Silicon resonant microcantilevers for absolute pressure measurement

This work is focused on the developing of silicon resonant microcantilevers for the measurement of the absolute pressure. The microcantilevers have been fabricated with a two-mask bulk micromachining process. The variation in resonance response of microcantilevers was investigated as a function of pressure 10−1-105 Pa, both in terms of resonance frequency and quality factor. A theoretical description of the resonating microstructure is given according to different molecular and viscous regimes. Also a brief discussion on the different quality factors contributions is presented. Theoretical and experimental data show a very satisfying agreement. The microstructure behavior demonstrates a certain sensitivity over a six decade range and the potential evolution of an absolute pressure sensor working in the same rang

Quantitative Modal Transition Systems

International audienceThis extended abstract offers a brief survey presentation of the specification formalism of modal transition systems and its recent extensions to the quantitative setting of timed as well as stochastic systems. Some applications will also be briefly mentioned

A Common CNR1 (Cannabinoid Receptor 1) Haplotype Attenuates the Decrease in HDL Cholesterol That Typically Accompanies Weight Gain

We have previously shown that genetic variability in CNR1 is associated with low HDL dyslipidemia in a multigenerational obesity study cohort of Northern European descent (209 families, median  = 10 individuals per pedigree). In order to assess the impact of CNR1 variability on the development of dyslipidemia in the community, we genotyped this locus in all subjects with class III obesity (body mass index >40 kg/m2) participating in a population-based biobank of similar ancestry. Twenty-two haplotype tagging SNPs, capturing the entire CNR1 gene locus plus 15 kb upstream and 5 kb downstream, were genotyped and tested for association with clinical lipid data. This biobank contains data from 645 morbidly obese study subjects. In these subjects, a common CNR1 haplotype (H3, frequency 21.1%) is associated with fasting TG and HDL cholesterol levels (p = 0.031 for logTG; p = 0.038 for HDL-C; p = 0.00376 for log[TG/HDL-C]). The strength of this relationship increases when the data are adjusted for age, gender, body mass index, diet and physical activity. Mean TG levels were 160±70, 155±70, and 120±60 mg/dL for subjects with 0, 1, and 2 copies of the H3 haplotype. Mean HDL-C levels were 45±10, 47±10, and 48±9 mg/dL, respectively. The H3 CNR1 haplotype appears to exert a protective effect against development of obesity-related dyslipidemia

The impact of camera optical alignments on weak lensing measures for the Dark Energy Survey

Telescope Point Spread Function (PSF) quality is critical for realising the potential of cosmic weak lensing observations to constrain dark energy and test General Relativity. In this paper we use quantitative weak gravitational lensing measures to inform the precision of lens optical alignment, with specific reference to the Dark Energy Survey (DES). We compute optics spot diagrams and calculate the shear and flexion of the PSF as a function of position on the focal plane. For perfect optical alignment we verify the high quality of the DES optical design, finding a maximum PSF contribution to the weak lensing shear of 0.04 near the edge of the focal plane. However this can be increased by a factor of approximately three if the lenses are only just aligned within their maximum specified tolerances. We calculate the E and B-mode shear and flexion variance as a function of de-centre or tilt of each lens in turn. We find tilt accuracy to be a few times more important than de-centre, depending on the lens considered. Finally we consider the compound effect of de-centre and tilt of multiple lenses simultaneously, by sampling from a plausible range of values of each parameter. We find that the compound effect can be around twice as detrimental as when considering any one lens alone. Furthermore, this combined effect changes the conclusions about which lens is most important to align accurately. For DES, the tilt of the first two lenses is the most important.Comment: 10 pages, 8 figure

Bayesian inference of accurate population sizes and FRET efficiencies from single diffusing biomolecules.

It is of significant biophysical interest to obtain accurate intramolecular distance information and population sizes from single-molecule Förster resonance energy transfer (smFRET) data obtained from biomolecules in solution. Experimental methods of increasing cost and complexity are being developed to improve the accuracy and precision of data collection. However, the analysis of smFRET data sets currently relies on simplistic, and often arbitrary methods, for the selection and denoising of fluorescent bursts. Although these methods are satisfactory for the analysis of simple, low-noise systems with intermediate FRET efficiencies, they display systematic inaccuracies when applied to more complex systems. We have developed an inference method for the analysis of smFRET data from solution studies based on rigorous model-based Bayesian techniques. We implement a Monte Carlo Markov chain (MCMC) based algorithm that simultaneously estimates population sizes and intramolecular distance information directly from a raw smFRET data set, with no intermediate event selection and denoising steps. Here, we present both our parametric model of the smFRET process and the algorithm developed for data analysis. We test the algorithm using a combination of simulated data sets and data from dual-labeled DNA molecules. We demonstrate that our model-based method systematically outperforms threshold-based techniques in accurately inferring both population sizes and intramolecular distances.This is the final published version. It's also available from ACS in Analytical Chemistry: http://pubs.acs.org/doi/pdf/10.1021/ac501188r

Precision and accuracy of single-molecule FRET measurements - a multi-laboratory benchmark study

Single-molecule Förster resonance energy transfer (smFRET) is increasingly being used to determine distances, structures, and dynamics of biomolecules in vitro and in vivo. However, generalized protocols and FRET standards to ensure the reproducibility and accuracy of measurements of FRET efficiencies are currently lacking. Here we report the results of a comparative blind study in which 20 labs determined the FRET efficiencies (E) of several dye-labeled DNA duplexes. Using a unified, straightforward method, we obtained FRET efficiencies with s.d. between ±0.02 and ±0.05. We suggest experimental and computational procedures for converting FRET efficiencies into accurate distances, and discuss potential uncertainties in the experiment and the modeling. Our quantitative assessment of the reproducibility of intensity-based smFRET measurements and a unified correction procedure represents an important step toward the validation of distance networks, with the ultimate aim of achieving reliable structural models of biomolecular systems by smFRET-based hybrid methods

Structural Heterogeneity and Quantitative FRET Efficiency Distributions of Polyprolines through a Hybrid Atomistic Simulation and Monte Carlo Approach

Förster Resonance Energy Transfer (FRET) experiments probe molecular distances via distance dependent energy transfer from an excited donor dye to an acceptor dye. Single molecule experiments not only probe average distances, but also distance distributions or even fluctuations, and thus provide a powerful tool to study biomolecular structure and dynamics. However, the measured energy transfer efficiency depends not only on the distance between the dyes, but also on their mutual orientation, which is typically inaccessible to experiments. Thus, assumptions on the orientation distributions and averages are usually made, limiting the accuracy of the distance distributions extracted from FRET experiments. Here, we demonstrate that by combining single molecule FRET experiments with the mutual dye orientation statistics obtained from Molecular Dynamics (MD) simulations, improved estimates of distances and distributions are obtained. From the simulated time-dependent mutual orientations, FRET efficiencies are calculated and the full statistics of individual photon absorption, energy transfer, and photon emission events is obtained from subsequent Monte Carlo (MC) simulations of the FRET kinetics. All recorded emission events are collected to bursts from which efficiency distributions are calculated in close resemblance to the actual FRET experiment, taking shot noise fully into account. Using polyproline chains with attached Alexa 488 and Alexa 594 dyes as a test system, we demonstrate the feasibility of this approach by direct comparison to experimental data. We identified cis-isomers and different static local environments as sources of the experimentally observed heterogeneity. Reconstructions of distance distributions from experimental data at different levels of theory demonstrate how the respective underlying assumptions and approximations affect the obtained accuracy. Our results show that dye fluctuations obtained from MD simulations, combined with MC single photon kinetics, provide a versatile tool to improve the accuracy of distance distributions that can be extracted from measured single molecule FRET efficiencies