Search Results (1,096)

Non-melanoma skin cancer (NMSC), comprising basal cell carcinoma (BCC) and cutaneous squamous cell carcinoma (cSCC), represents the most common type of cancer worldwide, particularly among Caucasians. While BCC is locally invasive with minimal metastatic potential, cSCC is a highly aggressive tumor with a significant potential for metastasis, particularly in elderly populations. Tumor development and progression and the metastasis of cSCC are influenced by a complex interplay between tumor cells and the tumor microenvironment. Recent research highlights the importance of various immune cell subsets, including T cells, tumor-associated macrophages (TAMs), and dendritic cells, in influencing tumor progression, immune evasion, and treatment resistance. This review outlines key regulatory mechanisms in the immune tumor microenvironment (TME) of cSCC and explores the role of cytokines, immune checkpoints, and stromal interactions. We further discuss the relevance of three-dimensional (3D) in vitro models such as spheroids, organoids, and tumor-on-chip systems as tools to mimic immune–tumor interactions with higher physiological relevance, such as macrophage activation and polarization against cSCC cells. Globally, 3D models offer new opportunities for immunotherapy screening and mechanistic studies. Understanding the immune landscape in cSCC through advanced modeling techniques holds strong clinical potential for improving diagnostic and therapeutic strategies. Full article

Neuropathic pain is a significant global clinical issue that poses substantial challenges to both public health and the economy due to its complex underlying mechanisms. It has emerged as a serious health concern worldwide. Recent studies involving dorsal root ganglion (DRG) stimulation have provided strong evidence supporting its effectiveness in alleviating chronic pain and its potential for sustaining long-term pain relief. In addition to that, there has been ongoing research with clinical evidence relating to the role of small non-coding ribonucleic acids known as microRNAs in regulating gene expressions affecting pain signals. The signal pathway involves alterations in neuronal excitation, synaptic transmission, dysregulated signaling, and subsequent pro-inflammatory response activation and pain development. When microRNAs are dysregulated in the dorsal root ganglia neurons, they polarize macrophages from anti-inflammatory M2 to inflammatory M1 macrophages causing pain signal generation. By reversing this polarization, a therapeutic activity can be induced. However, the direct delivery of these nucleotides has been challenging due to limitations such as rapid clearance, degradation, and reduction in half-life. Therefore, safe and efficient carrier vehicles are fundamental for microRNA delivery. Here, we present a comprehensive analysis of miRNA-based nano-systems for chronic neuropathic pain, focusing on their impact in dorsal root ganglia. This review provides a critical evaluation of various delivery platforms, including viral, polymeric, lipid-based, and inorganic nanocarriers, emphasizing their therapeutic potential as well as their limitations in the treatment of chronic neuropathic pain. Innovative strategies such as hybrid nanocarriers and stimulus-responsive systems are also proposed to enhance the prospects for clinical translation. Serving as a roadmap for future research, this review aims to guide the development and optimization of miRNA-based therapies for effective and sustained neuropathic pain management. Full article

In the context of global warming, polar tourism is developing rapidly, and the demand for polar cruise travel in the Northwest Passage continues to increase, while sea ice has long been a key factor limiting the development of polar cruise tourism. This study focuses on the operational risk of sea ice on cruise ships in the Northwest Passage (NWP), aiming to provide a scientific basis for ensuring the safety of cruise ship navigation and promoting the sustainable development of polar tourism. Based on ice data from 2015 to 2024, this study used the Polar Operational Limit Assessment Risk Indexing System (POLARIS) methodology recommended by the International Maritime Organization (IMO) to establish three scenarios for the route of ice class IC cruise ships: light ice, normal ice, and heavy ice. The navigable windows were systematically analyzed and critical waters along the route were identified. The results indicate that the navigable windows for IC ice-class cruise ships under light ice conditions are from mid-July to early December, while the navigable period under normal ice conditions is only from mid- to late September, and navigation is not possible under heavy ice conditions. The study identified Larsen Sound, Barrow Strait, Bellot Strait and Eastern Beaufort Sea as critical waters on the NWP cruise route. Among them, Larsen Sound and Eastern Beaufort Sea have a more prominent impact on voyage scheduling because their navigation weeks overlap less with other waters. This study provides a new idea for the risk assessment of polar cruise ships in ice regions. The research results can provide an important reference for the safe operation of polar cruise ships in the NWP and the decision-making of relevant parties. Full article

Mitochondria are currently of great interest to scientists. The role of mitochondrial DNA (mtDNA) mutations has been proven in the genesis of more than 200 pathologies, which are called mitochondrial disorders. Therefore, the study of mitochondria and mitochondrial DNA is of great interest not only for understanding cell biology but also for the treatment and prevention of many mitochondria-related pathologies. There are two main trends of mitochondrial therapy: mitochondrial replacement therapy (MRT) and mitochondrial transplantation therapy (MTT). Also, there are two main categories of MRT based on the source of mitochondria. The heterologous approach includes the following methods: pronuclear transfer technique (PNT), maternal spindle transfer (MST), Polar body genome transfer (PBT) and germinal vesicle transfer (GVT). An alternative approach is the autologous method. One promising autologous technique was the autologous germline mitochondrial energy transfer (AUGMENT), which involved isolating oogonial precursor cells from the patient, extracting their mitochondria, and then injecting them during ICSI. Transmission of defective mtDNA to the next generation can also be prevented by using these approaches. The development of a healthy child, free from genetic disorders, and the prevention of the occurrence of lethal mitochondrial disorders are the main tasks of this method. However, a number of moral, social, and cultural objections have restricted its exploration, since humanity first encountered the appearance of a three-parent baby. Therefore, this review summarizes the causes of mitochondrial diseases, the various methods involved in MRT and the results of their application. In addition, a new technology, mitochondrial transplantation therapy (MTT), is currently being actively studied. MTT is an innovative approach that involves the introduction of healthy mitochondria into damaged tissues, leading to the replacement of defective mitochondria and the restoration of their function. This technology is being actively studied in animals, but there are also reports of its use in humans. A bibliographic review in PubMed and Web of Science databases and a search for relevant clinical trials and news articles were performed. A total of 81 publications were selected for analysis. Methods of MRT procedures were reviewed, their risks described, and the results of their use presented. Results of animal studies of the MTT procedure and attempts to apply this therapy in humans were reviewed. MRT is an effective way to minimize the risk of transmission of mtDNA-related diseases, but it does not eliminate it completely. There is a need for global legal regulation of MRT. MTT is a new and promising method of treating damaged tissues by injecting the body’s own mitochondria. The considered methods are extremely good in theory, but their clinical application in humans and the success of such therapy remain a question for further study. Full article

Mars’ south polar cap hosts dynamic landforms known as Swiss cheese features (SCFs), which form through the sublimation of carbon dioxide (CO₂) ice driven by the planet’s extreme seasonal and diurnal solar insolation cycles. These shallow, rounded depressions—first identified by Mars Global Surveyor in 1999 and later monitored by the Mars Reconnaissance Orbiter (MRO)—have been observed to increase in size over time. However, large-scale analysis of SCF formation and growth has been limited by the slow and labor-intensive nature of manual mapping techniques. This study applies object-based image analysis (OBIA) to automate the detection and measurement of SCFs using High-Resolution Imaging Science Experiment (HiRISE) images spanning five Martian years. Results show that SCFs exhibit a near-linear increase in area, suggesting that summer sublimation consistently outpaces winter CO₂ deposition. Validation against manual digitization shows discrepancies of less than 1%, confirming the reliability of the OBIA method. Regression-based extrapolation of growth trends indicates that the current generation of SCFs likely began forming between Martian years 7 and 16, approximately corresponding to Earth years 1976 to 1998. These findings provide a quantitative assessment of SCF evolution and contribute to our understanding of recent climate-driven surface changes on Mars. HiRISE images were processed using the eCognition software to detect, classify, and measure SCFs, demonstrating that OBIA is a scalable and effective tool for analyzing dynamic planetary landforms. Full article

Advanced Synthetic Aperture Radar (SAR) has become an essential modality in remote sensing, offering all-weather capabilities and sensitivity to vegetation biophysical parameters and surface conditions, while effectively complementing optical sensor data. This study evaluates the impact of precipitation on the Normalized Polarimetric Radar Vegetation Index (NPRVI) using dual-polarization Sentinel-1 C-band SAR data from agricultural fields at the Beltsville Agricultural Research Center (BARC). Field-measured precipitation and Global Precipitation Measurement (GPM) precipitation datasets were temporally aligned with Sentinel-1 acquisition times to assess the sensitivity of radar signals to precipitation events. NPRVI exhibited a strong sensitivity to precipitation, particularly within the 1 to 7 h prior to the satellite overpass, even for small amounts of precipitation. A quality assessment (QA) framework was developed to flag and correct precipitation-affected radar observations through interpolation. The adjusted NPRVI values, based on the QA framework using precipitation within a 6 h window, showed strong agreement between field- and GPM-derived data, with an RMSE of 0.09 and a relative RMSE of 19.8%, demonstrating that GPM data can serve as a viable alternative for quality adjustment despite its coarse spatial resolution. The adjusted NPRVI for both soybean and corn fields significantly improved the temporal consistency of the time series and closely followed NDVI trends, while also capturing crop-specific seasonal variations, especially during periods of NDVI saturation or limited variability. These findings underscore the value of the proposed radar-based QA framework in enhancing the interpretability of vegetation dynamics. NPRVI, when adjusted for precipitation effects, can serve as a reliable and complementary tool to optical vegetation indices in agricultural and environmental monitoring. Full article

Global challenges such as climate change and population growth require improvements in crop monitoring models. To address these issues, this study advances the identification of potato crop phenological stages using satellite remote sensing, a field where cereals have been the primary focus. We introduce a methodology using Sentinel-1 (S1) and Sentinel-2 (S2) time series data to pinpoint critical phenological stages—emergence, canopy closure, flowering, senescence onset, and harvest timing—at the field scale. Our approach utilizes analysis of NDVI, fAPAR, and IRECI2 from S2, alongside VH and VV polarizations from S1, informed by domain knowledge of the spectral and morphological responses of potato crops. We propose the integration of NDVI and VH indices, NDVI_VH, to improve stage detection accuracy. Comparative analysis with ground-observed stages validated the method’s effectiveness, with NDVI proving to be one of the most informative indices, achieving RMSEs of 12 and 14 days for emergence and closure, and 17 days for the onset of senescence. The integrated NDVI_VH approach complemented NDVI, particularly in harvest and flowering stages, where VH enhanced accuracy, achieving an overall R² value of 0.80. The study demonstrates the potential of combining SAR and optical data for post-season crop phenology analysis, providing insights that can inform the development of new methods and strategies to enhance on-season crop monitoring and yield forecasting. Full article

The Very Long Baseline Interferometry Global Observing System (VGOS), a global network of stations equipped with small-diameter, fast-slewing antennas and broadband receivers, is primarily utilized for geodesy and astrometry. In China, the Shanghai and Urumqi VGOS stations have been developed to perform radio source observation regularly. However, these VGOS stations have not yet been used to observe Earth satellites or deep-space probes. In addition, suitable systems for processing VGOS satellite data are unavailable. In this study, we explored a data processing pipeline and method suitable for VGOS data observed in the dual linear polarization mode and applied to the differential observation of satellites. We present the VGOS observations of the Chang’e 5 lunar orbiter as a pilot experiment for VGOS observations of Earth satellites to verify our processing pipeline. The interferometric fringes were obtained by the cross-correlation of Chang’e 5 lunar orbiter signals. The data analysis yielded a median delay precision of 0.16 ns with 30 s single-channel integration and a baseline closure delay standard deviation of 0.14 ns. The developed data processing pipeline can serve as a foundation for future Earth-orbiting satellite observations, potentially supporting space-tie satellite missions aimed at constructing the terrestrial reference frame (TRF). Full article

Emergency displacement has become an increasingly salient global phenomenon, precipitated by the intensification of climate crises and persistent geopolitical conflicts. These events forcibly displace millions each year and generate complex social, political, and institutional challenges. While the literature on displacement is expanding, much of it centers on individual and household experiences, often overlooking the collective dimensions of displacement. This article addresses this gap by critically examining the concept of the displaced community, a term used to describe collectivities formed in host societies comprising individuals who have been forcibly uprooted. The article undertakes a conceptual investigation of displaced communities, seeking to define their constitutive features while accounting for their internal heterogeneity and contextual variability. To sharpen analytical clarity, the study contrasts displaced communities with healthy communities, thereby situating two polar ends of a continuum. Based on these two types of community, the question arises, “can displaced communities be healthy communities?” The article advances a conceptual model of a healthy displaced community, positing that such a construct extends conventional understandings of resilience by foregrounding the processual dynamics of recovery and adaptation. Specifically, it is argued that community health in contexts of forced displacement must be understood as the outcome of iterative processes intentionally involving community-based intervention, empowerment, and long-term sustainability. Drawing on published case studies and empirical accounts of work with displaced populations, the article demonstrates how these three pillars—community intervention, empowerment, and sustainability—are implemented in practice. It concludes with policy and practice recommendations designed to prevent further deterioration and promote the development of health and well-being within displaced communities. Full article

Atherosclerosis is a chronic inflammatory disease and a major pathological basis of numerous cardiovascular conditions, with a high global mortality rate. Macrophages play a pivotal role in its pathogenesis through phenotypic switching and foam cell formation. Prostaglandin E2 receptor subtype 4 (EP4) highly expressed on the macrophage surface, is involved in various pathophysiological processes, such as inflammation and lipid metabolism. However, the role of macrophage EP4 in the progression of atherosclerosis remains unclear. To determine whether macrophage EP4 affects the progression of atherosclerosis by regulating foam cell formation and macrophage polarization. Myeloid-specific EP4 knockout mice with an ApoE-deficient background were fed a Western diet for 16 weeks. Our results showed that EP4 expression was significantly downregulated during atherosclerosis. EP4 deficiency was found to exacerbate atherosclerotic plaque formation and destabilizes plaques. In vitro studies further demonstrated that loss of EP4 in myeloid cells promoted foam cell formation and M1 macrophage polarization. Both transcriptomic and proteomic analysis showed that EP4 may regulate these processes by regulating CD36 expression in macrophage, which was further confirmed by Western blot and qPCR. In summary, deficiency of EP4 receptor in macrophages enhance foam cell formation and M1 polarization by upregulating CD36 expression, thereby accelerating the progression of atherosclerosis. Full article

The imbalance between urban and rural development has become a global structural problem that needs to be solved urgently. In this context, the tourism industry, with its strong correlation and cross-regional integration characteristics, provides a key practical entry point and mechanism for systematically promoting integrated development by stimulating factor flow, reconstructing the value chain, and reshaping local identity. Based on the synergetic theory, this paper constructs the theoretical framework of the synergetic evolution of the tourism industry and urban–rural integration, and analyzes the synergetic effect of the tourism industry and urban–rural integration in 58 prefecture-level cities in the Yellow River Basin from 2007 to 2021 and the dynamic characteristics of its spatio-temporal evolution by using the entropy TOPSIS, Haken model, and spatial Markov chain methods. The results show the following: ① As the order parameter of synergistic evolution, the tourism industry dominates the evolution direction of the whole system, mainly showing positive feedback effect, showing a significant stage characteristic in general, and gradually reducing the difference from the initial regional differentiation to the middle stage, finally reaching a higher level of unity. ② The synergic evolution of the tourism industry and urban–rural integration in the Yellow River Basin presents significant temporal and spatial differences in the upstream, midstream, and downstream, with the overall characteristics of “collaborative improvement in the upstream, significant agglomeration in the midstream, and reverse decoupling in the downstream”. ③ The dynamic evolution of the synergistic development of the tourism industry and urban–rural integration in the Yellow River Basin has significant characteristics of spatial interaction and dynamic transfer. Its level has the effect of “path dependence”, showing a good trend of upward transfer, and the spatial neighborhood has a significant impact on the synergetic level transfer. The development trend of each region shows that “the upstream region is upward and stable, the midstream region has significant agglomeration and diffusion effects, and the downstream region is driven by polar nuclei and spatial differentiation”. Full article

Dust aerosols significantly affect climate and air quality in Northwest China (30–50° N, 70–110° E), where frequent dust storms complicate accurate aerosol classification when using CALIPSO satellite data. This study introduces an Enhanced 1D U-Net model to enhance dust aerosol retrieval, incorporating Inception modules for multi-scale feature extraction, Transformer blocks for global contextual modeling, CBAM attention mechanisms for improved feature selection, and residual connections for training stability. Using CALIPSO Level 1B and Level 2 Vertical Feature Mask (VFM) data from 2015 to 2020, the model processed backscatter coefficients, polarization characteristics, and color ratios at 532 nm and 1064 nm to classify aerosol types. The model achieved a precision of 94.11%, recall of 99.88%, and F1 score of 96.91% for dust aerosols, outperforming baseline models. Dust aerosols were predominantly detected between 0.44 and 4 km, consistent with observations from CALIPSO. These results highlight the model’s potential to improve climate modeling and air quality monitoring, providing a scalable framework for future atmospheric research. Full article

The persistent contamination of aquatic environments by heavy metals, particularly Pb²⁺, Cd²⁺, and Cu^2+, poses a serious global threat due to their toxicity, persistence, and bioaccumulative behavior. In response, low-cost and eco-friendly adsorbents are being explored, among which CaCO₃-based biocomposites derived from mollusk shells have shown exceptional performance. In this study, a hybrid biocomposite composed of poly(vinyl alcohol) (PVA) and oyster shell-derived CaCO₃ was computationally investigated using Density Functional Theory (DFT) to elucidate the electronic and structural basis for its high metal-removal efficiency. Calculations were performed at the B3LYP/6-311++G(d,p), M05-2X/6-311+G(d,p), and M06-2X/6-311++G(d,p) levels using GAUSSIAN 16. Among them, B3LYP was identified as the most balanced in terms of accuracy and computational cost. The hybridization with CaCO₃ reduced the HOMO-LUMO gap by 20% and doubled the dipole moment (7.65 Debye), increasing the composite’s polarity and reactivity. Upon chelation with metal ions, the gap further dropped to as low as 0.029 eV (Cd²⁺), while the dipole moment rose to 17.06 Debye (Pb²⁺), signaling enhanced charge separation and stronger electrostatic interactions. Electrostatic potential maps revealed high nucleophilicity at carbonate oxygens and reinforced electrophilic fields around the hydrated metal centers, correlating with the affinity trend Cu²⁺ > Cd²⁺ > Pb²⁺. Fukui function analysis indicated a redistribution of reactive sites, with carbonate oxygens acting as ambiphilic centers suitable for multidentate coordination. Natural Bond Orbital (NBO) analysis confirmed the presence of highly nucleophilic lone pairs and weakened bonding orbitals, enabling flexible adsorption dynamics. Furthermore, NCI/RDG analysis highlighted attractive noncovalent interactions with Cu²⁺ and Pb²⁺, while FT-IR simulations demonstrated the formation of hydrogen bonding (O–H···O=C) and Ca²⁺···O coordination bridges between phases. Full article

The rapid growth of computationally intensive tasks in the Internet of Vehicles (IoV) poses a triple challenge to the efficiency, security, and stability of Mobile Edge Computing (MEC). Aiming at the problems that traditional optimization algorithms tend to fall into, where local optimum in task offloading and edge computing nodes are exposed to the risk of data tampering, this paper proposes a secure offloading strategy that integrates the Improved Polar Lights Optimization algorithm (IPLO) and blockchain. First, the truncation operation when a particle crosses the boundary is improved to dynamic rebound by introducing a rebound boundary processing mechanism, which enhances the global search capability of the algorithm; second, the blockchain framework based on the Delegated Byzantine Fault Tolerance (dBFT) consensus is designed to ensure data tampering and cross-node trustworthy sharing in the offloading process. Simulation results show that the strategy significantly reduces the average task processing latency (64.4%), the average system energy consumption (71.1%), and the average system overhead (75.2%), and at the same time effectively extends the vehicle’s power range, improves the real-time performance of the emergency accident warning and dynamic path planning, and significantly reduces the cost of edge computing usage for small and medium-sized fleets, providing an efficient, secure, and stable collaborative computing solution for IoV. Full article

Long-distance navigation requires global positioning methods to have complete autonomy, particularly when the Global Positioning System is unavailable. Considering that bionic polarized light-based global positioning technology exhibits good autonomy, this study develops an error model for autonomous global positioning based on the polarized skylight and a true north measurement instrument, using an approach of partial derivatives. The proposed model can rapidly and accurately provide the global error distribution of a bionic positioning method under varying angular measurement errors at different times. In addition, the conditions under which the proposed error model remains valid are investigated. The results indicate that the investigation can be simplified to verify whether the denominators of four partial derivatives of an implicit function system are simultaneously non-zero. The accuracy of the proposed error model is verified through numerical simulations. The results indicate that when the deviations of the two independent variables are up to 0.0001°, the positioning error mostly remains less than 14 m. In contrast, fewer geographical locations have positioning errors approaching positive infinity. By analyzing the global error distribution, one can effectively design and optimize the parameters of the autonomous global positioning system, enhancing its reliability and stability. Full article