Large-scale gene expression measurement techniques provide a unique opportunity to gain insight into biological processes under normal and pathological conditions. To interpret the changes in ...expression profiles for thousands of genes, we face the nontrivial problem of understanding the significance of these changes. In practice, the sources of background variability in expression data can be divided into three categories: technical, physiological, and sampling. To assess the relative importance of these sources of background variation, we generated replicate gene expression profiles on high-density Affymetrix GeneChip oligonucleotide arrays, using either identical RNA samples or RNA samples obtained under similar biological states. We derived a novel measure of dispersion in two-way comparisons, using a linear characteristic function. When comparing expression profiles from replicate tests using the same RNA sample (a test for technical variability), we observed a level of dispersion similar to the pattern obtained with RNA samples from replicate cultures of the same cell line (a test for physiological variability). On the other hand, a higher level of dispersion was observed when tissue samples of different animals were compared (an example of sampling variability). This implies that, in experiments in which samples from different subjects are used, the variation induced by the stimulus may be masked by non-stimuli-related differences in the subjects' biological state. These analyses underscore the need for replica experiments to reliably interpret large-scale expression data sets, even with simple microarray experiments.
The aim of this study was to examine high-sensitivity troponin T and I (hsTnT and hsTnI) after a treadmill run under laboratory conditions and to find a possible connection with echocardiographic, ...laboratory and other assessed parameters. Nineteen trained men underwent a standardized 2-hour-long treadmill run. Concentrations of hsTnT and hsTnI were assessed before the run, 60, 120 and 180 minutes after the start and 24 hours after the run. Changes in troponins were tested using non-parametric analysis of variance (ANOVA). The multiple linear regression model was used to find the explanatory variables for hsTnT and hsTnI changes. Values of troponins were evaluated using the 0h/1h algorithm. Changes in hsTnT and hsTnI levels were statistically significant (p<0.0001 and p<0.0001, respectively). In a multiple regression model (adjusted R
: 0.60, p=0.005 for hsTnT and adjusted R
: 0.60, p=0.005 for hsTnI), changes in both troponins can be explained by relative left wall thickness (LV), training volume, body temperature after the run and creatinine changes. According to the 0h/1h algorithm, none of the runners was evaluated as negative. Relative LV wall thickness, creatinine changes, training volume and body temperature after the run can predict changes in hsTnT and hsTnI levels. When medical attention is needed after physical exercise, hsTn levels should be tested only when clinical suspicion and the patient’s history indicate a high probability of myocardial damage.
The rapid development in the field of electric vehicles requires a careful evaluation of the design process. The presence of a simulation model of the electric vehicle can effectively detect many ...faulty areas during the development process without risks. The MATLAB and Simulink environment is considered one of the most important tools used in the simulation process. In this paper, we will present the model of electric car used for transporting postal parcels (postal cars). The model includes simulating the operation of a permanent magnet synchronous electric motor. We will assume that the car is moving according to a driving cycle. The results will show the torque forces required to achieve the required speed. We will further calculate the traction and the resistance forces during the driving cycle and the engine efficiency in addition. Perhaps the most important problem facing electric car designers is calculating the amount of energy consumed from the battery or hydrogen fuel, and this is what was achieved as the result of the simulation process in this research. In the end, use one of the artificial intelligence tools (fuzzy controller) to improve battery life by providing the electric car driver with an alert system that will increase the ability to monitor the battery condition and thus increase battery life. The benefit of this paper emerges in realizing the importance of modeling and using simulation using artificial intelligence in developing the design of the electric car, specially the electric motor and battery size, and thus achieving one of the most important goals of the United Nations of preserving the environment and reducing carbon emissions.
Tumors of low malignant potential (LMP) represent 20% of epithelial ovarian cancers (EOCs) and are associated with a better prognosis than the invasive tumors (TOV). Defining the relationship between ...LMPs and TOVs remains an important goal towards understanding the molecular pathways that contribute to prognosis, as well as providing molecular markers, for these EOCs. To this end, DNA microarray analyses were performed either in a primary culture or a tumor tissue model system and selected candidate genes showing a distinctive expression profile between LMPs and TOVs were identified using a class prediction approach based on three statistical methods of analysis. Both model systems appear relevant as candidate genes identified by either model allowed the proper reclassification of samples as either LMPs or TOVs. Selected candidate genes (CAS, CCNE1, LGALS8, ITGbeta3, ATP1B1, FLIP, KRT7 and KRT19) were validated by real-time quantitative PCR analysis and show differential expression between LMPs and TOVs. Immunohistochemistry analyses showed that the two tumor classes were distinguishable by their expression of CAS, TNFR1A, FLIP, CKS1 and CCNE1. These results define signature patterns for gene expression of LMPs and TOVs and identify gene candidates that warrant further study to deepen our understanding of the biology of EOC.
Gene expression microarray technology continues to evolve and its use has expanded into all areas of biology. However, the high dimensionality of the data makes analysis a difficult challenge. ...Evaluating measurements and estimating the significance of the observed differences among samples remain important issues that must be addressed for each technology platform. In this work we use a consecutive sampling method to characterize the dispersion patterns of data generated from Illumina fiberoptic bead-based oligonucleotide arrays.
To describe general properties of the dispersion we used a linear function SD = a + bY(mean), approximating the standard deviation across arrays (Y(mean) is the mean expression of a given consecutive sample). First we examined three levels of variability: 1) same cell culture, same reverse transcription, duplicate hybridizations; 2) same cell culture, reverse transcription replicates; 3) parallel cultures. Each higher level is expected to introduce a new source of variability. We observed minor differences in the constant term: the mean values are 3.5, 3.1 and 3.5, respectively. However, the mean coefficient b increased from 0.045 to 0.147 and 0.133. We compared the coefficients derived from the consecutive sampling to those obtained from the standard deviation of individual gene expressions and found them in good agreement. In the second experiment samples we detected 11 genes with systematically different expressions between the experiment samples treated with glucose oxidase and controls and corroborated the selection using the Mann-Whitney and other tests. We also compared the consecutive sampling and coincidence method to t-test: the average percentage of consistency was above 80 for the former and below 50 for the latter.
Our results indicate that the consecutive sampling method and standard deviation function provide a convenient description of the overall dispersion of Illumina arrays. We observed that the constant term of the standard deviation function is at average approximately the same for duplicate hybridization as for the assays with additional sources of variability. Furthermore, among the genes affected by glucose oxidase treatment we identified 6 genes in oxidative stress pathways and 5 genes involved in DNA repair. Finally, we noted that the consecutive sampling and coincidence test provide, under given conditions, more consistent results than the t-test.
This article was reviewed by Alexander Karpikov (nominated by Mark Gerstein), Jordan King and Eugene V. Koonin.
The level of cardiorespiratory capacity, as measured by maximum VO(2)max oxygen consumption, is a significant factor related to the risk of metabolic syndrome, coronary heart disease and other health ...disorders. A total cohort of 2901 examinations was divided into 5 groups according to the nature of physical activity: group A - endurance athletes, group B - team sports players, group C - other competitive athletes, group D - recreational leisure-time athletes, group E - people with health problems. Cardiorespiratory fitness was assessed according to the VO(2)max and METmax parameters found in the stress test on a bicycle ergometer. A gradually increased load until exhaustion was used. While in groups A to D cases that would be classified as NYHA 1 (METmax lower than 9) were quite rare (10 cases out of 2777, i.e. 0.3 %), in groups E it was 20 % in men (16 cases out of 82) and 52 % in women (23 cases out of 44) of those examined. Accordingly, fitness age in groups A, B and C generally corresponded to a lower age than the calendar age, in groups E of both men and women, fitness age was significantly higher compared to the calendar age. High fitness age represents a significant risk of morbidity in relation to non-communicable diseases and probably also a significant limitation of their quality of life in later age.
•Building a MATLAB Simulink model to simulate an electric vehicle on a drive cycle.•Simulate tow cases: with battery capacity 75 kw, with hydrogen fuel cell capacity 75 kw.•Simulate tow dive cycle: ...proposed drive cycle, real drive cycle (NEDC).•Compare distance and power consumption in both.•The future is in favor of hydrogen fuel cells rather than lithium batteries, despite the fact that the later are still feasible now.
This research puts forward the modeling of a Hydrogen Fuel Cell Electric Vehicle (HFCEV) and its validation, in comparison with battery electrical vehicle (BEV) based on a postal vehicle and its subsystems. The main investigation parameters are the amount of hydrogen consumed, and the change in the state of charging of the battery. For the profile of the same speed route, an HFCEV model and a BEV model, consisting of multiple subsystems, were developed, and simulated in the MATLAB® Simulink environment. We make use of various sources of drive cycles to obtain our outcomes such as the New European Diving Cycle (NEDC). By running simulations for different stages, we are able to generate simulation results. The discrepancies in the graphs and the visual demonstrations guided us to variable conclusions on how different factors affect an electric vehicle’s performance and efficiency. The simulation result shows that the (BEV) is 30% more effective for NEDC drive cycle comparing with (HFCEV).
Cystic fibrosis (CF) is caused by a defect in the CF transmembrane conductance regulator (CFTR) protein that functions as a chloride channel. Dysfunction of the CFTR protein results in salty sweat, ...pancreatic insufficiency, intestinal obstruction, male infertility, and severe pulmonary disease. Most of the morbidity and mortality of CF patients results from pulmonary complications. Differences in susceptibility to bacterial infection and variable degree of CF lung disease among CF patients remain unexplained. Many phenotypic expressions of the disease do not directly correlate with the type of mutation in the Cftr gene. Using a unique CF mouse model that mimics aspects of human CF lung disease, we analyzed the differential gene expression pattern between the normal lungs of wild-type mice (WT) and the affected lungs of CFTR knockout mice (KO). Using microarray analysis followed by quantitation of candidate gene mRNA and protein expression, we identified many interesting genes involved in the development of CF lung disease in mice. These findings point to distinct mechanisms of gene expression regulation between mice with CF and control mice.
V první části článku jsou prezentovány hlavní vlastnosti a výhody trakčních napájecích stanic pro soustavu 25 kV 50 Hz s nepřímými polovodičovými měniči. V další části jsou uvedeny informace o ...perspektivní měničové struktuře pro tyto napájecí stanice. Hlavní část článku je věnována teoretické analýze metody pro synchronizované řízení výkonu napájecích stanic s polovodičovými měniči.
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