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Objective To explore the effects of lncRNA ANCR regulating miR-497-5p on vascular lumen formation, apoptosis and PI3K/AKT signaling pathway of gastric cancer cells. Methods Gastric cancer cells were collected and divided into gastric cancer cell (GC) group, gastric cancer cell +lncRNA ANCR-NC (AN) group, gastric cancer cell + lncRNA ANCR overexpressed plasmid (AM) group, gastric cancer cell + lncRNA ANCR siRNA (AI) group, gastric cancer cells + miR-497-5p-NC (MN) group, gastric cancer cells + miR-497-5p siRNA (MI) group, gastric cancer cells +miR-497-5p mimics (MM) group, and gastric cancer cells + lncRNA ANCR siRNA+miR-497-5p mimics (IM) group. Vascular lumen formation was observed by lumen formation assay, cell apoptosis was detected by PI staining method, and protein expression of PI3K and AKT was detected by western blotting. The interaction between lncRNA ANCR and miR-497-5p was confirmed by double luciferase reporting assay. Results Compared with AN group and MN group, the apoptosis rate of AM group and MI group was significantly decreased (P＜0.05), the number of vascular lumen formation and the expression of PI3K and AKT protein were significantly increased (P＜0.05). Compared with AM and MI groups, the apoptosis rate of AI and MM groups was significantly increased (P＜0.05), while the number of vascular lumen formation and the expression of PI3K and AKT protein were significantly decreased (P＜0.05). Compared with AI and MM groups, the apoptosis rate of IM group was significantly increased (P＜0.05), the number of vascular lumen formation and the expression of PI3K and AKT protein were significantly decreased (P＜0.05). The results of double luciferase report showed that transfection of lncRNA ANCR could significantly reduce the luciferase activity of miR-497-5p-3′-UTR-WT (P＜0.05), but had no significant effect on mutant genes (P＞0.05). Conclusion Inhibition of lncRNA ANCR can effectively inhibit the formation of vascular lumen, promote cell apoptosis, and inhibit the expression of PI3K/AKT signaling pathway in gastric cancer cells, which may be related to the targeted activation of miR-497-5p.

The fusion of hyperspectral and multispectral images presents a challenge as it involves blending a low-resolution hyperspectral image (HSI) with a corresponding multispectral image (MSI) to produce a high-resolution hyperspectral image (HRI). A number of existing techniques have limitations; for instance, matrix decomposition-based approaches fail to retain adequate spatial and spectral image information during fusion, while tensor decomposition-based processes have high computational overhead. In this paper, we propose a novel method for fusing hyperspectral and multispectral images. Our method leverages the strong correlation among the spectral bands of hyperspectral images and employs the SVD technique to extract spectral feature subspaces. This approach results in a more compact and representative feature space for fusion. Secondly, the proposed method utilizes Elastic Net regularization in combination with ${L_1}$ L 1 and ${L_2}$ L 2 regularization for effective feature selection of highly covariate features. Weighted group sparse regularization is employed to enhance the fusion effect, enabling better representation of the image's structure and features. The algorithm is subsequently evaluated on multiple datasets to confirm its effectiveness. The results of the experiment suggest that the suggested algorithm greatly enhances the spatial resolution and visual clarity of HSI images while preserving the spectral characteristics when compared to conventional methods for fusion of hyperspectral images. Additionally, the constraint for regulation can competently reduce any noise or artefacts, thereby boosting image discrimination. To summarize, the utilization of a sparse tensor-based hyperspectral image fusion algorithm with subspace learning provides an efficacious approach for processing hyperspectral imagery. This method is capable of improving spatial resolution, extracting advantageous features from hyperspectral imagery, and ultimately supports the process of remote sensing image analysis and application. [ABSTRACT FROM AUTHOR]

Background: Ischemic cardio-cerebrovascular disease is the leading cause of mortality worldwide. However, studies focusing on elderly and very elderly patients are scarce. Hence, our study aimed to characterize and investigate the long-term prognostic implications of ischemic cardio-cerebrovascular diseases in elderly Chinese patients. Methods: This retrospective cohort study included 1026 patients aged ≥ 65 years who were categorized into the mono ischemic cardio-cerebrovascular disease (MICCD) (either coronary artery disease or ischemic stroke/transient ischemic attack) (n = 912) and the comorbidity of ischemic cardio-cerebrovascular disease (CICCD) (diagnosed with both coronary artery disease and ischemic stroke/transient ischemic attack at admission) (n = 114). The primary outcome was all-cause death. The mortality risk was evaluated using the Cox proportional hazards risk model with multiple adjustments by conventional and propensity-score-based approaches. Results: Of the 2494 consecutive elderly patients admitted to the hospital, 1026 (median age 83 years [interquartile range]: 76.5–86.4; 94.4% men) met the inclusion criteria. Patients with CICCD consisted mostly of very elderly (79.2% vs. 66.1%, P < 0.001) individuals with a higher burden of comorbidities. Over a median follow-up of 10.4 years, 398 (38.8%) all-cause deaths were identified. Compared with the MICCD group, the CICCD group exhibited a higher adjusted hazard ratio (HR) (95% confidential interval, CI) of 1.71 (1.32–2.39) for long-term mortality after adjusting for potential confounders. The sensitivity analysis results remained robust. After inverse probability of treatment weighting (IPTW) modeling, the CICCD group displayed an even worse mortality risk (IPTW-adjusted HR: 2.07; 95% CI 1.47–2.90). In addition, anemia (adjusted HR: 1.48; 95% CI 1.16–1.89) and malnutrition (adjusted HR: 1.43; 95% CI 1.15–1.78) are also independent risk factors for all-cause mortality among elderly and very elderly patients. Conclusions: Our results thus suggest that elderly patients with ischemic cardio-cerebrovascular disease and anemia or malnutrition may have higher mortality, which may be predicted upon admission. These findings, however, warrant further investigation. [ABSTRACT FROM AUTHOR]

Incorporating single-electron tunneling (SET) of metallic nanoparticles (NPs) into modern electronic devices offers great promise to enable new properties; however, it is technically very challenging due to the necessity to integrate ultrasmall (