An Emerging Cross-Species Marker for Organismal Health: Tryptophan-Kynurenine Pathway

Tryptophan (TRP) is an essential dietary amino acid that, unless otherwise committed to protein synthesis, undergoes metabolism via the Tryptophan-Kynurenine (TRP-KYN) pathway in vertebrate organisms. TRP and its metabolites have key roles in diverse physiological processes including cell growth and maintenance, immunity, disease states and the coordination of adaptive responses to environmental and dietary cues. Changes in TRP metabolism can alter the availability of TRP for protein and serotonin biosynthesis as well as alter levels of the immune-active KYN pathway metabolites. There is now considerable evidence which has shown that the TRP-KYN pathway can be influenced by various stressors including glucocorticoids (marker of chronic stress), infection, inflammation and oxidative stress, and environmental toxicants. While there is little known regarding the role of TRP metabolism following exposure to environmental contaminants, there is evidence of linkages between chemically induced metabolic perturbations and altered TRP enzymes and KYN metabolites. Moreover, the TRP-KYN pathway is conserved across vertebrate species and can be influenced by exposure to xenobiotics, therefore, understanding how this pathway is regulated may have broader implications for environmental and wildlife toxicology. The goal of this narrative review is to (1) identify key pathways affecting Trp-Kyn metabolism in vertebrates and (2) highlight consequences of altered tryptophan metabolism in mammals, birds, amphibians, and fish. We discuss current literature available across species, highlight gaps in the current state of knowledge, and further postulate that the kynurenine to tryptophan ratio can be used as a novel biomarker for assessing organismal and, more broadly, ecosystem health.     

Robust control of water quality in intensive aquaculture using multi-variable quantitative feedback theory: From an Indian context

This paper addresses the problem of controlling turbidity, dissolved oxygen, ammonium-ion concentration, and water-temperature to maintain the desired water quality in an intensive aquaculture plant. The research is carried out to fit into the present scenario of intensive aquaculture in India. The plant model along with uncertain parameters are derived using physical laws and the data acquired from an aquaculture pond in Assam, India. A pre-compensated multi-variable quantitative feedback theory (QFT)-based fully populated robust matrix controller is proposed to mitigate the control challenge. A novel method is used to design the pre-compensator to enhance the diagonal dominance of plant transfer function matrix. The desired robust stability, reference tracking, and sensitivity specifications are fulfilled by the proposed QFT-based robust controller despite the parametric uncertainty. The effectiveness of the proposed method is validated through numerical simulation. A comparative study against a $H_{\infty }$ controller shows that the proposed controller strategy gives a satisfactory performance compared to it.     

Mechanical characterization of jute-basalt hybrid composites with graphene as nanofiller

Natural fibre composites, due to their biodegradable and eco friendly nature, are being explored for potential application in wide areas. But their strengths need to be enhanced. Hybridization of the natural fibres with incorporation of nanofillers helps to tailor the properties of nanofillers, and individual fibers and enhance the properties of resultant composite. The present work aims to explore the mechanical propertis of jute-basalt hybrid composites by incorporating graphene nanofillers of varying concentrations. Basalt, jute and jute-basalt hybrid composites with varying concentrations of graphene (0 wt%, 0.2 wt%, 0.4 wt%, 0.6 wt%, 1 wt%) are prepared. Effect of hybridization of different fibers and influence of graphene on mechanical properties are analyzed. The effect of nature of top and bottom laminates on mechanical properties is also observed. Maximum improvement in tensile strength, flexural strength and hardness is found to be 13 %, 29 % and 55 %, respectively, with hybrid composite containing 1 wt.% graphene compared to hybrid composite without graphene. Impact strength is found to be highest for hybrid composite containing 0.4 wt.% graphene with 17 % increase compared to hybrid composite without graphene.

     

Glass transition,topology, and elastic models of Se-based glasses

Features intrinsic to disorder and network aspects are ubiquitous in structural glasses. Among this important class of materials, chalcogenide glasses are special—they are built of short-range covalent forces, making them simpler than silicate glasses that possess mixed ionic and covalent forces. Selenium-based glasses also display complex elastic phase transitions that have been described from various models, including mean-field approaches to molecular simulations. These point to the presence of two sharply defined elastic phase transitions, a rigidity and stress transition that are non-mean-field in character, and separate the three distinct topological phases of flexible, isostatically rigid, and stressed-rigid. This article reviews the physics of these glassy networks. The elastic phases and glass transition temperature are explained on a molecular level in terms of topological constraint theory (TCT), connectivity, and the open degrees of freedom. The broader aspects of TCT in relation to phase change materials, high-k dielectrics, and cements are also commented upon.