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"Zhu, Xuan"
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Web-based virtual environments for decision support in water systems
\"Water management is a complex process dealing with a wide range of often conflicting considerations. Especially in flood risk assessment and disaster management, stakeholder involvment is an important component in the decision making process. How to integrate different information sources and how to present them in such a way that even non-experts can capture the situation in a relatively short time and take decisions--that is the overall objective of this research. ... Case study applications focus on the role of 3D information in river delta development, flood disaster management and coastal protection. Implications for next-generation decision support systems are outlined.\"--Back cover.
Book
A Review of Spectral Indices for Mangrove Remote Sensing
Mangrove ecosystems provide critical goods and ecosystem services to coastal communities and contribute to climate change mitigation. Over four decades, remote sensing has proved its usefulness in monitoring mangrove ecosystems on a broad scale, over time, and at a lower cost than field observation. The increasing use of spectral indices has led to an expansion of the geographical context of mangrove studies from local-scale studies to intercontinental and global analyses over the past 20 years. In remote sensing, numerous spectral indices derived from multiple spectral bands of remotely sensed data have been developed and used for multiple studies on mangroves. In this paper, we review the range of spectral indices produced and utilised in mangrove remote sensing between 1996 and 2021. Our findings reveal that spectral indices have been used for a variety of mangrove aspects but excluded identification of mangrove species. The included aspects are mangrove extent, distribution, mangrove above ground parameters (e.g., carbon density, biomass, canopy height, and estimations of LAI), and changes to the aforementioned aspects over time. Normalised Difference Vegetation Index (NDVI) was found to be the most widely applied index in mangroves, used in 82% of the studies reviewed, followed by the Enhanced Vegetation Index (EVI) used in 28% of the studies. Development and application of potential indices for mangrove cover characterisation has increased (currently 6 indices are published), but NDVI remains the most popular index for mangrove remote sensing. Ultimately, we identify the limitations and gaps of current studies and suggest some future directions under the topic of spectral index application in connection to time series imagery and the fusion of optical sensors for mangrove studies in the digital era.
Journal Article
Circular RNA circ_0020710 drives tumor progression and immune evasion by regulating the miR-370-3p/CXCL12 axis in melanoma
Background
Circular RNAs (circRNAs) have been reported to have critical regulatory roles in tumor biology. However, their contribution to melanoma remains largely unknown.
Methods
CircRNAs derived from oncogene CD151 were detected and verified by analyzing a large number of melanoma samples through quantitative real-time polymerase chain reaction (qRT-PCR). Melanoma cells were stably transfected with lentiviruses using circ_0020710 interference or overexpression plasmid, and then CCK-8, colony formation, wound healing, transwell invasion assays, and mouse xenograft models were employed to assess the potential role of circ_0020710. RNA immunoprecipitation, luciferase reporter assay and fluorescence in situ hybridization were used to evaluate the underlying mechanism of circ_0020710.
Results
Our findings indicated that circ_0020710 was generally overexpressed in melanoma tissues, and high level of circ_0020710 was positively correlated with malignant phenotype and poor prognosis of melanoma patients. Elevated circ_0020710 promoted melanoma cell proliferation, migration and invasion in vitro as well as tumor growth in vivo. Mechanistically, we found that high level of circ_0020710 could upregulate the CXCL12 expression via sponging miR-370-3p. CXCL12 downregulation could reverse the malignant behavior of melanoma cells conferred by circ_0020710 over expression. Moreover, we also found that elevated circ_0020710 was correlated with cytotoxic lymphocyte exhaustion, and a combination of AMD3100 (the CXCL12/CXCR4 axis inhibitor) and anti-PD-1 significantly attenuated tumor growth.
Conclusions
Elevated circ_0020710 drives tumor progression via the miR-370-3p/CXCL12 axis, and circ_0020710 is a potential target for melanoma treatment.
Journal Article
Bioinformatics-based analysis reveals elevated MFSD12 as a key promoter of cell proliferation and a potential therapeutic target in melanoma
Although recent therapeutic advances based on our understanding of molecular phenomena have prolonged the survival of melanoma patients, the prognosis of melanoma remains dismal and further understanding of the underlying mechanism of melanoma progression is needed. In this study, differential expression analyses revealed that many genes, including AKT1 and CDK2, play important roles in melanoma. Functional analyses of differentially expressed genes (DEGs), obtained from the GEO (Gene Expression Omnibus) database, indicated that high proliferative and metastatic abilities are the main characteristics of melanoma and that the PI3K and MAPK pathways play essential roles in melanoma progression. Among these DEGs, major facilitator superfamily domain-containing 12 (MFSD12) was found to have significantly and specifically upregulated expression in melanoma, and elevated MFSD12 level promoted cell proliferation by promoting cell cycle progression. Mechanistically, MFSD12 upregulation was found to activate PI3K signaling, and a PI3K inhibitor reversed the increase in cell proliferation endowed by MFSD12 upregulation. Clinically, high MFSD12 expression was positively associated with shorter overall survival (OS) and disease-free survival (DFS) in melanoma patients, and MFSD12 was an independent prognostic factor for OS and DFS in melanoma patients. Therapeutically, in vivo assays further confirmed that MFSD12 interference inhibited tumor growth and lung metastasis in melanoma. In conclusion, elevated MFSD12 expression promotes melanoma cell proliferation, and MFSD12 is a valuable prognostic biomarker and promising therapeutic target in melanoma.
Journal Article
Bacterial cell wall-specific nanomedicine for the elimination of Staphylococcus aureus and Pseudomonas aeruginosa through electron-mechanical intervention
Personalized synergistic antibacterial agents against diverse bacterial strains are receiving increasing attention in combating antimicrobial resistance. However, the current research has been struggling to strike a balance between strain specificity and broad-spectrum bactericidal activity. Here, we propose a bacterial cell wall-specific antibacterial strategy based on an in situ engineered nanocomposite consisting of carbon substrate and decorated TiO
x
dots, termed TiO
x
@C. The fiber-like carbon substrate of TiO
x
@C is able to penetrate the bacterial membrane of
Pseudomonas aeruginosa
(
P. aeruginosa
), but not that of
Staphylococcus aureus
(
S. aureu
s) due to its thicker bacterial wall, thus achieving bacterial wall specificity. Furthermore, a series of experiments demonstrate the specific electro-mechanical co-sterilization effect of TiO
x
@C. On the one hand, TiO
x
@C can disrupt the electron transport chain and block the energy supply of
S. aureus
. On the other hand, TiO
x
@C capable of destroying the membrane structure of
P. aeruginosa
could cause severe mechanical damage to
P. aeruginosa
as well as inducing oxidative stress and protein leakage. In vivo experiments demonstrate the efficacy of TiO
x
@C in eliminating 97% of bacteria in wounds and promoting wound healing in wound-infected female mice. Overall, such a bacterial cell wall-specific nanomedicine presents a promising strategy for non-antibiotic treatments for bacterial diseases.
Personalized antibacterial agents against diverse bacteria strains are promising for combating antimicrobial resistance, but a balance between strain specificity and broad-spectrum bactericidal activity is elusive. Here, the authors report an antibacterial nanoagent TiOx@C with bacterial cell wall specificity, multi-targeting and bactericidal effect against
S. aureus
and
P. aeruginosa
.
Journal Article
Predicting Wildfire Risk in Southwestern Saudi Arabia Using Machine Learning and Geospatial Analysis
In recent years, ecosystems in Saudi Arabia have experienced severe degradation due to factors such as hyperaridity, overgrazing, climate change, urban expansion, and an increase in uncontrolled wildfires. Among these, wildfires have emerged as the second most significant threat to forests after urban expansion. This study aims to map wildfire susceptibility in southwestern Saudi Arabia by identifying key driving factors and evaluating the performance of several machine learning models under conditions of limited and imbalanced data. The models tested include Maxent, logistic regression, random forest, XGBoost, and support vector machine. In addition, an NDVI-based phenological approach was applied to assess seasonal vegetation dynamics and to compare its effectiveness with conventional machine learning-based susceptibility mapping. All methods generated effective wildfire risk maps, with Maxent achieving the highest predictive accuracy (AUC = 0.974). The results indicate that human activities and dense vegetation cover are the primary contributors to wildfire occurrence. This research provides valuable insights for wildfire risk assessment in data-scarce regions and supports proactive fire management strategies in non-traditional fire-prone environments.
Journal Article
In situ generation of micrometer-sized tumor cell-derived vesicles as autologous cancer vaccines for boosting systemic immune responses
Cancer vaccine, which can promote tumor-specific immunostimulation, is one of the most important immunotherapeutic strategies and holds tremendous potential for cancer treatment/prevention. Here, we prepare a series of nanoparticles composed of doxorubicin- and tyrosine kinase inhibitor-loaded and hyaluronic acid-coated dendritic polymers (termed HDDT nanoparticles) and find that the HDDT nanoparticles can convert various cancer cells to micrometer-sized vesicles (1.6−3.2 μm; termed HMVs) with ~100% cell-to-HMV conversion efficiency. We confirm in two tumor-bearing mouse models that the nanoparticles can restrain tumor growth, induce robust immunogenic cell death, and convert the primary tumor into an antigen depot by producing HMVs in situ to serve as personalized vaccines for cancer immunotherapy. Furthermore, the HDDT-healed mice show a strong immune memory effect and the HDDT treatment can realize long-term protection against tumor rechallenge. Collectively, the present work provides a general strategy for the preparation of tumor-associated antigen-containing vesicles and the development of personalized cancer vaccines.
Autologous tumor cell vaccines can elicit anti-tumor immune responses. Here, the authors report the design of dendritic polymer-based nanoparticles loaded with doxorubicin and the tyrosine kinase inhibitor apatinib that can induce immunogenic cell death and the in situ production of immuno-stimulatory micrometer-sized vesicles, promoting anti-tumor immune responses in preclinical models.
Journal Article
Hyperbaric oxygen enhances tumor penetration and accumulation of engineered bacteria for synergistic photothermal immunotherapy
Bacteria-mediated cancer therapeutic strategies have attracted increasing interest due to their intrinsic tumor tropism. However, bacteria-based drugs face several challenges including the large size of bacteria and dense extracellular matrix, limiting their intratumoral delivery efficiency. In this study, we find that hyperbaric oxygen (HBO), a noninvasive therapeutic method, can effectively deplete the dense extracellular matrix and thus enhance the bacterial accumulation within tumors. Inspired by this finding, we modify
Escherichia coli
Nissle 1917 (EcN) with cypate molecules to yield EcN-cypate for photothermal therapy, which can subsequently induce immunogenic cell death (ICD). Importantly, HBO treatment significantly increases the intratumoral accumulation of EcN-cypate and facilitates the intratumoral infiltration of immune cells to realize desirable tumor eradication through photothermal therapy and ICD-induced immunotherapy. Our work provides a facile and noninvasive strategy to enhance the intratumoral delivery efficiency of natural/engineered bacteria, and may promote the clinical translation of bacteria-mediated synergistic cancer therapy.
Delivering bacteria-based drug for cancer therapy is limited by their penetration into extracellular matrix (ECM). Here the authors report effective depletion of ECM with hyperbaric oxygen therapeutic strategy to enhance bacterial accumulation within tumors and to induce immunogenic cell death.
Journal Article
Detection of Transmission Line Insulator Defects Based on an Improved Lightweight YOLOv4 Model
Defective insulators seriously threaten the safe operation of transmission lines. This paper proposes an insulator defect detection method based on an improved YOLOv4 algorithm. An insulator image sample set was established according to the aerial images from the power grid and the public dataset on the Internet, combining with the image augmentation method based on GraphCut. The insulator images were preprocessed by Laplace sharpening method. To solve the problems of too many parameters and low detection speed of the YOLOv4 object detection model, the MobileNet lightweight convolutional neural network was used to improve YOLOv4 model structure. Combining with the transfer learning method, the insulator image samples were used to train, verify, and test the improved YOLOV4 model. The detection results of transmission line insulator and defect images show that the detection accuracy and speed of the proposed model can reach 93.81% and 53 frames per second (FPS), respectively, and the detection accuracy can be further improved to 97.26% after image preprocessing. The overall performance of the proposed lightweight YOLOv4 model is better than traditional object detection algorithms. This study provides a reference for intelligent inspection and defect detection of suspension insulators on transmission lines.
Journal Article