Search Results (31,307)

Faecal egg counts (FECs) are used to assess the intensity of gastrointestinal nematode (GIN) infections in herbivores. FEC distribution is aggregated, meaning that approximately 20% of animals harbour 80% of infections. In times of escalating anthelmintic resistance, it may be necessary to restrict treatment to the animals with the heaviest infections. This strategy is called targeted selective treatment (TST) and is relevant to GIN, for example. The difficulty lies in identifying which animals to treat. One solution is to select potentially at-risk animals based on age (for example, treating the young) or to perform individual faecal egg counts (though this is costly). We propose a solution for determining the suitability of selective treatment based on the level of FEC (200 or 500 eggs per gram of faeces). First, we demonstrated that the mean FEC in a group is strictly related to its variance (Taylor’s power law) using published data and our own unpublished data on horses from France, Poland, and Mexico. The study focused on small and large strongyles in horses. Taylor’s power law states that sample variance (Var) and the population mean are related by a simple equation: Var = a Mean^b or log(Var) = log(a) + b log(Mean). The influence of factors such as age, status (mare, stallion, yearling, etc.), day-to-day variability, and previous anthelmintic treatments did not alter this relationship. To reduce the number of FECs, we estimated the mean FEC on a composite faecal sample. We then calculated the variability and therefore the number of horses with an FEC above the chosen acceptable level. When the mean is high, the number of horses to be treated is also high and TST is not beneficial. When the FEC is average, TST may be worthwhile, either based on the FEC of individual horses or on the horse class at risk. Based on the percentage of horses with an FEC above the acceptable level, farmers can decide whether to treat all animals or establish a TST protocol. Caution should be exercised when using TST in the presence of large strongyles. Full article

We quantify the transmission and absorption of 75–110 GHz radiation through ex vivo porcine skin. Millimeter waves are currently used in a range of technologies, including communication systems, fog-penetrating radar, and the detection of hidden weapons or drugs. They have also been proposed for use in non-lethal weaponry and, more recently, in targeted cancer therapies. Since pigs are often used as biological models for humans, determining how deeply millimeter waves penetrate a pig’s skin and influence the underlying tissues is essential for understanding their potential effects on humans. This experimental study aims to quantify that penetration and associated energy loss. The results show significant absorption in the skin and fat layer. Attenuation of over three orders of magnitude can be expected in penetration through a layer with a thickness of about 12 mm (−30 dB). The reflectance from the skin is similar at all frequencies. The values range from −10 to −20 dB, which probably depends on the texture of the skin. Therefore, most skin transfer loss is caused by absorption. Full article

In the global wave of energy transition, ground-source heat pump (GSHP) systems are widely adopted for their ability to efficiently provide space heating and cooling. By utilizing stable shallow geothermal energy, these systems significantly reduce operational energy consumption in buildings, playing a crucial role in enhancing building energy efficiency and achieving low-carbon strategies. However, large-scale ground heat exchanger (GHE) clusters with non-identical circuits often face hydraulic and thermal imbalances, leading to degraded system performance. This study investigates the hydraulic and thermal behavior of a large-scale GHE system in Shandong Province, China. Hydraulic and thermal models are first developed based on Kirchhoff’s laws and the principle of energy conservation, and then used to simulate and analyze the influence of the number and depth of boreholes on hydraulic and thermal conditions. The results indicate that the flow imbalance rate and pipe length ratio follows a power-law relationship, δ_f = a (L_v/h)^{^b} + d, with fitted coefficients, a = 0.0677–0.1294, b = −0.7086 to −1.0805, d = 0.0036–0.0921, while the heat exchange imbalance rate follows a linear relationship, δ_q = kδ_f + o, with k = 0.0906–0.265 and o = 0.0028–0.0039. Increasing the number of boreholes or decreasing depth exacerbates flow imbalance (10–58%), but soil thermal resistance dominates, limiting the increase in the heat exchange imbalance rate (2.2–9%). The formula and the quantitative relationship proposed in this paper aim to provide guidance for the engineering design of large-scale non-identical circuit GHE clusters. Full article

Background: The development of Multi-Target-Directed Ligands (MTDLs) has emerged as a significant strategy for addressing complex, overlapping pathologies such as cancer and Alzheimer’s disease (AD). This study aims to provide a robust computational framework for the design of dual-target inhibitors. Methods: This study presents an integrated and rigorous computational pipeline combining Quantitative Structure–Activity Relationship (QSAR) modeling, Molecular Docking, and Molecular Dynamics (MD) simulations with Dynamic Cross-Correlation Matrix (DCCM) analysis. Using a dataset of 57 known tubulin inhibitors, two high-performing QSAR models were developed to guide the rational design of 16 novel trimethoxyphenyl-based analogues. Results: Following ADMET and drug-likeness filtering, Lead Candidates 15 and 16 were identified. Quantitative activity predictions confirmed their enhanced potency thresholds, which were subsequently validated through static docking against β-tubulin (PDB: 4O2B) and Acetylcholinesterase (PDB: 1EVE). In total, 100 ns MD simulations and MM-GBSA calculations demonstrated superior binding stability and energetically favorable profiles for both targets, while DCCM analysis confirmed the functional synchrony of the protein–ligand complexes. Conclusions: The results provide a validated structural hypothesis for dual-target inhibition. The identified leads, 15 and 16, demonstrate strong predictive potential and are prioritized for chemical synthesis and in vitro biological evaluation. Full article

The European Air Quality Directive defines benzo(a)pyrene as the chemical index for polycyclic aromatic hydrocarbon (PAH) carcinogenicity and sets a limit for its concentration in PM₁₀ to address the exposure risk associated with the class. It also mandates monitoring six additional PAHs at a limited number of selected sites to assess the benzo(a)pyrene’s contribution to the class in ambient air. For this aim, as part of the “Reti Speciali” project, benzo(a)pyrene and seven other PAHs were measured at 10 urban sites across Italy in 2016–2019, and the spatial and temporal pattern of these compounds were analyzed to evaluate benzo(a)pyrene’s effectiveness in representing the carcinogenicity of the entire PAH class. Results showed that in Italy, benzo(a)pyrene accounted for 61% ± 4.4% of total carcinogenicity when benzo(a)anthracene, benzo(b)fluoranthene, benzo(k)fluoranthene, dibenzo(a-h)anthracene, and indenopyrene were considered, and about 1% less when chrysene and benzo(ghi)perylene were also added. This value varies by site (from 51% ± 11% in Taranto to 66% ± 7.5% in Cosenza) and decreases in summer due to benzo(a)pyrene’s strong photochemical degradation. In Europe, this percentage is generally similar or lower. For instance, in the United Kingdom, across 24 urban sites, it averages 56% ± 2.9%. These findings suggest that benzo(a)pyrene does not represent the overall carcinogenicity of PAHs nor a constant percentage, highlighting the need to further investigate the use of benzo(a)pyrene as the sole marker of PAH toxicity. Full article

Background: Alzheimer’s disease (AD) is a multifactorial neurodegenerative disorder and the leading cause of dementia worldwide. Progressive synaptic dysfunction underlies declines in cognition, daily functioning, and the development of neuropsychiatric syndromes. Neuropsychiatric syndromes that include agitation and aggression affect 40–60% of patients and represent a major source of caregiver burden. Serotonin 5-HT_2B receptor levels are increased in the AD patient brain, and thus, treatment of AD animal models with the selective 5-HT_2B receptor antagonist MW073 in prevention or disease stage paradigms attenuates Aβ- or tau-induced dysfunction. Methods: We investigated the effects of MW073 treatment on the aggressive behavior of Tg2576 mice in a resident–intruder assay. Results: MW073 treatment significantly reduced aggressive behavior in male Tg2576 mice. Conclusions: MW073 efficacy in treating aggression in Tg2576 mice implicates 5-HT_2B receptor-mediated signaling in AD neuropsychiatric symptoms as well as cognitive and behavioral dysfunction. Full article

Background/Objectives: Alzheimer’s disease (AD) exhibits marked genetic heterogeneity between early-onset (EOAD) and late-onset (LOAD) forms. EOAD is typically associated with highly penetrant variants, whereas LOAD follows a polygenic architecture dominated by non-coding variation. However, the tissue-specific regulatory consequences of these variants remain insufficiently characterized. This study aimed to compare the regulatory genomic architectures underlying EOAD and LOAD using a multi-tissue integrative approach. Methods: GWAS-associated variants for EOAD and LOAD were retrieved from the GWAS Catalog using a relaxed significance threshold (p < 1 × 10⁻⁵). Variants were functionally annotated and integrated with GTEx v8 eQTL data across 13 neurologically relevant tissues and peripheral blood. Regulatory effects were evaluated using eQTL slope estimates. Basal gene expression patterns were assessed using GTEx RNA-seq data, and protein–protein interaction and functional enrichment analyses were performed using the STRING database. Results: A total of 287 variants were analyzed (32 EOAD, 255 LOAD), with minimal overlap. EOAD exhibited a highly focal regulatory profile, identifying GSE1 as the sole eQTL-regulated gene, restricted to the dorsolateral prefrontal cortex (BA9). In contrast, LOAD displayed a broad multi-tissue regulatory architecture involving APH1B, APOE, CEP63, and HAVCR2, with heterogeneous tissue-specific effects. LOAD-regulated genes converged on pathways related to γ-secretase activity, amyloid precursor protein processing, and Notch signaling, whereas GSE1-associated interactions were enriched for chromatin organization and epigenetic repression. Conclusions: EOAD and LOAD exhibit distinct regulatory genomic architectures, with EOAD characterized by focal, region-specific regulation and LOAD by widespread, tissue-dependent effects, highlighting stage-specific molecular mechanisms contributing to AD heterogeneity. Full article

Background: Children with special healthcare needs (CSHCNs) face persistent barriers to timely immunization in China, but comparative evidence across disease groups and vaccines, and data on immune function, are limited. Methods: We conducted a retrospective cohort study linking electronic medical records, vaccination records, and a structured telephone and questionnaire follow-up. We estimated timely vaccination by National Immunization Program (NIP) dose definitions, assessed catch-up completion at follow-up, and compared cellular/humoral/complement immune indices with published pediatric reference ranges. Group differences used ANOVA/Kruskal–Wallis and chi-square (χ²)/Fisher’s exact tests with Bonferroni correction. Results: Timely vaccination was lower than the national healthy child benchmarks for all NIP vaccines (all p < 0.001); the Japanese encephalitis virus (JE; 24.0%) and measles-containing vaccine (MCV; 25.9%) had the lowest timely completion. A subset of CSHCNs did not receive recommended catch-up vaccinations, primarily due to persistent caregivers’ concern and point of vaccination (POV) staff’s hesitancy. Delays clustered in neonatal/perinatal disorders for Bacillus Calmette–Guérin (BCG) and hepatitis B vaccine, dose 1 (HepB1). Catch-up completion was highest for hepatitis B vaccine, dose 3 (HepB3) (86.3%) and BCG (81.8%), and lowest for the diphtheria and tetanus vaccine (DT) (49.4%); MCV2 completion was particularly low in hematological diseases. Immunoglobulin A (IgA) and immunoglobulin G (IgG) concentrations were significantly lower in neonatal/perinatal disorders and infectious disease groups versus neurological and immune disorder groups (p < 0.05). No severe adverse events were reported after catch-up. Conclusions: CSHCNs in China face substantial barriers to timely NIP immunization. Timeliness and catch-up vary substantially by vaccine and underlying condition; neonatal/perinatal disorders contribute disproportionately to early-life delays. Disease-specific guidance, strengthened POV–specialist clinic coordination, immunological monitoring, and supportive policies could improve the vaccination coverage and effectiveness in this vulnerable population. Full article

With the rapid development of multi-modal large models, the Visual–Language–Action (VLA) model has gradually become a new paradigm for autonomous robot operations. The VLA model encodes experimental images and text instructions separately using an image encoder and a text encoder. The encoded multi-modal vector information is then fed into a large language model (LLM) to generate the next action. While they inherit the generalization capabilities of large language models, VLA models often struggle to ensure accuracy and reliability in complex scenes. Some studies have attempted to improve VLA performance by enhancing the fine-tuning process or introducing staged operations; however, these improvements often overlook the stable extraction of important visual features, which are crucial for VLA models. In typical VLA tasks, the instruction text inherently contains semantic information related to image elements. Research has shown that leveraging text supervision for visual feature extraction can enhance feature quality. In this paper, we propose a semantically supervised visual encoder called SeDINO (Semantically Supervised DINO), which efficiently fuses DINO’s element localization capabilities with CLIP’s semantic information. We further employ an MLP (Multi-Layer Perceptron) network to align the semantic vectors output by the CLIP text encoder with the image feature vectors derived from DINO, fully leveraging DINO’s element localization and CLIP’s semantic interaction capabilities. We validate SeDINO on six mainstream image datasets, and it demonstrates superior segmentation performance compared to current leading models. Additionally, we incorporate the proposed SeDINO into the VLA framework, using OpenVLA-7B and DINOv2-base as backbone models, and evaluate it on the LIBERO dataset and real-world scenarios. Full article

Riemerella anatipestifer (R. anatipestifer) is a pathogenic bacterium belonging to the genus Riemerella within the family Flavobacteriaceae, which has multidrug resistance (MDR) and can cause high pathogenicity in waterfowl. The aim of this study was to investigate the antimicrobial resistance and genomic characteristics of R. anatipestifer strains isolated from several regions of China from 2023 to 2024. Two strains were selected for challenge tests, and virulence protection tests were conducted on florfenicol-resistant and florfenicol-sensitive strains. A total of 88 strains of R. anatipestifer were collected from the Shandong, Jiangsu, Guangdong, Hebei and Henan regions. The results showed that the 88 strains included serotypes 1, 2, 5, 6, 7 and 10. Serotype 5 was the most prevalent in the Shandong region. All strains were multidrug-resistant, with the hexaresistance accounting for the highest proportion (42.1%). A total of five resistance genes (tet(X), floR, ermF, qnrS, rmtB) and seven virulence genes were found (ompA, camp, AS87_04050, SIP, Fur, TbdR1, luxE). The challenge test showed that the LD₅₀ of RA12 was 2.75 × 10⁷ CFU/mL, and that of RA26 was 2.57 × 10⁷ CFU/mL. Phylogenetic tree analysis revealed that strain RA26 was closely related to strain 20190403E1-1, and strain RA16 was closely related to strain JW1. In addition, serotypes 2 and 7 identified in this study have been undergoing clonal transmission in China. Virulence protection tests indicated that the results of in vitro drug susceptibility tests were consistent with the therapeutic effects after in vivo treatment, and no R. anatipestifer was found in the visceral tissues of surviving ducklings. This study provides a reference for the rational use of antibiotics. Full article

Although Simarouba glauca DC. has been recognized for its therapeutic properties, its anticancer effects against oral cancer have not been adequately investigated. The present study aimed to evaluate the activity of S. glauca leaf extracts against oral squamous cell carcinoma (OSCC). S. glauca leaves were extracted using solvents of increasing polarity, and the resulting fractions were evaluated for their phytochemical composition, antioxidant activity, and cytotoxic effects. Among all extracts, the S. glauca hexane extract (SGHE) exhibited the most potent anticancer activity against cell lines representing OSCC (CAL-27), cervical cancer (HeLa), and mouse mammary tumors (4T1). Bioactivity-guided fractionation identified D-erythro-Sphinganine as a major constituent present in hexane extract, possibly contributing to anticancer activity. But since the anticancer activity of crude hexane extract is superior compared to isolated D-erythro-Sphinganine, we predict a synergistic interaction among the multiple bioactive compounds present in the crude hexane extract. Hence, further studies were carried out with crude hexane extract. Mechanistic studies have shown that the anticancer activity of hexane extract is due to its ability to (a) alter cell cycle progression, (b) trigger apoptosis, and (c) inhibit cell migration in CAL-27 cells. Overall, these findings indicate that the hexane extract of S. glauca leaf possesses multi-target anticancer potential and warrants further mechanistic and in vivo investigations. Full article

Kolmogorov–Arnold Networks employ learnable univariate activation functions on edges rather than fixed node nonlinearities. Standard B-spline implementations require $O\left(3KW\right)$ parameters per layer (K basis functions, W connections). We introduce shared Gaussian radial basis functions with learnable centers ${\mu }_k^{\left(l\right)}$ and widths ${\sigma }_k^{\left(l\right)}$ maintained globally per layer, reducing parameter complexity to $O(KW+2LK)$ for L layers—a threefold reduction, while preserving Sobolev convergence rates $O\left(h^{s-\Omega }\right)$. Width clamping at ${\sigma }_{min}={10}^{-6}$ and tripartite regularization ensure numerical stability. On MNIST with architecture $[784,128,10]$ and $K=5$, RBF-KAN achieves $87.8\%$ test accuracy versus $89.1\%$ for B-spline KAN with $1.4\times$ speedup and 33% memory reduction, though generalization gap increases from $1.1\%$ to $2.7\%$ due to global Gaussian support. Physics-informed neural networks demonstrate substantial improvements on partial differential equations: elliptic problems exhibit a $45\times$ reduction in PDE residual and maximum pointwise error, decreasing from $1.32$ to $0.18$; parabolic problems achieve a $2.1\times$ accuracy gain; hyperbolic wave equations show a $19.3\times$ improvement in maximum error and a $6.25\times$ reduction in $L^2$ norm. Superior hyperbolic performance derives from infinite differentiability of Gaussian bases, enabling accurate high-order derivatives without polynomial dissipation. Ablation studies confirm that coefficient regularization reduces mean error by 40%, while center diversity prevents basis collapse. Optimal basis count $K\in [3,5]$ balances expressiveness and overfitting. The architecture establishes Gaussian RBFs as efficient alternatives to B-splines for learnable activation networks with advantages in scientific computing. Full article

Heteroatom functionalization of graphene is an effective strategy for designing more sustainable lithium-ion battery electrodes, as it can tune both interfacial adhesion and the electronic features of the carbon lattice. In this work, we investigated the interfacial compatibility between three graphene sheets—pristine graphene, graphene doped with one nitrogen atom (Graphene–N), and graphene doped with one sulfur atom (Graphene–S)—and three lignocellulosic binders (carboxymethylcellulose (CMC); coniferyl alcohol (LcnA); and sinapyl alcohol (LsiA)) using density functional theory (DFT). Geometries were optimized using CAM-B3LYP and M06-2X in combination with the LANL2DZ basis set, while ωB97X-D/LANL2DZ was employed for dispersion-consistent single-point refinements. The computed adsorption energies indicate that all binder–surface combinations are thermodynamically favorable within the present finite-model framework (ΔE_int ≈ −22.6 to −31.1 kcal·mol⁻¹), with LSiA consistently showing the strongest stabilization across surfaces. Nitrogen doping produces a modest but systematic strengthening of adsorption relative to pristine graphene for all binders and is accompanied by electronic signatures consistent with localized donor/basic sites while preserving the delocalized π framework. In contrast, sulfur doping yields a more binder-dependent response: it maintains strong stabilization for LSiA but weakens LCnA relative to pristine/N-doped sheets, consistent with an S-induced local distortion/polarizability pattern that can alter optimal π–π registry depending on the adsorption geometry. A combined interpretation of adsorption energies, electronic descriptors (including ΔE_gap as a model-dependent HOMO–LUMO separation), and topological analyses (AIM, ELF, LOL, and MEP) supports that Graphene–N provides the best overall balance between electronic continuity and chemically active interfacial sites, whereas Graphene–S can enhance localized anchoring but introduces more heterogeneous, lone-pair–dominated domains that may partially perturb electronic connectivity. Full article

Brown adipose tissue (BAT) plays a key role in non-shivering thermogenesis and is a promising target for enhancing energy expenditure to combat obesity. Soluble epoxide hydrolase (sEH) is a cytosolic enzyme that catalyzes the conversion of epoxy fatty acids into less active diols. We have reported that local administration of the sEH inhibitor, t-TUCB, to the endogenous interscapular BAT (iBAT) of diet-induced obese mice decreased serum triglycerides and enhanced the expression of essential genes associated with lipid metabolism. Here, the effects of sEH inhibition by t-AUCB were assessed on human brown adipocyte (HuBr) differentiation and in nude mice transplanted with t-AUCB-treated HuBr. HuBr cells were differentiated with t-AUCB (1–10 µM) or the vehicle (0.1% DMSO). HuBr differentiated with t-AUCB at 5 μM (AUCB 5) or DMSO was mixed with matrix gel and transplanted into the nude mice. The mice were then fed a high-fat diet for eight weeks. The mice receiving AUCB 5-treated HuBr exhibited markedly reduced lipid accumulation in the iBAT compared with DMSO or matrix-only controls, along with increased protein expression of thermogenic PGC1α and UCP1, fatty acid transporter CD36, and CPT1A in the iBAT, while the NFκB inflammatory pathways were suppressed in both the AUCB 5 and DMSO groups. Moreover, the PGC1α and CPT1A protein levels were elevated, and the adipocyte sizes were decreased in the epididymal white adipose tissue of the AUCB 5 group. Our findings indicate that the transplantation of HuBr treated with AUCB 5 may stimulate thermogenesis, enhance lipid metabolism, and reduce inflammation in iBAT. Full article

Gun violence in U.S. schools not only causes loss of life and physical injury but also leaves enduring psychological trauma, damages property, and results in significant economic losses. One way to reduce this loss is to detect the gun early, notify the police as soon as possible, and implement lockdown procedures immediately. In this project, a novel gun detector Internet of Things (IoT) system is developed that automatically detects the presence of a gun either from images or from gunshot sounds, and sends notifications with exact location information to the first responder’s smartphones using the Internet within a second. The device also sends wireless commands using Message Queuing Telemetry Transport (MQTT) protocol to close the smart door locks in classrooms and announce to act using public address (PA) system automatically. The proposed system will remove the burden of manually calling the police and implementing the lockdown procedure during such traumatic situations. Police will arrive sooner, and thus it will help to stop the shooter early, the injured people can be taken to the hospital quickly, and more lives can be saved. Two custom deep learning AI models are used: (a) to detect guns from image data having an accuracy of 94.6%, and (b) the gunshot sounds from audio data having an accuracy of 99%. No single gun detector device is available in the literature that can detect guns from both image and audio data, implement lockdown and make PA announcement automatically. A prototype of the proposed gunshot detector IoT system, and a smartphone app is developed, and tested with gun replicas and blank guns in real-time. Full article