Search Results (759)

Background: Postoperative wound complications following total joint arthroplasty (TJA) significantly impact patient outcomes and healthcare costs. Reliable preoperative biomarkers for identifying patients at increased risk are critical for optimizing patient management and reducing complication rates. This study evaluated the predictive utility of the C-reactive protein to albumin ratio (CAR) and the prognostic nutritional index (PNI) for periprosthetic joint infection (PJI) and postoperative wound complications in patients undergoing total hip arthroplasty (THA) and total knee arthroplasty (TKA). Methods: We retrospectively studied patients who underwent primary THA and TKA in our department from March 2019 to April 2024. The study included a total of 842 patients (568 knees and 274 hips). Preoperative blood samples were assessed for serum CRP, albumin, and total lymphocyte count, facilitating the calculation of CAR and PNI values. Patient outcomes were monitored, identifying PJI and aseptic wound complications such as persistent wound drainage, hematoma, seroma, skin erosion, and wound dehiscence within 2 weeks post-surgery. Results: The average follow-up time for patients was 39.2 months (range 13–73 months). PJI was significantly linked with elevated admission CAR and diminished PNI ratio (p < 0.001 and p < 0.001). ROC analysis demonstrated optimal predictive cut-off values for CAR at 3.1 (Area under curve [AUC]: 0.92, specificity 97.4%, sensitivity 92.3%) and PNI at 49.4 (AUC: 0.93, specificity 94.7%, sensitivity 91.7%). Furthermore, both CAR (Odds ratio [OR]: 3.84, 95% confidence interval [CI]: 1.6–9.1, p = 0.002) and PNI (OR: 21.8, 95% CI: 9–48.6, p < 0.001) were identified as two independent risk factors associated with the development of PJI following THA or TKA. Further subgroup analysis revealed distinct predictive thresholds for CAR and PNI according to surgical procedure type (TKA and THA), enhancing diagnostic accuracy. Conclusions: Preoperative admission elevated CAR and decreased PNI effectively predict PJI and postoperative wound complications in THA and TKA, supporting their utility as simple, cost-effective biomarkers in clinical practice. Incorporating CAR and PNI evaluations into preoperative assessments can enhance patient stratification and preventive strategies, thus mitigating risks and improving surgical outcomes. Full article

Soil erosion is a critical environmental issue that leads to land degradation, reduced agricultural productivity, and ecological imbalance. This study aims to assess soil loss under various land surface conditions by developing 11 distinct scenarios using the RUSLE (Revised Universal Soil Loss Equation) model integrated within the Google Earth Engine (GEE) platform. Remote sensing-derived indices including NDVI, EVI, NDWI, SAVI, and BSI were incorporated to represent vegetation cover, moisture, and bare/built-up surfaces. The K, LS, P, and R factors were held constant, allowing the C factor to vary based on each index, simulating real-world landscape differences. Soil loss maps were generated for each scenario, and spatial variability was analyzed using bubble charts, bar graphs, and C-map visualizations. The results show that vegetation-based indices such as NDVI and EVI lead to significantly lower soil loss estimations, while indices associated with built-up or bare surfaces like BSI predict higher erosion risks. These findings highlight the strong relationship between land cover characteristics and erosion intensity. This study demonstrates the utility of integrating satellite-based indices into erosion modeling and provides a scenario-based framework for supporting land management and soil conservation practices. The proposed approach can aid policymakers and land managers in prioritizing conservation efforts and mitigating erosion risk. Moreover, maintaining and enhancing vegetative cover is emphasized as a key strategy for promoting sustainable land use and long-term ecological resilience. Full article

Soil erosion in granite-derived weathering mantles poses serious threats to slope stability and ecological sustainability in subtropical regions. While polyacrylamide (PAM) is widely used to improve soil structure, its concentration-dependent effects on multiple soil functions remain unclear. This study developed a multifunctional Soil Function Index (SFI) framework integrating erosion resistance (SFI₁), water regulation (SFI₂), and ecological function (SFI₃) to evaluate the effects of PAM application (0‰, 1‰, 3‰, 5‰, 7‰) on gully-prone sandy material. Herein, SFI₁ was quantified through shear strength (τ) and soil erodibility (K_r); SFI₂ was assessed using soil hydraulic parameters (saturated hydraulic conductivity and water retention curves) and SFI₃ was derived from the grass root system analysis. The results showed that SFI₁ and SFI₂ increased nonlinearly with PAM concentration, reaching maximum values of 0.983 and 0.980 at 7‰, with K_r reduced by 77.3% and non-capillary porosity (NAP) increased by 8.1%. In contrast, SFI₃ peaked at 0.858 under 3‰ and declined sharply to 0.000 at 7‰, due to micropore over-compaction, reduced aeration, and limited plant-available water. The total SFI exhibited a unimodal trend, with a maximum of 0.755 at 3‰, beyond which ecological suppression offset physical improvements. These findings demonstrate that PAM modifies soil multifunctionality through pore-scale restructuring, inducing function-specific thresholds and trade-offs. A PAM concentration of 3‰ is identified as optimal, achieving a balance between erosion control, hydrological performance, and ecological viability in the management of subtropical granite-derived sandy slopes. Full article

This study modified corn, oat, barley, and buckwheat starches using a Henan-specific sourdough starter, revealing that the initial starch architecture governs differentiated functional transformations. Pore-dominant starches (corn/buckwheat) underwent “inside-out” enzymatic pathways—corn starch exhibited a 38.21% reduced particle size through pore expansion, with long amylopectin chain degradation forming thermally stable gels, establishing it as an ideal base for anti-staling sauces and frozen dough. Buckwheat starch demonstrated a 44% increased amylose content facilitated by porous structures, where post digestion double helix formation elevated the resistant starch (RS) content by 7%, achieving a significant 28.19% GI (Glycemic Index) reduction. Conversely, fissure-dominant starches (oat/barley) experienced “surface-inward” limited erosion—oat starch, constrained by surface cracks, showed amorphous region degradation and short-chain proliferation, accelerating glucose release and adapting it for rapid digestion products like energy bars. Barley starch primarily underwent amorphous zone modification, enhancing the pasting efficiency to provide raw materials for instant meal replacement powders. Full article

Turbidite channels are final conduits for the transfer of terrigenous detritus to the deep-sea depositional systems. Studying their morphology and geometric parameters can provide information on density flow characteristics and sedimentary processes, making it an objective and quantitative way to differentiate the deep-sea deposits they feed, which are of special interest to the oil industry. In this work, the morphology is studied, the main geometric parameters are calculated, and the potential sedimentary fill of a turbiditic channel, the Columbretes Grande channel, located on the Ebro continental margin (NW Mediterranean Sea), is reconstructed and visualized in 3D. This complete morphometric analysis shows a concave and smooth channel indicating a profile in equilibrium with local evidence of erosion. Considering the height of the flanks (< 150 m), the existence of well-developed levees, the high sinuosity of some of its reaches, and the relatively low slopes, the channel can be classified as depositional. The sinuosity index is close to 2 in some courses, and the gentle slopes suggest that the fine-grained turbidity currents that episodically circulate in its interior reach the channel’s end. Full article

Background/Objectives: Cardiovascular disease (CVD) remains one of the leading causes of death worldwide, with several well-established risk factors. Among dermatological conditions, psoriasis is a well-known contributor to cardiometabolic risk, while lichen planus (LP) remains an underexplored chronic inflammatory disorder in this context. This study aimed to comparatively assess the prevalence and clinical patterns of metabolic syndrome (MetS) components in patients with LP versus psoriasis and healthy controls, focusing on the intrinsic inflammatory burden in patients not receiving systemic therapy. We also examined whether specific clinical subtypes of LP carry distinct metabolic profiles. Methods: We conducted a cross-sectional observational study at a tertiary dermatology center between January 2020 and December 2024. A total of 236 adult patients were included: 78 with LP, 79 with psoriasis, and 79 controls with minor dermatological conditions. Demographic, clinical, and laboratory data were collected. LP subtypes (cutaneous, mucocutaneous, reticular oral, erosive oral) were evaluated using the Lichen Planus Activity Index (LPAI) and Oral Lichen Planus Clinical Index (OLP-CI); psoriasis severity was assessed using the Psoriasis Area and Severity Index (PASI). Cardiometabolic comorbidities were assessed according to established guidelines. Results: LP patients showed significantly higher prevalence of hypertension (OR 1.94, p = 0.044) and type 2 diabetes mellitus (OR 3.09, p = 0.015) compared to controls. Compared to psoriasis, LP was associated with a higher prevalence of mixed dyslipidemia (OR 3.41, p = 0.033), while psoriasis showed more abdominal obesity (OR 0.35, p = 0.003). Mucosal LP subtypes, especially erosive and reticular oral LP, were linked to elevated cardiometabolic risk. Conclusions: LP, particularly its oral subtypes, is associated with a distinct cardiometabolic risk profile comparable to or exceeding that of psoriasis. These findings support the need for systematic metabolic screening in LP patients as part of comprehensive care. Full article

Temporal alterations in coastlines depict the significant changes in coastal areas, driven by both natural processes and human activities. For island nations, monitoring of the coastline is essential due to their vulnerability to such impacts. In this study, Funafuti Atoll, an archipelago of small and scattered islands around the capital of Tuvalu, is selected as the study region, and the aim is to extract coastlines of different islands and investigate coastal area changes between 2019 and 2023 using Sentinel-2 imagery. A simple linear iterative clustering-based superpixel segmentation and adaptive thresholding approach is employed for coastline extraction. Initially, superpixel segmentation is conducted to cluster 3-band image pixels into coherent regions, excluding the sea area. Subsequently, the normalized difference vegetation index (NDVI) is calculated, and the superpixels are used to obtain corresponding NDVI regions, on which adaptive Gaussian thresholding is applied to extract coastlines. Finally, the areas enclosed by the extracted coastline boundaries are utilized for change analysis. The results indicate that islands along the western rim of Funafuti exhibited significant alteration (an average decrease of −14.48%), whereas those along the eastern rim remained relatively stable due to the presence of coral rubble ridges and steep slopes. The change analysis revealed that from 2019 to 2020, approximately 15.1 hectares (ha) were eroded, resulting in a net area change rate of −4.14%. Between 2020 and 2021, erosion increased to 20.2 ha, yielding a net change of −7.75%. From 2021 to 2022, 13.2 ha were eroded, corresponding to a −1.74% change. From 2022 to 2023, a net gain of 10.3 ha occurred (+0.25%), primarily due to land reclamation along the lagoon-facing coast of Fongafale Island. Overall, all islands showed a decreasing area trend between 2019 and 2023, with an average net change of −12.97%. The coastal changes occurred along the sand-dominated coast with gentle slopes, possibly driven by the impact of tropical cyclones, prolonged swells, and coastal flooding, which act as the primary driving forces for the study region. Full article

As an important ecological barrier and animal husbandry resource base in arid and semi-arid areas, grassland degradation directly affects regional ecological security and sustainable development. Ili Prefecture is located in the western part of Xinjiang, China, and is a typical grassland resource-rich area. However, in recent years, driven by climate change and human activities, grassland degradation has become increasingly serious. In view of the lack of comprehensive evaluation indicators and the inconsistency of grassland evaluation grade standards in remote sensing monitoring of grassland resource degradation, this study takes the current situation of grassland degradation in Ili Prefecture in the past 20 years as the research object and constructs a comprehensive evaluation index system covering three criteria layers of vegetation characteristics, environmental characteristics, and utilization characteristics. Net primary productivity (NPP), vegetation coverage, temperature, precipitation, soil erosion modulus, and grazing intensity were selected as multi-source indicators. Combined with data sources such as remote sensing inversion, sample survey, meteorological data, and farmer survey, the factor weight coefficient was determined by analytic hierarchy process. The Grassland Degeneration Comprehensive Index (GDCI) model was constructed to carry out remote sensing monitoring and evaluation of grassland degradation in Yili Prefecture. With reference to the classification threshold of the national standard for grassland degradation, the GDCI grassland degradation evaluation grade threshold (GDCI reduction rate) was determined by the method of weighted average of coefficients: non-degradation (0–10%), mild degradation (10–20%), moderate degradation (20–37.66%) and severe degradation (more than 37.66%). According to the results, between 2000 and 2022, non-degraded grasslands in Ili Prefecture covered an area of 27,200 km², representing 90.19% of the total grassland area. Slight, moderate, and severe degradation accounted for 4.34%, 3.33%, and 2.15%, respectively. Moderately and severely degraded areas are primarily distributed in agro-pastoral transition zones and economically developed urban regions, respectively. The results revealed the spatial and temporal distribution characteristics of grassland degradation in Yili Prefecture and provided data basis and technical support for regional grassland resource management, degradation prevention and control and ecological restoration. Full article

Against the backdrop of multifaceted strategies to combat climate change, understanding soil erosion’s role in carbon cycling is critical due to terrestrial carbon pool vulnerability. This study integrates bibliometric methods with visualization tools (CiteSpace, VOSviewer) to analyze 3880 Web of Science core publications (1994–2024, inclusive), constructing knowledge graphs and forecasting trends. The results show exponential publication growth, shifting from slow development (1994–2011) to rapid expansion (2012–2024), aligning with international climate policy milestones. The Chinese Academy of Sciences led productivity (519 articles), while the US demonstrated major influence (H-index 117; 52,297 citations), creating a China–US bipolar research pattern. It was also found that Dutch journals dominate this research field. A keyword analysis revealed a shift from erosion-driven carbon transport to ecosystem service assessments. Emerging hotspots include microbial community regulation, climate–erosion feedback, and model–policy integration, though developing country collaboration remains limited. Future research should prioritize isotope tracing, multiscale modeling, and studies in ecologically vulnerable regions to enhance global soil carbon management. This study provides a novel analytical framework and forward-looking perspective for the soil erosion research on soil carbon cycling, serving as an extension of climate change mitigation strategies. Full article

Deforestation and land-use changes lead to significant soil degradation and erosion, particularly in Amazonian ecosystems, due to the region’s climate and geology. This study characterizes soil quality using physical, chemical, and biological parameters across different land uses. It uses a soil quality index (SQI) based on a minimum data set (MDS), from 19 evaluated parameters. The land uses evaluated were cacao monoculture (CMC), agroforestry systems associated with fruit and timber species (FAFS and TAFS, respectively), and a secondary forest. The SQI was composed of six variables, bulk density (BD), soil organic matter (SOM), urease activity (UR), pH, dehydrogenase activity (DH), and leaf litter, which are considered relevant indicators that allow for an adequate evaluation of soil quality. According to the SQI assessment, FAFS has a moderate-quality rating (0.40), followed by secondary forest (0.35), TAFS (0.33), and CMC (0.30), the last three categorized as low-quality. The methods used are replicable and efficient for evaluating changes in soil properties based on different land uses and management systems in landscapes similar to those of the Ecuadorian Amazon. Also worth mentioning is the potential of agroforestry as a sustainable land-use strategy that can enhance above- and below-ground biodiversity and nutrient cycling. Therefore, implementing agroforestry practices can contribute to long-term soil conservation and the resilience of tropical ecosystems. Full article

Hurricanes are powerful tropical storms that can severely damage mangrove forests through uprooting trees, sediment erosion, and saltwater intrusion, disrupting their critical role in coastal protection and biodiversity. After a hurricane, evaluating mangrove damage helps prioritize rehabilitation efforts, as these ecosystems play a key ecological role in coastal regions. Thus, we analyzed the defoliation of mangrove forest canopies and their early recovery, approximately 2.5 years after the landfall of Category 3 Hurricane Roslyn in October 2002 in Marismas Nacionales, Mexico. The following mangrove traits were analyzed: (1) the yearly time series of the Combined Mangrove Recognition Index (CMRI) standard deviation from 2020 to 2025, (2) the CMRI rate of change (slope) following the hurricane’s impact, and (3) the canopy height model (CHM) before and after the hurricane using satellite and UAV-LiDAR data. Hurricane Roslyn caused a substantial decrease in canopy cover, resulting in a loss of 47,202 ha, which represents 82.8% of the total area of 57,037 ha. The CMRI standard deviation indicated early signs of canopy recovery in one-third of the mangrove-damaged areas 2.5 years post-impact. The CMRI slope indicated that areas near the undammed rivers had a maximum recovery rate of 0.05 CMRI units per month, indicating a predicted canopy recovery of ~2.5 years. However, most mangrove areas exhibited CMRI rates between 0.01 and 0.03 CMRI units per month, anticipating a recovery time between 40 months (approximately 3.4 years) and 122 months (roughly 10 years). Unfortunately, most of the already degraded Laguncularia racemosa forests displayed a negative CMRI slope, suggesting a lack of canopy recovery so far. Additionally, the CHM showed a median significant difference of 3.3 m in the canopy height of fringe-type Rhizophora mangle and Laguncularia racemosa forests after the hurricane’s landfall. Full article

Soil erosion-prone areas require effective microbial treatments to improve soil bacterial communities and functional traits. Understanding the driving effects of different microbial interventions on soil ecology is essential for restoration efforts. Single and combined microbial treatments were applied to soil. Bacterial community structure was analyzed via 16S IRNA high-throughput sequencing, and functional groups were predicted using FAPROTAX. Soil microbial carbon, nitrogen, metabolic entropy, and enzymatic activity were assessed. Microbial Carbon and Metabolic Activity: The Arbuscular mycorrhizal fungi (AMF) and Bacillus mucilaginosus (BM) (AMF.BM) treatment exhibited the highest microbial carbon content and the lowest metabolic entropy. The microbial carbon-to-nitrogen ratio ranged from 1.27 to 3.69 across all treatments. Bacterial Community Composition: The dominant bacterial phyla included Firmicutes, Proteobacteria, Acidobacteria, Bacteroidetes, and Actinobacteria. Diversity and Richness: The AMF and Trichoderma harzianum (TH) (AMF.TH) treatment significantly reduced diversity, richness, and phylogenetic diversity indices, while the AMF.BM treatment showed a significantly higher richness index (p < 0.05). Relative Abundance of Firmicutes: Compared to the control, the AMF, TH.BM, and TH treatments decreased the relative abundance of Firmicutes, whereas the AMF.TH treatment increased their relative abundance. Environmental Correlations: Redundancy and correlation analyses revealed significant correlations between soil organic matter, magnesium content, and sucrase activity and several major bacterial genera. Functional Prediction: The AMF.BM treatment enhanced the relative abundance and evenness of bacterial ecological functions, primarily driving nitrification, aerobic ammonia oxidation, and ureolysis. Microbial treatments differentially influence soil bacterial communities and functions. The AMF.BM combination shows the greatest potential for ecological restoration in erosion-prone soils. Full article

It is vital to stabilize pillar dams in underground reservoirs in coal mine goafs to protect groundwater resources and quarry safety, practice green mining, and protect the ecological environment. Considering the actual occurrence of coal pillar dams in underground reservoirs, acoustic emission (AE) mechanical tests were performed on dry, naturally absorbed, and soaked coal samples. According to the mechanical analysis, Quantitative analysis revealed that dry samples exhibited the highest mechanical parameters (peak strength: 12.3 ± 0.8 MPa; elastic modulus: 1.45 ± 0.12 GPa), followed by natural absorption (peak strength: 9.7 ± 0.6 MPa; elastic modulus: 1.02 ± 0.09 GPa), and soaked absorption showed the lowest values (peak strength: 7.2 ± 0.5 MPa; elastic modulus: 0.78 ± 0.07 GPa). The rate of mechanical deterioration increased by ~25% per 1% increase in moisture content. It was identified that the internal crack development presented a macrofracture surface initiating at the sample center and expanding radially outward, and gradually expanding to the edges by adopting AE seismic source localization and the K-means clustering algorithm. Soaked absorption was easier to produce shear cracks than natural absorption, and a higher water content increased the likelihood. The b-value of the AE damage evaluation index based on crack development was negatively correlated with the rock damage state, and the S-value was positively correlated, and both effectively characterized it. The research results can offer reference and guidance for the support design, monitoring, and warning of coal pillar dams in underground reservoirs. (The samples were tested under two moisture conditions: (1) ‘Soaked absorption’—samples fully saturated by immersion in water for 24 h, and (2) ‘Natural absorption’—samples equilibrated at 50% relative humidity and 25 °C for 7 days). Full article

This research aims to characterize sediment dynamics in the Rupinaro catchment, a uniquely terraced and human-shaped basin in Italy’s Liguria region, employing geomorphometric methods to unravel sediment connectivity in a landscape vulnerable to shallow landslides. Within a scenario-based approach, we utilized high-resolution LiDAR-derived digital terrain models (DTMs) to calculate the Connectivity Index, comparing sediment dynamics between the original terraced landscape and a virtual natural scenario. To reconstruct a pristine slope morphology, we applied a topographic roughness-based skeletonization algorithm that simplifies terraces into linear features to simulate natural hillslope conditions and remove anthropogenic structures. The analysis was carried out considering diverse targets (e.g., hydrographic networks, road networks) and the effect of land use. The results reveal significant differences in sediment connectivity between the anthropogenic and natural morphologies, with implications for erosion and landslide susceptibility. The findings reveal that sediment connectivity is moderately higher in the scenario without terraces, indicating that terraces function as effective barriers to sediment transfer. This highlights their potential role in mitigating landslide susceptibility on steep slopes. Additionally, the results show that roads exert a stronger influence on the Connectivity Index, significantly altering flow paths. These modifications appear to contribute to increased landslide susceptibility in adjacent areas, as reflected by the higher observed landslide density within the study region. Full article

Guangxi is among China’s regions most severely affected by karst rocky desertification (KRD). Over the past two decades, global climate change and human activities have jointly led to significant changes in the extent and intensity of KRD in Guangxi. Given this context, it is crucial to comprehensively analyze the spatiotemporal evolution of KRD in Guangxi and its driving forces. This study proposed a novel three-dimensional feature space model for monitoring KRD in Guangxi. We then applied transition matrices, dynamic degree indices, and landscape metrics to analyze the spatiotemporal evolution of KRD. We also proposed a Spatiotemporal Interaction Intensity Index (STII) to quantify mutual influences among KRD patches. Finally, we used GeoDetector to analyze the driving factors of KRD. The results indicate the following: (1) The three-dimensional model showed high applicability for large-scale KRD monitoring, with an overall accuracy of 92.86%. (2) KRD in Guangxi exhibited an overall recovery–deterioration–recovery trend from 2000 to 2023. The main recovery phases were 2005–2015 and 2020–2023. During these phases, both severe and moderate KRD showed strong signals of recovery, including significant declines in area, number of patches, and Landscape Shape Index, along with persistently low STII values. In contrast, from 2015 to 2020, KRD predominantly deteriorated, primarily characterized by transitions from no KRD to potential KRD and from potential KRD to light KRD. (3) For severe KRD patches, the intensity of interaction required from neighboring patches to promote recovery exceeded that which led to deterioration, indicating the difficulty of reversing severe KRD. (4) Slope, land use, and elevation were the main drivers of KRD in Guangxi from 2000 to 2023. Erosive rainfall exhibited a higher explanatory power for KRD than average precipitation. Two-factor interactions significantly enhanced the driving forces of KRD. These findings provide a scientific basis for KRD management. Full article