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In Vitro Osteogenic Study of hMSCs Under Diabetic Conditions

Description

Patients with type 2 diabetes mellitus experience a slower healing process and poor osteointegration, making it difficult for them to heal properly after a bone fracture. This study aims to compare the proliferation and differentiation of human mesenchymal stromal cells

Patients with type 2 diabetes mellitus experience a slower healing process and poor osteointegration, making it difficult for them to heal properly after a bone fracture. This study aims to compare the proliferation and differentiation of human mesenchymal stromal cells at different glucose concentrations, as well as with an advanced glycated end-product (AGE) concentration, to mimic a healthy, prediabetic, and diabetic environment in an in vitro model over several experiments. Each experiment was composed of treatment groups in either growth or osteogenic media, with varying levels of glucose concentration or an advanced glycated end-product concentration. The treatment groups were cultured in 24 well plates over 28 days with staining of FITC-maleimide, DAPI, or alkaline phosphatase conducted at varying time points. The plates were imaged, then analyzed in ImageJ and GraphPad Prism. The study supports that at 28 days in culture, the more glucose added to osteogenic media treatment groups, the lower the nuclear count. At 14 days the same is true of growth media treatment groups, though the trend does not persist until 28 days. It does not seem that cell surface area of osteogenic groups, and growth media treatment groups was affected by glucose level. At 14 days, the alkaline phosphatase expression was unaffected by glucose level. However, at the 28 day time point the higher the glucose level of osteogenic treatment groups, the less expression of alkaline phosphatase. The effect of the added AGE concentration on hMSC osteogenesis was inconclusive. Overall, this study enhanced understanding of the role that glucose and AGEs play in the bone healing process for diabetic patients, allowing for future improvements of biomaterials and engineered tissue.

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2019-05

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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

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.

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2020-05

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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

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.

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Date Created
2018-12

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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

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.

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Date Created
2021-05

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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

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.

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Created

Date Created
2021-05