Obesity among Iranian Adolescent Girls: Location of Residence and Parental Obesity

This cross-sectional study was conducted to investigate the prevalence and predictors of overweight and obesity by location of residence among randomly-selected 2,577 urban school girls aged 12-17 years in Rasht, Iran. Data on age, frequency of skipping breakfast per week, physical activity, hours of television viewing, self-perception about body condition, and home address were collected. Birthweight of the girls, educational levels of parents, weights and heights of parents, and employment status of mothers were asked to the parents using a self-administrated questionnaire. The overall prevalence of overweight and obesity in this population was 18.6% and 5.9% respectively. Overweight or obesity was more common among girls from low-income areas compared to high-income areas (21.6% vs 17.1%, p<0.001). Maternal education was positively related to overweight/obesity of the girls. Results of logistic regression analysis showed that risk of overweight/obesity was higher in girls whose either parent was overweight or obese. Furthermore, living in low-income areas and skipping breakfast were independently related to overweight/ obesity. These data suggest that overweight and obesity are a public-health concern among school girls, especially in low-income areas in Rasht. Knowing risk factors in population subgroups is important for planners in the country because it helps target interventions

Multiple Congenital Anomalies in a Preterm Neonate with G6PD Deficiency from Consanguineous Parents

Introduction: Congenital anomalies can be defined as structural or functional disorders, including metabolic disorders. The prevalence of congenital anomalies is not high. Case Presentation: We would like to present a 34-week- preterm neonate with glucose-6-phosphate dehydrogenase deficiency who was born with several fetal anomalies from consanguineous parents. Mother had a twin-birth pregnancy which one of twins died because of lung hemorrhage and the second twin was born with multiple anomalies four fingers in both hands, short legs attached to the pelvic bone, and absence of tibia, fibula, and ankle bones. Hemimelia, which was mostly known as the congenital deformity and a type of phocomelia, is extremely rare. To detect most of these types of anomalies, magnetic resonance imaging, radiography, ultrasound, and computed tomography scan can be used. Conclusion: Congenital anomalies are the cause of many infants' deaths. To detect most of these types of anomalies, MRI, radiography, ultrasound, and computed tomography (CT) scan can be used

Predicting parameters of heat transfer in a shell and tube heat exchanger using aluminum oxide nanofluid with artificial neural network (ANN) and self-organizing map (SOM)

This study is a model of artificial perceptron neural network including three inputs to predict the Nusselt number and energy consumption in the processing of tomato paste in a shelland-tube heat exchanger with aluminum oxide nanofluid. The Reynolds number in the range of 150–350, temperature in the range of 70–90 K, and nanoparticle concentration in the range of 2–4% were selected as network input variables, while the corresponding Nusselt number and energy consumption were considered as the network target. The network has 3 inputs, 1 hidden layer with 22 neurons and an output layer. The SOM neural network was also used to determine the number of winner neurons. The advanced optimal artificial neural network model shows a reasonable agreement in predicting experimental data with mean square errors of 0.0023357 and 0.00011465 and correlation coefficients of 0.9994 and 0.9993 for the Nusselt number and energy consumption data set. The obtained values of eMAX for the Nusselt number and energy consumption are 0.1114, and 0.02, respectively. Desirable results obtained for the two factors of correlation coefficient and mean square error indicate the successful prediction by artificial neural network with a topology of 3-22-2.https://www.mdpi.com/journal/sustainabilityMechanical and Aeronautical Engineerin

ZnO nanowire microelectrode arrays for integration with neuronal networks

Microelectrode arrays (MEAs) have been shown as a successful approach for neuroscientists to monitor the signal communication within the neuronal networks for understanding the functionality of the nervous system. However, using conventional planar MEAs is shown to be incapable of precise signal recording from neuronal networks at single-cell resolution due to low signal-to-ratio (SNR). This thesis looks at developing an electronic platform that comprises of zinc oxide nanowires (ZnO-NWs) on MEAs as a future device to record action potential (AP) signals with high SNR from human neuronal networks at single-cell resolution. Specifically, I studied the controlled growth of ZnO nanowires with various morphologies at exact locations across the substrate. I then investigated the biocompatibility of ZnO nanowires with different morphology and geometry for interaction with human NTera2.D1 (hNT) neurons. Finally, I examined the electrical characteristics of MEAs that were integrated with ZnO nanowires and metal encapsulated ZnO nanowires in comparison to the planar MEAs. The hydrothermal growth of ZnO nanowires is thoroughly investigated as a technique to allow synthesis of the nanowires at a low temperature (95°C) with a low cost and high scalability that can also be applied on flexible substrates. The morphology of the ZnO nanowires was varied (diameters of 20–300 nm, lengths of 0.15–6.2 µm, aspect ratios of 6–95 and densities of 10–285 NWs/µm²) by controlling the critical growth parameters such as the precursor concentration (2.5–150 mM), growth time (1–20 h) and additive polyethylenimine (PEI) concentration (0–8 mM). The diameter and length of the ZnO nanowires were increased by increasing the precursor concentration and growth time. Using the standard precursor concentration of 25 mM, growth times of up to 4 h were found effective for the active growth of the nanowires due to the consumption of the precursor ions and precipitation of ZnO. The addition of 6 mM PEI to the growth solution was shown to mediate the growth solution, allowing the extension of the nanowire growth to 20 h or longer. The PEI molecules were also attached to the lateral faces of the nanowires that confined their lateral growth and promoted their axial growth (enhanced aspect ratio from 12 ± 3 to 67 ± 21). Standard photolithography techniques were also introduced to selectively grow ZnO nanowires on exact locations across the substrates. The role of the ZnO seed layer geometry, seed layer area and gap, on the growth of ZnO nanowires was also investigated. Despite using the constant growth parameters (25 mM of precursor concentration with 4 h of growth time) changing the seed line widths (4 µm–1 mm) and the gap between the seed lines (2 µm–800 µm) resulted in the morphology of the nanowires to vary across the same substrate (diameters of 50–240 nm, lengths of 1.2–4.6 µm, aspect ratios of 9–34 and densities of 28–120 NWs/µm²). The seed area ratio of 50% was determined as a threshold to influence the nanowire morphology, where decreasing the seed area ratio below 50% (by increasing the adjacent gap or decreasing the seed layer area) increased the growth rate of the nanowires. The biocompatibility of ZnO nanowires with human hNT neurons was investigated in this work for the first time. The adhesion and growth of hNT neurons on the arrays of ZnO nanowire florets were determined to be influenced by both geometry and morphology of the nanowires. The growth of the hNT neurons was promoted by 30% compared to the control Si/SiO₂ substrate surface when ZnO nanowires with lengths shorter than 500 nm and densities higher than 350 NWs/µm² were grown. The hNT neurons on all nanowires were also demonstrated to be functionally viable as they responded to the glutamate stimulation. ZnO nanowires were shown to improve the electrical properties of the MEAs by reducing the electrochemical impedance due to the increased 3D surface area. The ZnO nanowires that were grown with 50 mM of precursor concentration for 4 h of growth time lowered the impedance from 835 ± 40 kΩ of planar Cr/Au MEAs to 540 ± 20 kΩ at a frequency of 1 kHz. In contrast, the ZnO nanowires that were grown with PEI for 35 h showed that despite the increased surface area by a factor of 45× the impedance was found to be quite high, 2.25 ± 0.2 MΩ at 1 kHz of frequency. The adsorption of PEI molecules to the lateral surfaces of the nanowires was thought to behave as a passivation layer that could have restricted the charge transfer characteristics of the ZnO-NW MEAs. Encapsulation of the pristine ZnO nanowires that were grown with standard precursor concentration of 25 mM for 4 h of growth time with different metallic layers (Cr/Au, Ti and Pt) further improved the electrical characteristics of the MEAs. The ZnO nanowires that were encapsulated with a 10 nm thin layer of Ti and Pt achieved the lowest electrochemical impedance of 400 ± 25 kΩ at 1 kHz in this work. The robustness of the Ti encapsulated ZnO nanowires were also improved in comparison to the PEI ZnO nanowires. The improved electrochemical characteristics and mechanical stability of the MEAs integrated with metal encapsulated ZnO nanowires have shown a great promise for improving the SNR of recording signals from neuronal cells for long term measurements. This work concludes that both pristine ZnO nanowire MEAs and metal encapsulated ZnO nanowire MEAs will be capable of recording AP signals from human neuronal networks at single-cell resolution. However, further optimisation and extensions of the work are required to record AP signals from human neuronal cells

ZnO nanowire microelectrode arrays for integration with neuronal networks

Microelectrode arrays (MEAs) have been shown as a successful approach for neuroscientists to monitor the signal communication within the neuronal networks for understanding the functionality of the nervous system. However, using conventional planar MEAs is shown to be incapable of precise signal recording from neuronal networks at single-cell resolution due to low signal-to-ratio (SNR). This thesis looks at developing an electronic platform that comprises of zinc oxide nanowires (ZnO-NWs) on MEAs as a future device to record action potential (AP) signals with high SNR from human neuronal networks at single-cell resolution. Specifically, I studied the controlled growth of ZnO nanowires with various morphologies at exact locations across the substrate. I then investigated the biocompatibility of ZnO nanowires with different morphology and geometry for interaction with human NTera2.D1 (hNT) neurons. Finally, I examined the electrical characteristics of MEAs that were integrated with ZnO nanowires and metal encapsulated ZnO nanowires in comparison to the planar MEAs. The hydrothermal growth of ZnO nanowires is thoroughly investigated as a technique to allow synthesis of the nanowires at a low temperature (95°C) with a low cost and high scalability that can also be applied on flexible substrates. The morphology of the ZnO nanowires was varied (diameters of 20–300 nm, lengths of 0.15–6.2 µm, aspect ratios of 6–95 and densities of 10–285 NWs/µm²) by controlling the critical growth parameters such as the precursor concentration (2.5–150 mM), growth time (1–20 h) and additive polyethylenimine (PEI) concentration (0–8 mM). The diameter and length of the ZnO nanowires were increased by increasing the precursor concentration and growth time. Using the standard precursor concentration of 25 mM, growth times of up to 4 h were found effective for the active growth of the nanowires due to the consumption of the precursor ions and precipitation of ZnO. The addition of 6 mM PEI to the growth solution was shown to mediate the growth solution, allowing the extension of the nanowire growth to 20 h or longer. The PEI molecules were also attached to the lateral faces of the nanowires that confined their lateral growth and promoted their axial growth (enhanced aspect ratio from 12 ± 3 to 67 ± 21). Standard photolithography techniques were also introduced to selectively grow ZnO nanowires on exact locations across the substrates. The role of the ZnO seed layer geometry, seed layer area and gap, on the growth of ZnO nanowires was also investigated. Despite using the constant growth parameters (25 mM of precursor concentration with 4 h of growth time) changing the seed line widths (4 µm–1 mm) and the gap between the seed lines (2 µm–800 µm) resulted in the morphology of the nanowires to vary across the same substrate (diameters of 50–240 nm, lengths of 1.2–4.6 µm, aspect ratios of 9–34 and densities of 28–120 NWs/µm²). The seed area ratio of 50% was determined as a threshold to influence the nanowire morphology, where decreasing the seed area ratio below 50% (by increasing the adjacent gap or decreasing the seed layer area) increased the growth rate of the nanowires. The biocompatibility of ZnO nanowires with human hNT neurons was investigated in this work for the first time. The adhesion and growth of hNT neurons on the arrays of ZnO nanowire florets were determined to be influenced by both geometry and morphology of the nanowires. The growth of the hNT neurons was promoted by 30% compared to the control Si/SiO₂ substrate surface when ZnO nanowires with lengths shorter than 500 nm and densities higher than 350 NWs/µm² were grown. The hNT neurons on all nanowires were also demonstrated to be functionally viable as they responded to the glutamate stimulation. ZnO nanowires were shown to improve the electrical properties of the MEAs by reducing the electrochemical impedance due to the increased 3D surface area. The ZnO nanowires that were grown with 50 mM of precursor concentration for 4 h of growth time lowered the impedance from 835 ± 40 kΩ of planar Cr/Au MEAs to 540 ± 20 kΩ at a frequency of 1 kHz. In contrast, the ZnO nanowires that were grown with PEI for 35 h showed that despite the increased surface area by a factor of 45× the impedance was found to be quite high, 2.25 ± 0.2 MΩ at 1 kHz of frequency. The adsorption of PEI molecules to the lateral surfaces of the nanowires was thought to behave as a passivation layer that could have restricted the charge transfer characteristics of the ZnO-NW MEAs. Encapsulation of the pristine ZnO nanowires that were grown with standard precursor concentration of 25 mM for 4 h of growth time with different metallic layers (Cr/Au, Ti and Pt) further improved the electrical characteristics of the MEAs. The ZnO nanowires that were encapsulated with a 10 nm thin layer of Ti and Pt achieved the lowest electrochemical impedance of 400 ± 25 kΩ at 1 kHz in this work. The robustness of the Ti encapsulated ZnO nanowires were also improved in comparison to the PEI ZnO nanowires. The improved electrochemical characteristics and mechanical stability of the MEAs integrated with metal encapsulated ZnO nanowires have shown a great promise for improving the SNR of recording signals from neuronal cells for long term measurements. This work concludes that both pristine ZnO nanowire MEAs and metal encapsulated ZnO nanowire MEAs will be capable of recording AP signals from human neuronal networks at single-cell resolution. However, further optimisation and extensions of the work are required to record AP signals from human neuronal cells

Obesity among Iranian Adolescent Girls: Location of Residence and Parental Obesity

This cross-sectional study was conducted to investigate the prevalence and predictors of overweight and obesity by location of residence among randomly-selected 2,577 urban school girls aged 12-17 years in Rasht, Iran. Data on age, frequency of skipping breakfast per week, physical activity, hours of television viewing, self-perception about body condition, and home address were collected. Birthweight of the girls, educational levels of parents, weights and heights of parents, and employment status of mothers were asked to the parents using a self-administrated questionnaire. The overall prevalence of overweight and obesity in this population was 18.6% and 5.9% respectively. Overweight or obesity was more common among girls from low-income areas compared to high-income areas (21.6% vs 17.1%, p<0.001). Maternal education was positively related to overweight/obesity of the girls. Results of logistic regression analysis showed that risk of overweight/obesity was higher in girls whose either parent was overweight or obese. Furthermore, living in low-income areas and skipping breakfast were independently related to overweight/ obesity. These data suggest that overweight and obesity are a public-health concern among school girls, especially in low-income areas in Rasht. Knowing risk factors in population subgroups is important for planners in the country because it helps target interventions