Master Frame Extraction of Fetal Cardiac Images Using B Mode Ultrasound Images

Fetal Echocardiography is used for monitoring the fetal heart and for detection of Congenital Heart Disease (CHD). It is well known that fetal cardiac four chamber view has been widely used for preliminary examination for the detection of CHD. The end diastole frame is generally used for the analysis of the fetal cardiac chambers which is manually picked by the clinician during examination/screening. This method is subjected to intra and inter observer errors and also time consuming. The proposed study aims to automate this process by determining the frame, referred to as the Master frame from the cine loop sequences that can be used for the analysis of the fetal heart chambers instead of the clinically chosen diastole frame. The proposed framework determines the correlation between the reference (first) frame with the successive frames to identify one cardiac cycle. Then the Master frame is formed by superimposing all the frames belonging to one cardiac cycle. The master frame is then compared with the clinically chosen diastole frame in terms of fidelity metrics such as Dice coefficient, Hausdorff distance, mean square error and structural similarity index. The average value of the fidelity metrics considering the dataset used for this study 0.73 for Dice, 13.94 for Hausdorff distance, 0.99 for Structural Similarity Index and 0.035 for mean square error confirms the suitability of the proposed master frame extraction thereby avoiding manual intervention by the clinician. .

Synthesis, Molecular Modeling, DNA Damage Interaction, and Antioxidant Potential of Hesperidin Loaded on Gold Nanoparticles

The flavonoglycone hesperidin is recognized as a potent anti-inflammatory, anticancer, and antioxidant agent. However, its poor bioavailability is a crucial bottleneck regarding its therapeutic activity. Gold nanoparticles are widely used in drug delivery because of its unique properties that differ from bulk metal. Hesperidin loaded gold nanoparticles were successfully prepared to enhance its stability and bioactive potential, as well as to minimize the problems associated with its absorption. The free radical scavenging activities of hesperidin, gold nanoparticles, and hesperidin loaded gold nanoparticles were compared with that of Vitamin C and subsequently evaluated in vitro using 2,2-diphenyl-1-picrylhydrazyl assay. The antioxidant pharmacophore-based structure-activity relationship analysis was assessed by the density functional theory as well as quantum chemical calculations. Moreover, the structural properties were utilized using Becke’s three-parameter hybrid exchange and Lee-Yang-Parr’s correction of functional approaches. Hesperidin-loaded gold nanoparticles were found to decrease hydrogen peroxide (H2O2) and thus induce Deoxyribonucleic acid (DNA) instability. In addition, hesperidin-gold nanoparticles were observed to display important antioxidant potential as well as ameliorate the functional activity of macrophages against Escherichia coli, possibly protecting DNA. These particles might be appropriate for clinical trials and could prove useful for the treatment of various life-threatening disorders.

Vasodilatation Measurement Using Finger Vascular Images by Near-Infrared Light and Comparison with RH-PAT

Examination of vascular endothelial function can help infer atherosclerosis progression. This study investigated whether vascular visualization by near-infrared (NIR) light can detect vasodilatation after cuff pressure release of the upper arm and what the correlation is between the brightness decrease ratio (R1) corresponding to vasodilation and the reactive hyperemia index (RHI). We obtained finger vascular images of 53 male subjects by photographing NIR light (wavelength 850 nm) transmitted through the middle phalanx of the middle finger with a charge-coupled device camera. The upper arm was compressed for 10 min using a cuff (200 mmHg), and vascular images before and after cuff compression release were obtained. We analyzed the finger vascular images by NIR light and digital pulse volume using endothelial peripheral arterial tonometry (Endo-PAT). We also calculated the average brightness of each vascular image. Using only the data of the ischemic finger, R1 was defined using the average brightness just before cuff release and the minimum average brightness after cuff release. The brightness of vascular images of the ischemic finger decreased after cuff release probably because of vasodilation. We found significant correlation between R1 and the RHI (r = 0.52; P < 0.001). R1 in the lowest RHI quartile was significantly smaller compared to the highest and second-highest RHI quartiles (P < 0.05). Vascular visualization by NIR light can detect vasodilation after cuff release. This is significantly correlated with the RHI on Endo-PAT.

Comparison of Stress Distribution in Surrounding Bone during Insertion of Dental Implants on Four Implant Threads under the Effect of an Impact: A Finite Element Study

The design of an implant thread plays a fundamental role in the osseointegration process, particularly in low-density bone. It has been postulated that design features that maximize the surface area available for contact may improve mechanical anchorage and stability in cancellous bone. The primary stability of a dental implant is determined by the mechanical engagement between the implant and bone at the time of implant insertion. The contact area of implant-bone interfaces and the concentrated stresses on the marginal bones are principal concerns of implant designers. Numerous factors influence load transfer at the bone-implant interface, for example, the type of loading, surface structure, amount of surrounding bone, material properties of the implant and implant design. The purpose of this study was to investigate the effects of the impact two different projectile of implant threads on stress distribution in the jawbone using three-dimensional finite element analysis.

Synthesis and Characterization of Phosphoric Silica Catalyst from Bamboo Leaves for Production of Triacetin

In this research, the bamboo leaf shows promise as an alternative raw material for silica production. This study investigated the performance of heterogeneous catalyst prepared from silica derived bamboo leaf ash after that impregnated with phosphoric acid at ratio various. The catalyst was characterized by X-Ray Diffraction (XRD), Fourier Transform Infrared Spectroscopy (FTIR), Scanning Electron Microscope Energy Dispersive X-Ray Spectroscopy (SEM-EDS), Brunauer Emmet Teller (BET) and Barrett, Joyner and Halenda (BJH) method and triacetin product analyzed by GC-MS. The optimum condition phosphoric silica catalyst was obtained at phosphoric silica molar ratio of 1:2 and employed in the acetylation of glycerol, respectively. As result, 24 % selectivity for triacetin was obtained in the presence of catalytic amount 5%, molar ratio 1:9 at 100 °C for 4 hours. Bamboo leaf derived phosphoric silica calcined showed high potential to be used as an easy to prepare and high-performance solid catalyst for industrial scale.

Heat Treatment Effect on Biological Behavior of Polyetheretherketone Composites

Polyetheretherketone is a semi-crystalline thermoplastic polymer, that so with heat treatments, it is possible to get different properties which are very important for the material performance. Heat treatment is a broadly utilized to develop the semi-crystalline polymers properties. In the present investigation, annealing of polyetheretherketone (PEEK) was carried out at temperatures above its glass transition temperature (Tg) to study its effects upon the biological conduct of the control and PEEK ternary composites. The bioactivity of the specimens was evaluated by investigating the apatite formation after immersion for different periods in a simulated body fluid (SBF). The biocompatibility of specimens was assessed by MTT assay. Additionally, the antibacterial property of the specimens versus S. aureus was observed with the optical density methods. The results manifested that the formation of hydroxyapatite was obviously observed on specimens after immersion for (7 and 14 days) in the simulated body fluid (SBF). Otherwise, the results of MTT assay recorded the PEEK specimens that excited the activity of fibroblasts, and therefore a high cytocompatibility was noticed and the specimens revealed antibacterial properties against S. aureus. So, the results of the bioactivity, biocompatibility and antibacterial tests in vitro demonstrated that the heat treatment enhanced biological behavior.

Blood Pressure Estimation from Photoplethysmography with Motion Artifacts Using Long Short Term Memory Network

Continuous measurement of the Blood Pressure (BP) is important in hypertensive patientsand elderly population. Traditional cuff based methods are difficult to use since it is uncomfortable towear a cuff throughout the day. A more suitable method is to estimate the BP using the Photoplethysmography(PPG) signal. However, it is difficult to estimate a BP when the PPG is corrupted withMotion Artifacts (MAs). In this paper, Long Short Term Memory (LSTM) an extension of RecurrentNeural Networks (RNN) is used used to improve the accuracy of the estimation of the BP from thecorrupted PPG. It shows that an accuracy of 97.86 is achieved.

Cytotoxicity and Ion Release of Functionally Graded Al2O3- Ti Orthopedic Biomaterial

The aim of this study was to evaluate the biocompatibility of Al2O3-Ti functionally graded material (FGM) successfully fabricated by Spark Plasma Sintering (SPS) technology, and to compare with pure Ti and alumina. Pre-osteoblast MC3T3-E1 cells were used to examine cell viability, proliferation and differentiation using lactate dehydrogenase (LDH) cytotoxicity detection kit, MTT assay and Alkaline Phosphatase (ALP) colorimetric test at different time points. Furthermore, ion release from the materials into the culture medium was assessed. The results showed cell viability over 80% for FGM and alumina which dismissed any cytotoxicity risk due to materials or manufacturing. The results of MTT tests identified superiority of FGM than Ti and alumina, particularly in late proliferation. Nevertheless, in cell differentiation, all materials performed similarly with no statistical differences. Furthermore, it was indicated that Ti had no ion release, while alumina had small amount of Al ion dissolution. FGM, however, had more ions detachment, particularly Al ions.

A Hybrid Machine Learning Model Based on Global and Local Learner Algorithms for Diabetes Mellitus Prediction

Health is a critical condition for living things, even before the technology exists. Nowadays the healthcare domain provides a lot of scope for research as it has extremely evolved. The most researched areas of health sectors include diabetes mellitus (DM), breast cancer, brain tumor, etc. DM is a severe chronic disease that affects human health and has a high rate throughout the world. Early prediction of DM is important to reduce its risk and even avoid it. In this study, we propose a DM prediction model based on global and local learner algorithms. The proposed global and local learners stacking (GLLS) model; combines the prediction algorithms from two largely different but complementary machine learning paradigms, specifically XGBoost and NB from global learning whereas kNN and SVM (with RBF kernel) from local learning and aggregates them by stacking ensemble technique using LR as meta-learner. The effectiveness of the GLLS model was proved by comparing several performance measures and the results of different contrast experiments. The evaluation results on UCI Pima Indian diabetes data-set (PIDD) indicates the model has achieved the better prediction performance of 99.5%, 99.5%, 99.5%, 99.1%, and 100% in terms of accuracy, AUC, F1 score, sensitivity, and specificity respectively, compared to other research results mentioned in the literature. Moreover, to better validate the GLLS model performance, three additional medical data sets; Messidor, WBC, ILPD, are considered and the model also achieved an accuracy of 82.1%, 98.6%, and 89.3% respectively. Experimental results proved the effectiveness and superiority of our proposed GLLS model.

Effect of Formulation Variables for the Production of WGA-Grafted, Levodopa-Loaded PLGA Nanoparticles

Levodopa is used for the treatment of Parkinson’s disease (PD) for the last few decades. However, adverse reactions such as dyskinesia, somnolence, nausea, itching, rash, as well as the need for frequent dosing and low bioavailability problems affect the success of the treatment. To prevent side effects caused by conventional therapy, a nanoparticular drug delivery system has been developed, in which receptors are constantly stimulated, and the frequency of dosing is reduced. In this study, levodopa was loaded in Poly lactic-co-glycolic acid (PLGA) nanoparticles (NP) which modified with Wheat Germ Agglutinin (WGA) To increase the effectiveness of levodopa, reduce its side effects and apply to the nasal area which is an alternative way for brain targeting with lower doses. To obtain the optimum levodopa loaded PLGA nanoparticles, the effect of some formulation variables such as polyvinyl alcohol (PVA) concentration, homogenization speed, polymer amount and molecular weight, and levodopa content on the entrapment efficiency (EE) and particle size of the nanoparticles were investigated. Besides these variables, the effect of different parameters on the WGA binding constant was also searched. In addition to in vitro release studies, Differential Scanning Calorimetry (DSC) and Fourier Transform Infrared Spectrophotometer (FT-IR), and Transmission electron microscopy (TEM) analysis were used in the characterization of nanoparticles. Among all formulations, A2 and A8a which was produced with different molcular weights of PLGA, different added levodopa amounts and with different homogenization speeds were chosen as optimum formulations due to their sustained release properties and the ability to release 80 % of their drug content.WGA binding constant was found 78.20 % for A8a-1 and 95 % for A2-1. In this study, we aimed to determine the effect of different formulation parameters on the development of levodopa loaded and WGA grafted PLGA nanoparticles and on the quality characteristics of nanoparticle formulations such as particle size, zeta potential, and EE. In this paper, our results are demonstrated for a better understanding of the effect of process parameters on the development of nanoparticle-based drug delivery systems by using the double-emulsion solvent evaporation technique and on WGA binding of drug-loaded PLGA nanoparticles.