Search Results (160)

Background: Environmental exposures, such as per- and polyfluoroalkyl substances (PFAS), in conjunction with social and behavioral factors, can significantly impact liver health. This research investigates the combined effects of PFAS (perfluorooctanoic acid (PFOA) and perfluorooctane sulfonate (PFOS), alcohol consumption, smoking, income, and education on liver function among the U.S. population, utilizing data from the 2017–2018 National Health and Nutrition Examination Survey (NHANES). Methods: PFAS concentrations in blood samples were analyzed using online solid-phase extraction combined with liquid chromatography–tandem mass spectrometry (LC-MS/MS), a highly sensitive and specific method for detecting levels of PFAS. Liver function was evaluated using biomarkers such as alanine aminotransferase (ALT), aspartate aminotransferase (AST), alkaline phosphatase (ALP), gamma-glutamyltransferase (GGT), total bilirubin, and the fatty liver index (FLI). Descriptive statistics and multivariable linear regression analyses were employed to assess the associations between exposures and liver outcomes. Bayesian Kernel Machine Regression (BKMR) was utilized to explore the nonlinear and interactive effects of these exposures. To determine the relative influence of each factor on liver health, Posterior Inclusion Probabilities (PIPs) were calculated. Results: Linear regression analyses indicated that income and education were inversely associated with several liver injury biomarkers, while alcohol use and smoking demonstrated stronger and more consistent associations. Bayesian Kernel Machine Regression (BKMR) further highlighted alcohol and smoking as the most influential predictors, particularly for GGT and total bilirubin, with posterior inclusion probabilities (PIPs) close to 1.0. In contrast, PFAS showed weaker associations. Regression coefficients were small and largely non-significant, and PIPs were comparatively lower across most liver outcomes. Notably, education had a higher PIP for ALT and GGT than PFAS, suggesting a more protective role in liver health. People with higher education levels tend to live healthier lifestyles, have better access to healthcare, and are generally more aware of health risks. These factors can all help reduce the risk of liver problems. Overall mixture effects demonstrated nonlinear trends, including U-shaped relationships for ALT and GGT, and inverse associations for AST, FLI, and ALP. Conclusion: These findings underscore the importance of considering both environmental and social–behavioral determinants in liver health. While PFAS exposures remain a long-term concern, modifiable lifestyle and structural factors, particularly alcohol, smoking, income, and education, exert more immediate and pronounced effects on hepatic biomarkers in the general population. Full article

In this work, hybrid membranes were fabricated by depositing polyvinyl chloride (PVC) fibers onto PET track-etched membranes (TeMs) using the electrospinning technique. The resulting structures exhibited enhanced hydrophobicity, with contact angles reaching 155°, making them suitable for applications in both water–oil mixture separation and membrane distillation processes involving low-level liquid radioactive waste (LLLRW), saline solutions, and natural water sources. The use of hybrids of TeMs and nanofiber membranes has significantly increased productivity compared to TeMs only, while maintaining a high degree of purification. Permeate obtained after MD of LLLRW and river water was analyzed by conductometry and the atomic emission spectroscopy (for Sr, Cs, Al, Mo, Co, Sb, Ca, Fe, Mg, K, and Na). The activity of radioisotopes (for ¹²⁴Sb, ⁶⁵Zn, ⁶⁰Co, ⁵⁷Co, ¹³⁷Cs, and ¹³⁴Cs) was evaluated by gamma-ray spectroscopy. In most cases, the degree of rejection was between 95 and 100% with a water flux of up to 17.3 kg/m²·h. These membranes were also tested in the separation of cetane–water emulsion with productivity up to 47.3 L/m²·min at vacuum pressure of 700 mbar and 15.2 L/m²·min at vacuum pressure of 900 mbar. Full article

In this paper, different poly((ethylene glycol)-(propylene glycol)) methacrylate (P(EGPG)MA) hydrogels were synthesized by gamma-radiation-induced polymerization and crosslinking from a monomer–bisolvent mixture using the following monomers: (ethylene glycol)₆ methacrylate (EG₆MA), ((ethylene glycol)₆-(propylene glycol)₃) methacrylate (EG₆PG₃MA), ((propylene glycol)₆-(ethylene glycol)₃) methacrylate (PG₆EG₃MA), and (propylene glycol)₅ methacrylate (PG₅MA), along with different water/ethanol compositions as the solvent. The monomer–bisolvent mixture was exposed to various radiation doses (5, 10, 15, 25, and 50 kGy). Considerable emphasis was placed on optimizing and tuning the reaction conditions necessary for the fabrication of methacrylic networks with pendant EGPG terminals. A further investigation was conducted on the effects of monomer composition, different preparation conditions, and radiation processing on thermal properties, microstructure, swelling behavior, and volume phase transition. Special attention was dedicated to PPG₆EG₃MA hydrogel, whose volume phase transition temperature is near physiological temperatures. This study identifies an optimal radiation dose and a water/ethanol solvent ratio for the synthesis of the radiation-induced hydrogels. Employing ionizing radiation within the sterilization dose range enables the simultaneous fabrication and sterilization of these hydrogels, offering an efficient production process. The findings provide new insights into the role of bisolvent composition on hydrogel formation and properties, and they present practical guidelines for optimizing hydrogel synthesis across a wide range of applications. Full article

Streamers are small, thin plasma channels that form the precursors of hot lightning leaders and that are associated with phenomena such as transient luminous events or terrestrial gamma-ray flashes. We provide an easily accessible audiovisual introduction for students and early researchers, serving as a supplement to traditional review papers. This overview contains an introduction to the collision-dominated motion of electrons in an ambient field and an ambient gas, including a discussion of cross-sections and friction force. Based on this, we will discuss electron avalanches before moving to streamers. Here, we will focus on the avalanche-to-streamer transition and present properties and different modeling approaches. Finally, we will discuss streamers in different gas mixtures as well as their relation to lightning and plasma chemistry. The viewer of the supplementary video will receive a first overview of streamer physics. Full article

At weaning, piglets deal with numerous changes and stressors, which can lead to reduced feed intake, digestive disturbances, and gut inflammation. In this context, there is a compelling need to develop new and innovative nutritional strategies aimed at restoring intestinal balance in piglets after weaning and controlling the weaning-associated intestinal inflammation. This study investigated the effect of a diet, including a synbiotic additive (a mix of grape seed and camelina meals as the prebiotic and a lactobacilli mixture as the probiotic) on intestinal inflammation in piglets after weaning. An acute inflammation was induced by the intraperitoneally challenge with Escherichia coli lipopolysaccharide (LPS). The experimental groups were as follows: Control group (piglets fed a conventional corn-soybean meal-based diet), LPS group (piglets fed the Control diet and challenged with 80 µg/b.w. of LPS), SYN group (piglets fed a basal diet, including 5% prebiotic mix and 0.1% probiotic mix, SYN diet), and SYN+LPS group (piglets fed the SYN diet and challenged with 80 µg/b.w. of LPS). Using genomic and proteomic techniques, genes and proteins related to intestinal inflammation were measured in both the jejunum and colon. The results showed that the LPS challenge induced an exacerbated inflammatory response in the jejunum and colon of piglets, inducing an overexpression of a large palette of inflammation-related mediators, including lactate dehydrogenase (LDH) activity, cytokines (e.g., interleukin (IL)—IL-1β, IL-6, tumor necrosis factor alpha—TNF-α), and chemokines (e.g., monokine induced by interferon-gamma—MIG, regulated on activation, normal T cell expressed and secreted—RANTES). All these effects are prevented by the SYN diet, which controls the amplitude of intestinal inflammation induced by the LPS challenge in piglets. Overall, these results suggested that piglets, after weaning, fed the synbiotic diet are less susceptible to the LPS challenge. This diet might be used as a nutritional strategy to alleviate intestinal inflammation in piglets after weaning. Full article

This study investigates the applicability of finite mixture models (FMMs) for accurately modeling yarn quality parameters in 28/1 Ne ring-spun polyester/viscose yarns, focusing on both yarn imperfections and mechanical properties. The research addresses the need for advanced statistical modeling techniques to better capture the inherent heterogeneity in textile production data. To this end, the Poisson mixture model is employed to represent count-based defects, such as thin places, thick places, and neps, while the gamma mixture model is used to model continuous variables, such as tenacity and elongation. Model parameters are estimated using the expectation–maximization (EM) algorithm, and model selection is guided by the Akaike and Bayesian information criteria (AIC and BIC). The results reveal that thin places are optimally modeled using a two-component Poisson mixture distribution, whereas thick places and neps require three components to reflect their variability. Similarly, a two-component gamma mixture distribution best describes the distributions of tenacity and elongation. These findings highlight the robustness of FMMs in capturing complex distributional patterns in yarn data, demonstrating their potential in enhancing quality assessment and control processes in the textile industry. Full article

As system complexity increases, accurately capturing true system reliability becomes increasingly challenging. Rather than relying on exact analytical solutions, it is often more practical to use approximations based on observed time-to-failure data. Finite mixture models provide a flexible framework for approximating arbitrary probability density functions and are well suited for reliability modelling. A critical factor in achieving accurate approximations is the choice of parameter estimation algorithm. The REBMIX&EM algorithm, implemented in the rebmix R package, generally performs well but struggles when components of the finite mixture model overlap. To address this issue, we revisit key steps of the REBMIX algorithm and propose improvements. With these improvements, we derive parameter estimators for finite mixture models based on three parametric families commonly applied in reliability analysis: lognormal, gamma, and Weibull. We conduct a comprehensive simulation study across four system configurations, using lognormal, gamma, and Weibull distributions with varying parameters as system component time-to-failure distributions. Performance is benchmarked against five widely used R packages for finite mixture modelling. The results confirm that our proposal improves both estimation accuracy and computational efficiency, consistently outperforming existing packages. We also demonstrate that finite mixture models can approximate analytical reliability solutions with fewer components than the actual number of system components. Our proposals are also validated using a practical example from Backblaze hard drive data. All improvements are included in the open-source rebmix R package, with complete source code provided to support the broader adoption of the R programming language in reliability analysis. Full article

T cells play a crucial role in the immune system by identifying and eliminating tumor cells. Malignant cancer cells can hijack mitochondria (MT) from nearby T cells, affecting their metabolism and weakening their immune functions. This phenomenon, observed through co-culture systems and fluorescent labeling, has been further explored with the development of the MERCI algorithm, which predicts T cell MT hijacking in cancer cells using single-cell RNA (scRNA) sequencing data. However, MERCI is limited by its reliance on a linear model and its inability to handle data sparsity. To address these challenges, we introduce MitoR, a computational algorithm using a Poisson–Gamma mixture model to predict T cell MT hijacking from tumor scRNA data. In performance comparisons, MitoR demonstrated improved performance compared to MERCI’s on gold-standard benchmark datasets scRNA-bench1 (top AUROC: 0.761, top accuracy: 0.769) and scRNA-bench2 (top AUROC: 0.730, top accuracy: 0.733). Additionally, MitoR showed an average 4.14% increase in AUROC and an average 3.86% increase in accuracy over MERCI in all rank strategies and simulated datasets. Finally, MitoR revealed T cell MT hijacking events in two real-world tumor datasets (basal cell carcinoma and esophageal squamous-cell carcinoma), highlighting their role in tumor immune evasion. Full article

In high-energy physics, resistive plate chamber (RPC) detectors operating in avalanche mode make use of a high-performance gas mixture. Its main component, Tetrafluoroethane (C₂H₂F₄), is classified as a fluorinated greenhouse gas. The RPC EcoGas@GIF++ collaboration is pursuing an intensive R&D on new gas mixtures for RPCs to explore eco-friendly alternatives complying with recent European regulations. The performance of different RPC detectors has been evaluated at the CERN Gamma Irradiation Facility with Tetrafluoropropene (C₃H₂F₄)-CO₂-based gas mixtures. A long-term ageing test campaign was launched in 2022, and since 2023, systematic long-term performance studies have been carried out thanks to dedicated beam tests. The results of these studies are discussed together with their future perspectives. Full article

An investigation of the effect of gamma radiation was carried out on the setting time of alkali-activated binder paste. Mechanically activated coal fly ash (FA), ground granulated blast furnace slag (BFS), and their 1:1 mass mixture (MIX) were activated by water glass with a module of 1.5. Fresh paste was cast into molds and exposed to Co-60 gamma radiation, at a dose rate of 9.62–9.53 Gy/h, until the final setting. The initial and final setting times were determined by measuring the penetration of the Vicat needle at regular intervals. The initial setting times were 1 h 3 min for BFS, 1 h 55 min for MIX, and 3 h 28 min for FA. The final setting times were 1 h 10 min for BFS, 2 h 13 min for MIX, and 4 h 1 min for FA. The received doses were 8.02 Gy for BFS, 17.54 Gy for MIX, and 34.14 Gy for FA. Exposure to gamma radiation resulted in a shorter initial setting time for BFS, a shorter final setting time for FA, and results with an insufficiently visible impact on MIX. For dose rates in the 9–10 Gy/h range, the irradiation by Co-60 gamma rays during setting did not lead to flash, nor did it delay the setting of alkali-activated binder pastes. Full article

In this study, we describe the anti-obesity effects of a novel combination of Lactobacillus mixture (Lactobacillus curvatus HY7601 and Lactobacillus plantarum KY1032) and leaf extract of Lagerstroemia speciosa (L. speciosa) in mice. The administration of the probiotic mixture of HY7601 and KY1032 in combination with the leaf extract of L. speciosa significantly attenuated fat tissue formation and body weight gain in mice fed a high-fat diet. The white adipose fat mass, comprising the inguinal and epididymal fat pads, was most effectively reduced when the probiotic mixture and L. speciosa leaf extract was orally administered to the mice in combination. This combination also reduced the mRNA expression of adipogenic genes (those encoding CCAAT/enhancer-binding protein alpha, peroxisome proliferator-activated receptor gamma, and fatty acid-binding protein 4) in inguinal and epididymal white adipose tissue depots and the liver. Finally, the combination of reduced blood glucose concentrations regulated the insulin resistance of high-fat diet-fed obese mice. These findings provide insight into the mechanisms underlying the effect of this combination and suggest that using Lactobacillus mixture (HY7601 and KY1032) is as safe as microbial monotherapy, but more effective at preventing obesity. Full article

The rate of spontaneous action potentials (APs) generated by sinoatrial node cells (SANC) is regulated by local Ca²⁺ release (LCR) from the sarcoplasmic reticulum via Ca²⁺ release channels (ryanodine receptors, RyRs). LCR events propagate and self-organize within the network of RyR clusters (Ca release units, CRUs) via Ca-induced-Ca-release (CICR) that depends on CRU sizes and locations: While larger CRUs generate stronger release signals, the network’s topology governs signal diffusion and propagation. This study used super-resolution structured illumination microscopy to image the 3D network of CRUs in rabbit SANC. The peripheral CRUs formed a spatial mesh, reflecting the cell surface geometry. Two distinct subpopulations of CRUs were identified within each cell, with size distributions conforming to a two-component Gamma mixture model. Furthermore, neighboring CRUs exhibited repulsive behavior. Functional properties of the CRU network were further examined in a novel numerical SANC model developed using our experimental data. Model simulations revealed that heterogeneities in both CRU sizes and locations facilitate CICR and increase the AP firing rate in a cooperative manner. However, these heterogeneities reduce the effect of β-adrenergic stimulation in terms of its relative change in AP firing rate. The presence of heterogeneities in both sizes and locations allows SANC to reach higher absolute AP firing rates during β-adrenergic stimulation. Thus, the CICR facilitation by heterogeneities in CRU sizes and locations regulates and optimizes cardiac pacemaker cell operation under various physiological conditions. Dysfunction of this optimization could be a key factor in heart rate reserve decline in aging and disease. Full article

The growing demand for more sustainable routes and processes in the mixture separation and purification industry has generated a need to search for innovations, with new solvent alternatives being a possible solution. In this context, a new class of green solvents, known as deep eutectic solvents (DESs), has been gaining prominence in recent years in both academic and industrial spheres. These solvents, when compared to ionic liquids (ILs), are more environmentally friendly, less toxic, low-cost, and easier to synthesize. In addition, they have significantly lower melting points than their precursors, offering a promising option for various applications in this industrial sector. Understanding and studying the thermodynamic behavior of systems composed of these substances in purification and separation processes, such as liquid–liquid extraction and azeotropic distillation, is extremely important. This work aimed to study the phase behavior of liquid–liquid equilibrium (LLE) and vapor–liquid equilibrium (VLE) of water + 1-butanol + DES (choline chloride + glycerol) systems with a molar ratio of 1:2. Experimental LLE data, obtained at 298.15 K and 101.3 kPa, and VLE data, obtained at 101.3 kPa and in the temperature range of 364.05 K–373.85 K, were submitted to the thermodynamic quality/consistency test, proposed by Marcilla et al. and Wisniak, and subsequently modeled using the gamma–gamma approach for the LLE and gamma–phi for the VLE. The non-random two-liquid (NRTL) model was used to calculate the activity coefficient. The results are presented for the VLE in a temperature–composition phase diagram (triangular prism) and triangular phase diagrams showing the binodal curve and tie lines (LLE). The separation and distribution coefficients of LLE were determined to evaluate the extractive potential of the DES. For the VLE, the values of the relative volatility of the system were calculated, considering the entrainer free-basis, to evaluate the presence or absence of azeotropes in the range of collected points. From these data, it was possible to compare DES with ILs as extracting agents, using data from previous studies carried out by the research group. Therefore, the results indicate that the NRTL model is efficient at correlating the fluid behavior of both equilibria. Thus, this study serves as a basis for future studies related to the understanding and design of separation processes. Full article

The Pareto–Feller distribution has been widely used across various disciplines to model “heavy-tailed” phenomena, where extreme events such as high incomes or large losses are of interest. In this paper, we present a new bivariate distribution based on the Appell hypergeometric function with marginal Pareto–Feller distributions obtained from two independent gamma random variables. The proposed distribution has the beta prime marginal distributions as special case, which were obtained using a Kibble-type bivariate gamma distribution, and the stochastic representation was obtained by the quotient of a scale mixture of two gamma random variables. This result can be viewed as a generalization of the standard bivariate beta I (or inverted bivariate beta distribution). Moreover, the obtained bivariate density is based on two confluent hypergeometric functions. Then, we derive the probability distribution function, the cumulative distribution function, the moment-generating function, the characteristic function, the approximated differential entropy, and the approximated mutual information index. Based on numerical examples, the exact and approximated expressions are shown. Full article

This paper is set to analytically describe properties of the hyperbolic distribution. This law, along with the variance-gamma distribution, is one of the most popular normal mean–variance mixtures from the point of view of various applications. We have found closed form expressions for the cumulative distribution and partial-moment-generating functions of the hyperbolic distribution. The obtained formulas use the values of the Humbert confluent hypergeometric and Whittaker special functions. The results are applied to the problem of European option pricing in the related Lévy model of financial market. The research demonstrates that the discussed normal mean–variance mixture is analytically tractable. Full article