Nonpharmacological Management of Cancer-Related Cachexia: A Systematic Review.

Objectives: Cancer-related cachexia affects approximately 50% to 80% of cancer patients and contributes significantly to cancer-related mortality, accounting for 20% of deaths. This multifactorial syndrome is characterized by systemic inflammation, anorexia, and elevated energy expenditure, leading to severe weight loss and muscle wasting. Understanding the underlying mechanisms is critical for developing effective interventions.

Preparation, structural changes and functional properties of the covalent complexes of almond protein and phloretin.

Proteins and polyphenols exhibit distinct biological activities and functional properties. A comprehensive investigation into the formation mechanisms, structures, and functional properties of protein-polyphenol complexes will deepen our understanding of their interactions and establish a theoretical foundation and technical support for development of novel functional foods and pharmaceutical products. The almond protein-phloretin (AP-PHL) covalent complex was synthesized through the covalent binding of hydroxyl radicals to phloretin (PHL), utilizing almond protein (AP) as the raw material.

New insights into influencing the extraction efficiency of tigernut oil: Impact of heat on oil absorption and enzymatic hydrolysis of tigernut starch in a starch-protein-oil model system.

Tigernut is a potential source of valuable edible oil; however, current oil extraction techniques are inefficient. We assessed high temperature-induced variations in oil absorption and enzymatic hydrolysis of tigernut starch (TS) in the presence of protein to explore the intrinsic reasons for the low oil extraction from tigernut. The results showed that, due to high temperature and the presence of protein, an increase in the volume mean diameters and agglomeration of TS granules occurred.

A review of RNA nanoparticles for drug/gene/protein delivery in advanced therapies: Current state and future prospects.

Nanotechnology involves the utilization of materials with exceptional properties at the nanoscale. Over the past few years, nanotechnologies have demonstrated significant potential in improving human health, particularly in medical treatments. The self-assembly characteristic of RNA is a highly effective method for designing and constructing nanostructures using a combination of biological, chemical, and physical techniques from different fields.

A novel super-resolution STED microscopy analysis approach to observe spatial MCU and MICU1 distribution dynamics in cells.

The uptake of Ca by mitochondria is an important and tightly controlled process in various tissues. Even small changes in the key proteins involved in this process can lead to significant cellular dysfunction and, ultimately, cell death. In this study, we used stimulated emission depletion (STED) microscopy and developed an unbiased approach to monitor the sub-mitochondrial distribution and dynamics of the mitochondrial calcium uniporter (MCU) and mitochondrial calcium uptake 1 (MICU1) under resting and stimulated conditions.

Systematic review and meta-analysis of the treatment of hypernatremia in adult hospitalized patients: impact on mortality, morbidity, and treatment-related side effects.

Background: Hypernatremia is relatively common in acutely ill patients and associated with mortality. Guidelines recommend a slow rate of correction (≤ 0.5 mmol/L per hour).

Unveiling per- and polyfluoroalkyl substances contamination in e-cigarette refill liquids: A comprehensive analytical assessment.

A robust analytical method was developed for the determination of per- and polyfluoroalkyl substances (PFAS) in e-cigarette refill liquids using solid-phase extraction (SPE) with weak anion-exchange sorbent, followed by detection with high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS). The design of experiment approach was employed to optimize sample preparation, leading to the validation of the method with limits of detection for PFAS ranging from 0.24 to 1.

How does age impact understanding of epistemic adverbs in health communication?

Objective: Not much is known about how one's understanding of words may differ with age. Here we explore how epistemic adverbs - as used in health communication to indicate degrees of uncertainty and risk - are understood by older and younger monolingual speakers of Australian English.

Methods: We used an online dissimilarity rating task with sentence pairs presented as first and second doctor opinions which differed only with respect to the embedded epistemic adverbs (e.

Optimal selection of machine learning algorithms for ciprofloxacin prediction based on conventional water quality indicators.

The long-term presence of antibiotics in the aquatic environment will affect ecology and human health. Techniques for determining antibiotics are often time-consuming, labor-intensive and costly, and it is desirable to seek new methods to achieve rapid prediction of antibiotics. Many scholars have shown the effectiveness of machine learning in water quality prediction, however, its effectiveness in predicting antibiotic concentrations in the aquatic environment remains inconclusive.

Climate-adaptive optimal water resources management: A multi-sectoral approach for the Munneru river basin, India.

Climate change profoundly affects water resource allocation by disrupting the availability, distribution, and quality of water across various regions. Optimal allocation of water resources represents a comprehensive strategy for water resource management by addressing the intricate connections between water allocation systems and their repercussions on the environment, society, and economy. In this study, an Optimal Water Resources Management (OWRM) framework was developed, focusing on the optimal allocation of water resources and crop planting structures across various sectors.

Emergy-based valuation of glacier ecosystem services: A case from the Tibetan Plateau.

Glaciers provide multiple ecosystem services (ES) to human society. Due to the continued global warming, the valuation of glacier ES is of urgent importance because this knowledge can support the protection of glaciers. However, a systematic valuation of glacier ES is still lacking, particularly from the perspective of ES contributors.

Optimizing a link-based travel incentive scheme integrating personal carbon trading for low-carbon commuting.

The pressing need to reduce greenhouse gas emissions and optimize traffic demand underlines the importance of effective travel demand management. Previous studies have explored budget-based and aggregated incentive programs, which diminish a heavy financial burden on governments and tend to be limited in contributing to effective behavior change in practice due to budget issues. This study proposes a personal carbon trading travel incentive (PCTTI) mechanism, to encourage private car commuters using low-carbon travel routes.

Intellectual capital, environment-related absorptive capacity and environmental performance: Firm-level evidence from China's E&E sector.

Much of the existing literature on environmental performance has focused on human capital and intangible assets such as environmental policies and strategies, the role of intellectual capital has largely been overlooked. This study aims to investigate the impact of intellectual capital on environmental performance at the firm level, specifically in the electrical and electronics (E&E) sector in China. By considering human, relational, and structural capital as integral elements of intellectual capital, we assess their direct influence on environmental performance and explore how these components interact with other factors in driving environmental outcomes.

IFN alpha signaling drives hematopoietic stem cells malfunction under acute inflammation.

Inflammation stimulation regulates the activity of hematopoietic stem cells (HSCs) through direct-sensing and cytokine-mediation. It is known that HSCs directly sense lipopolysaccharide (LPS), a classical infection-related inflammatory signal, via toll like receptor 4 (TLR4) and subsequently become active. However, the mechanism underlying the activity change of HSCs induced by LPS remains incompletely disclosed.

Constructing atomically dispersed Ni-Mn catalysts for electrochemical CO reduction over the wide potential window.

Single-atom catalysts (SACs), known for their high atomic utilization efficiency, are highly attractive for electrochemical CO conversion. Nevertheless, it is struggling to use a single active site to overcome the linear scaling relationship among intermediates. Herein, an isolated diatomic Ni-Mn dual-sites catalyst was anchored on nitrogenated carbon, which exhibits remarkable electrocatalytic performance towards CO reduction.

Structure-activity relationship of small organic molecule functionalized Bi-based heterogeneous catalysts for electrocatalytic reduction of CO to formate.

Ligand engineering has proven to be an effective strategy for tuning and controlling the microenvironment of coordinated metal centers, highlighting the critical bridge between the activity and structural features of catalysts during electrocatalytic CO reduction reactions (eCORR). However, the limited availability of diverse organic ligands has hindered the development of novel high-performing electrocatalysts. In contrast, small organic molecules have been widely used in the fabrication of metal complexes due to their well-defined functionalities, low cost, and easy accessibility.

Water-soluble carboxymethyl chitosan and rhamnolipids promote the remediation of Cd-contaminated soil by mediating the growth of Hylotelephium spectabile and regulating the rhizospheric ecological environment.

The application of biodegradable chelating agents in phytoremediation is a promising approach. This study aimed to investigate the effects and roles of underlying mechanisms of water-soluble carboxymethyl chitosan (WSCC) and rhamnolipids (RLs) on the remediation of Cd-contaminated soil by Hylotelephium spectabile. WSCC and RLs mediated the growth of H.

Development of a bioreactor with an integrated non-dispersive infrared CO sensor for rapid and sensitive detection of Cr(VI) toxicity in water.

Whole-cell bioreactors equipped with external physico-chemical sensors have gained attention for real-time toxicity monitoring. However, deploying these systems in practice is challenging due to potential interference from unknown wastewater constituents with liquid-contacted sensors. In this study, a novel approach using a bioreactor integrated with a non-dispersive infrared CO₂ sensor for both toxicity detection and real-time monitoring of microbial growth phases was successfully demonstrated.

Homopregnane-type ferrocene-steroid conjugates exhibit immunomodulatory activity.

Numerous compounds with useful biological activities were previously prepared by tethering ferrocene to natural product scaffolds. Some conjugates of ferrocene and steroids in particular were demonstrated to act as both potent and selective antiproliferative agents. Motivated by a lack of structural diversity in the pregnane series of conjugates, we performed chemical modifications of several naturally occurring progestogens, their biosynthetic precursors and chemically related derivatives so as to obtain conjugates 1-8, in which the steroid skeleton and ferrocene core are linked by the steroid sidechain.

Solution processable triarylamine-based polyamide for electrochromic supercapacitors and smart displays with energy reuse.

Electrochromic (EC) materials based on ion insertion/desertion mechanisms provide a possibility for energy storage. Solution-processable energy storage EC polyamides have great potential for use in smart displays and EC supercapacitors. A suitable monomer structure design is particularly important for enhancing the electrochemical properties of polyamides.

Estimation of Central Aortic Pressure Waveforms by Combination of a Meta-Learning Neural Network and a Physics-Driven Method.

The accurate non-invasive detection and estimation of central aortic pressure waveforms (CAPW) are crucial for reliable treatments of cardiovascular system diseases. But the accuracy and practicality of current estimation methods need to be improved. Our study combines a meta-learning neural network and a physics-driven method to accurately estimate CAPW based on personalized physiological indicators.

Accelerating Plasmonic Hydrogen Sensors for Inert Gas Environments by Transformer-Based Deep Learning.

Rapidly detecting hydrogen leaks is critical for the safe large-scale implementation of hydrogen technologies. However, to date, no technically viable sensor solution exists that meets the corresponding response time targets under technically relevant conditions. Here, we demonstrate how a tailored long short-term transformer ensemble model for accelerated sensing (LEMAS) speeds up the response of an optical plasmonic hydrogen sensor by up to a factor of 40 and eliminates its intrinsic pressure dependence in an environment emulating the inert gas encapsulation of large-scale hydrogen installations by accurately predicting its response value to a hydrogen concentration change before it is physically reached by the sensor hardware.

Continuous Polarizability-Based Separation of Lithium Iron Phosphate and Graphite Using a Dielectrophoretic Particle Separator.

The recovery of valuable materials from spent lithium-ion batteries (LIBs) has experienced increasing demand in recent years. Current recycling technologies are typically energy-intensive and are often plagued by high operation costs, low processing efficiency, and environmental pollution concerns. In this study, an efficient and environmentally friendly dielectrophoresis (DEP)-based approach is proposed to separate the main components of "black mass" mixtures from LIBs, specifically lithium iron phosphate (LFP) and graphite, based on their polarizability differences.