Thyroid profile and LDH Isoenzymes as prognostic biomarkers for diabetic and/or obese subjects

Background: This study aimed to evaluate the levels of thyroid hormones and lactate dehydrogenase (LDH) isoenzymes in obese and/or diabetic patients. Subjects and methods: Forty male subjects categorized into four equal groups; group 1: Non obese control subjects, group 2: Subjects suffering from type 2 diabetes mellitus (T2DM), group 3: Obese subjects (BMI ≥ 30 kg/m2) and group 4: Subjects thatwere obese and had type 2 diabetes mellitus (T2DM). Liver, kidney, lipid, thyroid hormones, total LDH and LDH isoenzymes levels were determined. Results: There was a significant increase of TSH level (p<0.001) in diabetic group as compared with control group and a highly significant increase of TSH was obtained in obese and obese diabetic groups versus control and diabetic patients. LDH 2 was also highly significantly decreased in obese and obese diabetic groups versus diabetic patients. Percentage of LDH 4 was significantly decreased in both diabetic and obese groups and not significantly changed in obese diabetic patients as compared with the control group. LDH 5 percentage showed very highly significant decrease in diabetic, obese and highly significant decrease in obese diabetic groups when compared with control subjects while it was not significantly changed in obese and obese diabetic groups as compared with diabetic patients. Conclusion: LDH isozymes can be used as valuable diagnostic markers for metabolic syndrome. This may help to explore the metabolic changes associated with obesity and diabetes complication and following up the complication of these abnormalities.Keywords: Thyroid profile, lactate dehydrogenase, obesity, diabetes

SIRT3 and cancer: Tumor promoter or suppressor?

AbstractSirtuins (SIRT1–7), the mammalian homologues of the Sir2 gene in yeast, have emerging roles in age-related diseases, such as cardiac hypertrophy, diabetes, obesity, and cancer. However, the role of several sirtuin family members, including SIRT1 and SIRT3, in cancer has been controversial. The aim of this review is to explore and discuss the seemingly dichotomous role of SIRT3 in cancer biology with particular emphasis on its potential role as a tumor promoter and tumor suppressor. This review will also discuss the potential role of SIRT3 as a novel therapeutic target to treat cancer

Optimization of Fuzzy Logic Controller for Supervisory Power System Stabilizers

This paper presents a powerful supervisory power system stabilizer (PSS) using an adaptive fuzzy logic controller driven by an adaptive fuzzy set (AFS). The system under study consists of two synchronous generators, each fitted with a PSS, which are connected via double transmission lines. Different types of PSS-controller techniques are considered. The proposed genetic adaptive fuzzy logic controller (GAFLC)-PSS, using 25 rules, is compared with a static fuzzy logic controller (SFLC) driven by a fixed fuzzy set (FFS) which has 49 rules. Both fuzzy logic controller (FLC) algorithms utilize the speed error and its rate of change as an input vector. The adaptive FLC algorithm uses a genetic algorithmto tune the parameters of the fuzzy set of each PSS. The FLC’s are simulated and tested when the system is subjected to different disturbances under a wide range of operating points. The proposed GAFLC using AFS reduced the computational time of the FLC, where the number of rules is reduced from 49 to 25 rules. In addition, the proposed adaptive FLC driven by a genetic algorithm also reduced the complexity of the fuzzy model, while achieving a good dynamic response of the system under study

Face mask detection using deep learning on NVIDIA Jetson Nano

In December 2019, the coronavirus pandemic started. Coronavirus desease-19 (COVID-19) is transmitted directly from contaminated surfaces via direct touch. To combat the virus, a multitude of equipment is needed. Masks are a vital element of personal protection in crowded places. As a result, determining if a person is wearing a face mask is critical to assimilating to contemporary society. To accomplish the objective, the model presented in this paper used deep learning libraries and OpenCV. This approach was chosen for safety concerns due to its high resource efficiency during deployment. The classifier was built using the MobileNetV2 structure, which was designed to be lightweight and capable of being utilized in embedded devices such as the NVIDIA Jetson Nano to do real-time mask recognition. The stages of model construction were collecting, pre-processing, splitting data, creating the model, training the model, and applying the model. This system utilized image processing techniques and deep learning to process a live video feed. When someone is not wearing a mask, the output eventually produces an alarm sound through a built-in buzzer. Experimental results and testing were used to verify the suggested system's performance. Including both training and testing, the achieved recognition rate was 99%

Optimization of Fuzzy Logic Controller for Supervisory Power System Stabilizers

This paper presents a powerful supervisory power system stabilizer (PSS) using an adaptive fuzzy logic controller driven by an adaptive fuzzy set (AFS). The system under study consists of two synchronous generators, each fitted with a PSS, which are connected via double transmission lines. Different types of PSS-controller techniques are considered. The proposed genetic adaptive fuzzy logic controller (GAFLC)-PSS, using 25 rules, is compared with a static fuzzy logic controller (SFLC) driven by a fixed fuzzy set (FFS) which has 49 rules. Both fuzzy logic controller (FLC) algorithms utilize the speed error and its rate of change as an input vector. The adaptive FLC algorithm uses a genetic algorithmto tune the parameters of the fuzzy set of each PSS. The FLC’s are simulated and tested when the system is subjected to different disturbances under a wide range of operating points. The proposed GAFLC using AFS reduced the computational time of the FLC, where the number of rules is reduced from 49 to 25 rules. In addition, the proposed adaptive FLC driven by a genetic algorithm also reduced the complexity of the fuzzy model, while achieving a good dynamic response of the system under study

The effects of the internal and the external factors affecting artificial intelligence (AI) adoption in e-innovation technology projects in the UAE? Applying both innovation and technology acceptance theories

This study has examined factors, such as technology and employee influence on artificial intelligence (AI) adoption of e-innovative projects in the United Arab Emirates. The present study revealed the success or failure of e-innovation adoption in the public sector of the UAE and hinted at potential e-innovative projects to consider essential factors before adopting it. The study's sample covered the government sector, and the data collection method was a survey questionnaire with a sample size of 1037 responses made up of government employees. This paper was mainly built upon the diffusion of innovation and technology acceptance theories. The analysis findings showed that technology (an external factor) significantly and positively contributed to adopting AI e-innovation technology. Further analysis revealed that employee (internal factor) proxies directly influenced the adoption of AI e-innovation technology. Overall, internal and external factors contributed to adopting e-innovation technology in the United Arab Emirates. For future directions, additional factors related to the market should be considered to explore their contribution

Hepatoprotective Effect of Captopril on Liver Toxicity Induced by High and Low Dose of Paracetamol in Rats:Histological Study

Many patients may administered medications like captopril (ACE inhibitor) for treatment of chronic diseases and may also take Paracetamol as an Over The Counter (OTC) drug which may interact with captopril. Therefore, the aim of this study is to evaluate of the hepatoprotective effect of captopril on liver toxicity induced by low and high dose of paracetamol in rats. This study was conducted in two phases: first study for low dose of paracetamol (300 mg/kg); animals were divided into 4 groups of 6 rats each (n = 6); all groups were treated orally either 0.9 % Normal Saline (NS), captopril 20 mg/kg, paracetamol 300 mg/kg or captopril 20 mg/kg plus paracetamol 300 mg/kg for 10 consecutive days. Second study for single high dose of paracetamol (3000 mg/kg); animals were divided into 4 groups of 6 rats each (n = 6); all groups were pretreated orally either 0.9 % Normal Saline (NS) or captopril 20 mg/kg for 7 consecutive days followed by single oral administration of Paracetamol 3000 mg/kg or normal saline. The administration of Paracetamol or normal saline was performed 24 hours after the last administration of captopril. After 48 hours of hepatic injury induction, the animals were then sacrificed and the liver was removed for histopathological studies. Low dose (300 mg/kg) for 10 days and high single dose (3000 mg/kg) of paracetamol produced hepatotoxic effects. While captopril 20 mg/kg showed marked protection against changes induced by low and high dose of paracetamol on the liver

The high correlation between counts and area fractions of lipofuscin granules, a biomarker of oxidative stress in muscular dystrophies

Images of cryostat unstained sections of two skeletal muscles, diaphragm and extensor digitorum longus (EDL), from wild-type normal and dystrophic mdx mice were captured with a fluorescence microscope, binarised and analysed by an automated procedure using ImageJ free software. The numbers, Feret diameters and areas of autofluorescent lipofuscin (LF)-like granules in the sections were determined from the binary images. The mean numbers of counted LF granules per mm(3) muscle tissue correlated highly (r ≥ 0.9) with the area fractions of the granules in sections of both normal and mdx muscles. The similar distribution patterns of granule sizes in sections of diaphragm and EDL muscles are consistent with the high correlations

Determination of the Adequate Thickness of Granular Subbase Beneath Foundations

Where the native soils have poor structural qualities or are expansive, the soil investigation report may recommend importation of soils better suited to providing a subbase for structures. This requires considering two soil layers in bearing capacity calculations. Calculation of the ultimate bearing capacity of shallow footing on a two layered system of soil depends on the pattern of the failure surface that develops below the footing. For a weak clay layer overlaid by a top dense sand layer, previous studies assumed that the failure surface is a punching shear failure through the upper sand layer and Prandtl's failure mode in the bottom weak clay layer. In this paper, the bearing capacity of subbase layer underneath by a soft clay layer is investigated. The properties of the subbase material are measured in the laboratory. Design charts were obtained which can be used to select the suitable thickness of the subbase layer for a design allowable bearing capacity