including monoclonal antibodies, have triggered a permanent need for bioprocess optimization. Biochemical engineering approaches often include the optimization of basal and feed media to improve productivities of Chinese hamster ovary (CHO) cell cultures. Often, l ‐tyrosine is added as dipeptide to deal with its poor solubility at neutral pH. Showcasing IgG1 production with CHO cells, we investigated the supplementation of three l ‐tyrosine (TYR, Y) containing dipeptides: glycyl‐l ‐tyrosine (GY), l ‐tyrosyl‐l ‐valine (YV), and l ‐prolyl‐l ‐tyrosine (PY). While GY and YV led to almost no phenotypic and metabolic differences compared to reference samples, PY significantly amplified TYR uptake thus maximizing related catabolic activity. Consequently, ATP formation was roughly four times higher upon PY application than in reference samples.     

Determination of manganese‐ and manganese‐containing fungicides with lucigenin–Tween‐20‐enhanced chemiluminescence detection

A flow‐injection (FI) method is reported for the determination of Mn(II), maneb and mancozeb fungicides based on the catalytic effect of Mn(II) on the oxidation of lucigenin and dissolved oxygen in a basic solution. The Tween‐20 surfactant has been reported for first time to enhance lucigenin chemiluminescence (CL) intensity in the presence of Mn(II) (53%) and maneb and mancozeb (89%). The calibration graphs were linear in the concentration range of 0.001–1.5 mg L^–1 (R² = 0.9982 (n = 11) with a limit of detection (S/N = 3) of 0.1 µg L^–1 for Mn(II) and 0.01–3.0 mg L^–1 [R² = 0.9989 and R² = 0.9992 (n = 6)] with a limit of detection (S/N =3) of 1.0 µg L^–1 for maneb and mancozeb respectively. Injection throughputs of 90 and 120 h^–1 for Mn(II) and maneb and mancozeb respectively, and relative standard deviations of 1.0–3.4% were obtained in the concentration range studied. The experimental variables, e.g., reagents concentrations, flow rates, sample volume, and photomultiplier tube voltage, were optimized and potential interferences were investigated. The analysis of Mn(II) in river water reference materials (SLRS‐4 and SLRS‐5) showed good agreement with the certified values incorporating an on‐line 8‐hydroxyquinoline chelating column in the manifold for removing interfering metal ions. Recoveries for maneb and mancozeb were in the range of 92 ± 5 to 104 ± 3% and 91 ± 2 to 100 ± 4% (n = 3) respectively. The effect of 30 other pesticides (fungicides, herbicides and insecticides) was also examined in the lucigenin–Tween‐20 CL system. Copyright © 2015 John Wiley & Sons, Ltd.     

Comparison analysis of primary ligand‐binding sites in seven‐helix membrane proteins

Seven‐helix transmembrane proteins, including the G‐protein‐coupled receptors (GPCRs), mediate a broad range of fundamental cellular activities through binding to a wide range of ligands. Understanding the structural basis for the ligand‐binding selectivity of these proteins is of significance to their structure‐based drug design. Comparison analysis of proteins' ligand‐binding sites provides a useful way to study their structure‐activity relationships. Various computational methods have been developed for the binding‐site comparison of soluble proteins. In this work, we applied this approach to the analysis of the primary ligand‐binding sites of 92 seven‐helix transmembrane proteins. Results of the studies confirmed that the binding site of bacterial rhodopsins is indeed different from all GPCRs. In the latter group, further comparison of the binding sites indicated a group of residues that could be responsible for ligand‐binding selectivity and important for structure‐based drug design. Furthermore, unexpected binding‐site dissimilarities were observed among adrenergic and adenosine receptors, suggesting that the percentage of the overall sequence identity between a target protein and a template protein alone is not sufficient for selecting the best template for homology modeling of seven‐helix membrane proteins. These results provided novel insight into the structural basis of ligand‐binding selectivity of seven‐helix membrane proteins and are of practical use to the computational modeling of these proteins. © 2010 Wiley Periodicals, Inc. Biopolymers 95: 31–38, 2011.     

The Use of Two‐Way Linear Mixed Models in Multitreatment Meta‐Analysis

Summary Meta‐analysis summarizes the results of a series of trials. When more than two treatments are included in the trials and when the set of treatments tested differs between trials, the combination of results across trials requires some care. Several methods have been proposed for this purpose, which feature under different labels, such as network meta‐analysis or mixed treatment comparisons. Two types of linear mixed model can be used for meta‐analysis. The one expresses the expected outcome of treatments as a contrast to a baseline treatment. The other uses a classical two‐way linear predictor with main effects for treatment and trial. In this article, we compare both types of model and explore under which conditions they give equivalent results. We illustrate practical advantages of the two‐way model using two published datasets. In particular, it is shown that between‐trial heterogeneity as well as inconsistency between different types of trial is straightforward to account for.     

A stage‐wise approach for the analysis of multi‐environment trials

Plant breeders and variety testing agencies routinely test candidate genotypes (crop varieties, lines, test hybrids) in multiple environments. Such multi‐environment trials can be efficiently analysed by mixed models. A single‐stage analysis models the entire observed data at the level of individual plots. This kind of analysis is usually considered as the gold standard. In practice, however, it is more convenient to use a two‐stage approach, in which experiments are first analysed per environment, yielding adjusted means per genotype, which are then summarised across environments in the second stage. Stage‐wise approaches suggested so far are approximate in that they cannot fully reproduce a single‐stage analysis, except in very simple cases, because the variance–covariance matrix of adjusted means from individual environments needs to be approximated by a diagonal matrix. This paper proposes a fully efficient stage‐wise method, which carries forward the full variance–covariance matrix of adjusted means from the individual environments to the analysis across the series of trials. Provided the variance components are known, this method can fully reproduce the results of a single‐stage analysis. Computations are made efficient by a diagonalisation of the residual variance–covariance matrix, which necessitates a corresponding linear transformation of both the first‐stage estimates (e.g. adjusted means and regression slopes for plot covariates) and the corresponding design matrices for fixed and random effects. We also exemplify the extension of the general approach to a three‐stage analysis. The method is illustrated using two datasets, one real and the other simulated. The proposed approach has close connections with meta‐analysis, where environments correspond to centres and genotypes to medical treatments. We therefore compare our theoretical results with recently published results from a meta‐analysis.     

2‐Picoline‐borane: A non‐toxic reducing agent for oligosaccharide labeling by reductive amination

Analysis of N‐glycans is often performed by LC coupled to fluorescence detection. The N‐glycans are usually labeled by reductive amination with a fluorophore containing a primary amine to allow fluorescence detection. Moreover, many of the commonly applied labels also allow improved mass spectrometric detection of oligosaccharides. For reductive amination, the amine group of the label reacts with the reducing‐end aldehyde group of the oligosaccharide to form a Schiff base, which is reduced to a secondary amine. Here, we propose the use of 2‐picoline‐borane as the reducing agent, as a non‐toxic alternative to the extensively used, but toxic sodium cyanoborohydride. Using dextran oligosaccharides and plasma N‐glycans, we demonstrate similar labeling efficacies for 2‐picoline‐borane and sodium cyanoborohydride. Therefore, 2‐picoline‐borane is a non‐toxic alternative to sodium cyanoborohydride for the labeling of oligosaccharides.