Oxidative stress contributes to cobalt oxide nanoparticles-induced cytotoxicity and DNA damage in human hepatocarcinoma cells.

BackgroundCobalt oxide nanoparticles (Co(3)O(4)NPs) are increasingly recognized for their utility in biological applications, magnetic resonance imaging, and drug delivery. However, little is known about the toxicity of Co(3)O(4)NPs in human cells.MethodsWe investigated the possible mechanisms of genotoxicity induced by Co(3)O(4)NPs in human hepatocarcinoma (HepG2) cells. Cell viability, reactive oxygen species (ROS), glutathione, thiobarbituric acid reactive substance, apoptosis, and DNA damage were assessed in HepG2 cells after Co(3)O(4)NPs and Co(2+) exposure.ResultsCo(3)O(4)NPs elicited a significant (P < 0.01) reduction in glutathione with a concomitant increase in lipid hydroperoxide, ROS generation, superoxide dismutase, and catalase activity after 24- and 48-hour exposure. Co(3)O(4)NPs had a mild cytotoxic effect in HepG2 cells; however, it induced ROS and oxidative stress, leading to DNA damage, a probable mechanism of genotoxicity. The comet assay showed a statistically significant (P < 0.01) dose- and time-related increase in DNA damage for Co(3)O(4)NPs, whereas Co(2+) induced less change than Co(3)O(4)NPs but significantly more than control.ConclusionOur results demonstrated that Co(3)O(4)NPs induced cytotoxicity and genotoxicity in HepG2 cells through ROS and oxidative stress

Investigating the Influence of Job Satisfaction, Job Burnout and Job Engagement on Turnover Intention Among Private Sector Employees in Saudi Arabia

This research was conducted on private sector employees in Riyadh, the capital of Saudi Arabia. A quantitative methodology was used with a survey of 336 participants to investigate the influence of job engagement, job satisfaction and job burnout on turnover intention. The results support the research hypotheses that job satisfaction and job engagement negatively influence turnover intention, job burnout has a positive influence on turnover intention, and Job Engagement has a positive influence on job Satisfaction and job burnout. Keywords: Job Satisfaction, Job Burnout, Job Engagement, Turnover Intention. DOI: 10.7176/EJBM/13-10-13 Publication date:May 31st 202

Towards Automation and Human Assessment of Objective Skin Quantification

The goal of this study is to provide an objective criterion for computerised skin quality assessment. Humans have been impacted by a variety of face features. Utilising eye-tracking technology assists to get a better understanding of human visual behaviour, this research examined the influence of face characteristics on the quantification of skin evaluation and age estimation. The results revealed that when facial features are apparent, individuals do well in age estimation. Also, this research attempts to examine the performance and perception of machine learning algorithms for various skin attributes. Comparison of the traditional machine learning technique to deep learning approaches. Support Vector Machine (SVM) and Convolutional Neural Networks (CNNs) were used to evaluate classification algorithms, with CNNs outperforming SVM. The primary difficulty in training deep learning algorithms is the need of large-scale dataset. This thesis proposed two high-resolution face datasets to address the requirement of face images for research community to study face and skin quality. Additionally, the study of machine-generated skin patches using Generative Adversarial Networks (GANs) is conducted. Dermatologists confirmed the machine-generated images by evaluating the fake and real images. Only 38% accurately predicted the real from fake correctly. Lastly, the performance of human perception and machine algorithm is compared using the heat-map from the eye-tracking experiment and the machine learning prediction on age estimation. The finding indicates that both humans and machines predict in a similar manner

Characterization of Sunn hemp begomovirus and its geographical origin based on in silico structural and functional analysis of recombinant coat protein

Sequence alignment of the 897 bp amplicon obtained from a diseased sunn hemp (Crotalaria juncea L.) plant DNA revealed a complete 771 bp coat protein (CP) gene flanked by 3’ regions of the AV2 and AC3 genes. Southern hybridization using (α-32P) dCTP labeled (CP) gene probe of Indian tomato leaf curl virus (IToLCV) demonstrated the association of begomovirus with the leaf curl disease of sunn hemp. Phylogenetic data suggested that, the AV2, CP and AC3 genes have closest genetic relationship with begomovirus isolates from India, China and Bangladesh, respectively. In silico recombination analysis elucidated a 297 nucleotides hot spot (346 to 643 nucleotides) within AV2 overlapping region of CP gene, amenable to genetic rearrangements, with lineage from tomato leaf curl virus Bangalore (ToLCuVB) and Indian cassava mosaic virus-Ind (ICMV) as major and minor parents, respectively. Thus, it is concluded that the recombinant CP genes related to begomoviruses are evolved from the Indian isolates, causing broad host specificity and molecular diversity among the related begomoviruses across the geographical limits of Southeast Asia.Keywords: Begomovirus, sunn hemp, coat protein, recombination, phylogenetic analysis, in silico analysi

Plugging efficiency of flaky and fibrous lost circulation materials in different carrier fluid systems

Lost circulation is one of the most significant contributors to wellbore instability and causes an increase in drilling operation costs. It is also a major contributor to the nonproductive time and must be minimized for improved economic and operational performance. The objective of this research is to provide tools and information about specific loss circulation management techniques that drillers can use to minimize lost circulation. This study involves comprehensive approaches to test the plugging efficiency of three different lost circulation materials (LCMs) from two groups of materials (flaky and fibrous). It also highlights the carrier fluids (drilling fluids) and the determination of the optimum drilling fluid properties. Different fracture sizes and the effect of the various LCM are analyzed. The impact of LCM’s shape, size, and physical and chemical properties along with the fracture sizes is discussed. Examining the particle size distribution before and after mixing with the fluids shows the capability of the materials in plugging the fracture while maintaining the minimum porosity and permeability of the plug. It also helps to strengthen the fracture gradient of the formation by knowing the actual particle sizes. The primary objective of this work is to precisely study and analyze these factors on the three LCMs along with different carrier fluids to investigate their plugging efficiency and potentially resolve or minimize the severity of the lost circulation problem

Data mining of the essential causes of different types of fatal construction accidents

Accident analysis is used to discover the causes of workplace injuries and devise methods for preventing them in the future. There has been little discussion in the previous studies of the specific elements contributing to deadly construction accidents. In contrast to previous studies, this study focuses on the causes of fatal construction accidents based on management factors, unsafe site conditions, and workers' unsafe actions. The association rule mining technique identifies the hidden patterns or knowledge between the root causes of fatal construction accidents, and one hundred meaningful association rules were extracted from the two hundred and fifty-three rules generated. It was discovered that many fatal construction accidents were caused by management factors, unsafe site circumstances, and risky worker behaviors. These analyses can be used to demonstrate plausible cause-and-effect correlations, assisting in building a safer working environment in the construction sector. The study findings can be used more efficiently to design effective inspection procedures and occupational safety initiatives. Finally, the proposed method should be tested in a broader range of construction situations and scenarios to ensure that it is as accurate as possible

Shear Strength of Copper Joints Prepared by Low Temperature Sintering of Silver Nanoparticles

In this work, mechanical properties of Cu-to-Cu joint samples prepared by low temperature sintering of Ag nanoparticle paste have been investigated. The silver nanopaste was prepared by a controlled thermal decomposition of an organometallic precursor. The as-synthesized Ag particles were spherical, with an average diameter of 8.5 nm. The Cu-to-Cu joint samples were made by placing a small amount of Ag nanopaste between two polished Cu plates and sintering at 150C, 200C, 220C and 350C in air. A normal load was applied to aid sintering. Mechanical properties were measured by imposing a uniform stress across the sample bond area and measuring the corresponding strain. The application of external load was found to have a positive effect on the material’s mechanical properties. Furthermore, interestingly high values of shear strength were observed.Byly zkoumány mechanické vlastnosti Cu-to-Cu spojů připravených nízkoteplotní sintrací pasty Ag nanočástic. Ag nanopasta byla připravena řízeným tepelným rozkladem organokovových prekurzorů. Syntetizované Ag NPs byly kulovité, o středním průměru 8,5 nm. Cu-to-Cu spoje byly vyrobeny umístěním malého množství Ag nanopasty mezi dvě leštěné Cu desky a sintrováním při 150C, 200C, 220C and 350C na vzduchu. Zatížení bylo použito na k podpoře sintrace. Mechanické vlastnosti byly měřeny stanovením napětí lomu a deformace. Bylo zjištěno, že aplikace vnějšího zatížení má pozitivní vliv na mechanické vlastnosti spoje