Correction of Fatty Acids Metabolism as Treatment Strategy of Autism

Autism is a neurodevelopmental disorder clinically presented as abnormalities in social interaction and communication, repetitive behaviors, usually accompanied by various neurobehavioral disorders, such as learning disability, hyperactivity and anxiety

Neurotoxins and Autism

Recently, a great concern has risen about the increasing prevalence of autism as a neurodevelopmental disorder. Environmental factors as significant contributors to children’s health through a wide range of routes are linked to remarkable increases in this disorder. It is well known and accepted that young children are more vulnerable to environmental toxins, compared to adults. Modern day lifestyles with more mercury and lead exposures, fast food, cell phones, and microwaves place children at higher risk of neurotoxicity. Moreover, a huge number of synthetic chemicals termed as high-production-volume (HPV) chemicals are found in many products such as medications, cosmetics, building materials, plastic, and car fuels. These HPVs highly contribute to brain damage in developing infants. Other environmental toxins include thalidomide, valproic acid, misoprostol, and many infectious agents among which are pathogenic bacteria or their metabolites are found to be neurotoxic and/or linked to incidences of autism. This chapter summarizes the most important routes of exposure to environmental neurotoxins and explains how these toxins are related to the remarkable increase in the prevalence of autism through different etiological mechanisms such as oxidative stress, neuroinflammation, impaired neurochemistry and glutamate excitotoxicity

Hardware Design and Software Simulation for Four Classical Cryptosystems

AbstractThe classical Cryptosystems are very old cryptosystems that were primarily used in the pre-computer era. They are considered weak nowadays and too easy to break, especially with computers. However, these simple cryptosystems give a good illustration of several of the important ideas of the cryptography and cryptanalysis's Systems. They are considered as the heart of cryptography science and it's good to start with. In this paper, we are going to design several cryptosystems using Java programming language such as shift cipher, affine cipher and others. In addition, we will practice on several number theory algorithms especially the modular arithmetic and prime numbers as well as on decomposing a large problem into modules and testing a circuit that is too large to test exhaustively. The software can be used then to send and receive an encrypted messages using the email systems. Moreover, a hardware design for Caesar and Affine Ciphers will be simulated via Multisim software and implemented using the logic gates and circuits and the skills learned from digital logic design course

Increase of cytosolic phospholipase A2 as hydrolytic enzyme of phospholipids and autism cognitive, social and sensory dysfunction severity

Abstract Background Autism is neurodevelopmental disorder that is characterized by developmental, behavioral, social and sensory abnormalities. Researchers have focused in last years in immunological alteration and inflammation as a hot subject in autism field. This work aims to study the alteration in phospholipids (PE, PS, and PC) together with the change in cPLA2 concentration as the main phospholipid hydrolytic enzyme in autistic patients compared to control. It was also extended to find a correlation between these biomarkers and severity of autism measured as childhood autism rating scale (CARS), Social responsiveness scale (SRS), and Short sensory profile (SSP). Methods Phospholipids (PE, PS, PC) and cPLA2 as biochemical parameters were determined in the plasma of 48 Saudi autistic male patients, categorized as mild-moderate and severe as indicated by their Childhood Autism Rating Scale (CARS), social responsiveness scale (SRS) and short sensory profile (SSP) and compared to 40 age- and gender-matched control samples. Results The reported data demonstrate significantly lower levels of PE, PS, and PC together with a significant increase in cPLA2. While association between severity of autism and impaired phospholipid concentration was completely lacked, an association between cPLA2 and impaired sensory processing was observed. Conclusions The impaired phospholipid level and remarkable increased in cPLA2 concentration asserted their roles in the etiology of autism. Receiver operating characteristic analysis together with predictiveness diagrams proved that the measured parameters could be used as predictive biomarkers of clinical symptoms and provide significant guidance for future therapeutic strategy to re-establish physiological homeostasis

Impaired lipid metabolism markers to assess the risk of neuroinflammation in autism spectrum disorder

Autism spectrum disorder (ASD) is a multifactorial disorder caused by an interaction between environmental risk factors and a genetic background. It is characterized by impairment in communication, social interaction, repetitive behavior, and sensory processing. The etiology of ASD is still not fully understood, and the role of neuroinflammation in autism behaviors needs to be further investigated. The aim of the present study was to test the possible association between prostaglandin E2 (PGE2), cyclooxygenase-2 (COX-2), microsomal prostaglandin E synthase-1 (mPGES-1), prostaglandin PGE2 EP2 receptors and nuclear kappa B (NF-κB) and the severity of cognitive disorders, social impairment, and sensory dysfunction. PGE2, COX-2, mPGES-1, PGE2-EP2 receptors and NF-κB as biochemical parameters related to neuroinflammation were determined in the plasma of 47 Saudi male patients with ASD, categorized as mild to moderate and severe as indicated by the Childhood Autism Rating Scale (CARS) or the Social Responsiveness Scale (SRS) or the Short Sensory Profile (SSP) and compared to 46 neurotypical controls. The data indicated that ASD patients have remarkably higher levels of the measured parameters compared to neurotypical controls, except for EP2 receptors that showed an opposite trend. While the measured parameter did not correlate with the severity of social and cognitive dysfunction, PGE2, COX-2, and mPGES-1 were remarkably associated with the dysfunction in sensory processing. NF-κB was significantly increased in relation to age. Based on the discussed data, the positive correlation between PGE2, COX-2, and mPGES-1 confirm the role of PGE2 pathway and neuroinflammation in the etiology of ASD, and the possibility of using PGE2, COX-2 and mPGES-1 as biomarkers of autism severity. NF-κB as inflammatory inducer showed an elevated level in plasma of ASD individuals. Receiver operating characteristic analysis together with predictiveness diagrams proved that the measured parameters could be used as predictive biomarkers of biochemical correlates to ASD

Identification of Biomarkers of Impaired Sensory Profiles among Autistic Patients

<div><p>Background</p><p>Autism is a neurodevelopmental disorder that displays significant heterogeneity. Comparison of subgroups within autism, and analyses of selected biomarkers as measure of the variation of the severity of autistic features such as cognitive dysfunction, social interaction impairment, and sensory abnormalities might help in understanding the pathophysiology of autism.</p><p>Methods and Participants</p><p>In this study, two sets of biomarkers were selected. The first included 7, while the second included 6 biomarkers. For set 1, data were collected from 35 autistic and 38 healthy control participants, while for set 2, data were collected from 29 out of the same 35 autistic and 16 additional healthy subjects. These markers were subjected to a principal components analysis using either covariance or correlation matrices. Moreover, libraries composed of participants categorized into units were constructed. The biomarkers used include, PE (phosphatidyl ethanolamine), PS (phosphatidyl serine), PC (phosphatidyl choline), MAP2K1 (Dual specificity mitogen-activated protein kinase kinase 1), IL-10 (interleukin-10), IL-12, NFκB (nuclear factor-κappa B); PGE2 (prostaglandin E2), PGE2-EP2, mPGES-1 (microsomal prostaglandin synthase E-1), cPLA2 (cytosolic phospholipase A2), 8-isoprostane, and COX-2 (cyclo-oxygenase-2).</p><p>Results</p><p>While none of the studied markers correlated with CARS and SRS as measure of cognitive and social impairments, six markers significantly correlated with sensory profiles of autistic patients. Multiple regression analysis identifies a combination of PGES, mPGES-1, and PE as best predictors of the degree of sensory profile impairment. Library identification resulted in 100% correct assignments of both autistic and control participants based on either set 1 or 2 biomarkers together with a satisfactory rate of assignments in case of sensory profile impairment using different sets of biomarkers.</p><p>Conclusion</p><p>The two selected sets of biomarkers were effective to separate autistic from healthy control subjects, demonstarting the possibility to accurately predict the severity of autism using the selected biomarkers. The effectiveness of the identified libraries lied in the fact that they were helpful in correctly assigning the study population as control or autistic patients and in classifying autistic patients with different degree of sensory profile impairment.</p></div

Determination of statistical significance of components in principal component analysis using Monte Carlo simulation.

<p>Set 1 (a) and 2 (b) data obtained from mild/moderate and severe autism groups were analyzed with PCA. Scree plots show eigenvalues of raw data (blue), as well as the 50^th (green) and 95^th percentile (yellow) simulated data. A principal component was considered statistically significant (circled in red) whenever its raw data eigenvalue lay above the corresponding 95^th percentile simulated data eigenvalue.</p

Variable (marker) contributions to the first and second principal components (PC1 and PC2) in principal component analysis of 29 autistic and 16 healthy control subjects.

<p>Data were collected for a set of 6 markers; PGE2, PGE2-EP2, PGES, COX-2, cPLA2, and 8-isoprostane (set 2). In this analysis, autistic and control groups were mostly separated on PC1 coordinate. The most discriminatory variables are shown in boldface. The portion of variance explained by each principal component is shown between parentheses. * indicates a statistically significant principal component.</p

Variable (marker) contributions to the first and second principal components (PC1 and PC2) in principal component analysis of six markers tat corelated with sensory profiles of autistic patients.

<p>Variable (marker) contributions to the first and second principal components (PC1 and PC2) in principal component analysis of six markers tat corelated with sensory profiles of autistic patients.</p