Matching Items (137)
Description
The influenza virus, also known as "the flu", is an infectious disease that has constantly affected the health of humanity. There is currently no known cure for Influenza. The Center for Innovations in Medicine at the Biodesign Institute located on campus at Arizona State University has been developing synbodies as a possible Influenza therapeutic. Specifically, at CIM, we have attempted to design these initial synbodies to target the entire Influenza virus and preliminary data leads us to believe that these synbodies target Nucleoprotein (NP). Given that the synbody targets NP, the penetration of cells via synbody should also occur. Then by Western Blot analysis we evaluated for the diminution of NP level in treated cells versus untreated cells. The focus of my honors thesis is to explore how synthetic antibodies can potentially inhibit replication of the Influenza (H1N1) A/Puerto Rico/8/34 strain so that a therapeutic can be developed. A high affinity synbody for Influenza can be utilized to test for inhibition of Influenza as shown by preliminary data. The 5-5-3819 synthetic antibody's internalization in live cells was visualized with Madin-Darby Kidney Cells under a Confocal Microscope. Then by Western Blot analysis we evaluated for the diminution of NP level in treated cells versus untreated cells. Expression of NP over 8 hours time was analyzed via Western Blot Analysis, which showed NP accumulation was retarded in synbody treated cells. The data obtained from my honors thesis and preliminary data provided suggest that the synthetic antibody penetrates live cells and targets NP. The results of my thesis presents valuable information that can be utilized by other researchers so that future experiments can be performed, eventually leading to the creation of a more effective therapeutic for influenza.
ContributorsHayden, Joel James (Author) / Diehnelt, Chris (Thesis director) / Johnston, Stephen (Committee member) / Legutki, Bart (Committee member) / Barrett, The Honors College (Contributor) / Department of Psychology (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2014-05
Description
Over the last decade, the ability to track daily activity through step counting devices has undergone major changes. Advanced technologies have brought about new step counting devices and new form factors. The validity of these new devices is not fully known. The purpose of this study was to validate and compare the step counting accuracy of commercially available hip- and wrist-worn accelerometers. A total of 185 participants (18-64 years of age) were analyzed for this study, with the sample composed nearly evenly of each gender (53.5% female) and BMI classification (33% overweight, 31.9% obese). Each participant wore five devices including hip-worn Omron HJ-112 and Fitbit One, and wrist-worn Fitbit Flex, Nike Fuelband, and Jawbone UP. A range of activities (some constant among all participants, some randomly assigned) were then used to accumulate steps including walking on a hard surface for 400m, treadmill walking/running at 2mph, 3mph, and ≥5mph, walking up five flights of stairs, and walking down five flights of stairs. To validate the accuracy of each device, steps were also counted by direct observation. Results showed high concordance with directly observed steps for all devices (intraclass correlation coefficient range: 0.86 to 0.99), with hip-worn devices more accurate than wrist-worn devices. Absolute percent error values were lower among hip-worn devices and at faster walking/running speeds. Nike Fuelband consistently was the worst performing of all test devices. These results are important because as pedometers become more complex, it is important that they remain accurate throughout a variety of activities. Future directions for this research are to explore the validity of these devices in free-living settings and among younger and older populations.
ContributorsKramer, Cody Lee (Author) / Buman, Matthew (Thesis director) / Hoffner, Kristin (Committee member) / Marshall, Simon (Committee member) / Barrett, The Honors College (Contributor) / School of Nutrition and Health Promotion (Contributor)
Created2014-05
Description
The influenza virus is the main cause of thousands of deaths each year in the United States, and far more hospitalizations. Immunization has helped in protecting people from this virus and there are a number of therapeutics which have proven effective in aiding people infected with the virus. However, these therapeutics are subject to various limitations including increased resistance, limited supply, and significant side effects. A new therapeutic is needed which addresses these problems and protects people from the influenza virus. Synbodies, synthetic antibodies, may provide a means to achieve this goal. Our group has produced a synbody, the 5-5 synbody, which has been shown to bind to and inhibit the influenza virus. The direct pull down and western blot techniques were utilized to investigate how the synbody bound to the influenza virus. Our research showed that the 5-5 synbody bound to the influenza nucleoprotein (NP) with a KD of 102.9 ± 74.48 nM. It also showed that the synbody bound strongly to influenza viral extract from two different strains of the virus, the Puerto Rico (H1N1) and Sydney (H3N2) strains. This research demonstrated that the 5-5 synbody binds with high affinity to NP, which is important because influenza NP is highly conserved between various strains of the virus and plays an important role in the replication of the viral genome. It also demonstrated that this binding is conserved between various strains of the virus, indicating that the 5-5 synbody potentially could bind many different influenza strains. This synbody may have potential as a therapeutic in the future if it is able to demonstrate similar binding in vivo.
ContributorsKombe, Albert E. (Author) / Diehnelt, Chris (Thesis director) / Woodbury, Neal (Committee member) / Legutki, Bart (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor) / School of International Letters and Cultures (Contributor)
Created2014-05
Description
One of the major challenges that were yet to be solved for solid phase peptide synthesis was the lack of an efficient peptide sequencing technique that was less hazardous, easier to perform , and was more cost-effective. Sequencing peptides were held important in the field of Chemistry and Biochemistry because it aided in drug discovery, finding ligands that bind to a specific target protein and finding alternative agents in transporting molecules to its desired location. Therefore, the overall purpose of this experiment was to develop a method of solid phase sequencing technique that was more environmental friendly, sequences at a faster rate, and was more cost-effective.
ContributorsCordovez, Lalaine Anne Ordiz (Author) / Woodbury, Neal (Thesis director) / Zhao, Zhan-Gong (Committee member) / Legutki, Joseph Barten (Committee member) / Barrett, The Honors College (Contributor) / Department of Chemistry and Biochemistry (Contributor)
Created2014-05
Description
We, a team of students and faculty in the life sciences at Arizona State University (ASU), currently teach an Introduction to Biology course in a Level 5, or maximum-security unit with the support of the Arizona Department of Corrections and the Prison Education Program at ASU. This course aims to enhance current programs at the unit by offering inmates an opportunity to practice literacy and math skills, while also providing exposure to a new academic field (science, and specifically biology). Numerous studies, including a 2005 study from the Arizona Department of Corrections (ADC), have found that vocational programs, including prison education programs, reduce recidivism rates (ADC 2005, Esperian 2010, Jancic 1988, Steurer et al. 2001, Ubic 2002) and may provide additional benefits such as engagement with a world outside the justice system (Duguid 1992), the opportunity for inmates to revise personal patterns of rejecting education that they may regret, and the ability of inmate parents to deliberately set a good example for their children (Hall and Killacky 2008). Teaching in a maximum security prison unit poses special challenges, which include a prohibition on most outside materials (except paper), severe restrictions on student-teacher and student-student interactions, and the inability to perform any lab exercises except limited computer simulations. Lack of literature discussing theoretical and practical aspects of teaching science in such environment has prompted us to conduct an ongoing study to generate notes and recommendations from this class through the use of surveys, academic evaluation of students' work and ongoing feedback from both teachers and students to inform teaching practices in future science classes in high-security prison units.
ContributorsLarson, Anika Jade (Author) / Mor, Tsafrir (Thesis director) / Brownell, Sara (Committee member) / Lockard, Joe (Committee member) / Barrett, The Honors College (Contributor) / School of Politics and Global Studies (Contributor) / School of Life Sciences (Contributor)
Created2015-05
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
This thesis contains three chapters, all of which involve using culturally inclusive education to explore the experiences of religious undergraduate biology students. The first chapter is an essay entitled "Toward Culturally Inclusive Undergraduate Biology Education," which describes a literature review performed with the aim of characterizing the landscape of cultural competence and related terms for biology educators and biology education researchers. This chapter highlights the use of 16 different terms related to cultural competence and presents these terms, their definitions, and highlights their similarities and differences. This chapter also identifies gaps in the cultural competence literature, and presents a set of recommendations to support better culturally inclusive interventions in undergraduate science education. The second chapter, entitled "Different Evolution Acceptance Instruments Lead to Different Research Findings," describes a study in which the source of 30 years of conflicting research on the relationship between evolution acceptance and evolution understanding was determined. The results of this study showed that different instruments used to measure evolution acceptance sometimes lead to different research results and conclusions. The final chapter, entitled "Believing That Evolution is Atheistic is Associated with Poor Evolution Education Outcomes Among Religious College Students," describes a study characterizing definitions of evolution that religious undergraduate biology students may hold, and examines the impact that those definitions of evolution have on multiple outcome variables. In this study, we found that among the most religious students, those who thought evolution is atheistic were less accepting of evolution, less comfortable learning evolution, and perceived greater conflict between their personal religious beliefs and evolution than those who thought evolution is agnostic.
ContributorsDunlop, Hayley Marie (Author) / Brownell, Sara (Thesis director) / Collins, James (Committee member) / Barnes, M. Elizabeth (Committee member) / School of Human Evolution & Social Change (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)
Created2019-05
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