Physiological model using diffuse reflectance spectroscopy for nonmelanoma skin cancer diagnosis

Diffuse reflectance spectroscopy (DRS) is a noninvasive, fast, and low‐cost technology with potential to assist cancer diagnosis. The goal of this study was to test the capability of our physiological model, a computational Monte Carlo lookup table inverse model, for nonmelanoma skin cancer diagnosis. We applied this model on a clinical DRS dataset to extract scattering parameters, blood volume fraction, oxygen saturation and vessel radius. We found that the model was able to capture physiological information relevant to skin cancer. We used the extracted parameters to classify (basal cell carcinoma [BCC], squamous cell carcinoma [SCC]) vs actinic keratosis (AK) and (BCC, SCC, AK) vs normal. The area under the receiver operating characteristic curve achieved by the classifiers trained on the parameters extracted using the physiological model is comparable to that of classifiers trained on features extracted via Principal Component Analysis. Our findings suggest that DRS can reveal physiologic characteristics of skin and this physiologic model offers greater flexibility for diagnosing skin cancer than a pure statistical analysis. Physiological parameters extracted from diffuse reflectance spectra data for nonmelanoma skin cancer diagnosis.     

On the relative stabilities of the alkali cations 222 cryptates in the gas phase and in water-methanol solution

The relative stabilities of the alkali [M ⊂ 222]⁺ cryptates (M = Na, K, Rb and Cs) in the gas phase and in solution (80:20 v/v methanol:water mixture) at 298 K, are computed using a combination of ab initio quantum-chemical calculations (HF/6-31G and MP2/6-31+G*//HF/6-31+G*) and explicit-solvent Monte Carlo free-energy simulations. The results suggest that the relative stabilities of the cryptates in solution are due to a combination of steric effects (compression of large ions within the cryptand cavity), electronic effects (delocalization of the ionic charge onto the cryptand atoms) and solvent effects (dominantly the ionic dessolvation penalty). Thus, the relative stabilities in solution cannot be rationalized solely on the basis of a simple match or mismatch between the ionic radius and the cryptand cavity size as has been suggested previously. For example, although the [K ⊂ 222]⁺ cryptate is found to be the most stable in solution, in agreement with experimental data, it is the [Na ⊂ 222]⁺ cryptate that is the most stable in the gas phase. The present results provide further support to the notion that the solvent in which supramolecules are dissolved plays a key role in modulating molecular recognition processes. Figure Alkali cryptates [M ⊂ 222]+ (M = Na, K, Rb and Cs) relative stabilities in gas and methanol:water solution: solvent effects and molecular recognition

---

Electronic supplementary material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Evolutionary constraints on polyembryony in parasitic wasps: a simulation model

Polyembryony involves the production of several genetically identical progeny from a single egg through clonal division. Although polyembryonic development allows highly efficient reproduction, especially in some parasitoid wasps, it is far less common than monoembryony (development of one embryo per egg). To understand what might constrain the evolutionary success of polyembryony in parasitoids, we developed Monte Carlo models that simulate the competition between polyembryonic females and their monoembryonic counterparts. We investigated which simulated life‐history traits of the females allow the monoembryonic mode of development to succeed. Published empirical studies were surveyed to explore whether these traits indeed differ between polyembryonic parasitoids and related monoembryonic species. The simulations predict an advantage to monoembryony in parasitoids whose reproduction is limited by host availability rather than by egg supply, and that parasitize small‐bodied hosts. Comparative data on the parasitoid families Encyrtidae and (to a lesser extent) Braconidae, but not the data from Platygastridae, circumstantially support these predictions. The model also predicts monoembryony to outcompete polyembryony when: 1) hosts vary considerably in quality, 2) polyembryonic development carries high physiological costs, and 3) monoembryonic females make optimal clutch size decisions upon attacking hosts. These multiple constraints may account for the rarity of polyembryony among parasitoid species.     

Quantifying personal exposure to air pollution from smartphone‐based location data

Personal exposure assessment is a challenging task that requires both measurements of the state of the environment as well as the individual's movements. In this paper, we show how location data collected by smartphone applications can be exploited to quantify the personal exposure of a large group of people to air pollution. A Bayesian approach that blends air quality monitoring data with individual location data is proposed to assess the individual exposure over time, under uncertainty of both the pollutant level and the individual location. A comparison with personal exposure obtained assuming fixed locations for the individuals is also provided. Location data collected by the Earthquake Network research project are employed to quantify the dynamic personal exposure to fine particulate matter of around 2500 people living in Santiago (Chile) over a 4‐month period. For around 30% of individuals, the personal exposure based on people movements emerges significantly different over the static exposure. On the basis of this result and thanks to a simulation study, we claim that even when the individual location is known with nonnegligible error, this helps to better assess personal exposure to air pollution. The approach is flexible and can be adopted to quantify the personal exposure based on any location‐aware smartphone application.     

MolMod – an open access database of force fields for molecular simulations of fluids

The MolMod database is presented, which is openly accessible at http://molmod.boltzmann-zuse.de and contains intermolecular force fields for over 150 pure fluids at present. It was developed and is maintained by the Boltzmann-Zuse Society for Computational Molecular Engineering (BZS). The set of molecular models in the MolMod database provides a coherent framework for molecular simulations of fluids. The molecular models in the MolMod database consist of Lennard-Jones interaction sites, point charges, and point dipoles and quadrupoles, which can be equivalently represented by multiple point charges. The force fields can be exported as input files for the simulation programmes ms2 and ls1 mardyn, GROMACS, and LAMMPS. To characterise the semantics associated with the numerical database content, a force field nomenclature is introduced that can also be used in other contexts in materials modelling at the atomistic and mesoscopic levels. The models of the pure substances that are included in the database were generally optimised such as to yield good representations of experimental data of the vapour–liquid equilibrium with a focus on the vapour pressure and the saturated liquid density. In many cases, the models also yield good predictions of caloric, transport, and interfacial properties of the pure fluids. For all models, references to the original works in which they were developed are provided. The models can be used straightforwardly for predictions of properties of fluid mixtures using established combination rules. Input errors are a major source of errors in simulations. The MolMod database contributes to reducing such errors.     

蒙特卡罗模拟多束光辐照下生物组织中的光吸收分布

用蒙特卡罗方法模拟了均匀分布光和高斯分布光在生物组织内的传播。通过比较单束以及多束均匀分布光和高斯分布光照射下组织内的光子能量分布规律,分析了不同光源和光斑大小对光吸收分布的影响。结果表明:与均匀光束比较,高斯光束辐照时,激光能量较为集中,但侧向传播范围较窄。在总功率相同的情况下,使用单束大功率宽光源与多束功率较小的小光斑光源均能明显地增大光的侧向传播距离,但使用多束功率较小的小光斑光辐照时生物组织中的最大光吸收率增大。多束组合光源光束间距对光吸收分布影响很大。     

A theoretical model for the association of amphiphilic transmembrane peptides in lipid bilayers

A theoretical model is proposed for the association of trans-bilayer peptides in lipid bilayers. The model is based on a lattice model for the pure lipid bilayer, which accounts accurately for the most important conformational states of the lipids and their mutual interactions and statistics. Within the lattice formulation the bilayer is formed by two independent monolayers, each represented by a triangular lattice, on which sites the lipid chains are arrayed. The peptides are represented by regular objects, with no internal flexibility, and with a projected area on the bilayer plane corresponding to a hexagon with seven lattice sites. In addition, it is assumed that each peptide surface at the interface with the lipid chains is partially hydrophilic, and therefore interacts with the surrounding lipid matrix via selective anisotropic forces. The peptides would therefore assemble in order to shield their hydrophilic residues from the hydrophobic surroundings. The model describes the self-association of peptides in lipid bilayers via lateral and rotational diffusion, anisotropic lipid-peptide interactions, and peptide-peptide interactions involving the peptide hydrophilic regions. The intent of this model study is to analyse the conditions under which the association of trans-bilayer and partially hydrophilic peptides (or their dispersion in the lipid matrix) is lipid-mediated, and to what extent it is induced by direct interactions between the hydrophilic regions of the peptides. The model properties are calculated by a Monte Carlo computer simulation technique within the canonical ensemble. The results from the model study indicate that direct interactions between the hydrophilic regions of the peptides are necessary to induce peptide association in the lipid bilayer in the fluid phase. Furthermore, peptides within each aggregate are oriented in such a way as to shield their hydrophilic regions from the hydrophobic environment. The average number of peptides present in the aggregates formed depends on the degree of mismatch between the peptide hydrophobic length and the lipid bilayer hydrophobic thickness: The lower the degree of mismatch is the higher this number is. Received: 30 December 1996 / Accepted: 9 May 1997     

Estimating population structure from AFLP amplification intensity

In the last decade, amplified fragment length polymorphisms (AFLPs) have become one of the most widely used molecular markers to study the genetic structure of natural populations. Most of the statistical methods available to study the genetic structure of populations using AFLPs consider these markers as dominant and are thus unable to distinguish between individuals being heterozygous or homozygous for the dominant allele. Some attempts have been made to treat AFLPs as codominant markers by using AFLP band intensities to infer the most likely genotype of each individual. These two approaches have some drawbacks, the former discarding potentially valuable information and the latter being sometimes unable to correctly assign genotypes to individuals. In this study, we propose an alternative likelihood‐based approach, which does not attempt at inferring the genotype of each individual, but rather incorporate the uncertainty about genotypes into a Bayesian framework leading to the estimation of population‐specific F_IS and F_ST coefficients. We show with simulations that the accuracy of our method is much higher than one using AFLP as dominant markers and is generally close to what would be obtained by using the same number of Single‐Nucleotide Polymorphism (SNP) markers. The method is applied to a data set of four populations of the common vole (Microtus arvalis) from Grisons in Switzerland, for which we obtained 562 polymorphic AFLP markers. Our approach is very general and has the potential to make AFLP markers as useful as SNP data for nonmodel species.     

Iteration model of starch hydrolysis by amylolytic enzymes.

An elaborate computer program to simulate the process of starch hydrolysis by amylolytic enzymes was been developed. It is based on the Monte Carlo method and iteration kinetic model, which predict productive and non-productive amylase complexes with substrates. It describes both multienzymatic and multisubstrate reactions simulating the "real" concentrations of all components versus the time of the depolymerization reaction the number of substrates, intermediate products, and final products are limited only by computer memory. In this work, it is assumed that the "proper" substrate for amylases is the glucoside linkages in starch molecules. Dynamic changes of substrate during the simulation adequately influence the increase or decrease of reaction velocity, as well as the kinetics of depolymerization. The presented kinetic model, can be adapted to describe most enzymatic degradations of a polymer. This computer program has been tested on experimental data obtained for alpha- and beta-amylases.     

Multiple imputation for multivariate data with missing and below-threshold measurements: time-series concentrations of pollutants in the Arctic

Many chemical and environmental data sets are complicated by the existence of fully missing values or censored values known to lie below detection thresholds. For example, week-long samples of airborne particulate matter were obtained at Alert, NWT, Canada, between 1980 and 1991, where some of the concentrations of 24 particulate constituents were coarsened in the sense of being either fully missing or below detection limits. To facilitate scientific analysis, it is appealing to create complete data by filling in missing values so that standard complete-data methods can be applied. We briefly review commonly used strategies for handling missing values and focus on the multiple-imputation approach, which generally leads to valid inferences when faced with missing data. Three statistical models are developed for multiply imputing the missing values of airborne particulate matter. We expect that these models are useful for creating multiple imputations in a variety of incomplete multivariate time series data sets.