Correlative microscopy.

In recent years correlative microscopy, combining the power and advantages of different imaging system, e.g., light, electrons, X-ray, NMR, etc., has become an important tool for biomedical research. Among all the possible combinations of techniques, light and electron microscopy, have made an especially big step forward and are being implemented in more and more research labs. Electron microscopy profits from the high spatial resolution, the direct recognition of the cellular ultrastructure and identification of the organelles. It, however, has two severe limitations: the restricted field of view and the fact that no live imaging can be done. On the other hand light microscopy has the advantage of live imaging, following a fluorescently tagged molecule in real time and at lower magnifications the large field of view facilitates the identification and location of sparse individual cells in a large context, e.g., tissue. The combination of these two imaging techniques appears to be a valuable approach to dissect biological events at a submicrometer level. Light microscopy can be used to follow a labelled protein of interest, or a visible organelle such as mitochondria, in time, then the sample is fixed and the exactly same region is investigated by electron microscopy. The time resolution is dependent on the speed of penetration and fixation when chemical fixatives are used and on the reaction time of the operator for cryo-fixation. Light microscopy can also be used to identify cells of interest, e.g., a special cell type in tissue or cells that have been modified by either transfections or RNAi, in a large population of non-modified cells. A further application is to find fluorescence labels in cells on a large section to reduce searching time in the electron microscope. Multiple fluorescence labelling of a series of sections can be correlated with the ultrastructure of the individual sections to get 3D information of the distribution of the marked proteins: array tomography. More and more efforts are put in either converting a fluorescence label into an electron dense product or preserving the fluorescence throughout preparation for the electron microscopy. Here, we will review successful protocols and where possible try to extract common features to better understand the importance of the individual steps in the preparation. Further the new instruments and software, intended to ease correlative light and electron microscopy, are discussed. Last but not least we will detail the approach we have chosen for correlative microscopy.

Current Sheet Regulation of Solar Near-Relativistic Electron Injection Histories

We present a sample of three large near-relativistic (>50 keV) electron events observed in 2001 by both the ACE and the Ulysses spacecraft, when Ulysses was at high-northern latitudes (>60°) and close to 2 AU. Despite the large latitudinal distance between the two spacecraft, electrons injected near the Sun reached both heliospheric locations. All three events were associated with large solar flares, strong decametric type II radio bursts and accompanied by wide (>212°) and fast (>1400 km s-1) coronal mass ejections (CMEs). We use advanced interplanetary transport simulations and make use of the directional intensities observed in situ by the spacecraft to infer the electron injection profile close to the Sun and the interplanetary transport conditions at both low and high latitudes. For the three selected events, we find similar interplanetary transport conditions at different heliolatitudes for a given event, with values of the mean free path ranging from 0.04 AU to 0.27 AU. We find differences in the injection profiles inferred for each spacecraft. We investigate the role that sector boundaries of the heliospheric current sheet (HCS) have on determining the characteristics of the electron injection profiles. Extended injection profiles, associated with coronal shocks, are found if the magnetic footpoints of the spacecraft lay in the same magnetic sector as the associated flare, while intermittent sparse injection episodes appear when the spacecraft footpoints are in the opposite sector or a wrap in the HCS bounded the CME structure.

Massive protostars as gamma-ray sources.

Massive protostars have associated bipolar outflows with velocities of hundreds of km s-1. Such outflows can produce strong shocks when they interact with the ambient medium leading to regions of nonthermal radio emission. Aims. We aim at exploring under which conditions relativistic particles are accelerated at the terminal shocks of the protostellar jets and whether they can produce significant gamma-ray emission. Methods. We estimate the conditions necessary for particle acceleration up to very high energies and gamma-ray production in the nonthermal hot spots of jets associated with massive protostars embedded in dense molecular clouds. Results. We show that relativistic bremsstrahlung and proton-proton collisions can make molecular clouds with massive young stellar objects detectable by the Fermi satellite at MeV-GeV energies and by Cherenkov telescope arrays in the GeV-TeV range. Conclusions. Gamma-ray astronomy can be used to probe the physical conditions in star-forming regions and particle acceleration processes in the complex environment of massive molecular clouds.

Whole-body MRI: comprehensive evaluation on a 48-channel 3T MRI system in less than 40 minutes. Preliminary results

OBJECTIVE: To evaluate a comprehensive MRI protocol that investigates for cancer, vascular disease, and degenerative/inflammatory disease from the head to the pelvis in less than 40 minutes on a new generation 48-channel 3T system. MATERIALS AND METHODS: All MR studies were performed on a 48-channel 3T MR scanner. A 20-channel head/neck coil, two 18-channel body arrays, and a 32-channel spine array were employed. A total of 4 healthy individuals were studied. The designed protocol included a combination of single-shot T2-weighted sequences, T1-weighted 3D gradient-echo pre- and post-gadolinium. All images were retrospectively evaluated by two radiologists independently for overall image quality. RESULTS: The image quality for cancer was rated as excellent in the liver, pancreas, kidneys, lungs, pelvic organs, and brain, and rated as fair in the colon and breast. For vascular diseases ratings were excellent in the aorta, major branch vessel origins, inferior vena cava, portal and hepatic veins, rated as good in pulmonary arteries, and as poor in the coronary arteries. For degenerative/inflammatory diseases ratings were excellent in the brain, liver and pancreas. The inter-observer agreement was excellent. CONCLUSION: A comprehensive and time efficient screening for important categories of disease processes may be achieved with high quality imaging in a new generation 48-channel 3T system.

Landslide detection and monitoring capability of boat-based mobile laser scanning along Dieppe coastal cliffs, Normandy

Integrated in a wide research assessing destabilizing and triggering factors to model cliff dynamic along the Dieppe's shoreline in High Normandy, this study aims at testing boat-based mobile LiDAR capabilities by scanning 3D point clouds of the unstable coastal cliffs. Two acquisition campaigns were performed in September 2012 and September 2013, scanning (1) a 30-km-long shoreline and (2) the same test cliffs in different environmental conditions and device settings. The potentials of collected data for 3D modelling, change detection and landslide monitoring were afterward assessed. By scanning during favourable meteorological and marine conditions and close to the coast, mobile LiDAR devices are able to quickly scan a long shoreline with median point spacing up to 10cm. The acquired data are then sufficiently detailed to map geomorphological features smaller than 0.5m2. Furthermore, our capability to detect rockfalls and erosion deposits (>m3) is confirmed, since using the classical approach of computing differences between sequential acquisitions reveals many cliff collapses between Pourville and Quiberville and only sparse changes between Dieppe and Belleville-sur-Mer. These different change rates result from different rockfall susceptibilities. Finally, we also confirmed the capability of the boat-based mobile LiDAR technique to monitor single large changes, characterizing the Dieppe landslide geometry with two main active scarps, retrogression up to 40m and about 100,000m3 of eroded materials.

Espectrofotometria multicanal e arranjos de fotodiodos

This paper describes some aspects of multichannel spectrophotometry, principles of photodiode arrays and their applications in Analytical Chemistry.

Disease profiles of detainees in the Canton of Vaud in Switzerland: gender and age differences in substance abuse, mental health and chronic health conditions.

BACKGROUND: Literature on the disease profile of prisoners that differentiates by age and gender remains sparse. This study aimed to describe the health of correctional inmates in terms of substance abuse problems and mental and somatic health conditions, and compare it by gender and age. METHODS: This study examined cross-sectional data from the Canton of Vaud in Switzerland on the health conditions of detainees who were in prison on January 1, 2011 or entered prison in 2011. Health conditions validated by physician examination were reported using the International Classification of Diseases (ICD) version 10. The analyses were descriptive by groups of prisoners: the entire sample (All), Men, Older adults and Women. RESULTS: A total of 1,664 individuals were included in the analysis. Men comprised 91.5 % of the sample and had a mean age of 33 years. The other 8.5 % were women and had an average age of 39. Older adults (i.e., age 50 and older) represented 7 % of the total sample. Overall, 80 % of inmates were non-Swiss citizens, but the proportion of Swiss prisoners was higher among the older adults (51 %) and women (29 %). Overall, 41 % of inmates self-reported substance abuse problems. Of those, 27 % were being treated by psychiatrists for behavioral disorders related to substance abuse. Chronic infectious diseases were found in 9 % of the prison population. In addition, 27 % of detainees suffered from serious mental health conditions. Gender and age had an influence on the disease profile of this sample: compared to the entire prison population, the older inmates were less likely to misuse illegal drugs and to suffer from communicable infections but exhibited more problems with alcohol and a higher burden of chronic health conditions. Female prisoners were more disposed to mental health problems (including drug abuse) and infectious diseases. In terms of chronic diseases, women suffered from the same conditions as men, but the diseases were more prevalent in women. CONCLUSION: It is important to understand the different disease profiles of prisoners by gender and age, as it helps identify the needs of different groups and tailor age-and gender-specific interventions.

Eletrodos fabricados por "silk-screen"

A review dealing with the use of screen-printing technology to manufacture disposable electrodes is presented, covering in details virtually all the publications in the area up to early 1997 and including 206 references. The elements and different strategies on constructing modified electrodes are highlighted. Commercial and Home-made ink recipes are discussed. Microelectrode arrays, built by the combination of photostructuring and screen-printing technologies to the mass production of advanced disposable sensors, are also discussed. Future research trends are predicted.

Design concepts for the Cherenkov Telescope Array CTA: an advanced facility for ground-based high-energy gamma-ray astronomy

Ground-based gamma-ray astronomy has had a major breakthrough with the impressive results obtained using systems of imaging atmospheric Cherenkov telescopes. Ground-based gamma-ray astronomy has a huge potential in astrophysics, particle physics and cosmology. CTA is an international initiative to build the next generation instrument, with a factor of 5-10 improvement in sensitivity in the 100 GeV-10 TeV range and the extension to energies well below 100 GeV and above 100 TeV. CTA will consist of two arrays (one in the north, one in the south) for full sky coverage and will be operated as open observatory. The design of CTA is based on currently available technology. This document reports on the status and presents the major design concepts of CTA.

Design concepts for the Cherenkov Telescope Array CTA: an advanced facility for ground-based high-energy gamma-ray astronomy

Ground-based gamma-ray astronomy has had a major breakthrough with the impressive results obtained using systems of imaging atmospheric Cherenkov telescopes. Ground-based gamma-ray astronomy has a huge potential in astrophysics, particle physics and cosmology. CTA is an international initiative to build the next generation instrument, with a factor of 5-10 improvement in sensitivity in the 100 GeV-10 TeV range and the extension to energies well below 100 GeV and above 100 TeV. CTA will consist of two arrays (one in the north, one in the south) for full sky coverage and will be operated as open observatory. The design of CTA is based on currently available technology. This document reports on the status and presents the major design concepts of CTA.

Design concepts for the Cherenkov Telescope Array CTA: an advanced facility for ground-based high-energy gamma-ray astronomy

Ground-based gamma-ray astronomy has had a major breakthrough with the impressive results obtained using systems of imaging atmospheric Cherenkov telescopes. Ground-based gamma-ray astronomy has a huge potential in astrophysics, particle physics and cosmology. CTA is an international initiative to build the next generation instrument, with a factor of 5-10 improvement in sensitivity in the 100 GeV-10 TeV range and the extension to energies well below 100 GeV and above 100 TeV. CTA will consist of two arrays (one in the north, one in the south) for full sky coverage and will be operated as open observatory. The design of CTA is based on currently available technology. This document reports on the status and presents the major design concepts of CTA.

Learning Preferences with Kernel-Based Methods

Learning of preference relations has recently received significant attention in machine learning community. It is closely related to the classification and regression analysis and can be reduced to these tasks. However, preference learning involves prediction of ordering of the data points rather than prediction of a single numerical value as in case of regression or a class label as in case of classification. Therefore, studying preference relations within a separate framework facilitates not only better theoretical understanding of the problem, but also motivates development of the efficient algorithms for the task. Preference learning has many applications in domains such as information retrieval, bioinformatics, natural language processing, etc. For example, algorithms that learn to rank are frequently used in search engines for ordering documents retrieved by the query. Preference learning methods have been also applied to collaborative filtering problems for predicting individual customer choices from the vast amount of user generated feedback. In this thesis we propose several algorithms for learning preference relations. These algorithms stem from well founded and robust class of regularized least-squares methods and have many attractive computational properties. In order to improve the performance of our methods, we introduce several non-linear kernel functions. Thus, contribution of this thesis is twofold: kernel functions for structured data that are used to take advantage of various non-vectorial data representations and the preference learning algorithms that are suitable for different tasks, namely efficient learning of preference relations, learning with large amount of training data, and semi-supervised preference learning. Proposed kernel-based algorithms and kernels are applied to the parse ranking task in natural language processing, document ranking in information retrieval, and remote homology detection in bioinformatics domain. Training of kernel-based ranking algorithms can be infeasible when the size of the training set is large. This problem is addressed by proposing a preference learning algorithm whose computation complexity scales linearly with the number of training data points. We also introduce sparse approximation of the algorithm that can be efficiently trained with large amount of data. For situations when small amount of labeled data but a large amount of unlabeled data is available, we propose a co-regularized preference learning algorithm. To conclude, the methods presented in this thesis address not only the problem of the efficient training of the algorithms but also fast regularization parameter selection, multiple output prediction, and cross-validation. Furthermore, proposed algorithms lead to notably better performance in many preference learning tasks considered.

Epithelial-to-mesenchymal transition mediates docetaxel resistance and high risk of relapse in prostate cancer

Molecular characterization of radical prostatectomy specimens after systemic therapy may identify a gene expression profile for resistance to therapy. This study assessed tumor cells from patients with prostate cancer participating in a phase II neoadjuvant docetaxel and androgen deprivation trial to identify mediators of resistance. Transcriptional level of 93 genes from a docetaxel-resistant prostate cancer cell lines microarray study was analyzed by TaqMan low-density arrays in tumors from patients with high-risk localized prostate cancer (36 surgically treated, 28 with neoadjuvant docetaxel þ androgen deprivation). Gene expression was compared between groups and correlated with clinical outcome. VIM, AR and RELA were validated by immunohistochemistry. CD44 and ZEB1 expression was tested by immunofluorescence in cells and tumor samples. Parental and docetaxel-resistant castration-resistant prostate cancer cell lines were tested for epithelial-to-mesenchymal transition (EMT) markers before and after docetaxel exposure. Reversion of EMT phenotype was investigated as a docetaxel resistance reversion strategy. Expression of 63 (67.7%) genes differed between groups (P < 0.05), including genes related to androgen receptor, NF-k B transcription factor, and EMT. Increased expression of EMT markers correlated with radiologic relapse. Docetaxel-resistant cells had increased EMT and stem-like cell markers expression. ZEB1 siRNA transfection reverted docetaxel resistance and reduced CD44 expression in DU-145R and PC-3R. Before docetaxel exposure, a selected CD44 þ subpopulation of PC-3 cells exhibited EMT phenotype and intrinsic docetaxel resistance; ZEB1/CD44 þ subpopulations were found in tumor cell lines and primary tumors; this correlated with aggressive clinical behavior. This study identifies genes potentially related to chemotherapy resistance and supports evi-dence of the EMT role in docetaxel resistance and adverse clinical behavior in early prostate cancer.

Anisotropic surface properties of micro/nanostructured a-C:H:F thin films with self-assembly applications

The singular properties of hydrogenated amorphous carbon (a-C:H) thin filmsdeposited by pulsed DC plasma enhanced chemical vapor deposition (PECVD), such as hardness and wear resistance, make it suitable as protective coating with low surface energy for self-assembly applications. In this paper, we designed fluorine-containing a-C:H (a-C:H:F) nanostructured surfaces and we characterized them for self-assembly applications. Sub-micron patterns were generated on silicon through laser lithography while contact angle measurements, nanotribometer, atomic force microscopy (AFM), and scanning electron microscopy (SEM) were used to characterize the surface. a-C:H:F properties on lithographied surfaces such as hydrophobicity and friction were improved with the proper relative quantity of CH4 and CHF3 during deposition, resulting in ultrahydrophobic samples and low friction coefficients. Furthermore, these properties were enhanced along the direction of the lithographypatterns (in-plane anisotropy). Finally, self-assembly properties were tested with silicananoparticles, which were successfully assembled in linear arrays following the generated patterns. Among the main applications, these surfaces could be suitable as particle filter selector and cell colony substrate.

Swarm Intelligent Selection and Optimization of Machining System Parameters for Microchannel Fabrication in Medical Devices

Current technology trends in medical device industry calls for fabrication of massive arrays of microfeatures such as microchannels on to nonsilicon material substrates with high accuracy, superior precision, and high throughput. Microchannels are typical features used in medical devices for medication dosing into the human body, analyzing DNA arrays or cell cultures. In this study, the capabilities of machining systems for micro-end milling have been evaluated by conducting experiments, regression modeling, and response surface methodology. In machining experiments by using micromilling, arrays of microchannels are fabricated on aluminium and titanium plates, and the feature size and accuracy (width and depth) and surface roughness are measured. Multicriteria decision making for material and process parameters selection for desired accuracy is investigated by using particle swarm optimization (PSO) method, which is an evolutionary computation method inspired by genetic algorithms (GA). Appropriate regression models are utilized within the PSO and optimum selection of micromilling parameters; microchannel feature accuracy and surface roughness are performed. An analysis for optimal micromachining parameters in decision variable space is also conducted. This study demonstrates the advantages of evolutionary computing algorithms in micromilling decision making and process optimization investigations and can be expanded to other applications