An Optimized Instance Segmentation of Underlying Surface in Low-Altitude TIR Sensing Images for Enhancing the Calculation of LSTs.

The calculation of land surface temperatures (LSTs) via low-altitude thermal infrared remote (TIR) sensing images at a block scale is gaining attention. However, the accurate calculation of LSTs requires a precise determination of the range of various underlying surfaces in the TIR images, and existing approaches face challenges in effectively segmenting the underlying surfaces in the TIR images. To address this challenge, this study proposes a deep learning (DL) methodology to complete the instance segmentation and quantification of underlying surfaces through the low-altitude TIR image dataset. Mask region-based convolutional neural networks were utilized for pixel-level classification and segmentation with an image dataset of 1350 annotated TIR images of an urban rail transit hub with a complex distribution of underlying surfaces. Subsequently, the hyper-parameters and architecture were optimized for the precise classification of the underlying surfaces. The algorithms were validated using 150 new TIR images, and four evaluation indictors demonstrated that the optimized algorithm outperformed the other algorithms. High-quality segmented masks of the underlying surfaces were generated, and the area of each instance was obtained by counting the true-positive pixels with values of 1. This research promotes the accurate calculation of LSTs based on the low-altitude TIR sensing images.

Astragaloside IV ameliorates indomethacin-induced intestinal inflammation in rats through inhibiting the activation of NLRP3 inflammasome.

The administration of nonsteroidal anti-inflammatory drugs (NSAIDs) may cause significant intestinal alteration and inflammation and lead to the occurrence of inflammatory diseases resembling duodenal ulcers. Astragaloside IV (AS-IV) is a glycoside of cycloartane-type triterpene isolated from the dried root of Astragalus membranaceus (Fisch.) Bge. (family Fabaceae), and has been used for ameliorating the NSAID-induced inflammation in the small intestine. The present study aimed to investigate the effects of AS-IV on indomethacin (IND)-induced inflammation in the small intestine of rats and its underlying mechanisms. Hematoxylin-eosin (H&E) staining, transmission and scanning electron microscopy were carried out to observe the surface morphology and ultrastructure of the small intestinal mucosa. Immunofluorescence and ELISA tests were employed to detect the expressions of NLRP3, ASC, caspase-1, and NF-κB proteins, as well as inflammatory factors IL-1ß and IL-18, to uncover potential molecular mechanisms responsible for mitigating small intestinal inflammation. The results demonstrated that AS-IV significantly decreased the ulcer index, improved the surface morphology and microstructure of the small intestinal mucosa, and increased mucosal blood flow. Molecular docking revealed a strong and stable binding capacity of AS-IV to NLRP3, ASC, caspase-1, and NF-κB proteins. Further experimental validation exhibited that AS-IV markedly decreased levels of IL-1ß and IL-18, and inhibited the protein expression of NLRP3, ASC, caspase-1, and NF-κB. Our data demonstrate that AS-IV ameliorates IND-induced intestinal inflammation in rats by inhibiting the activation of NLRP3 inflammasome and reducing the release of IL-1ß and IL-18, thereby representing a promising therapy for IND-induced intestinal inflammation.

Enhanced exo-inulinase activity and stability by fusion of an inulin-binding module.

In this study, an inulin-binding module from Bacillus macerans was successfully fused to an exo-inulinase from Kluyveromyces marxianus, creating a hybrid functional enzyme. The recombinant exo-inulinase (rINU), the hybrid enzyme (rINUIBM), and the recombinant inulin-binding module (rIBM) were, respectively, heterologously expressed and biochemically characterized. It was found that both the inulinase activity and the catalytic efficiency (k cat/K m(app)) of the rINUIBM were considerably higher than those of rINU. Though the rINU and the rINUIBM shared the same optimum pH of 4.5, the optimum temperature of the rINUIBM (60 °C) was 5 °C higher than that of the rINU. Notably, the fused IBM significantly enhanced both the pH stability and the thermostability of the rINUIBM, suggesting that the rINUIBM obtained would have more extensive potential applications. Furthermore, the fusion of the IBM could substantially improve the inulin-binding capability of the rINUIBM, which was consistent with the determination of the K m(app). This meant that the fused IBM could play a critical role in the recognition of polysaccharides and enhanced the hydrolase activity of the associated inulinase by increasing enzyme-substrate proximity. Besides, the extra supplement of the independent non-catalytic rIBM could also improve the inulinase activity of the rINU. However, this improvement was much better in case of the fusion. Consequently, the IBM could be designated as a multifunctional domain that was responsible for the activity enhancement, the stabilization, and the substrate binding of the rINUIBM. All these features obtained in this study make the rINUIBM become an attractive candidate for an efficient inulin hydrolysis.