Search Results (7,622)

Background: Glioblastoma exhibits profound intratumoral heterogeneity, with anatomically distinct tumor zones characterized by divergent molecular programs that drive therapy resistance. Whether magnetic resonance imaging (MRI)-derived radiomic features can capture these regional transcriptomic differences remains unknown. We aimed to determine whether subcompartment-level radiomic features associate with transcriptomic pathway enrichment scores derived from biologically approximate tumor zones. Methods: We matched 28 patients (mean age 58.5 years; 13/28 MGMT methylated) across the IvyGAP RNA-seq atlas and the IVYGAP-RADIOMICS datasets. Single-sample GSEA (ssGSEA) pathway scores were computed for 24 gene sets. Radiomic features (3920 per subcompartment) were reduced to 597. Nested leave-one-patient-out cross-validation (LOPO-CV) with Elastic Net served as the primary predictive analysis; linear mixed-effects models (LMM) provided exploratory associational analysis. Analyses used a biologically motivated but spatially non-co-registered zone-to-subcompartment mapping; all reported associations are zone-approximate. Results: Twenty-one of 24 pathways showed no predictive signal (R²_cv ≤ 0). Inflammatory Response (R²_cv = 0.185, 95% CI [0.071, 0.355], p = 0.008) was the only pathway supported by both the nested CV (FDR = 0.096) and the exploratory LMM (FDR = 0.024, ΔR² = 0.214 beyond subcompartment effects) analyses; the LMM association was robust to clinical covariate adjustment (likelihood ratio test p = 0.004). Angiogenesis (R²_cv = 0.209, 95% CI [0.028, 0.353], p = 0.006) reached nested CV significance (FDR = 0.096) but was not corroborated by the LMM (FDR = 0.445); it is therefore reported as a tentative single-framework signal requiring independent validation. T2-derived texture features were selected in 100% of folds for both pathways. Conclusions: Inflammatory Response is the only pathway supported by both analytical frameworks; Angiogenesis is a tentative nested-CV-only signal pending independent validation. The absence of signal for 21 of 24 pathways should not be interpreted as evidence of biological inaccessibility: at N = 28 (vs. N ≈ 240 required by Riley criteria), severe underpowering, attenuation from the non-spatial zone-to-subcompartment mapping, and methodological constraints each independently suffice to suppress real associations. Five of the 24 gene sets (the IvyGAP zone modules) are non-independent from the outcome data and cannot be interpreted as discovery. All reported associations are zone-approximate and may partly reflect macro-compartment (between-subcompartment) effects; validation in larger cohorts with spatially precise co-registration is essential. Full article

Mercury (Hg) decontamination in active and decommissioned mining areas is a difficult task since Hg may affect environmental matrices and man-made materials. Despite its toxicity as an inorganic form being rather limited with respect to organic compounds (e.g., methyl-Hg), severe effects to human health and ecosystems are recognized. In this work, we review the geochemical activities carried out in the last 13 years at the Abbadia San Salvatore (AbSS) mining and production area. This site belongs to Mt. Amiata (Tuscany, central Italy), which is considered the third-largest Hg-district in the world. Air, water, soil and man-made materials within the AbSS area were investigated to verify to what extent such matrices were affected by Hg contamination. The geochemical investigations are used as important tools to proceed with specific remediation operations of edifices, mining structures and machineries as well as the local groundwater system. To the best of our knowledge, restoration of decommissioned areas affected by Hg contamination at a large scale, such as the AbSS exploitation and production site, is rather uncommon. Currently, the remediation activities in the AbSS area are going on and they are expected to be concluded at the end of 2026 or the beginning of 2027, when the former mining area will turn into a public archeometallurgical museum. Full article

To achieve the large-scale, high-value utilization of vanadium–titanium slag (VTS) in the metallurgical industry, this study replaces blast furnace slag (BFS) with VTS to construct a quaternary all-solid-waste cementitious system composed of VTS, BFS, steel slag (SS), and desulfurization gypsum (DG). It systematically investigates the effects of VTS content (0–60%) on the mechanical properties, leaching toxicity, and hydration heat behavior of the system. XRD, TG–DSC, and SEM–EDS techniques are employed to explore the influence of VTS on hydration behavior and microstructural evolution. The results show that when VTS replaces 30% of the BFS (A3, VTS:BFS:SS:DG = 3:3:3:1), the 28-day compressive strength reaches 31.33 MPa. The leaching concentrations of heavy metals in all specimens are far below the standards for drinking water quality. Hydration heat analysis reveals that the incorporation of VTS advances the acceleration period of hydration. The A3 specimen maintains a relatively high heat release rate in the middle and later stages (after 72 h), and its cumulative heat release is significantly higher than that of the system without VTS, revealing the “slow hydration” mechanism of VTS at later stages. The [SiO₄]–[AlO₄] bonds in VTS undergo a depolymerization–repolymerization process. In addition, an appropriate amount of VTS promotes the deposition of hydration products such as ettringite (AFt), C–S–H, and C–A–S–H gels through micro-filling effects and heterogeneous nucleation, thereby improving the microstructure of the system. However, excessive VTS (≥45%) significantly inhibits the hydration reaction and reduces gel formation due to the decrease in highly reactive BFS components and the increased TiO₂ content. This study provides new insights into the resource utilization of VTS in multi-solid-waste cementitious materials. In addition, VTS-based cementitious materials are suitable for practical scenarios with low early strength requirements, such as goaf backfilling. Therefore, future studies should further investigate the long-term sulfate resistance and carbonation resistance of these materials under real application conditions. Full article

The diagnosis of type 2 diabetes using classical clinical and laboratory biomarkers (HbA1c, glucose, lipids, BMI, and blood pressure) is a classification by symptoms and does not provide insight into the underlying pathophysiological disorders (insulin resistance, ß-cell dysfunction, visceral adipose tissue hormonal secretion, and chronic systemic inflammation). A better understanding of these disorders may help in the selection of appropriate and potentially more successful personalized therapeutic interventions. Based on extensive clinical trial experience, a method for individual phenotyping and consecutive personalized diabetes therapy has been developed in our practice, which we have been using for more than 15 years and would like to share for discussion and debate. In this Part 1, the pathophysiological background and diagnostic approach to phenotyping is described. A consecutive Part 2 will present the translation of the phenotyping result into a personalized diabetes therapy, and another consecutive Part 3 will provide more comprehensive real-world patient observations when practicing this concept. This article is intended as a discussion/concept paper and does not present unpublished patient-level outcome data or formal effectiveness analyses. Prospective validation studies are needed to evaluate the clinical utility of this phenotype-based framework. Full article

Nature-based solutions (NbSs) are increasingly recognized as sustainable and cost-effective strategies for mitigating drought impacts. However, robust quantitative evidence on the effectiveness of NbSs for drought mitigation, especially under future climate change scenarios, remains limited. In particular, the extent to which grazing management can reduce agricultural and hydrological droughts over long time horizons is still poorly understood. This study examines the long-term effectiveness of grazing management as a NbS for mitigating drought under historical and future climate conditions in the Ganale Dawa River Basin, Ethiopia. We combined remote sensing, machine learning, and climate projections to simulate soil moisture and runoff using a long short-term memory (LSTM) model. Protected areas were used as proxies for light grazing, while adjacent non-protected areas represented heavy grazing. Agricultural and hydrological droughts were quantified using the standardized soil moisture index (SSMI) and standardized runoff index (SRI), respectively. The results show that light grazing consistently reduced drought severity compared to heavy grazing across all periods. Agricultural drought severity was reduced by up to ~15% under SSP2-4.5 and SSP5-8.5, while hydrological drought severity showed substantially larger reductions, exceeding ~40% in mid- and late-future periods. Differences between grazing regimes widened under stronger climate forcing, indicating that grazing management benefits become more pronounced under future climate stress. These findings demonstrate that grazing management is an effective NbS for enhancing long-term drought resilience. Scaling up sustainable grazing practices could, therefore, serve as a practical climate adaptation strategy for drought-prone basins in Ethiopia and similar regions. Full article

Background/Objectives: Corneal epithelial thickness (CET) alterations reflect distinct mechanisms in aqueous-deficient and evaporative dry eye disease (DED) subtypes. In this study, we compare the CET profiles between patients with Sjögren’s syndrome (SS) and those with meibomian gland dysfunction (MGD) to elucidate the underlying mechanisms. Methods: We retrospectively analyzed 30 patients with SS and 30 age- and sex-matched with MGD. Assessments included corneal staining, Ocular Surface Disease Index (OSDI), tear meniscus height (TMH), non-invasive breakup time, lipid layer thickness (LLT), and anterior segment optical coherence tomography (AS-OCT) CET mapping. Regional CET and superior–inferior asymmetry were compared. Results: The SS group exhibited higher corneal staining scores (2.18 ± 1.23 vs. 1.03 ± 1.18, p = 0.001) and lower TMHs (0.14 ± 0.06 vs. 0.18 ± 0.07 mm, p = 0.013), while the MGD group reported greater OSDI scores (40.39 ± 22.49 vs. 31.25 ± 22.81, p = 0.029). A significantly thinner central epithelium (p = 0.043) and localized inferior paracentral thinning (2–5 mm zone, p = 0.008) were noted in SS. Corneal staining was identified as the primary independent predictor of central and inferior CET reduction in both groups. In the MGD group, LLT was associated with the preserved inferior CET (p = 0.045) and superior–inferior thickness difference (p = 0.015). Conclusions: Distinct structural signatures are observed between DED subtypes. SS features central/inferior thinning from aqueous deficiency-mediated friction, whereas MGD shows a relatively preserved epithelial thickness influenced by LLT. Regional CET analysis may provide mechanistic insights into DED subtyping. Full article

In the fault diagnosis of complex industrial systems, labeled samples are expensive to obtain, which leads to insufficient training data for the belief rule base (BRB) model. Although unlabeled samples are abundant, the uncertainty of their pseudo-labels may undermine semi-supervised learning and hinder accurate parameter optimization of the BRB model. To address these issues, a dual-source evidence-driven semi-supervised BRB method (SS-BRB) is proposed for fault diagnosis. The proposed method makes effective use of unlabeled samples while preserving the interpretability and inference transparency of the BRB model. To improve the reliability of pseudo-labels in semi-supervised learning, a dual-source evidence-driven pseudo-labeling mechanism is designed. In this mechanism, local similarity information is combined with the global inference results of the BRB model. An entropy factor and a feature distance factor are introduced to adaptively adjust the confidence of pseudo-labels. In this way, the quality of pseudo-labels is improved, and the influence of noisy samples is reduced. Based on this mechanism, high-confidence pseudo-labeled samples are incorporated into the training set to further optimize the model. Experimental results show that the proposed method achieves good diagnostic performance on both the gearbox dataset and the WD615 diesel engine dataset. Even with limited labeled data, the proposed method still achieves high accuracy, robustness, and good generalization performance. Full article

At present, the characteristics of key enzyme genes in the upstream pathway for triterpenoid saponin biosynthesis in P. grandiflorum, as well as their expression patterns over the growth duration, have not been systematically analyzed. This study, at the whole-genome level, conducts the first bioinformatics and expression analyses of the SS and SE gene families in P. grandiflorum. Four PgSS and seven PgSE genes were identified and distributed across six chromosomes. Members within the same subfamily exhibited highly conserved sequences and structures, while distinct structural divergence was observed between different subfamilies. Phylogenetic analysis showed that PgSS and PgSE genes were closely related to those of dicotyledons such as Panax ginseng and Polygala tenuifolia, suggesting high evolutionary conservation. Promoter analysis revealed abundant light- and hormone-responsive elements and MYB/MYC binding sites, indicating regulation by multiple signals. Protein secondary structures were dominated by the Alpha helix and were structurally stable. Quantitative real-time polymerase chain reaction (qPCR) demonstrated that expression levels of PgSS and PgSE in one-year-old Platycodonis Radix were significantly higher than in perennial Platycodonis Radix, especially for the PgSE family. This study characterized the basic biological features and growth-stage-dependent expression patterns of the SS and SE gene families in P. grandiflorum. The results identify key candidate genes and molecular targets for regulating triterpenoid saponin biosynthesis, and provide data supporting quality improvement and active metabolite research in this medicinal plant. Full article

Employing eco-friendly and low-carbon methods to restore petroleum-polluted soil is a growing trend. However, the low-carbon remediation theories and methods for petroleum-polluted soil are still in their early stages. Herein, the carbon footprint and environmental impacts of different petroleum-polluted soil remediation methods were studied based on life cycle assessment (LCA). It was found that the carbon footprint and environmental impacts of the solidification/stabilization (S/S) method were much lower than those of pyrolysis and chemical oxidation methods. Moreover, compared with other S/S materials, the carbon footprint of lime–fly ash solidification for petroleum-polluted soil was the lowest, at only 12.72 kg CO₂ eq. Moreover, its unconfined compressive strength (UCS) increased by 700% compared to the untreated petroleum-polluted soil. On this basis, the response surface method was further employed to optimize remediation parameters using carbon footprint and UCS growth rate as response variables. The results showed that the optimal parameters for solidifying petroleum-polluted soil were lime content of 10.41%, fly ash content of 21.89%, and a curing time of 27 days. This study provides the important theoretical basis and practical guidance for the low-carbon and efficient remediation of petroleum-polluted soil. Full article

Heavy metal mercury is one of the most significant and toxic environmental contaminants. Its inorganic form (Hg²⁺) and organic form (organic mercury, OrHg) can cause irreversible harm to human health and the ecological environment, and the latter is particularly prone to bioaccumulation and bioamplification in the food chain. Therefore, there is an urgent need for a rapid, reliable and specific detection of Hg²⁺ and OrHg to evaluate the potential risk for human health. Here, a novel label-free fluorescent sensing platform based on ssDNA aptamer (A_A-T7)-templated AuNCs was established for sensitive recognition and specific detection of Hg²⁺ and OrHg. In the presence of OrHg, the fluorescence of pure A_A-T7-templated AuNCs was visibly enhanced through forming Ag/AuNCs based on Ag⁰-doped AIEE effect. However, they were obviously quenched because of generating non-fluorescent Au/Ag/Hg ANPs via metallophilic interactions among Au³⁺, Ag⁺, and Hg²⁺ (5d¹⁰-4d¹⁰-5d¹⁰) when only Hg²⁺ existed. This fluorescent sensing platform could detect as low as 20.0 nM (4.0 ng Hg/g) and has a good linear detection range, with target concentrations ranging from 0.25 μM to 2.00 μM, recoveries of 98.0–108.0%, and RSD ≤ 5.0%. Low-toxic A_A-T7-templated AuNCs could be used for cytotoxicity analysis and intracellular fluorescent imaging. The method has been successfully applied to the determination of Hg²⁺ and OrHg in tap water, seawater and dried golden pomfret fish muscle samples, demonstrating promising prospects for the assay of mercury species in environmental samples and aquatic products to ensure human health and food safety. Full article

Background/Objectives: To evaluate and compare the qualitative and quantitative image performance of multiplexed sensitivity-encoding diffusion-weighted imaging (MUSE-DWI) against conventional single-shot (ss-DWI) and high-resolution single-shot (HR-ssDWI) sequences in patients with esophageal cancer. Methods: Twenty patients who underwent esophagus MRI, including ss-DWI, HR-ssDWI and MUSE-DWI, were retrospectively enrolled. Image quality, esophageal contour, lesion conspicuity and image distortion were independently graded by two radiologists using a five-point scale and compared between the three sequences. Signal-to-noise ratio (SNR) and contrast-to-noise ratio (CNR) of esophageal tissue were measured and compared between the three sequences. Results: After Bonferroni correction (p < 0.017), MUSE-DWI had significantly higher scores than HR-ssDWI in image quality, esophageal contour delineation and lesion conspicuity, and all three sequences had statistically significant differences in image distortion scores with MUSE-DWI performing the best. Quantitative analysis revealed that MUSE-DWI had the highest SNR and CNR values; significant differences were found in SNR between ss-DWI and HR-ssDWI (p < 0.001), and in both SNR and CNR between HR-ssDWI and MUSE-DWI (p < 0.001), while no significant differences were observed in SNR and CNR between ss-DWI and MUSE-DWI (p > 0.017). Conclusions: MUSE-DWI outperforms ss-DWI and HR-ssDWI in reducing image distortion, with comparable quantitative image quality metrics to ss-DWI. It represents a valuable optimized DWI technique for esophageal clinical imaging. Full article

A low-titanium-slag-based multi-solid-waste cementitious system was developed for cemented paste backfill. The cementitious binder was prepared from low-titanium slag (LTS), steel slag (SS), municipal solid waste incineration (MSWI) fly ash, and flue gas desulfurization gypsum (FGDG), while lead–zinc tailings were used as the aggregate for backfill materials preparation. The activation of low-titanium slag, proportion optimization, and strength development mechanisms were systematically investigated. Mechanical grinding effectively activated low-titanium slag, and its activity index reached 108% after 90 min of grinding at 28 d. Steel slag alone could not fully activate low-titanium slag in the ternary system, whereas the incorporation of MSWI fly ash significantly enhanced the synergistic activation effect. The quaternary system with 40% MSWI fly ash replacement showed higher cumulative heat release and better later-age strength. The optimum backfill proportion was a solid mass concentration of 81% with a binder-to-tailings ratio of 1:4, yielding a 28 d compressive strength of 11.07 MPa with satisfactory flowability and setting behavior. Microstructural results indicated that the continuous formation of ettringite and gel phases promoted pore refinement and matrix densification. Moreover, the leaching concentrations of Pb, Zn, Cr, and soluble Cl were all below the relevant groundwater quality limits. These results demonstrate a feasible route for the high-value co-utilization of low-titanium slag and MSWI fly ash in cemented backfill materials. Full article

Recent years have seen growing interest in the relationship between the heart and kidney disease, resulting in the general term cardiorenal syndrome (CRS) being coined for disorders involving both the heart and kidneys. However, no accurate animal model exists that can replicate the specific cardiorenal associations characteristic of the human CRS subtype. Preclinical studies published between 1990 and 2024 were identified from online electronic databases. These were reviewed and subjected to meta-analysis according to PRISMA, with the quality assessed using the SYRCLE tool. In total, the review and analysis included 251 papers discussing the rodent presentation of cardiorenal associations, expressed by various hemodynamic, echocardiographic and histopathologic parameters, and selected molecular hallmarks. A wide spectrum of invasive and non-invasive animal approaches has been proposed for CRS. Numerous approaches evoked cardiorenal impairments by elevating systemic pressure. Among the “one-hit” models, Dahl/SS and ISO-HF most commonly resulted in cardiac and renal alterations mimicking CRS-2, while DOCA-salt or STZ were the most likely to elicit cardiac injury in progression of renal failure. The clinical relevance of “two-hit” animal models of cardiorenal associations merits another study. Full article

Industrialization has led to the substantial release of heavy metals and organic pollutants into soil and groundwater, resulting in severe contaminated site issues that pose significant threats to ecosystems and human health. This review aims to systematically review the current development status and challenges of contaminated site remediation technologies, and explore the potential of artificial intelligence (AI) applications in site remediation, to provide a theoretical reference for advancing intelligent remediation. Conventional remediation technologies mainly include physical methods (e.g., solidification/stabilization (S/S), soil vapor extraction (SVE), thermal desorption, pump and treat (P&T), groundwater circulation wells (GCWs)), chemical methods (e.g., chemical oxidation/reduction, electrokinetic remediation (EKR), soil washing), and biological methods (phytoremediation, microbial remediation), along with combined strategies that integrate multiple approaches. Although these technologies have achieved certain successes in engineering practice, they still face common challenges such as risks of secondary pollution, long remediation periods, high costs, poor adaptability to complex hydrogeological conditions, and insufficient long-term stability, making it difficult to fully meet the remediation demands of complex contaminated sites. Subsequently, the potential of emerging technologies—including nanomaterial-based remediation, bioelectrochemical systems, and molecular biology-assisted remediation—is introduced. On this basis, the forefront applications of AI in contaminated site remediation are discussed, covering site monitoring and characterization, risk assessment, remedial strategy selection, process prediction and parameter optimization, material design, and post-remediation intelligent stewardship. Machine learning (ML), explainable AI (XAI), and hybrid modeling approaches have markedly improved remediation efficiency and decision-making. Looking forward, with advancements in XAI, mechanism-data fusion models, and environmental foundation models, AI is poised to drive a paradigm shift toward intelligent and precision remediation. However, challenges related to data quality, model interpretability, and interdisciplinary expertise remain key barriers to overcome. Full article

Background: Conditioning activity (CA) is used to elicit post-activation performance enhancement (PAPE), but it is unclear whether load response principles from back squat models generalize to unilateral split squat conditioning when external load and surface instability are manipulated together. Thus, the current study examined acute effects of stable vs. unstable split squat CA with or without external load on jump performance and phase-specific electromyography (EMG). Methods: Twenty men completed a randomized crossover of three CAs (2 × 3 reps): unloaded stable split squat (SS), unloaded BOSU SS, and BOSU loaded at 50% split squat one-repetition maximum. Single leg jump (SLJ) and countermovement jump (CMJ) were assessed pre-CA and at 3 min (SLJ) and 4 min (CMJ) post-CA. EMG was recorded from the biceps femoris (BF), semitendinosus (ST), vastus lateralis (VL), vastus medialis (VM) gluteus medius (Gmed), peroneus longus (PL), gastrocnemius lateralis (GL) and gastrocnemius medialis (GM). Signals were time-normalized across the split squat cycle and quantified using phase-specific area under the curve (AUC) (descending/ascending). Results: SLJ and CMJ increased after all conditions compared with the pre-test (p < 0.05). SS and unloaded BOSU SS produced comparable jump outcomes, whereas BOSU loaded yielded the greatest CMJ increase (p < 0.04). Unloaded BOSU SS selectively increased hamstring activation (BF, ST) without changes in Gmed or PL. BOSU loaded increased EMG amplitude across all measured muscles. Conclusions: External load primarily drives acute CMJ potentiation, whereas instability mainly redistributes recruitment toward the hamstrings without improving jump performance beyond the stable condition. These findings indicated that when the goal is acute jump enhancement, external load should be prioritized, whereas unstable surfaces may be used to selectively target posterior chain activation. Full article