Network Analysis of Gut Microbiome and Metabolome to Discover Microbiota-Linked Biomarkers in Patients Affected by Non-Small Cell Lung Cancer

Several studies in recent times have linked gut microbiome (GM) diversity to the pathogenesis of cancer and its role in disease progression through immune response, inflammation and metabolism modulation. This study focused on the use of network analysis and weighted gene co-expression network analysis (WGCNA) to identify the biological interaction between the gut ecosystem and its metabolites that could impact the immunotherapy response in non-small cell lung cancer (NSCLC) patients undergoing second-line treatment with anti-PD1. Metabolomic data were merged with operational taxonomic units (OTUs) from 16S RNA-targeted metagenomics and classified by chemometric models. The traits considered for the analyses were: (i) condition: disease or control (CTRLs), and (ii) treatment: responder (R) or non-responder (NR). Network analysis indicated that indole and its derivatives, aldehydes and alcohols could play a signaling role in GM functionality. WGCNA generated, instead, strong correlations between short-chain fatty acids (SCFAs) and a healthy GM. Furthermore, commensal bacteria such as Akkermansia muciniphila, Rikenellaceae, Bacteroides, Peptostreptococcaceae, Mogibacteriaceae and Clostridiaceae were found to be more abundant in CTRLs than in NSCLC patients. Our preliminary study demonstrates that the discovery of microbiota-linked biomarkers could provide an indication on the road towards personalized management of NSCLC patients.     

Synthesis,Surface Properties,and Self-Aggregation Behavior of a Branched N,N-Dimethylalkylamine Oxide Surfactant

Amine-oxide surfactants have emerged as highly stable, nontoxic, and cost-effective constituents of detergent formulations, specifically as wetting agents and foam boosters. With the aim of enhancing their functional behavior, a new member of this family, N,N-dimethyl-2-propylheptan-1-amine oxide, bearing a branched alkyl tail (C₁₀DAO-branched) was synthesized and purified using a simple and easily scalable strategy starting from 2-propylheptan-1-ol. 2D-nuclear magnetic resonance (NMR) and mass spectrometry confirm the obtainment of the desired product in high yield and purity. The protonation behavior of the branched surfactant is not affected by alkyl tail branching, as shown by potentiometric titrations. In contrast, surface activity and aggregation behavior of C₁₀DAO-branched is dramatically different from that of the linear analog N,N-dimethyldecyl-1-amine oxide (C₁₀DAO-linear), in that it occupies a higher area at the solution interface and aggregates at much higher concentration, forming larger aggregates, as detected using tensiometry and dynamic light scattering (DLS), respectively. Aggregation behavior of C₁₀DAO-branched is less sensitive to pH variations. Foaming tests show that C₁₀DAO-branched is a more effective foam booster than its linear analog, in both acidic and basic solutions. The experimental results indicate that the branched surfactant can be used in applications that require enhanced and pH-independent surface activity and foamability.     

Efficient implementation of pseudochaotic piecewise linear maps with high digitization accuracies

In this paper we discuss the efficient implementation of pseudochaotic piecewise linear maps with high digitization accuracies, taking the R'enyi chaotic map as a reference. The proposed digital architectures are based on a novel algorithmic approach that uses carry save adders for the nonlinear arithmetic modular calculations arising when computing piecewise linear maps with a finite precision. As a result, the system can be implemented by digital circuits obtaining high throughputs, which are not dependent on the digital resolution while involving a hardware complexity linearly proportional to the number of bits used for representing the discretized state. The proposed solutions result to be particularly suitable for the implementation of pseudorandom number generators based on pseudochaos, or for the definition of efficient digital blocks that can be integrated in most of the pseudochaotic cyphers proposed in the literature. Copyright © 2010 John Wiley & Sons, Ltd.     

Dynamic option hedging with transaction costs: A stochastic model predictive control approach

This paper proposes stochastic model predictive control as a tool for hedging derivative contracts (such as plain vanilla and exotic options) in the presence of transaction costs. The methodology combines stochastic scenario generation for the prediction of asset prices at the next rebalancing interval with the minimization of a stochastic measure of the predicted hedging error. We consider 3 different measures to minimize in order to optimally rebalance the replicating portfolio: a trade‐off between variance and expected value of hedging error, conditional value at risk, and the largest predicted hedging error. The resulting optimization problems require solving at each trading instant a quadratic program, a linear program, and a (smaller‐scale) linear program, respectively. These can be combined with 3 different scenario generation schemes: the lognormal stock model with parameters recursively identified from data, an identification method based on support vector regression, and a simpler scheme based on perturbation noise. The hedging performance obtained by the proposed stochastic model predictive control strategies is illustrated on real‐world data drawn from the NASDAQ‐100 composite, evaluated for a European call and a barrier option, and compared with delta hedging.     

Photochemically Controlled Molecular Machines with Sequential Logic Operation

A molecular machine is an assembly of molecular components (i.e., a supramolecular structure) designed to perform specific mechanical movements in response to external stimuli. Biomolecular machines are essential for living organisms and are proven examples of the feasibility and utility of nanotechnology. Artificial molecular machines have been built in the laboratory and their use for smart materials and devices is the subject of much investigation. Here we discuss molecular machines based on rotaxane-like species, whose operation depends both on the type and sequencing of stimuli. These systems have the potential to store information and when carefully designed, the interplay of thermodynamic and kinetic features of supramolecular assemblies can yield sequential behavior. The investigation of ‘intelligent’ molecules capable of recognizing a specific input code can introduce new concepts to the field of chemistry and stimulate research in the bottom-up construction of nanodevices.     

The h-index as an almost-exact function of some basic statistics

Scientometrics - As is known, the h-index, h, is an exact function of the citation pattern. At the same time, and more generally, it is recognized that h is “loosely” related to the...     

Nanofabricated atom optics: Atom chips

Abstract

Small tight trapping and guiding potentials can be created for neutral atoms moving microns above surfaces patterned with nanofabricated charged and current-carrying structures. Surfaces holding such structures form atom chips which, for coherent matter wave optics, may form the basis for a variety of novel applications and research tools, similar to integrated circuits in electronics. In this paper we describe the basic principles of atom chip experiments.     

Conditions for time-controllability of behaviours

This paper develops a behavioural framework to study controllability of systems whose dynamics are described by systems of linear, constant coefficient partial differential equations. Questions about the notion of controllability are addressed with special importance given to the time-evolution. Algebraic conditions concerning time-controllability are proved.