Global, Regional, and National Cancer Incidence, Mortality, Years of Life Lost, Years Lived With Disability, and Disability-Adjusted Life-Years for 29 Cancer Groups, 1990 to 2017: A Systematic Analysis for the Global Burden of Disease Study.

Risk of gestational diabetes mellitus following assisted reproductive technology: systematic review and meta-analysis of 59 cohort studies

Abstract Objective: The use of assisted reproductive technology (ART) has been associated with an increased risk of gestational diabetes mellitus (GDM) in previous studies, but its risk has not been consistent. Therefore, we aimed to estimate the risk of GDM in women who conceived with ART via a systematic review and meta-analysis of cohort studies. Methods: ISI Web of Knowledge, Medline/PubMed, Scopus, and Embase databases were searched to identify studies that evaluated the risk of GDM through May 2017 using the relevant keywords. Two reviewers independently performed the screening, data extraction, and quality assessment. Meta-analysis was performed with a random effects model. Results: The search yielded 957 records relating to GDM and use of ART, from which 59 eligible cohorts were selected for meta-analysis (n?=?96,785). There was evidence of substantial heterogeneity among these studies (?(2)((58))?=?3072.34, p?I-2=98.1%). The pooled estimate of GDM risk using the random effects model was 9.00% (95% CI: 7.90?10.20). Visual inspection of the funnel plot indicated the presence of low publication bias, but Egger?s test did not reveal publication bias. Conclusions: The findings revealed that the risk of GDM was very high among women who conceived with ART treatment. GDM screening, management, and improved care are vital in ART pregnancy.

Could emotional eating act as a mediator between sleep quality and food intake in female students?

Immunization using male germ cells and gametes as rich sources of cancer testis antigens for inhibition of 4T1 breast tumors' growth and metastasis in BALB/c mice

Opening of first mega ICU in Markazi province Gallery

The first mega ICU of province was inaugurated in presence of Governor General and chancellor and deputies of Markazi province.

Immunization using male germ cells and gametes as rich sources of cancer testis antigens for inhibition of 4T1 breast tumors' growth and metastasis in BALB/c mice

Could emotional eating act as a mediator between sleep quality and food intake in female students?

Effect of Acceptance and Commitment Therapy on the Quality of Life in Infertile Women During Treatment: A Randomized Control Trial

A novel Fuzzy Bayesian Network approach for safety analysis of process systems; An application of HFACS and SHIPP methodology

Abstract Chemical process industries (CPI) are inherently hazardous complex systems where large inventory of extremely flammable and explosive chemicals are processed and stored in a highly congested process area. A reliable safety analysis method plays a significant role to measure risks and to develop preventive strategies in process industries. This paper proposed a novel Fuzzy Bayesian Network for dynamic safety analysis of process systems by incorporating Bayesian network (BN) with Fuzzy Best Worst Method (Fuzzy-BWM). In the proposed approach a comprehensive and in-depth analysis of human and organizational factors (HOFs) involving in the accident scenario occurrence was also provided by integrating Human Factor Analysis and Classification System (HFACS) and System Hazard Identification, Prediction and Prevention (SHIPP) methodology into the model. An ethylene storage tank was selected to verify the applicability of the proposed approach and its application potential. The study also explained a comparison between the results of the proposed Fuzzy-BWM approach with the conventional BN approach and a quantitative risk assessment (QRA) conventional technique such as bow-tie (BT). The findings revealed the capability of the proposed Fuzzy-BWM approach to provide high reliable results and to detect risks that using the BT and BN approaches were not identified. (C) 2019 Elsevier Ltd. All rights reserved.

Biodegradation of high concentrations of petroleum compounds by using indigenous bacteria isolated from petroleum hydrocarbons-rich sludge: Effective scale-up from liquid medium to composting process