β-cyclodextrin polymer composites for the removal of pharmaceutical substances, endocrine disruptor chemicals, and dyes from aqueous solution- A review of recent trends.

Cyclodextrin (CD) and its derivatives are receiving attention as a new-generation adsorbent for water pollution treatment due to their external hydrophilic and internal hydrophobic properties. Among types of CD, β-Cyclodextrin (βCD) has been a material of choice with a proven track record for a range of utilities in distinct domains, owing to its unique cage-like structural conformations and inclusion complex-forming ability, especially to mitigate emerging contaminants (ECs). This article outlines βCD composites in developing approaches of their melds and composites for purposes such as membranes for removal of the ECs in aqueous setups have been explored with emphasis on recent trends.

Biosynthesis of selenium nanoparticles using cell-free extract of Xenorhabdus cabanillasii GU480990 and their potential mosquito larvicidal properties against yellow fever mosquito Aedes aegypti.

Nanomaterials are successful due to their numerous applications in various domains such as cancer treatment, environmental applications, drug and gene delivery. Selenium is a metalloid element with broad biological activities and low toxicity especially at the nanoscale. Several studies have shown that nanoparticles synthesized from microbial and plant extracts are effective against important pests and pathogens.

Investigation of pre-treatment techniques on spent substrate of Pleurotus ostreatus for enhanced biobutanol production using Clostridium acetobutylicum MTCC 11274.

Addressing global energy demand, researchers sought eco-friendly biobutanol production from lignocellulosic waste biomass. In the present research work, five different pre-treatment methods viz., Microwave, Ultrasound, Alkali, Acid, and Hybrid, were investigated to explore its biobutanol production potential by utilizing Pleurotus ostreatus spent as substrate.

Interfacial coupling of CuFeO induced hotspots over self-assembled g-CN nanosheets as an efficient photocatalytic bacterial disinfectant.

Most bacterial disinfectants contain high levels of extremely toxic and environmental hazardous chemicals, which pose a significant threat to the ecosystem. Semiconductor photocatalysis exhibits attractive prospects as an emerging greener technology for waste water disinfection. However, the fast recombination of charge carriers limits its practical application.

Development of chitosan-based cerium and titanium oxide loaded polycaprolactone for cutaneous wound healing and antibacterial applications.

Cerium dioxide (CeO) based nanomaterials have emerged as promising dermal equivalents, promoting fibroblast infiltration and tissues regeneration. To enhance the antibacterial and wound healing activity, herein chitosan (CS)-CeO combined nano titanium dioxide (TiO) complex loaded polycaprolactone (PCL) nanohybrid (CS-CeO/TiO/PCL) scaffolds were prepared through casting method. The nanohybrid scaffolds' physiochemical, morphological, mechanical, and biological properties were evaluated using advanced analytical techniques.

A Deep Learning Framework with an Intermediate Layer Using the Swarm Intelligence Optimizer for Diagnosing Oral Squamous Cell Carcinoma.

One of the most prevalent cancers is oral squamous cell carcinoma, and preventing mortality from this disease primarily depends on early detection. Clinicians will greatly benefit from automated diagnostic techniques that analyze a patient's histopathology images to identify abnormal oral lesions. A deep learning framework was designed with an intermediate layer between feature extraction layers and classification layers for classifying the histopathological images into two categories, namely, normal and oral squamous cell carcinoma.

Feasibility assessment of a stepped solar still integrated with hexagram fin: an experimental and numerical approach toward sustainability.

Effective utilization and conservation of freshwater is a global concern due to the rapid population growth and industrial usage. To address this challenge, various approaches have been developed and implemented to convert brackish water into freshwater and meet the global water demand. This study introduces hexagram-shaped aluminum fins attached to a powder-coated basin to improve the freshwater production rate of stepped solar still.

Exploring the origins and cleanup of mercury contamination: a comprehensive review.

Mercury is a global pollutant that poses significant risks to human health and the environment. Natural sources of mercury include volcanic eruptions, while anthropogenic sources include industrial processes, artisanal and small-scale gold mining, and fossil fuel combustion. Contamination can arise through various pathways, such as atmospheric deposition, water and soil contamination, bioaccumulation, and biomagnification in food chains.

Unleashing the room temperature boronization: Blooming of Ni-ZIF nanobuds for efficient photo/electro catalysis of water.

Water splitting provides an environmental-friendly and sustainable approach for generating hydrogen fuel. The inherent energetic barrier in two-core half reactions such as the Hydrogen Evolution Reaction (HER) and Oxygen Evolution Reaction (OER) leads to undesired increased overpotential and constrained reaction kinetics. These challenges pose significant challenges that demand innovative solutions to overcome.

Phytochemical Analysis and Antioxidant Activity of Centella Asiatica Extracts: An Experimental and Theoretical Investigation of Flavonoids.

Centella asiatica (CA) is a medicinal plant widely used in the East, with many of its phytoconstituents remaining unexplored. In this study, compounds were extracted and identified from to determine its medicinal properties. Phytochemical screening was conducted on shoot, callus, and cell suspension extracts, revealing the presence of tannins, flavonoids, terpenoids, saponins, and steroids in all three cultures, with no alkaloids detected.

Exploration and Enhancement of Classifiers in the Detection of Lung Cancer from Histopathological Images.

Lung cancer is a prevalent malignancy that impacts individuals of all genders and is often diagnosed late due to delayed symptoms. To catch it early, researchers are developing algorithms to study lung cancer images. The primary objective of this work is to propose a novel approach for the detection of lung cancer using histopathological images.

Thermo-kinetic behaviour of green synthesized nanomaterial enhanced organic phase change material: Model fitting approach.

Metal, carbon and conducting polymer nanoparticles are blended with organic phase change materials (PCMs) to enhance the thermal conductivity, heat storage ability, thermal stability and optical property. However, the existing nanoparticle are expensive and need to be handle with high caution during operation as well during disposal owing to its toxicity. Subsequently handling of solid waste and the disposal of organic PCM after longevity usage are of utmost concern and are less exposed.

Enhancement of Classifier Performance Using Swarm Intelligence in Detection of Diabetes from Pancreatic Microarray Gene Data.

In this study, we focused on using microarray gene data from pancreatic sources to detect diabetes mellitus. Dimensionality reduction (DR) techniques were used to reduce the dimensionally high microarray gene data. DR methods like the Bessel function, Discrete Cosine Transform (DCT), Least Squares Linear Regression (LSLR), and Artificial Algae Algorithm (AAA) are used.

Split injection strategy control map development through prediction-based calibration approach to improve the biodiesel-fuelled diesel engine characteristics.

Karanja oil blended with diesel acts as a good alternative for a CI engine due to its low emission and high oxygen content as compared to pure diesel which leads to the non-toxic and biodegradable nature of the fuel. The objective of this project is to enhance the performance and emission characteristics of a diesel engine that runs on biofuel by accurately calibrating its fuel injector control parameters. To achieve this goal, the project focuses on creating optimal split injector control maps using a novel global model-based calibration approach that considers the entire range of engine speed-load conditions.

Learned-SBL-GAMP based hybrid precoders/combiners in millimeter wave massive MIMO systems.

In Millimeter-Wave (mm-Wave) massive Multiple-Input Multiple-Output (MIMO) systems, hybrid precoders/combiners must be designed to improve antenna gain and reduce hardware complexity. Sparse Bayesian learning via Expectation Maximization (SBL-EM) algorithm is not practically feasible for high signal dimensions because estimating sparse signals and designing optimal hybrid precoders/combiners using SBL-EM still provide high computational complexity for higher signal dimensions. To overcome the issues of high computational complexity along with making it suitable for larger data sets, in this paper, we propose Learned-Sparse Bayesian Learning with Generalized Approximate Message Passing algorithm (L-SBL-GAMP) algorithm for designing optimal hybrid precoders/combiners suitable for mmWave Massive MIMO systems.

Modulating the Effect of β-Sitosterol Conjugated with Magnetic Nanocarriers to Inhibit EGFR and Met Receptor Cross Talk.

The cross-talk between the EGFR (Epidermal Growth Factor Receptor) and MET (Hepatocyte Growth Factor Receptor) poses a significant challenge in the field of molecular signaling. Their intricate interplay leads to dysregulation and contributes to cancer progression and therapeutic resistance. β-Sitosterol (BS), a plant sterol with promising anticancer properties, shows increased research on its potential as a chemopreventive agent.

Detection of Diabetes through Microarray Genes with Enhancement of Classifiers Performance.

Diabetes is a life-threatening, non-communicable disease. Diabetes mellitus is a prevalent chronic disease with a significant global impact. The timely detection of diabetes in patients is necessary for an effective treatment.

Evaluation and Exploration of Machine Learning and Convolutional Neural Network Classifiers in Detection of Lung Cancer from Microarray Gene-A Paradigm Shift.

Microarray gene expression-based detection and classification of medical conditions have been prominent in research studies over the past few decades. However, extracting relevant data from the high-volume microarray gene expression with inherent nonlinearity and inseparable noise components raises significant challenges during data classification and disease detection. The dataset used for the research is the Lung Harvard 2 Dataset (LH2) which consists of 150 Adenocarcinoma subjects and 31 Mesothelioma subjects.

Extraction, characterization and biological activity of Galactomannan rich endosperm of Borassus flabellifer (Linn.) suitable for biofabrication of tissue scaffolds.

The study deals with the isolation, purification and characterization of galactomannan from the endosperm of Borassus labellifer (Linn.) to be used for biomaterial fabrication in tissue engineering (TE) applications. The isolated Borassus flabellifer (Linn.

Adenosine/β-Cyclodextrin-Based Metal-Organic Frameworks as a Potential Material for Cancer Therapy.

Recently, researchers have employed metal-organic frameworks (MOFs) for loading pharmaceutically important substances. MOFs are a novel class of porous class of materials formed by the self-assembly of organic ligands and metal ions, creating a network structure. The current investigation effectively achieves the loading of adenosine (ADN) into a metal-organic framework based on cyclodextrin (CD) using a solvent diffusion method.

Enhancement of Antioxidant Properties of the Medicinal Plant, Costus Pictus by Optimization of its Drying and Extraction Criteria.

Antioxidants act as major protective factors against different infections and diseases. The search for natural antioxidants has gained significant momentum due to its associated health benefits. It prompted the investigation of the antioxidant properties of widely recognized medicinal plants, considering their prominent role in conventional medicine.

Synergistic visible light assisted photocatalytic degradation of p-chlorophenol and rifampicin from aqueous solution using a novel g-CN quantum dots incorporated α-MoO nanohybrid - Mechanism, pathway and toxicity studies.

In this work, a simple g-CN quantum dots enriched MoO nanohybrid was formulated for the synergistic photocatalytic degradation of an industrially active organic pollutant, p-chlorophenol (PCP) and a widely prescribed antibiotic, rifampicin (RIF). The nanohybrid was synthesised via a facile ultrasonic assisted hydrothermal method and characterized using various characterization analysis. The efficient Z-scheme charge transfer of the nanohybrid resulted in the elimination of 98% PCP and 89% RIF under visible light with a rate constant of 0.

Biopreservative technologies of food: an alternative to chemical preservation and recent developments.

Despite centuries of developing strategies to prevent food-associated illnesses, food safety remains a significant concern, even with multiple technological advancements. Consumers increasingly seek less processed and naturally preserved food options. One promising approach is food biopreservation, which uses natural antimicrobials found in food with a long history of safe consumption and can help reduce the reliance on chemically synthesized food preservatives.