Role of Endocrine-Disrupting Chemicals in the Pathogenesis of Non-Alcoholic Fatty Liver Disease: A Comprehensive Review

Non-alcoholic fatty liver disease (NAFLD) is considered the most common liver disorder, affecting around 25% of the population worldwide. It is a complex disease spectrum, closely linked with other conditions such as obesity, insulin resistance, type 2 diabetes mellitus, and metabolic syndrome, which may increase liver-related mortality. In light of this, numerous efforts have been carried out in recent years in order to clarify its pathogenesis and create new prevention strategies. Currently, the essential role of environmental pollutants in NAFLD development is recognized. Particularly, endocrine-disrupting chemicals (EDCs) have a notable influence. EDCs can be classified as natural (phytoestrogens, genistein, and coumestrol) or synthetic, and the latter ones can be further subdivided into industrial (dioxins, polychlorinated biphenyls, and alkylphenols), agricultural (pesticides, insecticides, herbicides, and fungicides), residential (phthalates, polybrominated biphenyls, and bisphenol A), and pharmaceutical (parabens). Several experimental models have proposed a mechanism involving this group of substances with the disruption of hepatic metabolism, which promotes NAFLD. These include an imbalance between lipid influx/efflux in the liver, mitochondrial dysfunction, liver inflammation, and epigenetic reprogramming. It can be concluded that exposure to EDCs might play a crucial role in NAFLD initiation and evolution. However, further investigations supporting these effects in humans are required.     

Adsorptive Removal of Manganese Ions from Polluted Aqueous Media by Glauconite Clay-Functionalized Chitosan Nanocomposites

The presence of Mn(II) in water exceeding the permitted concentration limits declared by the World Health Organization (WHO) influences individuals, animals, and the ecosystem negatively. Therefore, there is a necessity for an efficient material to eliminate this potentially toxic element from wastewater. We herein focused on the adsorptive removal of Mn(II) ions from polluted aqueous media using natural Egyptian glauconite clay (G) and its nanocomposites with modified chitosan (CS). We applied modified chitosan with glutaraldehyde (GL), ethylenediaminetetraacetic acid (EDTA), sodium dodecyl sulfate (SDS), and cetyltrimethyl ammonium bromide (CTAB). The utilized nanocomposites were referred to as GL-CS/G, EDTA-GL-CS/G, SDS-CS/G, and CTAB-CS/G, respectively. The point of zero charge values of the materials were estimated. The adsorption properties of the G clay and its nanocomposites toward the removal of Mn(II) ions from polluted aqueous media as well as the adsorption mechanism were explored using a batch technique. The glauconite (G) and its nanocomposites: GL-CS/G, CTAB-CS/G, EDTA-GL-CS/G, and SDS-CS/G, exhibited maximum adsorption capacity values of 3.60, 24.0, 26.0, 27.0, and 27.9 mg g^?1, respectively. The adsorption results fitted well the Langmuir isotherm and pseudo-second-order kinetic models. The estimated thermodynamic parameters: ΔH° (from 1.03 to 5.55 kJ/mol) and ΔG° (from ? 14.5 to ? 18.8 kJ/mol), indicated that Mn(II) ion adsorption process was endothermic, spontaneous, and physisorption controlled. Furthermore, the obtained adsorption results are encouraging and revealing a great potentiality for using the modified adsorbents as accessible adsorbents for Mn(II) ion removal from polluted aqueous solutions, depending on their reusability, high stability, and good adsorption capacities.

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Agro-Waste Generated Pd/CAP-Ash Catalyzed Ligand-Free Approach for Suzuki–Miyaura Coupling Reaction

Catalysis Letters - We converted agro-waste Custard Apple Peels (CAP) to ash via thermal treatment, on which Pd(OAc)2 was immobilized easily that produced a low-cost, highly efficient Pd/CAP-ash...     

National-scale implementation of mandatory freshwater farm plans: a mechanism to deliver water quality improvement in productive catchments in New Zealand?

Nutrient Cycling in Agroecosystems - Reducing agriculturally derived diffuse contaminant losses (via non-point sources) from land to water has proven difficult for decades. Owing to the diversity...     

Impact of defects on the decomposition of chemical warfare agent simulants in Zr-based metal organic frameworks

Metal organic frameworks (MOFs) containing zirconium secondary building units (SBUs) in UiO-67 and related MOFs, are highly active for neutralizing both the chemical warfare agents and simulants, such as dimethyl methylphosphonate (DMMP). However, two recent publications gave conflicting reports of DMMP reaction with UiO-67 under ultra high vacuum (UHV) conditions, with one reporting chemisorption and reaction (Wang et al., J Phys Chem C, 2017, 121, 11261–11272) and the other reporting only physisorption and reversible desorption (Ruffley et al., J Phys Chem C, 2019, 123, 19748–19758) from very similar temperature programmed desorption experiments. We show that the discrepancy between these experiments may be explained by different levels of missing linker defects in the UiO-67 samples. We present density functional theory calculations showing that SBU sites having two-adjacent missing linkers exhibit reaction barriers that are about 30 kJ/mol lower than SBU sites having a single missing linker. We also show that topology of the undercoordinated sites plays an important role in the reaction barrier under UHV conditions.     

Tests of a Two-Stage Core at the KV-1 Test Facility: Physical Aspects and Results

Atomic Energy - The physical aspects and main results of reactor tests of a two-stage core consisting of fresh fuel assemblies and a significant number of fuel assemblies from the previous core,...     

Multicriteria Collision Risk Ranking of Aircraft by Data from an Onboard Radar Station

Journal of Communications Technology and Electronics - An option of multicriteria collision risk ranking of aircraft by data from an onboard radar station (OBRS) is proposed. This method can be...     

Performance Analysis of Learning Rate Parameter on Prediction of Signal Power Loss for Network Optimization and Better Generalization

Wireless Personal Communications - This research work explores the neural network learning capabilities by using a multi-layer perceptron artificial neural network to predict signal power loss by...