Search Results (1,284)

The authors hypothesize that idiopathic Parkinson’s disease may result from an alteration in microvascular flow at a “critical point” in the nervous system that is characterized by pigmented cells that express neuromelanin and/or lipofuscin. “Critical points” include the olfactory epithelium/bulb, the autonomic nervous system, the enteric nervous system, the prefrontal–cortico-pontine network, and the amygdala. Hypoxia–ischemia following blood flow disturbance would recruit and activate leukocytes and induce the infiltration of peripheral immune cells into neural tissue. The excess of toxic factors produced by hyperactive immune cells, such as myeloperoxidase and its derivatives, would cause the oxidation of lipids, proteins, and biogenic monoamines such as dopamine, which in turn would facilitate the accumulation and precipitation of neuromelanin, lipofuscin, and alpha-synuclein. In addition, neuromelanin and lipofuscin precipitates may accentuate the misfolding and aggregation of alpha-synuclein. This “amplification” mechanism could help explain the crucial role of pigmented neurons in the onset of Parkinson’s disease pathology, triggering abnormal neurotoxic alpha-synuclein spread throughout the nervous system from the “critical point” of origin, and enabling a self-perpetuating degenerative process. The proposed hypothesis may have implications for the identification of new therapeutic targets, early prevention strategies, and the development of vascular and/or immune biomarkers. Full article

To effectively manage and conserve ecosystems, it is crucial to understand how vegetation changes over time and space and what drives these changes. The Normalized Difference Vegetation Index (NDVI) is a key measure of plant growth that is highly sensitive to climate variations. Despite its importance, there has been limited research on vegetation changes in the upper sections of the Irtysh River. In our study, we combined various datasets, including NDVI, temperature, precipitation, soil moisture, elevation, and land cover. We conducted several analyses, such as Theil–Sen median trend analysis, Mann–Kendall trend and mutation tests, partial correlation analysis, the geographical detector model, and wavelet analysis, to reveal the region’s pronounced warming and moistening trend in recent years, the response relationship between NDVI and the climate, and the primary drivers influencing NDVI variations. We also delved into the spatiotemporal evolution of NDVI and identified key factors driving these changes by analyzing atmospheric circulation patterns. Our main findings are as follows: (1) Between 1901 and 2022, the area’s temperature rose by 0.018 °C/a, with a noticeable increase in the rate of warming around 1990; precipitation increased by 0.292 mm/a. From 1950 to 2022, soil moisture exhibited a steady increase of 0.0002 m³ m⁻³/a. Spatial trend distributions indicated that increasing trends in temperature and precipitation were evident across the entire region, while trends in soil moisture showed significant spatial variation. (2) During 1982 to 2022, the vegetation greening trend was 0.002/10a, indicating a gradual improvement in vegetation growth in the study area. The spatial distribution of monthly average NDVI values revealed that the main growing season of vegetation spanned April to November, with peak NDVI values occurring in June–August. Combined with serial partial correlation and spatial partial correlation analysis, temperatures during April to May effectively promoted the germination and growth of vegetation, while soil moisture accumulation from June to August (or January to August) effectively met the water demand of vegetation during its growth process, with a significant promoting effect. Geographical detector results demonstrate that temperature exhibits the strongest explanatory power for NDVI variation, whereas land cover has the weakest. The synergistic promotional effect of multiple climatic factors is highly pronounced. (3) Wavelet analysis revealed that the periodic characteristics of NDVI and climate variables over a 2–15-year timescale may have been associated with the impacts of atmospheric circulation. Taking NDVI and climatic factors from June to August as an example, before 2000, temperature was the dominant influencing factor, followed by precipitation and soil moisture; after 2000, precipitation and soil moisture became the primary drivers. The North Atlantic Oscillation (NAO) and Arctic Oscillation (AO) were the primary atmospheric circulation patterns influencing vegetation variability in the region. Their effects were reflected in the inverse relationship observed between NAO/AO indices and NDVI, with typical phases of high and low NDVI closely corresponding to shifts in NAO and AO activity. This study helps us to understand how plants have been changing in the upper parts of the Irtysh River. These insights are critical for guiding efforts to develop the area in a way that is sustainable and beneficial for the environment. Full article

As a critical agroforestry crop in Southern China, Moso bamboo, maintains regional timber security and bamboo shoot production, with its net ecosystem productivity (NEP) directly determining dry matter accumulation and economic yield. This study integrates 2024 continuous flux observations with XGBoost and SHAP explanations to characterize the subtropical bamboo forest carbon budget and its nonlinear driving mechanisms. The results show a weak carbon sink in 2024 with an annual cumulative NEP of 120 g C m⁻², as high respiration of 860 g C m⁻² limited organic matter conversion by consuming nearly 88% of the 980 g C m⁻² total primary production. The peak production period during May and June was offset by growth stagnation in August, caused by extreme heat and drought. Net radiation served as the primary driver, with a positive contribution threshold of 75.28 W m⁻², whereas precipitation exceeding 1.85 mm or air temperatures over 17.85 °C hindered carbon accumulation through radiation attenuation and metabolic heat loss. Strong radiation–precipitation interactions confirm that water’s impacts on yield are deeply contingent upon radiation backgrounds. These nonlinear regulatory pathways provide a scientific foundation for stabilizing bamboo forest productivity through synergistic water-radiation management and structural optimization during extreme climate events. Full article

Rice (Oryza sativa L.) readily accumulates cadmium (Cd), posing dietary exposure risks in populations dependent on rice-based diets. This study investigated how sulfur (S) redox processes regulate Cd mobility in S-deficient, Cd-contaminated paddy soil under waterlogged conditions. A pot experiment was conducted with two S treatments (−S and +S, 30 mg kg⁻¹) throughout the rice growing season. S addition markedly increased pore water S²⁻ concentrations during early growth (tillering) and mid-season (booting) and suppressed the diffusion of SO₄²⁻ from non-rhizosphere to rhizosphere at later stages (filling–maturity). Consequently, Cd in soil pore water was significantly lower in +S than −S treatments at all stages. Sulfur-amended soil showed a redistribution of Cd from labile fractions (exchangeable and carbonate-bound) to more stable fractions (Fe/Mn oxide-bound). Sulfur application also altered the rhizosphere microbiome: the relative abundance of sulfate-reducing bacteria (SRB) increased at the booting and filling stages, while sulfur-oxidizing bacteria (SOB) became more dominant at maturity. Additionally, +S enhanced Cd sequestration on rice root iron plaque by 32–67% during the grain-filling and maturity stages compared to −S. Throughout the rice growing period, redox-driven shifts in the S²⁻/SO₄²⁻ ratio emerged as a key control on Cd behavior, with low pe + pH (strongly reducing conditions) promoting Cd sulfide precipitation and high pe + pH (more oxidizing conditions) causing Cd remobilization. Full article

The sustainable management of Northern China’s vulnerable agro-pastoral ecotone requires a clearer understanding of how tillage systems affect crop productivity through local soil-climate interactions. Therefore, this study was conducted to quantify and compare the long term effects of different tillage practices on soil hydrothermal regimes, resource use efficiency, and maize yield stability in a semi-arid agroecosystem. A long term five-year field experiment with maize was conducted in this ecotone to assess three tillage methods: no tillage (NT), deep ploughing (DP), and conventional rotary tillage (RT). Seasonal monitoring included soil moisture, temperature, bulk density, and straw cover. Analyses focused on soil water use efficiency (WUE), the production efficiency per soil thermal unit (PEsoil), and pathways affecting theoretical calculated yield. Results show that relative to RT and DP, NT consistently elevated soil water content within the 0–30 cm profile during the growing season, with the most marked increases from pre-sowing to the V12 stage. This water-conserving effect was stronger in wet years, highlighting the role of precipitation in NT’s performance. DP also retained more soil water than RT, particularly in deeper layers, though its effect was less pronounced than NT’s. Regarding temperature, NT lowered the daily mean soil temperature and accumulated growing degree days (GDD) in early growth phases, a result of residue cover buffering thermal changes. Despite reduced heat accumulation, NT achieved the greatest efficiencies for both heat and water use (PEsoil and WUE), showing increases of 62.03% and 16.64% over RT, respectively, without yield penalty. Key mechanisms include permanent straw mulch under NT, which curtails evaporation, promotes water infiltration, and stabilizes soil structure, thereby modulating hydrothermal dynamics. Structural equation modeling indicated that soil water content, ear number per hectare, and hundred-kernel weight directly and positively determined final yield. Tillage methods exerted indirect effects on yield by modifying soil physical traits and microclimatic conditions. In this semi-arid setting, both NT and DP outperformed RT in conserving soil water, moderating soil temperature, and boosting resource use efficiency. These practices present viable strategies for strengthening crop resilience and sustaining productivity amid climatic variability. Full article

This study investigates the synergistic effects of Cr–Zr and Mn–Zr additions on the microstructural evolution and mechanical properties of Al–6 wt.%Cu alloys. Alloys were designed with solute concentrations positioned below, near, and above their maximum solubility limits, and were evaluated under as-cast, T4, and T6 heat treatment conditions. Mechanical testing revealed distinct behavioral trends depending on the heat treatment: the T4 heat treatment condition generally exhibited superior hardness and yield strength, whereas the T6 heat treatment condition resulted in a slight reduction in hardness but facilitated a significant recovery in tensile strength and structural stability, particularly in alloys designed near the solubility limit. To elucidate the crystallographic origins of these mechanical variations, X-ray diffraction analysis was conducted to monitor changes in lattice parameters, dislocation density, and micro-strain. The results showed that T4 heat treatment induced lattice contraction and a decrease in dislocation density, suggesting that the high strength under T4 heat treatment conditions arises from lattice distortion caused by supersaturated solute atoms. Conversely, T6 aging led to lattice relaxation approaching that of pure aluminum, yet simultaneously triggered a re-accumulation of dislocation density and micro-strain due to the coherency strain fields surrounding precipitates, which effectively impede dislocation motion. Therefore, rather than proposing a single, definitive optimization condition, this study aims to secure foundational data regarding the correlation between these microstructural descriptors and mechanical behavior, providing a guideline for balancing the strengthening contributions in transition metal-modified Al–Cu alloys. Full article

Background: Esophageal squamous cell carcinoma (ESCC) remains a highly lethal malignancy with limited effective treatments. Broadleaf Vetch (Vicia amoena, BV) is a traditional medicinal herb with potential anticancer properties, but its mechanisms in ESCC are not fully understood. Methods: Network pharmacology was used to identify BV-related therapeutic targets and pathways. Molecular docking validated interactions between BV components and core proteins. In vitro assays evaluated proliferation, colony formation, migration, invasion, epithelial–mesenchymal transition (EMT) markers, and ferroptosis-related indices. An ESCC xenograft model was used to assess antitumor efficacy in vivo. Results: Five major BV components and 363 ESCC-related targets were identified, highlighting the PI3K–AKT pathway and key nodes such as EGFR, AKT1, SRC, TP53, and GPX4. BV significantly inhibited ESCC cell proliferation, migration, and invasion, and reversed EMT marker expression. Ferroptosis induction was evidenced by significant Fe²⁺ accumulation, elevated reactive oxygen species (ROS) and malondialdehyde levels, alongside glutathione depletion. BV treatment also precipitated mitochondrial dysfunction. In parallel, BV downregulated GPX4 and SLC7A11. Notably, these changes were largely reversed by the ferroptosis inhibitor Ferrostatin-1. In vivo, BV suppressed tumor growth and regulated EMT- and ferroptosis-associated proteins in xenograft tissues. Conclusions: BV exerts dual antitumor effects in ESCC by suppressing EMT and inducing ferroptosis. These findings suggest BV may represent a potential multi-target phytotherapeutic candidate for ESCC. Full article

Pesticide residues from agriculture pose persistent threats to ecosystems and human health. Precipitation and surface runoff facilitate the transport of pesticide residues, leading to their subsequent accumulation in lakes and rivers. Microalgae-based bioremediation offers a promising and environmentally friendly approach for degrading and detoxifying these residues. This study employed liquid chromatography–mass spectrometry (LC-MS) to determine pesticide residues in various microalgal solutions. Using three-dimensional excitation-emission matrix (3D-EEM) spectroscopy and fluorescence regional integration (FRI), we quantified the dynamics of dissolved organic matter (DOM) and its relationship with pesticide degradation in the microalgal system. Over time, Tolypothrix tenuis exhibited the highest degradation rate for THX (95.7%), while Anabaena showed the most effective degradation for ATZ (53.8%). Based on structural analysis of degradation products, three potential degradation pathways for THX and ATZ under microalgae action were proposed. Moreover, the degradation process may also involve reactive oxygen species and intracellular enzymes. Hydroxylation and carboxylation were the primary reactions involved in THX degradation, leading to ring opening and subsequent mineralization. In ATZ, the initially removed groups included methyl and carbonyl groups, with the final products undergoing hydroxylation and subsequent mineralization to water and carbon dioxide. This study, conducted within the context of aquatic environmental protection, investigates the threat of pesticide residues to aquatic ecosystems. It further elucidates the associated environmental impacts and degradation mechanisms from a microalgal perspective. Full article

The subject of this research is the exploration of the potential of remote sensing and Geographic Information Systems (GIS) for basin-scale spatio-temporal monitoring of drought and its impacts in the Ukrina River Basin, Bosnia and Herzegovina (BH), during the last decade (2015–2024). The aim is to integrate meteorological, hydrological, agricultural, and socio-economic drought signals and to delineate areas of long-term drought exposure. Meteorological drought was evaluated using CHIRPS precipitation and the Standardized Precipitation Index (SPI) calculated at 1-, 3-, 6-, and 12- month accumulation scales using Gamma fitting and a fixed long term reference period; hydrological drought was examined using available water-level records complemented by the Standardized Water Level Index (SWLI) and supported by correspondence with standardized ERA5-Land runoff anomalies; agricultural drought was mapped using remote sensing indices—the Temperature Condition Index (TCI), Vegetation Condition Index (VCI), and Vegetation Health Index (VHI)—calculated from MODIS satellite data; and socio-economic effects were assessed using municipal crop-production statistics (2015–2019). The results indicate that drought conditions were most pronounced in 2015, 2017, 2021, and especially 2022, showing consistent agreement between precipitation deficits, hydrological responses, and vegetation stress, while 2016, 2018–2020, 2023, and 2024 were generally more favorable. As a key novelty, a persistent drought-prone zone was delineated by intersecting drought-affected areas across major episodes, providing a basin-scale identification of chronic drought hotspots for a river basin in BH. The persistent zone covers 40.02% of the basin and spans nine cities and municipalities, with >93% located in Prnjavor, Derventa, Stanari, and Teslić. Hotspots are concentrated mainly in lowlands below 400 m a.s.l., with a statistically significant concentration across lower elevation classes, indicating higher long-term exposure in the central and northern valley sectors, and land use overlay further highlights high relative exposure of productive land. Overall, the integrated remote sensing and GIS framework strengthens drought monitoring by providing spatially explicit and repeatable evidence to support targeted adaptation planning and drought-risk management. Full article

Camellia oleifera, a woody oil crop unique to China, plays a crucial role in alleviating the global pressure of edible oil supply and maintaining ecological security. However, it remains challenging to accurately forecast Camellia oleifera yield in complex landscapes using only remote sensing data. The aim of this study is to develop an interpretable deep learning model, namely Shapley Additive Explanations–guided Attention–long short-term memory (SALSTM), for estimating Camellia oleifera yield by integrating an improved spectral bloom index and environmental parameters. The study area is located in Hengyang City in Hunan Province. Sentinel-2 imagery, meteorological observation from 2019 to 2023, and topographic data were collected. First, an improved spectral bloom index (ISBI) was constructed as a proxy for flowering density, while average temperature, precipitation, accumulated temperature, and wind speed were selected to represent environmental regulation variables. Second, a SALSTM model was designed to capture temporal dynamics from multi-source inputs, in which the LSTM module extracts time-dependent information and an attention mechanism assigns time-step-wise weights. Feature-level importance derived from SHAP analysis was incorporated as a guiding prior to inform attention distribution across variable dimensions, thereby enhancing model transparency. Third, model performance was evaluated using root mean square error (RMSE) and coefficient of determination (R²). The result show that the constructed SALSTM model achieved strong predictive performance in predicting Camellia oleifera yield in Hengyang City (RMSE = 0.5738 t/ha, R² = 0.7943). Feature importance analysis results reveal that ISBI weight > 0.26, followed by average temperature and precipitation from flowering to fruit stages, these features are closely associated with C. oleifera yield. Spatially, high-yield zones were mainly concentrated in the central–southern hilly regions throughout 2019–2023, In contrast, low-yield zones were predominantly distributed in the northern and western mountainous areas. Temporally, yield hotspots exhibited a gradual increasing while low-yield zones showed mild fluctuations. This framework provides an effective and transferable approach for remote sensing-based yield estimation of flowering and fruit-bearing crops in complex landscapes. Full article

Rainfall is an essential component of boreal forest ecosystems. Aerotechnogenic pollution significantly affects the composition of rainfall. To predict the dynamics of biogeochemical cycles and develop strategies to enhance forest resilience in the Arctic zone, it is necessary to study the composition and characteristics of rainfall. The objective of this study is to evaluate the variation in the chemical composition of stemflow in the most typical pine and spruce forests of Fennoscandia under conditions of aerotechnogenic pollution based on long-term monitoring data from 1999 to 2022. The research was carried out in forests exposed to atmospheric industrial pollution from the largest copper–nickel smelter in northern Europe (Murmansk Region, Russia). The study of rainwater composition was conducted in four microsites: open areas (OA), between crowns (BWC), below crowns (BC) and stemflow (SF). A significant influence of the tree canopy on the rainfall composition was noted. Stemflow was found to have the highest concentration of pollutants, indicating a significant biochemical role of this type of precipitation. The results showed an increase in the concentrations of heavy metals and sulfates in rainwater as we moved closer to the pollution source. Below crowns and in the stemflow of spruce forests, element concentrations are higher compared to pine forests. The highest concentrations of major pollutants in stemflow (Ni, Cu and SO₄²⁻) are observed in June—at the beginning of the growing season. Long-term dynamics reveal a decrease in the concentrations of Cu, Cd and Cr in defoliated forests and technogenic sparse forests. Stemflow volume rises from background to technogenic sparse forests due to deteriorating tree-crown conditions. This is associated with the deteriorating condition of tree stands, as manifested by reductions in tree height, diameter and needle cover. It has been established that under pollution conditions, trees’ assimilating organs actively accumulate heavy metals, thereby altering the composition of precipitation passing through the canopy. Full article

Enhanced silicate rock weathering (ESRW) has been proposed as a promising carbon dioxide removal strategy, yet its carbon sequestration pathways, durability, and ecosystem dependence remain incompletely understood. Here, we synthesize evidence from field experiments, observational studies, and modeling to compare ESRW-induced carbon dynamics across forest and cropland ecosystems using a unified SOC–SIC dual-pool framework. Across both systems, ESRW operates through shared geochemical processes, including proton consumption during silicate dissolution and base cation release, which promote atmospheric CO₂ uptake. However, carbon fate diverges markedly among ecosystems. Forest systems, characterized by high biomass production, deep rooting, and strong hydrological connectivity, primarily favor biologically mediated pathways, enhancing net primary productivity and mineral-associated organic carbon (MAOC) formation, while facilitating downstream export of dissolved inorganic carbon (DIC). In contrast, intensively managed croplands more readily accumulate measurable soil inorganic carbon (SIC) and soil DIC over short to medium timescales, particularly under evapotranspiration-dominated or calcium-rich conditions, although SOC responses are often moderate and variable. Importantly, only a subset of ESRW-driven pathways—such as MAOC formation and secondary carbonate precipitation—represent durable carbon storage on decadal to centennial timescales. By explicitly distinguishing carbon storage from carbon transport, this synthesis clarifies the conditions under which ESRW can contribute to climate change mitigation and highlights the need for ecosystem-specific deployment and monitoring strategies. Full article

The “bauxite gas reservoir” in the Ordos Basin represents a novel exploration domain, yet the mechanisms governing its widespread aluminous fracture fillings remain unclear. This study integrates core observation, thin-section analysis, geochemical simulation, and rock physics to investigate the formation and impact of these fracture systems. Results identify a characteristic filling evolutionary sequence of “wall-lining film → oolitic/globular → plug-like → vermicular.” Geochemical simulations confirm that increasing pH and decreasing Eh driven by water–rock interactions are the key drivers for aluminous mineral precipitation. A distinct well log response model characterized by high GR, DEN, and CNL values coupled with low AC and RT is established for effective identification. Seepage experiments reveal that while Al–Si colloidal fracture fillings reduce permeability, they act as natural proppants to preserve effective flow channels, acting as a crucial high-permeability network for gas migration despite the mineral occlusion. These findings refine the accumulation theory for bauxite series reservoirs and provide geological evidence for deep tight gas exploration. Full article

Landfills serve as a primary disposal method for municipal solid waste in China, with over 20,000 operational sites nationwide; however, long-term operations risk leachate leakage and groundwater contamination. Amid intensifying climate change and human activities, understanding contaminant evolution mechanisms in landfills has become critically urgent. Focusing on a representative plain-based landfill in North China, this study integrated field investigations and groundwater monitoring to establish a monthly coupled groundwater flow–solute transport model (using MODFLOW and MT3DMS codes) based on site-specific hydrogeological boundaries and multi-year monitoring data, analyzing spatiotemporal plume evolution under the coupled impacts of precipitation variability (climate change) and intensive groundwater extraction (human activities), spanning the historical period (2021–2024) and future projections (2025–2040). Historical simulations demonstrated robust model performance with satisfactory calibration against observed water levels and chloride concentrations, revealing that the current contamination plume exhibits a distinct distribution beneath the site. Future projections indicate nonlinear concentration increases: in the plume core zone, concentrations rise with precipitation, whereas at the advancing front, concentrations escalate with extraction intensity. Spatially, high-risk zones (>200 mg/L) emerge earlier under wetter conditions—under the baseline scenario (S0), such zones form by 2033 and exceed site boundaries by 2037. Plume expansion scales positively with extraction intensity, reaching its maximum advancement and coverage under the high-extraction scenario. These findings demonstrate dual drivers—precipitation accelerates contaminant accumulation through enhanced leaching, while groundwater extraction promotes plume expansion via heightened hydraulic gradients. This work elucidates coupled climate–human activity impacts on landfill contamination mechanisms, proposing a transferable numerical modeling framework that provides a quantitative scientific basis for post-closure supervision, risk assessment, and regional groundwater protection strategies, thereby aligning with China’s Standard for Pollution Control on the Landfill Site of Municipal Solid Waste and the Zero-Waste City initiative. Full article

The global environmental challenges of solid waste accumulation and aquatic eutrophication demand innovative and sustainable strategies. This study introduces a circular “waste-treats-waste” approach by converting dolomite-rich phosphate tailings (PT), a widespread industrial by-product, into a high-value adsorbent for phosphorus (P) removal. Thermal modification at 950 °C for 1 h dramatically enhanced the adsorption capacity by approximately 45 times, from 2.52 mg/g (raw PT) to 112.41 mg/g. This performance is highly competitive with, and often superior to, many engineered adsorbents. The calcination process was pivotal, decomposing carbonates into highly active CaO and MgO while developing a porous structure. Using a multi-technique characterization approach (X-ray diffraction (XRD), Fourier transform infrared spectra (FTIR), TESCAN VEGA3 tungsten filament scanning electron microscope (SEM), the Brunauer–Emmett–Teller method (BET)), the key immobilization mechanism was identified as hydroxyapatite formation, driven by Ca²⁺/Mg²⁺-phosphate precipitation and surface complexation. Nonlinear regression analysis revealed that the adsorption kinetics obeyed the pseudo-second-order model, and the equilibrium data were best described by the Freundlich isotherm. This indicates a chemisorption process occurring on a heterogeneous surface, consistent with the complex structure created by thermal modification. Notably, post-adsorption pore structure expansion suggested synergistic pore-filling and surface reorganization. This work not only demonstrates a circular economy paradigm for repurposing industrial solid waste on a global scale but also offers a cost-effective and high-performance pathway for controlling phosphorus pollution in aquatic systems, contributing directly to resource efficiency and sustainable environmental remediation. Full article