Search Results (2,845)

This umbrella review provides a comprehensive synthesis of the available evidence on the relationship between digital device use and adolescent sleep. It summarizes results from systematic reviews and meta-analyses, presenting the magnitude and direction of observed associations. A total of seven systematic reviews, including five qualitative reviews and two meta-analyses, were included, comprising 127 primary studies with a combined sample of 867,003 participants. The findings suggest a negative impact of digital device use on various sleep parameters, including sleep duration, bedtime procrastination, and sleep quality. Devices such as smartphones and computers were found to have a greater adverse effect, while television use showed a weaker association. The most significant disruptions were observed in relation to social media and internet use, with problematic usage leading to delayed bedtimes, shorter sleep duration, and increased sleep onset latency. The review also highlights the role of timing and duration of device use, with late-night use particularly contributing to sleep disturbances. Biological, psychological, and social mechanisms are proposed as potential pathways underlying these effects. Despite moderate evidence supporting the negative impact of digital media on sleep, there is considerable heterogeneity across studies, and many relied on self-reported data, which may limit the generalizability of the findings. Future research should aim to standardize exposure and outcome measures, incorporate objective data collection methods, and explore causal relationships through longitudinal studies. This umbrella review underscores the importance of developing targeted public health strategies, parental guidance, and clinical awareness to mitigate the potential adverse effects of digital device use on adolescent sleep and mental health. Full article

Rapid evaluations of farmland soil quality can provide data support for farmland protection and utilization. This study focuses on the soda–saline soil region of Da’an City, Jilin Province, covering an area of 4879 km²; it proposes a framework for evaluating farmland soil quality based on multi-source remote sensing data (Sentinel-2 MSI, GF-5 AHSI hyperspectral and field hyperspectral data). Soil organic matter content, salt content, and pH were selected as indicators of cultivated land soil quality in soda–saline soil areas. A threshold of 20% crop residue cover was set to mask high-cover areas, extracting bare soil information. The spectral indices SI1 and SI2 were utilized to predict the comprehensive grade of soil organic matter + salinity based on the cloud model ($M{E}_c$ = 0.74 and $M{E}_v$ = 0.68). The pH grade was predicted using the red-edge ratio vegetation index (RVIre) ($M{E}_c$ = 0.95 and $M{E}_v$ = 0.98). The short-board method was used to construct a soil quality evaluation system. The results indicate that 13.73% of the cultivated land in Da’an City is of high quality (grade 1), 80.63% is of medium quality (grades 2–3), and 5.65% is of poor quality (grade 4). This study provides a rapid assessment tool for the sustainable management of cultivated land in saline–alkali areas at the county level. Full article

Meniscal injuries are common and often lead to chronic pain, joint instability, and an increased risk of osteoarthritis. Traditional treatments, such as partial meniscectomy, may accelerate joint degeneration. In recent years, biologically active therapies, including platelet-rich plasma (PRP), mesenchymal stem cells (MSCs), hyaluronic acid (HA), bone marrow aspirate concentrate (BMAC), collagen, growth factors (GFs), and silk fibroin (SF), have emerged as promising strategies to enhance meniscal healing. This review evaluates the efficiency of these biological agents in promoting meniscal repair, with a particular focus on their potential integration into injectable hydrogel systems for targeted, minimally invasive delivery. Recent literature from 2015 to 2025 has provided growing insights into the role of biologically active agents and biomaterials in meniscal repair. Among the agents studied, PRP, MSCs, and HA have shown particular promise in modulating inflammation and supporting tissue regeneration. While biological therapies alone may not replace surgery for complex tears, they offer promising, less invasive alternatives that support tissue preservation. However, variability in study design, agent quality, and treatment protocols remains challenging. Further long-term research will be essential to confirm clinical benefits and optimize hydrogel-based delivery methods. Full article

This study investigates the application of laser spot welding to join protective housing components in the automotive electronics industry. The PBT GF 30 components were joined using two primary configurations: a purely overlapping joint and a top-overlap joint, both autogenous (i.e., without filler material). To complement the experimental analysis, a numerical model, previously validated for a simpler joint configuration, was adapted and applied to configurations beyond the overlapping and top-overlap joint, more representative of practical automotive industry components. The results demonstrated that butt-overlap joints exhibited significantly higher strength (85% increase) than purely overlapping joints. This enhancement is attributed to the combined effect of normal and shear stresses in the top-overlap configuration, whereas purely overlapping joints rely solely on shear stress. The validated numerical model accurately predicted the experimental results, including displacement and force values. While minor deviations were observed, the numerical model’s predictions converged within the average experimental values and standard deviation, demonstrating that such a model can be used to precisely design laser-welded joints for similar applications. Full article

This paper investigates the application of image segmentation techniques in endodontics, focusing on improving diagnostic accuracy and achieving faster segmentation by delineating specific dental regions such as teeth and root canals. Deep learning architectures, notably 3D U-Net and GANs, have advanced the image segmentation process for dental structures, supporting more precise dental procedures. However, challenges like the demand for extensive labeled datasets and ensuring model generalizability remain. Two semi-automatic segmentation workflows, Grow From Seeds (GFS) and Watershed (WS), were developed to provide quicker acquisition of ground truth training data for deep learning models using 3D Slicer software version 5.8.1. These workflows were evaluated against a manual segmentation benchmark and a recent dental segmentation automated tool on three separate datasets. The evaluations were performed by the overall shapes of a maxillary central incisor and a maxillary second molar and by the region of the root canal of both teeth. Results from Kruskal–Wallis and Nemenyi tests indicated that the semi-automated workflows, more often than not, were not statistically different from the manual benchmark based on dice coefficient similarity, while the automated method consistently provided significantly different 3D models from their manual counterparts. The study also explores the benefits of labor reduction and time savings achieved by the semi-automated methods. Full article

Cracking in asphalt layers of rigid–flexible composite pavements under coupled ambient temperature fields and traffic loading represents a critical failure mode. Traditional models based on uniform temperature assumptions inadequately capture the crack propagation mechanisms. This study developed a thermo-mechanical coupling model that incorporates realistic temperature-modulus gradients to analyze the compressive-shear behavior and simulate crack propagation using the extended finite element method (XFEM) coupled with a modified Paris’ law. Key findings reveal that the asphalt layer exhibits a predominant compressive-shear stress state; increasing the base modulus from 10,000 MPa to 30,000 MPa reduces the maximum shear stress by 22.8% at the tire centerline and 8.6% at the edge; thermal stress predominantly drives crack initiation, whereas vehicle loading governs the propagation path; field validation via cored samples confirms inclined top-down cracking under thermo-mechanical coupling; and the fracture energy release rate (G_f) reaches a minimum of 155 J·m⁻² at 14:00, corresponding to a maximum fatigue life of 32,625 cycles, and peaks at 350 J·m⁻² at 01:00, resulting in a reduced life of 29,933 cycles—reflecting a 9.0% temperature-induced fatigue life variation. The proposed model, which integrates non-uniform temperature gradients, offers enhanced accuracy in capturing complex boundary conditions and stress states, providing a more reliable tool for durability design and assessment of composite pavements. Full article

Wetlands play a crucial role in climate regulation, pollutant filtration, and biodiversity conservation. Accurate wetland classification through high-resolution remote sensing imagery is pivotal for the scientific management, ecological monitoring, and sustainable development of these ecosystems. However, the intricate spatial details in such imagery pose significant challenges to conventional interpretation techniques, necessitating precise boundary extraction and multi-scale contextual modeling. In this study, we propose WetSegNet, an edge-guided Multi-Scale Feature Interaction network for wetland classification, which integrates a convolutional neural network (CNN) and Swin Transformer within a U-Net architecture to synergize local texture perception and global semantic comprehension. Specifically, the framework incorporates two novel components: (1) a Multi-Scale Feature Interaction (MFI) module employing cross-attention mechanisms to mitigate semantic discrepancies between encoder–decoder features, and (2) a Multi-Feature Fusion (MFF) module that hierarchically enhances boundary delineation through edge-guided spatial attention (EGA). Experimental validation on GF-2 satellite imagery of Dongting Lake wetlands demonstrates that WetSegNet achieves state-of-the-art performance, with an overall accuracy (OA) of 90.81% and a Kappa coefficient of 0.88. Notably, it achieves classification accuracies exceeding 90% for water, sedge, and reed habitats, surpassing the baseline U-Net by 3.3% in overall accuracy and 0.05 in Kappa. The proposed model effectively addresses heterogeneous wetland classification challenges, validating its capability to reconcile local–global feature representation. Full article

Osteoporosis is a common skeletal disease characterized by decreased bone density, leading to bone fragility and fractures, especially in menopausal women. The purpose of this study is to confirm the anti-osteoporosis activity of stem cell extracellular vesicles (EVs) as a material of regenerative medicine. Mesenchymal stem cells have a potential to differentiate into osteocytes, so directly reconstruct bone tissue or facilitate bone regeneration via paracrine effects. Paracrine effects are mediated by functional molecules delivered in EVs released from stem cells. EVs containing high concentrations of growth factors (GFs) and neurotrophic factors (NFs) were attained via hypoxia culture of human amniotic membrane stem cells (AMSCs). From the EVs with a mean diameter of 77 nm, 751 proteins and 15 species of lipids were identified. Sprague-Dawley rats were ovariectomized, and eight weeks later, intravenously injected with EVs at doses of 1 × 10⁸, 3 × 10⁸ or 1 × 10⁹ particles/100 μL/body, weekly for eight weeks. One week after the final administration, the serum and bone parameters related to bone density were analyzed. Serum 17β-estradiol, alkaline phosphatase, and calcium levels that decreased in ovariectomized rats were restored by EVs in a dose-dependent manner. Bone parameters such as bone mineral density, bone mineral content, bone volume/tissue volume ratio, trabecular number, trabecular space, and bending strength were also improved by treatment with EVs. Such effects were confirmed by morphological findings of micro-computed tomography. Taken together, it is suggested that AMSC-EVs containing high concentrations of GFs and NFs preserve bone soundness by promoting bone regeneration and inhibiting bone resorption. Full article

This study comprehensively discusses the effect of multiple material recycling (five recycling cycles with the same technological conditions: injection molding → grinding → drying → injection molding → …) of commercial polypropylene-glass fiber composites (PPGF) (PP + 10, 20 and 30 wt.% GF) on the performance of the grinding process and the granulometric characteristics of the obtained regrinds, as well as selected surface, mechanical and thermal properties of the composites. An increase in mass (E_m) and volume (E_v) grinding efficiency was confirmed, along with an increase in GF content in the composite and the number of recycling cycles. Both the GF additive and the number of recycling cycles contributed to the deterioration of the aesthetic qualities of the composites (darkening and reduction in gloss). Slight changes in the surface hardness of the test materials were observed as a function of the number of recycling cycles, from 3 to 4% after five recycling cycles. The adverse effect of multiple recycling on the mechanical and thermal properties of PP and PPGF composites has been confirmed. The occurrence and increase in carbonyl index (CI) values, as a function of multiples recycling, was confirmed for a composite containing 20 wt.% GF (CI in the range from 0.045 to 0.092) and for PPGF containing 30 wt.% GF (CI in the range from 0.193 to 0.272). The effect of multiple material recycling on the glass fiber structure in the tested composites was also investigated using scanning electron microscopy (SEM) and optical microscopy. The issues of grinding and changes in the surface properties of PPGF composites in multiple material recycling processes discussed in this article may constitute a source of practical knowledge that will contribute to increasing the use of this type of secondary composite in industrial plastics processing processes. Full article

Placental dysfunction underlies the major obstetric syndromes, including preeclampsia, fetal growth restriction, placenta accreta spectrum, pregnancy loss, and monochorionic twin complications. Recent molecular studies have revealed that dysregulated oxygen sensing, impaired angiogenic signaling, altered immune tolerance, and defective trophoblast fusion represent shared pathogenic pathways that converge across these disorders. Integrating morphological evidence with mechanistic data highlights how villous maldevelopment, shallow trophoblast invasion, and aberrant vascular remodeling translate into clinical disease. Advances in biomarker research have already transformed clinical care: the sFlt-1/PlGF ratio is now established in the prediction and management of preeclampsia, while placental proteins such as PAPP-A and PP13, nucleic acid signatures including cfDNA, cfRNA and miRNAs, and extracellular vesicle cargo show promising potential for early, non-invasive detection of placental pathology. Multi-omics approaches, particularly single-cell and spatial transcriptomics combined with proteomic and metabolomic profiling, are paving the way for composite diagnostic panels that capture the polygenic and multicellular nature of placental disease. This review synthesizes current knowledge of molecular mechanisms, histological correlates, and translational biomarkers, and outlines how precision obstetrics may emerge from bridging mechanistic discoveries with clinical applications. Full article

Autopsy studies have shown that Alzheimer’s disease (AD) often coexists with cerebrovascular injury, affecting cognitive outcomes and the effectiveness of anti-amyloid-beta (Aβ) drugs. No fluid biomarkers of cerebrovascular injury have been identified yet. We investigated the association between white matter hyperintensities (WMH) severity and fluid biomarkers, including cerebrospinal fluid (CSF) neurofilament light chain and plasma placental growth factor (PlGF) levels. This study included 242 patients from memory clinics. Magnetic resonance imaging (MRI), CSF, and plasma samples were collected. Patients were classified as AD+ or non-AD based on the CSF Aβ42/Aβ40 ratio. In the discovery cohort (79 AD+ and 20 non-AD patients with 3D-T1 images), we analyzed the association between WMH volume and plasma PlGF. In the validation cohort (54 AD+ patients without 3D-T1 images), we analyzed the association between WMH grading and plasma PlGF. Among AD+ patients in the discovery cohort, plasma PlGF levels remained significantly associated with WMH volume and grading after adjusting for age, sex, and global cognition. Among the AD+ patients in the validation cohort, the high-PlGF (above median) group had significantly greater WMH volumes and a higher number of patients with a high WMH grading than the low-PlGF (below median) group. Plasma PlGF is a promising marker of cerebrovascular injury in AD. Full article

As the automotive industry increasingly relies on plastic components to meet fuel efficiency and emissions targets, the challenge of managing end-of-life vehicle (ELV) plastics continues to grow. Currently, more than 80% of ELV plastics in the U.S. are landfilled due to limited economic incentives and technical barriers to recycling. This study examines a mechanical recycling pathway for thermoplastic components disassembled from ELVs and assesses their usability for reintegration into new vehicle parts. Four representative materials were chosen based on material labels embedded in recovered parts and aligned with their virgin industrial equivalents: polypropylene (PP), 10% talc-filled PP (PP-T10), 20% talc-filled PP (PP-T20), and a 20% glass-/mineral-filled polyamide (PA6 + GF7 + MF13). The materials underwent shredding, drying, and injection molding before being characterized by particle size analysis, density measurement, thermal analysis (TGA, DSC), mechanical testing, and heat deflection temperature (HDT) evaluation. The results in this work indicated that minor differences in crystallinity were observed and small differences between model materials and ELV materials could have contributed to these changes. Mechanical testing revealed that neat polypropylene suffered a 15–20% reduction in stiffness and tensile strength, but talc-filled polypropylene and glass/mineral-filled nylon retained >90% of their modulus, strength, and heat deflection temperature values relative to virgin controls. Differences between virgin and ELV materials could have been attributed to use life degradation, contamination during use life, or even chemical/processing differences in model materials and ELV materials. However, these findings suggest that mechanically recycled, disassembled ELV plastics can retain sufficient structural performance to support circularity efforts in the automotive sector. Full article

The effects of administering 10 mL of maternal bovine appeasing substance (mBAS) or water (control; CT) at weaning (day 0) before transport on feedlot adaptation and efficiency were evaluated in twenty-two Angus-influenced heifers (n = 11/treatment) over 28 days. Body weight (BW), salivary cortisol, blood for complete blood cell count, rectal temperature, chute score and exit speed were collected on days 0, 14 and 27. Intake, feeding duration, frequency and rate, as well as activity and rumination were monitored daily using automated systems. Average daily gain (ADG) and gain-to-feed ratio (G:F) were calculated for each 14-day interval as well as for the entire feeding period. Treated heifers spent less time eating (p ≤ 0.06) on weeks 1 and 2, with greater feeding rate and activity (p < 0.01) in week 1, followed by reduced activity (p ≤ 0.05) in weeks 2, 3 and 4. Rumination was longer (p < 0.05) in weeks 3 and 4, coinciding with greater (p ≤ 0.05) final BW, ADG_0–27, ADG_14–27, and G:F_0–27, G:F_14–27. Lymphocyte and hematocrit were lower (p < 0.05) on days 14 and 27, respectively, and platelets tended to be greater (p = 0.08) than CT for the entire period. Treated heifers achieved numerically greater profit margins than CT. Overall, mBAS enhanced feedlot adaptability post-weaning, improving production efficiency, which may translate into potential profitability; however, this interpretation should be viewed cautiously considering some design limitations. Full article

Preeclampsia affects 2–8% of pregnancies globally and remains a leading cause of maternal and perinatal morbidity, with limited preventive options beyond low-dose aspirin. Low-molecular-weight heparin (LMWH) has emerged as a promising therapeutic candidate due to its pleiotropic effects extending beyond anticoagulation, including anti-inflammatory, pro-angiogenic, and placental-protective properties. This comprehensive narrative review examines LMWH’s effects on preeclampsia-associated biomarkers and evaluates clinical evidence for its preventive efficacy. LMWH exerts multifaceted effects on disease pathophysiology, including restoration of angiogenic balance through sFlt-1 reduction and PlGF preservation, attenuation of inflammatory responses via decreased TNF-α and IL-6 production, normalization of coagulation parameters, and enhancement of trophoblast invasion and placental vascularization. Clinical trials reveal heterogeneous results, with meta-analyses suggesting significant benefit primarily in high-risk subgroups. Women with previous severe placenta-mediated complications demonstrate relative risk reductions of 40–60% for recurrent preeclampsia with LMWH prophylaxis, particularly when initiated before 16 weeks’ gestation. Combination therapy with low-dose aspirin appears to enhance protective effects. However, larger trials in unselected populations have failed to demonstrate significant benefit, highlighting the importance of appropriate patient selection. Current international guidelines reflect this evidence heterogeneity, with most recommending against routine LMWH use while acknowledging potential benefit in selected high-risk populations, particularly those with antiphospholipid syndrome or previous severe early-onset disease. Future research should focus on biomarker-guided patient selection, optimal dosing regimens, and integration with multimodal preventive strategies to maximize therapeutic benefit while minimizing unnecessary interventions. Full article

Aberrant activation of proangiogenic signaling pathways, particularly the vascular endothelial growth factor (VEGF) axis, drives neovascularization and tumor progression in colorectal cancer (CRC). Bevacizumab targets VEGF-A-mediated angiogenesis, but the lack of validated predictive biomarkers limits personalized treatment. In this prospective study, we evaluated a panel of circulating angiogenic biomarkers combined with clinical parameters, using mathematical models to predict survival in metastatic CRC patients treated with bevacizumab and chemotherapy. Low VEGF-A and VEGF-D levels, together with high bFGF, were associated with improved overall survival (OS). A logistic regression model incorporating these biomarkers, regional lymph node invasion, and primary tumor resection status showed significant prognostic accuracy (p < 0.001). Incorporating CypA further refined the model, identifying patients with low VEGF-A, VEGF-D, and CypA, and high VEGF-C and PlGF, as having the most favorable OS. These findings demonstrate that integrating clinical and circulating biomarker data can improve individualized risk assessment and support personalized therapeutic strategies for CRC patients receiving bevacizumab. Full article