Studying the Effect of Adding Titanium Dioxide (TiO2) Nanoparticles on the Compressive Strength of Chemical and Heat-activated Acrylic Denture Base Resins

Problem: The commonly used acrylic resins for fabricating denture base suffer from poor mechanical properties. Aim: This study aimed to assess the effect of incorporating Titanium Dioxide (TiO2) nanoparticles (NPs) as a reinforcement agent on the compressive strength of acrylic denture base materials. Materials and methods: Thirty-two cylindrical specimens (22 mm in height and 12 mm in diameter) were prepared from PMMA resins with and without TiO2 NPs. They were allocated into two main groups according to the materials used such as cold cure and heat cure denture base resins and then subdivided into two subgroups each containing eight specimens: control (without nanoparticles) and experimental (with 2 wt.% TiO2 NPs). TiO2 NPs were synthesized via a chemical processing route and particle morphology and size distribution were assessed using SEM and AFM while XRD technique was employed to determine the crystalline structure of the NPs. Compression test was performed on the specimens using a universal Instron testing machine to compare the compressive strength. Results: Size of crystalline TiO2 NPs varied between 40-80 nm. The mean compressive strength for the cold cure acrylic resin (control group) and its nanocomposite (experimental group) were found as 15.37 MPa and 17.42 MPa while for the heat cure acrylic resin and its nanocomposite were 23.04 MPa and 24.30 MPa. A statistically significant difference was recorded in the compressive strength between the cold cure acrylic resin and its nanocomposite. However, the difference was non-significant in the case of heat cure acrylic resin. Conclusion: The compressive strength of both cold cure and heat cure acrylic resins increased after incorporation TiO2 NPs

Mapping gene associations in human mitochondria using clinical disease phenotypes

Nuclear genes encode most mitochondrial proteins, and their mutations cause diverse and debilitating clinical disorders. To date, 1,200 of these mitochondrial genes have been recorded, while no standardized catalog exists of the associated clinical phenotypes. Such a catalog would be useful to develop methods to analyze human phenotypic data, to determine genotype-phenotype relations among many genes and diseases, and to support the clinical diagnosis of mitochondrial disorders. Here we establish a clinical phenotype catalog of 174 mitochondrial disease genes and study associations of diseases and genes. Phenotypic features such as clinical signs and symptoms were manually annotated from full-text medical articles and classified based on the hierarchical MeSH ontology. This classification of phenotypic features of each gene allowed for the comparison of diseases between different genes. In turn, we were then able to measure the phenotypic associations of disease genes for which we calculated a quantitative value that is based on their shared phenotypic features. The results showed that genes sharing more similar phenotypes have a stronger tendency for functional interactions, proving the usefulness of phenotype similarity values in disease gene network analysis. We then constructed a functional network of mitochondrial genes and discovered a higher connectivity for non-disease than for disease genes, and a tendency of disease genes to interact with each other. Utilizing these differences, we propose 168 candidate genes that resemble the characteristic interaction patterns of mitochondrial disease genes. Through their network associations, the candidates are further prioritized for the study of specific disorders such as optic neuropathies and Parkinson disease. Most mitochondrial disease phenotypes involve several clinical categories including neurologic, metabolic, and gastrointestinal disorders, which might indicate the effects of gene defects within the mitochondrial system. The accompanying knowledgebase (http://www.mitophenome.org/) supports the study of clinical diseases and associated genes

Altered Negative Unconscious Processing in Major Depressive Disorder: An Exploratory Neuropsychological Study

Major depressive disorder (MDD) has been characterized by abnormalities in emotional processing. However, what remains unclear is whether MDD also shows deficits in the unconscious processing of either positive or negative emotions. We conducted a psychological study in healthy and MDD subjects to investigate unconscious emotion processing and its valence-specific alterations in MDD patients.We combined a well established paradigm for unconscious visual processing, the continuous flash suppression, with positive and negative emotional valences to detect the attentional preference evoked by the invisible emotional facial expressions.Healthy subjects showed an attentional bias for negative emotions in the unconscious condition while this valence bias remained absent in MDD patients. In contrast, this attentional bias diminished in the conscious condition for both healthy subjects and MDD.Our findings demonstrate for the first time valence-specific deficits specifically in the unconscious processing of emotions in MDD; this may have major implications for subsequent neurobiological investigations as well as for clinical diagnosis and therapy

Prospective mental imagery as its link with anxiety and depression in prisoners

Mental imagery is known to play a key role in the development and maintenance of depression and anxiety. Prisoners commonly experience psychological distress, but interventions to address this are currently lacking. We aimed to examine the link between prospective mental imagery and anxiety and depression among prisoners. One hundred twenty-three male prisoners from a Category C prison in southwest England participated in the study. They completed the Centre for Epidemiologic Studies Depression Scale (CES-D) and the General Anxiety Disorder Scale (GAD-7) to measure whether they experience depression and/or anxiety symptoms. Furthermore, they completed additional questionnaires to evaluate their prospective mental imagery. Results showed that 67.5% of prisoners presented with more depression symptoms and 27.7% with more anxiety symptoms. Supporting earlier findings, our data revealed that some dimensions of prospective mental imagery were significantly related with increased anxiety and depression symptoms in prisoners. Namely, intrusive negative personally relevant imagery was a positive predictor and likelihood of positive events a negative predictor of both anxiety and depression symptoms. The perceived likelihood of negative events was a positive predictor of depression. Intrusive verbal thought was a positive predictor of anxiety. The obtained results suggest the need to develop interventions not only targeting the reduction of prospective negative imagery but also the enhancement of positive mental imagery

A simulation study on the effects of neuronal ensemble properties on decoding algorithms for intracortical brain-machine interfaces

Background: Intracortical brain-machine interfaces (BMIs) harness movement information by sensing neuronal activities using chronic microelectrode implants to restore lost functions to patients with paralysis. However, neuronal signals often vary over time, even within a day, forcing one to rebuild a BMI every time they operate it. The term "rebuild" means overall procedures for operating a BMI, such as decoder selection, decoder training, and decoder testing. It gives rise to a practical issue of what decoder should be built for a given neuronal ensemble. This study aims to address it by exploring how decoders' performance varies with the neuronal properties. To extensively explore a range of neuronal properties, we conduct a simulation study. Methods: Focusing on movement direction, we examine several basic neuronal properties, including the signal-to-noise ratio of neurons, the proportion of well-tuned neurons, the uniformity of their preferred directions (PDs), and the non-stationarity of PDs. We investigate the performance of three popular BMI decoders: Kalman filter, optimal linear estimator, and population vector algorithm. Results: Our simulation results showed that decoding performance of all the decoders was affected more by the proportion of well-tuned neurons that their uniformity. Conclusions: Our study suggests a simulated scenario of how to choose a decoder for intracortical BMIs in various neuronal conditions

Integrating water exclusion theory into βcontacts to predict binding free energy changes and binding hot spots

10.1186/1471-2105-15-57BMC Bioinformatics151-BBMI

Relative contribution of various chronic diseases and multi-morbidity to potential disability among Dutch elderly

BACKGROUND: The amount of time spent living with disease greatly influences elderly people’s wellbeing, disability and healthcare costs, but differs by disease, age and sex. METHODS: We assessed how various single and combined diseases differentially affect life years spent living with disease in Dutch elderly men and women (65+) over their remaining life course. Multistate life table calculations were applied to age and sex-specific disease prevalence, incidence and death rates for the Netherlands in 2007. We distinguished congestive heart failure, coronary heart disease (CHD), breast and prostate cancer, colon cancer, lung cancer, diabetes, COPD, stroke, dementia and osteoarthritis. RESULTS: Across ages 65, 70, 75, 80 and 85, CHD caused the most time spent living with disease for Dutch men (from 7.6 years at age 65 to 3.7 years at age 85) and osteoarthritis for Dutch women (from 11.7 years at age 65 to 4. 8 years at age 85). Of the various co-occurrences of disease, the combination of diabetes and osteoarthritis led to the most time spent living with disease, for both men (from 11.2 years at age 65 to 4.9 -years at age 85) and women (from 14.2 years at age 65 to 6.0 years at age 85). CONCLUSIONS: Specific single and multi-morbid diseases affect men and women differently at different phases in the life course in terms of the time spent living with disease, and consequently, their potential disability. Timely sex and age-specific interventions targeting prevention of the single and combined diseases identified could reduce healthcare costs and increase wellbeing in elderly people