Search Results (3,446)

Quantitative assessment of ecosystem health (EH) effectively provides a scientific reference for regional landscape ecological development and socio-ecological system coordination. This study combined the VORSH framework and the XGBoost-SHAP model to assess EH and its spatiotemporal driving factors in the Pinglu Canal Economic Zone. The results show that the comprehensive ecosystem health index (EHI) generally remained at a moderate level during this period, exhibiting a pattern of initial decline followed by recovery, resulting in an overall improving trend. The period from 2005 to 2010 was identified as a critical transitional phase, during which EH began to recover and gradually improve. The Pinglu Canal Economic Zone exhibits distinct spatial heterogeneity in EH. Areas with poor and unhealthy grades are primarily distributed around urban peripheries, plain regions, and near certain water bodies. In contrast, healthy and relatively healthy areas are predominantly located in the densely vegetated mountainous regions of the southwest, north, and east. Between 2000 and 2020, the EH status demonstrated a significant overall upward trend, with most areas experiencing slight improvement and only a few regions exhibiting significant degradation. Topography and temperature were the primary factors driving the spatiotemporal variations in EH, while the influence of human activities continued to intensify with ongoing socioeconomic development. Full article

Type 2 diabetes mellitus (T2DM) is a global health burden characterized by hyperglycemia, oxidative stress, and systemic inflammation, which leads to complications that remain insufficiently managed by standard therapies. Photobiomodulation therapy (PBMT) has been proposed to be a complementary approach, but its effects in T2DM are unclear. We conducted a systematic review and meta-analysis of randomized controlled trials to evaluate the effects of PBMT on metabolic, inflammatory, and neurological outcomes in adults with T2DM. Five databases were searched until June 2025 (PROSPERO CRD420251083550) for relevant studies. Metabolic, inflammatory, and neurological outcomes were defined a priori as primary outcomes and were synthesized narratively due to substantial heterogeneity and incomplete reporting that precluded valid quantitative pooling. Although periodontal outcomes were not predefined as primary outcomes, they were reported in multiple trials; thus, these were analyzed quantitatively as secondary outcomes where sufficient homogeneity enabled meta-analysis. The narrative synthesis of primary outcomes showed inconsistent and largely short-term effects on glycemic control, systemic inflammation, and neurological function. In contrast, meta-analysis of secondary periodontal outcomes demonstrated modest but statistically significant improvements in clinical attachment level (−0.21 mm) and probing depth (−0.25 mm), with no effect on plaque index. Overall, the certainty of the evidence was low. PBMT may offer statistically significant but small adjunctive periodontal effects in adults with T2DM. However, the certainty of evidence is low, and these effects are unlikely to be clinically meaningful in isolation. Evidence for systemic metabolic, inflammatory, and neurological outcomes is preliminary and requires confirmation in larger, standardized RCTs. Full article

This study examines agricultural labour dynamics and sustainability practices in East Crete, assessing how labour structure, education, and input intensity shape ecological outcomes. Using data from 108 farms in Heraklion and Lassithi, we constructed composite indicators, such as Labour Intensity, Sustainability Engagement, and Training-Adjusted Labour indices. Analysis of 37 farms with data revealed a heterogeneous landscape. Traditional family-based systems persist alongside uneven shifts toward agroecological practices. The Training-Adjusted Labour Index correlated with reduced pesticide use, while subsidy participation alone was not a reliable predictor of sustainable behaviour. Findings highlight limits of compliance-based incentives and the importance of knowledge-driven transitions. This study advocates typology-informed policies and longitudinal research for future policy design. Full article

The high salt concentration in kitchen waste (KW) can impede the performance of subsequent biological treatment. However, the impact of salt stress on the quality of vermicomposting products generated from KW remains unclear. In this study, the effects of high salt concentration in KW on earthworm function and vermicompost quality were investigated by comparing two groups: a 1.5% salt (ST) group and a control (CK) group without salt. Results showed a significant decrease in the number and weight of earthworms in the ST (p < 0.01), with a mortality rate of 24.33% (p < 0.05) after vermicomposting. Compared to the CK, ST treatment resulted in a significant increase in catalase activity and a significant decrease in superoxide dismutase activity (p < 0.01). In addition, mucus secretion by earthworms decreased by 82.6% in ST (p < 0.01). Moreover, salt stress reduced KW humification during vermicomposting, lowering the humification index and β:α index by 23.7% and 41.2%, respectively. Microbial composition shifted under spatially heterogeneous selection pressures, leading to a 37.5% decrease in Ascomycota abundance, a 58.3% increase in Bacteroidetes abundance, and a 72.3% reduction in Proteobacteria abundance. Furthermore, the vertical stratification of physicochemical conditions significantly affected both microbial abundance and earthworm biomass in the ST treatment (p < 0.01), suggesting a salt–microbe–earthworm interaction mechanism. This study reveals that salt stress disrupts humification by impairing key microbial functions and ecological roles of earthworms during vermicomposting of KW. Full article

Atopic dermatitis (AD) is a chronic inflammatory skin disease in which barrier impairment, immune dysregulation, and gut–skin dysbiosis intersect, prompting growing interest in probiotics as microbiota-modulating adjuncts. We conducted a narrative review of peer-reviewed articles indexed in PubMed, Scopus, and Google Scholar, restricted to publications from 1 January 2018 to 31 October 2025 (searches last run in December 2025). Eligible evidence included randomized controlled trials (RCTs), observational studies, and mechanistic or conceptual reviews addressing microbiome alterations and microbiota-modulating interventions in AD. Most pediatric RCTs using multistrain, Lactobacillus-dominant formulations (often combined with Bifidobacterium) reported modest improvements in AD severity and pruritus and in selected barrier- and inflammation-related biomarkers. However, direct cutaneous microbiome “restoration” outcomes were reported in a minority of studies, and most clinical evidence relies on clinical endpoints and gut–skin axis plausibility rather than longitudinal skin microbiome readouts. Single-strain regimens showed inconsistent effects, and evidence in adolescents and adults remained heterogeneous. Mechanistically, probiotics may enhance short-chain fatty acid (SCFA) signaling, dampen toll-like receptor 2/4 (TLR2/4)-nuclear factor kappa B (NF-κB) activation, and promote interleukin-10 (IL-10)- and transforming growth factor-β (TGF-β)-driven tolerance. Probiotics are a biologically plausible adjunct targeting the gut–skin axis in AD and are generally well tolerated; however, heterogeneity across trials, limited follow-up, inconsistent adverse-event reporting, and scarce skin microbiome endpoints preclude firm clinical recommendations. Full article

The dry area in northwest China (ARNC), with its tough climate, serious soil erosion, and poor soil quality, is one of China’s most fragile ecosystems. Studying changes in plant growth cycles here is very important for improving environmental monitoring and making plans to adapt to climate change. While vegetation growing season parameters (Start/End of Season: SOS/EOS) serve as vital indicators of ecosystem dynamics, comprehensive understanding has been constrained by limited long-term phenological datasets and insufficient exploration of multi-factor interactions. This study used PLS-SEM to analyze 27-year (1990–2016) vegetation index data, systematically quantifying spatiotemporal variations in growing season phenology and disentangling climate–terrain driving mechanisms. The results revealed the following key findings. (1) Spatial heterogeneity in phenological patterns, with the annual average Start of Season (SOS) and End of Season (EOS) being 114.7 Day and 301.7 Day, respectively, exhibiting a northwest–high to southeast–low gradient. The findings indicate a prolongation of the vegetation growing season, with significant spatial variability. (2) Interannual fluctuations showed the SOS and EOS coefficient of variation (CV) values of 0.230 and 0.234, respectively, with southeastern regions displaying higher instability than northwestern counterparts. (3) The spatial variation in SOS/EOS is primarily influenced by meteorological and geographical factors, with an explanatory power exceeding 30%. This research advances mechanistic understandings of arid ecosystem responses to environmental stressors, providing a scientific foundation for targeted ecological restoration, desertification mitigation, and sustainable land management in climate-sensitive drylands. Full article

The alpine grassland is one of the most representative ecosystems on the Qinghai–Tibet Plateau, Growth monitoring is fundamental for the alpine grassland maintenance and husbandry sustainability. In this study, by the integration of regression model, principal component analysis, and SHAP-enhanced machine learning, a comprehensive growth index (CGI) was proposed for the accurate and quick assessment of alpine grassland growth in Qinghai Province, located in the eastern Qinghai–Tibet Plateau. The temporal and spatial growth behaviors of the main grassland types over 2001–2023 were then determined and the differences in key driving factors and their responses explored. The results indicated that the CGI composed of KNDVI, EVI, MSAVI, GNDVI and CVI characterized the typical ecological and physical parameters related to grassland growth, proved to be optimal and efficient in long-term growth monitoring. Alpine grassland growth fluctuated but gradually increased from 2001 to 2023, but individual types exhibited different trends. In particular, the two main types of alpine meadow and alpine steppe displayed the weakest increasing trend in growth, with the good-growth and continuous-increasing area proportions of 26.01% and 18.03%, 70.45% and 74.72%, respectively. Soil total nitrogen was the most critical common factor and significantly increased the growth across all five grassland types, then followed by grazing intensity and precipitation, which exhibits diverse effects on the individual types. The result implies the significant heterogeneity in the key driviers which affect the alpine grassland growth over large scale. Full article

Persistent cloud cover during the growing season and mosaic cropping patterns introduce temporal gaps and mixed pixels, undermining the reliability of large-scale crop identification and acreage statistics. To address these issues, we develop a high spatiotemporal-resolution remote-sensing approach tailored to heterogeneous farmlands. First, an improved Spatiotemporal Adaptive Reflectance Fusion Model (STARFM) is used to fuse Landsat, Sentinel-2, and MODIS observations, reconstructing a continuous Normalized Difference Vegetation Index (NDVI) time series at 30 m spatial and 8-day temporal resolution. Second, at the field scale, we derive phenological descriptors from the reconstructed series—key phenophase timing, amplitude, temporal trend, and growth rate—and use a Random Forest (RF) classifier for detailed crop discrimination. We further integrate SHapley Additive exPlanations (SHAP) to quantify each feature’s class-discriminative contribution and signed effect, thereby guiding feature-set optimization and threshold refinement. Finally, we generate a 2024 crop distribution map and conduct comparative evaluations. Relative to baselines without fusion or without phenological variables, the fused series mitigates single-sensor limitations under frequent cloud/rain and irregular acquisitions, enhances NDVI continuity and robustness, and reveals inter-crop temporal phase shifts that, when jointly exploited, reduce early-season confusion and improve identification accuracy. Independent validation yields an overall accuracy (OA) of 90.78% and a Cohen’s kappa(κ) coefficient of 0.882. Coupling dense NDVI reconstruction with phenology-aware constraints and SHAP-based interpretability demonstrably improves the accuracy and reliability of cropping-structure extraction in complex agricultural regions and provides a reusable pathway for regional-scale precision agricultural monitoring. Full article

Background: Obstructive sleep apnea (OSA) is a heterogeneous disorder associated with substantial cardiometabolic and neurocognitive morbidity. Although the apnea–hypopnea index (AHI) remains the conventional measure of OSA severity, it only partially reflects the underlying pathophysiological complexity. Growing evidence indicates that nocturnal hypoxemia may be a more powerful marker of adverse outcomes than event frequency alone. Therefore, this study aimed to identify distinct OSA phenotypes based on oximetry-derived features and to assess whether these profiles offer additional clinical insight beyond traditional AHI-based classification. Methods: This multicenter retrospective study, part of the Living with OSA and CPAP: The Apulia Region Experience project, included 1386 adults diagnosed with OSA across 15 sleep centers in Southern Italy. Standardized clinical, anthropometric, and polysomnographic (PSG) data were collected. Hierarchical clustering analysis was performed based on PSG oximetry-derived variables. Resulting clusters were compared across demographic, clinical, hypoxemic, and therapeutic features. Results: Three reproducible clusters emerged. Cluster 1 (mild–non-obese) included younger, leaner patients with lower AHI (22.9 ± 10.5 events·h⁻¹), minimal desaturation (T90 5.6 ± 7.6%), and limited comorbidities. Cluster 2 (severe–obese–hypoxemic) represented the most critical phenotype, characterized by marked obesity (BMI 39.2 ± 8.2 kg·m⁻²), severe OSA (AHI 74.9 ± 17.9 events·h⁻¹), profound nocturnal hypoxemia (T90 51.5 ± 28.2%), and a high prevalence of metabolic disorders (76%), requiring higher CPAP pressures and frequent oxygen supplementation. Cluster 3 (older–comorbid) comprised older males (63.7 ± 11.8 years) with moderate-to-severe OSA (AHI 44.8 ± 15.2 events·h⁻¹) and multiple cardiometabolic comorbidities. Conclusions: Oximetry-derived variables identify distinct and clinically meaningful OSA phenotypes that extend beyond traditional AHI-based classification. Recognizing hypoxemia-driven subtypes could improve risk stratification and enable more personalized management strategies in clinical practice. Full article

Background: Brain tumors present a significant clinical problem due to high mortality and strong heterogeneity in size, shape, location, and tissue characteristics, complicating reliable MRI analysis. Existing automated methods are limited by non-selective skip connections that propagate noise, axis-separable attention modules that poorly integrate channel and spatial cues, shallow encoders with insufficiently discriminative features, and isolated optimization of segmentation or classification tasks. Methods: We propose a model using an EfficientNetV2S backbone with a Hierarchical Hybrid Attention (HHA) mechanism. The HHA couples a global-context pathway with a local-spatial pathway, employing a correlation-driven, per-pixel fusion gate to explicitly model interactions between them. Multi-scale dilated blocks are incorporated to enlarge the effective receptive field. The model is applied to a multiclass brain tumor MRI dataset, leveraging shared representation learning for joint segmentation and classification. Results: The design attains a Dice score of 92.25% and a Jaccard index of 86% for segmentation. For classification, it achieves an accuracy of 99.53%, with precision, recall, and F1 scores all close to 99%. These results indicate sharper tumor boundaries, stronger noise suppression in segmentation, and more robust discrimination in classification. Conclusions: The proposed framework effectively overcomes key limitations in brain tumor MRI analysis. The integrated HHA mechanism and shared representation learning yield superior segmentation quality with enhanced boundary delineation and noise suppression, alongside highly accurate tumor classification, demonstrating strong clinical utility. Full article

Soil salinization severely restricts vegetation restoration in Northwest China. Native Limonium plants, capable of naturally colonizing saline-alkalisaline–alkali wasteland, are potential germplasm for low-cost ecological restoration. This study focused on three wild Limonium species (Limonium aureum, Limonium bicolor, Limonium gmelinii) in Gansu Province. In this study, we integrated seed phenotypic diversity with stress tolerance. We then investigated seed germination indices (e.g., germination rate, energy, vigor index) and seedling physiological–biochemical indices of three Limonium species under 0, 100, 200, 300 mM NaCl and NaHCO₃ stress. These indices included leaf and root Na⁺ and K⁺ contents, chlorophyll a and b and carotenoid contents, and malondialdehyde (MDA), proline, soluble sugar, and soluble protein contents, plus SOD and CAT activities. Results showed seed area and thickness were key to germination performance, with L. aureum having the largest and thickest seeds and strongest germination potential. The onset concentration of significant inhibition for salt/alkali was 200 mM. At the seedling stage, L. aureum performed best at 100–200 mM, while all three were damaged at 300 mM. Principal component analysis indicated that L. aureum had the highest comprehensive scores under both NaCl and NaHCO₃ stresses, while L. bicolor and L. gmelinii presented distinct stress-specific adaptation differences. Thus, L. bicolor is recommended for salt-dominated soils and L. gmelinii for alkaline environments, and L. aureum can be used for mildly heterogeneous habitats. This study clarifies inter-species differences under stress, providing a direct theoretical basis for ecological restoration in saline–alkali areas. Full article

Background/Objectives: Cyclin-dependent kinase 4/6 inhibitors combined with endocrine therapy have become the standard of care for HR+/HER2− metastatic breast cancer. Given the metabolic functions of CDK4/6 and the endocrine activity of adipose tissue, body mass index has been proposed as a potential prognostic or predictive factor in this setting. This systematic review aimed to summarize current evidence on the association between BMI and treatment outcomes in HR+/HER2− MBC patients receiving CDK4/6i. Methods: A systematic literature search was conducted in PubMed and Scopus databases, covering publications from 2015 to 2025. We included real-world studies and clinical cohorts reporting survival outcomes of HR+/HER2− MBC patients treated with CDK4/6i in relation to BMI and other body composition parameters. Results: From 69 records identified, 14 studies met the inclusion criteria. Findings were heterogenous; four studies reported improved survival outcomes in higher BMI patients, whereas most identified no significant association. Studies incorporating computed tomography-based metrics demonstrated that body composition parameters such as visceral adiposity and skeletal muscle area were more reliable predictors of prognosis than BMI alone. Conclusions: Our findings indicate that BMI as a standalone metric is an insufficient predictor of clinical outcomes or treatment response for those receiving CDK4/6i, highlighting the need for precise body composition evaluation. More detailed anthropometric and metabolic profiling could clarify the clinical significance of adiposity in HR+/HER2− MBC. Full article

As a sink for microplastics (MPs) in the aquatic environment, sediments have garnered considerable attention. However, the occurrence characteristics of MPs in sediments of different water seasons are not clear, especially for reservoir sediment cores. This study aimed to elucidate the occurrence, spatial and vertical distribution, fragmentation and pollution risk of MPs in the sediment cores of the Xiangxi River, Three Gorges Reservoir (TGR) during different seasons. In sediment cores, the average abundance of MPs was 8.57 × 10³ ± 5.65 × 10³ items/kg DW in the wet season (WS) and 7.98 × 10³ ± 4.00 × 10³ items/kg DW in the dry season (DS), respectively. The abundance of MPs in surface sediments and sediment cores exhibited spatial heterogeneity, reflecting seasonally contrasting hydrodynamic conditions between sites S1 and S3. However, the abundance of MPs in the river estuary was the highest, both in surface sediments and sediment cores. Interestingly, the occurrence characteristics of MPs in surface sediments indicated that in addition to anthropogenic activity, hydrological conditions of the river can also have an impact on the spatial distribution of MP abundance in surface sediments. Polypropylene (PP), polyethylene (PE), polystyrene (PS), and polyethylene-propylene copolymer (EPM) were identified as the dominant polymer types (57–99%), with small-sized microplastics (SMPs, 0–300 μm) being the most prevalent. Water seasons influenced the size distribution of MPs in surface sediments. Using a conditional fragmentation model, MP sources were inferred by comparing fragmentation parameters (λ and α) in sediments with those reported for atmospheric deposition, reservoir water, and water-level fluctuation zone soils. Furthermore, the pollution load index (PLI) exceeded 1, indicating MP accumulation in the sediments. The pollution risk index (PRI) values indicated a considerable (300 < PRI < 1000) pollution risk in two water seasons, primarily due to the presence of polyvinyl chloride (PVC). This study enhances the understanding of MP behavior and associated environmental risks in reservoir sediments, offering valuable insights for future research and pollution mitigation efforts. Full article

The sustainability of reservoir resettlement depends on the synergistic development of resettlers’ livelihoods and host regions; however, existing studies lack an integrated analytical framework. Combining the Sustainable Livelihoods Framework with synergistic development theory, this study establishes a dual-system evaluation model comprising the Regional Development Support (RDS) and Resettlers’ Livelihood Development (RLD) indices. Using survey data from 289 households across 10 counties in Zhejiang’s QC Reservoir project, we apply composite weighting, coupling coordination modeling, and spatial analysis to evaluate the levels of synergistic development and examine spatial patterns. The findings reveal that (1) there is significant gradient differentiation in the Synergistic Development Index (SDI), with scores ranging from 0.134 to 0.738; (2) spatial autocorrelation is weak (Moran’s I = −0.089), reflecting industrial heterogeneity; and (3) four distinct coordination types are identified, with employment–industry mismatch and ecological constraints being the primary limiting factors. This study provides a diagnostic framework for assessing resettlement outcomes and offers guidance for formulating differentiated policy interventions. Full article

Hypertensive kidney disease (HKD) represents a significant contributor to chronic kidney disease and end-stage renal failure, yet its early detection remains challenging due to nonspecific clinical and imaging findings. The lack of a noninvasive diagnostic tool, preventing the use of biopsy and diagnosis by exclusion, suggests the underdiagnosis of patients and overestimation of HKD as the cause of renal replacement therapy. Ultrasonography, including Doppler assessment and renal resistive index measurements, provides a widely accessible, noninvasive approach to evaluate renal structure and hemodynamics, aiding in the identification of early renal impairment or renal artery stenosis. Shear-wave elastography (SWE) has emerged as a promising modality for noninvasive assessment of renal stiffness, potentially detecting structural changes prior to functional deterioration. Current evidence demonstrates SWE’s diagnostic potential in chronic kidney disease and early hypertensive renal disease; however, limitations such as inter-device variability, heterogeneous patient populations, and short follow-up periods constrain its clinical applicability. Neither ultrasonography nor SWE can yet serve as standalone diagnostic tools for HKD, emphasizing the need for standardization, further validation, and longitudinal studies to clarify their role in patient management and prediction. Full article