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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.