Search Results (65)

Despite concern over air pollution, fine-scale spatial and demographic disparities in exposure remain largely unquantified in Australian cities due to sparse monitoring and coarse models. In Greater Melbourne, this gap limits neighbourhood-level assessment of PM_2.5 exposure and associated environmental inequalities. To address this gap, we integrated 6-month averaged PM_2.5 observations (October 2023 to March 2024) from 5 regulatory monitoring stations and 13 low-cost sensors (LCSs) to develop a land use regression (LUR) model estimating concentrations at a 100 m resolution. These estimates were used to calculate population-weighted PM_2.5 exposure (PWE) at the mesh block level across Melbourne. To examine factors associated with spatial heterogeneity in PWE, we applied a hybrid modeling framework combining Spatially Explicit Random Forest (Spatial-RF) and Geographically Weighted Regression (GWR), incorporating physical, built-environment, and socio-demographic variables from the Synthesized Multi-Dimensional Environmental Exposure Database (SEED). The Spatial-RF model initially exhibited an R² of 0.56. After multicollinearity diagnostics using the Variance Inflation Factor (VIF), three key explanatory variables were selected for GWR modeling: the Normalized Difference Vegetation Index (NDVI), the Index of Education and Occupation (IEO), and the proportion of culturally and linguistically diverse populations (CALDP). The developed GWR model achieved higher model performance (R² = 0.65) than Spatial-RF and global Ordinary Least Squares (OLS) regression (R² = 0.38), revealing strong spatial non-stationarity. Results show that PWE generally ranged from 5 to 7 µg/m³, exceeding the 2021 WHO air quality guideline, with hotspots in the urban core and along major transport corridors. Elevated exposure occurred in both socioeconomically disadvantaged areas and residents in urban centers with higher socio-economic status, reflecting complex, spatially contingent exposure inequalities. These findings support fine-scale, equity-oriented air quality management. Full article

Cholangiocarcinoma (CCA) is a rare malignancy of the biliary tree with increasing global incidence and mortality and limited therapeutic options. Intrahepatic cholangiocarcinoma (iCCA) metabolism exhibits enhanced glycolysis, oxidative phosphorylation, and glutamine utilization. In this study, we investigated the therapeutic potential of targeting glutaminolysis in iCCA, identifying glutamate dehydrogenase (GDH)—which converts glutamate to α-ketoglutarate—as a key metabolic hub. We evaluated the effects of pomegranate waste extract (PWE), a by-product of industrial pomegranate juice production, on cell viability, proliferation, migration, ATP production, and extracellular acidification in CCLP1 cells, an established iCCA model. Our results are consistent with an altered cellular energy metabolism. We further assessed GDH enzymatic activity, expression, and transcriptional regulation in the presence or absence of PWE and its major components, punicalagin and ellagic acid. GDH expression was downregulated by PWE in a dose-dependent manner through inhibition of NF-κB signaling, revealing a new mechanistic link between NF-κB and GDH. In addition, GDH enzymatic activity was dose-dependently inhibited by PWE, as well as punicalagin and ellagic acid. Notably, punicalagin was identified as a novel competitive inhibitor of GDH. Overall, these findings provide the first evidence that modulation of glutaminolysis through GDH targeting impairs iCCA cell growth and metabolism, supporting GDH as a promising metabolic target. This study highlights pomegranate-derived compounds as potential leads for the development of adjunctive or preventive strategies in intrahepatic cholangiocarcinoma. Full article

In this study, a double-lattice photonic crystal structure was designed to achieve deep ultraviolet lasing without the use of any Distributed Bragg Reflector (DBR), which is called a photonic-crystal surface-emitting laser (PCSEL). The plane wave expansion (PWE) method was used to study the influence of various structural parameters on the resonant wavelength. Utilizing the random forest algorithm, we determined that the importance of the lattice constant to the resonant wavelength is 95.24%. Furthermore, we realized the reverse design of double-lattice photonic crystals from the target wavelength to optimal structural parameters through a radial basis function (RBF) network algorithm. Comparative analysis of the extreme learning machine (ELM) and back propagation (BP) algorithms demonstrated that RBF-based performance was notably superior to the training outcomes of other algorithms. The mean absolute error (MAE) of the lattice constant of the test set in the training results was 0.7610 nm, root mean square error (RMSE) was $1.143\times {10}^{-3}$ nm, and mean absolute relative error (MARE) was $5.489\times {10}^{-3}$. We verified the reliability of the algorithm and designed 13 groups of photonic crystals with different epitaxial structures. The mean square error (MSE) was 0.6188 ${\mathrm{nm}}^2$ compared with that of the plane wave expansion method. This work demonstrates applicability across various wavebands and epitaxial structures in GaN-based devices, providing a novel approach for the rapid iteration of deep ultraviolet PCSELs. Full article

Considering the global objective of carbon emission reduction, this paper focuses on optimizing the operational efficiency of grid-connected electric vehicles (EVs) and promoting sustainable energy integration and thus proposes a novel dual-incentive mechanism combining real-time pricing (RTP) and carbon quotas. A core of this study is the development of a bilevel programming model that effectively captures the strategic interaction between power suppliers (PS) and microgrid (MG) users. At the upper level, the model enables the PS to optimize electricity prices, achieving both revenue maximization and grid balance maintenance; at the lower level, it supports MGs in rational scheduling of EV charging/discharging, photovoltaic and wind energy (PWE) utilization, and load consumption, ensuring the fulfillment of user demands while maximizing MG profits. To address the non-convex factors in the model that hinder an efficient solution, another key is the design of a bilevel distributed genetic algorithm, which realizes efficient decentralized decision making and provides technical support for the practical application of the model. Through comprehensive simulations, the study verifies significant quantitative outcomes. The proposed algorithm converges after only 61 iterations, ensuring efficient solution performance. The average purchase price of electricity from the PS for the MG is USD 1.1, while the selling price of PWE sources from MG for the PS is USD 0.6. This effectively promotes the MG to prioritize the consumption of PWE sources and encourages the PS to repurchase the electricity generated by PWE sources. On average, carbon emissions decreased by approximately 300 g each time slot, and the average amount of carbon trading was around USD 8. Ultimately, this research delivers a practical and impactful solution for the development of MGs and the advancement of carbon reduction goals. Full article

Background: Aromatic plants like peppermint (Mentha x piperita, Lamiaceae) have a long tradition of use. Most of the plant material is used to produce herbal drugs and for the isolation of essential oils. However, since essential oils are present in very small amounts, the largest proportion of plants remains unused. Objectives: The aims of this study were the analysis of chemical, biochemical, antimicrobial, and pharmacological properties of peppermint waste material extracts (derived from stems, post-distillation waste, and deodorized leaves) in comparison with the officially prepared extract. Results: The obtained results revealed that the investigated peppermint waste extracts (PWEs) are a rich source of phenolic compounds, where rosmarinic acid was determined as the dominant one (7.05–21.19 mg/g d.e.). Antioxidant potential and hepatoprotective effect of PWE were comparable with the official extract, where the most active ones were those prepared by treating the deodorized leaves with both 45% and 75% ethanol. In addition, PWE exhibited notable antimicrobial and anticholinesterase activity. Results of pharmacological studies on experimental animals showed that peppermint extracts (official and those made from deodorized leaves) did not interfere with the effect of the tested drugs, midazolam and fluoxetine. The examined extracts neither exerted an influence on motor coordination nor acted as antidepressants. Results of the elevated plus maze test indicated that PWE affected the activity of the central nervous system. Conclusions: PWEs represent a significant source of phenolic compounds, especially rosmarinic acid, and they can be used in the pharmaceutical industry to produce various herbal products and in the food industry as natural additives. Full article

Polygala tenuifolia Willd., a widely used traditional Chinese medicine, has the function of coordinating heart and kidney and eliminating swelling. However, its renal-protective efficacy and possible material basis remain unknown. The aim of the study was to investigate the renal-protective effect of Polygala tenuifolia Willd. and identify the potential active substance and molecular mechanism. A gentamicin-induced kidney injury model was established to investigate efficacy. Secondly, potential active substances and molecular mechanisms were studied through integrated gut microbiota–drug interaction analysis and network pharmacology at a cellular level. Finally, 16S rRNA sequencing and untargeted metabolomics were used to elucidate the gut microbiota composition and metabolic profile change. Polygala tenuifolia Willd. extracts (PWE), with tenuifoliside A (TFSA) as the key compound, significantly reversed gentamicin-induced acute kidney injury in mice. The gut microbiota-derived carboxylesterase metabolized TFSA into four characteristic metabolites (M1–M4). Notably, both TFSA and M4 were detected in kidney and exerted protective effects via inhibiting TLR4–NF-κB pathway. Furthermore, metabolic pathways and gut microbiota composition change were identified. PWE treatment significantly increased the abundance of beneficial bacteria such as Akkermansia and Blautia, while reducing the abundance of harmful bacteria such as Oscillospira. Subsequently, PWE can reverse amino acid metabolic abnormalities by regulating the biosynthesis of phenylalanine, tyrosine, and tryptophan and ameliorating tryptophan metabolism disorder. This study was the first to verify the renal-protective effect of PWE and identify the effective substance basis (TFSA) and the molecular mechanism, providing a scientific foundation for the development of kidney drug treatment strategies targeting the intestinal flora. Full article

Background: Heart rate variability (HRV) is a well-established marker of autonomic nervous system (ANS) activity. It is also an important tool for investigating cardiovascular and neurological health. Changes in HRV have been associated with epilepsy and sudden unexpected death in epilepsy (SUDEP), conditions in which autonomic dysregulation is believed to play a significant role. HRV is traditionally measured using electrocardiography (ECG) under standardized laboratory conditions. Recently, however, wearable devices such as the Empatica E4 wristband have emerged as promising tools for continuous, noninvasive HRV monitoring in real-life, ambulatory, and clinical settings where laboratory infrastructure may be lacking. Methods: We evaluated the validity and clinical utility of the Empatica E4 wristband in two cohorts. In the first cohort of healthy controls (n = 29), we compared HRV measures obtained with the E4 against those obtained with a gold-standard laboratory ECG device under seated rest and metronomic breathing conditions. In persons with epilepsy (PWE, n = 42), we assessed HRV across wake and sleep states, as well as during exposure to sodium channel blockers. This was done to determine whether the device could detect physiologically and clinically meaningful changes in autonomic nervous system (ANS) function. Results: In healthy participants, the Empatica E4 provided heart rate (HR), root mean square of successive R-R intervals (RMSSD), and standard deviation of all interbeat intervals (SDNN) values that were strongly correlated with laboratory measurements. Both devices detected the expected increase in RMSSD during metronomic breathing; however, the E4 consistently reported higher absolute values than the ECG. In patients with epilepsy (PWE), the E4 reliably captured parasympathetic activation during sleep and detected a significant reduction in heart rate variability (HRV) in patients taking sodium channel blockers, demonstrating its sensitivity to clinically relevant autonomic changes. Conclusions: The Empatica E4 wristband is valid for measuring HRV in research and clinical contexts. It can detect modulations of ANS activity that are physiologically meaningful. While HRV metrics were robust, other signals, such as electrodermal activity and temperature, were less reliable. These results highlight the potential of wearable devices as practical alternatives to laboratory-based autonomic testing, especially in emergency and resource-limited settings, and emphasize their importance in epilepsy care risk assessment. Full article

Soil surfactants are essential tools for enhancing irrigation water efficiency and improving the quality and functionality of amenity turfgrass. They play a crucial role in sports turf management by reducing soil water repellency, which helps prevent dry spots, ensures even moisture distribution, and supports water conservation efforts. Most research on soil surfactants and amenity turfgrasses focuses on their effects on soil moisture, infiltration, and addressing localized dry spots during drought conditions, with limited studies on their impact under wet or saturated conditions. This study aimed to evaluate the impact of soil surfactants on the quality and health of turfgrass under wet conditions. Field studies were conducted over a span of five years, beginning in the USA in 2019 and continuing in Ireland from 2020 to 2023. The research in Ireland was conducted at three locations, each featuring different rootzones: a “push-up” green with loam soil, USGA-specification sand, and natural link sand. The site in the USA was a native loam soil. The study compared a commercial soil surfactant (ProWet Evolve; PWE) and a non-treated control (NT) in a randomized complete block design with four replications, with sequential applications starting in June and continuing until mid-September each year. The rootzone volumetric water content (VWC%), turfgrass quality, and normalized difference vegetation index (NDVI) were measured bi-weekly. Environmental conditions, with above-average precipitation each year, significantly influenced results. Although there were no significant or consistent differences in VWC% between the soil surfactant and NT-treated plots, turfgrass quality was significantly enhanced in the soil surfactant-treated plots and supported by higher NDVI values. Even in prolonged wet conditions with high VWC%, improved turfgrass quality was consistently observed in soil surfactant-treated plots across multiple locations in both countries over the five-year study period. Full article

This study proposes the use of a low-symmetry hexagonal photonic crystal (LSHPC) incorporating Kerr-type nonlinearity to enhance self-collimation. The equifrequency contours (EFCs) of a C₂-symmetric LSHPC composed of nonlinear LiNbO₃ rods are analyzed as a function of the nonlinear refractive index. The self-collimation characteristics, transmission spectrum, group velocity dispersion (GVD), and third-order dispersion (TOD) are investigated using the Plane Wave Expansion (PWE) and Finite Difference Time Domain (FDTD) methods. The results demonstrate that increasing the nonlinear index leads to a significant flattening of the EFCs, which enhances self-collimation performance. Furthermore, symmetry-lowering perturbations improve beam confinement and enable all-angle self-collimation. These findings highlight the potential of Kerr-type nonlinear photonic crystals for integrated photonic circuits requiring precise control over light propagation. Full article

Introduction: Among U.S. adults, over 3 million report a history of epilepsy, accounting for nearly 1.2% of the population. Sleep deprivation is a well-known risk factor for increased likelihood, intensity, and length of seizures. However, the long-term impact of sleep deprivation on people with epilepsy is not well explored. The purpose of this study was to assess mortality risk among individuals with epilepsy based on sleep duration. Methods: Data from the 2008–2018 National Health Interview Survey (NHIS) were linked with mortality data from the National Death Index (NDI) for US adults aged 65 years and older. Survival curves showed the combined effect of sleep deprivation and epilepsy, using the Kaplan–Meier product-limit method to estimate the percent survival of the subject at each point in time. Results: For all-cause mortality, the unadjusted hazard ratio (HR) for sleep deprivation to no sleep deprivation among people with epilepsy (PWE) was HR = 1.92. The adjusted HR was elevated, HR = 1.94, among individuals who had epilepsy and sleep deprivation but close to 1.0 among individuals who had a history of sleep deprivation without epilepsy after adjusting for demographic and health variables. Conclusions: From a nationally representative sample, this first-of-its-kind study in the U.S. found that sleep deprivation and epilepsy combined have worse outcomes than sleep deprivation alone. Clinicians should screen and manage sleep disorders to improve their long-term prognosis of people with epilepsy. Full article

Air pollution is a major trigger for chronic respiratory and circulatory diseases. As a key component of air pollution, fine particulate matter (PM_2.5) exposure is largely determined by land use type and population density. However, simultaneous consideration of their spatiotemporal distribution is lacking in existing studies on PM_2.5 exposure. In this paper, we first assess the dynamic evolution of land use patterns in Gansu Province, China, from 2000 to 2020, using a land use transfer matrix and dynamic degree. Population-weighted exposure (PWE) to PM_2.5 is then evaluated for each land use type at provincial, city, and county levels, with seasonal variations analyzed. Spatial autocorrelation analysis is finally performed to explore the spatiotemporal evolution of PM_2.5 exposure, whereas standard deviation ellipses and gravity center migration models highlight spatial distribution characteristics and shifting trends. Experimental results showed that 2010 was a turning point for annual PM_2.5 exposure at the provincial level in Gansu Province, with an initial increase followed by a decrease. Construction land had the highest annual PM_2.5 exposure, whereas forest had the lowest exposure (except in 2005). Exposure levels showed a seasonal pattern: higher in winter and spring and lower in summer and autumn. At city and county levels, southern Gansu indicated a continuous decline in annual PM_2.5 exposure across all land use types since 2000. Exposure levels exhibited a strong spatial positive correlation, with a fluctuating spatial convergence. This study comprehensively analyzes the multi-scale differences and spatiotemporal evolution patterns of PM_2.5 exposure across various land use types, contributing to provide scientific evidence and decision-making support for mitigating air pollution and enhancing coordinated air pollution control at multi-scale administrative levels. Full article

This study offers promising insights into the anti-obesity potential of Pleurotus ferulae, an edible mushroom valued in Asian cuisine for its nutritional benefits. A hot water extract of P. ferulae (PWE) administered to high-fat diet-induced obese mice over an 8-week period significantly reduced their body weight gain and fat accumulation. PWE not only improved the body weight metrics but also positively influenced the serum lipid profile of obese mice by lowering their total cholesterol and low-density lipoprotein cholesterol levels. In vitro studies using 3T3-L1 adipocytes showed that PWE inhibited adipocyte differentiation and lipid accumulation by downregulating key adipogenic transcription factors, particularly PPARγ and C/EBPα, as well as related lipogenic genes involved in fat synthesis and storage, such as Fabp4, Fasn, and Scd1. Chemical analysis revealed that PWE is rich in polysaccharides, which have been associated with various health benefits, including anti-obesity, anti-diabetic, and anti-cancer properties. These findings suggest that the bioactive compounds in PWE may serve as functional food components that could potentially be applied for the prevention and management of obesity and other metabolic disorders. Full article

Air pollution is one of the main risk factors for human health. The aim of this study was to provide an Integrated Environmental and Health Impact Assessment (IEHIA) tool to estimate the impacts on both environment and human health in Pisa municipality (central Italy). For each pollutant considered (PM_2.5, PM₁₀, and NO₂), both Population-Weighted Exposure (PWE) and Attributable Deaths (ADs) were calculated considering the difference between the PWE and the latest air quality guidelines suggested by the World Health Organization. The PWEs were 16.1 µg/m³, 24.9 µg/m³, and 25.9 µg/m³ for PM_2.5, PM₁₀, and NO₂, respectively. The ADs from natural causes due to exposure to PM_2.5, PM₁₀, and NO₂ were 63, 29, and 51, respectively. The AD distribution was mainly concentrated in urban areas for particulate matter and in urban and suburban areas for NO₂. The results highlighted significantly higher levels of air pollution than the reference levels, with a percentage of ADs from natural causes of approximately 6% of the total mortality in Pisa. IEHIA offers support for environmental and health policies and territorial planning. The authors recommend the adoption of prevention measures aimed at mitigating air pollution in critical areas, with a consequent reduction in avoidable mortality. Full article

This paper proposes a unique configuration for an all-optical D Flip Flop (D-FF) utilizing a quasi-square ring resonator (RR) and T-Splitter, as well as NOT and OR logic gates within a 2-dimensional square lattice photonic crystal (PC) structure. The components realizing the all-optical D-FF comprise of optical waveguides in a 2D square lattice PC of 45 × 23 silicon (Si) rods in a silica (SiO₂) substrate. The utilization of these specific materials has facilitated the fabrication process of the design, diverging from alternative approaches that employ an air substrate, a method inherently unattainable in fabrication. The configuration underwent examination and simulation utilizing both plane-wave expansion (PWE) and finite-difference time-domain (FDTD) methodologies. The simulation outcomes demonstrate that the designed waveguides and RR effectively execute the operational principles of the D-FF by guiding light as intended. The suggested configuration holds promise as a logic block within all-optical arithmetic logic units (ALUs) designed for digital computing optical circuits. The design underwent optimization for operation within the C-band spectrum, particularly at 1550 nm. The outcomes reveal a distinct differentiation between logic states ‘1’ and ‘0’, enhancing robust decision-making on the receiver side and minimizing logic errors in the photonic decision circuit. The D-FF displays a contrast ratio (CR) of 4.77 dB, a stabilization time of 0.66 psec, and a footprint of 21 μm × 12 μm. Full article

Although Coronavirus disease 2019 (COVID-19) vaccinations are generally recommended for persons with epilepsy (PwE), a significant vaccination gap remains due to patient concerns over the risk of post-vaccination seizure aggravation (PVSA). In this single-centre, retrospective cohort study, we aimed to determine the early (7-day) and delayed (30-day) risk of PVSA, and to identify clinical predictors of PVSA among PwE. Adult epilepsy patients aged ≥18 years without a history of COVID-19 infection were recruited from a specialty epilepsy clinic in early 2022. Demographic, epilepsy characteristics, and vaccination data were extracted from a centralized electronic patient record. Seizure frequency before and after vaccination, vaccination-related adverse effects, and reasons for or against vaccination were obtained by a structured questionnaire. A total of 786 PwEs were included, of which 27.0% were drug-resistant. At the time of recruitment, 74.6% had at least 1 dose of the COVID-19 vaccine. Subjects with higher seizure frequency (p < 0.0005), on more anti-seizure medications (p = 0.004), or had drug-resistant epilepsy (p = 0.001) were less likely to be vaccinated. No significant increase in seizure frequency was observed in the early (7 days) and delayed phases (30 days) after vaccination in our cohort. On the contrary, there was an overall significant reduction in seizure frequency 30 days after vaccination (1.31 vs. 1.89, t = 3.436; p = 0.001). This difference was seen in both types of vaccine (BNT162b2 and CoronaVac) and drug-resistant epilepsy, but just missed significance for the second dose (1.13 vs. 1.87, t = 1.921; p = 0.055). Only 5.3% had PVSA after either dose of vaccine. Higher pre-vaccination seizure frequency of ≥1 per week (OR 3.01, 95% CI 1.05–8.62; p = 0.04) and drug-resistant status (OR 3.32, 95% CI 1.45–249 7.61; p = 0.005) were predictive of PVSA. Meanwhile, seizure freedom for 3 months before vaccination was independently associated with a lower risk of PVSA (OR 0.11, 95% CI 0.04–0.28; p < 0.0005). This may guide epilepsy treatment strategies to achieve better seizure control for at least 3 months prior to vaccination. As COVID-19 shifts to an endemic phase, this study provides important data demonstrating the overall safety of COVID-19 vaccinations among PwE. Identification of high-risk patients with subsequent individualized approaches in treatment and monitoring strategies may alleviate vaccination hesitancy among PwE. Full article