Search Results (9,565)

Pancreatic cancer is among the deadliest malignancies, with limited treatment options and poor prognosis. Novel strategies are therefore urgently needed. Sotorasib, a KRAS G12C-specific inhibitor, offers targeted treatment for a small subset of patients with this mutation. Electrochemotherapy (ECT), which enhances the cytotoxicity of chemotherapeutic agents through electroporation-induced membrane permeabilization, has shown promise in various tumor types, including deep-seated malignancies such as pancreatic cancer. Combining ECT with sotorasib may potentiate antitumor effects in KRAS G12C-mutated pancreatic cancer; however, preclinical data on such combinations are lacking. This proof-of-concept study evaluated the cytotoxic effects of ECT using bleomycin (BLM) or cisplatin (CDDP) in combination with sotorasib in KRAS G12C-mutated MIA PaCa-2 and KRAS G12D-mutated PANC-1 pancreatic cancer cell lines. ECT alone significantly reduced cell viability, particularly in MIA PaCa-2 cells, where electric pulses induced approximately 75% cell death. Combining ECT with sotorasib resulted in an additive effect on KRAS G12C-mutated MIA PaCa-2 cells, though no synergy was observed, likely due to the high intrinsic sensitivity to electric pulses. These results support the potential of combining physical and molecular therapies in a subset of pancreatic cancer patients and lay the groundwork for further in vivo studies to optimize treatment parameters and explore clinical translatability. Full article

In this study, the possibility of using cement bypass dust as a cement additive was investigated. The utilization of cement bypass dust remains a major problem in cement production, as huge amounts of it are stored in landfills. In this study, a hydrothermal treatment is proposed to modify the properties of this dust and to expand its use. Hydrothermal treatment with pure bypass dust and quartz was carried out to achieve a CaO/SiO₂ ratio of 1 to 2. Samples were synthesized at 200 °C for 2, 4, 8, and 24 h. To examine the influence of the hydrothermal treatment on cement properties, a sample with a CaO/SiO₂ ratio of 1, hydrothermally treated for 8 h, was selected. This study employed XRD, XRF, DSC-TG, and isothermal calorimetry. Most of the target synthesis products, e.g., tobermorite and calcium silicate hydrates, formed after 8 h of sample synthesis, during which quartz was added to bypass dust and a CaO/SiO₂ ratio of 1 was achieved. An examination of the composition of the liquid medium following hydrothermal processing showed that almost all chlorine passed into the liquid medium, while some K₂O remained in the solid synthesis product. The synthesized additive is an effective catalyst for the hydration of Portland cement. After a 28-day curing period, specimens incorporating modified bypass dust replacing up to 10% of the Portland cement by weight demonstrated compressive strengths comparable to, or surpassing, those of specimens composed exclusively of Portland cement. Full article

Chronic Obstructive Pulmonary Disease (COPD) is a multifactorial condition associated with significant systemic complications such as cardiovascular disease (CVD), metabolic disorders, muscle wasting, and sarcopenia. While Body Mass Index (BMI) is a well-established indicator of obesity and has prognostic value in COPD, its role in predicting disease outcomes is complex. Muscle wasting is prevalent in COPD patients and exacerbates disease severity, contributing to poor physical performance, reduced quality of life, and increased mortality. Additionally, COPD is linked to metabolic disorders, such as dyslipidemia and diabetes, which contribute to systemic inflammation and worse prognosis and, therefore, should be treated. The systemic inflammatory response plays a central role in the development of sarcopenia. In this review, we highlight the mixed efficacy of statins in managing dyslipidemia in COPD, considering side effects, including muscle toxicity in such a frail population. Alternative lipid-lowering therapies and nutraceuticals, in addition to standard treatment, have the potential to target hypercholesterolemia, which is a coexisting condition present in more than 50% of all COPD patients, without worsening muscle wasting. The interference between adipose tissue and lung, and particularly the potential protective role of adiponectin, an adipocytokine with anti-inflammatory properties, is also reviewed. Respiratory, metabolic and muscular health in COPD is comprehensively assessed. Identifying and managing dyslipidemia and paying attention to other relevant COPD comorbidities, such as sarcopenia and muscle wasting, is important to improve the quality of life and to reduce the clinical burden of COPD patients. Future research should focus on understanding the relationships between these intimate mechanisms to facilitate specific treatment for systemic involvement of COPD. Full article

Detecting small objects using remote sensing technology has consistently posed challenges. To address this issue, a novel detection framework named ACLC-Detection has been introduced. Building upon the Yolov11 architecture, this detector integrates an attention mechanism with lightweight convolution to enhance performance. Specifically, the deep and shallow convolutional layers of the backbone network are both introduced to depthwise separable convolution. Moreover, the designed lightweight convolutional excitation module (CEM) is used to obtain the contextual information of targets and reduce the loss of information for small targets. In addition, the C3k2 module in the neck fusion network part, where C3k = True, is replaced by the Convolutional Attention Module with Ghost Module (CAF-GM). This not only reduces the model complexity but also acquires more effective information. The Simple Attention module (SimAM) used in it not only suppresses redundant information but also has zero impact on the growth of model parameters. Finally, the Inner-Complete Intersection over Union (Inner-CIOU) loss function is employed, which enables better localization and detection of small targets. Extensive experiments conducted on the DOTA and VisDrone2019 datasets have demonstrated the advantages of the proposed enhanced model in dealing with small objects in aerial imagery. Full article

To combat microphone eavesdropping on devices like smartphones, ultrasonic-based methods offer promise due to human inaudibility and microphone nonlinearity. However, existing systems suffer from low jamming efficiency, poor energy utilization, and weak robustness. Based on these problems, this paper proposes a novel ultrasonic-based jamming algorithm called the Time–Frequency Mosaic (TFM) technique, which can be used for anti-eavesdropping. The proposed TFM technique can generate short-time, frequency-coded jamming signals according to the voice frequency characteristics of different speakers, thereby achieving targeted and efficient jamming. A jamming prototype using the Time–Frequency Mosaic technique was developed and tested in various scenarios. The test results show that when the signal-to-noise ratio (SNR) is lower than 0 dB, the text Word Error Rate (WER) of the proposed method is basically over 60%; when the SNR is 0 dB, the WER of the algorithm in this paper is on average more than 20% higher than that of current jamming algorithms. In addition, when the jamming system maintains the same distance from the recording device, the algorithm in this paper has higher energy utilization efficiency compared with existing algorithms. Experiments prove that in most cases, the proposed algorithm has a better jamming effect, higher energy utilization efficiency, and stronger robustness. Full article

Background: Preeclampsia (PE) is a pregnancy-specific disease and hypertensive disorder with a multifactorial pathogenesis involving complex molecular regulatory networks. Recent studies highlight the critical role of non-coding RNAs, particularly miRNAs and lncRNAs, in PE development. This study investigates the molecular interaction between miR-7151-5p and the lncRNA KCNQ1OT1 and their functional contributions to PE pathogenesis. Methods: An integrative approach combining RNAhybrid-based bioinformatics, dual-luciferase reporter assays, qRT-PCR, Transwell migration and invasion assays, and RNA sequencing was employed to characterize the binding between miR-7151-5p and KCNQ1OT1 and assess their influence on trophoblast cell function and gene expression. Results: A bioinformatic analysis predicted a stable binding site between miR-7151-5p and KCNQ1OT1 (minimum free energy: –37.3 kcal/mol). The dual-luciferase reporter assay demonstrated that miR-7151-5p directly targets KCNQ1OT1, leading to suppressed transcriptional activity. In HTR8/SVneo cells, miR-7151-5p overexpression significantly downregulated both KCNQ1OT1 and Notch1 mRNA, whereas its inhibition showed no significant changes, suggesting additional regulatory mechanisms of Notch1 expression. Transwell assays indicated that miR-7151-5p overexpression suppressed trophoblast cell migration and invasion, whereas its inhibition enhanced these cellular behaviors. RNA-seq analysis further revealed that miR-7151-5p overexpression altered key signaling pathways, notably the TGF-β pathway, and significantly modulates PE-associated genes, including PLAC1, ANGPTL6, HIRA, GLA, HSF1, and BAG6. Conclusions: The regulatory effect of miR-7151-5p on KCNQ1OT1, along with its influence on trophoblast cell dynamics via Notch1 and TGF-β signaling pathways, highlights its role in PE pathogenesis and supports its potential as a biomarker in early PE screening. Full article

Background: Hearing loss is increasingly prevalent and poses a significant public health concern. While both aging and occupational noise exposure are recognized contributors, their interactive effects and gender-specific patterns remain underexplored. Methods: This cross-sectional study analyzed data from 135,251 employees in Jiangsu Province, China. Demographic information, noise exposure metrics, and hearing thresholds were obtained through field measurements, questionnaires, and audiometric testing. Multivariate logistic regression, restricted cubic spline modeling, and interaction analyses were conducted. Machine learning models were employed to assess feature importance. Results: A nonlinear relationship between age and high-frequency hearing loss (HFHL) was identified, with a critical inflection point at 37.8 years. Noise exposure significantly amplified HFHL risk, particularly in older adults (OR = 2.564; 95% CI: 2.456–2.677, p < 0.001), with consistent findings across genders. Men exhibited greater susceptibility at high frequencies, even after adjusting for age and co-exposures. Aging and noise exposure have a joint association with hearing loss (OR = 2.564; 95% CI: 2.456–2.677, p < 0.001) and an interactive association (additive interaction: RERI = 2.075, AP = 0.502, SI = 2.967; multiplicative interaction: OR = 1.265; 95% CI: 1.176–1.36, p < 0.001). And machine learning also confirmed age, gender, and noise exposure as key predictors. Conclusions: Aging and occupational noise exert synergistic effects on auditory decline, with distinct gender disparities. These findings highlight the need for integrated, demographically tailored occupational health strategies. Machine learning approaches further validate key risk factors and support targeted screening for hearing loss prevention. Full article

Crop disease identification is a pivotal research area in smart agriculture, forming the foundation for disease mapping and targeted prevention strategies. Among the most prevalent global wheat diseases, powdery mildew—caused by fungal infection—poses a significant threat to crop yield and quality, making early and accurate detection crucial for effective management. In this study, we present QY-SE-MResNet34, a deep learning-based classification model that builds upon ResNet34 to perform multi-class classification of wheat leaf images and assess powdery mildew severity at the single-leaf level. The proposed methodology begins with dataset construction following the GBT 17980.22-2000 national standard for powdery mildew severity grading, resulting in a curated collection of 4248 wheat leaf images at the grain-filling stage across six severity levels. To enhance model performance, we integrated transfer learning with ResNet34, leveraging pretrained weights to improve feature extraction and accelerate convergence. Further refinements included embedding a Squeeze-and-Excitation (SE) block to strengthen feature representation while maintaining computational efficiency. The model architecture was also optimized by modifying the first convolutional layer (conv1)—replacing the original 7 × 7 kernel with a 3 × 3 kernel, adjusting the stride to 1, and setting padding to 1—to better capture fine-grained leaf textures and edge features. Subsequently, the optimal training strategy was determined through hyperparameter tuning experiments, and GrabCut-based background processing along with data augmentation were introduced to enhance model robustness. In addition, interpretability techniques such as channel masking and Grad-CAM were employed to visualize the model’s decision-making process. Experimental validation demonstrated that QY-SE-MResNet34 achieved an 89% classification accuracy, outperforming established models such as ResNet50, VGG16, and MobileNetV2 and surpassing the original ResNet34 by 11%. This study delivers a high-performance solution for single-leaf wheat powdery mildew severity assessment, offering practical value for intelligent disease monitoring and early warning systems in precision agriculture. Full article

Background and Objectives: Cerebral palsy (CP) is a non-progressive neurological disorder characterized by motor impairments such as spasticity and poor postural control. Among these, trunk control plays a critical role in maintaining balance and enabling functional mobility. Since spasticity is known to interfere with motor coordination and posture, evaluating its response to trunk-focused interventions may offer additional clinical insights. This systematic review and meta-analysis evaluated the effectiveness of trunk-focused interventions on trunk control, gross motor function, balance, and spasticity. Materials and Methods: A systematic search was conducted in PubMed, Embase, Web of Science, MEDLINE, and CINAHL for randomized controlled trials (RCTs) published in the last 10 years up to 11 April 2023. Studies targeting trunk-specific interventions in children with CP were included. Meta-analyses were performed using RevMan 5.3, calculating standardized mean differences (SMDs) with 95% confidence intervals (CIs). Study quality was assessed using the PEDro scale. Results: Fifteen RCTs involving 454 children were included. Trunk control improved significantly (SMD = 3.67; 95% CI: 3.10–4.25; I² = 0%). Gross motor function showed a small but significant improvement (SMD = 0.49; 95% CI: 0.06–0.92; I² = 44%). Balance exhibited a large, though not statistically significant, effect (SMD = 0.90; 95% CI: −0.00 to 1.79; I² = 81%). Subgroup analysis indicated that interventions performed more than four times per week produced a significant effect on balance (SMD = 0.54; 95% CI: 0.08–1.01). Only one study assessed spasticity and found no group difference. Conclusions: Trunk-based interventions significantly improve trunk control and gross motor function in children with CP. While improvements in balance were inconsistent, higher-frequency interventions yielded more favorable results. Further research is warranted to clarify effects on spasticity and optimize intervention protocols for clinical application. Full article

In vitro meat presents a promising alternative to conventional meat production by addressing environmental and animal welfare concerns. However, broader market adoption depends on increasing consumer acceptance. Labels on product packaging have been shown to be effective in influencing consumer behavior in previous studies. This paper examines the impact of different front-of-package labels on German consumers’ choices regarding in vitro chicken meat, with the goal of identifying effective labeling strategies. To investigate this, an online choice experiment was conducted with 200 participants from Germany. In addition to the label, products varied in terms of price, origin, and calorie content. The data were analyzed using latent class analysis, which identified four distinct consumer segments characterized by their preferences, attitudes, and personal characteristics. The results were used to simulate market scenarios, evaluating the effectiveness of different labeling strategies for in vitro chicken meat. These insights provide a foundation for targeted marketing approaches that promote consumer acceptance and inform the introduction of in vitro meat products in Germany. Full article

The palm-vein recognition system has garnered attention as a biometric technology due to its resilience to external environmental factors, protection of personal privacy, and low risk of external exposure. However, with recent advancements in deep learning-based generative models for image synthesis, the quality and sophistication of fake images have improved, leading to an increased security threat from counterfeit images. In particular, palm-vein images acquired through near-infrared illumination exhibit low resolution and blurred characteristics, making it even more challenging to detect fake images. Furthermore, spoof detection specifically targeting palm-vein images has not been studied in detail. To address these challenges, this study proposes the Fourier-gated feature-fusion network (FGFNet) as a novel spoof detector for palm-vein recognition systems. The proposed network integrates masked fast Fourier transform, a map-based gated feature fusion block, and a fast Fourier convolution (FFC) attention block with global contrastive loss to effectively detect distortion patterns caused by generative models. These components enable the efficient extraction of critical information required to determine the authenticity of palm-vein images. In addition, fractal dimension estimation (FDE) was employed for two purposes in this study. In the spoof attack procedure, FDE was used to evaluate how closely the generated fake images approximate the structural complexity of real palm-vein images, confirming that the generative model produced highly realistic spoof samples. In the spoof detection procedure, the FDE results further demonstrated that the proposed FGFNet effectively distinguishes between real and fake images, validating its capability to capture subtle structural differences induced by generative manipulation. To evaluate the spoof detection performance of FGFNet, experiments were conducted using real palm-vein images from two publicly available palm-vein datasets—VERA Spoofing PalmVein (VERA dataset) and PLUSVein-contactless (PLUS dataset)—as well as fake palm-vein images generated based on these datasets using a cycle-consistent generative adversarial network. The results showed that, based on the average classification error rate, FGFNet achieved 0.3% and 0.3% on the VERA and PLUS datasets, respectively, demonstrating superior performance compared to existing state-of-the-art spoof detection methods. Full article

The economic impact of health promotion and disease prevention interventions in ageing populations remains debated, as theories of morbidity compression and expansion offer contrasting views on the relationship between life expectancy and duration of morbidity. A MEDLINE search was conducted to identify studies evaluating the economic impact of health promotion or primary or secondary prevention interventions in OECD countries, over a lifetime time horizon. Among the 29 studies included, 16 reported cost-saving interventions (reducing costs while improving health outcomes), 11 reported cost-effective interventions (health gains at an acceptable additional cost based on an established threshold), and two presented cost-ineffective interventions (costs exceeding the threshold for the health benefits achieved). Interventions targeting diabetes and obesity prevention were cost-saving; cancer screening and fall prevention strategies were cost-effective; whereas interventions targeting rare diseases were cost-ineffective. Regulatory interventions were also cost-saving, while most programme-based interventions were cost-effective. Cost-saving or cost-effective interventions generally adopted broader analytical perspectives, while cost-ineffective ones employed narrower perspectives. The four studies that incorporated competing risks—despite using a narrower healthcare sector perspective—still found the interventions to be cost-saving or cost-effective interventions. None of the included studies assessed whether interventions led to morbidity compression or expansion. Only a few studies considered equity impact; those that did reported improved outcomes for disadvantaged groups, in regulatory and community-based interventions. Further research is needed to quantify morbidity outcomes and enhance methodological consistency, particularly with respect to analytical perspectives, the integration of competing risks, and the inclusion of equity analyses. Full article

Although it is more than a century since it was first marketed, acetaminophen remains one of the most popular analgesic agents. In addition, acetaminophen has recently been applied to multimodal analgesia in combination with non-steroidal anti-inflammatory drugs, and its consumption significantly increased during the pandemic of coronavirus disease 2019 as well as diclofenac and ibuprofen. However, the detailed mode of analgesic action of acetaminophen is still unclear. In the present study, we comprehensively discuss conventional, recognized, and postulated mechanisms of analgesic acetaminophen and highlight the current mechanistic concepts while comparing with diclofenac and ibuprofen. Acetaminophen inhibits cyclooxygenase with selectivity for cyclooxygenase-2, which is higher than that of ibuprofen but lower than that of diclofenac. In contrast to diclofenac and ibuprofen, however, anti-inflammatory effects of acetaminophen depend on the extracellular conditions of inflamed tissues. Since the discovery of cyclooxygenase-3 in the canine brain, acetaminophen had been hypothesized to inhibit such a cyclooxygenase-1 variant selectively. However, this hypothesis was abandoned because cyclooxygenase-3 was revealed not to be physiologically and clinically relevant to humans. Recent studies suggest that acetaminophen is deacetylated to 4-aminophenol in the liver and after crossing the blood–brain barrier, it is metabolically converted into N-(4-hydroxyphenyl)arachidonoylamide. This metabolite exhibits bioactivities by targeting transient receptor potential vanilloid 1 channel, cannabinoid receptor 1, Cav3.2 calcium channel, anandamide, and cyclooxygenase, mediating acetaminophen analgesia. These targets may be partly associated with diclofenac and ibuprofen. The perspective of acetaminophen as a prodrug will be crucial for a future strategy to develop analgesics with higher tolerability and activity. Full article

A primary objective of this research entails the development of an innovative algorithm capable of tracking a drone in real-time. This objective serves as a fundamental requirement across various applications, including collision avoidance, formation flying, and the interception of moving targets. Nonetheless, regardless of the efficacy of any detection algorithm, achieving 100% performance remains unattainable. Deep neural networks (DNNs) were employed to enhance this performance. To facilitate real-time operation, the DNN must be executed within a Deep Learning Processing Unit (DPU), Neural Processing Unit (NPU), Tensor Processing Unit (TPU), or Graphics Processing Unit (GPU) system on board the UAV. Given the constraints of these processing units, it may be necessary to quantify the DNN or utilize a less complex variant, resulting in an additional reduction in performance. However, precise target detection at each control step is imperative for effective flight path control. By integrating multiple algorithms, the developed system can effectively track UAVs with improved detection performance. Furthermore, this paper aims to establish a versatile Unmanned Aerial System (UAS) development platform constructed using open-source components and possessing the capability to adapt and evolve seamlessly throughout the development and post-production phases. Full article

Inflammatory bowel disease (IBD), encompassing Crohn’s disease and ulcerative colitis, is increasingly recognized as a systemic condition with cardiovascular implications. Among these, heart failure has emerged as a significant complication. The aim of this narrative review was to explore the cellular and molecular pathways that link IBD and heart failure. Drawing upon findings from epidemiologic studies, experimental models, and clinical research, we examined the pathways through which IBD may promote cardiac dysfunction. Chronic systemic inflammation in IBD, driven by cytokines such as TNF-α and IL-1β, can impair myocardial structure and function. Furthermore, intestinal barrier dysfunction and gut dysbiosis can facilitate the translocation of proinflammatory microbial metabolites, including lipopolysaccharide and phenylacetylglutamine, and deplete cardioprotective metabolites like short-chain fatty acids, thereby exacerbating heart failure risk. Additional contributing factors include endothelial and microvascular dysfunction, autonomic dysregulation, nutritional deficiencies, shared genetic susceptibility, and adverse pharmacologic effects. IBD contributes to heart failure pathogenesis through multifactorial and interrelated mechanisms. Recognizing the role of the gut–heart axis in IBD is crucial for the early identification of cardiovascular risk, providing guidance for integrating care and developing targeted therapies to reduce the risk of heart failure in this vulnerable population. Full article