Knowledge of Diabetes Characteristics by Students at University of Tabuk, Saudi Arabia

This is a study of university students’ awareness of diabetes mellitus, and the extent of their knowledge about it. The research is a quantitative design based on a survey of students (N = 700) at the University of Tabuk in the Saudi province of Tabuk. The findings were that the students’ knowledge of diabetes indicators was encouraging, and that the faculty’s periodic diabetes awareness programs should be continued to ensure that new students can recognise diabetes characteristics. In assessing variables for knowledge of the disease in relation to the demographics of people on the Tabuk University campus, marital status and weight were significant indicators. The conclusion was that awareness programs should be continued to avoid complacency and to combat the disease.

Effect of dates on blood glucose and lipid profile among patients with type 2 diabetes

Poor fruit and vegetable consumption is one of the 10 major risk factors for mortality.There is a misconception regarding the consumption of dates among patients with diabetes.This manuscript assessed the effects of date consumption on fasting and postprandial blood glucose,glycated hemoglobin,total cholesterol,triglycerides,low-density lipoproteins,high-density lipoproteins,and microbial markers.Four literature databases were searched for relevant articles.Of the 595 studies retrieved,24 assessed the effects of dates on glycemic control and lipids.Overall,the evidence suggests that dates have a lowering effect on blood glucose.Dates reduce total cholesterol and triglyceride levels and increase high-density lipoprotein levels.Dates also promote the abundance of beneficial gut microbiota.Therefore,patients with diabetes and dyslipidemia can consume dates to reduce their blood glucose,cholesterol,and triglycerides.

Interactions of Aurein with Model Membranes and Antimalarials

Aurein is a cationic antimicrobial peptide, rich in phenylalanine residues. Although the peptide has been extensively studied, its mechanism of action is not fully understood and has not been established. This project is focused on studying the interactions of aurein with model biological membranes and antimalarials using Fourier Transform Infrared (FTIR), fluorescence, dynamic light scattering (DLS), atomic force microscopy (AFM), thermogravimetric analysis (TGA), and differential scanning calorimetry (DSC) techniques. FTIR data revealed conformational changes to the secondary structure of the peptide in the presence of the model membranes. The strongest interactions of aurein were found with DOPC and lipid raft systems. Fluorescence data revealed some differences in the mechanism of interaction between aurein and lipid rafts. Topographical analysis was performed using atomic force microscopy (AFM). AFM images of the peptide with its lipid rafts showed a change in surface roughness suggesting a different mechanism of interaction. DLS data in agreement with FTIR confirmed that aurein interacts differently with the lipid rafts. The results gathered from this study provided new insights on the interaction of aurein. On the other hand, drug-drug interaction issues continue to present a major dilemma for the clinician caring for complex patients such as those infected with infectious disease. This study has examined the interaction of aurein with quinine, primaquine, and chloroquine. Significant interactions between aurein and antimalarials occured at a higher concentration of antimalarials. Interactions between aurein and anti-malarials reveal a strong interaction between aurein and primaquine. Interactions between aurein and quinine or chloroquine were found to be weak and negligible. FTIR, TGA, and DSC may be used in a complementary way to gain insights into the possible drug-drug interactions involving aurein. These studies are needed to initiate in vivo controlled interaction studies between antibiotics and antimalarials.

The interplay mechanism between IDH mutation, MGMT-promoter methylation, and PRMT5 activity in the progression of grade 4 astrocytoma: unraveling the complex triad theory

Background:The dysregulation of Isocitrate dehydrogenase(IDH)and the subsequent production of 2-Hydroxyglutrate(2HG)may alter the expression of epigenetic proteins in Grade 4 astrocytoma.The interplay mechanism between IDH,O-6-methylguanine-DNA methyltransferase(MGMT)-promoter methylation,and protein methyltransferase proteins-5(PRMT5)activity,with tumor progression has never been described.Methods:A retrospective cohort of 34 patients with G4 astrocytoma is classified into IDH-mutant and IDH-wildtype tumors.Both groups were tested for MGMT-promoter methylation and PRMT5 through methylation-specific and gene expression PCR analysis.Inter-cohort statistical significance was evaluated.Results:Both IDH-mutant WHO grade 4 astrocytomas(n=22,64.7%)and IDH-wildtype glioblastomas(n=12,35.3%)had upregulated PRMT5 gene expression except in one case.Out of the 22 IDH-mutant tumors,10(45.5%)tumors showed MGMT-promoter methylation and 12(54.5%)tumors had unmethylated MGMT.All IDH-wildtype tumors had unmethylated MGMT.There was a statistically significant relationship between MGMT-promoter methylation and IDH in G4 astrocytoma(p-value=0.006).Statistically significant differences in progression-free survival(PFS)were also observed among all G4 astrocytomas that expressed PRMT5 and received either temozolomide(TMZ)or TMZ plus other chemotherapies,regardless of their IDH or MGMT-methylation status(p-value=0.0014).Specifically,IDH-mutant tumors that had upregulated PRMT5 activity and MGMT-promoter methylation,who received only TMZ,have exhibited longer PFS.Conclusions:The relationship between PRMT5,MGMT-promoter,and IDH is not tridirectional.However,accumulation of D2-hydroxyglutarate(2-HG),which partially activates 2-OG-dependent deoxygenase,may not affect their activities.In IDH-wildtype glioblastomas,the 2HG-2OG pathway is typically inactive,leading to PRMT5 upregulation.TMZ alone,compared to TMZ-plus,can increase PFS in upregulated PRMT5 tumors.Thus,using a PRMT5 inhibitor in G4 astrocytomas may help in tumor regression.

Cytotoxicity, Toxicity and Anticancer Activity of Manuka Honey, Saudi’s Honey and Peganum harmala Plant against Cancer Cells

Cancer occurs when the body’s cells grow beyond the usual control. Normal body cells multiply in a controlled manner and undergo apoptosis when the body no longer needs them. Different types of cancers exist, and the common ones include breast, cervical, prostate, lung, colon, and skin cancers. Several factors have been associated with cancers, and these factors include poor dieting, exposure to harmful chemicals and radiation, weak immune system, and genetics. Cancer presents an enormous health threat in the modern world and thus the need to identify an effective treatment. The conventional treatments used in the management of cancer include chemotherapy and physiotherapy. These forms of cancer treatments usually have enormous side effects on the subjects. In this respect, an alternative form of treatment would be effective in managing cancer patients. A substantial number of natural products have been observed to be effective in the management of cancer. These natural products include plants and other natural substances such as honey. This study focuses on the efficiency of natural products in the treatment of cancer. Also, the anticancer effects of Peganum harmala, Manuka honey, and Saudi honey will be analyzed. Bee honey and Peganum harmala have been traditionally used in the treatment of cancer. The extracts from Peganum harmala plant have also been shown to exhibit divers’ antitumor effects similar to the mode of action of a vast number of anticancer agents. These established hypotheses thus give the rationale for this study. In this experiment, extracts were obtained from Peganum harmala leaves and exposed to cervical, lung, and prostate cancer cells. Similarly, solutions of Manuka honey and Saudi honey were exposed to the cervical, lung, and prostate cancer cells. The experiment duration was 24 hours, which obtained results were recorded and analyzed. Peganum harmala extracts inhibit cancer cell growth at different and achievable concentrations. Manuka honey highly inhibits the growth of HeLa cancer cells while Saudi honey highly inhibits the growth of A549 cells. Peganum harmala can form an effective treatment for managing several types of cancers. Manuka Honey can be applied as an effective treatment for managing cervical cancer while Saudi honey can form an effective treatment for managing lung cancers.

Synthesis and Characterization of Poly Styrene-Co-Poly 2-Hydroxyethylmethacrylate (HEMA) Copolymer and an Investigation of Free-Radical Copolymerization Propagation Kinetics by Solvent Effects

A series of homo and copolymers of styrene (ST) and 2-hydroxyethyl methacrylate (HEMA) in three different media (bulk, tetrahydrofuran, and benzene) have been investigated by free radical polymerization method. The samples obtained from the synthesis were characterized by Fourier Transform-Infrared spectroscopy (FT-IR), proton nuclear magnetic resonance spectroscopy (1H NMR), atomic force microscopy (AFM), and differential scanning calorimetry (DSC). The results show that the synthesis of the polymers is more feasible under neat conditions rather than solvent directed reaction. Moreover, the DSC data shows that the polystyrene obtained is amorphous in nature and therefore displayed only a glass transition signal rather than crystallization and melting peaks. In addition, this study indicates that homolopolymerization of styrene via free radical polymerization tends to be preferable in less polar solvents like THF than in non-polar solvents like benzene. Benzene might destabilize the formation of the reactive radicals leading to the formation of the products. In summary, the homolpolymerization of styrene is more feasible than the homopolymerization 2-hydroxyethyl methacrylate under the experimental setup used. Styrene is more reactive than 2-hydroxyethyl methacrylate than free radical polymerization reaction due in part of the generation of the benzylic radical intermediate which is more stable leading to the formation of products than alkyl radical which are less stable. Furthermore, polymerization of styrene under neat conditions is preferable in solvent-assisted environments. The choice of solvent for the synthesis of these polymers is crucial and therefore the selection of solvent that leads to the formation of a more stable reaction intermediate is more favorable. It is worth noting that the structure of the proposed copolymer consists of a highly polar and hydrophilic monomer, 2-hydroxyethyl methacrylate and a highly non-polar and hydrophobic monomer, styrene. These functionalities constitute an amphiphilic copolymer with diverse characteristics. A plausible explanation underlying our observations is that the reaction conditions employed in the synthesis of these copolymers might not be the right route required under free radical polymerization.

Topological Aspects of Dendrimers via Connection-Based Descriptors

Topological indices(TIs)have been practiced for distinct wide-ranging physicochemical applications,especially used to characterize and model the chemical structures of various molecular compounds such as dendrimers,nanotubes and neural networks with respect to their certain properties such as solubility,chemical stability and low cytotoxicity.Dendrimers are prolonged artificially synthesized or amalgamated natural macromolecules with a sequential layer of branches enclosing a central core.A present-day trend in mathematical and computational chemistry is the characterization of molecular structure by applying topological approaches,including numerical graph invariants.Among topological descriptors,Zagreb connection indices(ZCIs)have much importance.This manuscript involves the establishment of general results to calculate ZCIs,namely first ZCI(FZCI),second ZCI(SZCI),third ZCI(TZCI),modified FZCI,modified SZCI and modified TZCI of two special types of dendrimers nanostars,namely,poly propylene imine octamin(PPIO)dendrimer and poly(propyl)ether imine(PPEtIm)dendrimer.Furthermore,we provide the numerical and graphical comparative analysis of our calculated results for both types of dendrimers with each other.

Comparative analysis of Nε-carboxymethyl-lysine and inflammatory markers in diabetic and non-diabetic coronary artery disease patients

BACKGROUND Coronary artery disease(CAD)is a major cause of death worldwide,and India contributes to about one-fifth of total CAD deaths.The development of CAD has been linked to the accumulation of Nε-carboxymethyl-lysine(CML)in heart muscle,which correlates with fibrosis.AIM To assess the impact of CML and inflammatory markers on the biochemical and cardiovascular characteristics of CAD patients with and without diabetes.METHODS We enrolled 200 consecutive CAD patients who were undergoing coronary angiography and categorized them into two groups based on their serum glycosylated hemoglobin(HbA1c)levels(group I:HbA1c≥6.5;group II:HbA1c<6.5).We analyzed the levels of lipoproteins,plasma HbA1c levels,CML,interleukin-6(IL-6),tumor necrosis factor alpha(TNF-α),and nitric oxide.RESULTS Group I (81 males and 19 females) patients had a mean age of 54.2 ± 10.2 years, with a mean diabetes duration of4.9 ± 2.2 years. Group II (89 males and 11 females) patients had a mean age of 53.2 ± 10.3 years. Group I had moresevere CAD, with a higher percentage of patients with single vessel disease and greater stenosis severity in the leftanterior descending coronary artery compared to group II. Group I also exhibited a larger left atrium diameter.Group I patients exhibited significantly higher levels of CML, TNF-α, and IL-6 and lower levels of nitric oxide ascompared with group II patients. Additionally, CML showed a significant positive correlation with IL-6 (r = 0.596,P = 0.001) and TNF-α (r = 0.337, P = 0.001) and a negative correlation with nitric oxide (r=-4.16, P = 0.001). Oddsratio analysis revealed that patients with CML in the third quartile (264.43-364.31 ng/mL) were significantlyassociated with diabetic CAD at unadjusted and adjusted levels with covariates.

Frequency of Null Phenotypes of Glutathione S-Transferase M1 and T1 among the Populations of Tabuk (Northwestern Part of Saudi Arabia)

Background: The variability in the distribution of the null phenotypes of GSTM1 and GSTT1, due to total or partial gene deletion resulting in the lack of the active enzyme, has been reported in different populations, especially in ethnically well-defined groups but not in Tabuk. This study investigated the variability in the distribution of the null phenotypes of GSTM1 and GSTT1 in the population of Tabuk (northwestern part of Saudi Arabia). Method: This study was conducted on 200 subjects of Tabuk—northwestern part of Saudi Arabia among which 100 were chronic smokers and 100 were nonsmokers. The subjects were reporting to hospital for routine checkup. All were without past history of any chronic disease and no significant abnormality. GST genotyping was done by multiplex PCR-based methods. The smoker and control groups were compared using a chi-square test with P GSTM1 deletion homozygosity of 14% and 1% was reported among non smokers and smokers, respectively whereas GSTT1 deletion homozygosity of 28% and 6% was reported among non smokers and smokers, respectively. Our results indicate that there are major differences in allelic distribution of GSTM1 and GSTT1 genes between the two groups investigated. Combined analysis of both genes revealed that 15% of smokers and non smokers harbor the deleted genotype of GSTM1 and 34% of smokers and non smokers harbor the deleted genotype of GSTT1 with significant differences. Conclusion: This study enables selecting subgroups among the general population who are more susceptible to DNA damage and will help genetic studies on the association of GST polymorphisms with disease risks and drug effects in Arab population. Studies with a larger sample size are needed to evaluate and confirm the validity of our results.

The Effects of Pragmatics Competence in EFL University Learners

As we know, Pragmatics is the way we convey meaning through communication, so the study aims at student’s opinions on the use of English language as a means of communication and to show the significance of language function, context, and authentic situations to develop pragmatic competence in Sudanese English Language university learners. To achieve the objectives, the study used a questionnaire to address the study questions and objectives. 150 employed students participated in the questionnaire. The study found that the students have positive views toward the using of the language as communicative means in various, functions, contexts, and authentic situations inside and outside the classroom to enhance the student’s fluency in using the target language as well as the take care about the language forms to avoid imperfect using of the language.

Hemoglobin Subunit Beta Gene Polymorphism rs33949930 T>C and Risk of Sickle Cell Disease—A Case Control Study from Tabuk (Northwestern Part of Saudi Arabia)

Background: Sickle cell disease and sickle cell trait are common erythrocyte disorders that are most often caused by a point mutation (rs334, designated HbS) in the hemoglobin beta gene (HBB);however of this fact, there is extreme variability in occurrence and clinical presentation of sickle cell disease which may be explained by some other genetic changes associated with the gene. In the present study we examined the association between HBB gene polymorphism rs33949930 T>C in the occurrence of sickle cell disease in Saudi Arabia population. Materials and Methods: A case control study of 100 sickle cell disease patients and 100 healthy controls from Tabuk, Saudi Arabia. HBB gene rs33949930 T>C polymorphism was analyzed using Allele specific polymerase chain reaction technique. Results: It was observed that the genotype percentages TT, TC and CC among the patients with sickle cell disease were 63.0%, 35.0% and 2.0% and healthy controls were 68.0%, 27.0% and 5.0% respectively. Allele frequency for T allele was observed to be fT = 0.20 and fT = 0.19, where as for C allele was fC = 0.80 and fC = 0.81 among cases and controls respectively (p = 0.29). Compared to the TT genotype, the odds ratio of 1.4 (95% CI 0.76 - 2.57), risk ratio of 1.2 (95% CI 0.86 - 1.65) and risk difference of 8.4 (-6.66 - 23.38) for heterozygous genotype of HBB rs33949930 T>C was observed in relation to sickle cell disease. In addition, some difference in the laboratory values was observed among sickle cell disease patients with the different variants of HBB gene rs33949930 T>C polymorphism, especially the carriers of heterozygous TC genotype;however, the difference doesn’t reach to statically significant number. Conclusion: Present study suggested that there was not any significant association between HBB gene rs33949930 T>C polymorphism and occurrence of sickle cell disease. However, the heterozygous TC genotype of the polymorphism showed some higher ratios among cases as compared to healthy control group.

Anomaly Detection for Industrial Internet of Things Cyberattacks

The evolution of the Internet of Things(IoT)has empowered modern industries with the capability to implement large-scale IoT ecosystems,such as the Industrial Internet of Things(IIoT).The IIoT is vulnerable to a diverse range of cyberattacks that can be exploited by intruders and cause substantial reputational andfinancial harm to organizations.To preserve the confidentiality,integrity,and availability of IIoT networks,an anomaly-based intrusion detection system(IDS)can be used to provide secure,reliable,and efficient IIoT ecosystems.In this paper,we propose an anomaly-based IDS for IIoT networks as an effective security solution to efficiently and effectively overcome several IIoT cyberattacks.The proposed anomaly-based IDS is divided into three phases:pre-processing,feature selection,and classification.In the pre-processing phase,data cleaning and nor-malization are performed.In the feature selection phase,the candidates’feature vectors are computed using two feature reduction techniques,minimum redun-dancy maximum relevance and neighborhood components analysis.For thefinal step,the modeling phase,the following classifiers are used to perform the classi-fication:support vector machine,decision tree,k-nearest neighbors,and linear discriminant analysis.The proposed work uses a new data-driven IIoT data set called X-IIoTID.The experimental evaluation demonstrates our proposed model achieved a high accuracy rate of 99.58%,a sensitivity rate of 99.59%,a specificity rate of 99.58%,and a low false positive rate of 0.4%.

Intelligent Intrusion Detection System for the Internet of Medical Things Based on Data-Driven Techniques

Introducing IoT devices to healthcare fields has made it possible to remotely monitor patients’information and provide a proper diagnosis as needed,resulting in the Internet of Medical Things(IoMT).However,obtaining good security features that ensure the integrity and confidentiality of patient’s information is a significant challenge.However,due to the computational resources being limited,an edge device may struggle to handle heavy detection tasks such as complex machine learning algorithms.Therefore,designing and developing a lightweight detection mechanism is crucial.To address the aforementioned challenges,a new lightweight IDS approach is developed to effectively combat a diverse range of cyberattacks in IoMT networks.The proposed anomaly-based IDS is divided into three steps:pre-processing,feature selection,and decision.In the pre-processing phase,data cleaning and normalization are performed.In the feature selection step,the proposed approach uses two data-driven kernel techniques:kernel principal component analysis and kernel partial least square techniques to reduce the dimension of extracted features and to ameliorate the detection results.Therefore,in decision step,in order to classify whether the traffic flow is normal or malicious the kernel extreme learning machine is used.To check the efficiency of the developed detection scheme,a modern IoMT dataset named WUSTL-EHMS-2020 is considered to evaluate and discuss the achieved results.The proposed method achieved 99.9%accuracy,99.8%specificity,100%Sensitivity,99.9 F-score.

Probability Based Regression Analysis for the Prediction of Cardiovascular Diseases

Machine Learning(ML)has changed clinical diagnostic procedures drastically.Especially in Cardiovascular Diseases(CVD),the use of ML is indispensable to reducing human errors.Enormous studies focused on disease prediction but depending on multiple parameters,further investigations are required to upgrade the clinical procedures.Multi-layered implementation of ML also called Deep Learning(DL)has unfolded new horizons in the field of clinical diagnostics.DL formulates reliable accuracy with big datasets but the reverse is the case with small datasets.This paper proposed a novel method that deals with the issue of less data dimensionality.Inspired by the regression analysis,the proposed method classifies the data by going through three different stages.In the first stage,feature representation is converted into probabilities using multiple regression techniques,the second stage grasps the probability conclusions from the previous stage and the third stage fabricates the final classifications.Extensive experiments were carried out on the Cleveland heart disease dataset.The results show significant improvement in classification accuracy.It is evident from the comparative results of the paper that the prevailing statistical ML methods are no more stagnant disease prediction techniques in demand in the future.

Intelligent Intrusion Detection for Industrial Internet of Things Using Clustering Techniques

The rapid growth of the Internet of Things(IoT)in the industrial sector has given rise to a new term:the Industrial Internet of Things(IIoT).The IIoT is a collection of devices,apps,and services that connect physical and virtual worlds to create smart,cost-effective,and scalable systems.Although the IIoT has been implemented and incorporated into a wide range of industrial control systems,maintaining its security and privacy remains a significant concern.In the IIoT contexts,an intrusion detection system(IDS)can be an effective security solution for ensuring data confidentiality,integrity,and availability.In this paper,we propose an intelligent intrusion detection technique that uses principal components analysis(PCA)as a feature engineering method to choose the most significant features,minimize data dimensionality,and enhance detection performance.In the classification phase,we use clustering algorithms such as K-medoids and K-means to determine whether a given flow of IIoT traffic is normal or attack for binary classification and identify the group of cyberattacks according to its specific type for multi-class classification.To validate the effectiveness and robustness of our proposed model,we validate the detection method on a new driven IIoT dataset called X-IIoTID.The performance results showed our proposed detection model obtained a higher accuracy rate of 99.79%and reduced error rate of 0.21%when compared to existing techniques.

Analyzing the Impact of Blockchain Models for Securing Intelligent Logistics through Unified Computational Techniques

Blockchain technology has revolutionized conventional trade.The success of blockchain can be attributed to its distributed ledger characteristic,which secures every record inside the ledger using cryptography rules,making it more reliable,secure,and tamper-proof.This is evident by the significant impact that the use of this technology has had on people connected to digital spaces in the present-day context.Furthermore,it has been proven that blockchain technology is evolving from new perspectives and that it provides an effective mechanism for the intelligent transportation system infrastructure.To realize the full potential of the accurate and efficacious use of blockchain in the transportation sector,it is essential to understand the most effective mechanisms of this technology and identify the most useful one.As a result,the present work offers a priority-based methodology that would be a useful reference for security experts in managing blockchain technology and its models.The study uses the hesitant fuzzy analytical hierarchy process for prioritizing the different blockchain models.Based on the findings of actual performance,alternative solution A1 which is Private Blockchain model has an extremely high level of security satisfaction.The accuracy of the results has been tested using the hesitant fuzzy technique for order of preference by similarity to the ideal solution procedure.The study also uses guidelines from security researchers working in this domain.

A Novel Approach for Security Enhancement of Data Encryption Standard

Data Encryption Standard(DES)is a symmetric key cryptosystem that is applied in different cryptosystems of recent times.However,researchers found defects in the main assembling of the DES and declared it insecure against linear and differential cryptanalysis.In this paper,we have studied the faults and made improvements in their internal structure and get the new algorithm for Improved DES.The improvement is being made in the substitution step,which is the only nonlinear component of the algorithm.This alteration provided us with great outcomes and increase the strength of DES.Accordingly,a novel 6×6 good quality S-box construction scheme has been hired in the substitution phase of the DES.The construction involves the Galois field method and generates robust S-boxes that are used to secure the scheme against linear and differential attacks.Then again,the key space of the improved DES has been enhanced against the brute force attack.The out-comes of different performance analyses depict the strength of our proposed substitution boxes which also guarantees the strength of the overall DES.

A Note on Bell-Based Bernoulli and Euler Polynomials of Complex Variable

In this article,we construct the generating functions for new families of special polynomials including two parametric kinds of Bell-based Bernoulli and Euler polynomials.Some fundamental properties of these functions are given.By using these generating functions and some identities,relations among trigonometric functions and two parametric kinds of Bell-based Bernoulli and Euler polynomials,Stirling numbers are presented.Computational formulae for these polynomials are obtained.Applying a partial derivative operator to these generating functions,some derivative formulae and finite combinatorial sums involving the aforementioned polynomials and numbers are also obtained.In addition,some remarks and observations on these polynomials are given.

Insights on antioxidant therapeutic strategies in type 2 diabetes mellitus:A narrative review of randomized control trials

BACKGROUND Type 2 diabetes mellitus(T2DM)is a metabolic disease of impaired glucose utilization.Imbalance in generation and elimination of free radicals generate oxidative stress which modulates glucose metabolism and insulin regulation,resulting in the occurrence and progression of diabetes and associated complications.Antioxidant supplements in T2DM can be seen as a potential preventive and effective therapeutic strategy.AIM To compare randomized controlled trials(RCTs)in which antioxidants have been shown to have a therapeutic effect in T2DM patients.METHODS We systematically searched the electronic database PubMed by keywords.RCTs evaluating the effect of antioxidant therapy on glycaemic control as well as oxidant and antioxidant status as primary outcomes were included.The outcomes considered were:A reduction in blood glucose;changes in oxidative stress and antioxidant markers.Full-length papers of the shortlisted articles were assessed for the eligibility criteria and 17 RCTs were included.RESULTS The administration of fixed-dose antioxidants significantly reduces fasting blood sugar and glycated hemoglobin and is associated with decreased malondialdehyde,advanced oxidation protein products,and increased total antioxidant capacity.CONCLUSION Antioxidant supplements can be a beneficial approach for the treatment of T2DM.

Nonlinear Components of a Block Cipher over Eisenstein Integers

In block ciphers,the nonlinear components,also known as substitution boxes(S-boxes),are used with the purpose to induce confusion in cryptosystems.For the last decade,most of the work on designing S-boxes over the points of elliptic curves,chaotic maps,and Gaussian integers has been published.The main purpose of these studies is to hide data and improve the security levels of crypto algorithms.In this work,we design pair of nonlinear components of a block cipher over the residue class of Eisenstein integers(EI).The fascinating features of this structure provide S-boxes pair at a time by fixing three parameters.However,in the same way,by taking three fixed parameters only one S-box is obtained through a prime field-dependent Elliptic curve(EC),chaotic maps,and Gaussian integers.The newly designed pair of S-boxes are assessed by various tests like nonlinearity,bit independence criterion,strict avalanche criterion,linear approximation probability,and differential approximation probability.