Search Results (104)

Myocardial infarction (MI) remains one of the most common cardiovascular diseases and a leading cause of morbidity and mortality worldwide. In recent years, natural polymeric patches have attracted increasing attention as a promising therapeutic platform for myocardial tissue repair. This study explored the fabrication and evaluation of screen-printed electrodes (SPEs) on chitosan film as a novel platform for cardiac patch applications. Chitosan is a biodegradable and biocompatible natural polymer that provides an ideal substrate for SPEs, providing mechanical stability and promoting cell adhesion. Silver ink was employed to enhance electrochemical performance, and the electrodes exhibited strong adhesion and structural integrity under wet conditions. Mechanical testing and swelling ratio analysis were conducted to assess the patch’s physical robustness and aqueous stability. Silver ink was employed to enhance electrochemical performance, which was evaluated using cyclic voltammetry. In vitro, electrical stimulation through the chitosan–SPE patch significantly increased the expression of cardiac-specific genes (GATA-4, β-MHC, troponin I) in bone marrow mesenchymal stem cells (BMSCs), indicating early cardiogenic differentiation potential. In vivo, the implantation of the chitosan–SPE patch in a rat MI model demonstrated good tissue integration, preserved myocardial structure, and enhanced ventricular wall thickness, indicating that the patch has the potential to serve as a functional cardiac scaffold. These findings support the feasibility of screen-printed electrodes fabricated on chitosan film substrates as a cost-effective and scalable platform for cardiac repair, offering a foundation for future applications in cardiac tissue engineering. Full article

This study proposes an optimized approach to address the high computational demands and significant GPU memory consumption commonly associated with Transformer-based models. Building upon the HAT framework, a shallow feature extraction module is enhanced to improve local feature representation, thereby achieving a better balance between computational efficiency and model performance. Furthermore, inspired by self-supervised learning (SSL) techniques and incorporating shift operations, the proposed method effectively reduces both the number of parameters and the overall computational load. The resulting ISR-SHA model is trained and evaluated on the DF2K dataset, achieving approximately a 30% reduction in FLOPs and parameter count compared to the original HAT model, with only marginal declines in PSNR (0.02) and SSIM (0.0006). Experimental results confirm that ISR-SHA outperforms most existing super-resolution models in terms of performance while significantly enhancing computational efficiency without compromising output quality. Full article

Secreted Frizzled-related protein 4 (SFRP4) has been identified as a patient-level biomarker of the stem-like subtype of gastric cancer (GC), which is associated with poor prognosis and resistance to chemotherapy. Although multiple studies have documented the clinical significance of SFRP4 in GC, its mechanistic role in the stem-like subtype remains incompletely understood. In this study, we elucidate how phosphorylation of SFRP4 by protein kinase A (PKA) converts it into a Wnt signaling agonist. We began with a phosphoproteomic database search to identify candidate kinases that phosphorylate SFRP4. Co-immunoprecipitation assays revealed a direct interaction between PKA and SFRP4, and in vitro kinase assays confirmed that PKA phosphorylates SFRP4 at key threonine residues. Phosphorylated SFRP4 then associates with β-catenin, augmenting Wnt-driven transcriptional activity. Importantly, pharmacological inhibition of PKA significantly reduced SFRP4 phosphorylation and suppressed stemness-associated phenotypes, such as sphere formation, migratory capacity, and chemoresistance, in gastric cancer cells. Collectively, our data demonstrate that PKA-mediated phosphorylation of SFRP4 enhances cancer stemness-related properties in GC through Wnt signaling. Furthermore, these results highlight the PKA–SFRP4 axis as a promising therapeutic target in the stem-like subtype of GC. Full article

The food-induced viscosity of the media can alter tablet disintegration and eventually the release of the drug it contains. The extent of this retardation depends on tablet formulation factors, such as the solubility of its excipients. Objectives: This research aimed to study the effect of filler solubility on the disintegration and dissolution of tablets under different testing conditions. Methods: Tablet formulations containing acetaminophen (as a model compound), mixtures of different ratios of fillers, and other excipients were directly compressed using uniform manufacturing parameters. These formulations were investigated under fasted- and fed-state conditions to determine the influence of viscosity on their disintegration, inspired by the liquid penetration ratio (LPR) theoretical framework. Disintegration and dissolution tests were performed using both compendial and novel testing apparatuses. Results: The soluble fillers in the tablets affected their disintegration and dissolution in the simulated fed-state medium, while fasted-state conditions affected the tablets only marginally. The testing devices showed partially contrasting results, which appeared to be due to the hydrodynamics of the testing media used. The novel CNC (computed numerical control) apparatus offered 3D motion and effectively exposed the tablets to the viscous testing media, unlike the compendial paddle apparatus. Conclusions: This study explored the impact of filler solubility on the disintegration and dissolution of tablets. As the LPR framework revealed, fillers with a higher solubility have positive effects on the disintegration and dissolution of tablets in viscous conditions. Additionally, the proportion of soluble filler used is also inversely correlated with the disintegration time. Further investigation of the formulation parameters, as well as the testing conditions, would provide additional insights into the effects of food on these tablets. Full article

The exposome represents the totality of endogenous and exogenous exposures across the lifespan. These exposures may result in DNA and RNA damage, in the form of adducts, which is a key factor in the etiology of a variety of human diseases, including cancer. It is understood that, following their repair, nucleic acid adducts are excreted into the urine, making urine an ideal, non-invasive matrix in which to study the whole-body nucleic acid adductome (the totality of nucleic acid adducts). However, the measurement of these adducts in urine presents challenges due to matrix interference and the variety of the chemical nature across the spectrum of nucleic adducts making their “one-size-fits-all” extraction by solid-phase extraction (SPE) challenging. Here, different types of SPE sorbents, and their combination, were evaluated for maximal recovery of nucleic acid adducts from urine. The SPE column combination of ENV+ coupled with PHE provided the best retention of a cocktail of 20 nucleic acid adduct standards. An untargeted high resolution mass spectrometry approach incorporating FeatureHunter 1.3 software was used to demonstrate the ability of this SPE method to successfully recover endogenous urinary nucleic acid adducts in addition to those represented by the cocktail of isotopically labeled standards. Using our approach, FeatureHunter 1.3 recognized approximately 500 adducts in both mouse and human urine samples. Isotopically labeled standards were used to identify a selection of the endogenous adducts and begin the characterization of the urinary nucleic acid adductome of mice and humans. Full article

Traumatic or degenerative defects of articular cartilage impair joint function, and the treatment of articular cartilage damage remains a challenge. By mimicking the cartilage extracellular matrix (ECM), exosome-seeded cryogels may enhance cell proliferation and chondral repair. ECM-based cryogels were cryopolymerized with gelatin, chondroitin sulfate, and various concentrations (0%, 0.3%, 0.5%, and 1%) of hyaluronic acid (HA), and their water content, swelling ratio, porosity, mechanical properties, and effects on cell viability were evaluated. The regenerative effects of bone marrow-derived mesenchymal stem cell (BM-MSC)-derived exosome (at a concentration of 10⁶ particles/mL)-seeded 0.3% HA cryogels were assessed in vitro and in surgically induced male New Zealand rabbit cartilage defects in vivo. The water content, swelling ratio, and porosity of the cryogels significantly (p < 0.05) increased and the Young’s modulus values of the cryogels decreased with increasing HA concentrations. MTT assays revealed that the developed biomaterials had no cytotoxic effects. The optimal cryogel composition was 0.3% HA, and the resulting cryogel had favorable properties and suitable mechanical strength. Exosomes alone and exosome-seeded cryogels promoted chondrocyte proliferation (with cell optical densities that were 58% and 51% greater than that of the control). The cryogel alone and the exosome-seeded cryogel facilitated ECM deposition and sulfated glycosaminoglycan synthesis. Although we observed cartilage repair via Alcian blue staining with both the cryogel alone and the exosome-seeded cryogel, the layered arrangement of the chondrocytes was superior to that of the control chondrocytes when exosome-seeded cryogels were used. This study revealed the potential value of using BM-MSC-derived exosome-seeded ECM-based cryogels for cartilage tissue engineering to treat cartilage injury. Full article

Purpose: We aimed to identify the impact of conversion surgery to survival in patients with stage IV esophageal cancer who have a stabilized disease and good treatment response before surgery. Patients and Methods: This retrospective study included patients with esophageal cancer M1 disease treated at a tertiary medical center from April 2002 to June 2021. For patients with a good clinical response to chemoradiation and well-controlled metastatic lesions, esophagectomy and lymphadenectomy were performed. A propensity score-matching (PSM) study with a 1:2 ratio and based on patient age, tumor stage, and metastasis status was conducted for verifying the results. Results: We enrolled 162 patients, including 124 treated with concurrent chemoradiation therapy (CCRT) alone and 38 treated with CCRT followed by esophagectomy. A total of 114 patients were analyzed using PSM, including 76 patients treated with CCRT alone and 38 patients treated with CCRT and surgery. The 3- and 5-year OS was 24.6% vs. 2.8% and 12.3% vs. 1.4% (p = 0.006), and PSM was 24.6% vs. 4.6% and 12.3% vs. 2.3% (p = 0.033) for those with or without esophagectomy, respectively. Multivariate analysis revealed surgery with esophagectomy as an independent prognostic factor for OS with odd ratios (95% confidence interval [CI]) of 1.91 (1.23–2.95) (p = 0.004). Conclusions: Surgical resection following CCRT holds a potential survival benefit for the patients with a favorable response to CCRT for patients with stage IV esophageal cancer. Full article

Natural language processing (NLP) has numerous applications and has been extensively developed in deep learning. In recent years, language models such as Transformer, BERT, and GPT have frequently been the foundation for related research. However, relatively few studies have focused on evaluating the quality of generated sentences. While traditional evaluation methods like BLEU can be applied, the challenge is that there is no ground truth reference for generated sentences, making it difficult to establish a reliable evaluation criterion. Therefore, this study examines the content generated by Bidirectional Encoder Representations and related recurrent methods based on the Transformer model. Specifically, we focus on analyzing sentence fluency by assessing the degree of part-of-speech (PoS) matching and the coherence of PoS context ordering. Determining whether the generated sentences align with the expected PoS structure of the model is crucial, as it significantly impacts the readability of the generated text. Full article

This study focuses on fabricating flexible multi-junction diodes using carbon nanotubes (CNTs) as the base material, employing doping engineering and recrystallization-driven thermal diffusion techniques to enhance optoelectronic and thermoelectric properties. N-type CNTs are synthesized through ammonia doping and combined with intrinsic P-type CNTs to create PN multi-junction “buckypaper”. Post-diffusion processes improve junction crystallinity and doping gradients, significantly boosting the rectification ratio and optoelectronic and thermoelectric response. The device follows the superposition principle, achieving notable increases in thermoelectric and photovoltaic outputs, with the Seebeck coefficient rising from 5.7 μV/K to 24.4 μV/K. This study underscores the potential of flexible carbon-based devices for energy harvesting applications and advancing optoelectronic and thermoelectric systems. Full article

The South American tomato pinworm, Tuta absoluta (Meyrick), is one of the major invasive pests that causes severe economic damage to several hosts, especially tomato plants, globally. Spinosad, a biopesticide widely used against several insect pests, also shows promising results against T. absoluta. Here, we investigated the evolution of spinosad resistance and its effects on biological traits and related gene effects to fully understand the relationship between resistance degree and associated fitness costs. The spinosad-resistant strain (SpRS) with a moderate level of resistance (14.40-fold) was developed following continuous selection of the susceptible strain (SS) against spinosad for eight generations. Fitness analysis showed that the larval and pupal developmental durations were significantly increased, while the adult emergence was substantially reduced in the SpRS compared to SS. Adult longevity (male and female), fecundity, and hatching rates significantly decreased in the SpRS T. absoluta compared to SS. Additionally, the gene expression analyses indicated the down-regulation of development and reproduction-related genes (Vg, VgR, JHBP, JHAMT, JHE, and JHDK) in the SpRS population. Further, the mRNA expression level of the resistance-related cytochrome P450 gene CYP321C40, followed by CYP4M116, CYP6AW1, CYP339A1, and CYP6AB327, were significantly increased in the SpRS T. absoluta. Taken together, these results indicated that although T. absoluta developed a moderate level of spinosad resistance accompanied by fitness costs, continuous and indiscriminate use might elevate the resistance level. Overall, these findings provide important information about the trade-off between resistance degree and fitness cost that might be crucial to designing resistance management strategies against this key invasive herbivore. Full article

Freeway incidents block road lanes and result in increasing travel time delays. The intense lane changes of upstream vehicles may also lead to capacity drop and more congestion. Connected vehicles (CVs) offer a viable solution to minimize the impact of such incidents via monitoring the status of the incidents and providing real-time driving guidance. This paper evaluates the performance of an existing CV-enabled incident management system, which minimizes travel time by effectively leading CVs to bypass incident spots. This study comprehensively quantifies the effects of system parameters (speed weight and lane-changing inertia), control segment length, and road information-updating intervals. This analysis identifies the optimal settings for the incident management system to minimize vehicle travel time delays. Additionally, this paper evaluates the influence of CV market penetration rates (MPRs), network volume-to-capacity ratios, and incident settings to understand the system benefits under varying connected environments and traffic conditions. The results reveal that with the control of the proposed system, overall travel delays can be reduced by up to 45% and that road congestion caused by incidents can be mitigated quickly. Full article

Botryocladia leptopoda is a red macroalga known for its bioactive compounds with antioxidant, anti-inflammatory, and skin-regenerative properties. The study aimed to examine their effects on UV protection, collagen synthesis, fibroblast proliferation, and pigmentation modulation. Bioactive compounds were extracted using two solvents, producing ethanol extract (FE) and alkaline extracts (AE). Methods involved characterizing extracts using mass spectrometry and assessing their effects on human fibroblasts under UVB-induced damage. UV absorbance, ROS production, and collagen synthesis were evaluated. The FE extract, which comprised 4-hydroxyquinoline, phytosphingosine, and docosapentaenoic acid, reinstated procollagen type I synthesis to 113% of baseline levels and reduced TGF-β1-mediated fibroblast proliferation to 87.78%. FE also suppressed Smad2 and α-SMA by 71% and 68%, respectively, indicating modulation of fibrosis-associated pathways. AE, containing 4-hydroxyquinoline and phenylalanine betaine, demonstrated dose-responsive cellular repair, reducing fibroblast proliferation to 97.86% and collagen Type I expression by 73% at 1000 μg/mL. Both extracts decreased ROS production, with FE and AE reducing levels by 21.4% and 19.7%, respectively, under UVB-induced oxidative stress. FE showed superior scar inhibition, while AE excelled in skin regeneration and pigmentation management. Full article

Flood disasters often result in significant losses of life and property, making them among the most devastating natural hazards. Therefore, reliable and accurate water level forecasting is critically important. Rainfall-runoff modeling, which is a complex and nonlinear time series process, plays a key role in this endeavor. Numerous studies have demonstrated that data-driven methods, particularly deep learning approaches such as convolutional neural networks (CNNs), long short-term memory (LSTM) networks, and transformers, have shown promising performance in water level prediction tasks. This study introduces the Conformer, a novel deep learning architecture that integrates the strengths of CNNs and transformers for rainfall-runoff modeling. The framework uses self-attention mechanisms combined with convolutional computations to extract essential features—such as water levels, precipitation, and meteorological data—from multiple stations, which are then aggregated to predict subsequent water level series. This study utilized data spanning from 1 April 2006 to 25 July 2021, totaling 5595 days (134,280 h), which were divided into training, validation, and test sets in an 8:1:1 ratio to train the model, adjust parameters, and evaluate performance, respectively. The effectiveness and feasibility of the proposed model are evaluated in the Lanyang River Basin, with a focus on predicting 7-day-ahead water levels. The results obtained from ablation experiments indicate that convolutional computations significantly enhance the ability of the model to capture the local relationships between water levels and other parameters. Additionally, performing convolution computations after executing self-attention operations yields even better results. Compared with other models in simulations, the Conformer model markedly outperforms the CNN, LSTM, and traditional transformer models in terms of the coefficient of determination (R²) and Nash–Sutcliffe efficiency (NSE) indicators. These findings highlight the potential of the Conformer model to replace the commonly used deep learning methods in the field of hydrology. Full article

Steam stripping of ammonia from ammonia-rich wastewater (5000–20,000 mg/L) was conducted in a continuous-flow rotating packed bed (RPB) at a pH of 11. This study aimed to elucidate the influence of key operational parameters, including the steam-to-liquid ratio, rotational speed (ω), initial ammonia concentration, steam inlet temperature (T_Si), and liquid inlet temperature (T_Li), on critical performance metrics such as the ammonia removal efficiency (ARE), the volumetric liquid mass transfer coefficient (K_La), and the concentration of the recovered ammonia solution (C_R). The findings revealed that a C_R of 22.88 wt.% was achieved under the optimal conditions of a steam-to-liquid ratio of 0.175 kg/kg, an initial concentration of 20,000 mg/L, a T_Si of 120 °C, and a T_Li of 70 °C. Key experimental factors, including the initial ammonia concentration, T_Si, and T_Li, significantly impacted the achievement of higher ARE and C_R values. The K_La values exhibited a decrease with the increase in the steam-to-liquid ratio, while they increased with ω. However, the K_La remained relatively consistent with ω values within the range of 600 to 1200 rpm. In comparison with prior studies, steam stripping of ammonia exhibits a higher ARE than air stripping with RPB and a higher C_R than conventional stripping methods. Moreover, RPB requires a smaller size to achieve equivalent ARE compared to conventional stripping apparatuses. Thus, the steam stripping process with RPB equipment emerges as a suitable method for ammonia recovery from ammonia-rich wastewater. Full article