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Background. Tumor progression and the therapeutic resistance associated with cancer agents are thought to be modulated by circular RNAs (circRNAs); however, its mechanism associated with nonsmall cell lung cancer (NSCLC) is still undetermined. The following investigation aimed to evaluate the involvement of circRNAs with NSCLC. Methods. The serum specimens of 146 NSCLC individuals who received complete four cycles of PTX chemotherapy were collected. The serum concentration of hsa_(c)irc₀005962 of these individuals was assessed with quantitative real-time polymerase chain reaction (qRT-PCR), followed by the evaluation of demographic and survival consequences for further assessments. Results. It was revealed that hsa_(c)irc₀005962 is substantially increased in NSCLC chemoresistant patients and was positively correlated with the disease stage. Furthermore, the hsa_(c)irc₀005962 value of the area under the curve was moderate, and increased hsa_(c)irc₀005962 expression was linked with shorter overall survival (OS). Hsa_(c)irc₀005962 stimulated paclitaxel resistance (PTX-R) in resistant NSCLC cells by regulating the axis of miR-126-5p/insulin-like growth factor 1 (IGF1). Conclusion. The results of this investigation highlight that hsa_(c)irc₀005962 induces chemoresistance in NSCLC patients and, therefore, can act as a physiological target to treat NSCLC.

Remote sensing indices are widely used in various fields of geoscience research. However, there are limits to how effectively the knowledge of indices can be managed or analyzed. One of the main problems is the lack of ontology models and research on indices, which makes it difficult to acquire and update knowledge in this area. Additionally, there is a lack of techniques to analyze the mathematical semantics of indices, making it difficult to directly manage and analyze their mathematical semantics. This study utilizes an ontology and mathematical semantics integration method to offer a novel knowledge graph for a remote sensing index knowledge graph (RSIKG) so as to address these issues. The proposed semantic hierarchical graph structure represents the indices of knowledge with an entity-relationship layer and a mathematical semantic layer. Specifically, ontologies in the entity-relationship layer are constructed to model concepts and relationships among indices. In the mathematical semantics layer, index formulas are represented using mathematical semantic graphs. A method for calculating similarity for index formulas is also proposed. The article describes the entire process of building RSIKG, including the extraction, storage, analysis, and inference of remote sensing index knowledge. Experiments provided in this article demonstrate the intuitive and practical nature of RSIKG for analyzing indices knowledge. Overall, the proposed methods can be useful for knowledge queries and the analysis of indices. And the present study lays the groundwork for future research on analysis techniques and knowledge processing related to remote sensing indices.

Geographic registration (geo-registration) is a crucial foundation for augmented reality (AR) map applications. However, existing methods encounter difficulties in aligning spatial data with the ground surface in complex outdoor scenarios. These challenges make it difficult to accurately estimate the geographic north orientation. Consequently, the accuracy and robustness of these methods are limited. To overcome these challenges, this paper proposes a rotation-invariant estimation method for high-precision geo-registration in AR maps. The method introduces several innovations. Firstly, it improves the accuracy of generating heading data from low-cost hardware by utilizing Real-Time Kinematic GPS and visual-inertial fusion. This improvement contributes to the increased stability and precise alignment of virtual objects in complex environments. Secondly, a fusion method combines the true-north direction vector and the gravity vector to eliminate alignment errors between geospatial data and the ground surface. Lastly, the proposed method dynamically combines the initial attitude relative to the geographic north direction with the motion-estimated attitude using visual-inertial fusion. This approach significantly reduces the requirements on sensor hardware quality and calibration accuracy, making it applicable to various AR precision systems such as smartphones and augmented reality glasses. The experimental results show that this method achieves AR geo-registration accuracy at the 0.1-degree level, which is about twice as high as traditional AR geo-registration methods. Additionally, it exhibits better robustness for AR applications in complex scenarios.

Programmed death ligand-1 (PD-L1) has been identified as a factor associated with poor prognosis in a range of cancers, and was reported to be mainly induced by PTEN loss in gliomas. However, the clinical effect of PD-L1 and its regulation by PTEN has not yet been determined in colorectal cancer (CRC). In the present study, we verified the regulation of PTEN on PD-L1 and further determined the effect of PTEN on the correlation between PD-L1 expression and clinical parameters in CRC. RNA interference approach was used to down-regulate PTEN expression in SW480, SW620 and HCT116 cells. It was showed that PD-L1 protein, but not mRNA, was significantly increased in cells transfected with siRNA PTEN compared with the negative control. Moreover, the capacity of PTEN to regulate PD-L1 expression was not obviously affected by IFN-γ, the main inducer of PD-L1. Tissue microarray immunohistochemistry was used to detect PD-L1 and PTEN in 404 CRC patient samples. Overexpression of PD-L1 was significantly correlated with distant metastasis (P<0.001), TNM stage (P<0.01), metastatic progression (P<0.01) and PTEN expression (P<0.001). Univariate analysis revealed that patients with high PD-L1 expression had a poor overall survival (P<0.001). However, multivariate analysis did not support PD-L1 as an independent prognostic factor (P = 0.548). Univariate (P<0.001) and multivariate survival (P<0.001) analysis of 310 located CRC patients revealed that high level of PD-L1 expression was associated with increased risks of metastatic progression. Furthermore, the clinical effect of PD-L1 on CRC was not statistically significant in a subset of 39 patients with no PTEN expression (distant metastasis: P = 0.102; TNM stage: P = 0.634, overall survival: P = 0.482). PD-L1 can be used to identify CRC patients with high risk of metastasis and poor prognosis. This clinical manifestation may be partly associated with PTEN expression.

Background: Circular RNAs (circRNAs) demonstrated critical roles within developing tumors and treatment resistance in an increasing body of research. The aim was to look into the functions and processes of hsa_circ_0003489 in the non-small cell lung cancer (NSCLC) paclitaxel (PTX) resistance. Methods: NSCLC cell-based cultures including A549 and H460 were employed for such an investigation. hsa_circ_0003489, miR-98-5p, and insulin-like growth factor 2 (IGF2) expression-profiles were evaluated with a quantitative real-time polymerase chain reaction (RT-qPCR). The PTX resistance was determined using MTT assay, and the ELISA test measured IGF2 expression. Facilitating corroboration for miR-98-5p relation and hsa_circ_0003489 or IGF2, a dual-luciferase reporter method was applied. Results: The hsa_circ_0003489 level was raised in cells and tissues from PTX-resistant (PR) NSCLC. In PR NSCLC cells, hsa_circ_0003489 knockdown reduced PTX resistance. For the purpose of the mechanism study, hsa_circ_0003489 knockdown substantially reduced IGF2 expression via miR-98-5p sponging, improving PTX sensitivity in PR NSCLC. Conclusion: Through miR-98-5p/IGF2 axis control, hsa_circ_0003489 knockdown helped NSCLC overcome PTX resistance, suggesting a potential circRNA-targeted therapy for the disease. Keywords: Hsa_circ_0003489, PTX resistance, NSCLC, miR-98-5p, IGF2

In multi-resolution remote sensing imagery, roads typically exhibit sparse, elongated, and structurally complex morphological characteristics, posing formidable connectivity modeling challenges for semantic segmentation models. Existing approaches predominantly focus on pixel-level accuracy, often neglecting the topological integrity of road networks, which leads to frequent discontinuities and omissions in predicted results. To address this, this paper proposes an end-to-end road extraction framework equipped with multi-receptive field modeling and structural connectivity preservation capabilities. The model incorporates a multi-receptive-field module to capture road patterns across varying spatial scales, a connectivity-aware decoding mechanism to strengthen structural coherence, and a topology-aware loss that explicitly guides the restoration of continuous road networks during training. On the DeepGlobe-Road dataset, TopoRF-Net achieves OA 98.57%, IoU 69.76%, F1-score 82.18%, Precision 85.50%, and Recall 79.12%; on the Massachusetts dataset, TopoRF-Net similarly achieved outstanding results: OA 96.65%, IoU 59.68%, F1-score 74.75%, Precision 77.98%, and Recall 71.77%. These results conclusively demonstrate that the proposed method significantly outperforms existing approaches in both precision and connectivity metrics, whilst exhibiting favorable parameter efficiency and inference performance.

Circular RNAs (circRNAs) have been shown to have critical roles in developing cancer and treatment resistance in an increasing body of research. The aim was to look into the functions and processes of hsa_(c)irc₀003220 in the non-small cell lung cancer (NSCLC) chemoresistance. The NSCLC cell lines H460 and A549 were employed in present work. hsa_(c)irc₀003220, miR-489-3p, and insulin-like growth factors (IGF1) mRNA levels were assessed with a quantitative real time polymerase chain reaction (qRT-PCR). The cisplatin, docetaxel, and paclitaxel (PTX) resistances were determined using 3-(4,5-dimethylthiazol-2-yl)-2,5-diphenyltetrazolium bromide assay, and the enzyme linked immunosorbent assay (ELISA) test measured IGF1 expression. In order to corroborate the miR-489-3p relation with hsa_(c)irc₀003220 or IGF1, a dual-luciferase reporter method was applied. The level of hsa_(c)irc₀003220 was raised in cells and tissues from PTX-resistant (PR) NSCLC. In PR NSCLC cells, hsa_(c)irc₀003220 knockdown reduced chemoresistance. For the purpose of the mechanism study, hsa_(c)irc₀003220 knockdown substantially reduced IGF1 expression via miR-489-3p sponging, reducing chemoresistance in PR NSCLC cells. By controlling the miR-489-3p/IGF1 axis, hsa_(c)irc₀003220 knockdown helped NSCLC overcome chemoresistance, suggesting a potential circRNA-targeted therapy for the disease.

How cancer cells cope with high levels of replication stress during rapid proliferation is currently unclear. Here, we show that macrophage migration inhibitory factor (MIF) is a 3’ flap nuclease that translocates to the nucleus in S phase. Poly(ADP-ribose) polymerase 1 co-localizes with MIF to the DNA replication fork, where MIF nuclease activity is required to resolve replication stress and facilitates tumor growth. MIF loss in cancer cells leads to mutation frequency increases, cell cycle delays and DNA synthesis and cell growth inhibition, which can be rescued by restoring MIF, but not nuclease-deficient MIF mutant. MIF is significantly upregulated in breast tumors and correlates with poor overall survival in patients. We propose that MIF is a unique 3’ nuclease, excises flaps at the immediate 3’ end during DNA synthesis and favors cancer cells evading replication stress-induced threat for their growth. Replication stress is associated with cancer formation and progression. Here the authors reveal that the macrophage migration inhibitory factor (MIF) functions as 3’ flap nuclease involved in resolving replication stress affecting overall tumor progression.

The design of output constrained control system for unmanned aerial vehicles deployed in confined areas is an important issue in practice and not taken into account in many autopilot systems. In this study, the authors address a neural networks-based adaptive trajectory tracking control algorithm for multi-rotors systems in the presence of various uncertainties in their dynamics. Given any sufficient smooth and bounded reference trajectory input, the proposed algorithm achieves that (i) the system output (Euclidean position) tracking error converges to a neighbourhood of zero and furthermore (ii) the system output remains uniformly in a prescribed set. Instead of element-wise estimation, a norm estimation approach of unknown weight vectors is incorporated into the control system design to relieve the onboard computation burden. The convergence property of the closed-loop system subject to output constraint is analysed via a symmetric barrier Lyapunov function augmented with several quadratic terms. Simulation results are demonstrated on a quadrotor model to validate the effectiveness of the proposed algorithm.

The human kinome comprises 538 kinases playing essential functions by catalyzing protein phosphorylation. Annotation of subcellular distribution of the kinome greatly facilitates investigation of normal and disease mechanisms. Here, we present Kinome Atlas (KA), an image-based map of the kinome annotated to 10 cellular compartments. 456 epitope-tagged kinases, representing 85% of the human kinome, were expressed in HeLa cells and imaged by immunofluorescent microscopy under a similar condition. KA revealed kinase family-enriched subcellular localizations and discovered a collection of new kinase localizations at mitochondria, plasma membrane, extracellular space, and other structures. Furthermore, KA demonstrated the role of liquid-liquid phase separation in formation of kinase condensates. Identification of MOK as a mitochondrial kinase revealed its function in cristae dynamics, respiration, and oxidative stress response. Although limited by possible mislocalization due to overexpression or epitope tagging, this subcellular map of the kinome can be used to refine regulatory mechanisms involving protein phosphorylation.