Search Results (2,296)

Background/Objectives: Lung squamous cell carcinoma (SCC), a major subtype of non-small cell lung cancer, remains a significant clinical challenge due to a scarcity of actionable molecular targets and the limited effectiveness of current targeted therapies. Emerging treatment strategies inhibit the gene expression of lineage survival oncogenes such as ΔNp63 and SOX2. CRISPR interference (CRISPRi) is a promising method to downregulate these genes; however, the efficacy depends on effective delivery. Here, we focused on the delivery system using nanobubbles (NBs) and ultrasound (US) for site-specific CRISPRi delivery to SCC. We evaluated the therapeutic efficacy of plasmid-based CRISPRi (pCRISPRi) targeting SOX2 or ΔNp63 using intratumoral pCRISPRi/NBs injections followed by US. Methods: A mixture of NBs and pCRISPRi was injected directly into the tumors and exposed to US-induced cavitation to facilitate pCRISPRi uptake. Tumor volume was measured every other day, and apoptosis was assessed by TUNEL assay. Results: In a lung SCC xenograft model, NBs/US-mediated pCRISPRi delivery induced apoptosis and significantly suppressed tumor growth. Conclusions: These findings suggest that US-guided, NB-facilitated delivery of pCRISPRi can locally suppress lineage survival oncogenes and trigger tumor cell death, representing a promising targeted therapy for lung SCC. Additionally, this platform could be adapted to other cancers by targeting alternative factors. Full article

The treatment of organic waste from dyes or other industry processes is a crucial issue that requires urgent attention. Photocatalysis is a promising method for tackling this problem, with ZnO being a commonly used photocatalyst material. This study compared the degrading efficiency of ZnO particles and ZnO-Ag composites by utilizing flame and spray pyrolysis techniques. Under UV light, methylene blue (MB) was used as a model organic waste. The generated particles were characterized using Brunauer–Emmett–Teller (BET) surface area, scanning electron microscopy (SEM), X-Ray diffraction (XRD), and a UV-Vis spectrometer. The findings showed that the ZnO and ZnO-Ag obtained using both methods exhibited hexagonal Wurtzite crystal structures, and there was no significant difference in the crystal sizes produced. SEM analysis indicated that the morphology of the resulting particles differed significantly, with flame-synthesized particles being remarkably smaller in size (one-thirtieth the size following spray synthesis) and having smoother surfaces. Furthermore, the addition of Ag particles to ZnO enhanced the MB degradation efficiency by two to three times, achieving a maximum of 64% at 75 min. The BET analysis showed that the surface area of ZnO doped with Ag was larger compared to that of pristine ZnO. On the other hand, the ZnO-Ag particles produced via spray pyrolysis exhibited a total pore volume (determined through nitrogen adsorption–desorption analysis) three times larger than that of the particles produced via the flame method. The particles produced via spray pyrolysis also had better MB degradation performance compared to those synthesized using flame pyrolysis. Full article

The digitalization of financial systems has intensified risks such as cyber fraud, data breaches, and financial exclusion, particularly for individuals with low digital financial literacy (DFL). As digital finance becomes ubiquitous, DFL has emerged as a critical competency. However, the determinants of DFL remain insufficiently explored. This study aims to validate a comprehensive, theory-driven model that identifies the key sociodemographic, economic, and psychological factors that influence DFL acquisition among investors. Drawing on six established learning and behavioral theories—we analyze data from 158,169 active account holders in Japan through ordinary least squares regression. The results show that higher levels of DFL are associated with being male, younger or middle-aged, highly educated, and unemployed and having greater household income and assets. In contrast, being married, having children, holding a myopic view of the future, and high risk aversion are linked to lower DFL. Interaction effects show a stronger income–DFL association for males and a diminishing return for reduced education with age. Robustness checks using a probit model with a binary DFL measure confirmed the OLS results. These findings highlight digital inequalities and behavioral barriers that shape DFL acquisition. This study contributes a validated framework for identifying at-risk groups and supports future interventions to enhance inclusive digital financial capabilities in increasingly digital economies. Full article

Quadratic Unconstrained Binary Optimization (QUBO) is the problem of finding binary variable assignments that minimize a given quadratic objective function. Many combinatorial optimization problems can be transformed into equivalent QUBO formulations, and significant research efforts have been devoted to developing efficient QUBO solvers. This paper presents a method for converting a real-world, industrial-scale scheduling problem arising in the heat treatment process of metal parts into an equivalent QUBO formulation. In current operations, two experienced operators manually spend about two hours each day to create a 24 h schedule for two furnaces, considering various constraints and processing priorities. We have developed a C++-based scheduling system that automatically converts this problem into a QUBO instance and solves it using QUBO++, a high-performance toolkit we have recently developed and released. The experimental results on actual scheduling instances show that QUBO++ consistently produces high-quality solutions in a short time, leveraging the computational merits of the QUBO formulation. The system reduces the labor equivalent to two hours of expert work per day, indicating that automated scheduling via QUBO++ is a promising approach for improving efficiency and accuracy in factory operations. Full article

Background: Malignant hyperthermia (MH) is a pharmacogenetic disorder of skeletal muscle triggered by certain anesthetic agents. While Ryanodine Receptor 1 (RYR1) and Calcium Voltage-Gated Channel Subunit Alpha1 S (CACNA1S) are well-established susceptibility genes, the complete genetic basis of MH remains unclear, particularly in Asian populations. Methods: We conducted gene panel testing targeting 24 calcium-related genes in 338 individuals from 247 Japanese families with suspected or confirmed MH. Variants were analyzed on a gene-by-gene basis, and their pathogenicity was assessed using in silico prediction tools. Additionally, patients were classified into subgroups based on the results of the calcium-induced calcium release (CICR) assay and the Clinical Grading Scale (CGS) score. Results: Candidate pathogenic variants were identified in 118 families (48.2%), including 73 (29.8%) in RYR1, 16 (6.5%) in CACNA1S, and 62 (25.3%) in other genes. Among CICR-positive families, RYR1 and CACNA1S variants were detected in 42.0% and 5.3% of cases, respectively. In individuals with high CGS scores (Ranks 5–6), RYR1 and CACNA1S variants were observed in 56.0% and 12.0%, respectively. Variants in other genes such as STAC3, CASQ1, ATP2A1, ASPH, HRC and TRPV1 were also detected. Conclusions: Our findings confirm the predominant role of RYR1 and CACNA1S in MH susceptibility in the Japanese population and highlight additional candidate genes that may contribute to the condition. Broader genetic screening and functional validation studies are warranted to further elucidate the polygenic nature of MH. Full article

The escalating challenges of greenhouse gas emissions, coupled with the severe depletion of oil reserves and the surging global energy demand, have emerged as critical concerns requiring urgent attention. Against this backdrop, biodiesel has been recognized as a viable alternative fuel for compression ignition (CI) engines. The primary objective of this research is to review the application of biodiesel in CI engines, with a focus on enhancing fuel properties and improving atomization performance. This article examines the spray and atomization characteristics of biodiesel fuels and conducts a comparative analysis with diesel fuel. The results show that biodiesel has a longer spray tip penetration, smaller spray cone angle, larger Sauter mean diameter (SMD) and faster droplet velocity due to its higher viscosity and surface tension. Blending with other fuels, such as ethanol, butanol, dimethyl ether (DME) and di-n-butyl ether, results in reduced viscosity and surface tension in these mixed fuels, representing a simple and effective approach for improving biodiesel atomization performance. A comprehensive analysis of spray and droplet impingement is also conducted. The findings reveal that biodiesel exhibits a higher probability of fuel–wall impingement, suggesting that future research should focus on two key directions: first, developing combined strategies to enhance impact-induced secondary atomization while minimizing fuel deposition; and second, investigating single-droplet impingement, specifically that of microscale biodiesel droplets and blended fuel droplets under real engine operating conditions. This paper also presents several advanced techniques, including air-assisted atomization, dual-fuel impingement, nano-biodiesel, and water-emulsified biodiesel, aimed at mitigating the atomization limitations of biodiesel, thereby facilitating the broader adoption of biodiesel in compression ignition engines. Full article

Federated Learning (FL) enables privacy-preserving model training across distributed clients. However, its reliance on voluntary client participation makes it vulnerable to strategic behaviors—actions that are not overtly malicious but significantly impair model convergence and fairness. Existing defense methods primarily focus on explicit attacks, overlooking the challenges posed by economically motivated “pseudo-honest” clients. To address this gap, we propose a Reputation-Aware Defense Framework to mitigate strategic behaviors in FL. This framework introduces a multi-dimensional dynamic reputation model that evaluates client behaviors based on gradient alignment, participation consistency, and update stability. The resulting reputation scores are incorporated into both aggregation and incentive mechanisms, forming a behavior-feedback loop that rewards honest participation and penalizes opportunistic strategies. We theoretically prove the convergence of reputation scores, the suppression of low-quality updates in aggregation, and the emergence of honest participation as a Nash equilibrium under the incentive mechanism. Experiments on datasets such as CIFAR-10, FEMNIST, MIMIC-III demonstrate that our approach significantly outperforms baseline methods in accuracy, fairness, and robustness, even when up to 60% of clients act strategically. This study bridges trust modeling and robust optimization in FL, offering a secure foundation for federated systems operating in open and incentive-driven environments. Full article

Plant-derived pharmaceuticals represent a highly compelling area of research and continue to attract significant interest from countries, regions, scientific communities, and pharmaceutical companies worldwide. Among these, α- and β-amyrins have been identified as high-value triterpenoid compounds with a broad spectrum of potential therapeutic properties, including anti-inflammatory, antidiabetic, antiatherosclerotic, analgesic, antigout, neuroprotective, anti-Parkinsonian, anticancer, antibacterial, and anti-HIV activities. Relevant information and data were obtained through comprehensive searches of major scientific databases, including Web of Science, Elsevier, and the National Library of Medicine. This study highlighted the pharmaceutical potential of α- and β-amyrins, supported by specific evidence from in vivo, in vitro, and clinical trials. Various extraction methods for α- and β-amyrins are discussed, followed by recommendations for future directions in the development of these compounds as pharmaceutical agents and functional food ingredients. This review highlights the therapeutic of α- and β-amyrin compounds in the prevention and treatment of various serious diseases worldwide, potentially opening new opportunities and directions for the pharmaceutical industry. Full article

Traditional methods for predicting surrounding rock grades ahead of tunnel faces encounter challenges: image-based approaches are susceptible to environmental interference, while parameter-based classification may disrupt construction. This study proposes an intelligent rock grade identification method by integrating longitudinal displacement profile (LDP) evolution patterns with deep learning. First, the numerical model was validated against V-D theoretical curves, and LDP evolution laws were systematically analyzed for three rock types (GSI = 15, 30, 50) under nine geological combinations. The results indicate that (1) homogeneous strata exhibit deformation peaks followed by declines; (2) GSI = 15 strata show significantly larger deformations; and (3) stratified schemes display pre-interface deformation peaks and post-interface deformation controlled by subsequent lithology. A novel hybrid neural network was developed to classify strata using LDP curves as input. The model achieved 93.25% training accuracy and 91.20% validation accuracy. Ablation experiments demonstrated their superiority over the other four models with partial module deletions, achieving improvements in test accuracy of 3.24%, 3.08%, 4.16%, and 6.48%, respectively, compared to those models. This lightweight solution effectively overcomes the limitations of manual expertise dependency in conventional models and environmental sensitivity in visual methods. By synergizing LDP evolution analysis with deep learning, this framework provides a reliable approach for real-time rock grade prediction during tunnel advancement. Full article

Background/Objectives: Periodontitis is a chronic infectious inflammatory disorder that affects the supporting structures of the teeth. The gingival epithelium plays a crucial role as a physical and immunological barrier, producing pro-inflammatory cytokines in response to microbial pathogens. Modulation of gingival epithelial function has been proposed as a therapeutic strategy to prevent the progression of periodontal disease. Houttuynia cordata, a perennial herb traditionally used in Asian medicine, is recognized for its anti-inflammatory properties, with documented benefits in the cardiovascular, respiratory, and gastrointestinal systems. However, its potential therapeutic role in oral pathologies, such as periodontitis, remains underexplored. This study aimed to investigate the anti-inflammatory effects of H. cordata extract on interleukin (IL)-1β-stimulated primary gingival keratinocytes (PGKs) subjected to IL-1β-induced inflammatory stress, simulating the conditions encountered during orthodontic treatment. Methods: Inflammation was induced in PGKs using IL-1β, and the impact of H. cordata extract pretreatment was assessed using quantitative real-time reverse transcription polymerase chain reaction, enzyme-linked immunosorbent assay, and immunoblotting. Results: H. cordata extract significantly downregulated the mRNA and protein expression levels of tumor necrosis factor-alpha, IL-8, and intercellular adhesion molecule-1 in IL-1β-stimulated PGKs without inducing cytotoxicity. Conclusions: These findings suggest that H. cordata holds promise as a preventive agent against periodontitis by attenuating inflammatory responses in gingival epithelial tissues. We believe that our findings will inform the development of prophylactic interventions to reduce periodontitis risk in patients undergoing orthodontic therapy. Full article

Zirconia is used widely for high-precision custom abutments; however, stress concentration can compromise osseointegration. Although glass–ceramic spray deposition (GCSD) can enhance the surface properties of zirconia, its biological effects remain unclear. In this study, the biological responses of human osteoblast-like (MG-63) cells to GCSD-modified zirconia surfaces were evaluated to assess the potential application in zirconia abutments. Disk-shaped zirconia and titanium alloy samples were prepared; titanium served as the control (Ti). Zirconia was subjected to polishing (NT), airborne-particle abrasion (AB), or GCSD with (GE) or without (GC) hydrofluoric acid (HF) etching. Surface characteristics, including wettability, surface energy (SE), and surface potential (SP), were analyzed. Cytotoxicity and MG-63 cell adhesion were assessed using the PrestoBlue assay, scanning electron microscopy (SEM), viability staining, and confocal laser scanning microscopy (CLSM). Statistical analysis was performed with a significance level of 0.05. GCSD produced a dense glass–ceramic coating on the zirconia surface, which significantly enhanced hydrophilicity as indicated by reduced water contact angles and increased SE in the GC and GE groups (p < 0.05). HF etching increased SP (p < 0.05). No cytotoxicity was observed in any group. SEM, viability staining, and CLSM revealed enhanced MG-63 cell attachment on Ti and GE surfaces and the highest viability ratio in the GE group. The NT group exhibited the lowest cell attachment and viability at all time points. GCSD effectively improved zirconia abutment surface properties by enhancing hydrophilicity and promoting MG-63 cell adhesion, with biocompatibility comparable to or better than that of titanium. Full article

Background/Objectives: Anterior redisplacement, defined as a postoperative anterior shift of the distal fragment despite intraoperative reduction, is occasionally observed after cephalomedullary nailing for trochanteric femoral fractures. However, its incidence and associated risk factors remain unclear. This study aimed to determine the incidence of anterior redisplacement following intramedullary nail fixation in geriatric trochanteric fractures, and to identify independent risk factors. Methods: This study retrospectively reviewed data from 598 consecutive hips in 577 patients (aged ≥65 years) who underwent intramedullary nail fixation for trochanteric fractures at a single center (2012–2023). Sagittal reduction on the lateral radiographic view was classified as posterior, anatomical, or anterior according to the position of the distal fragment, and was recorded preoperatively and postoperatively. Anterior redisplacement, the primary outcome, was defined as a change in alignment from a posterior or anatomical position postoperatively to an anterior position on any subsequent follow-up radiograph. Independent risk factors were identified by logistic regression. Results: Among the 543 hips reduced posteriorly (n = 204) or anatomically (n = 339), anterior redisplacement occurred in 73 (13.4%). The incidence of anterior redisplacement was significantly higher following anatomical compared to posterior reduction (19.5% vs. 3.4%; p < 0.001), and also higher in fractures that were anteriorly aligned preoperatively (18.0%) compared to anatomical (8.5%; p < 0.01) and posterior (6.2%; p < 0.01) alignment. Multivariate analysis revealed two independent predictors: preoperative anterior alignment (odds ratio [OR] 1.87, 95% confidence interval [CI] 1.24–2.81; p = 0.003) and postoperative anatomical (vs. posterior) reduction (OR 6.49, 95% CI 2.92–14.44; p < 0.001). Age, sex, Arbeitsgemeinschaft für Osteosynthesefragen/Orthopaedic Trauma Association classification, Evans–Jensen classification, nail length, and canal-filling ratio were not associated with redisplacement. No lag-screw cutout occurred during the follow-up. Conclusions: Anterior redisplacement occurred in one of seven geriatric trochanteric fractures despite apparently satisfactory fixation. An anatomical sagittal reduction—traditionally considered “ideal”—increases the risk more than sixfold, whereas a deliberate posterior-buttress is protective. Unlike patient-related risk factors, sagittal reduction is under the surgeon’s control. The study findings provide evidence that choosing a slight posterior bias can significantly improve stability. Full article

Background/Objectives: Low-dose corticosteroids have gained popularity in the treatment of acute respiratory distress syndrome (ARDS); however, the efficacy of high-dose corticosteroids as pulse steroid therapy remains controversial. This study aimed to evaluate the efficacy of pulse steroid therapy in patients with severe ARDS requiring venovenous (V-V) extracorporeal membrane oxygenation (ECMO), where enhanced anti-inflammatory effects may be beneficial. Methods: Using data from the J-CARVE registry, which included patients with severe ARDS managed with V-V ECMO across 24 Japanese hospitals between January 2012 and December 2022, we identified 373 patients treated with corticosteroids. The patients were divided into two groups: pulse steroid therapy and non-pulse steroid therapy. Propensity score matching was performed, and all-cause hospital mortality and ECMO-free days within 28 days were compared between groups. Pulse steroid therapy was defined as methylprednisolone at a dose of 1000 mg/day. Results: After matching, 48 patients were included in each group. The all-cause hospital mortality rates were 41.7% (20/48) in the pulse steroid group and 47.9% (23/48) in the non-pulse steroid group, with no significant difference (odds ratio, 1.28; 95% confidence interval: 0.53–3.12, p = 0.68). The median ECMO-free days were 9.5 (interquartile range [IQR]: 0–17.3) in the pulse steroid group and 3 (IQR: 0–17) in the non-pulse steroid group, showing no significant difference (p = 0.69). Conclusions: Pulse steroid therapy did not improve all-cause hospital mortality or ECMO-free days in patients with severe ARDS who required V-V ECMO. Full article

Genome editing is commonly used in biomedical research. Among the genome editing tools, zinc finger nucleases (ZFNs) are smaller in size than transcription activator-like effector nucleases (TALENs) and CRISPR-Cas9. Therefore, ZFNs are easily packed into a viral vector with limited cargo space. However, ZFNs also consist of left and right monomers, which both need to be expressed in the target cells. When each monomer is expressed separately, two expression cassettes are required, thus increasing the size of the DNA. This is a disadvantage for a viral vector with limited cargo space. We herein showed that T2A-coupled ZF-ND1 monomers were co-expressed from a single expression cassette and that the corresponding ZF-ND1s efficiently cleaved the target DNA sequences. Furthermore, the total amount of transfected plasmid DNA was reduced by half, and genome editing efficiency was equivalent to that of two separate ZF-ND1 monomers. This study provides a promising framework for the development of ZFN applications. Full article

Privacy preservation poses significant challenges in third-party data sharing, particularly when handling table data containing personal information such as demographic and behavioral records. Synthetic table data generation has emerged as a promising solution to enable data analysis while mitigating privacy risks. While Generative Adversarial Networks (GANs) are widely used for this purpose, they exhibit limitations in modeling table data due to challenges in handling mixed data types (numerical/categorical), non-Gaussian distributions, and imbalanced variables. To address these limitations, this study proposes a novel adversarial learning framework integrating gradient boosting trees for synthesizing table data, called Adversarial Gradient Boosting Decision Tree (AGBDT). Experimental evaluations on several datasets demonstrate that our method outperforms representative baseline models regarding statistical similarity and machine learning utility. Furthermore, we introduce a privacy-aware adaptation of the framework by incorporating k-anonymization constraints, effectively reducing overfitting to source data while maintaining practical usability. The results validate the balance between data utility and privacy preservation achieved by our approach. Full article