Use of stains to detect fingermarks

Detection of fi ngermarks at a crime scene or on related items is of prime interest for forensicinvestigators, mainly for identifi cation purposes. Most of the fi ngermarks are invisible to thenaked eye, however. The application of detection techniques is required to establish visual contrastbetween the secretion residue and the underlying substrate. We give here a review of thefi eld related to the concept of using stains to detect fi ngermarks. A distinction has been madebetween the physically driven classical detection techniques, the chemically driven ones, andthose based on nanostructured materials, an emerging fi eld in forensic science.

Calcium imaging of odor-evoked responses in the Drosophila antennal lobe.

The antennal lobe is the primary olfactory center in the insect brain and represents the anatomical and functional equivalent of the vertebrate olfactory bulb. Olfactory information in the external world is transmitted to the antennal lobe by olfactory sensory neurons (OSNs), which segregate to distinct regions of neuropil called glomeruli according to the specific olfactory receptor they express. Here, OSN axons synapse with both local interneurons (LNs), whose processes can innervate many different glomeruli, and projection neurons (PNs), which convey olfactory information to higher olfactory brain regions. Optical imaging of the activity of OSNs, LNs and PNs in the antennal lobe - traditionally using synthetic calcium indicators (e.g. calcium green, FURA-2) or voltage-sensitive dyes (e.g. RH414) - has long been an important technique to understand how olfactory stimuli are represented as spatial and temporal patterns of glomerular activity in many species of insects. Development of genetically-encoded neural activity reporters, such as the fluorescent calcium indicators G-CaMP and Cameleon, the bioluminescent calcium indicator GFP-aequorin, or a reporter of synaptic transmission, synapto-pHluorin has made the olfactory system of the fruitfly, Drosophila melanogaster, particularly accessible to neurophysiological imaging, complementing its comprehensively-described molecular, electrophysiological and neuroanatomical properties. These reporters can be selectively expressed via binary transcriptional control systems (e.g. GAL4/UAS, LexA/LexAop, Q system) in defined populations of neurons within the olfactory circuitry to dissect with high spatial and temporal resolution how odor-evoked neural activity is represented, modulated and transformed. Here we describe the preparation and analysis methods to measure odor-evoked responses in the Drosophila antennal lobe using G-CaMP. The animal preparation is minimally invasive and can be adapted to imaging using wide-field fluorescence, confocal and two-photon microscopes.

Effects of social support on the clinical course of Crohn's disease.

BACKGROUND: Social support has been found to be protective from adverse health effects of psychological stress. We hypothesized that higher social support would predict a more favorable course of Crohn's disease (CD) directly (main effect hypothesis) and via moderating other prognostic factors (buffer hypothesis). METHODS: Within a multicenter cohort study we observed 597 adults with CD for 18 months. We assessed social support using the ENRICHD Social Support Inventory. Flares, nonresponse to therapy, complications, and extraintestinal manifestations were recorded as a combined endpoint indicating disease deterioration. We controlled for several demographic, psychosocial, and clinical variables of potential prognostic importance. We used multivariate binary logistic regression to estimate the overall effect of social support on the odds of disease deterioration and to explore main and moderator effects of social support by probing interactions with other predictors. RESULTS: The odds of disease deterioration decreased by 1.5 times (95% confidence interval [CI]: 1.2-1.9) for an increase of one standard deviation (SD) of social support. In case of low body mass index (BMI) (i.e., 1 SD below the mean or <19 kg/m(2)), the odds decreased by 1.8 times for an increase of 1 SD of social support. In case of low social support, the odds increased by 2.1 times for a decrease of 1 SD of BMI. Low BMI was not predictive under high social support. CONCLUSIONS: The findings suggest that elevated social support may favorably affect the clinical course of CD, particularly in patients with low BMI. (Inflamm Bowel Dis 2010;).

Imputation in data fusion of heterogeneous data sets a model-based numerical experiment

Given the very large amount of data obtained everyday through population surveys, much of the new research again could use this information instead of collecting new samples. Unfortunately, relevant data are often disseminated into different files obtained through different sampling designs. Data fusion is a set of methods used to combine information from different sources into a single dataset. In this article, we are interested in a specific problem: the fusion of two data files, one of which being quite small. We propose a model-based procedure combining a logistic regression with an Expectation-Maximization algorithm. Results show that despite the lack of data, this procedure can perform better than standard matching procedures.

Characterization of microsatellite loci and reliable genotyping in a polyploid plant, Mercurialis perennis (Euphorbiaceae).

For many applications in population genetics, codominant simple sequence repeats (SSRs) may have substantial advantages over dominant anonymous markers such as amplified fragment length polymorphisms (AFLPs). In high polyploids, however, allele dosage of SSRs cannot easily be determined and alleles are not easily attributable to potentially diploidized loci. Here, we argue that SSRs may nonetheless be better than AFLPs for polyploid taxa if they are analyzed as effectively dominant markers because they are more reliable and more precise. We describe the transfer of SSRs developed for diploid Mercurialis huetii to the clonal dioecious M. perennis. Primers were tested on a set of 54 male and female plants from natural decaploid populations. Eight of 65 tested loci produced polymorphic fragments. Binary profiles from 4 different scoring routines were used to define multilocus lineages (MLLs). Allowing for fragment differences within 1 MLL, all analyses revealed the same 14 MLLs without conflicting with merigenet, sex, or plot assignment. For semiautomatic scoring, a combination of as few as 2 of the 4 most polymorphic loci resulted in unambiguous discrimination of clones. Our study demonstrates that microsatellite fingerprinting of polyploid plants is a cost efficient and reliable alternative to AFLPs, not least because fewer loci are required than for diploids.

A functional and structural study of the major metalloprotease secreted by the pathogenic fungus Aspergillus fumigatus.

Fungalysins are secreted fungal peptidases with the ability to degrade the extracellular matrix proteins elastin and collagen and are thought to act as virulence factors in diseases caused by fungi. Fungalysins constitute a unique family among zinc-dependent peptidases that bears low sequence similarity to known bacterial peptidases of the thermolysin family. The crystal structure of the archetype of the fungalysin family, Aspergillus fumigatus metalloprotease (AfuMep), has been obtained for the first time. The 1.8 Å resolution structure of AfuMep corresponds to that of an autoproteolyzed proenzyme with separate polypeptide chains corresponding to the N-terminal prodomain in a binary complex with the C-terminal zinc-bound catalytic domain. The prodomain consists of a tandem of cystatin-like folds whose C-terminal end is buried into the active-site cleft of the catalytic domain. The catalytic domain harbouring the key catalytic zinc ion and its ligands, two histidines and one glutamic acid, undergoes a conspicuous rearrangement of its N-terminal end during maturation. One key positively charged amino-acid residue and the C-terminal disulfide bridge appear to contribute to its structural-functional properties. Thus, structural, biophysical and biochemical analysis were combined to provide a deeper comprehension of the underlying properties of A. fumigatus fungalysin, serving as a framework for the as yet poorly known metallopeptidases from pathogenic fungi.

Role of Age and Sex in the Diagnosis of Early-stage Malignant Melanoma: A Cross-Sectional study.

Age and sex have been identified as predictors of outcome in malignant melanoma (MM). This aim of this multicentre, cross-sectional study was to analyse the role of age and sex as explanatory variables for the diagnosis of thin MM. A total of 2430 patients with MM were recruited. Cases of in situ-T1 MM were more frequent than T2-T4 MM (56.26% vs. 43.74%). Breslow thickness increased throughout decades of life (analysis of variance (ANOVA) p < 0.001), with a weak correlation between Breslow thickness and patient's age (r   = 0.202, p < 0.001). Breslow thickness was significantly less in women (1.79 vs. 2.38 mm, p = 0.0001). Binary logistic regression showed a significant (p < 0.001) odds ratio for age 0-29 years (1.18), and 30-59 years (1.16), and for women (1.09). Age and sex explained 3.64% of the variation observed in Tis-T1 frequency (R2 = 0.0364). Age and sex appear to explain a low percentage of the variation in the early detection of MM.

Enhancing efficacy of anticancer vaccines by targeted delivery to tumor-draining lymph nodes.

The sentinel or tumor-draining lymph node (tdLN) serves as a metastatic niche for many solid tumors and is altered via tumor-derived factors that support tumor progression and metastasis. tdLNs are often removed surgically, and therapeutic vaccines against tumor antigens are typically administered systemically or in non-tumor-associated sites. Although the tdLN is immune-suppressed, it is also antigen experienced through drainage of tumor-associated antigens (TAA), so we asked whether therapeutic vaccines targeting the tdLN would be more or less effective than those targeting the non-tdLN. Using LN-targeting nanoparticle (NP)-conjugate vaccines consisting of TAA-NP and CpG-NP, we compared delivery to the tdLN versus non-tdLN in two different cancer models, E.G7-OVA lymphoma (expressing the nonendogenous TAA ovalbumin) and B16-F10 melanoma. Surprisingly, despite the immune-suppressed state of the tdLN, tdLN-targeting vaccination induced substantially stronger cytotoxic CD8+ T-cell responses, both locally and systemically, than non-tdLN-targeting vaccination, leading to enhanced tumor regression and host survival. This improved tumor regression correlated with a shift in the tumor-infiltrating leukocyte repertoire toward a less suppressive and more immunogenic balance. Nanoparticle coupling of adjuvant and antigen was required for effective tdLN targeting, as nanoparticle coupling dramatically increased the delivery of antigen and adjuvant to LN-resident antigen-presenting cells, thereby increasing therapeutic efficacy. This work highlights the tdLN as a target for cancer immunotherapy and shows how its antigen-experienced but immune-suppressed state can be reprogrammed with a targeted vaccine yielding antitumor immunity.

Learning spatial filters for multispectral image segmentation

We present a novel filtering method for multispectral satellite image classification. The proposed method learns a set of spatial filters that maximize class separability of binary support vector machine (SVM) through a gradient descent approach. Regularization issues are discussed in detail and a Frobenius-norm regularization is proposed to efficiently exclude uninformative filters coefficients. Experiments carried out on multiclass one-against-all classification and target detection show the capabilities of the learned spatial filters.

Kernel-based methods for change detection in remote sensing images

Nowadays, the joint exploitation of images acquired daily by remote sensing instruments and of images available from archives allows a detailed monitoring of the transitions occurring at the surface of the Earth. These modifications of the land cover generate spectral discrepancies that can be detected via the analysis of remote sensing images. Independently from the origin of the images and of type of surface change, a correct processing of such data implies the adoption of flexible, robust and possibly nonlinear method, to correctly account for the complex statistical relationships characterizing the pixels of the images. This Thesis deals with the development and the application of advanced statistical methods for multi-temporal optical remote sensing image processing tasks. Three different families of machine learning models have been explored and fundamental solutions for change detection problems are provided. In the first part, change detection with user supervision has been considered. In a first application, a nonlinear classifier has been applied with the intent of precisely delineating flooded regions from a pair of images. In a second case study, the spatial context of each pixel has been injected into another nonlinear classifier to obtain a precise mapping of new urban structures. In both cases, the user provides the classifier with examples of what he believes has changed or not. In the second part, a completely automatic and unsupervised method for precise binary detection of changes has been proposed. The technique allows a very accurate mapping without any user intervention, resulting particularly useful when readiness and reaction times of the system are a crucial constraint. In the third, the problem of statistical distributions shifting between acquisitions is studied. Two approaches to transform the couple of bi-temporal images and reduce their differences unrelated to changes in land cover are studied. The methods align the distributions of the images, so that the pixel-wise comparison could be carried out with higher accuracy. Furthermore, the second method can deal with images from different sensors, no matter the dimensionality of the data nor the spectral information content. This opens the doors to possible solutions for a crucial problem in the field: detecting changes when the images have been acquired by two different sensors.

A low number of Swiss companies uses nanoparticles

Nanoparticles <100 nanometres are being introduced into industrial processes, but they are suspected to cause similar negative health effects to ambient particles. Poor knowledge about the scale of introduction has not allowed global risk analysis until now. In 2006 a targeted telephone survey among Swiss companies (1) showed the usage of nanoparticles in a few selected companies but did not provide data to extrapolate to the full Swiss workforce. The purpose of the study presented here was to provide a quantitative estimate of the potential occupational exposure to nanoparticles in Swiss industry. Method: A layered representative questionnaire survey among 1626 Swiss companies of the production sector was conducted in 2007. The survey was a written questionnaire, collecting data about the used nanoparticles, the number of potentially exposed persons in the companies and their protection strategy. Results: The response rate of the study was 58.3%. The number of companies estimated to be using nanoparticles in Switzerland was 586 (95% Confidence Interval 145 to 1027). It is estimated that 1309 workers (95% CI 1073 to 1545) do their job in the same room as a nanoparticle application. Personal protection was shown to be the predominant protection means. Such information is valuable for risk evaluation. The low number of companies dealing with nanoparticles in Switzerland suggests that policy makers as well as health, safety and environmental officers within companies can focus their efforts on a relatively small number of companies or workers. The collected data about types of particles and applications may be used for research on prevention strategies and adapted protection means. However, to reflect the most recent trends, the information presented here has to be continuously updated, and a large-scale inventory of the usage should be considered.

Metallic and nonmetallic shine in luster: An elastic ion backscattering study

Luster is a metal glass nanocomposite layer first produced in the Middle East in early Islamic times ( 9th AD) made of metal copper or silver nanoparticles embedded in a silica-based glassy matrix. These nanoparticles are produced by ion exchange between Cu+ and Ag+ and alkaline ions from the glassy matrix and further growth in a reducing atmosphere. The most striking property of luster is its capability of reflecting light like a continuous metal layer and it was unexpectedly found to be linked to one single production parameter: the presence of lead in the glassy matrix composition. The purpose of this article is to describe the characteristics and differences of the nanoparticle layers developed on lead rich and lead free glasses. Copper luster layers obtained using the ancient recipes and methods are analyzed by means of elastic ion backscattering spectroscopy associated with other analytical techniques. The depth profile of the different elements is determined, showing that the luster layer formed in lead rich glasses is 5–6 times thinner and 3–4 times Cu richer. Therefore, the metal nanoparticles are more densely packed in the layer and this fact is related to its higher reflectivity. It is shown that lead influences the structure of the metal nanoparticle layer through the change of the precipitation kinetics

Seismic attenuation and velocity dispersion in heterogeneous partially saturated porous rocks

Using a numerical approach, we explore wave-induced fluid flow effects in partially saturated porous rocks in which the gas-water saturation patterns are governed by mesoscopic heterogeneities associated with the dry frame properties. The link between the dry frame properties and the gas saturation is defined by the assumption of capillary pressure equilibrium, which in the presence of heterogeneity implies that neighbouring regions can exhibit different levels of saturation. To determine the equivalent attenuation and phase velocity of the synthetic rock samples considered in this study, we apply a numerical upscaling procedure, which permits to take into account mesoscopic heterogeneities associated with the dry frame properties as well as spatially continuous variations of the pore fluid properties. The multiscale nature of the fluid saturation is taken into account by locally computing the physical properties of an effective fluid, which are then used for the larger-scale simulations. We consider two sets of numerical experiments to analyse such effects in heterogeneous partially saturated porous media, where the saturation field is determined by variations in porosity and clay content, respectively. In both cases we also evaluate the seismic responses of corresponding binary, patchy-type saturation patterns. Our results indicate that significant attenuation and modest velocity dispersion effects take place in this kind of media for both binary patchy-type and spatially continuous gas saturation patterns and in particular in the presence of relatively small amounts of gas. The numerical experiments also show that the nature of the gas distribution patterns is a critical parameter controlling the seismic responses of these environments, since attenuation and velocity dispersion effects are much more significant and occur over a broader saturation range for binary patchy-type gas-water distributions. This analysis therefore suggests that the physical mechanisms governing partial saturation should be accounted for when analysing seismic data in a poroelastic framework. In this context, heterogeneities associated with the dry frame properties, which do not play important roles in wave-induced fluid flow processes per se, should be taken into account since they may determine the kind of gas distribution pattern taking place in the porous rock.

Generalized low-density codes with BCH constituents for full-diversity near-outage performance

A new graph-based construction of generalized low density codes (GLD-Tanner) with binary BCH constituents is described. The proposed family of GLD codes is optimal on block erasure channels and quasi-optimal on block fading channels. Optimality is considered in the outage probability sense. Aclassical GLD code for ergodic channels (e.g., the AWGN channel,the i.i.d. Rayleigh fading channel, and the i.i.d. binary erasure channel) is built by connecting bitnodes and subcode nodes via a unique random edge permutation. In the proposed construction of full-diversity GLD codes (referred to as root GLD), bitnodes are divided into 4 classes, subcodes are divided into 2 classes, and finally both sides of the Tanner graph are linked via 4 random edge permutations. The study focuses on non-ergodic channels with two states and can be easily extended to channels with 3 states or more.

Smoking and adolescence: Exploring tobacco consumption and related attitudes in three different age groups in Switzerland

The present study constitutes an investigation of tobacco consumption, related attitudes and individual differences in smoking or non-smoking behaviors in a sample of adolescents of different ages in the French-speaking part of Switzerland. We investigated three school-age groups (7th-grade, 9th-grade, and the second-year of high school) for differences in attitude and social and cognitive dimensions. We present both descriptive and inferential statistics. On an inferential level, we present a binary logistic regression-based model predicting risk of smoking. The resulting model most importantly suggests a strong relationship between smoking and alcohol consumption (both regular and sporadic). We interpret this result in terms of both the impact of the actual campaigns and the cognitive processes associated with adolescence.