Matching Items (126)
Description
Background: Breast cancer is the most frequently diagnosed cancer and the leading cause of cancer deaths in females worldwide, accounting for 23% of all new cancer cases and 14% of all total cancer deaths in 2008. Five tumor-normal pairs of primary breast epithelial cells were treated for infinite proliferation by using a ROCK inhibitor and mouse feeder cells. Methods: Raw paired-end, 100x coverage RNA-Seq data was aligned to the Human Reference Genome Version 19 using BWA and Tophat. Gene differential expression analysis was completed using Cufflinks and Cuffdiff. Interactive Genome Viewer was used for data visualization. Results: 15 genes were found to be down-regulated by at least one log-fold change in 4/5 of tumor samples. 75 genes were found to be down-regulated in 3/5 of our tumor samples by at least one log-fold change. 11 genes were found to be up-regulated in 4/5 of our tumor samples, and 68 genes were identified to be up-regulated in 3/5 of the tumor samples by at least one-fold change. Conclusion: Expression changes in genes such as AZGP1, AGER, ALG11, and S1007 suggest a disruption in the glycosylation pathway. No correlation was found between Cufflink's Her2 gene-expression and DAKO score classification.
ContributorsHernandez, Fernando (Author) / Anderson, Karen (Thesis director) / Mangone, Marco (Committee member) / Park, Jin (Committee member) / Barrett, The Honors College (Contributor) / Department of Information Systems (Contributor)
Created2013-05
Description
miRNAs are short non-coding regulatory RNAs that have an important roles in a wide range of biological processes. Dysfunction of miRNA regulation has also been shown to occur in diseases such as cancer. Despite the widespread influence of miRNAs in these contexts, the vast majority of miRNA targets are poorly characterized. The aim of this research project was to gain a better understating of miRNA targeting by using the model organism C. elegans. In order to do this I adapted a novel high-throughput assay to detect miRNA targets for use with the C. elegans 3`UTRome. As a proof of principle I performed this assay on 96 C. elegans 3`UTRs using high-throughput techniques. The results revealed miRNA interactions with two predicted 3`UTR targets for the miRNA lin-4 and ten unpredicted targets. The results also corroborated previous findings that certain worm miRNAs require special modifications to be expressed in human cells.
ContributorsKotagama, Kasuen Indrajith Bandara (Author) / Mangone, Marco (Thesis director) / Anderson, Karen (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2013-12
Description
Alternative polyadenylation (APA) is the biological mechanism in which the same gene can have multiple 3'untranslated region (3'UTR) isoforms due to the presence of multiple polyadenylation signal (PAS) elements within the pre mRNAs. Because APA produces mRNA transcripts that have different 3'UTR isoforms, certain transcripts may be subject to post-transcriptional regulation by regulatory non-coding RNAs, such as microRNAs or RNA binding proteins defects of which have been implicated in diseases such as cancer. Despite the increasing level of information, functional understanding of the molecular mechanisms involved in transcription is still poorly understood, nor is it clear why APA is necessary at a cell or tissue-specific level. To address these questions I wanted to develop a set of sensor strain plasmids capable of detecting cleavage and polyadenylation in vivo, inject the complete sensor strain plasmid into C. elegans and prepare stable transgenic lines, and perform proof-of-principle RNAi feeding experiments targeting genes associated with the cleavage and polyadenylation complex machinery. I demonstrated that it was possible to create a plasmid capable of detecting cleavage and polyadenylation in C. elegans; however, issues arose during the RNAi assays indicating the sensor strain plasmid was not sensitive enough to the RNAi to effectively detect in the worms. Once the problems involved with sensitivity and variability in the RNAi effects are resolved, the plasmid would be able to better address questions regarding the functional understanding of molecular mechanisms involved in transcription termination.
ContributorsWilky, Henry Patrick (Author) / Mangone, Marco (Thesis director) / Newbern, Jason (Committee member) / Blazie, Stephen (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)
Created2015-05
Description
A study was conducted to assess the effects of generational status on various measures of stigmatization, acculturative stress, and perceived social and interpersonal threat within the Mexican heritage population in the Southwest. The role of the fear of stigma by association, regardless of actual experiences of stigmatization, was investigated, including its relationships with acculturative stress, perceived threat, and social distancing. Exploratory analyses indicated that first generation Mexican Americans differed significantly from second generation Mexican Americans on the perception of Mexican nationals as ingroup members, the fear of stigma by association by Americans, and levels of acculturative stress. Additional analyses indicated that Mexican Americans with one parent born in Mexico and one in the United States held opinions and attitudes most similar to second generation Mexican Americans. Results from path analyses indicated that first-generation Mexican Americans were more likely than second-generation Mexican Americans to both see Mexican nationals as ingroup members and to be afraid of being stigmatized for their perceived association with them. Further, seeing Mexican nationals as in-group members resulted in less social distancing and lower perceived threat, but fear of stigma by association lead to greater perceived threat and greater acculturative stress. Implications for within- and between-group relations and research on stigma by association are discussed.
ContributorsBoyd, Brenna Margaret (Author) / Knight, George P (Thesis advisor) / Kwan, Sau (Committee member) / Neuberg, Steven (Committee member) / Arizona State University (Publisher)
Created2010
Description
Human activity recognition is the task of identifying a person’s movement from sensors in a wearable device, such as a smartphone, smartwatch, or a medical-grade device. A great method for this task is machine learning, which is the study of algorithms that learn and improve on their own with the help of massive amounts of useful data. These classification models can accurately classify activities with the time-series data from accelerometers and gyroscopes. A significant way to improve the accuracy of these machine learning models is preprocessing the data, essentially augmenting data to make the identification of each activity, or class, easier for the model. <br/>On this topic, this paper explains the design of SigNorm, a new web application which lets users conveniently transform time-series data and view the effects of those transformations in a code-free, browser-based user interface. The second and final section explains my take on a human activity recognition problem, which involves comparing a preprocessed dataset to an un-augmented one, and comparing the differences in accuracy using a one-dimensional convolutional neural network to make classifications.
ContributorsLi, Vincent (Author) / Turaga, Pavan (Thesis director) / Buman, Matthew (Committee member) / Computer Science and Engineering Program (Contributor) / Barrett, The Honors College (Contributor)
Created2021-05
Description
Background
The purpose of this study is to determine the feasibility of three widely used wearable sensors in research settings for 24 h monitoring of sleep, sedentary, and active behaviors in middle-aged women.
Methods
Participants were 21 inactive, overweight (M Body Mass Index (BMI) = 29.27 ± 7.43) women, 30 to 64 years (M = 45.31 ± 9.67). Women were instructed to wear each sensor on the non-dominant hip (ActiGraph GT3X+), wrist (GENEActiv), or upper arm (BodyMedia SenseWear Mini) for 24 h/day and record daily wake and bed times for one week over the course of three consecutive weeks. Women received feedback about their daily physical activity and sleep behaviors. Feasibility (i.e., acceptability and demand) was measured using surveys, interviews, and wear time.
Results
Women felt the GENEActiv (94.7 %) and SenseWear Mini (90.0 %) were easier to wear and preferred the placement (68.4, 80 % respectively) as compared to the ActiGraph (42.9, 47.6 % respectively). Mean wear time on valid days was similar across sensors (ActiGraph: M = 918.8 ± 115.0 min; GENEActiv: M = 949.3 ± 86.6; SenseWear: M = 928.0 ± 101.8) and well above other studies using wake time only protocols. Informational feedback was the biggest motivator, while appearance, comfort, and inconvenience were the biggest barriers to wearing sensors. Wear time was valid on 93.9 % (ActiGraph), 100 % (GENEActiv), and 95.2 % (SenseWear) of eligible days. 61.9, 95.2, and 71.4 % of participants had seven valid days of data for the ActiGraph, GENEActiv, and SenseWear, respectively.
Conclusion
Twenty-four hour monitoring over seven consecutive days is a feasible approach in middle-aged women. Researchers should consider participant acceptability and demand, in addition to validity and reliability, when choosing a wearable sensor. More research is needed across populations and study designs.
The purpose of this study is to determine the feasibility of three widely used wearable sensors in research settings for 24 h monitoring of sleep, sedentary, and active behaviors in middle-aged women.
Methods
Participants were 21 inactive, overweight (M Body Mass Index (BMI) = 29.27 ± 7.43) women, 30 to 64 years (M = 45.31 ± 9.67). Women were instructed to wear each sensor on the non-dominant hip (ActiGraph GT3X+), wrist (GENEActiv), or upper arm (BodyMedia SenseWear Mini) for 24 h/day and record daily wake and bed times for one week over the course of three consecutive weeks. Women received feedback about their daily physical activity and sleep behaviors. Feasibility (i.e., acceptability and demand) was measured using surveys, interviews, and wear time.
Results
Women felt the GENEActiv (94.7 %) and SenseWear Mini (90.0 %) were easier to wear and preferred the placement (68.4, 80 % respectively) as compared to the ActiGraph (42.9, 47.6 % respectively). Mean wear time on valid days was similar across sensors (ActiGraph: M = 918.8 ± 115.0 min; GENEActiv: M = 949.3 ± 86.6; SenseWear: M = 928.0 ± 101.8) and well above other studies using wake time only protocols. Informational feedback was the biggest motivator, while appearance, comfort, and inconvenience were the biggest barriers to wearing sensors. Wear time was valid on 93.9 % (ActiGraph), 100 % (GENEActiv), and 95.2 % (SenseWear) of eligible days. 61.9, 95.2, and 71.4 % of participants had seven valid days of data for the ActiGraph, GENEActiv, and SenseWear, respectively.
Conclusion
Twenty-four hour monitoring over seven consecutive days is a feasible approach in middle-aged women. Researchers should consider participant acceptability and demand, in addition to validity and reliability, when choosing a wearable sensor. More research is needed across populations and study designs.
ContributorsHuberty, Jennifer (Author) / Ehlers, Diane (Author) / Kurka, Jonathan (Author) / Ainsworth, Barbara (Author) / Buman, Matthew (Author) / College of Health Solutions (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2015-07-30
Validity of the Rapid Eating Assessment for Patients for assessing dietary patterns in NCAA athletes
Description
Background
Athletes may be at risk for developing adverse health outcomes due to poor eating behaviors during college. Due to the complex nature of the diet, it is difficult to include or exclude individual food items and specific food groups from the diet. Eating behaviors may better characterize the complex interactions between individual food items and specific food groups. The purpose was to examine the Rapid Eating Assessment for Patients survey (REAP) as a valid tool for analyzing eating behaviors of NCAA Division-I male and female athletes using pattern identification. Also, to investigate the relationships between derived eating behavior patterns and body mass index (BMI) and waist circumference (WC) while stratifying by sex and aesthetic nature of the sport.
Methods
Two independent samples of male (n = 86; n = 139) and female (n = 64; n = 102) collegiate athletes completed the REAP in June-August 2011 (n = 150) and June-August 2012 (n = 241). Principal component analysis (PCA) determined possible factors using wave-1 athletes. Exploratory (EFA) and confirmatory factor analyses (CFA) determined factors accounting for error and confirmed model fit in wave-2 athletes. Wave-2 athletes' BMI and WC were recorded during a physical exam and sport participation determined classification in aesthetic and non-aesthetic sport. Mean differences in eating behavior pattern score were explored. Regression models examined interactions between pattern scores, participation in aesthetic or non-aesthetic sport, and BMI and waist circumference controlling for age and race.
Results
A 5-factor PCA solution accounting for 60.3% of sample variance determined fourteen questions for EFA and CFA. A confirmed solution revealed patterns of Desserts, Healthy food, Meats, High-fat food, and Dairy. Pattern score (mean ± SE) differences were found, as non-aesthetic sport males had a higher (better) Dessert score than aesthetic sport males (2.16 ± 0.07 vs. 1.93 ± 0.11). Female aesthetic athletes had a higher score compared to non-aesthetic female athletes for the Dessert (2.11 ± 0.11 vs. 1.88 ± 0.08), Meat (1.95 ± 0.10 vs. 1.72 ± 0.07), High-fat food (1.70 ± 0.08 vs. 1.46 ± 0.06), and Dairy (1.70 ± 0.11 vs. 1.43 ± 0.07) patterns.
Conclusions
REAP is a construct valid tool to assess dietary patterns in college athletes. In light of varying dietary patterns, college athletes should be evaluated for healthful and unhealthful eating behaviors.
Athletes may be at risk for developing adverse health outcomes due to poor eating behaviors during college. Due to the complex nature of the diet, it is difficult to include or exclude individual food items and specific food groups from the diet. Eating behaviors may better characterize the complex interactions between individual food items and specific food groups. The purpose was to examine the Rapid Eating Assessment for Patients survey (REAP) as a valid tool for analyzing eating behaviors of NCAA Division-I male and female athletes using pattern identification. Also, to investigate the relationships between derived eating behavior patterns and body mass index (BMI) and waist circumference (WC) while stratifying by sex and aesthetic nature of the sport.
Methods
Two independent samples of male (n = 86; n = 139) and female (n = 64; n = 102) collegiate athletes completed the REAP in June-August 2011 (n = 150) and June-August 2012 (n = 241). Principal component analysis (PCA) determined possible factors using wave-1 athletes. Exploratory (EFA) and confirmatory factor analyses (CFA) determined factors accounting for error and confirmed model fit in wave-2 athletes. Wave-2 athletes' BMI and WC were recorded during a physical exam and sport participation determined classification in aesthetic and non-aesthetic sport. Mean differences in eating behavior pattern score were explored. Regression models examined interactions between pattern scores, participation in aesthetic or non-aesthetic sport, and BMI and waist circumference controlling for age and race.
Results
A 5-factor PCA solution accounting for 60.3% of sample variance determined fourteen questions for EFA and CFA. A confirmed solution revealed patterns of Desserts, Healthy food, Meats, High-fat food, and Dairy. Pattern score (mean ± SE) differences were found, as non-aesthetic sport males had a higher (better) Dessert score than aesthetic sport males (2.16 ± 0.07 vs. 1.93 ± 0.11). Female aesthetic athletes had a higher score compared to non-aesthetic female athletes for the Dessert (2.11 ± 0.11 vs. 1.88 ± 0.08), Meat (1.95 ± 0.10 vs. 1.72 ± 0.07), High-fat food (1.70 ± 0.08 vs. 1.46 ± 0.06), and Dairy (1.70 ± 0.11 vs. 1.43 ± 0.07) patterns.
Conclusions
REAP is a construct valid tool to assess dietary patterns in college athletes. In light of varying dietary patterns, college athletes should be evaluated for healthful and unhealthful eating behaviors.
ContributorsKurka, Jonathan (Author) / Buman, Matthew (Author) / Ainsworth, Barbara (Author) / College of Health Solutions (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2014-08-15
Description
In eukaryotes, most messenger RNA precursors (pre-mRNA) undergo extensive processing, leading to the cleavage of the transcript followed by the addition of a poly(A) tail. This process is executed by a large complex known as the Cleavage and Polyadenylation Complex (CPC). Its central subcomplex, the Cleavage and Polyadenylation Specificity Factor (CPSF) complex is responsible for recognizing a short hexameric element AAUAAA located at the 3’end in the nascent mRNA molecule and catalyzing the pre-mRNA cleavage. In the round nematode C. elegans, the cleavage reaction is executed by a subunit of this complex named CPSF3, a highly conserved RNA endonuclease. While the crystal structure of its human ortholog CPSF73 has been recently identified, we still do not understand the molecular mechanisms and sequence specificity used by this protein to induce cleavage, which in turn would help to understand how this process is executed in detail. Additionally, we do not understand in additional factors are needed for this process. In order to address these issues, we performed a comparative analysis of the CPSF3 protein in higher eukaryotes to identify conserved functional domains. The overall percent identities for members of the CPSF complex range from 33.68% to 56.49%, suggesting that the human and C. elegans orthologs retain a high level of conservation. CPSF73 is the protein with the overall highest percent identity of the CPSF complex, with its active site-containing domain possessing 74.60% identity with CPSF3. Additionally, we gathered and expressed using a bacterial expression system CPSF3 and a mutant, which is unable to perform the cleavage reaction, and developed an in vitro cleavage assay to test whether CPSF3 activity is necessary and sufficient to induce nascent mRNA cleavage. This project establishes tools to better understand how CPSF3 functions within the CPC and sheds light on the biology surrounding the transcription process as a whole.
ContributorsGallante, Christina (Author) / Mangone, Marco (Thesis director) / Sharma, Shalini (Committee member) / Hrach, Heather (Committee member) / School of Life Sciences (Contributor) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05
Description
Introduction: There is currently a lack of industry-wide gold standardization in accelerometer study
protocols, including within sleep-focused studies. This study seeks to address accuracy of
accelerometer data in detection of the beginnings and ends of sleep bouts in young adults with
polysomnography (PSG) corroboration. An existing algorithm used to differentiate valid/invalid wear
time and detect bouts of sleep has been modified with the goal of maximizing accuracy of sleep bout
detection. Methods: Three key decisions and thresholds of the algorithm have been modified with three
experimental values each being tested. The main experimental variable Sleepwindow controls the
amount of time before and after a determined bout of sleep that is searched for additional sedentary
time to incorporate and consider part of the same sleep bout. Results were compared to PSG and sleep
diary data for absolute agreement of sleep bout start time (START), end time (END) and time in bed
(TIB). Adjustments were made for outliers as well as sleep latency, snooze time, and the sum of both.
Results: Only adjustments made to a sleep window variable yielded altered results. Between a 5-, 15-,
and 30-minute window, a 15-minute window incurred the least error and most agreement to
comparisons for START, while a 5-minute window was best for END and TIB. Discussion: Contrary
to expectation, corrections for snooze, latency, and both did not substantially improve agreement to
PSG. Algorithm-derived estimates of START and END always fell after sleep diary and PSG both,
suggesting either participants’ sedentary behavior beginning and ends were at a delay from sleep and
wake times, or the algorithm estimates consistently later times than appropriate. The inclusion of a
sleep window variable yields substantial variety in results. A 15-minute window appears best at
determining START while a 5-minute window appears best for END and TIB. Further investigation on
the optimal window length per demographic and condition is required.
protocols, including within sleep-focused studies. This study seeks to address accuracy of
accelerometer data in detection of the beginnings and ends of sleep bouts in young adults with
polysomnography (PSG) corroboration. An existing algorithm used to differentiate valid/invalid wear
time and detect bouts of sleep has been modified with the goal of maximizing accuracy of sleep bout
detection. Methods: Three key decisions and thresholds of the algorithm have been modified with three
experimental values each being tested. The main experimental variable Sleepwindow controls the
amount of time before and after a determined bout of sleep that is searched for additional sedentary
time to incorporate and consider part of the same sleep bout. Results were compared to PSG and sleep
diary data for absolute agreement of sleep bout start time (START), end time (END) and time in bed
(TIB). Adjustments were made for outliers as well as sleep latency, snooze time, and the sum of both.
Results: Only adjustments made to a sleep window variable yielded altered results. Between a 5-, 15-,
and 30-minute window, a 15-minute window incurred the least error and most agreement to
comparisons for START, while a 5-minute window was best for END and TIB. Discussion: Contrary
to expectation, corrections for snooze, latency, and both did not substantially improve agreement to
PSG. Algorithm-derived estimates of START and END always fell after sleep diary and PSG both,
suggesting either participants’ sedentary behavior beginning and ends were at a delay from sleep and
wake times, or the algorithm estimates consistently later times than appropriate. The inclusion of a
sleep window variable yields substantial variety in results. A 15-minute window appears best at
determining START while a 5-minute window appears best for END and TIB. Further investigation on
the optimal window length per demographic and condition is required.
ContributorsMartin, Logan Rhett (Author) / Buman, Matthew (Thesis director) / Toledo, Meynard John (Committee member) / Kurka, Jonathan (Committee member) / College of Health Solutions (Contributor) / Barrett, The Honors College (Contributor)
Created2019-12
Description
The successful reduction of CO2 and protons by a light-induced cobalt porphyrin/cytb562 hybrid metalloenzyme in water is reported. Incorporation of the porphyrin into a protein scaffold results in increases in CO and H2 production over naked porphyrin. Rational point mutations to the CoPPIX binding site of cytb562 modulate production, indicating possible further improvements in catalytic activity.
ContributorsGwerder, Noah D (Author) / Ghirlanda, Giovanna (Thesis director) / Williams, Peter (Committee member) / Mangone, Marco (Committee member) / School of Molecular Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2020-05