Background Genetic etiologies of autism spectrum disorders (ASD) are complex, and the genetic factors identified so far are very diverse. In complex genetic diseases such as ASD, de novo or inherited chromosomal abnormalities are valuable findings for researchers with respect to identifying the underlying genetic risk factors. With gene mapping studies on these chromosomal abnormalities, dozens of genes have been associated with ASD and other neurodevelopmental genetic diseases. In the present study, we aimed to idenitfy the causative genetic factors in patients with ASD who have an apparently balanced chromosomal translocation in their karyotypes. Methods For mapping the broken genes as a result of chromosomal translocations, we performed whole genome DNA sequencing. Chromosomal breakpoints and large DNA copy number variations (CNV) were determined after genome alignment. Identified CNVs and single nucleotide variations (SNV) were evaluated with VCF‐BED intersect and Gemini tools, respectively. A targeted resequencing approach was performed on the JMJD1C gene in all of the ASD cohorts (220 patients). For molecular modeling, we used a homology modeling approach via the SWISS‐MODEL. Results We found that there was no contribution of the broken genes or regulator DNA sequences to ASD, whereas the SNVs on the JMJD1C, CNKSR2 and DDX11 genes were the most convincing genetic risk factors for underlying ASD phenotypes. Conclusions Genetic etiologies of ASD should be analyzed comprehensively by taking into account of the all chromosomal structural abnormalities and de novo or inherited CNV/SNVs with all possible inheritance patterns.
Propolis is one of the mixtures with the widest biological activity among natural products used in complementary medicine. HSV‐1 is a highly contagious and endemic virus. Available drugs are insufficient for recurrent HSV‐1 infections. Therefore, new approaches to treat HSV‐1 infections are still being developed. In this study, it was aimed to investigate the inhibition effect of ethanolic Anatolian propolis extracts obtained from the Eastern Black Sea Region (Pazar, Ardahan, and Uzungöl) on HSV‐1. In addition to the total phenolic (TPC) and the total flavonoid content (TFC), the phenolic profiles of the extracts were analyzed by HPLC‐UV. The antiviral activity of the extracts were tested by 3‐(4,5‐dimethylthiazol‐2‐yl)‐2,5‐diphenyltetrazolium bromide (MTT), quantitative Real Time Polymerase Chain Reaction (qRT‐PCR), and plaque reduction tests, and the results were evaluated statistically. It was determined that the total amount of phenolic substances varied between 44.12 and 166.91 mg GAE/g, and the total flavonoid content of the samples varied between 12.50 and 41.58 (mg QUE/g). It was shown that all propolis samples used in the current study were effective against HSV‐1, but the higher phenolic compounds contained in the samples showed the higher activity. The results show that ethanolic propolis extracts are promising candidates for HSV‐1 treatment.
The study aimed to develop a clinical diagnosis system to identify patients in the GD risk group and reduce unnecessary oral glucose tolerance test (OGTT) applications for pregnant women who are not in the GD risk group using deep learning algorithms. With this aim, a prospective study was designed and the data was taken from 489 patients between the years 2019 and 2021, and informed consent was obtained. The clinical decision support system for the diagnosis of GD was developed using the generated dataset with deep learning algorithms and Bayesian optimization. As a result, a novel successful decision support model was developed using RNN-LSTM with Bayesian optimization that gave 95% sensitivity and 99% specificity on the dataset for the diagnosis of patients in the GD risk group by obtaining 98% AUC (95% CI (0.95–1.00) and p < 0.001 ). Thus, with the clinical diagnosis system developed to assist physicians, it is planned to save both cost and time, and reduce possible adverse effects by preventing unnecessary OGTT for patients who are not in the GD risk group. Graphical Abstract Supplementary Information The online version contains supplementary material available at 10.1007/s11517-023-02800-7.
Gestational diabetes mellitus (GDM) is a disease characterized by carbohydrate intolerance that develops under the influence of placental hormones during pregnancy and is primarily caused by impaired insulin action and β-cell dysfunction. 1 Many studies show that GDM increases the risk of complications in offspring such as neonatal hypoglycemia or macrosomia due to hyperglycemia in pregnancy 2 and the risk of short-term adverse perinatal outcomes and long-term metabolic morbidity for women and their newborns. 3 Another importance of early diagnosis and treatment of GDM is that GDM predisposes the fetus to obesity, type 2 diabetes, and cardiovascular disease in later life through reverse intrauterine programming. [4][5][6][7][8][9] The International Association of Diabetes and Pregnancy Study Groups (IADPSG) recommended a new GDM diagnostic criterion in 2010 because of the greater risk of adverse gestational outcomes 10 : boundary blood glucose levels for fasting, 1 and 2 h after oral glucose of 5.1, 10.0, and 8.5 mmol L −1 , respectively,
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
hi@scite.ai
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.