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Transportation resilience, as a component of city sustainability, plays a crucial role in the daily management and emergency response of urban road systems. With coastal cities becoming increasingly vulnerable to typhoons, rainstorms, and other disasters, it is essential to assess the resilience of urban road transportation in a refined and differentiated approach. Existing resilience assessment methods often overlook significant biases, neglecting the dynamic response of road traffic and non-stationary characteristics of traffic systems. To address these limitations, we develop a quantitative resilience assessment method for urban road transportation during rainfall that is based on the improved Resilience Triangle. The method is applied to DiDi urban traffic speed and meteorological data of Shenzhen, China, from April to September 2018, with a focus on Typhoon Mangkhut as an extreme weather case. By analyzing transportation resilience variations across road densities, road hierarchies, and rainfall scenarios, we found that road densities and rainfall intensities explain resilience variations better than road hierarchies. Specifically, as accumulative precipitation exceeds 100 mm, a substantial surge in loss of performance is observed. Typhoon rainfalls result in a greater loss in urban road traffic compared to general rainfalls. The results offer valuable insights for urban road planning, traffic emergency management, and transportation resilience construction in the face of increasingly severe weather challenges.

BRAF activated non-coding RNA (BANCR), a long non-coding RNA (lncRNA), is crucial for cell migration in melanoma cells and non-small cell lung cancer (NSCLC) cells. However, little is known regarding the role of this gene in the proliferation of colorectal cancer. Therefore, we investigated the involvement of BANCR in the proliferation of colorectal cancer cells. In this study, we show that BANCR expression was significantly down-regulated in colorectal cancer tissues compared with normal tissues, and overexpression of BANCR suppressed colorectal cancer cell growth in vitro and in vivo. We also determined that pCDNA-BANCR-mediated colorectal cancer cell proliferation was associated with induction of G0/G1 cell-cycle arrest and apoptosis enhancement through regulation of p21, and its effects were most likely posttranscriptional. Taken together, our findings suggest that down-regulation of BANCR contributes to the proliferation of colorectal cancer cells, at least in part, through the regulation of p21 protein.

Emerging evidence has proven that long noncoding RNAs (lncRNAs) play important roles in human colorectal cancer (CRC) biology, although few lncRNAs have been characterized in CRC. Therefore, the functional significance of lncRNAs in the malignant progression of CRC still needs to be further explored. In this study, through analyzing TCGA RNA sequencing data and other publicly available microarray data, we found a novel lncRNA, LINC00460, whose expression was significantly upregulated in CRC tissues compared to adjacent normal tissues. Consistently, real-time qPCR results also verified that LINC00460 was overexpressed in CRC tissues and cells. Furthermore, high LINC00460 expression levels in CRC specimens were correlated with larger tumor size, advanced tumor stage, lymph node metastasis and shorter overall survival. In vitro and in vivo assays of LINC00460 alterations revealed a complex integrated phenotype affecting cell growth and apoptosis. Mechanistically, LINC00460 repressed Krüppel-like factor 2 (KLF2) transcription by binding to enhancer of zeste homolog 2 (EZH2). LINC00460 also functioned as a molecular sponge for miR-149-5p, antagonizing its ability to repress cullin 4A (CUL4A) protein translation. Taken together, our findings support a model in which the LINC00460/EZH2/KLF2 and LINC00460/miR-149-5p/CUL4A crosstalk serve as critical effectors in CRC tumorigenesis and progression, suggesting new therapeutic directions in CRC.

The large-scale storage and stable supply of oil products are essential for national energy security and economic development. As the economy expands and energy demands rise, centralized storage and supply systems become increasingly vital for ensuring the efficiency and reliability of oil product distribution. However, large oil storage depots present substantial safety risks. In the event of fires, explosions, or other accidents, emergency response efforts face stringent demands and challenges. To enhance the emergency response capabilities of oil storage and transportation bases (OSTBs), this paper proposes an innovative approach that integrates the improved analytic hierarchy process (IAHP) with the Entropy Weight Method (EMW) to determine the combined weights of various indices. This approach reduces the subjective bias associated with the traditional analytic hierarchy process (AHP). The emergency response capabilities of OSTBs are subsequently evaluated through fuzzy comprehensive analysis. An empirical study conducted on an OSTB in the Zhoushan archipelago quantitatively assesses its emergency preparedness. The results show that the base excels in pre-incident prevention, demonstrates robust preparedness and response capabilities, and exhibits moderate recovery abilities after incidents. These findings provide a theoretical foundation for reducing the likelihood of accidents, enhancing emergency response efficiency, and mitigating the severity of consequences. Practical recommendations are also offered based on the results.

As urbanization accelerates and urban hydrological cycles evolve, roof typology emerges as a pivotal role in water retention capacity and drainage efficiency. To systematically evaluate the influence of various roof types on urban hydrological processes, this study designed four distinct catchment scenarios: Thiessen Polygon Scenarios (TS), Roof Type Consideration Scenarios (RS), Full Flat-Roof Scenarios (FS), and Full Pitched-Roof Scenarios (PS). This study employed the Urban Flood Intelligent Model (UFIM) to simulate urban flooding scenarios, utilizing precipitation data from 21 August 2024 combined with four distinct return periods (1a, 5a, 10a, and 20a) as hydrological inputs. The results show that roof types significantly affected hydrological processes in urban communities. Flat roofs accumulate water and drain slowly, making it easy to form larger areas of accumulated water during peak rainfall periods, thereby increasing the risk of urban flooding. Pitched roofs drain quickly but experience a brief rise in water level during peak hours due to rapid drainage. Based on these insights, priority should be given to the use of sloped roof design in areas prone to accumulated water to accelerate drainage. In areas requiring runoff mitigation, the strategic integration of flat roofs with green roofs enhances rainwater retention capacity, thereby optimizing urban hydrological regulation and bolstering flood resilience.

Global warming is exacerbating flood hazards, making the robustness of flood risk management a critical issue. Without considering future scenarios, flood risk analysis built only on historical knowledge may not adequately address the coming challenges posed by climate change. A comprehensive risk analysis framework based on both historical inundations and future projections to tackle uncertainty is still lacking. In this view, a scenario-based, data-driven risk analysis framework that for the first time integrates recent historical floods and future risk trends is here presented, consisting of flood inundation-prone and high-risk zones. Considering the Poyang Lake Eco-Economic Zone (PLEEZ) in China as the study area, we reproduced historical inundation scenarios of major flood events by using Sentinel-1 imagery from 2015 to 2021, and used them to build the risk baseline model. The results show that 11.7% of the PLEEZ is currently exposed to the high-risk zone. In the SSP2-RCP4.5 scenario, the risk would gradually decrease after peaking around 2040 (with a 19.3% increase in high-risk areas), while under the traditional fossil fuel-dominated development pathway (SSP5-RCP8.5), the risk peak would occur with a higher intensity about a decade earlier. The attribution analysis results reveal that the intensification of heavy rainfall is the dominant driver of future risk increase and that the exploitation of unused land such as wetlands induces a significant increase in risk. Finally, a hierarchical panel of recommended management measures was developed. We hope that our risk analysis framework inspires newfound risk awareness and provides the basis for more effective flood risk management in river basins.

Background Long noncoding RNAs (lncRNAs) have emerged recently as a new class of genes that regulate cellular processes, such as cell growth and apoptosis. The SPRY4 intronic transcript 1 (SPRY4-IT1) is a 708-bp lncRNA on chromosome 5 with a potential functional role in tumorigenesis. The clinical significance of SPRY4-IT1 and the effect of SPRY4-IT1 on cancer progression are unclear. Methods Quantitative reverse transcriptase PCR (qRT-PCR) was performed to investigate the expression of SPRY4-IT1 in 48 breast cancer tissues and four breast cancer cell lines. Gain and loss of function approaches were used to investigate the biological role of SPRY4-IT1 in vitro. Microarray bioinformatics analysis was performed to identify the putative targets of SPRY4-IT1, which were further verified by rescue experiments, and by western blotting and qRT-PCR. Results SPRY4-IT1 expression was significantly upregulated in 48 breast cancer tumor tissues comparedwith normal tissues. Additionally, increased SPRY4-IT1 expression was found to be associated with a larger tumor size and an advanced pathological stage in breast cancer patients. The knockdown of SPRY4-IT1 significantly suppressed proliferation and caused apoptosis of breast cancer cells in vitro. Furthermore, we discovered that ZNF703 was a target of SPRY4-IT1 and was downregulated by SPRY4-IT1 knockdown. Moreover, we provide the first demonstration that ZNF703 plays an oncogenic role in ER (−) breast carcinoma cells. Conclusions SPRY4-IT1 is a novel prognostic biomarker and a potential therapeutic candidate for breast cancer.

Background Aberrant expression of long noncoding RNAs (lncRNAs) has frequently been reported in cancer studies, including those of colorectal cancer (CRC). Increasing evidence suggests that lncRNAs are significantly correlated with the pathogenesis, development and metastasis of cancer. Loc554202 is a 2166-bp transcript on human chromosome 9p21.3, the expression of which is dysregulated in breast and lung cancer cells. However, its role in CRC remains under investigation. Methods Quantitative real-time polymerase chain reaction (qRT-PCR) was carried out to assess the relative expression of Loc554202 in CRC cell lines and tissues. Gain and/or loss of function approaches were used to investigate the potential functional roles in cell proliferation and apoptosis in vitro and in vivo . qRT-PCR, western-blotting and immunohistochemistry were used to evaluate the mRNA and protein expression of apoptosis-related factors. Results Loc554202 was significantly downregulated in cancerous tissues and CRC cell lines compared with adjacent normal tissue and a normal human intestinal epithelial cell line. Low Loc554202 expression was closely associated with advanced pathologic stage and a larger tumor size. The overexpression of Loc554202 decreased the cell proliferation and induced apoptosis in vitro and hindered tumorigenesis in vivo . Loc554202 regulated cell apoptosis partly through the activation of specific caspase cleavage cascades. Conclusion Our results suggest that Loc554202 may play an important role in the progression of CRC and could be a candidate prognostic biomarker or a target for new cancer therapies.

In this study, we investigate the crystal structure, surface energy, and atomic arrangement of Cu2O. Understanding these properties is crucial for exploring the potential applications and understanding the behavior of this material. We employ the Wulff construction method and an artificial neural network (ANN) model to analyze the relative surface energies of different crystal facets and predict the surface energy of Cu2O. The ANN model exhibits excellent performance, demonstrating its effectiveness in predicting material properties and providing automated feature-learning and nonlinear-modeling capabilities. Moreover, we analyze the atomic arrangements on various crystal facets and observe the presence of oxygen atoms on the 100 facet, as well as exposed under-coordinated copper atoms on the 111 and 110 facets. High-index facets such as 211 exhibit a higher atomic step density and screw dislocation density. By precisely controlling the synthesis process, it is possible to manipulate the proportion of high-index facets. These findings highlight the significance of understanding the surface energy and atomic arrangement of Cu2O crystals for comprehending their properties and surface reactions. In summary, this study provides valuable insights into the crystal structure, surface energy, and atomic arrangement of Cu2O, offering inspiration for its properties and potential applications. The combination of the Wulff construction method and ANN modeling provides a comprehensive understanding of Cu2O crystals and their surface behavior, contributing to the field of materials science and laying the foundation for various future applications utilizing the unique properties of Cu2O.

In this study, we investigate the crystal structure, surface energy, and atomic arrangement of Cu[sub.2]O. Understanding these properties is crucial for exploring the potential applications and understanding the behavior of this material. We employ the Wulff construction method and an artificial neural network (ANN) model to analyze the relative surface energies of different crystal facets and predict the surface energy of Cu[sub.2]O. The ANN model exhibits excellent performance, demonstrating its effectiveness in predicting material properties and providing automated feature-learning and nonlinear-modeling capabilities. Moreover, we analyze the atomic arrangements on various crystal facets and observe the presence of oxygen atoms on the 100 facet, as well as exposed under-coordinated copper atoms on the 111 and 110 facets. High-index facets such as 211 exhibit a higher atomic step density and screw dislocation density. By precisely controlling the synthesis process, it is possible to manipulate the proportion of high-index facets. These findings highlight the significance of understanding the surface energy and atomic arrangement of Cu[sub.2]O crystals for comprehending their properties and surface reactions. In summary, this study provides valuable insights into the crystal structure, surface energy, and atomic arrangement of Cu[sub.2]O, offering inspiration for its properties and potential applications. The combination of the Wulff construction method and ANN modeling provides a comprehensive understanding of Cu[sub.2]O crystals and their surface behavior, contributing to the field of materials science and laying the foundation for various future applications utilizing the unique properties of Cu[sub.2]O.