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Structural insights into selective recognition of ATP-mimicking inhibitors by the atypical kinase HASPIN
Design of a slotted bowtie dual-polarized antenna for Sub-6 GHz multi-service wireless applications
A pilot study of the effect of norepinephrine dose on left ventricular-arterial coupling in patients with septic shock
A comparative study of machine learning models for microbiome-based diagnosis and multi-class staging of colorectal cancer
Saltation-consistent event-aware digital twins for uncertainty transport in non-smooth dynamical systems
Replacing fish oil with Tetraselmis chui microalgae biomass does not compromise rainbow trout health: Biochemical, histologic, antioxidant and immune gene expression
Abstract Microalgae offer a nutritionally robust alternative to fishmeal and fish oil, helping reduce pressure on wild stocks and supporting more sustainable aquafeed production. This study explored the potential of replacing fish oil with Tetraselmis ( Tetraselmis chui ) microalgae biomass in the diet of juvenile rainbow trout (89.0 ± 1.10 g) ( Oncorhynchus mykiss ), assessing its effects on the fish’s health. A control diet containing 53% crude protein and fish oil (FO) was modified by replacing FO with Tetraselmis at three graded inclusion levels: 33% (Tetra33), 66% (Tetra66), and 100% (Tetra100). The 84-day feeding trial evaluated key growth parameters, biochemistry, liver and intestinal histo-architectures, and immune-antioxidant gene expression profiles of the experimental fish. Time-series analyses of growth performance revealed no significant treatment effects from day 14 to day 70, except at the 84-day biomass sampling. The FO (7321.65 ± 60.03g) attained a significantly greater final weight (FW) than Tetra33 (6984.70 ± 86.15g) and Tetra100 (6823.93 ± 160.42g), while remaining statistically similar to Tetra66 (7051.77 ± 107.30g). Likewise, weight gain (WG) of the FO group (5519.65 ± 57.16g) exceeded that of the Tetra100 group (5043.93 ± 142.09g) but did not differ significantly from the Tetra33 (5220.70 ± 73.95g) and Tetra66 (5281.77 ± 110.86g). The feed conversion ratios (FCRs) and specific growth rates (SGRs) of the Tetra groups were comparable to the FO control. Dietary variation did not elicit significant changes in leukocyte distribution, biochemical indices, or gene expression patterns across Tetra groups relative to the FO. Similarly, the histological analysis revealed that Tetraselmis dietary inclusions did not trigger inflammatory reactions in hepatic or intestinal tissues in the Tetra groups compared to the FO. Minor but inconsequential histological modifications were noted, such as moderated sinusoid dilation in the liver and slight changes in intestinal villi of Tetra33 fish. Health biomarker analyses indicated that replacing fish oil with Tetraselmis preserved physiological homeostasis, whereas 66% replacement (Tetra66) yielded the best growth performance compared to FO. However, longer feeding trials are necessary to confirm long-term health and nutritional outcomes.
Accurate alpha-particle stopping power measurements in graphenic carbon foils and their application to high-precision, non-destructive areal density determination
Abstract A precise, non-destructive method for determining the areal density of thin graphenic carbon (GC) foils via alpha-particle energy loss is presented. Two types of GC foils — sourced from KETEK GmbH and Applied Nanotech Inc. — were investigated using a three-isotope mixed alpha source emitting particles in the 5.0–5.8 $$\textrm{MeV}$$ range. Both foils have similar nominal areal densities of approximately $$0.2\,\mathrm {mg\,cm^{-2}}$$ , but differ slightly in chemical composition and microstructure. High-resolution alpha spectroscopy yielded energy-loss measurements with relative uncertainties below 1%. The uncertainty of the extracted areal densities and stopping powers is dominated by the determination of foil mass, area and composition metrology, rather than by the alpha-energy-loss measurement itself. Experimental stopping powers were obtained by combining the measured energy loss with independently determined foil masses and areas, and were compared with established stopping-power models. A modified Bethe formalism incorporating Barkas and Bloch corrections, together with an empirically adjusted mean excitation energy $$I_\textrm{adj}$$ , provided the most consistent description of the data across the investigated energy range. The resulting values were $$(73 \pm 2)\,\textrm{eV}$$ for the KETEK foil and $$(85 \pm 3)\,\textrm{eV}$$ for the Applied Nanotech foil. The fitted stopping-power curves indicate a systematic difference between the two GC foils, consistent with their differing compositions and microstructures. Because the stopping-power model is calibrated against the same reference foils, however, this interpretation is model-dependent and requires further validation using independently characterised samples. While the method is well suited to thin foils, angular straggling and the non-linear energy dependence of the stopping power may limit its applicability beyond the thin-target approximation. The reported stopping-power data are relevant for benchmarking Monte Carlo simulations and modelling energy deposition in carbon-based materials, with applications in accelerator technology and radiopharmaceutical research. In medical physics, stopping power is closely related to linear energy transfer, which governs the biological effectiveness of alpha-emitting isotopes in targeted therapies.
Preclinical assessment of Preserflo MicroShunt implantation using an intraocular endoscope-holding robot
RTEDAP framework for real-time event-driven data aggregation and processing in tsunami early warning systems
Hybrid control structure employing fuzzy-sliding mode systems for the guidance of coaxial octorotor UAV
A cyanobacteria-mediated TiO₂ nanoparticle and propolis cream enhances antifungal activity and wound healing against Candida albicans in mice
Fourier spatial attention guided diffusion model for optimizing exposure inconsistencies in endoscopic images
Abstract Endoscopic imaging faces challenges from complex anatomical structures, limited illumination angles, and variable environmental factors, which lead to inconsistent exposure and degrade image quality and diagnostic accuracy. To address this issue, we propose FSADiff, a Fourier spatial attention guided diffusion model that integrates global frequency modeling in the Fourier domain and spatial additive attention during the inverse diffusion process to jointly address the problem of inconsistent exposure. Specifically, Fourier transform computes global correlations in the frequency domain through element-wise multiplication, enabling effective capture of overall exposure deviations. An additive attention branch then adaptively modulates the frequency-domain results in the spatial domain to suppress local degradations. In addition, we introduce a dynamic noise embedding strategy that leverages a knowledge-aware network to incorporate temporal noise information into both the denoising network and the color corrector model, thereby improving image restoration performance. We evaluate FSADiff on public datasets, Endo4IE and Endovis17, as well as a proprietary multicenter clinical nasopharyngeal dataset. FSADiff achieved superior results, yielding a Peak Signal-to-Noise Ratio of 29.00 on Endo4IE and 33.27 on Endovis17 (all 6.5+ improvement over state-of-the-art). On the clinical nasopharyngeal dataset, FSADiff achieved a Blind / Referenceless Image Spatial Quality Evaluator score of 39.17 (7.02 improvement over state-of-the-art). Further evaluation on image subsets from three hospitals demonstrated significant improvements in both overall and individual quality metrics ( p < 0.05).
Predictors of spinal cord injury in patients with traumatic spinal fractures: a prospective cohort study
Prediction of refracture risk after osteoporotic vertebral compression fracture surgery using the vertebral bone quality index from multi-sequence MRI
Microbial biotransformation of Syzygium australe modifies metabolomic profile assessed with multivariate analysis and molecular networking: In vitro and computational studies
Abstract Syzygium australe , a comparatively less studied species within the Syzygium genus, is emerging as a prospective source of bioactive phytochemicals. In this study, the impact of microbial biotransformation by Aspergillus niger on the metabolomic and bioactivity profiles of S. australe leaves extract (SAE) was evaluated. UPLC-T-TOF-MS/MS and molecular networking enabled the tentative identification of 80 metabolites in SAE, with flavonoids emerging as the dominant phytoconstituents. After biotransformation, sulfated flavonoids are the main metabolites in S. australe biotransformed extract (SABE), suggesting that enzymatic sulfonation is mediated by fungal sulfotransferase enzymes. Molecular networking revealed two key clusters: cluster A, which is primarily composed of quercetin derivatives, and cluster B, which corresponded to syringetin. Notably, the biotransformed metabolites in SABE were predominantly observed as self-looped nodes, indicating the formation of structurally unique compounds. Multivariate chemometric analyses revealed a significant metabolomic modulation and a clear discrimination between SAE and SABE. Compared with SABE, SAE significantly increased the free radical scavenging capacity, as evidenced by lower IC₅₀ values in DPPH and ABTS assays (36.96 ± 1.20 and 19.80 ± 0.85 µ g/mL respectively), which is likely a consequence of tannin degradation during microbial biotransformation. The bioactivity of SABE, particularly against pancreatic lipase, was enhanced, with an inhibition rate of 74.49 ± 4.80% at 100 µ g/mL. Molecular docking further supported these findings, highlighting isorhamnetin-3- O -sulfate as a key bioactive constituent with the highest binding affinity to pancreatic lipase (ΔG = − 12.47 kcal/mol). These findings highlight a significant potential and warrant further investigation using alternative microbial strains aiming to develop novel therapeutic agents.
Host-parasite interactions between Acrididae (Orthoptera: Caelifera) and Parasitengona (Acari: Trombidiformes) in the southwestern Zagros Mountains, Iran
Abstract Parasitengona mites (Acari: Trombidiformes) are common parasites of Orthoptera. Yet, we have limited knowledge on host-parasite interactions between these groups. Hence, in this study we investigate the interactions between these mites and their Acrididae hosts in the southwestern Zagros Mountains (Iran). Sampling was conducted at 22 stations, four times across two consecutive years (2020–2021). A total of 5,344 mite larvae were collected from 2,370 grasshoppers, representing 48 species, of which 1,137 individuals (48%) were parasitized. The mean number of mites per infested individual was 4.7; the maximum infestation observed was 103 Eutrombidium cf. trigonum larvae on Calliptamus barbarus . The most abundant mite species was E. sorbasiensis (4,282 larvae; 80%). Parasitism was sex-biased, with females more frequently infested than males (52% vs. 43%), likely due to larger body size. Mites exhibited preferences for specific attachment sites on their hosts, varying by mite species and host grooming behavior. Bipartite network analysis revealed a moderate degree of host specialization (H2′ = 0.38), and individual specialization indices (d′) indicated that most mite species were generalists. These findings suggest that while mites exploit a wide host range, infestation pressure is unevenly distributed and shaped by host traits, attachment-site preferences, and habitat quality, highlighting the importance of ecological and evolutionary factors in shaping host-parasite interactions.