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Background Interleukin-8 (IL-8) plays a vital role in the invasion and metastasis of hepatocellular carcinoma (HCC), and is closely associated with poor prognosis of HCC patients. Integrin αvβ3, a member of the integrin family, has been reported to be overexpressed in cancer tissues and mediate the invasion and metastasis of HCC cells. However, the relationship between IL-8 and integrin αvβ3 in HCC and the underlying mechanism of IL-8 and integrin αvβ3 in the invasion of HCC remains unclear. Methods The expression of IL-8, integrin αv and integrin β3 in HCC cells and tissues was detected by quantitative real-time PCR, Western blot and immunohistochemistry. Transwell assay and Western blot was used to detect the invasiveness, the expression of integrin β3 and the activation of PI3K/Akt pathway of HCC cells pretreated with IL-8 knockdown or exogenous IL-8. Results IL-8, integrin αv and integrin β3 were overexpressed in highly metastatic HCC cell lines compared with low metastatic cell lines. There was a positive correlation between integrin β3 and IL-8 expression in HCC tissues. IL-8 siRNA transfection reduced HCC cell invasion and the levels of integrin β3, p-PI3K and p-Akt. IL-8 induced HCC cell invasion and integrin β3 expression was significantly inhibited by transfection with CXCR1 siRNA or CXCR2 siRNA. When we stimulated HCC cells with exogenous IL-8, cell invasion and the levels of integrin β3, p-PI3K, and p-Akt increased, which could be effectively reversed by adding PI3K inhibitor LY294002. Conclusions Our results suggest that IL-8 promotes integrin β3 upregulation and the invasion of HCC cells through activation of the PI3K/Akt pathway. The IL-8/CXCR1/CXCR2/PI3K/Akt/integrin β3 axis may serve as a potential treatment target for patients with HCC.

Several studies have revealed that MFG-E8 (milk fat globule–epidermal growth factor 8) is related to tumour development and progression. However, the relationship between MFG-E8 expression and metastasis in colorectal cancer patients and the role of MFG-E8 in colorectal cancer invasion and progression remain unknown. In this study, we performed immunohistochemistry and quantitative real-time polymerase chain reaction to assess MFG-E8 expression in colorectal cancer and adjacent non-cancerous tissues. Colorectal cancer RNAseq data from The Cancer Genome Atlas project were downloaded and MFG-E8 expression was analysed. Gene set enrichment analysis was performed for gene ontology and pathway analysis associated with MFG-E8 expression. For in vitro studies, we used lentivirus-mediated MFG-E8 RNA interference and commercialized recombinant human MFG-E8 to investigate its role in colorectal cancer cell growth, migration and invasion. It seems that MFG-E8 was overexpressed in advanced colorectal cancer tissues compared with early-stage colorectal cancer tissues and adjacent non-cancerous tissues. Correlation analysis revealed that MFG-E8 expression was significantly related to plasma membrane invasion, lymph node metastasis, distant metastasis and tumour–node–metastasis stage. Survival analysis revealed that high MFG-E8 expression predicted a poorer prognosis than low MFG-E8 expression group both in our colorectal cancer cohort and The Cancer Genome Atlas colorectal cancer cohort. In vitro study suggested that MFG-E8 knockdown can suppress the growth of colorectal cancer cells without affecting the expression of the proliferation-related gene Ki67. MFG-E8 knockdown also suppressed colorectal cancer cell migration and invasion, a change accompanied by MMP-2 and MMP-9 downregulation. Moreover, MFG-E8 knockdown induced a shift from mesenchymal makers to epithelial makers, while pretreatment with rhMFG-E8 had the opposite effect. The effect of MFG-E8 on colorectal cancer cell migration, invasion and epithelial-to-mesenchymal was partially dependent on the PI3K/AKT signalling pathway. These findings provide a better understanding of the molecular mechanism underlying colorectal cancer progression and suggest a predictive role for MFG-E8 in colorectal cancer metastasis and prognosis.

The cylindrical cam conveying system is widely used in automated equipment due to its high motion accuracy. However, traditional designs are prone to instability caused by vibration at high rotational speeds, and the complex contours drive up the manufacturing cost. This paper proposes an innovative design scheme for a cylindrical cam linear conveying system based on the modified sine motion law. By segmentally combining sine and cosine functions, the motion curve of the follower is optimized, significantly reducing the maximum jerk and jump, and improving the dynamic impact characteristics. Combining mathematical modeling with Creo parametric design, the envelope equation of the cam contour is derived, and a three-dimensional model is constructed to achieve rapid and low-cost development. The modal analysis based on Ansys shows that the first six-order natural frequencies (288.27∼1877.9 Hz) of the cylindrical cam are much higher than the working frequency (12 Hz), verifying the structural stability under high-speed operating conditions. Experimental comparisons show that the modified sine law reduces the displacement error by 58.3%, the vibration acceleration by 37.8%, and the peak jerk value by 42.9%. The research proves that this scheme significantly reduces the cost while improving motion accuracy, providing theoretical and practical support for the engineering application of cylindrical cam systems with high dynamic performance.

Background Interleukin-8 (IL-8) plays a vital role in the invasion and metastasis of hepatocellular carcinoma (HCC), and is closely associated with poor prognosis of HCC patients. Integrin [alpha]v[beta]3, a member of the integrin family, has been reported to be overexpressed in cancer tissues and mediate the invasion and metastasis of HCC cells. However, the relationship between IL-8 and integrin [alpha]v[beta]3 in HCC and the underlying mechanism of IL-8 and integrin [alpha]v[beta]3 in the invasion of HCC remains unclear. Methods The expression of IL-8, integrin [alpha]v and integrin [beta]3 in HCC cells and tissues was detected by quantitative real-time PCR, Western blot and immunohistochemistry. Transwell assay and Western blot was used to detect the invasiveness, the expression of integrin [beta]3 and the activation of PI3K/Akt pathway of HCC cells pretreated with IL-8 knockdown or exogenous IL-8. Results IL-8, integrin [alpha]v and integrin [beta]3 were overexpressed in highly metastatic HCC cell lines compared with low metastatic cell lines. There was a positive correlation between integrin [beta]3 and IL-8 expression in HCC tissues. IL-8 siRNA transfection reduced HCC cell invasion and the levels of integrin [beta]3, p-PI3K and p-Akt. IL-8 induced HCC cell invasion and integrin [beta]3 expression was significantly inhibited by transfection with CXCR1 siRNA or CXCR2 siRNA. When we stimulated HCC cells with exogenous IL-8, cell invasion and the levels of integrin [beta]3, p-PI3K, and p-Akt increased, which could be effectively reversed by adding PI3K inhibitor LY294002. Conclusions Our results suggest that IL-8 promotes integrin [beta]3 upregulation and the invasion of HCC cells through activation of the PI3K/Akt pathway. The IL-8/CXCR1/CXCR2/PI3K/Akt/integrin [beta]3 axis may serve as a potential treatment target for patients with HCC. Keywords: Interleukin-8, Integrin [alpha]v[beta]3, Invasion, Hepatocellular carcinoma

In computational molecular and materials science, determining equilibrium structures is the crucial first step for accurate subsequent property calculations. However, the recent discovery of millions of new crystals and super large twisted structures has challenged traditional computational methods, both ab initio and machine-learning-based, due to their computationally intensive iterative processes. To address these scalability issues, here we introduce DeepRelax, a deep generative model capable of performing geometric crystal structure relaxation rapidly and without iterations. DeepRelax learns the equilibrium structural distribution, enabling it to predict relaxed structures directly from their unrelaxed ones. The ability to perform structural relaxation at the millisecond level per structure, combined with the scalability of parallel processing, makes DeepRelax particularly useful for large-scale virtual screening. We demonstrate DeepRelax’s reliability and robustness by applying it to five diverse databases, including oxides, Materials Project, two-dimensional materials, van der Waals crystals, and crystals with point defects. DeepRelax consistently shows high accuracy and efficiency, validated by density functional theory calculations. Finally, we enhance its trustworthiness by integrating uncertainty quantification. This work significantly accelerates computational workflows, offering a robust and trustworthy machine-learning method for material discovery and advancing the application of AI for science. Structure relaxation is an iterative process particularly demanding in large-scale material discovery campaigns. Here, the authors realize a deep generative model able to relax material structures in a single step while estimating its accuracy.

Background Maize seed oil plays a significant role in human nutrition, animal feed, and bioenergy applications. Despite extensive quantitative trait loci (QTL) studies conducted on this trait, the broad confidence intervals of the identified QTLs have made it difficult to precisely pinpoint candidate genes, thereby limiting their practical application in high-oil maize breeding. Results In this study, we integrated QTL data related to maize seed oil content reported over the past two decades, compiling a total of 339 QTLs from 31 studies. By integrating high-density genetic linkage maps, 72 oil content-related meta-QTLs (MQTLs) were identified. Compared with previous studies on seed oil content QTLs, the average confidence interval of the MQTLs was reduced by 5.89-fold. Through colocalization analysis with genome-wide association study (GWAS) marker-trait associations (MTAs), over 60% of the MQTLs were validated by GWAS-MTAs. Additionally, four known functional genes were identified within the MQTL regions, and 44 candidate genes were further uncovered through homologous gene comparison. These genes are likely involved in critical biological processes such as transcriptional regulation (e.g., CADTFR7 ), fatty acid biosynthesis (e.g., Zm00001d036137 ), and material transport (e.g., Zm00001d013817 ), thereby influencing seed oil content accumulation. Conclusions Collectively, these findings provide valuable insights into the genetic regulation of maize seed oil content and offer potential molecular targets for the development of high-oil maize varieties.

Maize seed oil plays a significant role in human nutrition, animal feed, and bioenergy applications. Despite extensive quantitative trait loci (QTL) studies conducted on this trait, the broad confidence intervals of the identified QTLs have made it difficult to precisely pinpoint candidate genes, thereby limiting their practical application in high-oil maize breeding. In this study, we integrated QTL data related to maize seed oil content reported over the past two decades, compiling a total of 339 QTLs from 31 studies. By integrating high-density genetic linkage maps, 72 oil content-related meta-QTLs (MQTLs) were identified. Compared with previous studies on seed oil content QTLs, the average confidence interval of the MQTLs was reduced by 5.89-fold. Through colocalization analysis with genome-wide association study (GWAS) marker-trait associations (MTAs), over 60% of the MQTLs were validated by GWAS-MTAs. Additionally, four known functional genes were identified within the MQTL regions, and 44 candidate genes were further uncovered through homologous gene comparison. These genes are likely involved in critical biological processes such as transcriptional regulation (e.g., CADTFR7), fatty acid biosynthesis (e.g., Zm00001d036137), and material transport (e.g., Zm00001d013817), thereby influencing seed oil content accumulation. Collectively, these findings provide valuable insights into the genetic regulation of maize seed oil content and offer potential molecular targets for the development of high-oil maize varieties.

Maize seed oil plays a significant role in human nutrition, animal feed, and bioenergy applications. Despite extensive quantitative trait loci (QTL) studies conducted on this trait, the broad confidence intervals of the identified QTLs have made it difficult to precisely pinpoint candidate genes, thereby limiting their practical application in high-oil maize breeding. In this study, we integrated QTL data related to maize seed oil content reported over the past two decades, compiling a total of 339 QTLs from 31 studies. By integrating high-density genetic linkage maps, 72 oil content-related meta-QTLs (MQTLs) were identified. Compared with previous studies on seed oil content QTLs, the average confidence interval of the MQTLs was reduced by 5.89-fold. Through colocalization analysis with genome-wide association study (GWAS) marker-trait associations (MTAs), over 60% of the MQTLs were validated by GWAS-MTAs. Additionally, four known functional genes were identified within the MQTL regions, and 44 candidate genes were further uncovered through homologous gene comparison. These genes are likely involved in critical biological processes such as transcriptional regulation (e.g., CADTFR7), fatty acid biosynthesis (e.g., Zm00001d036137), and material transport (e.g., Zm00001d013817), thereby influencing seed oil content accumulation. Collectively, these findings provide valuable insights into the genetic regulation of maize seed oil content and offer potential molecular targets for the development of high-oil maize varieties.

Maize seed oil plays a significant role in human nutrition, animal feed, and bioenergy applications. Despite extensive quantitative trait loci (QTL) studies conducted on this trait, the broad confidence intervals of the identified QTLs have made it difficult to precisely pinpoint candidate genes, thereby limiting their practical application in high-oil maize breeding. In this study, we integrated QTL data related to maize seed oil content reported over the past two decades, compiling a total of 339 QTLs from 31 studies. By integrating high-density genetic linkage maps, 72 oil content-related meta-QTLs (MQTLs) were identified. Compared with previous studies on seed oil content QTLs, the average confidence interval of the MQTLs was reduced by 5.89-fold. Through colocalization analysis with genome-wide association study (GWAS) marker-trait associations (MTAs), over 60% of the MQTLs were validated by GWAS-MTAs. Additionally, four known functional genes were identified within the MQTL regions, and 44 candidate genes were further uncovered through homologous gene comparison. These genes are likely involved in critical biological processes such as transcriptional regulation (e.g., CADTFR7), fatty acid biosynthesis (e.g., Zm00001d036137), and material transport (e.g., Zm00001d013817), thereby influencing seed oil content accumulation. Collectively, these findings provide valuable insights into the genetic regulation of maize seed oil content and offer potential molecular targets for the development of high-oil maize varieties.