Search Results (7,261)

Amplification of MDM2 is the molecular hallmark of atypical lipomatous tumor/well-differentiated liposarcoma (ALT/WDL) and dedifferentiated liposarcoma (DDL). While fluorescence in situ hybridization (FISH) is widely used for diagnosis, the diagnostic and prognostic value of droplet digital PCR (ddPCR) remains poorly defined. We retrospectively analyzed 341 primary adipocytic tumors, including 85 liposarcomas (22 DDL), using ddPCR to quantify MDM2 copy number variation (CNV). Diagnostic performance was compared with FISH, and associations with clinicopathological variables and outcomes were evaluated using non-parametric tests, ROC analysis, survival analysis, and Firth’s penalized Cox models. Comparison with FISH confirmed the diagnostic utility of ddPCR for detecting MDM2 amplification, while quantitative CNV assessment provided additional prognostic information. CNV values were significantly higher in deep-seated and dedifferentiated tumors and were strongly associated with local recurrence. ROC analysis identified a threshold of 16.85 copies predicting both dedifferentiation and recurrence (AUC 0.982 and 0.942, respectively). Patients with CNV ≥ 16.85 copies had significantly shorter recurrence-free and overall survival. In multivariable analysis, high CNV remained an independent predictor of recurrence (HR 36.6, 95% CI 4.0–4914.2). These findings support ddPCR as a robust method for MDM2 assessment and suggest that quantitative MDM2 copy number may improve both diagnosis and risk stratification in liposarcoma. Full article

Magnetic polymer nanocomposites (MPNCs) have attracted considerable attention as advanced multifunctional materials for water purification due to their high adsorption capacity, magnetic recoverability, and excellent reusability. This review presents a comprehensive overview of recent developments in the synthesis, characterization, and environmental applications of MPNCs for wastewater treatment. Particular emphasis is placed on the principal synthesis strategies, including in situ and ex situ approaches, and their influence on nanoparticle dispersion, interfacial interactions, and the physicochemical properties of the resulting nanocomposites. The review covers the most widely investigated magnetic nanomaterials, such as Fe₃O₄, γ-Fe₂O₃, CoFe₂O₄, ZnFe₂O₄, and other ferrites, incorporated into natural and synthetic polymer matrices including chitosan, cellulose, alginate, polyaniline, polypyrrole, poly(vinyl alcohol), and polystyrene. Advanced characterization techniques, including X-ray diffraction (XRD), scanning and transmission electron microscopy (SEM/TEM), Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), thermogravimetric analysis (TGA), vibrating sample magnetometry (VSM), and superconducting quantum interference device (SQUID) measurements, are discussed to evaluate the structural, chemical, thermal, and magnetic properties of these hybrid materials. The adsorption performance and underlying mechanisms of MPNCs for the removal of heavy metals, dyes, pharmaceutical compounds, organic pollutants, and oil contaminants are critically analyzed, highlighting the roles of polymer functionalization, nanocomposite architecture, and magnetic separation in enhancing treatment efficiency and reusability. In addition, the contribution of density functional theory (DFT) to understanding adsorption mechanisms and guiding the rational design of high-performance adsorbents is reviewed. Finally, current challenges and future perspectives, including green synthesis, multifunctional and stimuli-responsive materials, scalable manufacturing, and industrial implementation, are discussed. This review provides a comprehensive framework for the design and development of next-generation magnetic polymer nanocomposites for sustainable water remediation applications. Full article

The increasing accumulation of industrial solid waste and worsening groundwater pollution pose significant environmental challenges. This study introduces a Si-Ca-Fe-based ceramsite from solid wastes with exceptional Cd adsorption capacity. A comprehensive investigation was conducted on the phase evolution, adsorption properties, and underlying mechanisms of the synthesized ceramsite. The findings revealed that the optimum sintering temperature for the ceramsite, characterized by austenite and pyroxene, was 1140 °C, which balanced mechanical strength and Cd adsorption capacity. Remarkably, the ceramsite (6.0 g) was immersed in 5 L of a Cd(NO₃)₂ solution for 21 h under initial conditions (pH = 7 and temperature = 20 °C), and the ceramsite exhibited a notable Cd adsorption capacity of 5.47 mg/g (initial Cd concentration: 53.42 mg/L), with a maximum theoretical capacity of 9.32 mg/g according to the Langmuir isotherm. An in-depth analysis of adsorption kinetics, phase composition, and EDS data indicated that the primary adsorption mechanism was the zero-valent iron (ZVI) corrosion-driven reaction. This ZVI formed in situ under reducing conditions during the ceramsite’s preparation and subsequently aided in the precipitation of Cd(OH)₂. Additionally, the honeycomb structure of the ceramsite, containing fine pores (approximately 2–5 μm), enhanced physical adsorption via capillary action, further improving Cd removal. These insights offer a robust foundation for crafting efficient, solid waste-derived ceramsite tailored for heavy metal extraction from polluted water, presenting a compelling approach to concurrent waste recycling and environmental remediation. Full article

Marine oil spills represent a critical environmental threat. Petroleum contamination systematically accumulates in the world’s oceans, driving severe and long-term damage to the biodiversity of vulnerable coastal ecosystems. As its primary objective, this study assesses the ocean’s intrinsic genetic capacity to degrade aliphatic and aromatic hydrocarbons. Using the Ocean Gene Atlas v2.0 (OGA2) database, bacterial metabolic pathways were profiled via a four-marker framework: PF00487 (AlkB) and PF03433 (LadA) for medium and long-chain alkanes, alongside PF00355 and PF00848 domains for aromatic ring activation. The analyses revealed that while salinity levels between 34–36 PSU sustain baseline abundances, temperature acts as a primary selective filter, segregating microbial communities into distinct thermal niches. Medium-chain aliphatic potential (PF00487) is ubiquitous, reaching maximum values in surface polar waters near 0 °C before declining with depth. Conversely, long-chain machinery (PF03433) is restricted to warm surface hotspots. Aromatic-degrading potential (PF00355/PF00848) displayed high thermal resilience, narrowing vertically except for a mesopelagic cluster in the Arabian Sea. Global taxonomic analysis confirmed the dominance of Pseudomonadota (59%), which was mainly represented by the class Gammaproteobacteria (15%), with Alcanivorax (10%) as the most abundant genus. On the other hand, aromatic degraders persist as a low-abundance seed bank. In conclusion, the mere presence of specific genes does not automatically imply metabolic expression; actual in situ biodegradation remains strictly governed by transcriptional triggers and environmental factors. Full article

Permafrost peatlands in high-altitude regions store substantial amounts of organic carbon, yet the biogeochemical consequences of thermokarst collapse remain poorly understood. Using a space-for-time substitution approach, we selected four habitats representing a thermokarst development sequence in the Altai Mountains peatlands—slightly collapsed peat mounds (P1), severely collapsed peat mounds (P2), thawed herbaceous peat (PB1), and thermokarst ponds (PB2)—and conducted in situ greenhouse gas flux monitoring, soil physicochemical analysis, enzyme activity assays, and structural equation modeling. We found that thermokarst development fundamentally altered the greenhouse gas source–sink balance through three interconnected mechanisms. First, CO₂ fluxes shifted from net emission in P1 (684.1 mg m⁻² h⁻¹) to net uptake in PB2 (−25.6 mg m⁻² h⁻¹), driven primarily by the oxidative loss of mineral-associated organic carbon in the 40–60 cm layer (71.3% loss), whereas lateral dissolved organic carbon export accounted for only 12.3% of total carbon loss. Second, CH₄ fluxes in PB2 (3.8 ± 0.7 mg m⁻² h⁻¹) reached approximately 43% of the theoretical maximum, with this suppression associated with phosphorus limitation (total phosphorus < 0.05 g kg⁻¹) and a marked reduction in alkaline phosphatase activity. Third, N₂O uptake increased along the thaw sequence to −28.6 μg m⁻² h⁻¹ in PB2, with the 40–80 cm layer contributing 42% more than the surface layer. This increase in N₂O uptake occurred when the soil C/N ratio exceeded 300, a threshold that reflects the substantial stoichiometric imbalance between carbon and nitrogen following thermokarst development. These findings demonstrate that the transition from peat mounds to thermokarst ponds alters the net greenhouse gas source–sink balance through changes in MAOC stability, phosphorus availability, and carbon-to-nitrogen stoichiometry. Our results provide empirical constraints for evaluating carbon-climate feedbacks in cold-region peatlands. Full article

Objectives: Insomnia is a highly prevalent sleep disorder involving complex neurochem-ical dysregulation; however, the spatial distribution of neurotransmitters and small-molecule metabolites across distinct brain microregions in the insomniac state re-mains poorly characterized. This study aimed to map region-specific metabolic perturba-tions in situ in a p-chlorophenylalanine (PCPA)-induced insomnia rat model using opti-mized matrix-assisted laser desorption/ionization mass spectrometry imaging (MAL-DI-MSI) integrated with targeted metabolomics validation. Methods: On-tissue chemical derivatization MALDI-MSI was optimized using α-cyano-4-hydroxycinnamic acid (CHCA) as the matrix on a Bruker tims TOF flex mass spectrometer. The rats received PCPA (400 mg/kg, intraperitoneal) for three days to establish the insomnia model. Metabolite identifi-cation was conducted using MetaboScape® software (2020b) and the Human Metabolome Database. Ultra-performance liquid chromatography–tandem mass spectrometry was em-ployed to quantify nine key neurotransmitters and metabolites across six brain microre-gions. Key synthetic enzyme expression was evaluated by immunofluorescence and West-ern blotting analyses. Results: TMP-TFB-derived brain slices clearly showed the distribu-tion of neurotransmitters in brain microregions. MALDI-MSI demonstrated that the spatial distribution and abundance of eight neurotransmitters were disturbed in brains of PCPA-induced insomniac rats. A total of 346 metabolites were characterized across six brain microregions (cerebellum, cortex, hippocampus, brainstem, hypothalamus, and stri-atum), with principal coordinate analysis revealing clear metabolic separation between control and insomniac rats. PCPA treatment markedly disrupted tryptophan and tyrosine metabolism, evidenced by decreased 5-HT, 5-HTP, and 5-HIAA, alongside region-specific alterations in DA, NE, HVA, and Ach. Additionally, GABA levels decreased in the hippo-campus, striatum, and hypothalamus, whereas glutamate increased throughout the brain. Targeted metabolomics validated the MSI findings, and Bland–Altman analysis confirmed good consistency between the two analytical platforms. PCPA further disturbed the meta-bolic enzymes MAOA, DDC, and TPH2 within the Trp-5-HTP-5-HT-5-HIAA metabolic pathway in the brainstem and TYH and DBA within the tyrosine-DA-NE metabolic pathway in the striatum. Conclusions: This study demonstrates that region-specific altera-tions in tryptophan and tyrosine metabolism pathways provide mechanistic insights into insomnia pathogenesis and potential therapeutic targets. Full article

The newly discovered Caijiagou gold deposit is hosted in metasedimentary rocks of the Silurian Taiyangsi Formation in the West Qinling Orogen (WQO), central China. Three mineralization stages are recognized: (1) the quartz–sericite–pyrite stage (Stage I), characterized by fine-grained, disseminated pyrite (Py1) and arsenopyrite (Apy1) with trace amounts of native gold; (2) the main ore-stage, the quartz–polymetallic sulfide–ankerite stage (Stage II), which contains coarse-grained euhedral pyrite (Py2) and arsenopyrite (Apy2) intergrown with ankerite and native gold; and (3) the post-ore calcite stage (Stage III), which is barren. Hydrothermal alteration assemblages include silicification, sericitization, pyritization, and carbonatization. In situ trace element analyses show that gold is mainly hosted in Py2 (avg. 2.86 ppm Au) and Apy2 (avg. 1.95 ppm Au), with consistently low Co/Ni ratios (<0.6) in ore-stage sulfides, supporting a metamorphic fluid origin. Sulfur isotope values (δ³⁴S = +6.47‰ to +11.96‰) point to sulfur derived from thermochemical reduction of marine sulfate. Apatite from the main ore stage (Stage II) yields a U–Pb lower intercept age of 237 ± 4.3 Ma (MSWD = 0.89), placing the mineralization in the Middle Triassic (Indosinian orogeny). These results are consistent with a sediment-hosted orogenic gold model, and the geochemical and geochronological signatures provide insights into the ore-forming process and regional metallogeny of the WQO. Full article

This study aims to estimate latent heat flux (LHF) over the central Red Sea during the summer months (July and August) of 2000–2020, corresponding with the occurrence of the Tokar Gap (TG) wind jets. Sea surface temperature (SST) was derived from the SeaDAS-based multi-sensor ESA CCI/C3S satellite product (AVHRR-SST), and wind data were obtained from the scatterometer product. Both datasets were re-gridded to a uniform spatial resolution of 0.05°. The AVHRR-SST and scatterometer wind speed were compared with the corresponding ERA5 reanalysis fields. Because both the satellite-derived estimates and ERA5 are model-based products rather than independent in situ observations, this comparison constitutes an intercomparison between two approaches rather than a validation. The AVHRR-SST and scatterometer wind speed showed good agreement with ERA5 fields (correlation coefficients CC = 0.66 and 0.93, respectively). The spatial distribution of the estimated LHF reproduced the ERA5 LHF patterns but with relatively lower magnitudes. Time series analysis near the TG region showed that the estimated LHF underestimated ERA5 values, with a correlation coefficient of 0.77 and a root mean square error (RMSE) of 25.8 W/m². The results represent an intercomparison between two model- and satellite-based approaches and are limited by the absence of independent in situ buoy observations for direct validation. Full article

Medicinal plants constitute an essential component of global biodiversity and have long served as a primary source of traditional and modern therapeutic agents. Forest ecosystems harbor a significant proportion of medicinal plant diversity, providing habitats for numerous species with recognized pharmacological value. However, increasing anthropogenic pressures, including habitat destruction, overexploitation, land-use change, forest fragmentation, and climate change, have contributed to the decline of many medicinal plant populations worldwide. Consequently, a growing number of medicinal forest species are now classified as endangered, threatened, vulnerable, or protected under national and international conservation frameworks. This review synthesizes current scientific knowledge on endangered and protected medicinal plants found in forest ecosystems. A mixed-methods approach combining bibliometric assessment and qualitative literature analysis was employed to evaluate publication trends, geographical distribution, research hotspots, ecological characteristics, genetic resources, pharmacological properties, and conservation strategies related to threatened medicinal forest species. The review identified 77 medicinal plant species of conservation concern distributed across diverse forest regions worldwide, with the highest research activity originating from Asia, particularly India and China. The findings highlight the ecological importance and therapeutic potential of these species while emphasizing the critical threats posed by habitat degradation, unsustainable harvesting, and climate change. Advances in habitat suitability modeling, molecular genetics, ex situ propagation, and conservation planning have improved opportunities for species protection; however, significant knowledge gaps remain regarding population dynamics, long-term conservation effectiveness, and sustainable utilization. Strengthening integrated conservation approaches that combine habitat protection, sustainable management, scientific research, and traditional ecological knowledge is essential for safeguarding endangered medicinal forest plants and ensuring their continued contribution to biodiversity conservation, healthcare, and future drug discovery. Full article

Handling hydrogen-rich atmospheres requires materials that do not deteriorate in the presence of hydrogen and that ensure safe operation. Often high strength metallic materials, however, may show catastrophic mechanical failure in the presence of hydrogen. This phenomenon, called hydrogen embrittlement, can be very dangerous, as these failures occur in a time-delayed and sudden manner. Two commercially available materials, AMPCOLOY^® 83, a copper beryllium alloy, and AMPCO^® 18, an aluminum bronze, have been investigated to clarify their susceptibility to hydrogen embrittlement. Hydrogen permeation measurements were performed to assess diffusivity in the materials, and hydrogen content was analyzed by thermal desorption analysis (TDA) after electrochemical charging. Mechanical properties in hydrogen-affected state were assessed by slow strain rate tensile tests (SSRT), with in situ electrochemical charging and post-test fractographic inspection of the fracture surfaces. While the aluminum bronze showed no noticeable hydrogen-related deterioration, copper beryllium alloy experienced some embrittlement, however, having a low fracture strain even in the uncharged state. Full article

The root development strategies of individual varieties are key factors in adaptability. In our experiment, the root morphological characteristics of three winter wheat varieties were examined at specific soil depths of 30, 60, and 90 cm throughout the growing season using the CI-600 in situ root scanner. Plants were grown under optimal water supply and simulated drought conditions. After maturity, a complete biomass and yield analysis was conducted, and the connection between the root structure and production biology parameters was evaluated. There were considerable differences in the root structure among the varieties. The root length of Mv-Kolompos remained stable in the upper and middle soil layers even under water shortage. Mv-Verbunkos had an extensive root system, but the roots were concentrated in the upper soil layers and showed growth in this layer under drought conditions. The root length and surface of the Aura variety were lower than those of the other two varieties; however, the lateral roots of this genotype rapidly reached the deeper soil layers. However, even with regulated root development, this variety was unable to offset the negative effects of drought, and both biomass production and yield decreased significantly as a result of water shortage. Full article

The escalating accumulation of microplastics (MPs) in marine ecosystems presents a critical environmental crisis. However, current monitoring efforts rely heavily on labor-intensive, contamination-prone, and time-consuming laboratory analyses. While these conventional off-chip methods provide high accuracy, they inherently lack the throughput and autonomy required for continuous, real-time oceanic surveillance. To bridge this technological gap, microfluidic technologies (Lab-on-a-Chip) provide a viable route towards miniaturized, reagent-free in situ detection with reduced sample volumes and continuous operation capability. This review examines the transition from benchtop to field-deployable platforms and organizes the available microfluidic approaches for MP analysis into a structured overview. We examine on-chip sample manipulation and complementary separation techniques, such as acoustophoresis, dielectrophoresis, and optical tweezers, which are essential for isolating target particles from complex environmental matrices and overcoming intrinsic microfluidic challenges. Following sample preparation, we provide a comprehensive evaluation of state-of-the-art optical and spectroscopic identification methods optimized for continuous flow detection. Finally, we address current analytical limitations and discuss how the integration of machine learning with dynamic spectral libraries could enable autonomous, field-deployed monitoring networks for long-term MP surveillance. Full article

Wellbore instability poses a significant challenge to the safe and long-term production of natural gas hydrates (NGHs). Characterizing the geometry of the wellbore-adjacent plastic zone is critical for evaluating geomechanical risks during hydrate exploitation. In this paper, an elastic–plastic analytical model incorporating the Mohr–Coulomb failure criterion is developed to describe the stress distribution around the borehole under non-uniform in situ stress conditions. Particular attention is paid to the role of hydrate saturation, which is integrated into the constitutive framework to reflect the cementation effect of NGH-bearing sediments (GHBS). Analytical solutions for the stress fields in both the elastic and plastic regions are derived, which are accompanied by a computational scheme for determining the plastic zone radius. Using site-specific mechanical parameters from the Shenhu area in the South China Sea, a parametric analysis is conducted to quantify the influences of hydrate saturation, reservoir depressurization, and stress anisotropy on the evolution of the plastic zone shape. The results indicate that elevated hydrate saturation enhances the load-bearing capacity of the formation, whereas depressurization significantly expands the plastic region, leading to severe wellbore instability. These findings provide theoretical insights for optimizing drilling strategies in deep-water hydrate reservoirs. Full article

The origin and metallogenic role of pyrite in sandstone-hosted uranium deposits remain difficult to constrain because pyrite may record both early diagenetic reduction and later ore-fluid overprinting. Here, pyrite and associated uranium minerals from mineralized and barren sandstones of the Middle Jurassic Zhiluo Formation in the Yahewan uranium deposit, southern Ordos Basin, were investigated using petrography, SEM-BSE imaging, EPMA, LA-ICP-MS trace-element analysis, and in situ sulfur isotope analysis. Pyrite occurs mainly as framboidal, colloidal, pore-filling, fracture-filling, and massive aggregates and is commonly associated with organic matter and coffinite or coffinite-like U-silicate minerals. Most pyrite domains show low Co/Ni ratios, suggesting a predominantly authigenic to sedimentary–diagenetic origin. High U, Mo, V, W, Se and As occur mainly in pyrite-rich microdomains, but high-U analyses are interpreted cautiously because some signals may include contributions from adjacent coffinite or coffinite-like U-silicate phases, fracture-hosted uranium minerals, or mixed ablation. Together, the petrographic, trace-element and sulfur isotope data support a two-stage model in which early organic matter and authigenic/biogenic pyrite created local reducing microenvironments that were later overprinted by U-bearing basinal fluids. Full article

Traditional crack monitoring methods, relying on discrete point sensors, cannot capture the full spatiotemporal evolution of cracks. To address this limitation, this paper presents a distributed online monitoring approach using ultra-weak Fiber Bragg Grating (UWFBG) array sensing technology. A 16 m full-scale π-beam was instrumented with a grating array strain sensing system and tested under progressive mid-span loading until failure. The array successfully detected crack initiation at 848.7 kN (0.9P1) and tracked the transformation from L-shaped to U-shaped cracks, yielding a final crack count of 90 with a maximum width of 1.21 mm and length of 246.5 cm at 1791.7 kN. The strain–load curves exhibited a clear linear-to-nonlinear transition and continuous slope increase, closely matching manual observations. Quantitative correlation analysis further established a strong linear relationship between UWFBG peak strains and manually measured crack widths, with the fitting equation $\mathsf{\epsilon }=7918·\mathrm{w}-110$ and a coefficient of determination R² = 0.971, providing a specimen-specific basis for strain-based crack severity estimation that requires in-situ calibration before field application. The UWFBG array maintained stable signal acquisition throughout the entire loading process, offering superior data continuity and measurement range compared to resistive strain gauges, which suffered progressive data loss after cracking. The results demonstrate that the proposed method can provide real-time, full-field strain mapping and quantitative crack evolution monitoring, offering a powerful tool for bridge health assessment. Full article