Search Results (160,333)

Background: Gliomas are among the most common and heterogeneous primary brain tumors, exhibiting substantial molecular and transcriptomic diversity that complicates diagnosis, grading, and treatment planning. Advances in artificial intelligence (AI), particularly machine learning (ML), offer powerful opportunities to analyze high-dimensional gene expression data and support precision oncology. Methods: This study proposes an interpretable ML framework to classify brain tumor subtypes—glioblastoma, astrocytoma, and oligodendroglioma—and to predict tumor grades (2, 3, and 4) using microarray-based gene expression data. The analysis was conducted on the REMBRANDT dataset, comprising 464 labeled samples (221 glioblastoma, 148 astrocytoma, 67 oligodendroglioma, and 28 controls) and 314 tumor samples for grade classification. Results: The ML models achieved high performance for disease classification, with accuracies of 99.6% (AUC 99.89%) for glioblastoma, 98.3% (AUC 99.83%) for astrocytoma, and 98.95% (AUC 100%) for oligodendroglioma. Tumor grade predictions also performed strongly, achieving 83.7% accuracy (AUC 88.2%) for grade II vs. III, 91.3% (AUC 94.8%) for grade II vs. IV, and 84.2% (AUC 90.8%) for grade III vs. IV. SHAP analysis identified key genes contributing to the model predictions (e.g., WIF1, STX6, RGS5, and ACTR2), and KEGG enrichment identified the candidate pathways involved in vesicular transport, metabolism, and immune signaling. Conclusion: Overall, our findings demonstrate that interpretable ML models can accurately differentiate glioma subtypes and grades, and SHAP analysis can help identify the strongest predictors of our models. These findings provide additional insights into the heterogeneous genetic and molecular landscape of brain gliomas and are intended to complement, not replace, conventional histopathological diagnosis. Full article

Traditional leaf area index (LAI) measurement methods are destructive, time-consuming, and labor-intensive. In this study, 282 four-year-old central-leader apple trees were used as research subjects. Canopy reflectance spectra in the range of 4000−10,000 cm⁻¹ were collected, and the corresponding true LAI values were measured destructively by harvesting all leaves from a representative branch of each tree using a leaf area meter. The dataset was randomly divided into training (70%) and testing (30%) sets. Eight spectral pretreatment methods were compared. The Competitive Adaptive Reweighted Sampling (CARS) algorithm was employed to extract characteristic wavelengths. Subsequently, both a BP neural network and a Support Vector Machine (SVM) model for LAI prediction were constructed. The optimal model was selected based on evaluation metrics including the coefficient of determination (R²), mean absolute error (MAE), mean bias error (MBE), and mean absolute percentage error (MAPE). The combined preprocessing of MSC and SD yielded the optimal results, screening out 26 characteristic wavelengths. The SVM linear kernel model (c = 5, g = 0.3) constructed based on MSC + SD preprocessing performed best, achieving a validation set R² of 0.90, MAE of 0.2117, MBE of −0.1214, and MAPE of 16.09%. The performance on the training set and validation set was comparable, with no overfitting observed. The MSC + SD preprocessing combined with CARS feature screening and SVM linear kernel modeling enables rapid, non-destructive estimation of apple canopy LAI, providing an effective technical tool for precision orchard management. Full article

The scope of actual pro-environmental initiatives, programs, interventions, and campaigns is limited. Therefore, spillover effects from these activities to other domains of economy, the private sphere, and society are crucial to achieve a transformation of society towards sustainability. Starting from the known literature and using Google Scholar as a platform for searching additional studies, this explorative, traditional narrative review analyses behavioural spillover effects, where either one behaviour influences the likelihood of another behaviour, or an intervention shows an impact on an environmentally significant behaviour, which it did not primarily address. In the scientific literature, spillover is classified by direction (environmentally positive versus negative), involved behaviours (similar or cross-behavioural), timing (short or long term), context (e.g., work to private life), and social scope (personal, interpersonal, intra- and inter-organisational, intergroup, or international). Positive spillover can result from cognitive dissonance reduction, consistent self-perception, pro-environmental values, norms, self-identity, action-based learning, and habit formation. Negative spillover emerges through rebound effects, moral licensing, and psychological reactance. Stronger spillover is observed between similar behaviours, while cross-domain spillover is generally weaker. According to previous research, a facilitated participatory approach with strong pro-environmental orientation appears recommendable for practitioners to foster the value change required for effective and sustained positive spillover. Full article

Purpose: This study provides a critical examination of the literature on applying artificial intelligence (AI) and Extended Reality (XR) in restaurant settings and related foodservice operations. It focuses on how AI and XE influence consumer nutrition awareness and decision-making about food choices, and their implications for customer satisfaction, loyalty, and service delivery in foodservice environments. Design/methodology/approach: The study adopts a systematic literature review (SLR) approach following the PRISMA method. An initial search identified over 3900 academic papers published between 2016 and 2025. Studies were selected on the basis of predetermined inclusion and exclusion criteria, and 26 peer-reviewed articles were analyzed. The review provides a conceptual synthesis and develops propositions for practical applications and future research directions. Findings: The review reveals a shift from static systems that rely on optimization, toward adaptive and user-centered solutions that are behavior-oriented. AI applications predominate in the case of calorie tracking, personalized recommendations, and menu planning. Though deployment of XR technologies (e.g., AR and VR) is less prevalent, they offer potential for immersive, and real-time interventions. A key distinction emerges between studies demonstrating empirical effectiveness (e.g., improved understanding and healthier choices) and those focused on technical and/or conceptual developments. To date, there has been limited validation of behavioral impacts in foodservice settings. Originality: This study offers a theory-informed conceptualization of AI and XR applications in restaurant and foodservice contexts by integrating three perspectives: hospitality (menus and dining experience), nutrition (dietary awareness and healthier choices), and human–technology interaction (technology acceptance and user engagement). The study reconceptualizes AI- and XR-enabled systems as behavioral intervention tools and outlines a focused research agenda for advancing nutritional communication in foodservice environments. Full article

Background/Objectives: Managing postoperative drainage and reducing the length of hospital stays continue to represent significant challenges in thoracic surgery. While systemic antifibrinolytics are effective, concerns persist regarding neurotoxicity and thromboembolic risks. In this study, we evaluated the efficacy and safety of a unique, high-volume topical tranexamic acid (t-TXA) lavage protocol designed to optimize pleuroparenchymal contact and stabilize local hyperfibrinolysis. Methods: A retrospective comparative study was conducted involving 52 patients undergoing major lung resection, divided into a t-TXA group (n = 26) and a control group (n = 26). The t-TXA group received an intrathoracic lavage consisting of 5 g of tranexamic acid (TXA) diluted in 500 mL of saline, while the control group received 500 mL of saline alone. The primary outcomes included postoperative day (POD) 1 drainage volumes and length of stay (LOS). The secondary outcomes were focused on hematological parameters and safety profiles, including a structured one-year follow-up for all patients. Due to the study’s exploratory nature, primary outcomes were assessed using 95% confidence intervals for hypothesis generation rather than a priori sample size calculations. Results: No significant differences were observed between groups regarding sex, surgical approach, or resection type. The t-TXA group demonstrated a significantly shorter LOS (4.20 ± 1.23 days) compared to the control group (5.88 ± 2.23 days; p = 0.001). While POD 1 drainage was numerically lower in the t-TXA group (189.23 ± 235.06 mL) versus the control (284.23 ± 169.40 mL), this difference did not reach statistical significance (p = 0.101). However, exploratory correlation analysis revealed a moderate negative association between t-TXA application and POD 1 drainage (r = −0.412; p = 0.002). Postoperative platelet counts were significantly lower in the t-TXA group (p = 0.009). No thromboembolic events, late complications, or deaths occurred in either group during the one-year follow-up period. Conclusions: High-volume t-TXA lavage is a promising adjuvant associated with significantly shorter hospital stays and a trend toward reduced postoperative drainage. While our 12-month follow-up confirmed a favorable safety profile with no adverse events, these findings should be interpreted as preliminary and hypothesis-generating. The retrospective nature of this study precludes definitive recommendations, underscoring the need for well-powered prospective randomized trials to establish the long-term safety and clinical utility of t-TXA in thoracic surgery. Full article

Replicating the authentic masticatory properties of conventional animal meat remains a primary technical bottleneck for sustainable plant-based analogues. To address critical textural deficiencies like structural fragmentation, this study systematically optimized plant-based patty formulations. The independent and interactive effects of textured fibrous soy protein (TFSP), water, and konjac glucomannan (KGM) were quantified using single-factor experiments and Response Surface Methodology (RSM). Single-factor experiments revealed that springiness peaked at 60 g TFSP, 15 g water, and 10 g KGM, respectively, with excessive additions of each component resulting in structural network disruption. Designating springiness as the core metric, a reliable quadratic regression model identified the optimal matrix: 63.36 g TFSP, 14.39 g water, and 8.57 g KGM. Empirical validation achieved a maximum springiness of 1.56 mm and hardness of 5.51 N, with a negligible relative error (1.27%) from theoretical predictions. Mechanistically, KGM functioned as an active polymeric filler, interacting synergistically with hydrated protein fibers via hydrogen bonding and hydrophobic associations to reinforce the structural network. Comparative Texture Profile Analysis demonstrated that the optimized PBP exhibited a tender masticatory profile with hardness and springiness approximating conventional beef patties, while presenting lower chewiness and higher adhesiveness attributable to the water-binding capacity of KGM. Ultimately, this research provides mathematically validated engineering parameters and theoretical insights into protein–polysaccharide phase behaviors to facilitate the industrial manufacturing of premium plant-based meats. Full article

This case-control study investigated the association between polymorphisms in the dedicator of cytokinesis 2 (DOCK2) gene and susceptibility to COVID-19 in a Mexican population. Methods: Genotyping of five single-nucleotide polymorphisms (SNPs) in the DOCK2 gene (rs9307 A/G, rs1045176 G/T, rs1045168 C/T, rs2112703 A/C, and rs2287727 A/C) was performed using TaqMan assays in 248 COVID-19 patients and 288 healthy controls. Results: No significant differences were observed in the allelic or genotypic distributions of rs1045176 G/T and rs2287727 A/C between cases and controls. However, under multiple genetic inheritance models (co-dominant, dominant, recessive, heterozygous, and additive), the rs9307 A, rs1045168 C, and rs2112703 A alleles were significantly associated with a reduced risk of COVID-19 (p < 0.05). Furthermore, sub-analyses stratified by genotype in COVID-19 patients revealed that the rs9307 AA, rs1045168 CC, and rs2112703 AA genotypes correlated with altered plasma concentrations of lactic acid dehydrogenase (LDH), alanine aminotransferase (ALT), aspartate aminotransferase (AST), and ferritin. Conclusions: The DOCK2 SNPs rs9307 A/G, rs1045168 C/T, and rs2112703 A/C are associated with decreased susceptibility to COVID-19 in this population and influence plasma levels of LDH, ALT, AST, and ferritin, suggesting a potential role in disease pathogenesis and severity. Full article

The global demand for Salvia miltiorrhiza Bunge in the botanical medicine market is steadily increasing. However, its production has long relied on asexual root propagation, making it highly susceptible to germplasm degradation. Transitioning to seed reproduction offers the advantage of genetic renewal, yet it is constrained by unstable seed vigor and slow seedling growth. In the present study, comprehensive physiological and microbiome analyses of S. miltiorrhiza seeds from 14 regions across 7 provinces in China were conducted to elucidate the association between the seed microbiome and vigor, and to identify plant growth-promoting (PGP) strains. The results demonstrated: (1) Seed physical traits and germination characteristics varied significantly across geographic origins. Seed vigor, exhibiting the highest coefficient of variation, served as a key parameter reflecting germination quality. (2) High-vigor seeds harbored distinct microbial communities characterized by higher diversity indices, greater network complexity, and the significant enrichment of potentially beneficial bacteria (e.g., Pseudomonas). (3) Through correlation-directed screening of isolated pure cultures, Pseudomonas mendocina P-6 and Enterobacter ludwigii BM-12 were identified as exhibiting robust, multi-trait PGP capacity. In planta validation showed that these two strains significantly promoted the growth of 1-month-old S. miltiorrhiza seedlings, increasing total fresh weight by 33.9–71.3%. This study reveals the microecological drivers of seed vigor and provides candidate strains for inoculant development, thereby supporting the sustainable, seed-based propagation of S. miltiorrhiza. Full article

To investigate how steam-explosion pretreatment affects humification during sawdust composting, an aerobic composting experiment was conducted using sawdust, chicken manure, and spent mushroom substrate as feedstocks. Two treatments were established—a steam-explosion-pretreated sawdust group (SEW) and an untreated sawdust control (CK)—each with three replicate reactors. Samples were collected dynamically at five key composting stages (initial, heating, thermophilic, cooling, and maturation) for physicochemical, enzymatic, and microbial community analyses. Linear mixed-effects model analysis revealed that enzyme activities were significantly affected by treatment, composting time, and their interaction. SEW significantly enhanced cellulase and polyphenol oxidase activities, and increased laccase and peroxidase activities at specific stages. Compared with CK (humic substances, 75.30 g/kg), SEW promoted higher humic substance accumulation (120.80 g/kg) and altered the dynamics of dissolved organic carbon. Microbial co-occurrence networks in SEW (50 nodes, 602 edges) were more complex than CK (49 nodes, 464 edges), indicating tighter microbial interactions. Path analysis revealed that HS in CK was mainly influenced by DOC and temperature, while HS in SEW was associated with enzyme activities, microbial diversity, and Pseudogracilibacillus. These results suggest that steam-explosion pretreatment enhances substrate transformation and humic substance formation during composting. Full article

Background/Objectives: Glypican-1 (GPC1) is a heparan sulfate proteoglycan that plays a critical role in regulating various signaling pathways and tumor development. Overexpression of GPC1 promotes tumor cell proliferation and invasiveness, and is associated with poor clinical outcomes. Therefore, anti-GPC1 monoclonal antibodies (mAbs) have been developed in various modalities for tumor therapy. Methods: We developed novel anti-GPC1 mAbs using a flow cytometry-based high-throughput screening approach, the Cell-Based Immunization and Screening (CBIS) method. Results: A clone G₁Mab-28 (IgG₁, κ) reacted with GPC1-overexpressed Chinese hamster ovary-K1 (CHO/GPC1), but not parental CHO-K1, in flow cytometry. Furthermore, G₁Mab-28 recognizes the endogenous GPC1-expressing human esophageal squamous cell carcinoma KYSE770 cell line. Furthermore, G₁Mab-28 specifically recognized only CHO/GPC1, but not the other GPC family-overexpressed CHO-K1. The dissociation constant values of G₁Mab-28 for CHO/GPC1 and KYSE770 were determined to be 3.3 × 10⁻⁸ M and 4.6 × 10⁻⁹ M, respectively. Moreover, G₁Mab-28 is suitable for Western blotting and immunohistochemistry. Conclusions: G₁Mab-28, established by the CBIS method, is versatile for basic research and is expected to contribute to antibody-based tumor therapy. Full article

Iodoacetic acid (IAA), a highly cytotoxic disinfection byproduct commonly detected in drinking water, poses a potential risk to female reproductive health. The direct molecular mechanisms underlying its effects on the reproductive system epithelium remain unclear. This study demonstrates that IAA induces glycational stress in primary porcine uterine (UECs) and oviduct epithelial cells (OECs), representing an early event contributing to extensive cellular toxicity. IAA exposure inhibited Glyceraldehyde-3-Phosphate Dehydrogenase (GAPDH) enzymatic activity and promoted the accumulation of advanced glycation end products (AGEs) Nε-(carboxymethyl)lysine (CML), triggering mitochondrial dysfunction, redox imbalance, calcium dyshomeostasis, and endoplasmic reticulum stress. These disturbances activated a dysregulated signaling network involving the p38 MAPK, AKT, and NF-κB pathways, ultimately causing G1/S cell cycle arrest and apoptosis. Notably, pretreatment with the AGE inhibitor pyridoxamine reduced CML accumulation, restored mitochondrial function, and alleviated apoptotic cell death. These findings identify glycational stress as a key initiating mechanism for IAA-induced reproductive epithelial toxicity, providing mechanistic insight into the potential health risks of environmental disinfection byproducts. Full article

Chondrosarcoma (CHS), the second most common primary malignant cartilage tumor, is largely resistant to conventional therapies, making surgical resection the standard treatment. Proton therapy offers a physical advantage through the Bragg peak, enabling targeted irradiation while sparing surrounding tissues. However, differential biological responses between malignant and normal cartilage cells remain poorly understood. In this study, CHS SW1353 cells and normal chondrocytes (MC615) were exposed to proton irradiation. Biological responses were assessed via clonogenic survival, cell viability, apoptosis (caspase 3/7), micronucleus formation, cell cycle profiling, and oxidative stress markers. Proteomic changes were analyzed using mass spectrometry and bioinformatics. CHS cells exhibited higher radioresistance (D₁₀ = 6.45 Gy) than normal chondrocytes (D₁₀ = 5.08 Gy), oxidative stress adaptation, G1 arrest and proteomic plasticity, whereas normal chondrocytes displayed increased oxidative stress, extracellular matrix fragility and impaired integrin signaling. Notably, the tumor-specific increased levels of Tyrosine-protein kinase Fyn and Yes1-associated transcriptional regulator (YAP1) signaling suggest molecular drivers of radioresistance. Overall, proton irradiation elicits distinct biological and proteomic responses in malignant versus normal cartilage cells. These findings highlight potential radiosensitization targets, including Fyn/Src and YAP1/Hippo pathways, while underscoring the need to optimize proton therapy to enhance tumor control while minimizing damage to healthy cartilage. Full article

Introduction: Distress during pediatric magnetic resonance imaging (MRI) neuroimaging can compromise scan quality and negatively impact children’s experiences. This review aimed to systematically synthesize biomarkers and psychological factors associated with distress in children, adolescents, and young adults undergoing neuroimaging. Methods: This systematic review was conducted according to PRISMA and AMSTAR-2 guidelines and preregistered in OSF. A systematic search was performed in six electronic databases, including observational articles published between 2000 and 2025 that assessed distress during MRI and functional MRI (fMRI). Data extraction and risk of bias assessment (QUIPS tool) were performed independently by two reviewers. Results: Ten studies (n = 558) examining distress during neuroimaging were included in this review. Distress was assessed through subjective self- and parent-reports, objective physiological measures, and qualitative interviews. Overall, distress levels were low to moderate; most participants tolerated scans well, though younger age, male sex, parental anxiety, procedure length, and chronic illness were associated with greater discomfort. Noise, immobility, and boredom emerged as the most frequent triggers, while strategies such as distraction, age-appropriate information, and reducing waiting times were perceived as helpful. Among participants with cancer, scan-related anxiety was closely linked to fear of recurrence and perceived stress. Risk of bias across studies was moderate to high, particularly in domains of attrition and statistical reporting. Conclusions: Distress during scanning is driven by anticipatory and parental anxiety, procedure length, and chronic illness. Biomarkers (e.g., cortisol, blood pressure) showed inconsistent links with subjective distress, highlighting the need for integrated measures. Full article

Background/Objectives: Anaplastic thyroid carcinoma (ATC) is one of the most aggressive and lethal forms of malignant neoplasm of the endocrine system, and osteopontin (OPN) has been shown to be aberrantly expressed in this tumor type. Among the five OPN splicing isoforms (OPN-SI), OPN-4 has been recently reported in several tumor types, including ATC, but its functional role(s) have not yet been elucidated. Methods: To characterize OPN-4 roles in ATC cells, OPN-4 was ectopically overexpressed in the c643 ATC cell line, generating the c643/OPN-4 cells. OPN-roles were evaluated by cell functional assays, including cell proliferation and viability, using Carboxyfluorescein Succinimidyl Ester (CFSE), crystal violet, and trypan blue assays. For migration, clonogenicity, cell cycle and apoptosis assays were used. For assessment, c643/OPN-4 cells were cultured in two-dimensional (2D) monolayers or three-dimensional (3D) spheroids with the latter being maintained in a bespoke microfluidic system. Results: OPN-4 overexpression led to a significant reduction in cell proliferation, viability, migration and clonogenicity. c643/OPN-4 cells displayed a significant accumulation in the G0/G1 phase and a decrease in the S phase of the cell cycle; however this did not affect cell death or the expression levels of other OPN-SI. In a spheroid model of c643/OPN-4 cells, no significant differences were found in spheroid size or viability when compared to those formed by control cells. Notably, OPN-4 overexpression enhanced the effects of sorafenib on cell viability under dynamic treatment conditions involving continuous perfusion. Conclusions: These early findings point to the fact that OPN-4 may reduce some aspects of tumor progression features in ATC cells and open new avenues for investigating OPN-4 as a biomarker of therapeutic response in personalized treatment strategies. Full article

Garrya flavescens S. Wats. (GF) has been traditionally used to treat gastrointestinal spasms, yet its bioactivity within the central nervous system remains unexplored. This study aimed to characterize the bioactive constituents of GF and evaluate its anti-inflammatory and metabolic regulatory effects in lipopolysaccharide-activated microglia. Phytochemical profiling using LC-HRMS and HPLC identified rutin as a primary bioactive component, present at an exceptionally high concentration (9309 μg/g). In BV-2 microglial and RAW 264.7 cells, GF treatment significantly suppressed the expression of pro-inflammatory cytokines and mediators in a dose-dependent manner. Mechanistic studies revealed that GF specifically modulated the ERK signaling pathway. Furthermore, Seahorse XF analysis demonstrated that GF restored mitochondrial homeostasis by reducing basal respiration and proton leak while significantly enhancing spare respiratory capacity. Finally, conditioned medium from GF-treated microglia improved the viability of N2A neuronal cells. These findings highlight GF as a potent botanical source with significant neuroprotective potential, offering a promising candidate for functional food or nutraceutical applications targeting neuroinflammatory disorders. Full article