Outcome of Implant Diameter and Length on the Distribution of Stress with Immediate Loaded Implants: A 3D Finite Element Analysis.

Objectives: To assess the outcome of implant diameter and length on THE distribution of stress using a three-dimensional (3D) finite elements (FE) analysis, with immediate loading implants. Materials and Methods: This study made use of a 3D FE model of an implant encased in a chunk of bone. The LEADER/ITALIA-Fix type implant was created specifically for immediate loading. To create a solid model of the implant and bone and to carry out the FE analysis, the ANSYS V.12 programme was used. Results: The findings indicated that the neck of dental implants is the area of highest stress for all implant diameters and lengths, with an increase in implant length from 10 mm to 12 mm resulting in a slight raise in stress at the interface of implant-bone, and an increase in diameter from 3.75 mm to 4.25 mm having no appreciable impact on the value of stresses around dental implants. Conclusion: It was concluded that an increase in length has a negative effect on stress, while a diameter increase has no discernible impact on stress values.

Evaluation of the Characteristics of Nano Hybrid Composite Resin Modified with Graphene after Thermomechanical Loading Cycle.

To evaluate the characteristics of a thermomechanically loaded composite resin enhanced with graphene nanoparticles. A total of 60 specimens were manufactured with Test group TG1 (20), TG2 (20), and control group CG (20). All samples were subjected to surface roughness using a three-dimensional (3D) Optical profilometer and flexural strength. All specimens were subjected to thermomechanical cyclic loading. Microhardness measurement was performed with a microhardness tester. The average microhardness and flexural strength were higher in test groups TG1 and TG2 and lowest in control group CG. There was an improvement in surface roughness, flexural strength, and microhardness in the test group after the addition of graphene nanoparticles compared to the control group. Conclusion: The addition of graphene nanoparticles to composite resin significantly improved flexural strength and microhardness. The physical and chemical properties of the composite showed marked improvement.

Multiplex heteroatoms doped carbon nano dots with enhanced catalytic reduction of ionic dyes and QR code security label for anti-spurious applications.

Herein, a simple hydrothermal approach was used to make multiplex heteroatoms doped carbon dots from Tinospora cordifolia miers plant extract. Their ability to the catalytic activity of dyes and anti-spurious applications was evaluated. The formation of NBCNDs and source of (T. cordifolia miers) study the optical properties, and functional groups are investigated using UV-Visible spectroscopy and FT-IR techniques. The synthesized NBCNDs structure and elemental compositions were examined via HR-TEM, XRD, and XPS, respectively. According to the HRTEM images, the average particle size of the NBCNDs was around 4.3± 1 nm, with d-spacing of 0.19 nm. The obtained NBCNDs were exposed under 395 nm UV light to emit bluish-green tuneable fluorescence with QY (quantum yield) of 23.7%. The prepared NBCNDs as a potential catalyst for the AYR and CV dye reduction process using freshly prepared NaBH4, with determined rate constant values at 0.1220 and 0.1521 min-1, respectively. Lastly, we constructed a quick response (QR) code security label for anti-spurious applications using stencil techniques. The "confidential info" was encrypted using a QR code digital system, and the decryption was read using a smartphone under 365 nm light irradiation.

An integrated multi-objective whale optimized support vector machine and local texture feature model for severity prediction in subjects with cardiovascular disorder.

PURPOSE: The left ventricle (LV) myocardium undergoes deterioration with the reduction in ejection fraction (EF). The analysis of its texture pattern plays a major role in diagnosis of heart muscle disease severity. Hence, a classification framework with co-occurrence of local ternary pattern feature (COALTP) and whale optimization algorithm has been attempted to improve the prediction accuracy of disease severity level. METHODS: This analysis is carried out on 600 slices of 76 participants from Kaggle challenge that include subjects with normal and reduced EF. The myocardium of LV is segmented using optimized edge-based local Gaussian distribution energy (LGE)-based level set, and end-diastolic and end-systolic volumes were calculated. COALTP is extracted for two distance levels (d = 1 and 2). The t-test has been performed between the features of individual binary classes. The features are ranked using feature ranking methods. The experiments have been performed to analyze the performance of various percentages of features in each combination of bin for fivefold cross-validation. An integrated whale optimized feature selection and multi-classification framework is developed to classify the normal and pathological subjects using CMR images, and DeLong test has been performed to compare the ROCs. RESULTS: The optimized edge embedded to level set has produced better segmented myocardium that correlates with R = 0.98 with gold standard volume. The t-test shows that texture features extracted from severe subjects with distance level "1" are more statistically significant with a p value (< 0.00004) compared to other pathologies. This approach has produced an overall multi-class accuracy of 75% [confidence interval (CI) 63.74-84.23%] and effective subclass specificity of 70% (CI 55.90-81.22%). CONCLUSION: The obtained results show that the multi-objective whale optimized multi-class support vector machine framework can effectively discriminate the healthy and patients with reduced ejection fraction and potentially support the treatment process.

Visible-Light Driven Photocatalytic Degradation of Eosin Yellow (EY) Dye Based on NiO-WO3 Nanoparticles.

Herein, we report a simple synthesis, characterization and photocatalytic degradation application of composite NiO-WO3 nanoparticles. The nanoparticles were synthesized by facile low-temperature method and characterized by several techniques such as X-ray diffraction (XRD), scanning electron microscopy (SEM), transmission electron microscopy (TEM) and UV-Vis diffuse reflectance spectra (DRS). The synthesized NiO-WO3 nanoparticles were used as efficient photocatalyst for the photocatalytic degradation of Eosin yellow (EY) dye. Interestingly, the synthesized photocatalytic exhibited a significant visible-light driven photocatalytic degradation of Eosin yellow (EY) dye. Under optimized conditions (pH = 5, catalyst dosage = 3 µM and initial dye concentration= 1.0 g/L), the obtained photo degradation of EY dye was above 95% in 180 min under visible light irradiation. Remarkably, reusability of the prepared photocatalyst was also observed and the photo-degradation reactions follow the pseudo-first-order model.

Sunlight-Driven Photocatalytic Degradation of Methyl Orange Based on Bismuth Ferrite (BiFeO3) Heterostructures Composed of Interconnected Nanosheets.

Herein, we report the facile microwave-assisted synthesis, characterization and photocatalytic degradation applications of Bismuth ferrite heterostructures composed of interconnected nanosheets (BHNs). The synthesized materials were subjected to several analytical studies such as scanning electron microscopy (SEM), transmission electron microscopy (TEM), X-ray diffraction (XRD), energy dispersive spectroscopy (EDS), Fourier transform infrared (FTIR) spectroscopy and UV-visible spectroscopy in order to examine the morphological, structural, optical and photo catalytic properties. The structural and morphological characterizations confirmed the rhombohedral perovskite crystal structure and the formation of heterostructures composed of interconnected nanosheets for the synthesized material. The compositional characterization revealed that the synthesized material is bismuth ferrite with high purity. The BHNs were further used as efficient photocatalyst for the photocatalytic degradation of highly hazardous pollutant methyl orange under sunlight irradiation. The sunlight driven photocatalytic experiments revealed ~86% photodegradation of methyl orange dye in 150 min. The presented work revealed that the synthesized BHNs are excellent material for the photocatalytic degradation of various organic contaminants and hazardous pollutants.

Deep CNN with LM learning based myocardial ischemia detection in cardiac magnetic resonance images.

Cardiovascular disease (CVD) is a chronic dysfunction caused by deterioration in cardiac physiology. It results in about 31% of mortality worldwide. Among CVDs, myocardial ischemia (MI) leads to restriction in blood supply to heart tissues. There is a need to develop an effective computer aided detection (CAD) system to reduce the fatality. In this work, an attempt is made to perform mass screening of myocardial ischemic subjects and left ventricle (LV) volume estimation from cardiac magnetic resonance (CMR) images using deep convolutional neural network (CNN) with Levenberg-Marquardt (LM) learning. LV volume measurement is an important predictor of myocardial ischemia. The CMR samples used in this analysis are obtained from Medical Image Computing and Computer Assisted Intervention (MICCAI) 2009 database. The results of the proposed model are compared with deep CNN based on gradient descent (GD) learning algorithm. The results show that deep CNN architecture with LM learning classifies ischemic subjects with high accuracy (86.39%) and sensitivity (90%). The LM learning based method gives an AUC of 0.93. The estimated LV volumes obtained from the trained network gives high correlation with the ground truth. Thus the results support that proposed framework of deep CNN architecture with LM learning can be used as an effective CAD system for diagnosis of cardiovascular disorders.

Study of Tissue Variation and Analysis of MR Brain Images using Optimized Multilevel Threshold and Deep CNN Features in Neurodegenerative Disorders.

Dementia is a degenerative irreversible disorder that globally causes a high socio-economic burden. The pathology progression of mild cognitive impairment (MCI) and Alzheimer diseases (AD) are correlated with each other. There is a need to examine the pathology variation to discriminate the disorder to provide appropriate treatment strategies. This study investigates about the brain tissue variations to identify the subtle change in progression. The considered normal, MCI and AD magnetic resonance (MR) images are obtained from Alzheimer's disease Neuroimaging Initiative (ADNI). In this work, multilevel Tsallis based grey wolf optimization (GWO) is used to segment the brain tissues. Then the feature is extracted from segmented white matter (WM), grey matter (GM) and cerebro spinal fluid (CSF) using convolution neural network (CNN). The obtained deep features are given to principal component analysis (PCA) to obtain a prominent feature set for normal, MCI and AD. Further the tissue variation of optimized deep features is analyzed using support vector machine (SVM). The results shows that Tsallis based GWO perform reliable tissue segmentation for normal, MCI and AD. The deep features are able to observe discrimination than the fully considered feature set. Finally, the classifier result shows distinct tissue variation among normal, MCI and AD subjects. Further the prominent features give a classification accuracy of 77%, 80.22% and 78.7% for WM, GM and CSF respectively. This concludes that GM variation is a close biological substrate of dementia progressive condition than the effects of time or aging. Thus, the proposed framework can be used as an effective system for diagnosis of progression in neurodegenerative disorders.

Biological treatment for psoriasis and the risk of herpes zoster: results from the Psoriasis Longitudinal Assessment and Registry (PSOLAR).

Purpose: To describe the risk of herpes zoster (HZ) in patients with psoriasis and its relation to non-biologic systemic therapies or biologic treatment. Materials and methods: Psoriasis Longitudinal Assessment and Registry (PSOLAR) is an international, prospective, registry that follows adult patients with psoriasis eligible to receive non-biologic systemic therapies or biologic therapies. Mutually exclusive therapy cohorts were defined. HZ incident rates were calculated for each therapy cohort and rates between cohorts were compared using hazard ratios (HR) adjusted for potential confounders, in new users and prevalent-exposure patients. Results: A total of 55 HZ events were identified in 10,469 patients in PSOLAR. The adjusted hazard ratio in the overall study population (new user and prevalent-exposed patients) was 2.22 (95% CI: 0.82-5.97; p = .116) for tumor necrosis factor-α (TNF) inhibitors, 2.73 (0.98-7.58; p = .054) for ustekinumab, and 1.04 (0.20-5.41; p = .966) for methotrexate versus reference (combined phototherapy, systemic steroids, topical therapy, and immunomodulators other than methotrexate). Conclusions: Exposure to ustekinumab, TNF-α inhibitors, and methotrexate was not associated with a statistically significant increased risk of HZ. However, HRs were elevated for ustekinumab and TNF-α inhibitors; a larger number of HZ events would be needed to assess the presence or absence of risk.

Antibacterial macro molecules from marine organisms.

Marine ecosystem comprises of microorganisms, plants, invertebrates and vertebrates which were rich source of diverse antimicrobial products, which were structurally unique belonging to a known class of macromolecules like peptides, terpenes, alkaloids and proteins, etc. Natural macromolecules from marine ecological niches are a promising source of antibacterial agents against several drug resistant strains of pathogenic microorganisms; whereas rest of the metabolites were derived from marine flora and fauna while some arise from microbes associated with living organisms. >30,000 natural macromolecules have been identified and reported from marine organisms, however only few macromolecules are being explored and validated. The discovery of marine antibacterial macromolecules plays a significant part in the field of drug discovery and biomedical research. Despite the fact that literatures were documented on the antifungal, antiviral, antimalarial and anticancer properties, this review exclusively highlights the different antibacterial natural macromolecules from marine sources like bacteria, fungi, sponge, algae, bryozoans, tunicates, corals, cnidarians, arthropods and echinoderm along with their mode of action.

A Report of Adult Human Adenovirus Infections in a Tertiary Hospital.

We describe a review of human adenovirus (HAdV) infections occurring among adults in a tertiary hospital in Singapore from February to May 2013. A similar increase in cases was observed among children and military personnel during the same time period. The majority of isolates were identified as HAdV-7, likely an emerging pathogen in Asia.

Thermodynamic analysis of in situ gasification-chemical looping combustion (iG-CLC) of Indian coal.

Chemical looping combustion (CLC) is an inherent CO2 capture technology. It is gaining much interest in recent years mainly because of its potential in addressing climate change problems associated with CO2 emissions from power plants. A typical chemical looping combustion unit consists of two reactors-fuel reactor, where oxidation of fuel occurs with the help of oxygen available in the form of metal oxides and, air reactor, where the reduced metal oxides are regenerated by the inflow of air. These oxides are then sent back to the fuel reactor and the cycle continues. The product gas from the fuel reactor contains a concentrated stream of CO2 which can be readily stored in various forms or used for any other applications. This unique feature of inherent CO2 capture makes the technology more promising to combat the global climate changes. Various types of CLC units have been discussed in literature depending on the type of fuel burnt. For solid fuel combustion three main varieties of CLC units exist namely: syngas CLC, in situ gasification-CLC (iG-CLC) and chemical looping with oxygen uncoupling (CLOU). In this paper, theoretical studies on the iG-CLC unit burning Indian coal are presented. Gibbs free energy minimization technique is employed to determine the composition of flue gas and oxygen carrier of an iG-CLC unit using Fe2O3, CuO, and mixed carrier-Fe2O3 and CuO as oxygen carriers. The effect of temperature, suitability of oxygen carriers, and oxygen carrier circulation rate on the performance of a CLC unit for Indian coal are studied and presented. These results are analyzed in order to foresee the operating conditions at which economic and smooth operation of the unit is expected.

Subcortical Region Segmentation using Fuzzy Based Augmented Lagrangian Multiphase Level Sets Method in Autistic MR Brain Images.

In this work, the subcortical regions of control and autistic MR brain are segmented from the skull stripped images using Fuzzy C-Means (FCM) based Augmented Lagrangian (AL) multiphase level set method. The FCM method is used as he intensity discriminator for the multiphase level set method. The AL function avoids the re-initialization procedure. The segmented subcortical regions are validated with the ground truth images using dice similarity index. The texture features such as energy and entropy are calculated from the extracted cortical and subcortical regions. The results show that the multiphase level set method is able to segment the subcortical regions such as corpus callosum, brain stem and cerebellum. The dice similarity index gives above 0.85 for controls and 0.8 for autistic subjects. The texture feature energy calculated from the cortical region is high in autistics compared to the control subjects and vice versa in the case of entropy. The energy calculated from the subcortical regions is high in controls and entropy is high in autism subjects. Comparatively, the energyand entropy calculated from the total brain and brain stem gives significant variation (p<0.0001) between the control and autistic images. As the delayed growth of subcortical region is associated with high values of entropy, this study is clinically significant in the mass screening of neurodevelopmental disorders such as autism.

Study of Alzheimer’s Disease Progression In MR Brain Images based on Segmentation and Analysis of Ventricles using Modified DRLSE Method and Minkowski Functionals.

In this work, the ventricles in MR brain images are segmented using edge based modified Distance Regularized Level Set Evolution (DRLSE) method and the structural changes in the disease is further analysed using Minkowski functionals (MFs). Twenty normal and abnormal T1-weighted coronal mid slice MR image are considered for the analysis. The MR brain image is pre-processed using contrast enhancement method. The edge based modified DRLSE with a new penalty term is used to segment the ventricles from the enhanced images. The results of the level set method are compared with geodesic active contour method. The segmentation results are validated using ZSI (Zijdenbos Similarity Index) and F-score. The Minkowski functionals such as MF-area, MF-perimeter and MF-Euler number are calculated from the extracted ventricle region. The longitudinal analysis of ventricles is performed using these features. The results show that the DRLSE based level set method is able to extract the ventricle edges with less discontinuity. The F-score and ZSI is high for DRLSE (0.83 and 0.84) compared to geodesic method (0.79 and 0.80). The MF-area is able to discriminate the controls and the AD subjects with high statistical significance (p < 0.001). This analysis also shows that the MF- area increases with severity. These results could be used for the study of discrimination and progression of the Alzheimer's disease like disorders.

Analysis of cortical and sub-cortical regions in autistic mr images using level set method and structure tensors.

Autism is a complex disease that causes micro structural changes in brain due to delayed growth. In this work, the cortical regions of brain are extracted from T1 -weighted magnetic resonance mid-sagittal view slices. The images are skull stripped using edge based Level Set (LS) which is regularized by a signed distance function. This skull stripping technique is validated with the Brain extraction tool (BET). The extracted cortical regions are then analyzed by calculating the structure tensor matrix from the gradient of the skull stripped images. The anisotropy index derived from the tensor matrix is correlated with the clinical features such as verbal, full scale and performance Intelligent Quotients (IQ). The results show that the level set method is able to extract the cortical brain boundaries correctly with distinct edges. The structure tensor features extracted from the skull stripped images discriminates the control and autistic images. Also, the anisotropy index is negatively correlated with the performance IQ values of autistic subjects.

Fpga based hardware synthesis for automatic segmentation of retinal blood vessels in diabetic retinopathy images.

Diabetic Retinopathy (DR) is a disorder that affects the structure of retinal blood vessels due to long-standing diabetes mellitus. Real-Time mass screening system for DR is vital for timely diagnosis and periodic screening to prevent the patient from severe visual loss. Human retinal fundus images are widely used for an automated segmentation of blood vessel and diagnosis of various blood vessel disorders. In this work, an attempt has been made to perform hardware synthesis of Kirsch template based edge detection for segmentation of blood vessels. This method is implemented using LabVIEW software and is synthesized in field programmable gate array board to yield results in real-time application. The segmentation of blood vessels using Kirsch based edge detection is compared with other edge detection methods such as Sobel, Prewitt and Canny. The texture features such as energy, entropy, contrast, mean, homogeneity and structural feature namely ratio of vessel to vessel free area are obtained from the segmented images. The performance of segmentation is analysed in terms of sensitivity, specificity and accuracy. It is observed from the results that the Kirsch based edge detection technique segmented the edges of blood vessels better than other edge detection techniques. The ratio of vessel to vessel free area classified the normal and DR affected retinal images more significantly than other texture based features. FPGA based hardware synthesis of Kirsch edge detection method is able to differentiate normal and diseased images with high specificity (93%). This automated segmentation of retinal blood vessels system could be used in computer-assisted diagnosis for diabetic retinopathy screening in real-time application.

Lossless Compression on MRI Images Using SWT.

Medical image compression is one of the growing research fields in biomedical applications. Most medical images need to be compressed using lossless compression as each pixel information is valuable. With the wide pervasiveness of medical imaging applications in health-care settings and the increased interest in telemedicine technologies, it has become essential to reduce both storage and transmission bandwidth requirements needed for archival and communication of related data, preferably by employing lossless compression methods. Furthermore, providing random access as well as resolution and quality scalability to the compressed data has become of great utility. Random access refers to the ability to decode any section of the compressed image without having to decode the entire data set. The system proposes to implement a lossless codec using an entropy coder. 3D medical images are decomposed into 2D slices and subjected to 2D-stationary wavelet transform (SWT). The decimated coefficients are compressed in parallel using embedded block coding with optimized truncation of the embedded bit stream. These bit streams are decoded and reconstructed using inverse SWT. Finally, the compression ratio (CR) is evaluated to prove the efficiency of the proposal. As an enhancement, the proposed system concentrates on minimizing the computation time by introducing parallel computing on the arithmetic coding stage as it deals with multiple subslices.

Autologous chondrocyte implantation for knee focal cartilage defects: 3 years' follow-up at the University Malaya Medical Centre

Autologous chondrocyte implantation (ACI) is a widely accepted procedure for the treatment of large, fullthickness chondral defects involving various joints, but its use in developing countries is limited because of high cost and failure rates due to limited resources and support systems. Five patients (age <45 years) with focal cartilage defects received ACI at University of Malaya from 2006 to 2007 and followed up for 36 months. The average presubjective Knee Evaluation Forms (IKDC) improved from 38.44±6.29 to 25.6±8.04 postoperatively, the Oxford Knee Score (OKS) went from 25.6±8.04 to 13.96±1.63 and the American Knee Society Score (AKSS) improved from 80±14.33 to 92.96±5.82 post-operatively. Thus improvements were seen in the IKDC and AKSS score but not in the OKS. Magnetic resonance images showed the presence of cartilage tissue filling in the lateral and medial patellar facet and medial femoral condyle in three patients. Failures were seen in two patients, both with patellar defects and over the age of 36 years. Treatment with autologous chondrocyte implantation for focal cartilage defect in lateral and medial patellar facet and medial femoral condyle showed early improvement which was maintained at 3 yrs follow-up. ACI provided satisfactory outcome in focal cartilage defects involving the femoral condyle.

Prevalence of the trichomonas vaginalis infection in a tertiary care hospital in rural bangalore, southern India.

BACKGROUND: The infection with Trichomonas Vaginalis is one of the most common sexually transmitted diseases (STDs) in humans. The prevalence of this infection has been reported to be between 2 to 8%, depending on the different socio-cultural conditions. This study aimed to determine the prevalence of T. vaginalis in the women who were referred to the gynaecologic clinics at the MVJ medical college, Bangalore, India. METHODS: This descriptive, cross-sectional study was conducted on 750 women who were referred to the gynaecologic clinics from October 2010 to September 2012. Vaginal samples were obtained from them and they were examined by wet mount and culture methods for the detection of T. vaginalis. RESULTS: Sixteen out of the 750 vaginal swab specimens (2.1%) were culture positive for T. vaginalis and 13 among these positive specimens (1.7%) were wet mount positive. Only 12 of the 42 patients who were clinically diagnosed as having the T. vaginalis infection, were confirmed by the culture method. Five hundred and fifty of the participants (73.3%) had at least one of signs and symptoms of trichomoniasis. No statistical correlation was observed between the clinical manifestations and the parasitological results (p>0.05). CONCLUSION: This study showed a low prevalence of the T. vaginalis infection in the study population. Since the clinical signs of trichomonal vaginitis are the same as those of other STDs, a confirmatory laboratory diagnosis is necessary. Wet smears, as well as culture, are sensitive for the detection of T. vaginalis.