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Replacing Dietary Meat with Fish Significantly Increases Plasma Glucose without Affecting Protein Glycation

Description

Western diets, high in dietary fat and red meat, are associated with hyperglycemia and weight gain, symptoms that promote insulin resistance and diabetes. Previous studies have shown that elevated glucose promotes glycation of circulating proteins such as albumin, which is thought to lead to hyperglycemia complications. It was hypothesized that…

Western diets, high in dietary fat and red meat, are associated with hyperglycemia and weight gain, symptoms that promote insulin resistance and diabetes. Previous studies have shown that elevated glucose promotes glycation of circulating proteins such as albumin, which is thought to lead to hyperglycemia complications. It was hypothesized that diets with no meat consumption (pesco-vegetarian and lacto-vegetarian) would reduce protein glycation, in comparison to a diet with meat. Forty six healthy adult omnivorous subjects were randomized into one of three groups and instructed to either consume red meat (i.e. meat) or poultry twice per day (control), eliminate meat and increase fish consumption (pesco-vegetarian), or adopt a vegetarian diet devoid of fish, meat or poultry (lacto-vegetarian) for four weeks. Fasting plasma samples were collected from participants at baseline and after 4 weeks of the dietary intervention. Plasma glucose concentrations were measured using a commercially available kit. Percent glycated albumin was measured on a separate aliquot of plasma by mass spectrometry. Plasma glucose concentrations were significantly increased following 4-weeks of pesco-vegetarian diet (P=0.002, paired t-test). Neither the lacto-vegetarian (P=0.898) or the control diet (P=0.233) affected plasma glucose concentrations. Despite the significant increase in plasma glucose following a pesco-vegetarian diet, no change in percent glycated albumin was observed (P>0.50, ANOVA). These findings may indicate a protective effect of the pesco-vegetarian diet on protein glycation in the presence of elevated plasma glucose and suggest the need for additional studies to examine the link between increased fish consumption and glucose regulation.

ContributorsRaad, Noor (Author) / Sweazea, Karen (Thesis director, Committee member) / Borges, Chad (Committee member) / Barrett, The Honors College (Contributor) / School of Life Sciences (Contributor)

Created2015-05

Examination of an Organometallic Complex on Insulin Resistance in Periadolescent Male Rats Following a 10-week High Fat Diet

Description

With the rising prevalence of obesity and diabetes, novel treatments to help mitigate or prevent symptoms of these conditions are warranted. Prior studies have shown that fossilized plant materials found in soil lowers blood sugar in a mouse model of diabetes. The goal of this study is to determine whether…

With the rising prevalence of obesity and diabetes, novel treatments to help mitigate or prevent symptoms of these conditions are warranted. Prior studies have shown that fossilized plant materials found in soil lowers blood sugar in a mouse model of diabetes. The goal of this study is to determine whether a similar organometallic complex (OMC) could prevent insulin resistance in the skeletal muscle brought on by chronic high fat intake by examining the protein expression of key enzymes in the insulin signaling pathway and examining glucoregulatory measures. Six-week-old periadolescent male Sprague-Dawley rats (n=42) were randomly chosen to be fed either a high fat diet (HFD) (20% protein, 20% carbohydrates [6.8% sucrose], 60% fat) or a standard chow diet (18.9% protein, 57.33% carbohydrates, 5% fat) for 10 weeks. Rats from each diet group were then randomly assigned to one of three doses of OMC (0, 0.6, 3.0 mg/mL), which was added to their drinking water and fasting blood glucose was measured at baseline and again at 10 weeks. After 10 weeks, rats were euthanized, and soleus muscle samples were isolated, snap-frozen, and stored at -80°C until analyses. Fasting plasma glucose was measured using a commercially available glucose oxidase kit. Following 6 and 10 weeks, HFD rats developed significant hyperglycemia (p<0.001 and p=0.025) compared to chow controls which was prevented by high dose OMC (p=0.021). After 10 weeks, there were significant differences in fasting serum insulin between diets (p=0.009) where levels were higher in HFD rats. No significant difference was seen in p-PI3K expression between groups. These results suggest that OMC could prevent insulin resistance by reducing hyperglycemia. Further studies are needed to characterize the effects of diet and OMC on the insulin signaling pathway in skeletal muscle, the main site of postprandial glucose disposal. This study was supported by a grant from Isagenix International LLC as well as funds from Barrett, the Honors College at Arizona State University, Tempe Campus.

ContributorsStarr, Ashlee (Author) / Sweazea, Karen (Thesis director) / Johnston, Carol (Committee member) / Hyatt, JP (Committee member) / Sanford School of Social and Family Dynamics (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)

Created2018-12

Multimarker Sensor Development for Intermediate Glycemic Index, A Novel Approach for a Glycated Albumin Sensor

Description

Diabetes mellitus is a disease characterized by many chronic and acute conditions. With the prevalence and cost quickly increasing, we seek to improve on the current standard of care and create a rapid, label free sensor for glycated albumin (GA) index using electrochemical impedance spectroscopy (EIS). The antibody, anti-HA, was…

Diabetes mellitus is a disease characterized by many chronic and acute conditions. With the prevalence and cost quickly increasing, we seek to improve on the current standard of care and create a rapid, label free sensor for glycated albumin (GA) index using electrochemical impedance spectroscopy (EIS). The antibody, anti-HA, was fixed to gold electrodes and a sine wave of sweeping frequencies was induced with a range of HA, GA, and GA with HA concentrations. Each frequency in the impedance sweep was analyzed for highest response and R-squared value. The frequency with both factors optimized is specific for both the antibody-antigen binding interactions with HA and GA and was determined to be 1476 Hz and 1.18 Hz respectively in purified solutions. The correlation slope between the impedance response and concentration for albumin (0 \u2014 5400 mg/dL of albumin) was determined to be 72.28 ohm/ln(mg/dL) with an R-square value of 0.89 with a 2.27 lower limit of detection. The correlation slope between the impedance response and concentration for glycated albumin (0 \u2014 108 mg/dL) was determined to be -876.96 ohm/ln(mg/dL) with an R-squared value of 0.70 with a 0.92 mg/dL lower limit of detection (LLD). The above data confirms that EIS offers a new method of GA detection by providing unique correlation with albumin as well as glycated albumin. The unique frequency response of GA and HA allows for modulation of alternating current signals so that several other markers important in the management of diabetes could be measured with a single sensor. Future work will be necessary to establish multimarker sensing on one electrode.

ContributorsEusebio, Francis Ang (Author) / LaBelle, Jeffrey (Thesis director) / Pizziconi, Vincent (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)

Created2014-05

Developing an Electrochemical Impedance Spectroscopy-Based Insulin Sensor

Description

Currently, the management of diabetes mellitus (DM) involves the monitoring of only blood glucose using self-monitoring blood glucose devices (SMBGs) followed by taking interventional steps, if needed. To increase the amount of information that diabetics can have to base DM care decisions off of, the development of an insulin biosensor…

Currently, the management of diabetes mellitus (DM) involves the monitoring of only blood glucose using self-monitoring blood glucose devices (SMBGs) followed by taking interventional steps, if needed. To increase the amount of information that diabetics can have to base DM care decisions off of, the development of an insulin biosensor is explored. Such a biosensor incorporates electrochemical impedance spectroscopy (EIS) to ensure an extremely sensitive platform. Additionally, anti-insulin antibody was immobilized onto the surface of a gold disk working electrode to ensure a highly specific sensing platform as well. EIS measurements were completed with a 5mV sine wave that was swept through the frequency spectrum of 100 kHz to 1 Hz on concentrations of insulin ranging from 0 pM to 100 μM. The frequency at which the interaction between insulin and its antibody was optimized was determined by finding out at which frequency the R2 and slope of the impedance-concentration plot were best. This frequency, otherwise known as the optimal binding frequency, was determined to be 459 Hz. Three separate electrodes were developed and the impedance data for each concentration measured at 459 Hz was averaged and plotted against the LOG (pM insulin) to construct the calibration curve. The response was calculated to be 263.64 ohms/LOG(pM insulin) with an R2 value of 0.89. Additionally, the average RSD was determined to be 19.24% and the LLD was calculated to be 8.47 pM, which is well below the physiological normal range. These results highlight the potential success of developing commercial point-of-care insulin biosensors or multi-marker devices operating with integrated insulin detection.

ContributorsDecke, Zachary William (Author) / LaBelle, Jeffrey (Thesis director) / Pizziconi, Vincent (Committee member) / Cook, Curtiss (Committee member) / Barrett, The Honors College (Contributor) / Harrington Bioengineering Program (Contributor)

Created2013-05

Characterization of an Optimal Binding Frequency for a Glutaraldehyde Based Point of Care Glucose Sensor

Description

A point of care glucose sensor using electrochemical impedance spectroscopy (EIS) with a glutaraldehyde-linked enzyme shows promise as an effective biosensor platform. This report details the characterization of various factors on optimal binding frequency (OBF) and sensor performance to better prepare the sensor for future experimentation. Utilizing a screen printed…

A point of care glucose sensor using electrochemical impedance spectroscopy (EIS) with a glutaraldehyde-linked enzyme shows promise as an effective biosensor platform. This report details the characterization of various factors on optimal binding frequency (OBF) and sensor performance to better prepare the sensor for future experimentation. Utilizing a screen printed carbon electrode, the necessary amount of glucose oxidase was determined to be 10 mg/mL. Binding time trials ranging from 1-3 minutes demonstrated that 1.5 minutes was the optimal binding time. This timeframe produced the strongest impedance response at each glucose concentration. Using this enzyme concentration and binding time, the native OBF of the biosensor was found to be 1.18 Hz using vector analysis. Temperature testing showed little change in OBF in sensors exposed to 4 \u00B0C through 43.3 \u00B0C. Only exposure to 60 \u00B0C resulted in rapid OBF change which was likely due to glucose oxidase becoming denatured. Humidity tests showed little change in OBF and sensor performance between sensors prepared at the humidities of 7.5%, 10.625% and 16.5% humidity. Alternatively, solutions containing common interference molecules such as uric acid, acetaminophen, and ascorbic acid resulted in a highly shifted OBF and drastically reduced signal.

ContributorsMatloff, Daniel (Co-author) / Khanwalker, Mukund (Co-author) / Johns, Jared (Co-author) / LaBelle, Jeffrey (Thesis director) / Pizziconi, Vincent (Committee member) / Lin, Chi (Committee member) / Dean, W.P. Carey School of Business (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)

Created2018-12

Fetal Growth Models of Cardiac Size and Function, and Prediction of Congenital Cardiomyopathy in Fetuses with Diabetic Mothers

Description

2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing…

2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing fetal heart development but they warrant revalidation and adjustment. 377 normal fetuses with healthy mothers, 98 normal fetuses with diabetic mothers, and 37 fetuses with cardiomyopathy and diabetic mothers had their cardiac structural dimensions, cardiothoracic ratio, valve flow velocities, and heart rates measured by fetal ECHO in a retrospective chart review. Cardiac features were fitted to linear functions, with respect to gestational age, femur length, head circumference, and biparietal diameter and z-scores were created to model normal fetal growth for all parameters. These z-scores were used to assess what metrics had no difference in means between the normal fetuses of both healthy and diabetic mothers but differed from those diagnosed with cardiomyopathy. It was found that functional metrics like mitral and tricuspid E wave and pulmonary velocity could be important predictors for cardiomyopathy when fitted by gestational age, femur length, head circumference, and biparietal diameter. Additionally, aortic and tricuspid annulus diameters when fitted to estimated gestational age showed potential to be predictors for fetal cardiomyopathy. While the metrics overlapped over their full range, combining them together may have the potential for predicting cardiomyopathy in utero. Future directions of this study will explore creating a classifier model that can predict cardiomyopathy using the metrics assessed in this study.

ContributorsMishra, Shambhavi (Co-author) / Numani, Asfia (Co-author) / Sweazea, Karen (Thesis director) / Plasencia, Jonathan (Committee member) / Economics Program in CLAS (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)

Created2021-05

Fetal Growth Models of Cardiac Size and Function, and Prediction of Congenital Cardiomyopathy in Fetuses with Diabetic Mothers

Description

2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing…

2D fetal echocardiography (ECHO) can be used for monitoring heart development in utero. This study’s purpose is to empirically model normal fetal heart growth and function changes during development by ECHO and compare these to fetuses diagnosed with and without cardiomyopathy with diabetic mothers. There are existing mathematical models describing fetal heart development but they warrant revalidation and adjustment. 377 normal fetuses with healthy mothers, 98 normal fetuses with diabetic mothers, and 37 fetuses with cardiomyopathy and diabetic mothers had their cardiac structural dimensions, cardiothoracic ratio, valve flow velocities, and heart rates measured by fetal ECHO in a retrospective chart review. Cardiac features were fitted to linear functions, with respect to gestational age, femur length, head circumference, and biparietal diameter and z-scores were created to model normal fetal growth for all parameters. These z-scores were used to assess what metrics had no difference in means between the normal fetuses of both healthy and diabetic mothers, but differed from those diagnosed with cardiomyopathy. It was found that functional metrics like mitral and tricuspid E wave and pulmonary velocity could be important predictors for cardiomyopathy when fitted by gestational age, femur length, head circumference, and biparietal diameter. Additionally, aortic and tricuspid annulus diameters when fitted to estimated gestational age showed potential to be predictors for fetal cardiomyopathy. While the metrics overlapped over their full range, combining them together may have the potential for predicting cardiomyopathy in utero. Future directions of this study will explore creating a classifier model that can predict cardiomyopathy using the metrics assessed in this study.

ContributorsNumani, Asfia (Co-author) / Mishra, Shambhavi (Co-author) / Sweazea, Karen (Thesis director) / Plasencia, Jon (Committee member) / School of Mathematical and Statistical Sciences (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)

Created2021-05

Deep Learning Application to Improve Quality of Life in Diabetes

Description

Carbohydrate counting has been shown to improve HbA1c levels for people with diabetes. However, the learning curve and inconvenience of carbohydrate counting make it difficult for patients to adhere to it. A deep learning model is proposed to identify food from an image, where it can help the user manage…

Carbohydrate counting has been shown to improve HbA1c levels for people with diabetes. However, the learning curve and inconvenience of carbohydrate counting make it difficult for patients to adhere to it. A deep learning model is proposed to identify food from an image, where it can help the user manage their carbohydrate counting. This early model has a 68.3% accuracy of identifying 101 different food classes. A more refined model in future work could be deployed into a mobile application to identify food the user is about to consume and log it for easier carbohydrate counting.

ContributorsCarreto, Cesar (Author) / Pizziconi, Vincent (Thesis director) / Vernon, Brent (Committee member) / Harrington Bioengineering Program (Contributor) / Barrett, The Honors College (Contributor)

Created2021-05

Systematic Review of the Impact of Genistein on Diabetes Related Outcomes

Description

As the 7th leading cause of death in the world, with over 1.6 millions deaths attributed to it in 2016 alone, diabetes mellitus has been a rising global health concern. Type 1 diabetes is caused by lack of insulin production whereas type 2 diabetes is caused by insulin resistance. Both…

As the 7th leading cause of death in the world, with over 1.6 millions deaths attributed to it in 2016 alone, diabetes mellitus has been a rising global health concern. Type 1 diabetes is caused by lack of insulin production whereas type 2 diabetes is caused by insulin resistance. Both types of diabetes lead to increased glucose levels in the body if left untreated. This, in turn, leads to the development of a host of complications, one of which is ischemic heart disease. Accounting for the death of 16% of the world’s population, ischemic heart disease has been the leading cause of death since 2000. As of 2019, deaths from this disease have risen from 2 million to over 8.9 million globally. While medicine exists to counter the negative outcomes of diabetes mellitus, lower income nations suffer from the lack of availability and high costs of these medications. Therefore, this systematic review was performed to determine whether a non-medicinal treatment could provide similar therapeutic benefits for individuals with diabetes. Genistein is a phytoestrogen found in soy-based products, which has been potentially linked with preventing diabetes and improving diabetes-related symptoms such as hyperglycemia and abnormal insulin levels. We searched PubMed and SCOPUS using the terms ‘genistein’, ‘diabetes’, and ‘glucose’ and identified 32 peer-reviewed articles. In general, preclinical studies demonstrate that genistein decreases body weight as well as circulating glucose and triglycerides concentrations while increasing insulin levels and insulin sensitivity. It also delayed the onset of type 1 and type 2 diabetes. In contrast, clinical studies of genistein in general reported no significant relationship between genistein and body mass, circulating glucose, serum insulin, A1C concentrations, or onset of type 1 diabetes. However, genistein was found to improve insulin sensitivity, delay type 2 diabetes onset and improve serum triglyceride levels. In summary, preclinical and clinical studies suggest that genistein may help delay onset of type 2 diabetes and improve several symptoms associated with the disease. By translating these findings into clinical settings, genistein may offer a cost effective natural approach at mitigating complications associated with diabetes, although additional research is required to confirm these findings.

ContributorsJain, Rijul (Author) / Sweazea, Karen (Thesis director) / Al-Nakkash, Layla (Committee member) / Bolch, Charlotte (Committee member) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)

Created2021-04-16

An Urban Diet Impairs Tibial Vasodilation in Mourning Doves (Zenaida macroura)

Description

Birds maintain resting plasma glucose concentrations (pGlu) nearly twice that of comparably sized mammals. Despite this, birds do not incur much of the oxidative tissue damage that might be expected from a high pGlu. Their ability to stave off oxidative damage allows birds to serve as a negative model of…

Birds maintain resting plasma glucose concentrations (pGlu) nearly twice that of comparably sized mammals. Despite this, birds do not incur much of the oxidative tissue damage that might be expected from a high pGlu. Their ability to stave off oxidative damage allows birds to serve as a negative model of hyperglycemia-related complications, making them ideal for the development of new diabetes treatments with the potential for human application. Previous studies conducted by the Sweazea Lab at Arizona State University aimed to use diet as a means to raise blood glucose in mourning doves (Zenaida macroura) in order to better understand the mechanisms they utilize to stave off oxidative damage. These protocols used dietary interventions—a 60% high fat (HF) “chow” diet, and a high carbohydrate (HC) white bread diet—but were unsuccessful in inducing pathologies. Based on this research, we hypothesized that a model of an urban diet (high in fat, refined carbohydrates, and sodium) might impair vasodilation, as the effect of this diet on birds is currently unknown. We found that tibial vasodilation was significantly impaired in birds fed an urban diet compared to those fed a seed diet. Unexpectedly, vasodilation in the urban diet group was comparable to data of wild-caught birds from previous research, possibly indicating that the birds had already been eating a diet similar to this study’s urban diet before they were caught. This may constitute evidence that the seed diet improved vasodilation while the urban diet more closely mimicked the diet of the birds before the trial, suggesting that the model of the urban diet acted as the control diet in this context. This study is the first step in elucidating avian mechanisms for dealing with diabetogenic diets and has potential to aid in the development of treatments for humans with metabolic syndrome.

ContributorsRenner, Michael William (Author) / Sweazea, Karen (Thesis director) / Johnston, Carol (Committee member) / Basile, Anthony (Committee member) / Dean, W.P. Carey School of Business (Contributor) / School of Life Sciences (Contributor) / Barrett, The Honors College (Contributor)

Created2020-05

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