Search Results (75)

During a period of intense solar activity and highly disturbed geomagnetic conditions, a large Forbush decrease began on 10 May 2024 accompanied by a historic geomagnetic storm that lasted for four days. This extreme geomagnetic disturbance classified as G5 according to “NOAA Space Weather Scale for Geomagnetic Storms” is referred to in the literature as the Mother’s Day Storm. This resulted from multiple, at least seven, Coronal Mass Ejections (CMEs) that had been occurring since 7 May. In addition, on 11 May, a powerful X5.8 class solar flare, reaching its maximum at 01:32 UT, was followed by an abrupt increase in proton flux with energies > 100 MeV (with onset on 11 May at 01:45 UT and peaking at 02:45 UT), as recorded by GOES satellites. This resulted in a Ground Level Enhancement (GLE), identified as GLE74, occurring on 11 May 2024 during the recovery phase of the deep Forbush decrease (~15%). This Solar Energetic Particle (SEP) event consisted of both impulsive and gradual components, where the high-energy tail of the gradual component was recorded by several stations of the worldwide ground-based neutron monitor network. Approximately 15 minutes after the onset of the SEP event and 40 minutes prior to its peak, an alert was issued by the GLE Alert++ system of the Athens Neutron Monitor Station of the National and Kapodistrian University of Athens (NKUA), available as a federated product on the ESA SWE Portal under the Space Radiation Expert Service Centre. In this paper, a description of the solar activity, i.e., solar flares and CMEs, occurring during this time period is given. Moreover, recordings of cosmic ray data obtained by ground-based neutron monitors are used to perform a detailed analysis of GLE74. Finally, the response of the NKUA GLE Alert++ system to GLE74 is thoroughly presented. Full article

Background: Universal varicella vaccination has fundamentally altered the epidemiology of varicella-zoster virus (VZV) infections. While the incidence of primary varicella has declined, the characteristics of herpes zoster (HZ) in the post-vaccine generation remain a subject of debate. This study aimed to analyze the demographic and clinical characteristics of pediatric HZ in the context of a mature national immunization program. Methods: This retrospective observational study included children under 18 years of age diagnosed with HZ between 2018 and 2025 at the dermatology outpatient clinic of a tertiary hospital. Demographic, clinical, and epidemiologic variables were retrieved from hospital records. Results: A total of 64 pediatric patients (mean age: 10.5 ± 4.9 years; 59.4% male) were analyzed. The majority (93.8%) were vaccinated. Vaccinated children presented at a significantly younger age (mean: 9.1 ± 5.4 years) than those with a history of natural varicella infection without vaccination (mean: 12.3 ± 3.5 years; p = 0.007). The thoracic (39.1%) and cervical (35.9%) dermatomes were most frequently affected. Cervical involvement was significantly more frequent in younger children (mean age 7.1 years), whereas thoracic and lumbar dermatomes predominated in adolescents (mean age > 12 years; p = 0.001). Seasonal distribution was even, but the annual frequency peaked in 2023, whereas 2021 showed the lowest number. Only one patient (1.6%) developed postherpetic neuralgia, and no other complications were observed. Conclusions: Universal vaccination is associated with a shift in the onset of pediatric herpes zoster to younger individuals, often presenting with cervical dermatomal involvement hypothesized to be linked to vaccination injection sites. Clinicians should recognize that while HZ in vaccinated children is typically a self-limiting event that does not require an extensive immunologic workup in otherwise healthy, immunocompetent children, rare complications like postherpetic neuralgia can still occur. Limitations of this sin-gle-center, retrospective study include a high exclusion rate due to missing data, a small number of unvaccinated comparators, and the lack of viral genotyping to differentiate wild-type from vaccine-strain virus. Full article

The marine angiosperm Posidonia oceanica (Linnaeus) Delile, 1813 is a rich source of phytotherapeutic compounds whose potential applications for human health remain largely uninvestigated. Here, we determined the differential impact of aqueous extracts from P. oceanica’s green leaves (GLE) and rhizomes (RE) on the inflammation-related mRNA expressions and protein levels, nitric oxide (NO) release, and endocytic activity in LPS-stimulated RAW 264.7 macrophages. We also examined the influence of the extracts in modulating the activation of components of intracellular signaling pathways. Co-treatments of LPS-stimulated RAW 264.7 cells in the presence of either GLE or RE resulted in a reduction in NO production, associated with a down-regulation of Nos2 expression, reduced levels of COX-2 and TNFα proteins, and a decrease in Nfkb1 expression and NF-κB activation. No effect was exerted on the release of IL-6. Moreover, co-exposures to LPS and the extracts led to an elevation in pJNK and pAKT levels alongside a reduction in pERK. In contrast to GLE, RE specifically lowered IL-1β production, induced a more robust increase in IL-10, positively influenced the endocytic function of RAW 264.7 cells, and drastically up-regulated the phosphorylation of p38. The data obtained indicate that GLE and RE exhibit considerable promise as prospective anti-inflammatory and immunomodulatory agents. Full article

Introduction: Manual therapists routinely evaluate changes in pain, movement, and function through clinical tests that support clinical reasoning. The Prone Hip Extension Test (PHET) is commonly used as a self-perturbation task to assess lumbopelvic control and hip motion patterns related to gait. Performing the PHET actively and passively may reveal how voluntary activation and passive structures influence joint kinematics and contribute to force production. This study aimed to compare active and passive PHET execution and investigate how initial (IP) and final hip positions (FP) correlate with lower-limb neuromuscular function. Methods: Seven healthy volunteers (24.3 ± 3.4 years; 173.1 ± 7.5 cm; 72.1 ± 9.5 kg) without musculoskeletal conditions participated. Hip kinematics were recorded using a 12-camera Qualisys Oqus system (200 Hz) with 22 reflective markers, processed in Qualisys Track Manager 2.13 and exported to Visual3D. Participants performed three PHET trials in both IP and FP, with mean an-gles considered for analysis. Knee isokinetic performance was assessed on a Biodex System 4 at 180°/s and 300°/s for flexion and extension. Results: Significant differences between active and passive PHET emerged in the FP for rotational movements bilaterally (p = 0.02) and in IP adduction/abduction for both hips (right p = 0.03; left p = 0.02). No side-to-side differences were observed. Passive FP of the right hip showed multiple significant correlations with isokinetic flexion and extension parameters at 180°/s and 300°/s, particularly with torque/body weight, acceleration and deceleration times, and agonist/antagonist ratios (ρ ranging from −0.86 to 0.90). Conclusions: Meaningful differences exist between active and passive PHET performance, especially in frontal-plane IP and rotational FP measures. Additionally, passive FP strongly correlates with several neuromuscular variables, suggesting that PHET kinematics may reflect lower-limb isokinetic function. Full article

This study proposes a novel structure-preserving algorithm for the Ginzburg–Landau equation (GLE) by combining the Fourier pseudospectral method with the Exponential Average Vector Field (EAVF) scheme. The proposed numerical framework strictly preserves the energy dissipation property of GLE systems, as validated through theoretical analysis and numerical experiments on solitary wave dynamics. Compared to conventional methods such as the average vector field approach, the EAVF-based scheme demonstrates superior computational efficiency, including faster convergence and enhanced stability under larger time steps, enabling accurate long-term simulation of strongly nonlinear GLE systems. Furthermore, this research incorporates a pedagogical innovation through its implementation within an undergraduate innovation project. By adopting a “problem decomposition–code verification–modular development” training model, students engage in the full cycle of algorithm design, implementation, and validation. This practice-oriented approach significantly enhances students’ competencies in scientific programming, complex problem-solving, and research-oriented thinking, providing an effective paradigm for synergizing advanced computational research with talent cultivation in STEM education. Full article

Pangenotypic direct-acting antivirals (pDAAs) have transformed hepatitis C virus (HCV) treatment. In Italy, sofosbuvir/velpatasvir (SOF/VEL) and glecaprevir/pibrentasvir (GLE/PIB) are available. While both show similar efficacy, differences in patient profiles and potential drug–drug interactions (DDIs) may influence treatment choice. This study examined factors affecting pDAA selection and potential prescribing gaps. Using administrative databases (2018–2023) covering 3.7 million citizens, HCV patients were divided into SOF/VEL and GLE/PIB cohorts and compared by demographic, clinical, and therapeutic data. Among 5565 patients, 2837 (51%) received SOF/VEL and 2728 (49%) received GLE/PIB. SOF/VEL patients were older (60.8 vs. 57.6 years, p < 0.001) and had more comorbidities: diabetes (24% vs. 17%), mental disorders (22% vs. 14%), cancer (14% vs. 9%), and cardiovascular disease (31% vs. 22%). Hospitalization rates were higher (19% vs. 13%), as were exemption codes for chronic hepatitis (58% vs. 50%) and hypertension (32% vs. 23%). Polypharmacy was more common with SOF/VEL; 25% used ≥10 non-pDAA drugs (vs. 17%), and mean medications per patient were higher (6.3 ± 5.6 vs. 4.9 ± 5.2). SOF/VEL was often used for older, frailer patients, likely due to a more favourable DDI profile. These prescribing trends highlight the importance of tailoring pDAA choice to patient comorbidity profiles, ensuring appropriate and individualized HCV treatment. Full article

This paper investigates the chaotic and pattern dynamics of the time-fractional Ginzburg–Landau equation. First, we propose a high-precision numerical method that combines finite difference schemes with an improved Grünwald–Letnikov fractional derivative approximation. Subsequently, the effectiveness of the proposed method is validated through systematic comparisons with classical numerical approaches. Finally, numerical simulations based on this method reveal rich dynamical phenomena in the fractional Ginzburg–Landau equation: the system exhibits complex behaviors including chaotic oscillations and novel two- and three-dimensional pattern structures. This study not only advances the theoretical development of numerical solutions for fractional GLE but also provides a reliable computational tool for deeper understanding of its complex dynamical mechanisms. Full article

This work reviews self-guided (SG) molecular simulation methods and illustrates the characteristics and applications of these methods through several example simulations. The main characteristic of SG methods is that past motion in simulations is used to guide future motion. Two forms of these methods are self-guided molecular dynamics (SGMD) and self-guided Langevin dynamics (SGLD). SG methods achieve an enhanced conformational search through promoting low-frequency motion. A simple local averaging scheme is used to extract low-frequency properties from past simulation trajectories to promote low-frequency motion, which significantly enhances conformational search efficiency with little overhead in computing cost. Based on a generalized Langevin equation (GLE), an SGLD-GLE simulation method is developed, which has enhanced conformational searching ability and at the same time can vigorously sample the canonical ensemble. A reformulation of the SG methods leads to a quantitative relation between the guiding parameters and the conformational distribution, which allows the SG methods to be combined with the replica exchange scheme to perform replica-exchanging self-guided simulations (RXSGMD/RXSGLD). RXSGMD/RXSGLD are much more efficient than temperature-based replica exchange methods, especially for large systems. Full article

The role of green and low-carbon energy (gLE) resources in realizing the envisaged future decarbonized energy generation and supply cannot be overemphasized. The world has witnessed growing attention to the application of green energy (gE) sources such as solar, wind, hydro, geothermal, and biomass (energy crops, biogas, biodiesel, etc.). There is also the existence of low-carbon energy (LE) resources such as power-to-X, power-to-fuel, power-to-gas, e-fuel, waste-to-energy, etc., which possess huge potential for delivering sustainable energy, thus facilitating a pathway for achieving the desired environmental sustainability. In addition, the evolution of the cyber-physical power systems and the need for strengthening capacity in advanced energy materials are among the key factors that drive the deployment of gLE technologies around the world. This paper, therefore, presents the recent global developments in gLE resources, including the trends in their deployments for different applications in commercial premises. The study introduces different conceptual technical models and configurations of energy systems; the potential of multi-energy generation in a microgrid (m-grd) based on the gLE resources is also explored using the System Advisor Model (SAM) software. The m-grd is being fueled by solar, wind, and fuel cell resources for supplying a commercial load. The quantity of carbon emissions avoided by the m-grd is evaluated compared to a purely conventional m-grd system. The paper presents the cost of energy and the net present cost of the proposed m-grid; it also discusses the relevance of carbon capture and storage and carbon sequestration technologies. The paper provides deeper insights into the understanding of clean and unconventional energy resources. Full article

Glehnia littoralis Fr. Schmidt ex Miq. has been cultivated in China for a long time and used as a medicinal plant called “Beishashen” in traditional Chinese medicine and has been traditionally known to have antibacterial and anti-inflammatory effects, but its direct role in periodontitis has not been known. Currently used periodontal treatments require long-term administration, which causes many side effects. Therefore, in this study, we evaluated the effects of G. littoralis extract (GLE) on periodontitis in an experimental periodontitis-induced in vitro and vivo model and understood its potential molecular mechanism. The effect of GLE on periodontitis in vitro was investigated using human periodontal ligament (HPDL) cells mediated by PG-LPS. Additionally, a ligature-induced periodontitis model and a PG-LPS-induced periodontal inflammation model were used to investigate the effect of GLE in vivo. In vitro study results showed that GLE down-regulated the increased inflammatory cytokines and mediators in HPDL cells stimulated with PG-LPS, and simultaneously down-regulated the levels of 11β-HSD1 and glucocorticoid receptor (GR), thereby alleviating periodontal inflammation. At the same time, it restored the lost osteoblast differentiation potential of HPDL cells. In addition, in an in vivo model representatively used for periodontitis research, the periodontal inflammation-alleviating effect and the effect of restoring or protecting damaged periodontal tissue were confirmed. GLE can be considered as a new periodontitis treatment agent through regulating 11β-HSD1. Full article

In recent years, the continuous advancement of deep learning technology and its integration into the domain of low-light image enhancement have led to a steady improvement in enhancement effects. However, this progress has been accompanied by an increase in model complexity, imposing significant constraints on applications that demand high real-time performance. To address this challenge, inspired by the state-of-the-art Zero-DCE approach, we introduce a novel method that transforms the low-light image enhancement task into a curve estimation task tailored to each individual image, utilizing a lightweight shallow neural network. Specifically, we first design a novel curve formula based on Gamma correction, which we call the Gamma-based light-enhancement (GLE) curve. This curve enables outstanding performance in the enhancement task by directly mapping the input low-light image to the enhanced output at the pixel level, thereby eliminating the need for multiple iterative mappings as required in the Zero-DCE algorithm. As a result, our approach significantly improves inference speed. Additionally, we employ a lightweight network architecture to minimize computational complexity and introduce a novel global channel attention (GCA) module to enhance the nonlinear mapping capability of the neural network. The GCA module assigns distinct weights to each channel, allowing the network to focus more on critical features. Consequently, it enhances the effectiveness of low-light image enhancement while incurring a minimal computational cost. Finally, our method is trained using a set of zero-reference loss functions, akin to the Zero-DCE approach, without relying on paired or unpaired data. This ensures the practicality and applicability of our proposed method. The experimental results of both quantitative and qualitative comparisons demonstrate that, despite its lightweight design, the images enhanced using our method not only exhibit perceptual quality, authenticity, and contrast comparable to those of mainstream state-of-the-art (SOTA) methods but in some cases even surpass them. Furthermore, our model demonstrates very fast inference speed, making it suitable for real-time inference in resource-constrained or mobile environments, with broad application prospects. Full article

Posidonia oceanica (L.) Delile, a Mediterranean seagrass, is rich in bioactive compounds with anti-inflammatory potential. While marine-derived molecules are increasingly studied, their direct effects on blood–brain barrier (BBB) integrity under inflammatory conditions remain largely unexplored. This study evaluated the ability of aqueous extracts from its green leaves (GLEs) and rhizomes (REs) to protect the BBB using a human in vitro model consisting of brain-like endothelial cells co-cultured with brain pericytes. The model was exposed to TNFα, with or without GLEs or REs. We assessed NO production, endothelial permeability, expression of IL-6, NLRP3, ICAM-1, VCAM-1, CLAUDIN-5, and VE-CADHERIN, and the localization of junctional proteins. TNFα increased NO and IL-6 release, upregulated ICAM-1, VCAM-1, and NLRP3, and impaired BBB integrity by altering junctional protein levels and distribution. Co-treatment with GLEs or REs reduced the production of NO, the expression of NLRP3 and adhesion molecules and restored tight and adherens junction integrity. IL-6 levels remained unaffected. These findings suggest that P. oceanica’s extracts may help preserve BBB function and mitigate inflammation-induced damage. While further studies are needed to assess their bioavailability and in vivo efficacy, these natural compounds represent promising candidates for developing preventive strategies against neuroinflammatory disorders. Full article

Ganoderma leucocontextum, a newly identified species from the Tibetan Plateau, has been mainly studied for its polysaccharides and triterpenoids, with no prior reports on fungal immunomodulatory proteins (FIPs). This study explores the biological activity of FIP-gle2, cloned from G. leucocontextum and expressed in Pichia pastoris. The effects and mechanisms of recombinant FIP-gle2 (rFIP-gle2) on cell activity and melanin synthesis in mouse melanoma B16-F10 cells were investigated in vitro. The results showed that the FIP-gle2 gene, with an open reading frame (ORF) of 333 bp, encodes a 111-amino acid polypeptide with a molecular weight of 12.60 kDa and an isoelectric point of 4.48. We achieved a yield of 184.18 mg/L of rFIP-gle2. In vitro functional experiments showed that rFIP-gle2 significantly inhibited the proliferation of B16-F10 melanoma cells and induced apoptosis in a dose-dependent manner, particularly at concentrations above 1 μg/mL. At 3 μg/mL, rFIP-gle2 effectively inhibited tyrosinase activity and reduced melanin content, downregulating microphthalmia-associated transcription factor (MITF), tyrosinase (TYR), and tyrosinase-related proteins (TRP-1 and TRP-2). Furthermore, RNA-seq analysis indicated that differentially expressed genes in treated cells were enriched in the mitogen-activated protein kinase (MAPK) signaling pathway, with Western blotting confirming enhanced phosphorylation of JNK, ERK, and p38 proteins. Thus, P. pastoris is an effective host for rFIP-gle2 production, which shows potential for applications in pharmaceuticals, cosmeceuticals, and food fields. Full article

Skeletal muscle atrophy is one of the serious complications of diabetes, which increases the risk of frailty, falls, and mortality. However, interventions for muscle atrophy are limited, and research is needed regarding the treatment of muscle wasting. Recently, the bioconversion of natural products by lactic acid bacteria has been highlighted as a possibility to improve the bioavailability of active ingredients. This process also produces metabolites, which are key signaling mediators for a variety of physiological functions. This study investigated the effect of bioconverted guava leaf (Psidium guajava L., GL) by Lactobacillus plantarum on hyperglycemia-induced skeletal muscle atrophy in type 2 diabetes mellites (T2DM) mice. Diabetes was induced by a high-fat diet with a two-time streptozotocin (STZ) injection (60 mg/kg BW) in male C57BL/6J mice. After diabetes was induced (a fasting blood glucose level (FBG) ≥ 300 mg/dL), the mice were administered with GL (100 mg/kg/day) or bioconverted GL (FGL) (50 mg/kg/day) by oral gavage for 14 weeks. FGL contains different substances such as hydroxyl-isocaproic acid and hydroxyl-isovaleric acid compared to GLE itself, which have potential to prevent muscle degradation in T2DM mice. GL and FGL supplementation reduced the FBG level in T2DM mice. In addition, GL and FGL supplementation enhanced muscle strength, the skeletal muscle cross-sectional area, and ameliorated ubiquitin–proteasome system (UPS)-related pathways in T2DM mice. On the other hand, GLE supplementation ameliorated glucose tolerance demonstrated by oral glucose tolerance test and enhanced insulin signaling pathway. In addition, only FGL supplementation attenuated skeletal muscle inflammation and apoptosis with an improved mammalian target of the rapamycin (mTOR)-autophagy-related pathway. Although administered at a half dose of GLE, FGL demonstrated greater efficacy in regulating the expression of these molecular markers. The result suggests that even GL itself has anti-diabetic effects, and the functionality would be enhanced by the bioconversion of GL with L. Plantarum, which has an additive or/and a synergistic effect. Taken together, FGL could be used as a potential nutraceutical to attenuate muscle degradation by the inhibition of inflammation, the UPS, and the apoptosis pathway. Full article

Ground-Level Enhancements (GLEs) pose a potential hazard for crew and passengers on polar routes. The accurate estimation of the integral proton flux of Solar Energetic Particle (SEP) events is crucial for assessing the expected radiation dose. This paper describes a new approach that predicts the occurrence of GLEs and the associated >500 MeV intensity using proton and electron data. The new approach utilizes the Geostationary Operational Environmental Satellites (GOESs) for proton observations and the Advanced Composition Explorer (ACE) satellite for electron observations. Núñez et al. proposed a GLE occurrence predictor called the High Energy Solar Particle Events foRecastIng and Analysis (HESPERIA) University of Málaga Solar particle Event Predictor (UMASEP-500), which did not include a model for predicting the >500 MeV integral proton intensity. This paper presents a comparison in terms of the GLE event occurrence between the HESPERIA UMASEP-500 and a new approach called UMASEP-500. Although the new approach shows a slightly better critical success index (CSI), which combines the probability of detection (POD) and false alarm ratio (FAR), the difference is not statistically significant. The main advantage of the new UMASEP-500 is its ability to predict the expected >500 MeV proton intensity. This study provides initial insight into a new era of electron and proton telescopes that will be available at L1 in the coming years. Full article