Fabrication of garlic composites nano-biotics and investigating their anti-bacterial activities

Bacterial infections are considered the second main cause of death worldwide and the third main cause of death in the developed countries and as a result, many antibacterial coatings have been prepared in order to fight the different strains of bacteria and decrease the mortality rates. Natural antibacterial products become of great interest nowadays and their use is preferred over the synthetic products in order to overcome the resistance to the synthetic antibiotics. A wide variety of antibacterial coatings have been developed ranging from polymeric to polymer Nano-composites (PNCs) materials. Using nanomaterials as fillers within polymer matrices have been reported to enhance the antibacterial properties significantly. The polymeric nanoparticles (NPs) are promising for natural antibacterial drug delivery. In this study, two types of Garlic oil nano-composites (GO-NCs) have been developed by using two polymers which are poly lactic-co-glycolic (PLGA) and poly lactic-co-glycolic/poly ethylene glycol (PLGA/PEG) mixed with garlic oil (GO). The two polymer Nano-composites were named PLGA-GO-NCs and PLGA-PEG-GO-NCs respectively. Single emulsion/solvent evaporation (SE/SE) technique was involved in the preparation of the different nanocomposite formulations. The polymers conjugated with GO were prepared at three different homogenization time intervals (5, 10 and 15 min.) at the same homogenization speed of 11,000 rpm. All the preparation parameters, such as the concentration of polymers, concentration of GO, amounts of surfactant used (polaxmer 407) and the homogenization speed, were kept constant to identify the effect of the homogenization time on the physicochemical properties and the antibacterial activities of the PNCs. In addition, the effect of other factors such as the effect of solution settling, the use of Buchner funnel in solution filtration, the use of biological filters in solution filtration and the effect of mechanical shaking the solutions by using vortex stirring on the different formulations were carefully examined. The particle sizes, zeta potential and poly dipsersity index (PDI) and GO% in each formulation have been measured. The morphological examination of the prepared nanocomposite formulations was carried out by using Scanning Electron Microscope (SEM), and the chemical structural characteristics were examined by using Fourier Transform-Infra-red spectroscopy (FT-IR) and Ultraviolet-Visible spectrophotometry (UV-vis). In addition, antibacterial assessment has been carried out against Eichercia Coli (E. coli) (ATCC 8739) as a Gram-negative bacterium, and Staphylococcus aureus (S. aureus) (ATCC 6538) as a Gram-positive bacterium using Colony Counting Method (CCM). The results revealed four important factors that need to be considered during the preparation of GO NPs which are (i) settling of the solutions, (ii) filtration through biological filters, (iii) Buchner filtration and (iv) vortex stirring of solutions. These factors play a crucial role in controlling the size and stability of PNCs. Furthermore, we have observed that the addition of PEG to the PLGA-GO formulations has a significant effect on decreasing the particle sizes and increasing the GO% in the formulations. These results could be promising in producing polymeric drug/extract NPs of small particle sizes, high stability and of pronounced antibacterial activity which is stronger than the original dtug/extract

Cyber LOPA: An Integrated Approach for the Design of Dependable and Secure Cyber Physical Systems

Safety risk assessment is an essential process to ensure a dependable Cyber-Physical System (CPS) design. Traditional risk assessment considers only physical failures. For modern CPS, failures caused by cyber attacks are on the rise. The focus of latest research effort is on safety-security lifecycle integration and the expansion of modeling formalism for risk assessment to incorporate security failures. The interaction between safety and security and its impact on the overall system design, as well as the reliability loss resulting from ignoring security failures are some of the overlooked research questions. This paper addresses these research questions by presenting a new safety design method named Cyber Layer Of Protection Analysis (CLOPA) that extends existing LOPA framework to include failures caused by cyber attacks. The proposed method provides a rigorous mathematical formulation that expresses quantitatively the trade-off between designing a highly-reliable versus a highly-secure CPS. We further propose a co-design lifecycle process that integrates the safety and security risk assessment processes. We evaluate the proposed CLOPA approach and the integrated lifecycle on a practical case study of a process reactor controlled by an industrial control testbed, and provide a comparison between the proposed CLOPA and current LOPA risk assessment practice.Comment: Main Content: Title adjusted, Related work moved to end, added references, Sec IV (prev. sec V): expanded discussion, design and Alg. 1 updated | Sec V (prev. sec VI): Expanded discussion, Table V Expanded. Editorial: Fig 1 redrawn horiz., Eq (4)(5) math notation changed, same content. Eq (25) expanded, Page-wide eq. not ref as fig (shift by 1 of fig num), Fig 4 iterative design values show

Skin Lesion Analysis Toward Melanoma Detection Using Deep Learning Techniques

In the last few years, a great attention was paid to the deep learning Techniques used for image analysis because of their ability to use machine learning techniques to transform input data into high level presentation. For the sake of accurate diagnosis, the medical field has a steadily growing interest in such technology especially in the diagnosis of melanoma. These deep learning networks work through making coarse segmentation, conventional filters and pooling layers. However, this segmentation of the skin lesions results in image of lower resolution than the original skin image. In this paper, we present deep learning based approaches to solve the problems in skin lesion analysis using a dermoscopic image containing skin tumor. The proposed models are trained and evaluated on standard benchmark datasets from the International Skin Imaging Collaboration (ISIC) 2018 Challenge. The proposed method achieves an accuracy of 96.67% for the validation set .The experimental tests carried out on a clinical dataset show that the classification performance using deep learning-based features performs better than the state-of-the-art technique

Skin Lesion Analysis Toward Melanoma Detection Using Deep Learning Techniques

In the last few years, a great attention was paid to the deep learning Techniques used for image analysis because of their ability to use machine learning techniques to transform input data into high level presentation. For the sake of accurate diagnosis, the medical field has a steadily growing interest in such technology especially in the diagnosis of melanoma. These deep learning networks work through making coarse segmentation, conventional filters and pooling layers. However, this segmentation of the skin lesions results in image of lower resolution than the original skin image. In this paper, we present deep learning based approaches to solve the problems in skin lesion analysis using a dermoscopic image containing skin tumor. The proposed models are trained and evaluated on standard benchmark datasets from the International Skin Imaging Collaboration (ISIC) 2018 Challenge. The proposed method achieves an accuracy of 96.67% for the validation set .The experimental tests carried out on a clinical dataset show that the classification performance using deep learning-based features performs better than the state-of-the-art technique

Tests of Storage Rack Channel Columns with Rear Flanges

An experimental study was performed to investigate the ultimate strength and modes of failure of axially loaded channel rack columns with rear flanges. A total of 16 column specimens fabricated by press-brake forming method were tested up to failure. The material properties of the column specimens were determined using standard tensile coupon tests. The deformation and stress behavior of the tested columns were monitored using displacement transducers and strain gauges. The effects of column slenderness ratio, thickness, perforation, and end conditions on the column ultimate strength and mode of failure were studied. The test failure loads were compared to the ultimate load predictions of the 2001 AISI North American Specification. The comparison showed that the AISI procedure overestimates the failure load, which suggests that the proportioning of the cross-sectional dimensions of the lipped channel sections with rear flanges has a direct effect on the capacity of the columns

The Effect of Thickness And Accelerated Aging on Opalescence of Different Ceramic Materials

Purpose: The objective of the study was to evaluate the effect of ceramic material type and thickness on opalescence before and after accelerated aging. Materials and methods: 180 all-ceramic slices were divided into three groups (n=60) according to the ceramic material (InCoris TZI, Empress CAD HT, and Empress CAD LT). Each group was further subdivided into four subgroups (n = 15) according to their thickness (0.5 mm, 0.8 mm, 1 mm and 1.2 mm).). CIE Lab coordinates were measured for each slice against black and white backgrounds using intraoral spectrophotometer and OP was calculated. All specimens were subjected to accelerated aging using autoclave (134 ºC, 0.2 MPa for 5 h) and OP was calculated after accelerated aging. Repeated ANOVA combined with a Tukey-post hoc test were used to analyze the data obtained (P ≤ 0.05). Results: The results showed that ceramic material type and thickness have significant effect on opalescence with OP values (from 4.4±1.2 to 7.1±1.7) for InCoris TZI, (from 4.1±0.28 to 5.7±0.36) for CAD HT, and (from 5.9±0.7 to 8.7±4.6) for CAD LT, while the effect of accelerated aging was not statistically significant. Conclusion: The dental ceramic type affected the opalescence with Empress CAD HT showing the highest OP values. Increasing the thickness caused an increase in the opalescence of leucite reinforced glass ceramic, while it decreased the opalescence of zirconia. Therefore, manufactures should develop all-ceramic materials that can simulate the opalescence of natural teeth especially in esthetic ceramic restoration with lower thickness

Co-Evolutionary Particle Swarm Optimization Applied to the 7x7 Seega Game

Seega is an ancient Egyptian two-stage board game that, in certain aspects, is more difficult than chess. The two-player game is most commonly played on a 7 × 7 board, but is also sometimes played on a 5 × 5 or 9 × 9 board. In the first and more difficult stage of the game, players take turns placing one disk each on the board until the board contains only one empty cell. In the second stage players take turns moving disks of their color; a disk that becomes surrounded by disks of the opposite color is captured and removed from the board. Building on previous work, on the 5 × 5 version of Seega, we focus, in this paper, on the 7 × 7 board. Our approach employs co-evolutionary particle swarm optimization for the generation of feature evaluation scores. Two separate swarms are used to evolve White players and Black players, respectively; each particle represents feature weights for use in the position evaluation. Experimental results are presented and the performance of the full game engine are discussed

Applying Co-Evolutionary Particle Swam Optimization to the Egyptian Board Game Seega

Seega is an ancient Egyptian two-phase board game that, in certain aspects, is more difficult than chess. The two-player game is played on either a 5 × 5, 7 × 7, or 9 × 9 board. In the first and more difficult phase of the game, players take turns placing one disk each on the board until the board contains only one empty cell. In the second phase players take turns moving disks of their color; a disk that becomes surrounded by disks of the opposite color is captured and removed from the board. We have developed a Seega program that employs co-evolutionary particle swarm optimization in the generation of feature evaluation scores. Two separate swarms are used to evolve White players and Black players, respectively; each particle represents feature weights for use in the position evaluation. Experimental results are presented and the performance of the full game engine is discussed

Effect Of Various Sintering Protocols On The Translucency Of Highly Translucent Cubic Zirconia

Aim of the study: This study was carried out to evaluate the effect of various sintering protocols on the translucency of highly translucent cubic zirconia. Materials and methods: A total of forty discs of two types of zirconia ceramics were used in this study. The specimens were divided into two main groups according to the type of zirconia; Group 1 (n=20): Cubic zirconia (DD Cube X2 98color) and Group 2 (n=20): Tetragonal zirconia (BioZX2color). Each group was subdivided into two subgroups, where 10 discs were per subgroup according to the sintering protocol. Cubic and tetragonal zirconia blanks of dimensions (98 mm diameter × 25 mm thickness) were CAD/CAM milled into cylindrical-shaped blocks of dimensions (15 mm diameter × 25 mm thickness). Cylinders of both materials were cut with a diamond cutting saw into discs with larger dimensions (15 mm diameter × 1.2 mm thickness) to compensate for the approximately 23% shrinkage of the material during sintering, so as the final dimensions would be (12 mm diameter × 1 mm thickness). Discs were dried under a heating lamp and then conventionally and speed sintered according to the manufacturer\u27s instructions. The translucency of each subgroup was evaluated by measuring contrast ratio (CR) and translucency parameter (TP). Results: For both cubic or tetragonal zirconia, conventional sintering showed statistically significantly lower mean CR and higher mean TP than speed sintering (P-value \u3c0.001). Conclusion: Different sintering protocols showed a significant effect on the translucency of cubic and tetragonal zirconia

A Snapshot of photoresponsive liposomes in cancer chemotherapy and immunotherapy: opportunities and challenges

© 2023 The Authors. Published by American Chemical Society. This is an open access article under the Creative Commons Attribution-NonCommercial-NoDerivatives CC BY-NC-ND licence, https://creativecommons.org/licenses/by-nc-nd/4.0To provide precise medical regimens, photonics technologies have been involved in the field of nanomedicine. Phototriggered liposomes have been cast as promising nanosystems that achieve controlled release of payloads in several pathological conditions such as cancer, autoimmune, and infectious diseases. In contrast to the conventional liposomes, this photoresponsive element greatly improves therapeutic efficacy and reduces the adverse effects of gene/drug therapy during treatment. Recently, cancer immunotherpay has been one of the hot topics in the field of oncology due to the great success and therapeutic benefits that were well-recognized by the patients. However, several side effects have been encountered due to the unmonitored augmentation of the immune system. This Review highlights the most recent advancements in the development of photoresponsive liposome nanosystems in the field of oncology, with a specific emphasis on challenges and opportunities in the field of cancer immunotherapy.Peer reviewe