The tumor-specific targeting of chemotherapeutic agents for specific necrosis of cancer cells without affecting the normal cells poses a great challenge for researchers and scientists. Though ...extensive research has been carried out to investigate chemotherapy-based targeted drug delivery, the identification of the most promising strategy capable of bypassing non-specific cytotoxicity is still a major concern. Recent advancements in the arena of onco-targeted therapies have enabled safe and effective tumor-specific localization through stimuli-responsive drug delivery systems. Owing to their promising characteristic features, stimuli-responsive drug delivery platforms have revolutionized the chemotherapy-based treatments with added benefits of enhanced bioavailability and selective cytotoxicity of cancer cells compared to the conventional modalities. The insensitivity of stimuli-responsive drug delivery platforms when exposed to normal cells prevents the release of cytotoxic drugs into the normal cells and therefore alleviates the off-target events associated with chemotherapy. Contrastingly, they showed amplified sensitivity and triggered release of chemotherapeutic payload when internalized into the tumor microenvironment causing maximum cytotoxic responses and the induction of cancer cell necrosis. This review focuses on the physical stimuli-responsive drug delivery systems and chemical stimuli-responsive drug delivery systems for triggered cancer chemotherapy through active and/or passive targeting. Moreover, the review also provided a brief insight into the molecular dynamic simulations associated with stimuli-based tumor targeting.
Living walls enhancing the urban realm: a review Goel, Manika; Jha, Bandana; Khan, Safiullah
Environmental science and pollution research international,
06/2022, Volume:
29, Issue:
26
Journal Article
Peer reviewed
Open access
In the current Anthropocene epoch, globalization and urbanization have adversely affected our environment causing global warming. To counter the adverse effects of global warming, research is being ...conducted into many innovative technologies to identify viable solutions. This paper will focus on one such solution, Living walls and how the built form is enriched by the environmental and psychological benefits provided by Living walls. Buildings with Living walls have lively surroundings which enhance the urban fabric. This review paper shall elaborate on the effects of Living walls on the built environment in the urban realm and analyze how Living walls improve the urban fabric in terms of activity and behavior pattern, streetscape and building frontage.
Bone tumors, such as osteosarcomas, can occur anywhere in the bones, though they usually occur in the extremities of long bones near metaphyseal growth plates. Osteosarcoma is a malignant lesion ...caused by a malignant osteoid growing from primitive mesenchymal cells. In most cases, osteosarcoma develops as a solitary lesion within the most rapidly growing areas of the long bones in children. The distal femur, proximal tibia, and proximal humerus are the most frequently affected bones, but virtually any bone can be affected. Early detection can reduce mortality rates. Osteosarcoma’s manual detection requires expertise, and it can be tedious. With the assistance of modern technology, medical images can now be analyzed and classified automatically, which enables faster and more efficient data processing. A deep learning-based automatic detection system based on whole slide images (WSIs) is presented in this paper to detect osteosarcoma automatically. Experiments conducted on a large dataset of WSIs yielded up to 99.3% accuracy. This model ensures the privacy and integrity of patient information with the implementation of blockchain technology. Utilizing edge computing and fog computing technologies, the model reduces the load on centralized servers and improves efficiency.
Security and privacy in the Internet of Things (IoT) other significant challenges, primarily because of the vast scale and deployment of IoT networks. Blockchain-based solutions support decentralized ...protection and privacy. In this study, a private blockchain-based smart home network architecture for estimating intrusion detection empowered with a Fused Real-Time Sequential Deep Extreme Learning Machine (RTS-DELM) system model is proposed. This study investigates the methodology of RTS-DELM implemented in blockchain-based smart homes to detect any malicious activity. The approach of data fusion and the decision level fusion technique are also implemented to achieve enhanced accuracy. This study examines the numerous key components and features of the smart home network framework more extensively. The Fused RTS-DELM technique achieves a very significant level of stability with a low error rate for any intrusion activity in smart home networks. The simulation findings indicate that this suggested technique successfully optimizes smart home networks for monitoring and detecting harmful or intrusive activities.
The present study is associated with the development of proliposomes and liposomal derived gel for enhanced solubility and permeability of diacerein. Proliposomes were developed by thin film ...hydration method and converted into the liposomal derived gel using carbopol-934 as a gelling agent. Formulations with varied lecithin to cholesterol ratios were investigated to obtain the optimal size, entrapment efficiency, and enhanced in vitro dissolution. Dynamic light scattering analysis revealed the particle size and zeta potential in the range of 385.1±2.45-762.8±2.05 nm and -22.4±0.55-31.2±0.96mV respectively. Fourier transform infrared (FTIR) spectroscopic analysis depicted the physicochemical compatibility, powdered x-ray diffraction (PXRD) analysis predicted the crystalline nature of pure drug and its transition into amorphous form within formulation. The differential scanning calorimetry (DSC) demonstrated the thermal stability of the formulation. The in vitro drug release study using dialysis membrane displayed the enhanced dissolution of diacerein due to the presence of hydrophilic carrier (Maltodextrin) followed by sustained drug release due to the presence of lipid mixture (lecithin and cholesterol). Ex vivo permeation studies depicted 3.50±0.27 and 3.21±0.22 folds enhanced flux of liposomal gels as compared to control. The acute oral toxicity study showed safety and biocompatibility of the system as no histopathological changes in vital organs were observed. These results suggests that proliposomes and liposomal derived gel are promising candidates for the solubility and permeability enhancement of diacerein in the management of osteoarthritis.
The present study aimed to prepare solid lipid-based nanoparticles (SLNs) using Precirol® ATO 5 as solid lipid and Poloxamer 188 and Tween 80 as surfactant and co-surfactant respectively, and ...SLNs-derived gel for sustained delivery, enhanced in-vitro cytotoxicity, enhanced cellular uptake of 5-FU and enhanced permeation of 5-FU across the skin. The 5-FU-loaded SLNs were prepared by the hot melt encapsulation method and converted into SLN-derived gel using a gelling agent (Carbopol 940). The 5-FU-loaded SLNs had a particle size in the range of 76.82±1.48 to 327±4.46 nm, zeta potential between -11.3±2.11 and -28.4±2.40 mV, and entrapment efficiency (%) in range of 63.46±1.13 and 76.08±2.42. The FTIR analysis depicted that there was no chemical interaction between 5-FU and formulation components. Differential scanning calorimetric analysis showed thermal stability of 5-FU in the nanoparticles and powdered X-ray diffraction analysis revealed successful incorporation of 5-FU in nanoparticles. The in-vitro release study of 5-FU-loaded SLNs showed biphasic release behavior with initial burst release followed by sustained release over 48 hr. The 5-FU-loaded SLNs showed a greater cytotoxic effect on skin melanoma (B16F10 cells) and squamous cell carcinoma (A-431 cells) as compared to free 5-FU drug solution after 48 hr. Flow cytometry and fluorescence microscopy displayed enhanced quantitative and qualitative cellular uptake of SLNs. The SLNs formulation showed acceptable safety and biocompatible profile after an acute toxicity study in Wistar rats. Moreover, ex-vivo permeation studies depicted 2.13±0.076 folds enhanced flux of 5-FU-loaded SLN derived gel compared to 5-FU plain gel, and skin retention studies revealed target efficiency (%) 2.54±0.03 of 5-FU-loaded SLN derived gel compared to 5-FU plain gel.
A metamaterial-based planar polarization conversion screen is designed by exploiting the mutual interactions between two distinct types of resonators. The design starts from a unit cell comprising a ...subwavelength T-type resonator and a rectangular split-ring resonator (RSRR). In order to enhance the cross-polarization conversion, the unit cell is rotated by 90° to obtain a chiral geometry and the right diagonal elements are scaled down to construct a rotationally asymmetric <inline-formula> <tex-math notation="LaTeX">2\,\times \,2 </tex-math></inline-formula> supercell. The supercells are arranged periodically on either side of the substrate. In the bottom layer, each element is rotated by 90° with respect to the corresponding element in the top layer to achieve the asymmetric transmission property and to introduce the desired phase difference between the two orthogonal linear vector components of the transmitted wave. The proposed design exhibits very good circular polarization efficiency, which is primarily achieved by transverse magnetic dipole-magnetic dipole coupling. The polarizer has an ellipticity of 44.4° and a polarization extinction ratio of 37.30 dB at 14.79 GHz. Furthermore, the polarization conversion ratio for both linear orthogonal components is identical at this frequency. At 9.15 GHz, strong orthogonal polarization rotation is observed. The electrical size of the unit cell is <inline-formula> <tex-math notation="LaTeX">0.25\lambda _{0} \times 0.25\lambda _{0} \times 0.077\lambda _{0} </tex-math></inline-formula>. Simulation and measurement results are presented to verify the performance of the polarization converter.
The study presents a framework to analyze and detect meddling in real-time network data and identify numerous meddling patterns that may be harmful to various communication means, academic ...institutes, and other industries. The major challenge was to develop a non-faulty framework to detect meddling (to overcome the traditional ways). With the development of machine learning technology, detecting and stopping the meddling process in the early stages is much easier. In this study, the proposed framework uses numerous data collection and processing techniques and machine learning techniques to train the meddling data and detect anomalies. The proposed framework uses support vector machine (SVM) and K-nearest neighbor (KNN) machine learning algorithms to detect the meddling in a network entangled with blockchain technology to ensure the privacy and protection of models as well as communication data. SVM achieves the highest training detection accuracy (DA) and misclassification rate (MCR) of 99.59% and 0.41%, respectively, and SVM achieves the highest-testing DA and MCR of 99.05% and 0.95%, respectively. The presented framework portrays the best meddling detection results, which are very helpful for various communication and transaction processes.
With the continuous increase in avenues of personal data generation, privacy protection has become a hot research topic resulting in various proposed mechanisms to address this social issue. The main ...technical solutions for guaranteeing a user's privacy are encryption, pseudonymization, anonymization, differential privacy (DP), and obfuscation. Despite the success of other solutions, anonymization has been widely used in commercial settings for privacy preservation because of its algorithmic simplicity and low computing overhead. It facilitates unconstrained analysis of published data that DP and the other latest techniques cannot offer, and it is a mainstream solution for responsible data science. In this paper, we present a comprehensive analysis of clustering-based anonymization mechanisms (CAMs) that have been recently proposed to preserve both privacy and utility in data publishing. We systematically categorize the existing CAMs based on heterogeneous types of data (tables, graphs, matrixes, etc.), and we present an up-to-date, extensive review of existing CAMs and the metrics used for their evaluation. We discuss the superiority and effectiveness of CAMs over traditional anonymization mechanisms. We highlight the significance of CAMs in different computing paradigms, such as social networks, the internet of things, cloud computing, AI, and location-based systems with regard to privacy preservation. Furthermore, we present various proposed representative CAMs that compromise individual privacy, rather than safeguarding it. Besides, this article provides an extended knowledge (e.g., key assertion(s), strengths, weaknesses, clustering methods used in the anonymization process, and %age improvements in quantitative results) about each technique that provides a clear view of how much this topic has been investigated thus far, and what are the research gaps that seek pertinent solutions in the near future. Finally, we discuss the technical challenges of applying CAMs, and we suggest promising opportunities for future research. To the best of our knowledge, this is the first work to systematically cover current CAMs involving different data types and computing paradigms.
Modular multiplication is the most crucial operation in many public-key crypto-systems, which can be accomplished by integer multiplication followed by a reduction scheme. The reduction scheme ...involves a division operation that is costly in terms of computation time and resource consumption both on hardware and software platforms. Montgomery modular multiplication is widely used to eliminate the costly division operation. This work presents an efficient implementation of full-word Montgomery modular multiplication. This incorporates the more efficient Karatsuba algorithm where the complexity of multiplication is reduced form O(n2) to O(n1.58). The Karatsuba algorithm recommends to split the operands into smaller chunks. Two methods of operand splitting are exploited: (1) Four Parts (FP) splitting and (2) Deep Four Parts (DFP) splitting. These methods are then used in the design of Integer Multiplier (IM) and Montgomery Multiplier (MM). The design is synthesized using Xilinx ISE 14.1 Design Suite for Virtex-5, Virtex-6 and Virtex-7. Compared with the traditional implementations, the proposed scheme outperforms all other designs in terms of throughput and area-delay product. Moreover, the proposed scheme utilizes the least hardware resources in the known literature. The proposed MM design is able to compute modular multiplication for the Elliptic Curve Cryptography (ECC) field sizes of 192–512 bits.
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