Reactive oxygen species (ROS) are a by-product of aerobic metabolism and have been implicated in cancer, arthrosclerosis, diabetes and aging. Antioxidant enzymes, such as superoxide dismutase (SOD), work to neutralize ROS and oxidative stress occurs when the antioxidant capacity of the cell is overwhelmed. Using a Drosophila mutant with defective cytoplasmic SOD function (cSODn108), we are able to study the consequences of excess ROS on gene expression. Microarray experiments indicate gene expression changes associated with immune response, heat shock, detoxification, proteolysis, carbohydrate metabolism, lipid metabolism and behaviour. Behavioural and physiological assays investigated possible phenotypes predicted by changes in gene expression. We found that cSODn108 mutants feed less yet demonstrate a remarkable resistance to starvation. In addition, cSODn108 mutants show a reduced response to sucrose, odorants and decreased locomotor activity. These phenotypes correlate with observed gene expression changes and suggest a potentially altered energy metabolism in response to chronic oxidative stress.

The global gene expression profiles of industrial strains of <i>Saccharomyces cerevisiae</i> responding to nitrogen deficiency and very high sugar concentrations stresses were determined by oligonucleotide microarray analysis of ~ 6200 yeast open reading frames. Genomics analysis showed that 400 genes in S. cerevisiae was differentially expressed by more than 1.5-fold compared with controls at late-logarithmic phase of fermentation, as the yeast adapted to changing nutritional, environmental and physiological conditions. The genes of many pathways are regulated in a highly coordinated manner. The repressed expression of GDH1 and up-regulation of ARO10 within the contrast of Q270/Q10 indicated high energy demanding of yeast cells under high sugar stress. Activities of G3P shuttle indicated that under very high gravity environment, sufficient assimilatory nitrogen enhances yeasts ability of redox balancing, and therefore higher stress-tolerance and higher fermentation efficiency of yeast. Under contrast W270/Q270, the up-regulation of DUR1,2 responsible for urea degradation induces the glutamate biosynthesis and the consumption of -ketoglutarate. This may indicate that higher nitrogen level would enable higher activities in the TCA cycle, and therefore generate more energy for biosynthesis and yeast cell proliferation under very high gravity fermentation conditions. Nitrogen metabolism was also stimulated by high nitrogen level when yeast was grown in very high gravity environment.

This report discusses simulators in automata theory and which one should be best for use in laboratory assignments. Currently, the Formal Languages, Automata and Theory of Computation course (FABER) at Mälardalen University uses the JFLAP simulator for extra exercises. To see if any other simulators would be useful either along with JFLAP or standalone, tests were made with nine programs that are able to graphically simulate automata and formal languages. This thesis work started by making an overview of simulators currently available.After the reviews it has become clear to the author that JFLAP is the best choice for majority of cases. JFLAP is also the most popular simulator in automata theory courses worldwide.To support the use of JFLAP for the course a manual and course assignments are created to help the student to getting started with JFLAP. The assignments are expected to replace the current material in the FABER course and to help the uninitiated user to get more out of JFLAP.

The purpose of this study was to determine what the immediate effects of a relaxation treatment had upon the subject's perception of facial expression of emotion with state anxiety held constant. Specifically, this study attempted to compare subjects who received a 25-minute taped recorded relaxation treatment with subjects who did not receive the relaxation treatment and subsequent perception of facial expression of emotion. The research hypothesis was stated in the null form.A review of the relevant literature available on facial expression of emotion, relaxation treatment, and training programs designed for therapists supported the need for the study. In addition, the research indicated that techniques for reliably evaluating facial expression of emotion were not extant.All subjects for the study were graduate level students enrolled in at least one Guidance and Counseling course offered. spring quarter, 1978, at a midwestern university. The university's Research Computing Unit randomly selected 80 subjects from the total population of 167 potential. subjects. Randomly selected subjects were then randomly assigned to either the experimental group or study two the control group. The sex of the subject was controlled for in the random assignment of subjects to each group. Each group, experimental and control, consisted of 20 males and 20 females. Experimental group subjects ranged in age from 22 to 40, with a mean age of 29.8. Control group subjects ranged in age from 22 to 57, with a mean age of 30.7. The total of 80 randomly selected subjects who participated in this study were scheduled to participate in the at one time.The Multiple Affect Adjective Check List, Today Form (MAACL) was used to obtain the subject's state anxiety score (the covariate measure). Following the administration of the MAACL, experimental group subjects received a 25-minute tape recorded relaxation treatment. The Pictures of Facial Affect (PFA) was administered to both groups to measure the subject's perception of facial expression of emotion. The PFA consists of 110 high quality slides which depict 7 facial expressions of emotion. The 7 subtests of, the PFA include: happy, sad, fear, anger, surprise, disgust, and neutral. The PFA was administered to the experimental group following the relaxation treatment. The control group, which received no treatment, was given the PFA following the administration of the MAACL.Preliminary to the analysis of data, a KR-20 subtest analysis conducted on the PFA resulted in discarding subtests happy, fear, and surprise. These subtests lacked internal reliability. Further, the null hypothesis of no relation between the covariate (state anxiety as measured by the MAACL) and the set of selected dependent of the PFA was not rejected. The revised null hypothesis was tested through a multivariate analysis of variance. An F test significant at the .05 level was set. The results of the analysis indicated the revised null hypothesis was not rejected. Under the constraints of the study, the following conclusion was made. No significant differences were found between subjects who received relaxation treatment and subjects who did not receive relaxation treatment and subsequent perception of facial expression of emotion as measured by the PFA. However, an additional finding of the study was significant difference between men and women end their perception of facial expression of emotion. Suggestions for future research were offered based upon the analysis of data.

Dioxins are environmental contaminants that raise concern because they are potent and persistent. The most potent dioxin congener, 2,3,7,8-tetrachlorodibenzo-p-dioxin (TCDD), causes a wide variety of biochemical and toxic effects in laboratory animals and in humans. Major toxicities of TCDD are initiated by their binding to the AH receptor (AHR), a ligand-activated transcription factor that regulates expression of numerous genes. However, the specific genes whose dysregulation leads to major toxicities such as wasting, hepatotoxicity, and lethality are unknown. The objective of this thesis research was to identify the molecular mechanisms by which dioxins cause lethality. To this end, a powerful genetic rat model was utilized – the Han/Wistar (Kuopio) rat which is highly resistant to dioxin toxicity due to a major deletion in the AHR’s transactivation domain (TAD) leading to 3 potential AHR variant transcripts. We found that insertion-variant transcripts (IVs) are the dominant forms of AHR expressed in H/W rats, constitutively and after TCDD treatment. Gene expression array analysis revealed that the total number of TCDD-responsive genes in liver was significantly lower in H/W rats (that carry the TAD deletion) than in dioxin-sensitive rats (that carry wildtype AHR). Genes that are well-known to be AHR-regulated and dioxin-inducible  such as CYP1 transcripts  remained responsive to TCDD in H/W rats; thus the TAD deletion selectively interferes with expression of a subset of hepatic genes rather than abolishing global AHR-mediated responses. Genes that differed in response to TCDD between dioxin-sensitive rats and dioxin-resistant rats are integral parts of pathways known to be disrupted by dioxin treatment such as protein synthesis/degradation, fatty acid transport/metabolism, and apoptosis. These genes are worthy candidates for further mechanistic studies to test their role in major dioxin toxicities. Numerous differentially-regulated genes were downregulated; however, microRNAs, which downregulate mRNA levels in other systems, likely play no role in downregulation of mRNAs by dioxins in adult liver and are unlikely to be involved in hepatotoxicity. Findings in this research support the hypothesis that H/W rats are resistant to TCDD lethality because the TAD deletion prevents the AHR from dysregulating specific mRNA transcripts but not hepatic miRNAs.

The unspliced 9kb HIV-1 RNA (encoding Gag and GagPol) can undergo multiple splicing events to produce members of the 4kb (encoding Env, Vif, Vpr, and Vpu) or 2kb (encoding Tat, Rev and Nef), respectively. The incompletely spliced 9 and 4kb viral RNAs are exported by HIV-1 Rev which interacts with the RRE (Rev responsive element) in these RNAs as well as the nuclear export receptor Crm1. Several proteins can modulate Rev function and/or HIV-1 gene expression, including the nuclear phosphorprotein Sam68. We have found that overexpression of Sam68 stimulates HIV-1 structural gene expression and increases the proportion of unspliced, 3’ end processed viral RNA. This activity requires the RNA binding activity of Sam68. Surprisingly, Sam68 overexpression does not increase the proportion of unspliced, cleaved RNA found in the cytoplasm, suggesting that Sam68 alters the viral RNP to increase its translation. The Sam68 related proteins Slm1 and Slm2 also stimulate 3’ end cleavage and expression of unspliced HIV-1 RNAs. Sam68 and Slm2 were expressed in Hela cells, whereas Slm1 was not. Therefore, we reduced Sam68 expression alone or in combination with Slm2 to determine if these proteins were required for HIV-1 RNA processing or expression. Knockdown of Sam68 and/or Slm2 had little to no effect on viral RNA cleavage or structural gene expression from transiently transfected reporters. Furthermore, depletion of Sam68 only slightly reduced Gag expression from a stably expressed proviral reporter. These results suggest that additional redundant proteins may be present that functionally replace Sam68 and Slm2. We defined a region encompassing the N-terminal GSG (GRP33, Sam68, Gld1) and KH RNA binding motif as the minimal region of Sam68 required to stimulate HIV-1 gene expression in 293 and 293T cells. The minimal mutant enhanced unspliced RNA cleavage in 293T, but not in 293 cells suggesting that Sam68 may act at other stage of the viral lifecycle to increase gene expression.

Pasture feeding depresses adipose tissue development in beef cattle whereas grain feeding, enhances adipogenesis. Therefore, we hypothesized that specific fatty acids would differentially affect lipogenesis in explants of bovine subcutaneous (SC) and intramuscular (IM) adipose tissues. Angus steers were harvested at 12, 14, and 16 mo of age, and IM and SC adipose tissue explants from the 8-11th thoracic rib region were dissected and cultured in media. Media contained no supplemental fatty acids or 40 microM of five fatty acids, stearic acid (18:0), oleic acid (18:1 n-9), trans-11 vaccenic acid (18:1 trans-11), conjugated linoleic acid (CLA, 18:2 trans-10, cis-12), or alpha-linolenic acid (18:3 n-3). After 48 h of culture, lipogenesis using [U-14C]glucose and [1-14C]acetate was measured. Lipogenesis from glucose decreased between 12 and 16 mo of age in SC adipose tissue (from 8.9 to 4.0 nmol per 2 h per 100 mg; P = 0.001) and IM adipose tissue (from 4.4 to 2.7 nmol per 2 h 100 mg ; P = 0.08). Lipogenesis from acetate did not change over time in SC adipose (approximately 56 nmol per 2 h per 100 mg; P = 0.23), but increased over time in IM adipose tissue (from from 11.3 to 17.1 nmol per 2 h 100 mg; P = 0.02). Oleic acid increased lipid synthesis from glucose 125 percent (P = 0.04) in IM adipose tissue, whereas stearic acid and trans-vaccenic acid increased lipogenesis from glucose in SC adipose tissue by approximately 50 percent (P = 0.04). In SC adipose tissue only, trans-vaccenic and increased, lipogenesis from glucose (P < 0.02). Lipogenesis from acetate was depressed by CLA nearly 50 percent in SC adipose tissue. PPARγ gene expression increased between 14 and 16 mo of age in control IM and SC adipocytes. The increase in activity was also observed in AMPK gene expression. C/EBPβ and SCD gene expression did not increase in control samples until 16 mo of age. SC adipose tissue responded to stearic acid by increased GPR43 and AMPK gene expression at 12 mo of age. We conclude that fatty acids differentially affect lipid synthesis in IM and SC adipose tissues, which may account for the effects of pasture and grain feeding on adiposity.

Programmed Cell death (PCD) is a highly conserved and genetically controlled event that plays important roles in animal development, homeostasis and disease. Our first objective was to discover and characterize new genes involved in PCD. Since many PCD genes are conserved in Drosophila, and steroid-induced PCD of larval salivary glands (SGs) is transcriptionally regulated with features of both apoptosis and autophagy, we used this exceptionally well-suited in vivo system and performed Serial Analysis of Gene Expression (SAGE) in three pre-death stages. SAGE identified 1244 expressed transcripts, including genes involved in autophagy, apoptosis, immunity, cytoskeleton remodeling, and proteolysis. Of the 1244 transcripts, 463 transcripts belonged to knownlpredicted genes and were 5-fold differentially expressed prior to cell death. Next, we investigated the role of differentially expressed genes from SAGE, in cell death or cell survival, by RNA interference (RNAi ) in l(2)mbn haemocyte Drosophila cells. l(2)mbn cells undergo morphological changes in response to ecdysone treatment, and ultimately undergo PCD. We used cell viability, cell morphology, and apoptosis assays to identify the death-related genes and determined their ecdysone dependency and function in cell death regulation. Our RNAi screen identified six new pro-death related genes, including SH3PXJ and Soxl4, and 21 new pro-survival genes including SoxN. Identification of Soxl4 as pro-death and SoxN as pro-survival suggests that these Sox box proteins may have opposing roles in ecdysone-mediated cell death. Our final objective was to elucidate the function of CG409], a Drosophila homologue of human TNF-alpha induced proteins 8 (TNFAIP8) we identified from SAGE. We created loss-of-function and overexpression mutants of CG4091 to study gene function in vivo and employed immunoprecipitation and mass-spectrometry assays to identify proteins interacting with CG409] in vitro. We identified two proteins that are involved in n-fatty acid oxidation and several cytoskeletal proteins as interaction partners. Immunofluorescence based assays in vivo and in vitro revealed that CG409] is necessary for cytoskeletal remodeling. Further, defects in CG4091 expression affect cellular functions such as autophagy and lipid metabolism/trafficking that require an intact cytoskeleton. Together, our studies provided new insights into the molecular mechanisms involved in Drosophila SG cell death.

A key requirement for developing any innovative system in a computing environment is to integrate a sufficiently friendly interface with the average end user. Accurate design of such a user-centered interface, however, means more than just the ergonomics of the panels and displays. It also requires that designers precisely define what information to use and how, where, and when to use it. Facial expression as a natural, non-intrusive and efficient way of communication has been considered as one of the potential inputs of such interfaces. The work of this thesis aims at designing a robust Facial Expression Recognition (FER) system by combining various techniques from computer vision and pattern recognition. Expression recognition is closely related to face recognition where a lot of research has been done and a vast array of algorithms have been introduced. FER can also be considered as a special case of a pattern recognition problem and many techniques are available. In the designing of an FER system, we can take advantage of these resources and use existing algorithms as building blocks of our system. So a major part of this work is to determine the optimal combination of algorithms. To do this, we first divide the system into 3 modules, i.e. Preprocessing, Feature Extraction and Classification, then for each of them some candidate methods are implemented, and eventually the optimal configuration is found by comparing the performance of different combinations. Another issue that is of great interest to facial expression recognition systems designers is the classifier which is the core of the system. Conventional classification algorithms assume the image is a single variable function of a underlying class label. However this is not true in face recognition area where the appearance of the face is influenced by multiple factors: identity, expression, illumination and so on. To solve this problem, in this thesis we propose two new algorithms, namely Higher Order Canonical Correlation Analysis and Simple Multifactor Analysis which model the image as a multivariable function. The addressed issues are challenging problems and are substantial for developing a facial expression recognition system.

A key requirement for developing any innovative system in a computing environment is to integrate a sufficiently friendly interface with the average end user. Accurate design of such a user-centered interface, however, means more than just the ergonomics of the panels and displays. It also requires that designers precisely define what information to use and how, where, and when to use it. Facial expression as a natural, non-intrusive and efficient way of communication has been considered as one of the potential inputs of such interfaces. The work of this thesis aims at designing a robust Facial Expression Recognition (FER) system by combining various techniques from computer vision and pattern recognition. Expression recognition is closely related to face recognition where a lot of research has been done and a vast array of algorithms have been introduced. FER can also be considered as a special case of a pattern recognition problem and many techniques are available. In the designing of an FER system, we can take advantage of these resources and use existing algorithms as building blocks of our system. So a major part of this work is to determine the optimal combination of algorithms. To do this, we first divide the system into 3 modules, i.e. Preprocessing, Feature Extraction and Classification, then for each of them some candidate methods are implemented, and eventually the optimal configuration is found by comparing the performance of different combinations. Another issue that is of great interest to facial expression recognition systems designers is the classifier which is the core of the system. Conventional classification algorithms assume the image is a single variable function of a underlying class label. However this is not true in face recognition area where the appearance of the face is influenced by multiple factors: identity, expression, illumination and so on. To solve this problem, in this thesis we propose two new algorithms, namely Higher Order Canonical Correlation Analysis and Simple Multifactor Analysis which model the image as a multivariable function. The addressed issues are challenging problems and are substantial for developing a facial expression recognition system.