Publication Date: 2010 Mar 18 PMID: 20298554Authors: Olsen, B. - Murakami, C. J. - Kaeberlein, M.Journal: BMC BioinformaticsABSTRACT: BACKGROUND: The budding yeast Saccharomyces cerevisiae is one of the most widely studied model organisms in aging-related science. Although several genetic modifiers of yeast longevity have been identified, the utility of this system for longevity studies has been limited by a lack of high-throughput assays for quantitatively measuring survival of individual yeast cells during aging. RESULTS: Here we describe the Yeast Outgrowth Data Analyzer (YODA), an automated system for analyzing population survival of yeast cells based on the kinetics of outgrowth measured by optical density over time. YODA has been designed specifically for quantification of yeast chronological life span, but can also be used to quantify growth rate and survival of yeast cells in response to a variety of different conditions, including temperature, nutritional composition of the growth media, and chemical treatments. YODA is optimized for use with a Bioscreen C MBR shaker/incubator/plate reader, but is also amenable to use with any standard plate reader or spectrophotometer. CONCLUSIONS: We estimate that use of YODA as described here reduces the effort and resources required to measure chronological life span and analyze the resulting data by at least 15-fold.post to: CiteULike

Sensors and Actuators B: Chemical, Vol. 52, No. 1-2. (15 September 1998), pp. 125-142.

Perfect ‘chemical imaging’ aims at the time- and spatially-resolved recording of many chemical species. Comparison of results from ‘chemical imaging’ with calibration data may also be trained towards an identification of odor impressions, environmental or medical conditions (such as toxicity), process control parameters etc. This ‘chemical imaging’ can be approached by either using the well-established techniques of analytical chemistry or by using a large number of calibrated sensors and sensor systems. The latter are sometimes denoted ‘electronic noses’, provide an electronic approach to artificial olfaction and are considered in this paper. They offer a variety of principal advantages including the fact that calibration efforts and sizes can be minimized systematically for specific applications by fine-tuning individual components of the sensor system. The paper describes a systematic to design such sensor systems. In the traditional application of chemical sensors the output of an individual chemical sensor is recorded as one ‘feature’. The first aim towards perfect ‘chemical imaging’ is to determine a large number of independent features, which span a large ‘hyperspace of chemical features’. The second aim is then to extract information from this hyperspace by optimizing a feature extraction procedure towards four application-specific goals. (a) The first goal concerns to record certain chemical species quantitatively and hence aims at perfect ‘chemical imaging’ as defined above. (b) Alternative goals concern to record odor impressions, (c) environmental or medical conditions, (d) and process control parameters. Different kinds of calibration are wanted to extract the wanted information from the data represented in the hyperspace of chemical sensor features. Hence, four different strategies are required to compare the features monitored by the chemical sensor systems with independent calibration standards from (a) instruments in analytical chemistry, (b) human odor panels, (c) (micro-)biological or medical tests, (d) and process parameter measurements. This adjustment of measured sensor features to calibration standards determines a specific type of feature extraction and pattern recognition for a specific application. This pattern recognition of experimentally recorded features is of key importance not only for these ‘electronic’ noses but occurs in the same way in all real ‘biological’ noses. Hence, formal analogies between the technical and biological world of noses are obvious. It is therefore expected, that our current studies on chemical sensor systems will also lead to a deeper understanding of signal processing in biological sensor systems and vice versa. Expected synergies of comparative studies concern in particular the molecular scale understanding of (a) the elementary processes of chemical sensing, (b) human odor perception, and (c) interactions between the environment and biological organisms. In this context, biolectronics becomes an increasingly important discipline. By taking advantage of characteristic similarities and differences of components in technical and biological systems, high-performance hybrid systems will be developped in the future.
W Göpel

Publication Date: 2010 Mar 18 PMID: 20237567Authors: Huang, F. - Chakraborty, P. - Lundstrom, C. C. - Holmden, C. - Glessner, J. J. - Kieffer, S. W. - Lesher, C. E.Journal: NatureThe phenomenon of thermal diffusion (mass diffusion driven by a temperature gradient, known as the Ludwig-Soret effect) has been investigated for over 150 years, but an understanding of its underlying physical basis remains elusive. A significant hurdle in studying thermal diffusion has been the difficulty of characterizing it. Extensive experiments over the past century have established that the Soret coefficient, S(T) (a single parameter that describes the steady-state result of thermal diffusion), is highly sensitive to many factors. This sensitivity makes it very difficult to obtain a robust characterization of thermal diffusion, even for a single material. Here we show that for thermal diffusion experiments that span a wide range in composition and temperature, the difference in S(T) between isotopes of diffusing elements that are network modifiers (iron, calcium and magnesium) is independent of the composition and temperature. On the basis of this finding, we propose an additive decomposition for the functional form of S(T) and argue that a theoretical approach based on local thermodynamic equilibrium holds promise for describing thermal diffusion in silicate melts and other complex solutions. Our results lead to a simple and robust framework for characterizing isotope fractionation by thermal diffusion in natural and synthetic systems.post to: CiteULike