Search Results (3,129)

Fatigue failure constitutes an issue that cannot be ignored when designing welded steel structures due to the initiation of cracks at weld toes and defects under cyclic loading conditions. Traditional methods, such as the notch stress approach, estimate fatigue life by modeling local stress distributions using idealized weld geometries. While these methods are widely accepted in design codes, they can be limited by complexity and reduced accuracy in real-world applications. This study explores the use of artificial neural networks (ANNs) to enhance fatigue life prediction through data-driven modeling. The proposed method involves training an ANN using synthetic data generated through finite element simulations of S355 steel weldments under various loading histories, rates, and frequencies. The objective is to capture the influence of local geometric and stress features without relying solely on assumptions used in conventional approaches. The FEM-based training data incorporate both classical experimental findings and validated modeling practices. While performance evaluation of the ANN model is reserved for future work, this study lays the groundwork for replacing or supplementing the notch stress approach with a more adaptable and efficient predictive tool. The integration of machine learning into fatigue assessment has the potential to improve reliability, reduce computational burden, and support more informed maintenance and design decisions. Full article

Background: Lung adenocarcinoma (LUAD) and squamous cell carcinoma (LUSC), the major subtypes of non-small cell lung cancer (NSCLC), exhibit distinct molecular landscapes that demand precision in prognosis and therapy. While deep learning models can achieve high predictive accuracy, their black-box nature limits clinical translation. Methods: We introduce AttentioFuse, an interpretable deep learning framework employing a Reactome-guided mid-fusion strategy for multi-omics integration. AttentioFuse builds on three pillars: (i) dual-phase learning with omics-specific encoders to preserve modality-unique patterns, (ii) hierarchical attention mechanisms (cross-omics, feature-level, and fusion-layer) to quantify layer contributions dynamically, and (iii) integrated explainability combining DeepSHAP and global attention weights for gene-to-pathway interpretation. Two depth variants are instantiated under identical priors: a three-layer configuration (3F) for main discrimination and a five-layer configuration (AttentioFuse-5X) for deeper hierarchical interpretation; the 5X variant is trained end-to-end and yields comparable accuracy while enhancing pathway-level resolution. Results: Evaluated on The Cancer Genome Atlas (TCGA) LUAD/LUSC cohorts, AttentioFuse matches state-of-the-art performance in TNM staging while uncovering actionable biological insights, including pan-NSCLC AKT/mTOR metabolic control, histology-divergent Notch signaling roles, and additional pathways related to developmental reactivation, microbiota-associated metastasis, and extracellular matrix remodeling. Conclusions: By design, AttentioFuse-5X bridges predictive performance with hierarchical, pathway-resolved explanations, advancing oncology by transforming black-box predictions into biologically grounded decision support. Full article

The glioma tumor microenvironment (TME) exhibits profound heterogeneity that drives tumor progression and therapy resistance. By integrating single-cell RNA sequencing (eleven samples) and spatial transcriptomics (two samples), the cellular components of the glioma microenvironment were deconvoluted, revealing tumor-associated foam cells (TAFCs) as the most abundant and centrally connected subtype. The high expression of two prognostic candidate genes, growth differentiation factor 8 (GDF-8, also known as myostatin, MSTN) and transcription factor 12 (TCF12), in TAFCs was found to be correlated with poor overall survival. These two genes were associated with M2 macrophage infiltration, altered cholesterol homeostasis, and immunosuppressive signaling. Regulatory network and pathway analyses, based on computational motif enrichment and co-expression analysis, linked them to ribosome, Notch signaling, DNA repair, and cell-cycle pathways. Pseudotime trajectories revealed dynamic expression during differentiation. Additionally, drug sensitivity prediction analysis demonstrated that MSTN expression was significantly associated with sensitivity to paclitaxel and VE-822, while TCF12 expression showed potential associations with sensitivity to cytarabine, olaparib, Wee1 inhibitor, paclitaxel, and VE-822. Logistic regression analysis combining clinical parameters with MSTN and TCF12 expression effectively achieved risk stratification for glioma, with higher composite scores predicting worse 2- and 3-year survival outcomes. Calibration curves demonstrated high consistency between nomogram-predicted overall survival probabilities and actual observed outcomes. Immunofluorescence confirmed upregulated expression of MSTN and TCF12 in glioma tissues and their co-localization with macrophages. In conclusion, this study identified TAFCs as the central cells in the glioma microenvironment, with their signature genes MSTN and TCF12 representing candidate immunometabolic signatures associated with macrophage-mediated immunosuppression and metabolic reprogramming in glioma, suggesting their potential as biomarkers for patient stratification and as targets for immunometabolic therapies. Full article

Penile squamous cell carcinoma (PSCC) is rare, but a biologically aggressive malignancy. Recent comprehensive genomic profiling (CPG) efforts revealed the underlying genomic landscape of PSCC, identifying TP53, TERT, CDKN2A, PIK3CA, NOTCH1, and FAT1 as frequently altered genes with potential roles in penile oncogenesis. In addition, recurrent mutations encoded in the GPS1 gene have been observed in 7.4% of cases in a particular PSCC cohort. Functional studies demonstrated loss of function due to GPS1 Exon 9 missense mutations, proposing a possible role for these alterations as oncogenic driver events in PSCC. However, no other study confirmed the occurrence of GPS1 gene mutations in PSCC. To elucidate the biological function of GPS1 exon 9 mutations in PSCC pathogenesis, we utilized a comprehensive in-house cohort of 106 PSCC cases to explore their frequency and occurrence. Albeit, the previously reported GPS1 mutations p.D382H and p.M384I were not observed in this large cohort of PSCC cases; this analysis, however, revealed two novel GPS1 alterations in exon 9 in two (1.9%) of the analyzed cases: p.S372F (c.1115C>T) and p.A375D (c.1124C>A). This observation suggests that GPS1 exon 9 sequence is a target of genetic alteration during PSCC pathogenesis. However, the non-recurrent nature of these alterations indicates that they are unlikely to represent oncogenic drivers in this disease. Full article

In response to the challenges of low detection efficiency, high omission rate in small target detection and high model complexity in wood surface defect detection, this study proposes a lightweight detection model based on YOLO, which integrates a dual-path integrated attention network (DFA-Net). The model is built on the enhanced YOLOv5 framework and achieves a balance of accuracy and efficiency through the collaborative optimization of multiple modules. Specifically, this paper designs a dual-path downsampling convolutional module (DP-DCM), combining wavelet transform with dual-path feature fusion to improve multi-scale feature extraction capabilities while reducing the number of parameters. Next, a fusion attention module (FAM) is designed to dynamically focus on defect features in complex backgrounds through channel and spatial attention mechanisms. Furthermore, a focal modulation network (FMNet) is introduced to enhance the robustness of the augmentation model in detecting small defects. Finally, the NWD Loss function is used to mitigate the localization bias of small targets. Experimental results show that the improved model achieves a 92.8% mAP rate on five types of defect datasets (dead knots, live knots, cracks, notches, and marrow). Compared with the baseline model, YOLOv5s, the performance of this model has been improved by 6.5%. The model runs at a detection speed of 105 FPS, and the number of parameters is only 5.8 million, which is better than models such as YOLOv8 and YOLOv9-t. While maintaining a lightweight design, this method achieves high precision and real-time performance on a consumer-grade GPU platform, indicating its practical applicability in automated wood inspection scenarios. The proposed approach provides an efficient solution for intelligent wood sorting, contributing to improved wood utilization and enhanced processing automation. Full article

Notch wear in austenitic stainless steel turning develops rapidly and remains a key productivity limitation with carbide tools. This work identifies the initiation mechanism of notch wear when turning EN 1.4307 stainless steel using CVD-coated cemented carbide inserts with an Al₂O₃ top layer. Turning tests were performed under dry conditions, followed by optical wear measurements and chip surface analysis. The tool–chip interface chemistry and material transfer were characterized using SEM/EDS, while high-frequency acoustic emissions were recorded to resolve the dynamics of adhesive events. Thermo-mechanical FEM simulations were conducted to map contact pressure and temperature along the cutting edge. The results show that adhesive wear initiates immediately at engagement and governs notch formation: polluted SiO₂ deposits act as an active bonding medium, and repeated bond formation/rupture removes extremely thin flakes of tool and coating material, evidenced by Al₂O₃ and Ti(C,N) fragments on the chip and by characteristic acoustic cluster waves. A new tool–chip contact model is presented, indicating that high pressure and high temperature within the polluted SiO₂ near the chip’s outmost side promote larger, stronger adhesive bonds together with the absence of ceramic particles near the rake in the notch area. Oxidation and diffusion are assumed to be secondary processes that become relevant after local coating loss, while adhesion remains the primary removal mechanism during early and intermediate stages. Full article

Background. NOTCH receptors play a pivotal role in carcinogenesis. Upon ligand binding, a cascade of proteolytic cleavages mediated by ADAM proteases and the γ-secretase complex activates the receptor, ultimately releasing the NOTCH intracellular domain (NICD). NICD translocates to the nucleus, where it regulates gene expression. This review mainly aims to evaluate γ-secretase inhibitors (GSIs) as anticancer agents in preclinical and clinical settings, with a focus on their ability to block tumor progression, target cancer stem cells, and overcome resistance to standard therapies. Methods. A systematic search was conducted in the ISI Web of Science, PubMed, and Scopus databases, following PRISMA guidelines. The review included preclinical in vitro and in vivo studies, as well as clinical trials, investigating GSIs, either as monotherapy or in combination with other treatments, in TNBC, metastatic melanoma, PDAC, gastric cancer, and NSCLC. Exclusion criteria included duplicates, non-English articles, studies published before 2010, studies on non-cancer conditions, research unrelated to NOTCH signaling, and studies outside the selected cancer types. Overall, 69 articles were included and categorized into the five types of cancer analyzed (20 on NSCLC, 22 on TNBC, 11 on metastatic melanoma, 7 on GC, and 9 on PDAC). Of these, 60 studies corresponded to preclinical research in the types of cancer, and 9 studies corresponded to clinical trials in the types of cancer except for GC. Two independent authors screened and extracted relevant data, with disagreements resolved by the corresponding author. Findings were synthesized qualitatively across cancer types under study. Results. This review summarizes therapeutic advances involving GSIs in cancers driven by oncogenic NOTCH signaling, based on the 69 articles included. Preclinical studies show that GSIs synergize with chemotherapy and radiotherapy, particularly in NSCLC, melanoma, and TNBC, and block EMT, overcome therapeutic resistance, and improve prognosis. Commonly used GSIs include DAPT and RO4929097, which enhance the efficacy of agents, such as gemcitabine (PDAC), paclitaxel, osimertinib, erlotinib, and crizotinib (NSCLC), and 5-FU (gastric cancer, TNBC). Promising strategies include combining GSIs with SAHA, ATRA, CB-103, and other NOTCH signaling targeting molecules, either alone or with chemo- and radiotherapy. Clinical trials with GSIs, however, remain limited. RO4929097 is the most extensively tested GSI in clinical settings. PDAC trials combining GSIs with gemcitabine showed no benefit; melanoma trials yielded modest outcomes; and TNBC trials demonstrated partial responses to GSIs but overall low efficacy and significant adverse events. Discussion and Conclusions. Despite encouraging preclinical evidence, clinical trials with GSIs have underperformed, largely due to tumor heterogeneity, dosing limitations, and the non-selective nature of γ-secretase inhibition. Other NOTCH inhibitors, such as DLL4 antibodies, also resulted in partial responses and secondary effects. Future strategies should prioritize receptor-specific NOTCH inhibitors, patient stratification based on NOTCH pathway activation, and optimized combination regimens. Emerging approaches include integrating immunotherapy with advanced technologies such as CRISPR, CAR-T cells, and bispecific antibodies, as well as targeted delivery systems to enhance efficacy and reduce toxicity. Additional research directions include addressing the tumor microenvironment and EMT-driven resistance, elucidating the mechanisms of immune evasion, and inhibiting tumor angiogenesis. Finally, leveraging artificial intelligence and big-data-driven personalized medicine, including sex-specific considerations, will be essential for improving patient outcomes. Full article

Acute Lymphoblastic Leukemia (ALL) is a heterogeneous hematological malignancy in which disease progression and response to therapy are influenced by a complex network of molecular alterations, interactions with the bone marrow microenvironment, and epigenetic modulation mechanisms. Crosstalk between oncogenic, inflammatory, and immunoregulatory signaling pathways, together with epigenetic modifications, contributes to the maintenance of leukemic survival and the development of therapeutic resistance. This review analyzes the role of cytokines and chemokines such as IL-6, TNF-α, and CXCL12, which act as biological biomarkers and key mediators of leukemia niche remodeling, and the main signaling pathways involved in ALL, such as Wnt/β-catenin, JAK/STAT, PI3K/AKT/mTOR, Notch, and BCR, highlighting their functional interconnection with the tumor microenvironment. The role of epigenetics in modulating the dialogue between leukemia cells and stromal components is also discussed. Epigenetic programs govern leukemia’s dependence on stromal support, inflammatory and niche-derived signals, as well as the microenvironment signaling pathways. Overall, targeting leukemia-niche interactions is a crucial strategy for improving outcomes in ALL and to identify potential molecular vulnerabilities, also for developing new therapeutic approaches for the treatment of the disease. Full article

In this study, the flexural behavior of notched steel beams retrofitted with CFRP is investigated. Two series of tests, including W200 × 22 and W14” wide-flange notched beams rehabilitated with externally bonded (EB) CFRP are evaluated under static loading. The W200 × 22 beams were received directly from a factory, whereas the W14” wide-flange beams were extracted from the Original Champlain Bridge after roughly 60 years in service. The parameters considered include the CFRP elastic modulus, CFRP configuration, notch depth, anchorage system, and adhesive type. The effect of the CFRP elastic modulus on the rehabilitation technique is examined by using Normal Modulus (NM) and Ultra-High Modulus (UHM) CFRP with approximately the same tensile capacity. Failure modes, load–deflection behavior, strain distributions along the CFRPs, and Crack Mouth Opening Displacement (CMOD) are thoroughly discussed in this study. The results reveal that both UHM and NM CFRP significantly enhance the load-carrying capacity. However, specimens retrofitted with UHM CFRP exhibit a brittle behavior, whereas those strengthened with NM CFRP show a more ductile behavior. Full article

Periodontitis is a dysbiosis-driven inflammatory disease in which a pathogenic subgingival biofilm disrupts the host–microbe equilibrium and promotes progressive loss of tooth-supporting tissues. While periodontal destruction has traditionally been explained mainly through the host immune response, increasing experimental and clinical evidence suggests that epithelial–mesenchymal transition (EMT)-like changes in the gingival epithelium may contribute to barrier failure and tissue remodeling during disease progression. EMT is characterized by reduced epithelial adhesion and polarity, alongside a shift toward a mesenchymal-like phenotype with enhanced motility and impaired epithelial barrier function. This narrative review focuses on how periodontal pathogens, particularly red complex organisms and keystone species, may trigger gingival EMT through virulence factors such as gingipains, fimbriae, lipopolysaccharide, and outer membrane vesicles. These microbial signals can hijack host pathways including TGF-β/Smad, Wnt/β-catenin, and Notch to drive EMT-associated transcriptional changes and downstream functional consequences. Collectively, pathogen-induced gingival EMT may facilitate deeper microbial invasion, perpetuate chronic inflammation, impair wound healing, and contribute to fibrotic remodeling, ultimately linking microbial dysbiosis to connective tissue destruction. Understanding these mechanisms may support the development of EMT-related biomarkers and targeted interventions aimed at preserving epithelial barrier stability in periodontitis. Full article

Delamination is a critical failure mode in composite laminates that degrades the structural performance and load-carrying capacity. This study investigates the improvement of Mode I and Mode II interlaminar fracture toughness of carbon fiber-reinforced polymer (CFRP) laminates through the interleaving of electrospun thermoplastic nanofiber mats. Nanofiber veils were inserted between carbon fiber plies to enhance resistance to delamination under tensile opening (Mode I) and in-plane shear (Mode II) loading. The effects of nanofiber interleaving were evaluated using double cantilever beam (DCB) tests for Mode I and end notch flexure (ENF) tests for Mode II. Both tests were conducted on a symmetric quasi-isotropic laminate [-45/45/90/0₅]_s containing a thick unidirectional 0° ply at the mid-plane. Thermally induced residual stresses resulting from mismatches in ply coefficients of thermal expansion and unsymmetric arm lay-ups were accounted for in the experimental determination of fracture toughness. These stresses, generated during cooling from the cure temperature, influence the effective strain energy release rate and were included in the fracture toughness calculations to ensure accurate toughness evaluation and consistency with numerical predictions. The results demonstrate improved delamination fracture toughness, highlighting the potential of nanofiber interleaving for aerospace and wind energy applications. Full article

Background: Reverse shoulder arthroplasty (RSA) relies on secure baseplate fixation to the glenoid. This carries a risk of suprascapular nerve (SSN) injury during peripheral screw insertion. Although fixed safe zones have been described, it remains unclear whether these scale with scapular morphometry or whether common screw positions confer differential SSN risk. Methods: Twenty cadaveric shoulders (ten pairs) were dissected. The superior safe zone (distance from the supraglenoid tubercle to SSN at the suprascapular notch) and posterior safe zone (distance from the glenoid rim to SSN at the spinoglenoid notch) were measured. Scapular dimensions (height, spine length, width) were measured. In ten shoulders, simulated RSA baseplate fixation was performed with superior screws placed at 11, 12, or 1 o’clock and posterior screws at 8, 9, or 10 o’clock. Screw lengths were based on glenoid depth. Cortical breach and SSN proximity were recorded. Linear regression assessed relationships between scapular dimensions and safe zones. Results: The superior safe zone (mean 2.9 ± 0.5 cm) significantly correlated with scapular dimensions (r = 0.78–0.86; p < 0.0001). All superior screws remained intraosseous across configurations. The posterior safe zone (1.9 ± 0.6 cm) showed no correlation. Posterior cortical breach occurred in 50% of specimens across all tested positions and was associated with smaller scapular spine length (p = 0.027). No significant difference in SSN proximity was observed between posterior screw positions. Conclusions: Scapular dimensions predict the superior, but not posterior, safe zone. Scapulae with shorter spine lengths demonstrated increased risk of posterior cortical breach, independent of screw position. These findings establish anatomical scalability of the superior safe zone and suggest that scapular morphometry may inform preoperative RSA planning; however, prospective validation is needed before routine clinical implementation. Full article

Left ventricular noncompaction cardiomyopathy (LVNC) is characterised by a two-layered ventricular wall with prominent trabeculations and deep recesses adjacent to a thinned compact layer. The phenotype spans from incidental findings to severe heart failure and malignant arrhythmias. More than 190 genes belonging to sarcomeric, cytoskeletal, mitochondrial, transcriptional and signalling pathways have been implicated, although only a subset reaches high gene disease validity in contemporary frameworks. Objectives: (i) Delineate the validated genetic landscape of LVNC; (ii) integrate developmental biology with cardiac genomics; (iii) translate genotype knowledge into diagnostic, prognostic and therapeutic guidance; (iv) outline a research agenda for precision cardiology. Methods: A narrative, pathway-oriented review of human and experimental studies (2000–July 2024). Results: Thirty-two genes meet definitive/strong validity thresholds and cluster in five biological networks. Oligogenic constellations account for ~4% of probands in recent cohorts. Imaging correlates (especially quantitative trabecular complexity and diffuse fibrosis metrics) provide complementary risk information. Conclusions: LVNC represents a convergence phenotype triggered by perturbations across developmental and structural networks; clinical management benefits from integrated genomics–imaging workflows and mechanism-informed trial design. Full article

Periodic structures that may exist within the neutron imaging detector can introduce periodic noise into the imaging results, directly degrading image quality and further affecting the performance of deconvolution. This periodic noise appears as four-pointed star-shaped peaks in the amplitude spectrum of the frequency domain. However, the distribution of honeycomb-like noise structures in neutron imaging results makes it difficult to detect using conventional thresholding methods. We propose a method that applies a dilation operation before threshold detection to enhance the contrast between peaks and the surrounding areas. Then, a notch filter is used to smooth the peaks containing noise information, thereby removing the periodic noise structure. This approach effectively eliminates honeycomb structures of approximately 40 micrometers and improves the image quality after deconvolution processing. Full article

Background/Objective: Resin-based composite (RBC) gained wide popularity in dentistry due to its excellent biocompatibility, superior aesthetics, and good bonding to enamel and dentine. However, they have several shortcomings, including mechanical insufficiency and shrinkage tendency. Many researchers have utilized nanoparticles (NPs) as a reinforcing filler for RBCs. This article focused on assessing the impact of three different nanoparticles, ZrO₂, TiO_2, and SiO_2, with concentrations of 3 wt% and 7 wt%, on the elastic modulus (E) and fracture toughness (K_IC) of one commercial light-activated dental resin composite. Methods: 140 rectangular specimens were constructed according to ISO 4049 with dimensions (25 × 2 × 5 ± 0.03 mm) and (25 × 2 × 2 ± 0.03 mm) for fracture toughness and elastic modulus, respectively. Specimens were categorized into four main groups based on nanofiller types. Control: plain without filler (CC) and three modified ones with ZrO₂ (ZC), TiO₂ (TC), and SiO₂ (SC). Furthermore, modified groups were divided into two subgroups according to nanofiller concentration, 3 and 7 wt% (ZC3, ZC7, TC3, TC7, SC3, and SC7), n = 10. Mechanical testing for fracture toughness was completed using a single-edge notched beam, while a three-point bending test was used for elastic modulus. Analysis of data was based on two-way ANOVA and Bonferroni post hoc (α = 0.05). Results: ZrO₂ provided the most substantial improvement in both E and K_IC, with the optimal performance observed at 3 wt% for stiffness and 7 wt% for toughness. TiO₂ groups also enhanced these properties at both concentrations; however, the gains were less pronounced compared to ZrO₂. SiO₂ improved mechanical performance at 3 wt%, but a higher loading of 7 wt% resulted in reduced values. Conclusions: Resin-based composite modified with 3 wt% of NPs tends to possess higher fracture toughness and modulus of elasticity. Fracture toughness enhancement was concentration-dependent with ZrO₂ NPs, where the best result was obtained with 7 wt%. Nanoparticle-reinforced composite, particularly ZrO₂, may be suitable for prosthodontic applications. Full article