Search Results (346)

Pleural Mesothelioma (PM) remains a challenging malignancy associated with asbestos exposure and characterized by poor prognosis. This review aims to consolidate recent findings on the efficacy of perioperative therapies encompassing chemotherapy, surgery, and emerging immunotherapy strategies. Current management strategies debate the role of surgery in early-stage patients, particularly due to the limited success of solitary treatment modalities and significant rates of postoperative complications. Retrospective studies indicate that multimodal treatment, incorporating surgical resection with perioperative chemotherapy, can enhance overall survival (OS), especially in favorable prognostic subsets. However, significant randomized trials, notably the MARS and MARS 2 trials, revealed that the addition of aggressive surgical strategies like extrapleural pneumonectomy (EPP) did not confer survival benefits and was accompanied by heightened morbidity. In light of persistent challenges, integrating perioperative chemotherapy—primarily with platinum-based regimens—has shown improved disease control outcomes. Neoadjuvant chemotherapy permits real-time assessment of tumor responsiveness, providing valuable clinical insights for surgical candidacy. The role of immunotherapy, particularly immune checkpoint inhibitors (ICIs), is also under active exploration, with preliminary results suggesting promising activity and manageable safety profiles. In conclusion, while current protocols primarily recommend surgery for a select group of patients, ongoing investigations into neoadjuvant approaches, adjuvant therapies, and novel immunotherapeutic strategies are crucial for developing effective, personalized treatment paradigms for PM. Future efforts should prioritize clinical trials that integrate these therapies within a structured multidisciplinary approach to optimize patient outcomes. Full article

Taking the leap to the secondary and tertiary generations of the missions to Mars, a comprehensive outline was presented for a cluster of Martian Habitat Units (MHUs) designed for long-term settlements of research crew in Melas Chasma, Valles Marineris, Mars. Unlike initial exploration missions, where primary survival is ensured through basic engineering solutions, this concept targets later-stage missions focused on long-term human presence. Accordingly, the MHUs are designed not only for functionality but also to support the social and cultural well-being of scientific personnel, resulting in larger and more complex structures than those typically proposed for early-stage landings. To address the construction and structural integrity of the MHUs, the current work presents a comprehensive analysis of the feasibility of semi-3D-printed structural systems using in situ material to minimize the cost and engineering effort of logistics and construction of the units. Regolith-based additive manufacturing was utilized as the primary material, and the response of the structure, not only to the gravitational loads but also to those applied from the exterior flow field and wind pressure distributions, was simulated, as well as the considerations regarding the contribution of the extreme interior/exterior pressure differences. The full analyses and structural results are presented and discussed in this manuscript, as well as insights on manufacturing and its feasibility on Mars. The analyses demonstrate the feasibility of constructing the complex architectural requirements of the MHUs and their cost-effectiveness through the use of in situ resources. The manuscript presents an iterative structural optimization process, with results detailed at each step. Structural elements were modeled using FEM-based analysis in Karamba-3D to minimize near-yielding effects such as buckling and excessive displacements. The final structural system was integrated with the architectural design to preserve the intended spatial and functional qualities. Full article

Laser-induced breakdown spectroscopy (LIBS) has been used to explore the chemistry of three regions of Mars on respective missions by NASA and CNSA, with CNES contributions. All three LIBS instruments use ~100 mm diameter telescopes projecting pulsed infrared laser beams of 10–14 mJ to enable LIBS at 2–10 m distances, eliminating the need to position the rover and instrument directly onto targets. Over 1.3 million LIBS spectra have been used to provide routine compositions for eight major elements and several minor and trace elements on >3000 targets on Mars. Onboard calibration targets common to all three instruments allow careful intercomparison of results. Operating over thirteen years, ChemCam on Curiosity has explored lacustrine sediments and diagenetic features in Gale crater, which was a long-lasting (>1 My) lake during Mars’ Hesperian period. SuperCam on Perseverance is exploring the ultramafic igneous floor, fluvial–deltaic features, and the rim of Jezero crater. MarSCoDe on the Zhurong rover investigated for one year the local blocks, soils, and transverse aeolian ridges of Utopia Planitia. The pioneering work of these three stand-off LIBS instruments paves the way for future space exploration with LIBS, where advantages of light-element (H, C, N, O) quantification can be used on icy regions. Full article

Legged rovers are gaining interest for planetary exploration due to their high mobility. However, loose regolith on celestial surfaces like the Moon and Mars often leads to slippage as legs disturb the soil. To address this, a walking technique has been proposed that enhances soil support by transmitting vibrations from the robot’s legs. This approach aims to improve mobility by increasing the ground’s bearing capacity. To evaluate its effectiveness in space-like environments, this study experimentally investigates the effect of vibration on bearing capacity under low atmospheric pressure, which can influence soil behavior due to reduced air resistance. Using Silica No. 5 and Toyoura sand as test materials, experiments were conducted to compare bearing capacities under standard and low pressure. The results demonstrate that applying vibration significantly improves bearing capacity and that the influence of atmospheric pressure is minimal. These findings support the viability of vibration-assisted locomotion for planetary rovers operating in low-pressure extraterrestrial environments. Full article

Mars has been a primary focus of planetary science, with significant advancements over the past two decades across disciplines including geological evolution, surface environment, and atmospheric and space science. However, the rapid growth of the related literature has rendered traditional manual review methods increasingly inadequate. This inadequacy is particularly evident in interdisciplinary research, which is often characterized by dispersed topics and complex semantics. To address this challenge, this study proposes an automated analysis framework based on natural language processing (NLP) to systematically review the Martian research in Earth and space science over the past two decades. The research database contains 151,196 Mars-related sentences extracted from 10,655 publications spanning 2001 to 2024. Using machine learning techniques, the framework clusters Mars-related sentences into semantically coherent groups and applies topic modeling to extract core research themes. It then analyzes their temporal evolution across the Martian solid, surface, atmosphere, and space environments. Finally, through sentiment analysis and semantic matching, it highlights unresolved scientific questions and potential directions for future research. This approach offers a novel perspective on the knowledge structure underlying Mars exploration and demonstrates the potential of NLP for large-scale literature analysis in planetary science. The findings potentially provide a structured foundation for building an interdisciplinary, peer-reviewed Mars knowledge base, which may inform future scientific research and mission planning. Full article

This study examines the use of a mass-abatement scalable system with managed aquifer recharge (MAR-MASS) as a sustainable solution for restoring salinized aquifers and improving water quality by removing dissolved salts. It offers a practical remediation approach for aquifers affected by salinization in coastal regions, agricultural areas, and contaminated sites, where variable-density flow poses a challenge. Numerical simulations assessed hydrogeological properties such as hydraulic conductivity, anisotropy, specific yield, mechanical dispersion, and molecular diffusion. A conceptual model integrated hydraulic conditions with spatial and temporal discretization using the FLOPY API for MODFLOW 6 and the IFM API for FEFLOW 10. Python algorithms were run within the high-performance computing (HPC) server, executing simulations in parallel to efficiently process a large number of scenarios, including both preprocessing input data and post-processing results. The study simulated 6950 scenarios, each modeling flow and transport processes over 3000 days of method implementation and focusing on mass extraction efficiency under different initial salinity conditions (3.5 to 35 kg/m³). The results show that the MAR-MASS effectively removed salts from aquifers, with higher hydraulic conductivity prolonging mass removal efficiency. Of the scenarios, 88% achieved potability (0.5 kg/m³) in under five years; among these, 79% achieved potability within two years, and 92% of cases with initial concentrations of 3.5–17.5 kg/m³ reached potability within 480 days. This study advances scientific knowledge by providing a robust model for optimizing managed aquifer recharge, with practical applications in rehabilitating salinized aquifers and improving water quality. Future research may explore MAR-MASS adaptation for diverse hydrogeological contexts and its long-term performance. Full article

Although cranial growth has been extensively explored, forensic and biological anthropology lack a formal incorporation of how cranial growth processes impact the adult phenotype and downstream biological profile estimations. Objectives: This research uses an ontogenetic framework to identify when interlandmark distances (ILDs) stabilize during growth to reach adult levels of variation and to evaluate patterns of cranial sexual size dimorphism. Methods: Multivariate adaptive regression splines (MARS) were conducted on standardized cranial ILDs for 595 individuals from the Subadult Virtual Anthropology Database (SVAD) and the Forensic Data Bank (FDB) aged between birth and 25 years. Cross-Validated R-squared (CVRSq) values evaluated ILD variation explained by age while knot placements identified meaningful changes in ILD growth trajectories. Results: Results reveal the ages at which males and females reach craniometric maturity across splanchnocranium, neurocranium, basicranium and cross-regional ILDs. Changes in growth patterns observed here largely align with growth milestones of integrated soft tissue and skeletal structures as well as developmental milestones like puberty. Conclusions: Our findings highlight the variability in growth by sex and cranial region and move forensic anthropologists towards recognizing cranial growth as a mosaic, continuous process with overlap between subadults and adults rather than consistently approaching subadult and adult research separately. Full article

Future planetary exploration missions will rely heavily on efficient human–robot interaction to ensure astronaut safety and maximize scientific return. In this context, digital twins offer a promising tool for planning, simulating, and optimizing extravehicular activities. This study presents the development and evaluation of a digital twin for the AMADEE-24 analog Mars mission, organized by the Austrian Space Forum and conducted in Armenia in March 2024. Alternative local positioning methods were evaluated to enhance the system’s utility in Global Navigation Satellite System (GNSS)-denied environments. The digital twin integrates telemetry from the Aouda space suit simulators, inertial measurement unit motion capture (IMU-MoCap), and sensor data from the Intuitive Rover Operation and Collecting Samples (iROCS) rover. All nine experiment runs were reconstructed successfully by the developed digital twin. A comparative analysis of localization methods found that Simultaneous Localization and Mapping (SLAM)-based rover positioning and IMU-MoCap localization of the astronaut matched Global Positioning System (GPS) performance. Adaptive Cluster Detection showed significantly higher deviations compared to the previous GNSS alternatives. However, the IMU-MoCap method was limited by discontinuous segment-wise measurements, which required intermittent GPS recalibration. Despite these limitations, the results highlight the potential of alternative localization techniques for digital twin integration. Full article

A Digital Elevation Model (DEM) provides accurate topographic data for planetary exploration (e.g., Moon and Mars), essential for tasks like lander navigation and path planning. This study proposes the first latent diffusion-based algorithm for DEM generation, leveraging a conditional decoder to enhance reconstruction accuracy from RGB satellite images. The algorithm performs the diffusion process in the latent space and uses a conditional decoder module to enhance the decoding accuracy of the DEM latent vectors. Experimental results show that the proposed algorithm outperforms the baseline algorithm in terms of reconstruction accuracy, providing a new technical approach to efficiently reconstruct DEMs for extraterrestrial planets. Full article

The ongoing exploration of planets such as Mars is producing a wealth of data to define habitable environments beyond the Earth. The inferred presence of neutral to alkaline aqueous fluids on Mars in its early history suggests that many potentially habitable environments existed on the planet. Terrestrial analogues with similar chemical and physical properties are being explored and characterized in order to assess their suitability for triggering the Origin of Life on Mars. Recently, a novel Mars analogue site has been identified in the Bagno dell’Acqua Lake, which is located in the island of Pantelleria in Sicily (Italy). We report here that microbialite from the Bagno dell’Acqua Lake acts as an efficient catalyst for prebiotic processes, starting from a ternary mixture of well-recognized chemical precursors, including ammonium formate, diaminomalonitrile, and alpha-amino acids. Under thermal conditions, significant amounts of building blocks of both RNA and PNA were obtained. Furthermore, samples of the water from the Bagno dell’Acqua Lake have been found to promote the polymerization of the H-form of 3′,5′-cyclic GMP, resulting in the generation of RNA oligomers of up to 15 units in length. Full article

Laser-induced breakdown spectroscopy (LIBS) has played a critical role in Mars exploration missions, substantially contributing to the geochemical analysis of Martian surface substances. However, the complex nonlinearity of LIBS processes can considerably limit the quantification accuracy of conventional LIBS chemometric methods. Hence chemometrics based on artificial neural network (ANN) algorithms have become increasingly popular in LIBS analysis due to their extraordinary ability in nonlinear feature modeling. The hidden layer activation functions are key to ANN model performance, yet common activation functions usually suffer from problems such as gradient vanishing (e.g., Sigmoid and Tanh) and dying neurons (e.g., ReLU). In this study, we propose a novel LIBS quantification method, named the Bayesian optimization-based tunable Softplus backpropagation neural network (BOTS-BPNN). Based on a dataset comprising 1800 LIBS spectra collected by a laboratory duplicate of the MarSCoDe instrument onboard the Zhurong Mars rover, we have revealed that a BPNN model adopting a tunable Softplus activation function can achieve higher prediction accuracy than BPNN models adopting other common activation functions if the tunable Softplus parameter β is properly selected. Moreover, the way to find the proper β value has also been investigated. We demonstrate that the Bayesian optimization method surpasses the traditional grid search method regarding both performance and efficiency. The BOTS-BPNN model also shows superior performance over other common machine learning models like random forest (RF). This work indicates the potential of BOTS-BPNN as an effective chemometric method for analyzing Mars in situ LIBS data and sheds light on the use of chemometrics for data analysis in future planetary explorations. Full article

The Zhurong rover of the Tianwen-1 mission has detected sulfates in its landing area. The analysis of these sulfates provides scientific evidence for exploring past hydration conditions and atmospheric evolution on Mars. As a non-contact technique with long-range detection capability, Laser-Induced Breakdown Spectroscopy (LIBS) is widely used for elemental identification on Mars. However, quantitative analysis of anionic elements using LIBS remains challenging due to the weak characteristic spectral lines of evaporite salt elements, such as sulfur, in LIBS spectra, which provide limited quantitative information. This study proposes a quantitative analysis method for sulfur in sulfate-containing Martian analogs by leveraging spectral line correlations, full-spectrum information, and prior knowledge, aiming to address the challenges of sulfur identification and quantification in Martian exploration. To enhance the accuracy of sulfur quantification, two analytical models for high and low sulfur concentrations were developed. Samples were classified using infrared spectroscopy based on sulfur content levels. Subsequently, multimodal deep learning models were developed for quantitative analysis by integrating LIBS and infrared spectra, based on varying concentrations. Compared to traditional unimodal models, the multimodal method simultaneously utilizes elemental chemical information from LIBS spectra and molecular structural and vibrational characteristics from infrared spectroscopy. Considering that sulfur exhibits distinct absorption bands in infrared spectra but demonstrates weak characteristic lines in LIBS spectra due to its low ionization energy, the combination of both spectral techniques enables the model to capture complementary sample features, thereby effectively improving prediction accuracy and robustness. To validate the advantages of the multimodal approach, comparative analyses were conducted against unimodal methods. Furthermore, to optimize model performance, different feature selection algorithms were evaluated. Ultimately, an XGBoost-based feature selection method incorporating prior knowledge was employed to identify optimal LIBS spectral features, and the selected feature subsets were utilized in multimodal modeling to enhance stability. Experimental results demonstrate that, compared to the BPNN, SVR, and Inception unimodal methods, the proposed multimodal approach achieves at least a 92.36% reduction in RMSE and a 46.3% improvement in R². Full article

Fish kills are sudden mass mortalities that occur in freshwater and marine systems worldwide. Fish kill surveys are essential for assessing the ecological and economic impacts of fish kill events, but are often labor-intensive, time-consuming, and spatially limited. This study aims to address these challenges by exploring the application of unoccupied aerial systems (or drones) and deep learning techniques for coastal fish carcass detection. Seven flights were conducted using a DJI Phantom 4 RGB quadcopter to monitor three sites with different substrates (i.e., sand, rock, shored Sargassum). Orthomosaics generated from drone imagery were useful for detecting carcasses washed ashore, but not floating or submerged carcasses. Single shot multibox detection (SSD) with a ResNet50-based model demonstrated high detection accuracy, with a mean average precision (mAP) of 0.77 and a mean average recall (mAR) of 0.81. The model had slightly higher average precision (AP) when detecting large objects (>42.24 cm long, AP = 0.90) compared to small objects (≤14.08 cm long, AP = 0.77) because smaller objects are harder to recognize and require more contextual reasoning. The results suggest a strong potential future application of these tools for rapid fish kill response and automatic enumeration and characterization of fish carcasses. Full article

Rapid urbanization worldwide has led to ecological challenges, undermining eco-environmental resilience (EER). Understanding the coupling coordination between new-type urbanization (NTU) and EER is critical for achieving sustainable urban development. This study investigates the Chengdu–Chongqing Economic Circle using the coupling coordination degree (CCD) model to evaluate NTU-EER coordination levels and their spatiotemporal evolution. A random forest (RF) model, interpreted with Shapley Additive exPlanations (SHAP) and Partial Dependence Plot (PDP) algorithms, explores nonlinear driving mechanisms, while Geographically and Temporally Weighted Regression (GTWR) assesses drivers’ spatiotemporal heterogeneity. The results reveal the following: (1) NTU and EER levels steadily improved from 2004 to 2022, although coordination between cities still requires enhancement; (2) CCD exhibited a temporal pattern of “progressive escalation and continuous optimization,” and a spatial pattern of “dual-core leadership and regional diffusion,” with most cities shifting from NTU-lagged to synchronized development; (3) environmental regulations (MAR) and fixed asset investment (FIX) emerged as the most influential CCD drivers, and significant nonlinear interactions were observed, particularly those involving population size (HUM); (4) CCD drivers exhibited complex spatiotemporal heterogeneity, characterized by “stage dominance—marginal variation—spatial mismatch.” These findings enrich existing research and offer policy insights to enhance coordinated development in the Chengdu–Chongqing Economic Circle. Full article

Background: Lung ischemia reperfusion injury (LIRI) is a severe complication after lung transplantation (LT). Ferroptosis contributes to the pathogenesis of LIRI. Maresin1 (MaR1) is an endogenous pro-resolving lipid mediator that exerts protective effects against multiorgan diseases. However, the role and mechanism of MaR1 in the ferroptosis of LIRI after LT need to be further investigated. Methods: A mouse LT model and a pulmonary vascular endothelial cell line after hypoxia reoxygenation (H/R) culture were established in our study. Histological morphology and inflammatory cytokine levels predicted the severity of LIRI. Cell viability and cell injury were determined by CCK-8 and LDH assays. Ferroptosis biomarkers, including Fe²⁺, MDA, 4-HNE, and GSH, were assessed by relevant assay kits. Transferrin receptor (TFRC) and Acyl-CoA Synthetase Long Chain Family Member 4 (ACSL4) protein levels were examined by western blotting. In vitro, lipid peroxide levels were detected by DCFH-DA staining and flow cytometry analysis. The ultrastructure of mitochondria was imaged using transmission electron microscopy. Furthermore, the potential mechanism by which MaR1 regulates ferroptosis was explored and verified with signaling pathway inhibitors using Western blotting. Results: MaR1 protected mice from LIRI after LTx, which was reversed by the ferroptosis agonist Sorafenib in vivo. MaR1 administration decreased Fe²⁺, MDA, 4-HNE, TFRC, and ACSL4 contents, increased GSH levels, and ameliorated mitochondrial ultrastructural injury after LTx. In vitro, Sorafenib resulted in lower cell viability and worsened cell injury and enhanced the hallmarks of ferroptosis after H/R culture, which was rescued by MaR1 treatment. Mechanistically, the protein kinase A and YAP inhibitors partly blocked the effects of MaR1 on ferroptosis inhibition and LIRI protection. Conclusions: This study revealed that MaR1 alleviates LIRI and represses ischemia reperfusion-induced ferroptosis via the PKA-Hippo-YAP signaling pathway, which may offer a promising theoretical basis for the clinical application of organ protection after LTx. Full article