Ethobehavioral Studies of Fear, Sex, and Biological Rhythms

Thesis (Ph.D.)--University of Washington, 2016-06

Estimates of sex- and age-class-specific survival probabilities for a southern Great Barrier Reef green sea turtle population

Sex- and age-class-specific survival probabilities of a southern Great Barrier Reef green sea turtle population were estimated using a capture - mark - recapture (CMR) study and a Cormack - Jolly - Seber (CJS) modelling approach. The CMR history profiles for 954 individual turtles tagged over a 9-year period ( 1984 - 1992) were classified into three age classes ( adult, subadult, juvenile) based on somatic growth and reproductive traits. Reduced-parameter CJS models, accounting for constant survival and time-specific recapture, fitted best for all age classes. There were no significant sex-specific differences in either survival or recapture probabilities for any age class. Mean annual adult survival was estimated at 0.9482 (95% CI: 0.92 - 0.98) and was significantly higher than survival for either subadults or juveniles. Mean annual subadult survival was 0.8474 ( 95% CI: 0.79 - 0.91), which was not significantly different from mean annual juvenile survival estimated at 0.8804 ( 95% CI: 0.84 - 0.93). The time-specific adult recapture probabilities were a function of sampling effort but this was not the case for either juveniles or subadults. The sampling effort effect was accounted for explicitly in the estimation of adult survival and recapture probabilities. These are the first comprehensive sex- and age-class-specific survival and recapture probability estimates for a green sea turtle population derived from a long-term CMR program.

Themes in songs written by clients with traumatic brain injury: Differences across the Lifespan

This study aimed to identify age differences in the themes of songs written by patients with traumatic brain injury (TBI). Lyrics from 82 songs written by 11 female and 20 male patients aged between 5 and 60 years were categorised into eight themes and 24 categories. Incidence of categories and themes were calculated and compared across six age brackets. Results suggest that children, early adolescent, and middle adolescent patients with TBI focus on memories to a substantially greater degree than older patients. Early and late adolescent patient groups are most likely to be self-reflective, and to raise concerns about the future, when compared with other patient groups. (author abstract)

The relationship between self-awareness of attentional status, behavioral performance and oscillatory brain rhythms

High-level cognitive factors, including self-awareness, are believed to play an important role in human visual perception. The principal aim of this study was to determine whether oscillatory brain rhythms play a role in the neural processes involved in self-monitoring attentional status. To do so we measured cortical activity using magnetoencephalography (MEG) and functional magnetic resonance imaging (fMRI) while participants were asked to self-monitor their internal status, only initiating the presentation of a stimulus when they perceived their attentional focus to be maximal. We employed a hierarchical Bayesian method that uses fMRI results as soft-constrained spatial information to solve the MEG inverse problem, allowing us to estimate cortical currents in the order of millimeters and milliseconds. Our results show that, during self-monitoring of internal status, there was a sustained decrease in power within the 7-13 Hz (alpha) range in the rostral cingulate motor area (rCMA) on the human medial wall, beginning approximately 430 msec after the trial start (p < 0.05, FDR corrected). We also show that gamma-band power (41-47 Hz) within this area was positively correlated with task performance from 40-640 msec after the trial start (r = 0.71, p < 0.05). We conclude: (1) the rCMA is involved in processes governing self-monitoring of internal status; and (2) the qualitative differences between alpha and gamma activity are reflective of their different roles in self-monitoring internal states. We suggest that alpha suppression may reflect a strengthening of top-down interareal connections, while a positive correlation between gamma activity and task performance indicates that gamma may play an important role in guiding visuomotor behavior. © 2013 Yamagishi et al.

Un -equal opportunity: Sex and school among first and second generation Mexican immigrant adolescent girls

The purpose of this dissertation was to determine the interactions of sexuality and education among low socioeconomic status first and second generation Mexican immigrant adolescent girls. Much of the existing research differentiates between immigrant generations with little examination of the differences within a particular immigrant generation. This study utilized qualitative methods to examine how various social institutions intersected to influence the young women's decisions about education and sexuality. The methodology included more than three years of participant observation in a South Florida high school and surrounding community; structured and unstructured interviews with twenty young women, their family members, school personnel, and community activists; and surveys conducted with the young women and their parent or guardian. ^ Moving beyond the limits of essentialist immigration theories, this project revealed within group (i.e. immigrant generation) complexities as well as between group similarities. The data included in this dissertation delineate how relationships of power and control permeated the lives of first and second generation Mexican immigrant adolescent girls. The lens of this dissertation is focused on the salient issues of sexuality and education: two dominant forces in many adolescent lives. ^ I found the young women represented a variety of positions on the academic orientation and sexuality continuums and engaged in activities that both reinforced and countered their stated positions on each of these issues. Specifically, first and second generation immigrants are often viewed as maintaining opposing viewpoints about both education and female sexuality however, for these young women the within group variation was larger than the between group variation. While all the young women in this study expressed a belief in the value of education, they engaged in activities that both fortified and contradicted that expressed position. Additionally, although acculturation can lead to increased sexual activity and decreased engagement with education, the first generation immigrant young women in this study became pregnant and/or withdrew from school in equal proportions to their second generation counterparts. In summary, structural forces combined, often inadvertently, and contributed to these young women's spiraling negative academic orientation and/or rational choice of motherhood. Finally, the findings are linked to policy implications. ^

Performance Evaluation of a Statistical and a Neural Network Model for Nonrigid Shape-Based Registration

Shape-based registration methods frequently encounters in the domains of computer vision, image processing and medical imaging. The registration problem is to find an optimal transformation/mapping between sets of rigid or nonrigid objects and to automatically solve for correspondences. In this paper we present a comparison of two different probabilistic methods, the entropy and the growing neural gas network (GNG), as general feature-based registration algorithms. Using entropy shape modelling is performed by connecting the point sets with the highest probability of curvature information, while with GNG the points sets are connected using nearest-neighbour relationships derived from competitive hebbian learning. In order to compare performances we use different levels of shape deformation starting with a simple shape 2D MRI brain ventricles and moving to more complicated shapes like hands. Results both quantitatively and qualitatively are given for both sets.

Argaric Sociology: Sex and Death

The detailed, rich and diverse Argaric funerary record offers an opportunity to explore social dimensions that usually remain elusive for prehistoric research, such us social rules on kinship rights and obligations, sexual tolerance and the role of funerary practices in preserving the economic and political organization. This paper addresses these topics through an analysis of the social meaning of Argaric double tombs by looking at body treatment and composition of grave goods assemblages according to gender and class affiliation. The Argaric seems to have been a conservative society, scarcely tolerant regarding homosexuality, and willing to celebrate ancestry associated to certain places as a means of asserting residence and property rights.

Functional, clustered, feedforward, and mesoscale brain networks

The brain is a network spanning multiple scales from subcellular to macroscopic. In this thesis I present four projects studying brain networks at different levels of abstraction. The first involves determining a functional connectivity network based on neural spike trains and using a graph theoretical method to cluster groups of neurons into putative cell assemblies. In the second project I model neural networks at a microscopic level. Using diferent clustered wiring schemes, I show that almost identical spatiotemporal activity patterns can be observed, demonstrating that there is a broad neuro-architectural basis to attain structured spatiotemporal dynamics. Remarkably, irrespective of the precise topological mechanism, this behavior can be predicted by examining the spectral properties of the synaptic weight matrix. The third project introduces, via two circuit architectures, a new paradigm for feedforward processing in which inhibitory neurons have the complex and pivotal role in governing information flow in cortical network models. Finally, I analyze axonal projections in sleep deprived mice using data collected as part of the Allen Institute's Mesoscopic Connectivity Atlas. After normalizing for experimental variability, the results indicate there is no single explanatory difference in the mesoscale network between control and sleep deprived mice. Using machine learning techniques, however, animal classification could be done at levels significantly above chance. This reveals that intricate changes in connectivity do occur due to chronic sleep deprivation.

Evaluating gene by sex and age interactions on cardiovascular risk factors in Brazilian families

Background: In family studies, it is important to evaluate the impact of genes and environmental factors on traits of interest. In particular, the relative influences of both genes and the environment may vary in different strata of the population of interest, such as young and old individuals, or males and females. Methods: In this paper, extensions of the variance components model are used to evaluate heterogeneity in the genetic and environmental variance components due to the effects of sex and age (the cutoff between young and old was 43 yrs). The data analyzed were from 81 Brazilian families (1,675 individuals) of the Baependi Family Heart Study. Results: The models allowing for heterogeneity of variance components by sex suggest that genetic and environmental variances are not different in males and females for diastolic blood pressure, LDL-cholesterol, and HDL-cholesterol, independent of the covariates included in the models. However, for systolic blood pressure, fasting glucose and triglycerides, the evidence for heterogeneity was dependent on the covariates in the model. For instance, in the presence of sex and age covariates, heterogeneity in the genetic variance component was suggested for fasting glucose. But, for systolic blood pressure, there was no evidence of heterogeneity in any of the two variance components. Except for the LDL-cholesterol, models allowing for heterogeneity by age provide evidence of heterogeneity in genetic variance for triglycerides and systolic and diastolic blood pressure. There was evidence of heterogeneity in environmental variance in fasting glucose and HDL-cholesterol. Conclusions: Our results suggest that heterogeneity in trait variances should not be ignored in the design and analyses of gene-finding studies involving these traits, as it may generate additional information about gene effects, and allow the investigation of more sophisticated models such as the model including sex-specific oligogenic variance components.

Differential expression of 12 histone deacetylase (HDAC) genes in astrocytomas and normal brain tissue: class II and IV are hypoexpressed in glioblastomas

Background: Glioblastoma is the most lethal primary malignant brain tumor. Although considerable progress has been made in the treatment of this aggressive tumor, the clinical outcome for patients remains poor. Histone deacetylases (HDACs) are recognized as promising targets for cancer treatment. In the past several years, HDAC inhibitors (HDACis) have been used as radiosensitizers in glioblastoma treatment. However, no study has demonstrated the status of global HDAC expression in gliomas and its possible correlation to the use of HDACis. The purpose of this study was to evaluate and compare mRNA and protein levels of class I, II and IV of HDACs in low grade and high grade astrocytomas and normal brain tissue and to correlate the findings with the malignancy in astrocytomas. Methods: Forty-three microdissected patient tumor samples were evaluated. The histopathologic diagnoses were 20 low-grade gliomas (13 grade I and 7 grade II) and 23 high-grade gliomas (5 grade III and 18 glioblastomas). Eleven normal cerebral tissue samples were also analyzed (54 total samples analyzed). mRNA expression of class I, II, and IV HDACs was studied by quantitative real-time polymerase chain reaction and normalized to the housekeeping gene beta-glucuronidase. Protein levels were evaluated by western blotting. Results: We found that mRNA levels of class II and IV HDACs were downregulated in glioblastomas compared to low-grade astrocytomas and normal brain tissue (7 in 8 genes, p < 0.05). The protein levels of class II HDAC9 were also lower in high-grade astrocytomas than in low-grade astrocytomas and normal brain tissue. Additionally, we found that histone H3 (but not histone H4) was more acetylated in glioblastomas than normal brain tissue. Conclusion: Our study establishes a negative correlation between HDAC gene expression and the glioma grade suggesting that class II and IV HDACs might play an important role in glioma malignancy. Evaluation of histone acetylation levels showed that histone H3 is more acetylated in glioblastomas than normal brain tissue confirming the downregulation of HDAC mRNA in glioblastomas.

Influences of sex and age on biological rhythms of serum lipids and lipoproteins

Background: Few studies have evaluated seasonal variations of biochemical parameters routinely analyzed in clinical laboratories. Rhythmic patterns for lipids and lipoproteins have been demonstrated and have been the object of research, mainly because of their demonstrated association with coronary artery disease. This study evaluated the occurrence of biological rhythms on serum lipids and lipoproteins and the effects of sex and age on the rhythms in a Brazilian hospital outpatient population. Methods: Retrospective laboratory study was carried out to evaluate the results of total cholesterol (TC), HDL-cholesterol (HDL-C), LDL-cholesterol (LDL-C) and triglycerides (TG), from individuals registered at a university referral hospital over 8years. The studied population was composed of individuals of both sexes and all ages totaling 38,579 participants and 301,934 measurements. Statistical analyses were carried out using the SAS program and the temporal analysis used the Cosinor method. Results: TG rhythm was present only in females. All other parameters were equally rhythmic in both sexes. Regarding age, HDL-C presented rhythms in all age groups, but TC and LDL-C showed seasonality only for those > 13years, TG did not present rhythms in all age groups. Conclusion: Effects of sex and age on biological rhythms detected in TC, LDL-C and HDL-C should be considered a significant cause of pre-analytical variation in these laboratory tests. (C) 2009 Elsevier B.V. All rights reserved.

Comparison between detailed model simulation and artificial neural network for forecasting building energy consumption

There are several ways to attempt to model a building and its heat gains from external sources as well as internal ones in order to evaluate a proper operation, audit retrofit actions, and forecast energy consumption. Different techniques, varying from simple regression to models that are based on physical principles, can be used for simulation. A frequent hypothesis for all these models is that the input variables should be based on realistic data when they are available, otherwise the evaluation of energy consumption might be highly under or over estimated. In this paper, a comparison is made between a simple model based on artificial neural network (ANN) and a model that is based on physical principles (EnergyPlus) as an auditing and predicting tool in order to forecast building energy consumption. The Administration Building of the University of Sao Paulo is used as a case study. The building energy consumption profiles are collected as well as the campus meteorological data. Results show that both models are suitable for energy consumption forecast. Additionally, a parametric analysis is carried out for the considered building on EnergyPlus in order to evaluate the influence of several parameters such as the building profile occupation and weather data on such forecasting. (C) 2008 Elsevier B.V. All rights reserved.

Prediction of MHC class II-binding peptides using an evolutionary algorithm and artificial neural network

Motivation: Prediction methods for identifying binding peptides could minimize the number of peptides required to be synthesized and assayed, and thereby facilitate the identification of potential T-cell epitopes. We developed a bioinformatic method for the prediction of peptide binding to MHC class II molecules. Results: Experimental binding data and expert knowledge of anchor positions and binding motifs were combined with an evolutionary algorithm (EA) and an artificial neural network (ANN): binding data extraction --> peptide alignment --> ANN training and classification. This method, termed PERUN, was implemented for the prediction of peptides that bind to HLA-DR4(B1*0401). The respective positive predictive values of PERUN predictions of high-, moderate-, low- and zero-affinity binder-a were assessed as 0.8, 0.7, 0.5 and 0.8 by cross-validation, and 1.0, 0.8, 0.3 and 0.7 by experimental binding. This illustrates the synergy between experimentation and computer modeling, and its application to the identification of potential immunotheraaeutic peptides.