Single-Cell Proteomics: The Critical Role of Nanotechnology

In single-cell analysis, biological variability can be attributed to individual cells, their specific state, and the ability to respond to external stimuli, which are determined by protein abundance and their relative alterations. Mass spectrometry (MS)-based proteomics (e.g., SCoPE-MS and SCoPE2) can be used as a non-targeted method to detect molecules across hundreds of individual cells. To achieve high-throughput investigation, novel approaches in Single-Cell Proteomics (SCP) are needed to identify and quantify proteins as accurately as possible. Controlling sample preparation prior to LC-MS analysis is critical, as it influences sensitivity, robustness, and reproducibility. Several nanotechnological approaches have been developed for the removal of cellular debris, salts, and detergents, and to facilitate systematic sample processing at the nano- and microfluidic scale. In addition, nanotechnology has enabled high-throughput proteomics analysis, which have required the improvement of software tools, such as DART-ID or DO-MS, which are also fundamental for addressing key biological questions. Single-cell proteomics has many applications in nanomedicine and biomedical research, including advanced cancer immunotherapies or biomarker characterization, among others; and novel methods allow the quantification of more than a thousand proteins while analyzing hundreds of single cells.     

Chemical Modeling of Acid-Base Properties of Soluble Biopolymers Derived from Municipal Waste Treatment Materials

This work reports a study of the proton-binding capacity of biopolymers obtained from different materials supplied by a municipal biowaste treatment plant located in Northern Italy. One material was the anaerobic fermentation digestate of the urban wastes organic humid fraction. The others were the compost of home and public gardening residues and the compost of the mix of the above residues, digestate and sewage sludge. These materials were hydrolyzed under alkaline conditions to yield the biopolymers by saponification. The biopolymers were characterized by ¹³C NMR spectroscopy, elemental analysis and potentiometric titration. The titration data were elaborated to attain chemical models for interpretation of the proton-binding capacity of the biopolymers obtaining the acidic sites concentrations and their protonation constants. The results obtained with the models and by NMR spectroscopy were elaborated together in order to better characterize the nature of the macromolecules. The chemical nature of the biopolymers was found dependent upon the nature of the sourcing materials.     

Optimisation of rancidity stability in long‐chain PUFA concentrates obtained from a rainbow trout (Oncorhynchus mykiss) by‐product

This research was focused on the production of polyunsaturated fatty acid concentrates from a farmed rainbow trout (Oncorhynchus mykiss) by‐product (i.e. belly muscle). The effect of different process variables (urea/fatty acids (FA) contents ratio, crystallisation time and temperature and stirring speed of the urea/FA mixture) on the lipid oxidation development during the urea complexation process was investigated. For this purpose, an experimental design (26 runs) following the response‐surface methodology was developed. As a result, peroxide value and TOTOX index showed to be dependent on the crystallisation time and temperature and the urea/FA ratio, while no influence of the crystallisation stirring speed was detected on both indices; additionally, polyene index was affected by the urea/FA ratio and its interaction with the crystallisation time. An optimised desirability score near 1.0 was attained provided values of 2.8 °C, 3.05 h and 3.57 were applied for crystallisation temperature, crystallisation time and urea/FA ratio, respectively.     

Management Levers for Product Platforms

Platforming has become an important means of cost-sharing among industrial products. However, many firms face systemic downward pressure on commonality, with the result that many platforms realize less commonality than intended. Past research has hypothesized that divergence is the result of conflicting tensions between product customization/optimization and cost control. This article investigates the control and incentive levers available to platform managers to shape the behavior of the organization when divergence opportunities arise. Management levers are drawn from a series of 12 industrial case studies, stemming from investigations of the causes of divergences. These management levers are categorized as technical levers, financial levers, and organizational levers. This article illustrates each of the management levers with examples from the case studies.     

Level‐set topology optimization with many linear buckling constraints using an efficient and robust eigensolver

Linear buckling constraints are important in structural topology optimization for obtaining designs that can support the required loads without failure. During the optimization process, the critical buckling eigenmode can change; this poses a challenge to gradient‐based optimization and can require the computation of a large number of linear buckling eigenmodes. This is potentially both computationally difficult to achieve and prohibitively expensive. In this paper, we motivate the need for a large number of linear buckling modes and show how several features of the block Jacobi conjugate gradient (BJCG) eigenvalue method, including optimal shift estimates, the reuse of eigenvectors, adaptive eigenvector tolerances and multiple shifts, can be used to efficiently and robustly compute a large number of buckling eigenmodes. This paper also introduces linear buckling constraints for level‐set topology optimization. In our approach, the velocity function is defined as a weighted sum of the shape sensitivities for the objective and constraint functions. The weights are found by solving an optimization sub‐problem to reduce the mass while maintaining feasibility of the buckling constraints. The effectiveness of this approach in combination with the BJCG method is demonstrated using a 3D optimization problem. Copyright © 2016 John Wiley & Sons, Ltd.     

Thermal spikes in Ag/Fe and Cu/Fe ion beam mixing

Ion beam mixing has been studied since 1980, and since then a lot of experimental and theoretical work has been done and knowledge has been gathered. Nevertheless, there are still many fundamental aspects that need to be clarified and with that aim many experiments need to be performed. Copper and iron are miscible in the liquid state, while silver and iron are not. However, both systems are thermally immiscible in the solid state. In order to have an insight into the importance of mixing within thermal spikes during ion beam irradiation, we deposited Cu/Fe and Ag/Fe bilayers onto Si substrates and irradiated them at room temperature with 2 MeV Cu and 2.5 MeV Au ions. A combination of Rutherford backscattering spectrometry (RBS) and atomic force microscopy (AFM) was used to analyze the atomic transport at the interface and the morphology changes of the samples. From the element profiles at the interface we conclude a mixing efficiency, which is indeed larger than the prediction of the ballistic model in the Cu/Fe system and smaller in the Ag/Fe system. Since ballistic mixing is expected in any case, we argue that demixing and phase separation in the Ag/Fe system occur in the thermal spike phase of the cascade as a consequence of the positive heat of mixing. Further mixing does occur in the thermal spike in the Cu/Fe system and they remain mixed even at the solid state because of the high cooling rate. In addition, ion irradiation induces a large surface roughening of the Ag and Cu top layers as proven by AFM. This effect is important for the correct interpretation of the results. Furthermore, this recrystallization affects also the interface, producing a rough interface, that appears in the RBS spectra as an atomic ‘diffusion’ at the interface.     

The multiple window parameter transform

The multiwindow transform, an extension of parameter transform techniques that increase performance and scope by exploiting the long-range correlated information contained in multiple portions of an image, is presented. Multiple-window transforms allow the extraction of high-dimensional features with improvement in accuracy over conventional techniques while keeping linear to low-order-polynomial computational and space requirements with respect to image size and dimensionality of the features. Using correlated information provides a direct link between extracted features and supporting regions in the image. This, coupled with evidence integration techniques, is used to suppress noisy or nonexistent feature hypotheses. Parameter spaces are implemented as constraint satisfaction networks, where feature hypotheses with overlapping support in the image compete. After an iterative relaxation phase, surviving hypotheses have disjoint support, forming a segmentation of the image. Examples show the performance and provide insight about the behavior     

CWDM Metropolitan Multiple-Access Ring Network Based on Optical Packet Witching

We present a novel CWDM metropolitan multiple-access ring network based on optical switching of packets according to their wavelength. Each node within the MAN is identified by a combination of wavelength and numerical address. Hence, nodes are able to drop packets presenting a particular wavelength and numerical address, but can insert packets in any wavelength into the ring. This configuration allows wavelength sharing, as several nodes are identified by the same wavelength (but different numerical addresses), and simplifies switching requirements since the set of numerical addresses is reduced. We analyze the viability and scalability of such a network, determining the number of nodes supported by the network under different traffic scenarios and wavelength resources. The impact of switching time on network performance is also analyzed in order to determine which switching technology should be employed when implementing the network. An erratum to this article is available at .     

Perceptions of Multicultural Training in Predoctoral Internship Programs: A Survey of Interns and Training Directors.

Multicultural training at internship sites is a critical component in the preparation of doctoral-level psychologists, so the quality of this training is of the utmost importance. In the following study, the authors examine multicultural training from the perspective of predoctoral interns and training directors at counseling center sites that offer a major or minor rotation in multicultural therapy. Results suggest that perspectives vary between interns and training directors and that there is a great difference in the type of criteria used by each site as evidence of a major or minor rotation. The need for more standardized criteria to define major and minor rotations and suggestions for the Association of Psychology Postdoctoral and Internship Centers, internship training directors, and prospective interns are discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Rating defence major project success: The role of personal attributes and stakeholder relationships

In this paper we develop and test a model of the associations between major project managers' personal attributes and project success in the context of the Australian Defence industry. In our model, emotional intelligence, cognitive flexibility and systemic thinking were hypothesised to relate to project success, mediated by internal and external stakeholder relationships. The model was tested in an online survey with 373 major project managers. Emotional intelligence and cognitive flexibility were found to be related to the development, quality and effectiveness of major project managers' relationships with both internal and external stakeholders; and these in turn were associated with their ratings of project success. Systemic thinking, however, had no relationship with either stakeholder relationships or project success. Additional research is needed to examine the contribution of a wider range of personal attributes to stakeholder relationships and project success, and to assess whether this model is applicable in other industries and types of projects.