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Pectin is a major constituent of the plant cell wall. Pectate lyase (PEL, EC 4.2.2.2) uses anti-β-elimination chemistry to cleave the α-1,4 glycosidic linkage in the homogalacturonan region of pectin. However, limited information is available on the comprehensive and evolutionary analysis of PELs in the Malvaceae. In this study, we identified 597 PEL genes from 10 Malvaceae species. Phylogenetic and motif analyses revealed that these PELs are classified into six subfamilies: Clades I, II, III, IV, Va, and Vb. The two largest subfamilies, Clades I and II, contained 237 and 222 PEL members, respectively. The members of Clades Va and Vb only contained four or five motifs, far fewer than the other subfamilies. Gene duplication analysis showed that segmental duplication played a crucial role in the expansion of the PEL gene family in Gossypium species. The PELs from Clades I, IV, Va, and Vb were expressed during the fiber elongation stage, but nearly all PEL genes from Clades II and III showed no expression in any of the investigated fiber developmental stages. We further performed single-gene haplotype association analysis in 2,001 G. hirsutum accessions and 229 G. barbadense accessions. Interestingly, 14 PELs were significantly associated with fiber length and strength traits in G. barbadense with superior fiber quality, while only eight GhPEL genes were found to be significantly associated with fiber quality traits in G. hirsutum. Our findings provide important information for further evolutionary and functional research on the PEL gene family members and their potential use for fiber quality improvement in cotton.

Automated Aerial Triangulation (AAT), aiming to restore image poses and reconstruct sparse points simultaneously, plays a pivotal role in earth observation. AAT has evolved into a fundamental process widely applied in large-scale Unmanned Aerial Vehicle (UAV) based mapping. However classic AAT methods still face challenges like low efficiency and limited robustness. This paper introduces DeepAAT, a deep learning network designed specifically for AAT of UAV imagery. DeepAAT considers both spatial and spectral characteristics of imagery, enhancing its capability to resolve erroneous matching pairs and accurately predict image poses. DeepAAT marks a significant leap in AAT’s efficiency, ensuring thorough scene coverage and precision. Its processing speed outpaces incremental AAT methods by hundreds of times and global AAT methods by tens of times while maintaining a comparable level of reconstruction accuracy. Additionally, DeepAAT’s scene clustering and merging strategy facilitate rapid localization and pose determination for large-scale UAV images, even under constrained computing resources. The experimental results demonstrate that DeepAAT substantially improves over conventional AAT methods, highlighting its potential for increased efficiency and accuracy in UAV-based 3D reconstruction tasks. To benefit the photogrammetry society, the code of DeepAAT will be released at: https://github.com/WHU-USI3DV/DeepAAT.

Cotton fiber, the mainstay of the world’s textile industry, is formed by the differentiation of epidermal cells on the outer peridium of the ovule. The TBL gene family is involved in the regulation of epidermal hair development as well as response to abiotic stress. However, the function of TBL genes in cotton has not been systematically studied yet. Here, we identified 131 and 130 TBL genes in TM-1 (Gossypium hirsutum) and Hai7124 (Gossypium barbadense), respectively. Phylogenetic, gene structure, expression pattern and cis-element of promoter analysis were performed and compared. Single gene association analysis indicated that more TBL genes related to fiber quality traits were found in G. barbadense, whereas more genes associated with yield traits were found in G. hirsutum. One gene, GhTBL84 (GH_D04G0930), was induced by treatment at 4°C for 12 and 24 h in G. hirsutum and silencing of the GhTBL84 gene by VIGS technology in TM-1 can significantly improve the resistance of cotton seedlings to low temperature stress. In sum, our study conducted a genome-wide identification and comparative analysis of TBL family genes in G. hirsutum and G. barbadense and demonstrated a group of TBL genes significantly associated with fiber quality and excavated cold stress responsive gene, such as GhTBL84, providing a theoretical basis for further improving cotton agronomic traits.

The objective of this study was to evaluate whether RSV inhibits neutrophil extracellular traps (NETs) that induce joint hyperalgesia in C57BL/6 mice after adjuvant-induced arthritis. A subplantar injection of Freund's complete adjuvant was administered to C57BL/6 mice on day 0 for immunization in the AIA model. Resveratrol (RSV, 25 mg/kg) was administered intraperitoneally once daily starting on day 22 and continuing for two weeks. The effects of mechanical hyperalgesia and edema formation have been assessed in addition to histopathological scoring. Mice were sacrificed on day 35 to determine cytokine levels and PADI4 and COX-2 expression levels. ELISA was used to quantify neutrophil extracellular traps (NETs) along with neutrophil elastase-DNA and myeloperoxidase-DNA complexes in neutrophils. An immunohistochemical stain was performed on knee joints to determine the presence of nuclear factor kappa B p65 (NF-κB p65). AIA mice were found to have higher levels of NET in joints and their joint cells demonstrated an increased expression of the PADI4 gene. Treatment with RSV in AIA mice (25 mg/kg, i.p.) significantly (P<0.05) inhibited joint hyperalgesia, resulting in a significant increase in mechanical threshold, a decrease in articular edema, a decrease in the production of inflammatory cytokines, increased COX-2 expression, and a decrease in the immunostaining of NF-κB. Furthermore, treatment with RSV significantly reduced the amount of neutrophil elastase (NE)-DNA and MPO-DNA complexes, which were used as indicators of NET formation (P<0.05). This study indicates that RSV reduces NET production and hyperalgesia by reducing inflammation mediated by PADI4 and COX-2. According to these data, NETs contribute to joint pain and resveratrol can be used to treat pain in RA through this pathway. [ABSTRACT FROM AUTHOR]