👤 Elham Nazari

The formation and progression of atherosclerotic plaques occur through cellular dysfunction and remodeling of the extracellular matrix in the sub-endothelial space of vessels. The immunity against specific antigens is suggested to mitigate the atherosclerosis process. Primarily, studies have suggested that certain antigens, such as ox-LDL, ApoB-100, CETP, PCSK9, HSP60, MHC-II-derived peptides, and interleukins, are involved in atherosclerosis. However, recognizing the intricate interplay between immune responses and the formation of arterial plaques is essential to optimize immunization against atherosclerosis. In this review, the roles of some genes were presented in triggering atherosclerotic plaque events. Furthermore, some immunization approaches are presented to target these genes. The studies suggested that vaccination against the progression of atherosclerosis is an essential and effective approach to reducing the high death rate in autoimmune diseases. Show less

Koolen-de Vries syndrome (KdVS) is a rare multisystem genetic disorder due to deletions in the KANSL1 gene. The most common type of seizure documented in these patients is focal impaired consciousness seizure (FICS). These seizures present with difficult-to-distinguish characteristics, including autonomic symptoms, brief loss of consciousness, and post-ictal confusion. The ambiguity of this presentation can make it difficult to detect clinically. This case presents an eight-year-old male child with KdVS who presented to the clinic with complaints of increased outbursts, spatial disorientation, issues with mood and self-regulation, and episodes of "spacing out" as noted by his teacher. The initial diagnosis was dysautonomia and was conservatively managed. However, due to worsening neurocognitive outcomes, neurological referral and work-up were initiated to further elucidate the etiology of his symptoms. The patient's electroencephalography (EEG) findings showed frequent focal sharp waves consistent with FICS. He was then treated accordingly with diazepam and amantadine, which led to a significant improvement in neurological status. This case highlights the importance of the use of EEG in KdVS patients, as well as the implications of implementing guidelines recommending the low threshold required for use of EEG and full neurological work-up for patients with any alarm symptoms possibly indicative of FICS or other epileptiform activity. Show less

Non-alcoholic fatty liver disease (NAFLD) comprises a range of chronic liver diseases that result from the accumulation of excess triglycerides in the liver, and which, in its early phases, is categorized NAFLD, or hepato-steatosis with pure fatty liver. The mortality rate of non-alcoholic steatohepatitis (NASH) is more than NAFLD; therefore, diagnosing the disease in its early stages may decrease liver damage and increase the survival rate. In the current study, we screened the gene expression data of NAFLD patients and control samples from the public dataset GEO to detect DEGs. Then, the correlation betweenbetween the top selected DEGs and clinical data was evaluated. In the present study, two GEO datasets (GSE48452, GSE126848) were downloaded. The dysregulated expressed genes (DEGs) were identified by machine learning methods (Penalize regression models). Then, the shared DEGs between the two training datasets were validated using validation datasets. ROC-curve analysis was used to identify diagnostic markers. R software analyzed the interactions between DEGs, clinical data, and fatty liver. Ten novel genes, including ABCF1, SART3, APC5, NONO, KAT7, ZPR1, RABGAP1, SLC7A8, SPAG9, and KAT6A were found to have a differential expression between NAFLD and healthy individuals. Based on validation results and ROC analysis, NR4A2 and IGFBP1b were identified as diagnostic markers. These key genes may be predictive markers for the development of fatty liver. It is recommended that these key genes are assessed further as possible predictive markers during the development of fatty liver. Show less

The coat color of dromedary is usually uniform and varies from black to white, although dark- to light-brown colors are the most common phenotypes. This project was designed to gain knowledge on novel color-related variants using genotyping-by-sequencing (GBS). The association between the SNPs and coat color was tested using MLM (mixed linear models) with kinship matrix. Three GWAS models including white color vs. non-white color, black vs. non-black color, and light-brown vs. dark-brown color were performed. There were no distinct genetic clusters detected based on the color phenotypes. However, admixture occurred among all individuals of the four different coat color groups. We identified nine significant SNPs associated with white color after Bonferroni correction, located close to Show less