Numerical Study of Geosynthetic-Reinforced Soil Wall Subjected to Static Footing Loading

This study intends to examine the behavior of a GRS wall with static footing loading above it, while varying the positions of the footing. For the study of behavior of such complex structure, finite element modeling is handy and enables to look into the various stress/strain developed in the numerical model. In view of the above, a series of finite element (FEM) simulations using a software (Optum G2) is performed for the analysis of the GRS wall. The governing parameters, such as footing width (B), reinforcement length (L), offset distance (D), are evaluated and the effect of these factors on the ultimate bearing capacity (q) and settlement (s) of the footing is presented in this study. The results depict that the settlement of the footing substantially reduced in the range of 36% and its ultimate bearing capacity is increased to 42% more than the conventional retaining walls

Advances in Nanotechnology for Cancer Immunoprevention and Immunotherapy: A Review

One of the most effective cancer therapies, cancer immunotherapy has produced outstanding outcomes in the field of cancer treatment. However, the cost is excessive, which limits its applicability. A smart way to address this issue would be to apply the knowledge gained through immunotherapy to develop strategies for the immunoprevention of cancer. The use of cancer vaccines is one of the most popular methods of immunoprevention. This paper reviews the technologies and processes that support the advantages of cancer immunoprevention over traditional cancer immunotherapies. Nanoparticle drug delivery systems and nanoparticle-based nano-vaccines have been employed in the past for cancer immunotherapy. This paper outlines numerous immunoprevention strategies and how nanotechnology can be applied in immunoprevention. To comprehend the non-clinical and clinical evaluation of these cancer vaccines through clinical studies is essential for acceptance of the vaccines. © 2022 by the authors

Explainable Misinformation Detection Across Multiple Social Media Platforms

In this work, the integration of two machine learning approaches, namely domain adaptation and explainable AI, is proposed to address these two issues of generalized detection and explainability. Firstly the Domain Adversarial Neural Network (DANN) develops a generalized misinformation detector across multiple social media platforms DANN is employed to generate the classification results for test domains with relevant but unseen data. The DANN-based model, a traditional black-box model, cannot justify its outcome, i.e., the labels for the target domain. Hence a Local Interpretable Model-Agnostic Explanations (LIME) explainable AI model is applied to explain the outcome of the DANN mode. To demonstrate these two approaches and their integration for effective explainable generalized detection, COVID-19 misinformation is considered a case study. We experimented with two datasets, namely CoAID and MiSoVac, and compared results with and without DANN implementation. DANN significantly improves the accuracy measure F1 classification score and increases the accuracy and AUC performance. The results obtained show that the proposed framework performs well in the case of domain shift and can learn domain-invariant features while explaining the target labels with LIME implementation enabling trustworthy information processing and extraction to combat misinformation effectively.Comment: 28 pages,4 figure

Molecular Dynamics Study of the Solvation and Mechanical Properties of Elastin-like Peptides

Elastin is a disordered structural protein that imparts extensibility and elastic recoil to major arteries, lungs, and other elastic human tissues. Elastin-based peptides are biocompatible and able to self-assemble, making them suitable for biomimetic materials. Recent studies have begun to uncover the role of entropic effects, including the hydrophobic effect and conformational entropy, in the structural ensemble of elastin-like peptides. In this study, we use atomistic molecular dynamics simulations of peptides based on the hydrophobic domains of elastin to investigate their solvation and mechanical properties. The modulus of elastin-like domains obtained from equilibrium fluctuations is commensurate with elastic measurements from simulations as they are pulled to full extension and subsequently allowed to collapse. Our findings indicate that the hydrophobic effect is a significant driving force for elastic recoil, and suggest that the isolated hydrophobic domains are not responsible for the low resilience of elastin-based materials.M.Sc

Identification of priority genes involved in ADHD using multiple system biology approach and establishment of Asiatic acid as a natural inhibitor against GRIN2B receptor

Background: Network biology approaches have emerged as a promising tool to study disease mechanisms and explain comorbidities. Network biology approaches can be applied to integrate the complex neural networks that can help in understanding the molecular mechanisms of neurodevelopmental disorders and hence provide an insight into the diagnosis and treatment of these disorders. Aim: To identify priority genes involved in ADHD through multiple system biology approach and its subsequent treatment through molecular interaction studies. Methodology: In the present study, genes related to the neurodevelopmental disorders associated with ADHD were identified. STRING plugin on cytoscape was used to construct network and identify the hub genes. Further, expression, mutational, and regulatory analysis of the identified priority genes was done to evaluate its expression in brain. Computational drug designing approaches were further applied to identify the natural drug that can target the identified priority gene for the treatment of neurodevelopmental disorders. Objective: The present study is an attempt to identify the priority genes and thereby explain the molecular mechanism of neurodevelopmental disorders using computational network biology approaches in integration with other in-silico tools. Result: Our study concludes that GRIN2B can be a potential target in the mechanism of different neurodevelopmental disorders. The docking of GRIN2B receptor with neuroprotectant phytochemicals revealed that Asiatic acid, a naturally occurring pentacyclic triterpenoid, extracted from Centella asiatica can be used as a potential phytocompound for the treatment of Neurodevelopmental Disorders. Conclusion: Asiatic acid can be used as a therapeutic agent against GRIN2B receptor for treatment of ADHD

One-Pot Sequential Alkynylation and Cycloaddition: Regioselective Construction and Biological Evaluation of Novel Benzoxazole–Triazole Derivatives

Individually, benzoxazole and triazole moieties are of significant biological interest owing to their importance in drugs and pharmaceuticals. To assess their combined biological impact when woven into one molecule, we designed a novel, regioselective, multicomponent, one-pot (MCOP) approach for the construction of benzoxazole-linked triazoles. The synthesis has been achieved in two sequential steps involving copper-catalyzed alkynylation of benzoxazole followed by a 1,3-dipolar cycloaddition reaction. By combination of these two bioactive units into one core, a series of new benzoxazole-triazole scaffolds has been synthesized and subjected to in vitro antibacterial and anticancer evaluation. Tests against clinical isolates of <i>Staphylococcus aureus</i> and <i>Escherichia coli</i> showed potent Gram-negative activity for compounds <b>4</b>{<i>1,1,1</i>}, <b>4</b>{<i>1,1,4</i>}, and <b>4</b>{<i>1,2,1</i>}. The cytotoxicity of the synthesized library was determined against three cancer cell lines: HeLa, SKBr3, and Hep G2. Compound <b>4</b>{<i>2,2,2</i>} showed significant cytotoxicity against all the cell lines. These preliminary bioassay evaluations strongly suggest the promise and scope of these novel molecules as therapeutic agents in medical science

Prospects of Nanostructure Materials and Their Composites as Antimicrobial Agents

Nanostructured materials (NSMs) have increasingly been used as a substitute for antibiotics and additives in various products to impart microbicidal effect. In particular, use of silver nanoparticles (AgNPs) has garnered huge researchers' attention as potent bactericidal agent due to the inherent antimicrobial property of the silver metal. Moreover, other nanomaterials (carbon nanotubes, fullerenes, graphene, chitosan, etc.) have also been studied for their antimicrobial effects in order ensure their application in widespread domains. The present review exclusively emphasizes on materials that possess antimicrobial activity in nanoscale range and describes their various modes of antimicrobial action. It also entails broad classification of NSMs along with their application in various fields. For instance, use of AgNPs in consumer products, gold nanoparticles (AuNPs) in drug delivery. Likewise, use of zinc oxide nanoparticles (ZnO-NPs) and titanium dioxide nanoparticles (TiO2-NPs) as additives in consumer merchandises and nanoscale chitosan (NCH) in medical products and wastewater treatment. Furthermore, this review briefly discusses the current scenario of antimicrobial nanostructured materials (aNSMs), limitations of current research and their future prospects. To put various perceptive insights on the recent advancements of such antimicrobials, an extended table is incorporated, which describes effect of NSMs of different dimensions on test microorganisms along with their potential widespread applications