Sharif Digital Repository

Background: Gestational Diabetes Mellitus (GDM) is a health problem that is increasing around the world. Introduction: Prevention of GDM, rather than treatment, could have several benefits in terms of both health and economic cost. Even a slight reduction in maternal glucose in non-diabetic women, particularly in women at high risk for GDM, may have significant benefits for pregnancy results and the future health of off-springs. Probiotics are a relatively new intervention, which are assessed by mothers’ metabolism, and can reduce blood sugar levels, prevent gestational diabetes and reduce the maternal and fetal complications resulting from it. The aim of this study was to review the studies... 

Objectives: Detecting caries lesions is challenging for dentists, and deep learning models may help practitioners to increase accuracy and reliability. We aimed to systematically review deep learning studies on caries detection. Data: We selected diagnostic accuracy studies that used deep learning models on dental imagery (including radiographs, photographs, optical coherence tomography images, near-infrared light transillumination images). The latest version of the quality assessment tool for diagnostic accuracy studies (QUADAS-2) tool was used for risk of bias assessment. Meta-analysis was not performed due to heterogeneity in the studies methods and their performance measurements.... 

Objective: This study aimed to present and evaluate a new deep learning model for determining cervical vertebral maturation (CVM) degree and growth spurts by analyzing lateral cephalometric radiographs. Methods: The study sample included 890 cephalograms. The images were classified into six cervical stages independently by two orthodontists. The images were also categorized into three degrees on the basis of the growth spurt: pre-pubertal, growth spurt, and post-pubertal. Subsequently, the samples were fed to a transfer learning model implemented using the Python programming language and PyTorch library. In the last step, the test set of cephalograms was randomly coded and provided to two... 

Tabriz city in NW Iran is a seismic-prone province with recurring devastating earthquakes that have resulted in heavy casualties and damages. This research developed a new computational framework to investigate four main dimensions of vulnerability (environmental, social, economic and physical). An Artificial Neural Network (ANN) Model and a SWOT-Quantitative Strategic Planning Matrix (QSPM) were applied. Firstly, a literature review was performed to explore indicators with significant impact on aforementioned dimensions of vulnerability to earthquakes. Next, the twenty identified indicators were analyzed in ArcGIS, a geographic information system (GIS) software, to map earthquake... 

Deep learning (DL) has been employed for a wide range of tasks in dentistry. We aimed to systematically review studies employing DL for periodontal and implantological purposes. A systematic electronic search was conducted on four databases (Medline via PubMed, Google Scholar, Scopus, and Embase) and a repository (ArXiv) for publications after 2010, without any limitation on language. In the present review, we included studies that reported deep learning models' performance on periodontal or oral implantological tasks. Given the heterogeneities in the included studies, no meta-analysis was performed. The risk of bias was assessed using the QUADAS-2 tool. We included 47 studies: focusing on... 

Cationic polymers such as poly-L-lysine (PLL) are able to interact electrostatically with DNA to produce polymeric systems with nanometric diameters due to the neutralization and accumulation of DNA. This study integrates the outstanding properties of carbon quantum dots (CQDs) with PLL to develop a novel gene delivery vehicle with a core-shell hybrid nanostructure. The CQD/PLL core-shell nanoparticles (NPs) were, therefore, synthesized in such a way that they had narrow size distribution and an average diameter under 10 nm, both of which were confirmed by dynamic light scattering (DLS) and transmission electron microscopy (TEM). Fourier transform infrared (FTIR) spectroscopy exhibited that... 

Cationic polymers such as poly-L-lysine (PLL) are able to interact electrostatically with DNA to produce polymeric systems with nanometric diameters due to the neutralization and accumulation of DNA. This study integrates the outstanding properties of carbon quantum dots (CQDs) with PLL to develop a novel gene delivery vehicle with a core-shell hybrid nanostructure. The CQD/PLL core-shell nanoparticles (NPs) were, therefore, synthesized in such a way that they had narrow size distribution and an average diameter under 10 nm, both of which were confirmed by dynamic light scattering (DLS) and transmission electron microscopy (TEM). Fourier transform infrared (FTIR) spectroscopy exhibited that... 

Aggregation of the natively unfolded protein α-synuclein (α-syn) is key to the development of Parkinson's disease (PD). Some nanoparticles (NPs) can inhibit this process and in turn be used for treatment of PD. Using simulation strategies, we show here that α-syn self-assembly is electrostatically driven. Dimerization by head-to-head monomer contact is triggered by dipole-dipole interactions and subsequently stabilized by van der Waals interactions and hydrogen bonds. Therefore, we hypothesized that charged nano-objects could interfere with this process and thus prevent α-syn fibrillation. In our simulations, positively and negatively charged graphene sheets or superparamagnetic iron oxide... 

The present research comes up with a novel DNA-loaded poly-L-lysine (PLL)/hyaluronan (HA) nanocarrier (DNA-loaded PLL/HA NCs) for gene delivery applications, as a promising candidate for gene delivery into diverse cells. A straightforward approach was employed to prepare such a nanosystem through masking DNA-loaded PLL molecules by HA. Fourier-transform infrared (FTIR) spectroscopy, dynamic light scattering (DLS), field emission-scanning electron microscopy (FE-SEM) and transmission electron microscopy (TEM) were used to analyse the interaction of the molecules as well as the physicochemical properties of the NCs. The NCs showed a negative charge of –24 ± 3 mV, with an average size of 138 ±... 

Background Across low-income and middle-income countries (LMICs), one in ten deaths in children younger than 5 years is attributable to diarrhoea. The substantial between-country variation in both diarrhoea incidence and mortality is attributable to interventions that protect children, prevent infection, and treat disease. Identifying subnational regions with the highest burden and mapping associated risk factors can aid in reducing preventable childhood diarrhoea. Methods We used Bayesian model-based geostatistics and a geolocated dataset comprising 15 072 746 children younger than 5 years from 466 surveys in 94 LMICs, in combination with findings of the Global Burden of Diseases, Injuries,... 

Reiner RC Jr, Hay SI. Mapping geographical inequalities in childhood diarrhoeal morbidity and mortality in low-income and middle-income countries, 2000–17: analysis for the Global Burden of Disease Study 2017. Lancet 2020; 395: 1779–801—In this Article, the author byline has been amended to Local Burden of Disease Diarrhoea Collaborators. This correction has been made to the online version as of June 4, 2020, and the printed version is correct. © 2020 Elsevier Ltd  

Background: The burden of inflammatory bowel disease (IBD) is rising globally, with substantial variation in levels and trends of disease in different countries and regions. Understanding these geographical differences is crucial for formulating effective strategies for preventing and treating IBD. We report the prevalence, mortality, and overall burden of IBD in 195 countries and territories between 1990 and 2017, based on data from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2017. Methods: We modelled mortality due to IBD using a standard Cause of Death Ensemble model including data mainly from vital registrations. To estimate the non-fatal burden, we used data...