Discrete Element Method Modeling for the Failure Analysis of Dry Mono-Size Coke Aggregates

An in-depth study of the failure of granular materials, which is known as a mechanism to generate defects, can reveal the facts regarding the origin of the imperfections, such as cracks in the carbon anodes. The initiation and propagation of the cracks in the carbon anode, especially the horizontal cracks below the stub-holes, reduce the anode efficiency during the electrolysis process. The failure analysis of coke aggregates can be employed to determine the appropriate recipe and operating conditions in order to avoid the formation of cracks in the carbon anodes. In this paper, it will be shown that a particular failure mode can be responsible for the crack generation in the carbon anodes. The second-order work criterion is employed to analyze the failure of the coke aggregate specimens and the relationships between the second-order work, the kinetic energy, and the instability of the granular material are investigated. In addition, the coke aggregates are modeled by exploiting the discrete element method (DEM) to reveal the micro-mechanical behavior of the dry coke aggregates during the compaction process. The optimal number of particles required for the failure analysis in the DEM simulations is determined. The effects of the confining pressure and strain rate as two important compaction process parameters on the failure are studied. The results reveal that increasing the confining pressure enhances the probability of the diffusing mode of the failure in the specimen. On the other hand, the increase of strain rate augments the chance of the strain localization mode of the failure in the specimen.     

Strong association of common variants in the miRNA-binding site of NOD2 gene with clinicopathological characteristics and disease activity of systemic lupus erythematosus

Clinical Rheumatology - Systemic lupus erythematosus (SLE) is a multifactorial systemic autoimmune disease, in which genetic susceptibility plays a pivotal role. The nucleotide oligomerization...     

A Comparison of Three Different Deep Learning-Based Models to Predict the MGMT Promoter Methylation Status in Glioblastoma Using Brain MRI

Journal of Digital Imaging - Glioblastoma (GBM) is the most common primary malignant brain tumor in adults. The standard treatment for GBM consists of surgical resection followed by concurrent...     

Ovarian thecoma presenting with acute ovarian torsion in pregnancy; report of a rare case

Thecoma is a commonly benign ovarian tumor of the group “Sex cord‐stromal neoplasms.” This group represents <5 percent of ovarian tumors. Thecoma is extremely rare in pregnancy. Here, we describe a 17‐week pregnant woman presenting with acute ovarian pedicle torsion as a result of an ovarian thecoma.     

Impact of umbelliprenin-containing niosome nanoparticles on VEGF-A and CTGF genes expression in retinal pigment epithelium cells

AIM: To investigate the impact of niosome nanoparticles carrying umbelliprenin (UMB), an anti-angiogenic and anti-inflammatory plant compound, on the expression of vascular endothelial growth factor (VEGF-A) and connective tissue growth factor (CTGF) genes in a human retinal pigment epithelium (RPE)-like retina-derived cell line. METHODS: UMB-containing niosomes were created, optimized, and characterized. RPE-like cells were treated with free UMB and UMB-containing niosomes. The IC50 values of the treatments were determined using an MTT assay. Gene expression of VEGF-A and CTGF was evaluated using real-time polymerase chain reaction after RNA extraction and cDNA synthesis. Niosomes’ characteristics, including drug entrapment efficiency, size, dispersion index, and zeta potential were assessed. Free UMB had an IC50 of 96.2 μg/mL, while UMB-containing niosomes had an IC50 of 25 μg/mL. RESULTS: Treatment with UMB-containing niosomes and free UMB resulted in a significant reduction in VEGF-A expression compared to control cells (P=0.001). Additionally, UMB-containing niosomes demonstrated a significant reduction in CTGF expression compared to control cells (P=0.05). However, there was no significant reduction in the expression of both genes in cells treated with free UMB. CONCLUSION: Both free UMB and niosome-encapsulated UMB inhibits VEGF-A and CTGF genes expression. However, the latter demonstrates significantly greater efficacy, potentially due to the lower UMB dosage and gradual delivery. These findings have implications for anti-angiogenesis therapeutic approaches targeting age-related macular degeneration.     

A review of neuroradiological abnormalities in patients with coronavirus disease 2019 (COVID-19)

BackgroundSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has led to various neurological manifestations. There is an urgent need for a summary of neuroimaging findings to accelerate diagnosis and treatment plans. We reviewed prospective and retrospective studies to classify neurological abnormalities observed in patients with the SARS-CoV-2 infection.MethodsThe relevant studies published in Scopus, PubMed and Clarivate Analytics databases were analysed. The search was performed for full-text articles published from 23 January 2020 to 23 February 2021.ResultsIn 23 studies the number of patients with SARS-CoV-2 infection was 20,850 and the number of patients with neurological manifestations was 1996 (9.5%). The total number of patients with neuroradiological abnormalities was 602 (2.8%). SARS-CoV-2 has led to various neuroimaging abnormalities which can be categorised by neuroanatomical localisation of lesions and their main probable underlying pathogenesis. Cranial nerve and spinal root abnormalities were cranial neuritis and polyradiculitis. Parenchymal abnormalities fell into four groups of: (a) thrombosis disorders, namely ischaemic stroke and sinus venous thrombosis; (b) endothelial dysfunction and damage disorders manifested as various types of intracranial haemorrhage and posterior reversible encephalopathy syndrome; (c) hypoxia/hypoperfusion disorders of leukoencephalopathy and watershed infarction; and (d) inflammatory disorders encompassing demyelinating disorders, encephalitis, vasculitis-like disorders, vasculopathy and cytotoxic lesions of the corpus callosum. Leptomeninges disorders included meningitis. Ischaemic stroke was the most frequent abnormality in these studies.ConclusionThe review study suggests that an anatomical approach to the classification of heterogeneous neuroimaging findings in patients with SARS-CoV-2 and neurological manifestations would lend itself well for use by practitioners in diagnosis and treatment planning.     

Predicting diabetic foot ulceration using routinely collected data in a foot clinic. What level of prognostic accuracy can be achieved?

This study aimed to investigate the efficacy of using routinely collected clinical data in predicting the risk of diabetic foot ulcer (DFU). The first objective was to develop a prognostic model based on the most important risk factors objectively selected from a set of 39 clinical measures. The second objective was to compare the prediction accuracy of the developed model against that of a model based on only the 3 risk factors that were suggested in the systematic review and meta-analyses study (PODUS). In a cohort study, a set of 12 continuous and 27 categorical data from patients (n = 203 M/F:99/104) who attended a specialised diabetic foot clinic were collected at baseline. These patients were then followed-up for 24 months during which 24 (M/F:17/7) patients had DFU. Multivariate logistic regression was used to develop a prognostic model using the identified risk factors that achieved p < 0.2 based on univariate logistic regression. The final prognostic model included 4 risk factors (Adjusted-OR [95% CI]; p) in total. Impaired sensation (116.082 [12.06–1117.287]; p = 0.000) and presence of callus (6.257 [1.312–29.836]; p = 0.021) were significant (p < 0.05), while having dry skin (5.497 [0.866–34.89]; p = 0.071) and Onychomycosis (6.386 [0.856–47.670]; p = 0.071) that stayed in the model were not significant. The accuracy of the model with these 4 risk factors was 92.3%, where sensitivity and specificity were 78.9%, and 94.0% respectively. The 78.9% sensitivity of our prognostic 4-risk factor model was superior to the 50% sensitivity that was achieved when the three risk factors proposed by PODUS were used. Also our proposed model based on the above 4 risk factors showed to predict the DFU with higher overall prognostic accuracy. These findings have implications for developing prognostic models and clinical prediction rules in specific patient populations to more accurately predict DFU.