Mountain Scholar :: Browsing by Author "Hess, Ann, committee member"

Browsing by Author "Hess, Ann, committee member"

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Open Access
A comparison of methods to derive aggregated transfer factors: tested using wild boar data from the Fukushima prefecture
(Colorado State University. Libraries, 2017) Anderson, Donovan, author; Johnson, Thomas, advisor; Brandl, Alexander, committee member; Hess, Ann, committee member
In March of 2011, the Fukushima Daiichi disaster released airborne radioactive material dominated by Cs-134 and Cs-137. When the radionuclides settled, they contaminated soil and plants, with wild boar also becoming contaminated through various pathways. An estimate of the radiocesium concentration in wild boar tissues can be obtained from an aggregated transfer factor based on soil contamination levels. The aggregated transfer factor (Tag) for purposes of this study, is the ratio of Cs-137 concentration in wild boar tissues (Bq kg-1) divided by the Cs-137 surface contamination of soils (Bq m-2). In this study, two methods were used to estimate the Tag values, and a comparison was made to determine which method reduced uncertainty. Both methods rely on harvesting and measuring radiocesium in wild boar tissues (bicep femoris muscle). The radiocesium value used for soil, however, was different in the two methods. One was obtained from a public database of samples collected by the Japanese government in 2015. Oftentimes, the soil sample paired with the wild boar trap site were not within the home range of the wild boar, reducing accuracy of the predicted radiocesium concentration levels in the animal. The other method used soil samples collected at the point of wild boar capture. The purpose of this study is to ascertain if the use of the database radiocesium soil concentration values is of sufficient granularity to provide a useful estimate of Tag values. The mean Tag value calculated in the Fukushima prefecture for wild boar were 2.3×10-3 m2 kg-1 fresh weight. The research revealed that the database radiocesium concentration values for soil (Bq m-2) used in calculating aggregated transfer factors, do not accurately represent the containment levels in the wild boar. Collecting soil samples within the home range of the animal reduces uncertainty in calculating Tag values to estimate whole body contamination levels of a wild boar. Our data complements and supports the existing monitoring programs conducted by the National and Prefecture governments in Japan by showing lower concentrations of cesium in soil and wild boar within decontaminated areas.
Open Access
Analysis of 3D facial anthropometric measurements for respirator fit outcomes
(Colorado State University. Libraries, 2023) Hobbs-Murphy, Kayna, author; Rosecrance, John, advisor; Brazile, Bill, committee member; Anderson, Brooke, committee member; Morris, Kristen, committee member; Hess, Ann, committee member
Anthropometry is central to the development of efficacious products and environments (i.e., personal protective equipment, clothing, sunglasses, chairs, interior spaces, etc.) used by humans. Three-dimensional (3D) scanning is increasingly common for collecting anthropometric data, as it is faster and less intrusive than traditional manual methods. Additionally, 3D anthropometric methods used to derive facial dimensions provide greater contextual application in the development of respirators and facemasks. More than 2,000 3D facial scans were analyzed to assess measurement reliability and the dimensions of 27 facial features. This research represents the largest sample of 3D facial anthropometrics assessed to date. The three specific aims of the research included: 1) to assess the intra- and inter-rater reliability of 3D facial measurement methods, 2) to compare the 3D facial anthropometric summary statistics from the present study to relevant summary statistics from manual facial measurements found in the literature, and 3) to assess the presence of differences in 3D facial anthropometrics related to respirator fit, based on demographic factors of gender, race/ethnicity, and age. Post hoc analyses were completed to quantify 3D facial measurement differences between demographic groups (within the larger demographic categories of gender, race/ethnicity, and age group). The most notable results of this research include a) high reliability in 3D measurement data collection methods, b) differences in measurement data summary statistics between 3D and manual methods, and c) significant differences in facial measurements between demographic categories of gender (Male and Female/Other), race/ethnicity (White, Black, LatinX, Asian, and Other), and age (18-34, 35-54, and 55-72).
Open Access
Association between beef ribeye area measurements and steak portion size
(Colorado State University. Libraries, 2024) Schiefelbein, Abbey Faith, author; Nair, Mahesh N., advisor; Geornaras, Ifigenia, committee member; Clark, Daniel, committee member; Hess, Ann, committee member
As cattle weights have increased over the past decades, hot carcass weight and ribeye area (REA) have also increased. The REA is an important determinant of carcass value as it impacts the thickness of steaks when portioned to a pre-determined weight. Additionally, previous research has indicated that steak thickness impacts consumers' eating experience potentially due to its impact on the degree of doneness. The objective of this study was to examine the relationship between carcass REA and steak portion size. Beef carcasses (n = 100) were selected from a commercial beef harvesting facility based on REA in 1 in2 (6.45 cm2) increments ranging from less than 11 in2 (70.97 cm2) to greater than 19 in2 (122.58 cm2) based on a United States Department of Agriculture-approved camera (E+V) with 10 total categories. Data (hot carcass weight, back fat thickness, and marbling) were collected from each selected carcass. The REA measurements were obtained using the grading camera, a manual grid, and pen tracing and measured using ImageJ software. Strip loins (IMPS#180) from selected carcasses were collected, and weight, length, and three width (anterior, middle, and posterior) measurements of the strip loins were measured manually. Each strip loin was then scanned through a Marel I-Cut 56 portion cutter to determine the thickness of 12 oz (340.19 g) and 16 oz (453.59 g) portions and to determine the weight of a 1-in (2.54 cm) thick portion. To quantify and describe the relationship between steak thickness (cut to 12 oz and 16 oz portions) and steak weight (cut at 1-in. thickness), linear regression models were developed using traced REA as the independent variable. Additionally, more exhaustive linear regression models were developed to predict steak thickness or weight based on the traced REA, hot carcass weight, fat thickness, strip loin weight, strip loin length, strip loin width, and average maximum height of the strip loin. Each model was evaluated separately for the main effects of each variable, with significance determined at ɑ=0.05. There was a significant (P < 0.001) correlation and linear relationship (P < 0.05) between traced REA measurement and 12 oz (R2 = 0.71), 16 oz (R2 = 0.71), and 1-in.-thick (R2 = 0.75) portions examined in this study. For 12 oz steaks, the steak thickness decreased by an estimated 0.055 in. (0.14 cm) for every 1-in. increase in REA. Similarly, for the 16 oz steaks, the steak thickness decreased by an estimated 0.074 in. (0.19 cm) for every square in. increase in REA. The 1-in. steak portions had a mean weight of 340 g, and the steak weight increased an estimated 18 g for each square in. increase in REA. In addition, using the strip loin measurements, linear regression models were able to predict steak thickness for 12 oz and 16 oz portions with an R2 of 0.95 each and predict the steak weight for the 1-in. portion with an R2 of 0.98. As expected, REA strongly correlated with the portion size of strip loin steaks cut to a specified weight or thickness. Additionally, our results indicated that the weight and length of the strip loin were good predictors of steak thickness (for 12 oz and 16 oz portions) or steak weight (for 1-in.-thick portions). Further research exploring consumer acceptance and degree of doneness for steaks with varying thicknesses would provide data to determine REA ranges and targets that would optimize steak portion sizes and consumer acceptability.
Open Access
Benchmarking and analysis of current pre-slaughter management factors and their influence on welfare and meat quality outcomes in fed beef cattle
(Colorado State University. Libraries, 2023) Davis, Melissa, author; Edwards-Callaway, Lily, advisor; Nair, Mahesh, committee member; Hess, Ann, committee member; Mooney, Daniel, committee member
Several factors related to pre-slaughter management of fed beef cattle and their impacts on welfare and meat quality have been identified and discussed thoroughly in previous literature. However, a full catalog of these factors and indicators used to evaluate their impacts on cattle welfare is missing. Additionally, benchmarked data for these factors and welfare and meat quality outcomes, and an analysis of their relationships on a large scale is underrepresented in current literature. The objectives of the first chapter of this dissertation were to catalog pre-slaughter management factors, identify indicators used to evaluate their impacts, and ultimately gain a further understanding of the relationships between pre-slaughter management factors and cattle welfare. This review included an in-depth analysis of 69 studies from across the globe that identified factors related to transportation and handling using behavioral and physiological indicators to measure welfare that were the most researched throughout the studies. The discussion of this review also identified pre-slaughter factors that require benchmarking and/or more research on their potential impacts on cattle welfare. Thus, the objectives of the second chapter in this dissertation was to benchmark pre-slaughter management factors at a collection of commercial fed cattle processing facilities. This data collection took place at five commercial processing facilities in the West, Midwest, and Southwest regions of the United States from March 2021 to July 2022. Data were collected on a total of n = 637 slaughter lots representing n = 87,220 head of cattle. Transportation factors such as distance travelled and the time cattle waited on the truck to unload after arriving at the facility, space allowance in lairage for cattle, lairage duration and cattle mobility was recorded. Environmental factors were later recorded from an online weather service, and cattle characteristics and several meat quality factors including bruising, quality grading, carcass weight and dark cutting were obtained from plant records. Descriptive statistics were calculated for both the lot and individual animal level depending on the variable. Cattle travelled on average, 155.8 ± 209.6 km (Mean ± SD) to the processing facility from the feedlot, waited 30.3 ± 39.7 minutes to unload at the plant and were held in lairage for 200.7 ± 195.0 minutes. The mean lairage density was 3.1 ± 2.0 m2/animal, and a majority of cattle (91.8%, n = 77,645) were scored as having normal mobility. Carcass bruising prevalence was 69.7% (n = 57,099), and of those that were bruised, 65.2% (n = 39,856) had multiple bruises. Having this baseline benchmarking data outlines not only areas that need further improvement, but also areas in this sector that the industry has already improved upon. This benchmarking data also identified the need for additional analysis on the relationships between these factors and outcomes. Therefore, the objective in the final chapter of this dissertation was to assess the effects of these factors on select welfare and meat quality outcomes in fed beef cattle. Using the same data set and methods as in the second chapter, any slaughter lots with no response variables or < 75% of predictor variables present were excluded. A total of n = 619 slaughter lots representing 84,508 head of cattle were used for further analysis. Descriptive statistics for this subset of data and linear and logistic regression models were performed to assess relationships. Statistical significance was determined at P < 0.05. Predictor variables of interest included plant, breed, sex class, operation shift at the plant, distance travelled, truck waiting time to unload, lairage duration and space allowance, THI, and wind speed. Outcome variables of interest included mobility, bruising, dark cutting, quality grades, and hot carcass weights. All outcomes of interest were associated with several pre-slaughter factors of interest, particularly plant and cattle breed. Increased odds of impaired mobility were associated with increased distance travelled (1.001, 1.000 – 1.001; OR, CI) and truck waiting time (1.003, 1.001 – 1.004; OR, CI). Increased odds of carcass bruising were associated with decreases in distance travelled (0.997, 0.996 – 0.998; OR, CI), but increases in space allowance in lairage (1.035; 1.017 – 1.053; OR, CI). Cattle that experienced increases in lairage duration were associated with decreased hot carcass weights (P < 0.0367) and increased odds of cark cutting (1.034, 1.001 – 1.068; OR, CI). Additionally, cattle that were slaughtered during the first shift of operation at the plant were associated with decreased odds of being bruised (0.806, 0.772 – 0.842; OR, CI), being classified as a dark cutter (0.416, 0.336 - 0.514; OR, CI), and having a poorer quality grade (0.777, 0.657 - 0.920; OR, CI). Results from these studies identify areas where further and more detailed research is needed to fill knowledge gaps and fully understand these relationships. This research also has the potential to aid in informed decision-making regarding cattle management during the pre-slaughter period and further educate the industry on sustainable management practices.
Open Access
Benchmarking animal handling outcomes and analyzing impacting factors on cow-calf operations
(Colorado State University. Libraries, 2022) Calaba, Elaine, author; Edwards-Callaway, Lily, advisor; Hess, Ann, committee member; Engle, Terry, committee member; Ahola, Jason, committee member
Animal handling is an important part of the cattle industry; proper handling of animals can improve animal welfare and increase consumer confidence. One way handling is assessed on cow-calf operations is through producer education programs, such as the Beef Quality Assurance (BQA) program. A part of these producer education programs is assessing animal handling outcomes. However, there has not been much research into the occurrence and implication of cow handling outcomes. The objectives of this study were to: 1) quantify handling outcomes on cow-calf operations in the United States and 2) investigate potential factors that may influence these outcomes. An assessment was developed by refining existing BQA Cow-Calf program outcome definitions in addition to questions about animal factors, facilities, and management factors. Handling outcomes observed included: Prod Use, Miscatch, Vocalization, Jump, Slip/Stumble, Fall and Run. A total of 76 cow-calf operations were sampled in 24 states (Central, n = 17; East, n = 30; West, n = 29), with herd sizes ranging from 10 head to more than 5,000 head. Observations occurred during processing of either cows or yearling heifers through a cattle chute restraint system, regardless of procedure being performed. With herds less than 100 head, all cows or yearling heifers were observed as they moved through the single file alley, into the chute, and upon exiting the chute for a distance of three body lengths. On operations greater than 100 head, a maximum of 100 contiguous head were observed. Results indicate that most participants were BQA trained (70%) and had crossbred herds (63%) with a Docile temperament (57%) and had Daily Visual Contact with their herds (47%). The mean observations for Prod Use (18.1% ± 28.9), Miscatch (2.5% ± 5.1), and Fall (2.5% ± 4.2) exceeded the upper limit of BQA standards. The BQA threshold for Prod Use is 10%, Miscatch is 0%, and Fall is 2%. Vocalization (3.8% ± 7.6), Jump (7.5% ± 9.9), Run (7.7% ± 13.8), and Slip/Stumble (6.3% ± 9.1) were within BQA thresholds (5%, 25%, and 10% respectively). Prod Use had the greatest number of impacting factors including BQA status, Herd Size Group, Temperament, and Visual Contact while Miscatch, Vocalization, and Fall all had single impacting factors (Region, Temperament, Visual Contact, respectively). Visual Contact and Temperament had an association with the majority of outcomes. Future research should focus more in-depth on specific factors and the variety contained within and on the role of veterinarians in handling outcome frequencies.
Open Access
Between a boulder and a hard place: an actualistic experiment to infer the impact of cave roof fall on limb bones and its implications for the archaeological record
(Colorado State University. Libraries, 2022) Hajdu, Alexandru, author; Glantz, Michelle, advisor; Pante, Michael, committee member; Hess, Ann, committee member
Over 50 years of research has highlighted the important role hominins and carnivores play as agents of bone fragmentation. The work has largely been focused on differentiating the assemblages created by hominins from those modified by carnivores. Consequently, cave roof fall and other agents have received relatively little attention in this rich literature. Previous studies of cave roof fall have suggested it can modify assemblages in a manner that mimics hammerstone-on-anvil percussion of bones indicating the need for reliable criteria to distinguish between these two processes. Here, we conduct an actualistic experiment designed to simulate the effects of cave roof fall on bone assemblages. Sixteen (n=16) bison tibiae were fractured in four experiments with drop heights of 4.6 and 7.6 meters and rock weights of 6.8 and 13.6 kilograms. To represent a hominin assemblage sixteen (n=16) tibiae were randomly selected from a hammerstone-on-anvil collection created by Robert Kaplan and stored at Colorado State University. Bone surface modifications (BSM) counts that include pits, notches, grooves, and striations were created for both groups. Additionally, notch measurement ratios, Incipient notch counts, fragment counts, general fragment size frequency distributions, epiphyseal fragment measurements, percentages of fragments with BSMs, and presence/absence of stress relief traces (hackle marks and ribs) were collected from both groups. Results suggest that flake count, pit count and the percentage of fragments with pits and/or grooves are the variables which are different between cave roof fall and hammerstone-on-anvil percussion. These variables are significantly different between the two assemblages; however, they are not applicable to the archaeological record. This is because the traces that these variables were built upon are not distinguishable between the two actors. This qualitative approach to address the equifinality between cave roof fall and hammerstone-on-anvil percussion has failed to provide any valuable insights.
Open Access
Classification using out of sample testing of neural networks and Siamese-like neural network for handwritten characters
(Colorado State University. Libraries, 2020) Yeluri, Sri Sagar Abhishek, author; Anderson, Charles W., advisor; Beveridge, Ross, committee member; Hess, Ann, committee member
In a world where Machine Learning Algorithms in the field of Image Processing is being developed at a rapid pace, a developer needs to have a better insight into all the algorithms to choose one among them for their application. When an algorithm is published, the developers of the algorithm compare their algorithm with already available well-performing algorithms and claim their algorithm outperforms all or the majority of other algorithms in terms of accuracy. However, adaptability is a very important aspect of Machine Learning which is usually not mentioned in their papers. Adaptability is the ability of a Machine Learning algorithm to work reliably in the real world, despite the change in the environmental factors in comparison to the environment in which data used for training is recorded. A machine learning algorithm that can give good results only on the dataset has no practical applications. In real life, the application of the algorithm increases only when it is more adaptable in nature. A few other aspects that are important in choosing the right algorithm for an application are consistency, time and resource utilization and the availability of human intervention. A person choosing amongst a list of algorithms for an application will be able to make a wise decision if given additional information, as each application varies from one another and needs a different set of characteristics of an algorithm for it to be well received. We have implemented and compared three Machine Learning algorithms used in image processing, on two different datasets and compare the results. We observe that certain algorithms, even though better than others in terms of accuracy on paper, fall behind when tested in real-world datasets. We put forward a few suggestions that if followed will simplify the selection of an algorithm for a specific purpose.
Open Access
Colorfastness properties of persimmon dye on cotton and wool substrates
(Colorado State University. Libraries, 2014) Malensek, Nicholas, author; Li, Yan Vivian, advisor; Miller, Nancy, advisor; Kissell, Kevin, committee member; Hess, Ann, committee member
Persimmon dye is a natural dye that imparts unique properties, including fungal resistance and water resistance. This study investigated persimmon dye's performance on cotton and wool fabric. Color strength and appearance of dyed cotton and wool fabrics at various dyeing conditions (mordanting order, dye concentration, and dyeing time length) were evaluated. Dyed fabrics had high color strength when using a mordant. Color strength on dyed cotton and wool increased with increased dye concentration and dyeing time. In this study, post-mordanting, 200% dye concentration, and 60 minutes dyeing length yielded the highest color strength for cotton and wool. These samples were then assessed using AATCC laundering, perspiration, and crocking colorfastness tests. Cotton samples received a 2-3 to 4 shade change rating, while wool received a 3 to 4 depending on the test. Cotton and wool samples received a 4 to 5 staining rating except in crocking, where they received a 2-3 and 3, respectively. FTIR analysis showed that the persimmon dye formed weak bonds on both fabrics, resulting in minimal chemical changes. The results suggest that natural persimmon dye can provide good colorfastness and minimal chemical changes on wool and cotton. The comparison between dyed cotton and wool suggests wool fabric is better suited for persimmon dye application than cotton because of its slightly better colorfastness ratings and significantly higher color strength.
Open Access
Combining mechanistic and statistical models for predicting reaction outcomes in organic synthesis
(Colorado State University. Libraries, 2023) Gallegos, Liliana Cabrera, author; Paton, Robert S., advisor; McNally, Andrew, committee member; Rappé, Anthony, committee member; Hess, Ann, committee member
Computational modeling and machine learning tools have assisted in the fundamental challenge of predicting the "over-the-arrow" optimal reaction conditions to maximize the output (e.g., yield and selectivity). The work presented here explores multiple challenging synthetic reactions for reaction optimization ranging from: (i) precise photocatalytic transformations in chemical biology, (ii) new reactivity using organobismuth(V) reagents, (iii) challenging reversible nucleophilic alcohol addition reactions influence at equilibrium, and (iv) a late-stage key reaction step in a total synthesis project. Overall, this dissertation aims to assist in predicting optimal reaction outcomes by understanding and formulating reaction mechanisms from quantum mechanics and statistical methods while using open-source automated workflows to improve transparency and reproducibility within data-chemistry fields. Chapter 1 provides the necessary background to introduce the methods behind computational and statistical models that assist in addressing the challenges faced within the optimization process and the limitations of each strategy. First, there will be a brief overview of the computational protocols to generate and understand reaction mechanisms using quantum mechanical methods. Then, a summary of the data-driven approach introduces the statistical methods and metrics that build relationships to chemical reactivity using computer-readable mechanistically derived molecular descriptions. Chapter 2 tackles the challenge of studying the chemical reactivity in large biological systems (e.g., peptides and proteins) with quantum mechanical methods. First, the precise photocatalytic functionalization at selenocysteine reaction developed by the Payne lab is simulated using a simplified model substrate followed by a more realistic model that generates the final energy profile. Based on the resulting computational analysis, the utility of this late-stage functionalization reaction is later demonstrated on large polypeptide chains. Chapters 3 and 4 embark on a journey into new bismuth chemistry developed by the Ball group. The bismuth arylation reaction published in Nature transformed the following collaborative work discussed here, ranging from the computational protocols implemented in selectivity problems to the versatile chemical reactivity originating from bismuth(V) reagents. From the previously reported but otherwise unexplored DFT integration grid effects, the computed free energies on organobismuth reactions explored here would have led to significant errors and incorrectly predicting selectivities. With the optimal computational protocols, new reactivity using organobismuth reagents is investigated in Chapter 3 to propose a reaction mechanism for the selective arylation of 2- and 4-pyridiones. Chapter 4 describes the mechanistic investigation of the developed palladium-catalyzed cross-coupling reaction to achieve challenging C-C couplings in mild reaction conditions with the amino-bridged bismacycle reagent. A statistical modeling approach using automated workflows discussed in Chapter 7 is applied here to predict an optimal reaction design and capture the origin of the reactivity for various coupling substrates and modified organobismuth(V)-reagents for the developed Bisma-Stille cross-coupling reaction. Chapter 5 describes a mechanistic investigation to optimize a challenging key reaction in the total synthesis of the natural product of allopupukeanane developed by the Sarpong group. The reaction success in late-stage synthetic plans becomes detrimental as the availability of reactants in a multiple-step natural product synthesis becomes limiting. The elementary step influencing the reactivity is identified in the palladium-mediated cascade reaction. Then, a data-driven approach is implemented to screen various ligands and collect mechanistically derived molecular DFT features to incorporate into a Bayesian optimization tool developed by the Doyle lab. Automated workflows discussed in Chapter 7 were utilized to collect the features. This approach successfully identified more suitable and efficient reaction conditions for racemic mixture, byproduct formation, and catalyst decomposition challenges. The overall synthesis plan to access multiple natural products via the bridged bicycle scaffold highlighted in this chapter is an ongoing project by the Sarpong group. Chapter 6 pivots into data-driven approaches to formulate statistical relationships sampled over small and large datasets. First, the collaborative research in section 6.2 dives into building a multivariate linear regression model with a small dataset to explain the reaction performance in various solvents on the challenging reversible nucleophilic alcohol addition reaction developed by the Bandar group. The statistical conclusions provide the bases for modeling the solvent effects via DFT methods. Next, in section 6.3, a machine learning model is trained on a large diverse molecule dataset to predict NMR chemical shifts with high accuracy to DFT-derived NMR values at only a fraction of the cost of DFT methods. Here are two examples where a successful prediction is evaluated based on the research goal to obtain model accuracy or interpretability. Chapter 7 focuses on facilitating the transparency and reproducibility for collecting and generating meaningful statistical models for the data chemist in low- and high-throughput studies. The open-source, automated workflows, DISCO and REGGAE, allowed for the execution of projects mentioned in Chapters 4 to 6 at different stages of the research process (e.g., chemical data collection, feature selection, and then statistical modeling).
Open Access
Defining interactions between Mycobacterium leprae and Langerhans cells
(Colorado State University. Libraries, 2021) Fletcher, Darcy, author; Belisle, John, advisor; Henao-Tamayo, Marcela, committee member; Hess, Ann, committee member; Zabel, Mark, committee member
Leprosy is a chronic infection that affects the skin and peripheral nerves. Written accounts of the disease date back to at least 600 BC. Mycobacterium leprae, the causative agent of leprosy was first discovered by Dr. Gerhard Armauer Hansen in 1873. Leprosy remains a major health problem in several low- and middle-income countries including Brazil, India, and Indonesia. There are numerous clinical presentations of the disease which presents many challenges for controlling the disease including diagnosis, treatment regimen and duration, and occasional instances of drug resistant cases. Further challenges exist in studying the disease, knowledge of the intricate interactions with innate immune cells has made advances in some cell subsets but is limited in others leaving an incomplete picture of the disease. These gaps limit advances in disease management. M. leprae is an obligate, intracellular pathogen that grows preferentially between 33-35° C and selectively invades peripheral nerves and skin-resident innate immune cells including macrophages. Numerous host cells including macrophages and Schwann cells have been studied to understand their interaction with M. leprae, but other skin-resident immune cells like dendritic cells, specifically Langerhans cells, have not been studied as extensively. The findings that M. leprae antigens can be presented via CD1a on Langerhans cells has spurred interest in understanding how Langerhans cells interact and uptake M. leprae leading to downstream effects on T cell activation and overall immune responses. The hypothesis of this study is that M. leprae interacts with Langerhans cells via various cell surface receptors that influence a Th1 or Th2 immune response. This study interrogates the complex interactions between Mycobacterium leprae and Langerhans cells via multiple cell surface receptors. In Chapter 2, an ex vivo optical tissue clearing method was modified for fragile skin samples to analyze innate cell recruitment to the site of infection. Colocalization between Langerhans cells and a closely related mycobacterial spp. to M. leprae, M. haemophilum, was observed in a 3D optically cleared tissue. These observations indicate that wholistic insight of bacteria/innate immune cell interactions can be gleaned using experimentally infected tissues or human skin biopsies. Chapter 3 presents the contributions from multiple cell surface receptors present on Langerhans cells in recognizing and binding M. leprae. Langerin was found to play a role in binding M. leprae, however, was not the only cell surface receptor involved in recognition of M. leprae. CD5+ Langerhans cells can be separated into CD5high and CD5low LCs that have differences in binding capacity for M. leprae. This study builds the foundation to explore the wholistic contributions of Langerhans cells interactions and uptake of M. leprae. Further work should be conducted to identify M. leprae ligand(s) for CD5 and downstream effects on cytokine secretion and T cell activation.
Open Access
Development and testing of measures to assess nutrition behavior change in low income adults participating in the Expanded Food and Nutrition Education Program
(Colorado State University. Libraries, 2017) Murray, Erin K., author; Baker, Susan, advisor; Auld, Garry, advisor; Betts, Nancy, committee member; Hess, Ann, committee member
To view the abstract, please see the full text of the document.
Open Access
Discovering consumer preferences for steak thickness and common food service cookery methods for beef strip loin steaks
(Colorado State University. Libraries, 2016) Shubert, Danielle Marie, author; Woerner, Dale R., advisor; Belk, Keith E., committee member; Tatum, J. Daryl, committee member; Delmore, Robert J., committee member; Hess, Ann, committee member
The objective of this study was to quantify consumer preferences for steak thickness and cookery method. Paired strip loins from 38 carcasses with Small marbling scores were obtained from a commercial packing facility. Each strip loin was cut into 2 sections (4 sections per carcass) and each section was randomly assigned to 1 of 4 cookery methods (COOK): 1) grill (GRILL); 2) grill mark then finish in a steam oven (MARK+FINISH); 3) par cook in a steam oven then mark on a grill (PAR+MARK); 4) broil (BROIL). Each section was vacuum-sealed and aged at 2oC for 21 days before being frozen. After freezing, three sets of paired steaks were cut from each section representing three steak thickness treatments (THICK): 1) 1.9-cm; 2) 2.5-cm; 3) 3.8-cm. For each cookery method and steak thickness combination pair, a single steak was designated for evaluation by a consumer panel while the other steak was assigned to objective testing for measures of tenderness, cook loss, and visual appearance. Known beef consumers (N = 307) evaluated each of the 12 treatment combinations of thickness and cookery method for tenderness, juiciness, flavor desirability and overall desirability using a 15-cm unstructured line scale. A significant COOK x THICK interaction (P < 0.05) affected consumer panel ratings for tenderness, juiciness, and overall desirability. As a main effect, COOK influenced (P = 0.0005) consumer ratings for flavor desirability; however, inconsistencies between the present and previous studies suggest that consumer-rated flavor desirability may have been affected more heavily by tenderness, and juiciness in what is termed a “halo effect” than by actual differences in flavor due to cookery method. The BROIL, 1.9-cm thick steaks were more desirable than 2.5 and 3.8-cm BROIL steaks as rated by consumers for overall desirability, tenderness, and juiciness, and were more tender as evaluated using WBSF and SSF (P < 0.5). The GRILL method was among the most highly rated for consumer overall desirability, and no significant difference was found existed between THICK treatments. Consumer overall desirability ratings, consumer tenderness ratings and SSF values for the PAR+MARK cookery method had, more desirable values for 3.8-cm thick steaks compared to 1.9 and 2.5-cm thick steaks. The MARK+COOK method was rated the highest for consumer overall desirability, tenderness, juiciness, and had the lowest SSF and WBSF values (P < 0.5). The MARK+COOK method was the most likely to offer consumers a desirable eating experience at steak thicknesses of 2.5 and 3.8-cm thick. The PAR+MARK method was more likely to result in a more positive eating experience as steaks were cut thicker (3.8-cm) as demonstrated by consumer ratings for overall desirability. The GRILL method had the least amount of variation in consumer ratings for overall desirability between steak thicknesses for positive eating experience. Cookery method and steak thickness should be chosen in the correct combination in order to deliver consumers with a positive eating experience in food service industry.
Open Access
Evaluating the equine endometrial transcriptome during maternal recognition of pregnancy
(Colorado State University. Libraries, 2018) Klohonatz, Kristin, author; Bruemmer, Jason, advisor; Coleman, Stephen, committee member; Bouma, Gerrit, committee member; Hess, Ann, committee member; Thomas, Milton, committee member
To view the abstract, please see the full text of the document.
Open Access
Experimental and computational analysis of Caenorhabditis elegans small RNAs
(Colorado State University. Libraries, 2019) Brown, Kristen, author; Montgomery, Tai, advisor; Duval, Dawn, committee member; Prasad, Ashok, committee member; Hess, Ann, committee member
Caenorhabditis elegans contains twenty-five Argonautes, of which, only ALG-1 and ALG-2 are known to interact with microRNAs (miRNAs). ALG-5 belongs to the AGO subfamily of Argonautes that includes ALG-1 and ALG-2, but its role in small RNA pathways is unknown. We analyzed by high-throughput sequencing the small RNAs associated with ALG-5, ALG-1, and ALG-2, as well as changes in mRNA expression in alg-5, alg-1, and alg-2 mutants. We show that ALG-5 defines a distinct branch of the miRNA pathway affecting the expression of genes involved in immunity, defense, and development. In contrast to ALG-1 and ALG-2, which associate with the majority of miRNAs and have general roles throughout development, ALG-5 interacts with only a small subset of miRNAs and is specifically expressed in the germline. alg-5 is required for optimal fertility and mutations in alg-5 lead to a precocious transition from spermatogenesis to oogenesis. Our results provide a near-comprehensive analysis of miRNA-Argonaute interactions in C. elegans and reveal a new role for miRNAs in the germline. The small RNA field has grown rapidly since miRNAs were discovered to be conserved regulators of developmental timing. This growth occurred during a time when high-throughput transcriptomic data from microarrays and next-generation sequencing became widely accessible. As a result, research projects dissecting small RNA pathways often produce sequencing data that can be complex and difficult to perform appropriate data analysis for without specialized or advanced computational knowledge. Many researchers end up only study a subset of small RNAs, outsourcing their analysis, or piecing together a pipeline using tools developed for mRNA sequencing. We aim to reduce this barrier to entry in the field and improve reproducibility by creating an open-source, user-friendly data processing pipeline for small RNA sequencing. To create a simple, reproducible pipeline, we utilized the Common Workflow Language (CWL) and Python, while otherwise minimizing dependencies. The pipeline reads a configuration file and sample sheets that can be easily modified by a user to run the complete analysis from raw fastq file to summary statistics and publication-ready plots. We present AQuATx (automated quantitative analysis of transcript expression) for small RNAs and the analysis of C. elegans germline tissue as an example data set. Our software will allow bench scientists with little to no computational knowledge to easily analyze their small RNA sequencing data. Overall, the final software will be a valuable tool for anyone interested in studying small RNAs.
Open Access
Impact of actual and self-perceived body type on visual perception of distances
(Colorado State University. Libraries, 2015) Branan, Matthew, author; Turk, Phil, advisor; Witt, Jessica, committee member; Hess, Ann, committee member
We investigate several questions regarding the proposition that physical body size and one's image of their own body type affect the ability to make accurate judgements of distances. Data collected include subjects' guesses of distances of four cones set 10, 15, 20, and 25 meters away and the weight, BMI, and self-perception of body image for each of 67 subjects. Interest lies in determining the covariates that are most important in explaining one's ability to accurately judge distances and whether weight or BMI is the better explainer among the physical body size predictors. We utilize linear mixed models to account for correlation among each subjects' own distance guesses and to allow for flexible modeling of subject-specific effects. Flexibility is further promoted through use of model averaging techniques to account for model selection uncertainty inherent in typical approaches in which an analyst selects only one model from which inferences are made. A generalization of the coefficient of determination from ordinary linear models is made to the linear mixed model setting (R²LMM) in order to provide an additional goodness measure for fixed effects and for individual fixed effects themselves. Baseline differences among subjects' ability to accurately judge distances are so vast that extracting the importance of the fixed effects becomes difficult. It is found that body size is a significant predictor of subjects' ability to accurately judge distances but body image is not at the 0.05 significance level. We recommend choosing weight over BMI as a predictor of guessing behavior based on information criteria, model averaging, and the generalized R²LMM. Specifically, heavier individuals tend to guess more accurately.
Open Access
k-simplex volume optimizing projection algorithms for high-dimensional data sets
(Colorado State University. Libraries, 2021) Stiverson, Shannon J., author; Kirby, Michael, advisor; Peterson, Chris, advisor; Adams, Henry, committee member; Hess, Ann, committee member
Many applications produce data sets that contain hundreds or thousands of features, and consequently sit in very high dimensional space. It is desirable for purposes of analysis to reduce the dimension in a way that preserves certain important properties. Previous work has established conditions necessary for projecting data into lower dimensions while preserving pairwise distances up to some tolerance threshold, and algorithms have been developed to do so optimally. However, although similar criteria for projecting data into lower dimensions while preserving k-simplex volumes has been established, there are currently no algorithms seeking to optimally preserve such embedded volumes. In this work, two new algorithms are developed and tested: one which seeks to optimize the smallest projected k-simplex volume, and another which optimizes the average projected k-simplex volume.
Open Access
Pre-slaughter factors affecting mobility, blood parameters, bruising, and muscle pH of finished beef cattle in the United States
(Colorado State University. Libraries, 2023) Sullivan, Paxton, author; Edwards-Callaway, Lily, advisor; Hess, Ann, committee member; Nair, Mahesh Narayanan, committee member
Decades of work have focused on reducing fear, stress, and discomfort in cattle moving through the pre-slaughter phase by improving and promoting low-stress animal handling, transportation, and management processes. Even still, there is limited information about the effects of pre-slaughter factors on animal welfare and meat quality outcomes in finished cattle in the United States. The objective of this study was to track individual animals through the slaughter process to identify pre-slaughter factors associated with key welfare and quality outcomes. A total of 454 cattle from one slaughter facility were included in the study. Pre-slaughter factors assessed included: distance traveled, lairage density, lairage duration, season, and truck waiting time. Animal-related characteristics, i.e., body weight, breed, and sex, were also recorded. One trained observer scored mobility of all study cattle using the North American Meat Institute's 1-4 scale (i.e., normal to extremely reluctant to move). Postmortem, exsanguination blood was collected on animals and analyzed for cortisol, creatine kinase, and lactate. Carcass bruising was scored using a modified version of the National Beef Quality Audit's bruise scoring methodology (i.e., no bruise, one bruise that was ≤ the size of a deck of cards, one bruise that was > than the size of a deck of cards, and multiple bruises). Ultimate muscle pH was measured 32 to 36 hours postmortem. Multi-predictor models were selected for each outcome variable using Aikake Information Criterion (AIC). Continuous outcome variables were analyzed using linear mixed-effects models and categorical outcome variables with mixed-effects logistic regression models. Increased truck waiting time was associated with increased cortisol (P = 0.04) and lactate (P = 0.02) concentrations. Similarly, an increase in lairage duration was associated with an increase in creatine kinase (P = 0.05) and the odds of cattle being bruised (P = 0.03). Less space allowance per animal in lairage was associated with increased odds of cattle having impaired mobility (P = 0.01). There was a seasonal effect for many of the measured outcomes; the summer season was associated with greater lactate concentrations (P < 0.0001), increased odds of impaired mobility (P < 0.0001), and increased odds of carcass bruising (P = 0.003). The findings of this study indicate that many of the pre-slaughter factors assessed influence key welfare and meat quality outcomes of finished beef cattle, warranting future research and consideration.
Open Access
Random regression models for the prediction of days to finish in beef cattle
(Colorado State University. Libraries, 2011) Speidel, Scott Eugene, author; Enns, R. Mark, advisor; Crews, Denny, committee member; Peel, R. Kraig, committee member; Hess, Ann, committee member
To view the abstract, please see the full text of the document.
Open Access
Sampling methodology tradeoffs: evaluating monitoring strategies for the endangered humpback chub (Gila cypha) in the Little Colorado River, Arizona
(Colorado State University. Libraries, 2014) Pearson, Kristen Nicole, author; Kendall, William, advisor; Winkelman, Dana, committee member; Hess, Ann, committee member
Implementation of a reliable monitoring program is essential to informed population management. When recovering a sensitive species, priority should be on minimizing human induced negative effects, given already reduced population abundance. Thus, it is crucial to evaluate monitoring programs and make changes when more efficient techniques become available. To assess tradeoffs in sampling effort first necessitates obtaining accurate demographic parameter estimates. However, obtaining such estimates may be challenging especially when assessing a migratory species monitored on its spawning ground. Due to concerns regarding sampling availability, in such cases, it may be necessary to evaluate temporary emigration from the study site to avoid generating biased estimates of survival, detection and spawning probabilities. Evaluating temporary emigration is especially important when non-annual spawning is anticipated, as skipped spawners may be unavailable for detection during annual sampling events. Since the late 1980s, population monitoring for the potamodromous humpback chub (HBC) Gila cypha within the Lower Colorado River Basin (LCRB) has focused on hoop-net sampling within their primary spawning ground, the Little Colorado River (LCR). However, questions remain unanswered regarding their spawning strategy. Thus, due to the likely presence of both resident and migratory fish and suspected non-annual spawning, I evaluated temporary emigration from the LCR, which I equate to skipped spawning. Using, robust design mark-recapture methodologies, I was able to generate unbiased estimates of survival and skipped spawning probabilities as well as spawner abundance. Given concern for handling induced stress due to intensive hoop-net sampling and to gain additional insight into HBC life history strategies and population dynamics, in 2009, a passive detection system (i.e. full duplex PIT tag antenna array) was implemented in the LCR. With the addition of the array, this afforded an opportunity to evaluate sampling methodology tradeoffs between hoop-netting and array detections. Thus, using simulation analysis, and demographic parameter estimates generated from my skipped spawning analysis, I assessed the potential benefits and shortcomings of reducing hoop-net sampling effort and supplementing recapture data with passive array detections. From my analysis, I found considerable evidence for skipped spawning among both male and female HBC. Females on average had a higher probability of failing to spawn in a year subsequent to spawning (i.e. γ"male = 0.46 (95% credible interval [CRI]: 0.11, 0.81) and γ"female = 0.55 (95% CRI: 0.30, 0.75), although better sexing data is necessary to confirm this difference. Annual variability in skipped spawning probability was high (i.e. process variance (σ2) = 0.306) while survival probability remained stable throughout the study period (i.e. S = 0.75 (95% CRI: 0.66, 0.82), σ2 = 0.005). Based on my most reliable skipped spawning probability estimates, (i.e. probability a spawner transitions to a skipped spawner (γ") = 0.45 (95% CRI: 0.10, 0.80) and a skipped spawner remains a skipped spawner (γ') = 0.60 (95% CRI: 0.26, 0.83)) which exclude sex, I found HBC in the LCRB have an average breeding cycle of every 2.12 years, conditional on survival. By employing these estimates in simulation analysis, I found that hoop-net sampling can be reduced and supplemented with array detections without negatively affecting estimability of adult HBC survival and skipped spawning probabilities, given detection efficiency of the array remains sufficiently high. Because the array provides insight outside of traditional sampling periods and does not require repeated handling of this imperiled fish, it affords a viable means of reducing hoop-net sampling effort, thus, offering a potentially more efficient monitoring strategy.
Open Access
Stonecat ecology in St. Vrain Creek, CO
(Colorado State University. Libraries, 2018) D'Amico, Timothy W., author; Winkelman, Dana, advisor; Kendall, William, committee member; Hess, Ann, committee member
Stonecat Noturus flavus are a small-bodied native catfish found from southern Canada to the southern United States, and from the Appalachian Mountains to the Rocky Mountains. In Colorado, there are two remaining populations of Stonecat, including one geographically isolated population in St. Vrain Creek, which runs through the Front Range in Longmont, CO. There are five major drainages running through Colorado's Front Range, which is where most of the state's population is concentrated. As such, these streams are highly urbanized. When compared to the other four major Front Range streams, St. Vrain Creek contains a disproportionately high number of native fish species, including Colorado Species of Special Concern such as Stonecats. There has not yet been a quantitative analysis of population demographic parameters or individual habitat selection preferences of Stonecats. I sought to estimate both of these through a mark-recapture study using passive integrated transponder (PIT) tags. There are a number of assumptions associated with mark-recapture studies which I addressed through individual experiments, including tag loss, physical closure and detection probability of known tags. I evaluated tag loss under laboratory conditions. PIT tags were surgically implanted into the peritoneal cavity of Stonecats (n = 157) ranging from 71 mm to 213 mm through an incision closed with a single Braunamid suture and the fish were monitored for 120 weeks. After 120 weeks, there were fifteen lost tags (9.6%) and eight mortalities (5.0%). I evaluated our dataset of individual encounter histories and covariates including time since tagging, fish length and tag type in a multistate model framework using Program MARK. Time since tagging has an inverse effect on tag loss; if fish are going to lose tags, it will be relatively soon post-tagging. Additionally, fish length has a negative effect, with tag loss decreasing with fish length. These results support our assumption that using PIT tags to individually mark Stonecats is an appropriate method, and we now have a better understanding of tag loss rates over a long-term study period. I evaluated population demographic parameters and individual habitat selection preferences of Stonecats in a field experiment. PIT tags were surgically implanted in Stonecats (n = 679) ranging from 70 mm to 230 mm. I monitored tagged Stonecats with both static and mobile PIT antennae. Our results from the static antennae show that the proportion of Stonecat encounters are higher at night and during the summertime. From the mobile PIT antenna results, I determined Stonecats prefer coarse substrate at an intermediate velocity (0.29 m/s) and intermediate depth (0.3 m). Conclusions from this study will be used to inform future urban stream management in conjunction with managing for sensitive fishes such as Stonecats.