A proteomic analysis of green and white sturgeon larvae exposed to heat stress and selenium

Temperature and selenium are two environmental parameters that potentially affect reproduction and stock recruitment of sturgeon in the San Francisco Bay/Delta Estuary. To identify proteins whose expression is modified by these environmental stressors, we performed a proteomic analysis on larval green and white sturgeons exposed to 18 or 26 °C and micro-injected with Seleno-L-Methionine to reach 8 µg g⁻¹ selenium body burden, with L-Methionine as a control. Selenium and high temperature induced mortalities and abnormal morphologies in both species, with a higher mortality in green sturgeon. Larval proteins were separated by two-dimensional gel electrophoresis and differential abundances were detected following spot quantitation and hierarchical cluster analysis. In green sturgeon, 34 of 551 protein spots detected on gels showed a variation in abundance whereas in white sturgeon only 9 of 580 protein spots were differentially expressed (P < 0.01). Gel replicates were first grouped according to heat treatment. Fifteen of these spots were identified using MALDI TOF/TOF mass spectrometry. Proteins involved in protein folding, protein synthesis, protein degradation, ATP supply and structural proteins changed in abundance in response to heat and/or selenium. 40S ribosomal protein SA, FK506-binding protein 10, 65 kDa regulatory subunit A of protein phosphatase 2, protein disulfide isomerase, stress-induced-phosphoprotein 1, suppression of tumorigenicity 13 and collagen type II alpha 1, were differentially expressed in high temperature treatment only. Serine/arginine repetitive matrix protein 1, creatine kinase, serine peptidase inhibitor Kazal type 5 and HSP90 were sensitive to combined temperature and selenium exposure. Valosin-containing protein, a protein involved in aggresome formation and in protein quality control decreased more than 50% in response to selenium treatment. Potential use of such proteins as biomarkers of environmental stressors in larval sturgeons could indicate early warning signals preceding population decline.     

Weighted integral method in multi-dimensional stochastic finite element analysis

This paper, using the weighted integral method, proposes a new stochastic finite element method for estimating the response variability of multi-dimensional stochastic systems. Young's modules is considered to have spatial variation and is idealized as a multi-dimensional stochastic field. An essential feature of the proposed method is that the continuous stochastic field is rigorously taken care of by means of weighted integrations to construct element stiffness matrices, as the results, the issue involving the stochastic field is transformed into a problem involving only a few random variables. This may lead to substantial improvement in computational efficiency. Numerical examples show that the proposed SFEM is concluded as an efficient and accurate method.     

The role of mathematics and physics in migration predictions

Whilst one or two mathematical formulae have appeared frequently in papers on migration, little use has yet been made of them in analysing data, or in writing legislation on food contact materials and articles. In this short review, it is argued that mathematics and physics have far greater potential than has so far been realized in such roles, and certain basic principles that are crucial for effective use of these disciplines in migration research are discussed. The first of these is the great importance of the geometry, i.e. shape and size, of the food-container system; most (if not all) commonly used formulae have serious shortcomings because they apply only to one-dimensional geometries, which are not met in practice. The second is that results must be plotted in non-dimensional form if underlying unity of behaviour is to be detected — and the search for such unity is one of the main aims of mathematics. Finally, the paper discusses some causes of the large variability that is observed in practice between the results of nominally identical tests, and concludes that statistical methods should have far greater prominence than hitherto in all stages of migration research, and the drafting of legislation.     

A sizing method for stand-alone PV installations with variable demand

The practical applicability of the considerations made in a previous paper to characterize energy balances in stand-alone photovoltaic systems (SAPV) is presented. Given that energy balances were characterized based on monthly estimations, the method is appropriate for sizing installations with variable monthly demands and variable monthly panel tilt (for seasonal estimations).The method presented is original in that it is the only method proposed for this type of demand. The method is based on the rational utilization of daily solar radiation distribution functions. When exact mathematical expressions are not available, approximate empirical expressions can be used. The more precise the statistical characterization of the solar radiation on the receiver module, the more precise the sizing method given that the characterization will solely depend on the distribution function of the daily global irradiation on the tilted surface H_gβi.This method, like previous ones, uses the concept of loss of load probability (LLP) as a parameter to characterize system design and includes information on the standard deviation of this parameter (σ_LLP) as well as two new parameters: annual number of system failures (f) and the standard deviation of annual number of system failures (σ_f).This paper therefore provides an analytical method for evaluating and sizing stand-alone PV systems with variable monthly demand and panel inclination. The sizing method has also been applied in a practical manner.     

Discovering interobserver variability in the cytodiagnosis of breast cancer using decision trees and Bayesian networks

We evaluate the performance of two decision tree procedures and four Bayesian network classifiers as potential decision support systems in the cytodiagnosis of breast cancer. In order to test their performance thoroughly, we use two real-world databases containing 692 cases and 322 cases collected by a single observer and 19 observers, respectively. The results show that, in general, there are considerable differences in all tests (accuracy, sensitivity, specificity, PV+, PV− and ROC) when a specific classifier uses the single-observer dataset compared to those when this same classifier uses the multiple-observer dataset. These results suggest that different observers see different things: a problem known as interobserver variability. We graphically unveil such a problem by presenting the structures of the decision trees and Bayesian networks resultant from running both databases.     

Analysis of the variability of chloride threshold values in the literature

Efforts are being devoted in standards and construction codes in order to give rules and guidelines for designing durable structures. Also efforts are focused in developing the models in a more accurate approach to the calculation of the service life of concrete structures. Service life models consider that reinforced concrete exposed to chloride polluted environments initiate corrosion when a certain amount of chlorides arrives to the rebar surface. The so‐called chloride threshold level is considered as an essential parameter for assessing the probability of reinforcement corrosion, and becomes one of the key parameters needed for service life prediction, being of interest to have testing methods and expressions to introduce in the models. Numerous studies have been carried out to establish a critical chloride level for the onset of corrosion, but a wide range of chloride threshold values has been suggested which makes not feasible to define a single value. Present paper includes the analysis of the variability of the chloride threshold values published in the literature. Data from mortar and concrete and from laboratory and field exposure are compiled and included in the analysis. The influence of the testing method used for determination and several variables are considered.     

Alleviation of the acute stress response following mild orange essential oil administration

We investigated the effect of two different concentrations of orange aroma on peripheral and cardiac autonomic nervous system activity under a stressful condition in a highly reproducible manner. In the within‐subjects experiment, 19 subjects performed a 30‐min calculation task under three aroma conditions: 1% orange, 20% orange, and scentless air (control). Each aroma was delivered to the subject intermittently with the use of a proprietary olfactometer in a counter‐balanced order. Along with a visual analog scale (VAS), nose tip temperature and the cardiac activity on electrocardiograms were recorded throughout the experiment. Regardless of the aroma condition, significant decreases in nose tip temperature and the high‐frequency (HF) component of heart rate variability (HRV) and a significant increase in heart rate (HR) were observed during the task, denoting a typical acute stress response. However, the increase/decrease in HR and HF were significantly smaller with 1% orange than with 20% orange and the control condition, indicating an inhibition of sympathetic nervous system elevation and parasympathetic nervous system suppression. There were no significant differences between the two doses for the VAS scores. The findings suggest that mild orange essential oil inhalation inhibits the cardiac stress response while demonstrating no significant effect on subjective stress. © 2017 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.     

Statistical Variability Of Heat Penetration Parameters in Relation to Process Design

ABSTRACT: This study was undertaken to develop statistical approaches that can deal with variations in heating parameters when designing processes. In this context, the statistical variability of heat penetration parameters of a large amount of both hand-filled and machine-filled containers was investigated in different case studies. Two new statistical approaches are presented: an univariate and a bivariate statistical method. Both approaches appear successful for statistically based determination of heating parameters for process design. The statistical approaches also enable estimating the minimum number of heat penetration measurements to give reliable values to use in calculating safe thermal processes.     

Variability in captan residues in apples from a Canadian orchard

Apple trees in an orchard in Quebec, Canada were treated, following label directions, with the fungicide captan (1,2,3,6-tetrahydro-N-(trichloromethylthio)phthalimide) during the 2003 agricultural season. A total of 142 apples from three rows of trees were selected for determination of captan by GC/MS. Individual apples were found to contain captan levels ranging from 16.9 to 6350 ng g^-1. Only two individual apple samples exceeded the Canadian maximum residue limit (5000 ng g^-1) for captan in apples. Six composite samples, comprising half portions of eight individual apples, were analysed from each of the three experimental rows. Composite samples ranged in concentration from 166 to 2620 ng g^-1. The greatest uncertainty associated with the measured concentrations was due to variability among apples rather than the measurement of residue levels.     

A taxonomy of variability realization techniques

Development of software product families relies heavily on the use of variability to manage the differences between products by delaying design decisions to later stages of the development and usage of the constructed software systems. Implementation of variability is not a trivial task, and is governed by a number of factors. In this paper, we describe the factors that are relevant in determining how to implement variability, and present a taxonomy of variability realization techniques. Copyright © 2005 John Wiley & Sons, Ltd.