Performance assessment of semiempirical molecular orbital methods in the structural prediction of Sb(III) and Bi(III) complexes

In this paper we carried out a systematic study in order to assess the quality of some semiempirical methods (AM1, PM3 and PM6), comparing predicted structural properties of many Sb(III) and Bi(III) complexes with the corresponding experimental data, indicating which one is more appropriate to describe the structure of such compounds. Root-mean squared deviation (RMSD) and unsigned mean error (UME) were used to evaluate the accuracy of the semiempirical methods to predict the ground state geometries of complexes with many ligand types. Our results have shown that, in general, PM3 predicts more accurately the geometry of Sb(III) complexes, being considered by us as the method of choice to study Sb(III) complexes with a great variety of ligands. PM6 is indicated as the method of choice to study Bi(III) complexes with many types of ligands and also to study Sb(III) thiocompounds, even though PM6 showed an inability to reproduce Sb-N bonds for complexes with flexible ligands, presenting an average deviation of 71.5 % compared the X-ray data.     

Giant plasma membrane vesicles to study plasma membrane structure and dynamics

The plasma membrane (PM) is a highly heterogenous structure intertwined with the cortical actin cytoskeleton and extracellular matrix. This complex architecture makes it difficult to study the processes taking place at the PM. Model membrane systems that are simple mimics of the PM overcome this bottleneck and allow us to study the biophysical principles underlying the processes at the PM. Among them, cell-derived giant plasma membrane vesicles (GPMVs) are considered the most physiologically relevant system, retaining the compositional complexity of the PM to a large extent. GPMVs have become a key tool in membrane research in the last few years. In this review, I will provide a brief overview of this system, summarize recent applications and discuss the limitations.     

Multiple outputation: inference for complex clustered data by averaging analyses from independent data

This article applies a simple method for settings where one has clustered data, but statistical methods are only available for independent data. We assume the statistical method provides us with a normally distributed estimate, theta, and an estimate of its variance sigma. We randomly select a data point from each cluster and apply our statistical method to this independent data. We repeat this multiple times, and use the average of the associated theta's as our estimate. An estimate of the variance is given by the average of the sigma2's minus the sample variance of the theta's. We call this procedure multiple outputation, as all "excess" data within each cluster is thrown out multiple times. Hoffman, Sen, and Weinberg (2001, Biometrika 88, 1121-1134) introduced this approach for generalized linear models when the cluster size is related to outcome. In this article, we demonstrate the broad applicability of the approach. Applications to angular data, p-values, vector parameters, Bayesian inference, genetics data, and random cluster sizes are discussed. In addition, asymptotic normality of estimates based on all possible outputations, as well as a finite number of outputations, is proven given weak conditions. Multiple outputation provides a simple and broadly applicable method for analyzing clustered data. It is especially suited to settings where methods for clustered data are impractical, but can also be applied generally as a quick and simple tool.     

The impact of operations redesign on the safety stock investment in supply chains

This study is motivated by a real problem encountered in the manufacturing and distribution process at a local electronic manufacturer of security devices. We investigate the impact of operations redesign (i.e., operations merging) on the cost of safety stock in a supply chain. A simple safety stock method is used to derive a model for estimating safety stock levels. Our result shows that operations redesign can have a significant impact on safety stock investment. We extend and complement the existing literature in the following aspects: (i) we address the issue of safety stock deployment, i.e., we not only investigate the problem of how many operations should be delayed, but also determine which operations need to be delayed, (ii) we provide an efficient heuristic algorithm to determine which operations need to be merged, and (iii) we find the optimal operations redesign strategies under some special cases. Our analysis also reveals some important conditions and insights for better operations redesign, which enable us not only to decide when an operations redesign is appropriate, but also to suggest the scale and the format of the operations redesign.     

Conservation paleobiology: putting the dead to work

Geohistorical data and analyses are playing an increasingly important role in conservation biology practice and policy. In this review, we discuss examples of how the near-time and deep-time fossil record can be used to understand the ecological and evolutionary responses of species to changes in their environment. We show that beyond providing crucial baseline data, the conservation paleobiology perspective helps us to identify which species will be most vulnerable and what kinds of responses will be most common. We stress that inclusion of geohistorical data in our decision-making process provides a more scientifically robust basis for conservation policies than those dependent on short-term observations alone.     

Neuro-fuzzy concepts applied for planning of the cereal crops: applications to the maize hybrids growing in a Romanian region

The aim of our study is to improve the crop planning procedures using neuro-fuzzy concepts. In this paper we design a neuro-fuzzy procedure that offers the suitable maize hybrid, from a set of preferred hybrids, which must be organically farmed in the current year. Our method is a statistical one, on the one hand it processes data provided by the previous years and on the other hand it takes in account the vague character of the environmental factors. Also we present here some experimental results obtained by us on a certain set of real data, results which prove the efficiency of our approach.     

Lateral plasma membrane compartmentalization links protein function and turnover

Biological membranes organize their proteins and lipids into nano‐ and microscale patterns. In the yeast plasma membrane (PM), constituents segregate into a large number of distinct domains. However, whether and how this intricate patchwork contributes to biological functions at the PM is still poorly understood. Here, we reveal an elaborate interplay between PM compartmentalization, physiological function, and endocytic turnover. Using the methionine permease Mup1 as model system, we demonstrate that this transporter segregates into PM clusters. Clustering requires sphingolipids, the tetraspanner protein Nce102, and signaling through TORC2. Importantly, we show that during substrate transport, a simple conformational change in Mup1 mediates rapid relocation into a unique disperse network at the PM. Clustered Mup1 is protected from turnover, whereas relocated Mup1 actively recruits the endocytic machinery thereby initiating its own turnover. Our findings suggest that lateral compartmentalization provides an important regulatory link between function and turnover of PM proteins.     

Lifetime of actin-dependent protein nanoclusters

Protein nanoclusters (PNCs) are dynamic collections of a few proteins that spatially organize in nanometer-length clusters. PNCs are one of the principal forms of spatial organization of membrane proteins, and they have been shown or hypothesized to be important in various cellular processes, including cell signaling. PNCs show remarkable diversity in size, shape, and lifetime. In particular, the lifetime of PNCs can vary over a wide range of timescales. The diversity in size and shape can be explained by the interaction of the clustering proteins with the actin cytoskeleton or the lipid membrane, but very little is known about the processes that determine the lifetime of the nanoclusters. In this paper, using mathematical modeling of the cluster dynamics, we model the biophysical processes that determine the lifetime of actin-dependent PNCs. In particular, we investigated the role of actin aster fragmentation, which had been suggested to be a key determinant of the PNC lifetime, and we found that it is important only for a small class of PNCs. A simple extension of our model allowed us to investigate the kinetics of protein-ligand interaction near PNCs. We found an anomalous increase in the lifetime of ligands near PNCs, which agrees remarkably well with experimental data on RAS-RAF kinetics. In particular, analysis of the RAS-RAF data through our model provides falsifiable predictions and novel hypotheses that will not only shed light on the role of RAS-RAF kinetics in various cancers, but also will be useful in studying membrane protein clustering in general.     

The bovine corneal opacity and permeability test in routine ocular irritation testing and its improvement within the limits of OECD test guideline 437

Data on eye irritation are generally needed for the hazard identification of chemicals. As the Bovine Corneal Opacity and Permeability (BCOP) test has been accepted by many regulatory agencies for the identification of corrosive and severe ocular irritants since September 2009 (OECD Test Guideline 437, TG 437), we evaluated this alternative method for routine testing at BASF. We demonstrated our technical proficiency by testing the reference standards recommended in TG 437, and 21 additional materials with published BCOP and in vivo data. Our results matched the published in vitro data very well, but with some intentionally selected false negatives (FNs) and false positives (FPs), the concordance was 77% (24/31), with FN and FP rates of 20% (2/10) and 24% (5/21), respectively. In addition, we tested 21 in-house materials, demonstrating the utility of the BCOP assay for our own test material panel. Histopathological assessment of the corneas by light microscopy was also conducted, as this was suggested as a means of improving the identification of FNs. The histopathology corrected the classification of some FNs, but also increased the number of FPs. Parallel to the test method evaluation, we compared three new opacitometer models with the current standard device. We recommend the use of an opacitometer developed in our BASF laboratory, which has certified components and electronic data storage, resulting in what we consider to be excellent sensitivity, stability and reproducibility.     

Mechanism of cell death and disease resistance induction by transgenic expression of bacterio-opsin

One of the earliest signal transduction events that trigger the hypersensitive response (HR) of plants against pathogen attack is thought to be an alteration of proton flux across the plasma membrane (PM). However, no direct genetic evidence for the involvement of PM-localised proton channels or pumps in the induction of this response has been reported. We previously showed that expression of the bacterial proton pump bacterio-opsin (bO) in transgenic plants resulted in the spontaneous activation of the HR. Here we show that the bO protein is likely localised to the PM in transgenic tobacco plants. Furthermore, mutational analysis shows that induction of the HR by bO expression is dependent upon the capability of bO to translocate protons. Although bO functions as a light-driven proton pump in Halobacteria when assembled with retinal, we also show by mutational analysis that this chromophore binding is unnecessary for its in planta activity. Taken together, our results suggest that expression of bO in plants leads to the insertion of a passive proton channel into the PM. The activity of this channel in the PM results in spontaneous activation of cell death and HR-associated phenotypes including enhanced resistance to a broad spectrum of plant pathogens. Our work provides direct molecular evidence to support a working model in which alterations in ionic homeostasis at the level of the PM may work as one of the critical steps in the signalling pathway for the activation of the HR.     

Simplified enrichment of plasma membrane proteins for proteomic analyses in Arabidopsis thaliana

The plasma membrane (PM) serves as the point of contact between cells and the outside environment. As such, changes in the PM proteome are an important component of understanding cellular responses to a diverse array of stimuli. However, intricate sample handling to enrich PM proteomes by traditional methods is both technically challenging and time consuming. Here, we describe a simplified method for decreasing the representation of other membrane-containing organelles such as the endoplasmic reticulum, plastids and mitochondria from crude microsomal membrane isolations. The decrease in other organellar proteomes results in an increase in both the total number of PM proteins and the number of spectra identified from these proteins representing the PM proteome. Therefore, this strategy represents a simple and rapid method for enriching PM proteins from Arabidopsis cell cultures for proteomic analyses.     

Integration of a two-phase partition method into proteomics research on rat liver plasma membrane proteins

To comprehensively identify proteins of the rat liver plasma membrane (PM), we have adopted a proteomics strategy that utilizes sucrose density centrifugation in conjunction with aqueous two-phase partition for plasma membrane isolation, followed by SDS-PAGE, mass spectrometry and bioinformatics. Western blot analysis showed that this method results in highly purified plasma membrane fractions, which is a key to successful plasma membrane proteomics. The PM proteins were separated by SDS-PAGE and digested with trypsin. Through nano-ESI-LC MS/MS analysis we identified 428 rat liver membrane proteins, of which 304 had a gene ontology (GO) annotation indicating a cellular component, and 204 (67%) of the latter were known integral membrane proteins or membrane-associated proteins. In addition to proteins known to be associated with the plasma membrane, several hypothetical proteins have also been identified. This study not only provides a tool to study plasma membrane proteins with low levels of contamination, but also provides a data set for proteins of high to moderate abundance in rat liver plasma membranes, thus allowing for more comprehensive characterization of membrane proteins and a better understanding of membrane dynamics.     

Sensitive Detection of Protein Binding to the Plasma Membrane with Dual-Color Z-Scan Fluorescence

Delicate and transitory protein engagement at the plasma membrane (PM) is crucial to a broad range of cellular functions, including cell motility, signal transduction, and virus replication. Here, we describe a dual-color (DC) extension of the fluorescence z-scan technique, which has proven successful for quantification of peripheral membrane protein binding to the PM in living cells. We demonstrate that the coexpression of a second, distinctly colored fluorescent protein provides a soluble reference species that delineates the extent of the cell cytoplasm and lowers the detection threshold of z-scan PM-binding measurements by an order of magnitude. DC z-scan generates an intensity profile for each detection channel that contains information on the axial distribution of the peripheral membrane and reference protein. Fit models for DC z-scan are developed and verified using simple model systems. Next, we apply the quantitative DC z-scan technique to investigate the binding of two peripheral membrane protein systems for which previous z-scan studies failed to detect binding: human immunodeficiency virus type 1 (HIV-1) matrix (MA) protein and lipidation-deficient mutants of the fibroblast growth factor receptor substrate 2α. Our findings show that these mutations severely disrupt PM association of fibroblast growth factor receptor substrate 2α but do not eliminate it. We further detected binding of HIV-1 MA to the PM using DC z-scan. Interestingly, our data indicate that HIV-1 MA binds cooperatively to the PM with a dissociation coefficient of K_d ∼16 μM and Hill coefficient of n ∼2.     

Clonal biases of peripheral CD8 T cell repertoire directly reflect local inflammation in polymyositis

Polymyositis (PM) involves destruction of striated muscles by autoaggressive CD8 T cells, which accumulate and secrete cytotoxic effector molecules in the affected muscles. Previous studies of peripheral T cell repertoires from normal individuals and patients with viral infections have shown that primed CD8 T cells, unlike CD4 T cells, are prone to expand clonally and persist as large populations in the peripheral blood. These facts made us assume that autoaggressive myocytotoxic CD8 T cells would expand clonally in the peripheral blood from patients with PM. By clonal analyses of peripheral T cells from patients and age-matched controls, we show here that clonal expansion of CD8 T cells was more frequent in patients. This was not significant in CD4 T cells. In analogy to virus-specific T cells, the expanded T cells persisted as large populations over time. Analysis of the muscle biopsy specimens revealed that some of the expanded clones were infiltrating in the affected muscles from the same patients. These results provide the first evidence that local autoimmune reaction directly elicits significant biases in peripheral T cell repertoire. The expanded cells, which should be candidate autoaggressive T cells, were readily isolated from the peripheral blood for analysis of expressed genes including perforin. Thus, our findings should give us an immediate clue to analysis of the pathogenic T cells in PM.     

Practical considerations for nonclinical safety evaluation of therapeutic monoclonal antibodies

Monoclonal antibodies (mAbs) are a well established class of therapeutics as evidenced by a large number of FDA approved mAbs for the treatment of cancers and autoimmune diseases. Monoclonal antibodies that are molecularly engineered for enhanced functions and pharmacokinetic properties are routinely being considered for development by many biotechnology companies. Safety evaluation of current generation of mAbs poses new challenges due to the highly complex nature of engineering aspects and variability induced by the diverse recombinant cell systems to generate them. This review provides a basic outline for nonclinical safety evaluation of therapeutic antibodies. Important considerations for planning a preclinical program, the types of nonclinical safety studies, and a general timeline for their conduct in relation to clinical trials are described. A list of relevant regulatory documents issued by government agencies is also provided. Adoption of these principles will greatly enhance the quality and relevance of the nonclinical safety data generated and will facilitate future development of mAb therapeutics.     

CNV-CH: A Convex Hull Based Segmentation Approach to Detect Copy Number Variations (CNV) Using Next-Generation Sequencing Data

Copy number variation (CNV) is a form of structural alteration in the mammalian DNA sequence, which are associated with many complex neurological diseases as well as cancer. The development of next generation sequencing (NGS) technology provides us a new dimension towards detection of genomic locations with copy number variations. Here we develop an algorithm for detecting CNVs, which is based on depth of coverage data generated by NGS technology. In this work, we have used a novel way to represent the read count data as a two dimensional geometrical point. A key aspect of detecting the regions with CNVs, is to devise a proper segmentation algorithm that will distinguish the genomic locations having a significant difference in read count data. We have designed a new segmentation approach in this context, using convex hull algorithm on the geometrical representation of read count data. To our knowledge, most algorithms have used a single distribution model of read count data, but here in our approach, we have considered the read count data to follow two different distribution models independently, which adds to the robustness of detection of CNVs. In addition, our algorithm calls CNVs based on the multiple sample analysis approach resulting in a low false discovery rate with high precision.     

DNA sexing of Nipponia nippon by duplex polymerase chain reaction

The aim of this study was to develop a rapid, simple, sensitive, and accurate duplex polymerase chain reaction (PCR) to sex Nipponia nippon, a monomorphic bird. Amplification by duplex PCR of a sex-related gene on the female chromosome and the 12S rRNA gene yielded good results using genomic DNA extracted from a feather follicle or the membranes of eggshell samples. To simplify the DNA extraction procedure, a simple boiling method was used. Our simple boiling DNA extraction method produced similar PCR amplification results as when using DNA extracted using TRIzol. Sex determination in the endangered Nipponia nippon is of crucial value to breeding programs. The duplex PCR protocol that we developed provides a simple sex identification method that is based on amplification of a sex-related gene, and we anticipate that it will facilitate effective conservation and management of Nipponia nippon.     

Unravelling the functional interaction structure of a cellular network from temporal slope information of experimental data

Due to the unavoidable nonbiological variations accompanying many experiments, it is imperative to consider a way of unravelling the functional interaction structure of a cellular network (e.g. signalling cascades or gene networks) by using the qualitative information of time-series experimental data instead of computation through the measured absolute values. In this spirit, we propose a very simple but effective method of identifying the functional interaction structure of a cellular network based on temporal ascending or descending slope information from given time-series measurements. From this method, we can gain insight into the acceptable measurement error ranges in order to estimate the correct functional interaction structure and we can also find guidance for a new experimental design to complement the insufficient information of a given experimental dataset. We developed experimental sign equations, making use of the temporal slope sign information from time-series experimental data, without a specific assumption on parameter perturbations for each network node. Based on these equations, we further describe the available specific information from each part of experimental data in detail and show the functional interaction structure obtained by integrating such information. In this procedure, we use only simple algebra on sign changes without complicated computations on the measured absolute values of the experimental data. The result is, however, verified through rigorous mathematical definitions and proofs. The present method provides us with information about the acceptable measurement error ranges for correct estimation of the functional interaction structure and it further leads to a new experimental design to complement the given experimental data by informing us about additional specific sampling points to be chosen for further required information.     

Foraging-efficiency-predation-risk trade-off in the grey squirrel

Many animals must often respond to environmental patterns that simulatneously influence both foraging efficiency and predation risk. We noted that grey squirrels (Sciurus carolinensis) sometimes immediately consume food items in areas of relatively great exposure to predators, and at other times carry food items to the safety of a tree prior to consumption. We outlined a hypothesis that the squirrels were somehow trading-off energy intake rate against predation risk. A simple model shows that maximal energetic efficiency is associated with immediate consumption, whereas (under the field conditions studied) carrying items to the safety of trees provides for minimal exposure to predation. Our analysis of the model predicts that the tendency to carry a food item should decrease with distance of food from cover (travel time) and increase with item size (handling time). To test our predictions, we presented free-roaming grey squirrels with patches containing a fixed number of identical food items. We estimated the proportion of items carried to trees before consumption for 12 different combinations of distance to the nearest tree and item size. The results support our hypothesis and indicate that a simple behavioural criterion based solely on foraging rate or time exposed to predators is insufficient to explain the variation in the data.     

"SCINT," a Fortran IV program for the analysis of data for doubly labeled and variably quenched liquid scintillation samples

For some time now, we have been using double label techniques in our laboratory. In our work we generate large numbers of samples containing ¹⁴C and ³H and varying amounts of quenching agents. The analysis of this data led us to develop SCINT, a simple and versatile program written in FORTRAN IV for use on our Control Data 1700 computer facility. We feel that such a program may be of use to the many workers now involved with dual isotope procedures who also have access to similar computer facilities.