Search Results (125)

This article presents a performance assessment of an electrical power and cooling system powered by a parabolic dish collector and using refrigerants with low global warming potential. The study was conducted using energy and mass balances for each component and system. The simulation includes various parameters, such as solar radiation, the focal temperature of the solar collector, the ambient temperature, the power cycle pressure ratio, and the chiller’s evaporation temperature. The results show that the efficiency of the organic Rankine cycle with the refrigerant R1233zd(E) is similar to that of the refrigerants R123 and R245fa and is up to 11 and 50 times lower than with R290 and R744, respectively. The solar absorption chiller using the refrigerant R717 can achieve cooling with a supply temperature up to 5 °C lower than that of R718. The dynamic simulation results show that the energy efficiency of the proposed solar-powered generator–chiller is 14% higher than that of a standard solar-powered absorption chiller. Furthermore, the same solar-powered generator–chiller reduces the primary energy required by a conventional system by 60% (PESr = 0.60). The presented results may be useful for the design of sustainable generator–chillers for rural areas or for autonomous housing in tropical climates. Full article

Dopamine (DA) plays an extremely crucial role in the metabolic processes of the human body. Accurate detection of DA is of great significance for many major diseases. This study reports an innovative synthesis method for composite material in which sulfur (S) and nitrogen (N) are incorporated into multi-walled carbon nanotubes (MWCNTs), and platinum (Pt) nanoparticle sensors (Pt/CNTs-N-S) are loaded for the highly sensitive and selective electrochemical detection of DA. The linear range of this sensor is from 0.0078 to 2 mM, and the limit of detection (LOD) is 0.73 μM (S/N = 3) for DA detection. The outstanding detection performance exhibited by Pt/CNTs-N-S is mainly attributed to the co-doping of N and S, which improves the surface properties of MWCNTs, and the dispersion of Pt nanoparticles (5.22 nm), which significantly increases the electrochemically active surface area (ESCA). In addition, the Pt/CNTs-N-S sensor also exhibits excellent stability and anti-interference performance. Overall, this study provides a simple and practical strategy for the potential application of Pt-based sensors in the detection of DA. Full article

Background: Esophageal squamous cell carcinoma (ESCC) is the predominant subtype of esophageal cancer, with poor outcomes following neoadjuvant chemoradiotherapy (NCRT). Neoadjuvant chemoimmunotherapy (NCIT) has emerged as a promising strategy, but reliable predictive biomarkers remain lacking. This study aimed to develop an AI-driven pathomic model for NCIT response prediction and explore its biological mechanisms. Methods: We analyzed 269 H&E-stained whole-slide images (WSIs) from 198 ESCC patients (104 from Tongji Hospital, 94 from TCGA). Using ResNet152, we segmented WSIs into four tissue categories (tumor cells, stroma, lymphocytes, and necrosis), extracted spatially weighted pathomic features, and constructed the ECiT score via logistic regression. An integrated model combining the ECiT score with clinical variables (T stage, P53 status) was developed. Mechanistic analyses were performed using TCGA-ESCA and GSE160269 datasets. Results: The integrated model achieved AUCs of 0.897 (training) and 0.809 (temporal validation), outperforming clinical (AUC = 0.624) and pathomic-only (AUC = 0.751) models. Mechanistically, a high ECiT score correlated with enhanced immune activation (elevated CD4⁺ memory T cell infiltration), while low scores were linked to endoplasmic reticulum (ER) stress-unfolded protein response (UPR) activation. EIF2S3 was identified as a key molecular mediator, correlating with three pathomic features, UPR activation, and poor prognosis. Conclusions: This study may offer a preliminary indicator that could assist in personalized clinical decision-making. Correlative evidence suggests that the EIF2S3-mediated ER stress–UPR axis represents a potential candidate therapeutic target to overcome NCIT resistance, generating testable hypotheses to advance precision oncology for resectable locally advanced ESCC. Full article

Esca disease, the most widespread grapevine trunk disease in Europe, is characterized by both chronic and acute forms. In both cases, alterations in the plant’s physiological processes are significant and lead to yield losses and/or plant death. Studies have highlighted the effects of a mixture of foliar fertilizers and seaweeds in reducing foliar symptoms and improving both the quantity and quality of yield. These effects have now been evaluated on additional cultivars and in other vineyard areas. Furthermore, for the first time, the activity of the fertilizer mixture in reducing apoplexy and the resulting vine mortality has been assessed. During the 2022–2023 biennium, in four vineyards of the Lambrusco cultivar in the Province of Reggio Emilia, Northern Italy, affected by both chronic and acute forms of the disease, foliar applications of the mixture were carried out at 10-day intervals starting from the “nine leaves unfolded” BBCH (Biologische Bundesanstalt, Bundessortenamt and Chemical industry) stage 19 up to the “berries developing color” BBCH stage 83. The results confirmed the activity of the fertilizer mixture in reducing chronic symptoms, which appeared particularly pronounced in 2022, when rainfall quantity and distribution allowed regular development of phenological stages. In that year, in all vineyards, a reduction of approximately 50% and 60% in the incidence and severity of chronic leaf symptoms was recorded. Under these optimal growth conditions, treated vines generally showed superior yield and quality. Conversely, in 2023, characterized by heavy rains, smaller effects on foliar symptoms and no improvements in yield were observed. Applications of the mixture resulted in a significant reduction in apoplexy and, consequently, vine mortality, as verified in 2024. This effect did not appear to be influenced by climatic conditions. This study confirms that applications of the mixture aimed at reducing symptom expression and yield damage are a valid addition to the few available control practices. The positive effects observed on the acute form for the first time require further investigation. Full article

In response to recent policies on sustainable finance, nature restoration, soil protection, and biodiversity conservation, it is increasingly important for projects to assess their impacts on natural capital to safeguard Ecosystem Services (ES). Nature-Based Solutions (NBSs) are recognized as strategic tools for fostering cost-effective, nature- and people-centered development. Yet, standard economic and financial assessment methods often fall short, as many ES lack market prices. Indirect, ecosystem-based approaches—such as ES monetization and environmental cost accounting—are therefore critical. This study evaluates the feasibility of investing in NBSs by estimating their economic and financial value through indirect ES valuation. An empirical methodology is applied to quantify environmental costs relative to ES delivery, using Willingness to Pay (WTP) as a proxy for the economic relevance of NBSs. The proposed ES-Cost Accounting (ES-CA) framework was implemented across major NBS categories in Europe. Results reveal that the scale of NBS implementation significantly influences both unit environmental costs and ES provision: larger interventions tend to be more cost-efficient and generate broader benefits, whereas smaller solutions are more expensive per unit but provide more localized or specialized services. The findings offer practical guidance for robust cost–benefit analyses and support investment planning in sustainable climate adaptation and mitigation from an ES perspective. Full article

Financial inclusion should be shared with university students so that they link access to and use of financial products and services to low costs, without discrimination or inequality, to achieve the Sustainable Development Goals. This study aims to map the literature on the relationship between financial inclusion and undergraduate students within a contextual approach. The mapping was conducted through a scoping review, utilizing keyword pairwise searches, which we referred to as contextual constellations, as an emergent method. The search was conducted on the Web of Science and Scopus databases. The range of publications found ranges from 1973 to July 2024. The contextual analysis considered the following keywords: financial inclusion, undergraduate students, financial literacy, financial well-being, experiment, behavior, sustainable development goals, social and solidarity economy, decision, and innovation. The relationships were analyzed using VOSviewer software, version 1.6.20. The findings found the main articles that have contributed to knowledge about the relationship between financial inclusion and undergraduate students from the proposed context. Therefore, the research gaps in the relationship between financial inclusion and undergraduate students were identified. This research also offers the potential to conduct a mapping from a contextual perspective, identifying strong and weak relationships between research topics and keywords of interest. Full article

Background/Objectives: Hypoxia promotes esophageal adenocarcinoma (EAC) aggressiveness through stabilization of hypoxia-inducible factor-1α (HIF-1α), which regulates pro-survival, pro-metastatic, and immunosuppressive pathways, including the ectoenzyme CD73 (NT5E). Although CD73 is a known hypoxia-responsive gene, its functional integration with HIF-1α signaling in EAC remains incompletely understood. This study aimed to define the relationship between HIF-1α and CD73 in EAC and to evaluate the therapeutic potential of their combined inhibition. Methods: Gene expression and survival analyses were performed using CCLE and TCGA-ESCA datasets. CD73 and HIF-1α expression were evaluated in EAC patient tissues by immunohistochemistry. EAC cell lines were subjected to hypoxic conditions with genetic or pharmacologic inhibition of HIF-1α and/or CD73. Cell viability, migration, angiogenesis, VEGF secretion, and purinergic metabolite levels were assessed using luminescence assays, Boyden chamber migration assays, endothelial tube formation assays, ELISA, and targeted LC-MS/MS, respectively. Results: NT5E expression was transcriptionally upregulated by HIF-1α under hypoxia and correlated with advanced disease stage and poor overall survival in EAC patients. While CD73 inhibition alone modestly reduced EAC cell viability, combined inhibition of HIF-1α and CD73 synergistically decreased tumor cell survival, particularly under hypoxic conditions, and significantly altered extracellular adenosine metabolism. Dual targeting further suppressed migration, reduced VEGF secretion, and impaired angiogenic signaling, indicating disruption of tumor microenvironmental pathways critical for metastasis and immune evasion. Conclusions: These findings identify CD73 as a direct hypoxia-responsive effector of HIF-1α in EAC and demonstrate that dual inhibition of HIF-1α and CD73 synergistically disrupts tumor cell survival and pro-metastatic signaling. This combinatorial strategy represents a mechanistically integrated therapeutic approach to overcome hypoxia-driven resistance in esophageal adenocarcinoma. Full article

This study analyzed the microbiome of three varieties differing in genotype and technical purpose: Cristal, Riesling, and Avgustin, all exhibiting decline symptoms of unknown etiology. A total of 92 symptomatic and asymptomatic grapevines were analyzed using ITS and 16S rRNA amplicon sequencing and molecular genetic methods. Phytoplasmas and the pathogenic bacteria Xylella fastidiosa and Xylophilus ampelinus were not present in the samples. The decline symptoms were associated with a cocktail of fungal pathogens that cause grapevine trunk diseases. In particular, the analysis revealed the causative agents of Botryosphaeria dieback (Sphaeropsis spp. and Botryosphaeria spp.), fungi associated with the Esca complex (Phaeomoniella spp., Phaeoacremonium spp., Inonotus spp., Seimatosporium spp., Stereum spp., and Cadophora spp.), and the causative agents of Phomopsis dieback (Diaporthe spp.). The symptoms of decline may be increased by several facultative grapevine pathogens that have been identified in microbiome (genera Stemphylium, Alternaria, Aspergillus, Penicillium, Talaromyces, and Fusarium). The metagenomic data of the grapevine microbiome provides opportunities for developing disease control strategies, which is important for the sustainable management of vineyards. Full article

The purpose of this work was to study water-soluble platinum complexes as potential therapeutic agents. We used water-soluble platinum(II) complexes containing sulfonated N-heterocyclic carbene ligands (NHC), applied on two human cell models: human NB4 acute promyelocytic leukemia and PC3 prostatic cancer cells. We studied the toxic effects on these two types of human tumor cells. We analyzed metabolic activity, membrane damage, cell cycle, DNA fragmentation and programmed cell death. In human NB4 leukemia cells, the water-soluble dimethyl NHC complex 5Me proved highly toxic. It extinguished cell metabolism at 1 mM for 24 h. This treatment gave rise to the presence of fragmented DNA (subdiploid DNA). This compound promoted programed cell death in 60% of the cells. At longer times, the treatments produced neither higher fragmentation of DNA nor augmented apoptosis. 5Me complex, at 100 µM, showed slight toxicity on NB4 cells. In PC3 cells, dimethyl complex 5Me (1 mM for 24 h) is less toxic (reduced DNA fragmentation and programmed cell death) than in NB4 cells. Mono-NHC complexes 4 and 5 treatments at a high concentration for 24 h on PC3 cells produced apoptosis (30% of the cells) but their damage on cell permeability and DNA fragmentation was weak. Thus, PC3 cells are more resistant to NHC platinum(II) complexes than NB4 cells. Full article

Immunogenic cell death (ICD) is a specialized form of cell death that triggers antitumor immune responses. In tumors, ICD promotes the release of tumor-associated and tumor-specific antigens, thereby reshaping the immune microenvironment, restoring antitumor immunity, and facilitating tumor eradication. However, the regulatory mechanisms of ICD and its immunological effects vary across tumor types, and a comprehensive understanding remains limited. We systematically analyzed the expression of 34 ICD-related regulatory genes across 33 tumor types. Differential expression at the RNA, copy number variation (CNV), and DNA methylation levels was assessed in relation to clinical features. Associations between patient survival and RNA expression, CNVs, single-nucleotide variations (SNVs), and methylation were evaluated. Patients were stratified into immunological subtypes and further divided into high- and low-risk groups based on optimal prognostic models built using a machine learning framework. We explored the relationships between ICD-related genes and immune cell infiltration, stemness, heterogeneity, immune scores, immune checkpoint and regulatory genes, and subtype-specific expression patterns. Moreover, we examined the influence of immunotherapy and anticancer immune responses, applied three machine learning algorithms to identify prognostic biomarkers, and performed drug prediction and molecular docking analyses to nominate therapeutic targets. ICD-related genes were predominantly overexpressed in ESCA, GBM, KIRC, LGG, PAAD, and STAD. RNA expression of most ICD-related genes was associated with poor prognosis, while DNA methylation of these genes showed significant survival correlations in LGG and UVM. Prognostic models were successfully established for 18 cancer types, revealing intrinsic immune regulatory mechanisms of ICD-related genes. Machine learning identified several key prognostic biomarkers across cancers, among which NT5E emerged as a predictive biomarker in head and neck squamous cell carcinoma (HNSC), mediating tumor–immune interactions through multiple ligand–receptor pairs. This study provides a comprehensive view of ICD-related genes across cancers, identifies NT5E as a potential biomarker in HNSC, and highlights novel targets for predicting immunotherapy response and improving clinical outcomes in cancer patients. Full article

Microbial communities within human tissues are increasingly recognized as promising biomarkers for cancer detection. However, leveraging microbiome data for multiclass cancer classification remains challenging due to its compositional structure, high dimensionality, and lack of model interpretability. In this study, we address these challenges by introducing MicroAIbiome, a machine learning-based artificial intelligence (AI) pipeline designed to classify five cancer types such as esophageal carcinoma (ESCA), head and neck squamous cell carcinoma (HNSC), stomach adenocarcinoma (STAD), colon adenocarcinoma (COAD), and rectum adenocarcinoma (READ), using genus-level microbial relative abundances. Our pipeline incorporates zero-replacement, centered log-ratio (CLR) transformation, correlation filtering, and recursive feature elimination (RFE) to enable robust learning from compositional data. Among five evaluated classifiers, XGBoost achieved the highest accuracy of 78.23%, outperforming prior work. We further enhance interpretability using SHapley Additive exPlanations (SHAP)-based feature attribution to uncover class-specific microbial signatures, such as Corynebacterium in ESCA and Bacteroides in COAD. Our results highlight the importance of compositional preprocessing and explainable AI in advancing microbiome-based cancer diagnostics. Full article

Background/Objectives: This study aimed to evaluate the efficacy of a 445 nm diode laser in enhancing enamel resistance to acid-induced demineralization and to investigate the associated compositional and structural modifications using scanning electron microscopy (SEM), electron spectroscopy for chemical analysis (ESCA), and X-ray diffraction (XRD) crystallographic analysis. Methods: A total of 126 extracted human teeth were used. A total of 135 (n = 135) enamel discs (4 × 4 mm) from 90 teeth were assigned to either a laser-irradiated group or an untreated control group for SEM, ESCA, and XRD analyses. Additionally, 24 mono-rooted teeth were used to measure pulp temperature changes during laser application. Laser irradiation was performed using a 445 nm diode laser with a pulse width of 200 ms, a repetition rate of 1 Hz, power of 1.25 W, an energy density of 800 J/cm², a power density of 3980 W/cm², and a 200 µm activated fiber. Following acid etching, SEM was conducted to assess microstructural and ionic alterations. The ESCA was used to evaluate the Ca/P ratio, and XRD analyses were performed on enamel powders to determine changes in phase composition and crystal lattice parameters. Results: The laser protocol demonstrated thermal safety, with minimal pulp chamber temperature elevation (0.05667 ± 0.04131 °C). SEM showed that laser-treated enamel had a smoother surface morphology and reduced acid-induced erosion compared with controls. Results of the ESCA revealed no significant difference in the Ca/P ratio between groups. XRD confirmed the presence of hydroxyapatite structure in laser-treated enamel and detected an additional diffraction peak corresponding to a pyrophosphate phase, potentially enhancing acid resistance. Results of the spectral analysis showed the absence of α-TCP and β-TCP phases and a reduction in the carbonate content in the laser group. Furthermore, a significant decrease in the a-axis lattice parameter suggested lattice compaction in laser-treated enamel. Conclusions: Irradiation with a 445 nm diode laser effectively enhances enamel resistance to acid demineralization. This improvement may be attributed to chemical modifications, particularly pyrophosphate phase formation, and structural changes including prism-less enamel formation, surface fusion, and decreased permeability. These findings provide novel insights into the mechanisms of laser-induced enhancement of acid resistance in enamel. Full article

The development of reliable visual inference models is often constrained by the burdensome and time-consuming processes involved in collecting and annotating high-quality datasets. This challenge becomes more acute in domains where key phenomena are time-dependent or event-driven, narrowing the opportunity window to capture representative observations. Yet, accelerating the deployment of deep learning (DL) models is crucial to support timely, data-driven decision-making in operational settings. To tackle such an issue, this paper explores the use of 2D synthetic data grounded in real-world patterns to train initial DL models in contexts where annotated datasets are scarce or can only be acquired within restrictive time windows. Two complementary approaches to synthetic data generation are investigated: rule-based digital image processing and advanced text-to-image generative diffusion models. These methods can operate independently or be combined to enhance flexibility and coverage. A proof-of-concept is presented through a couple case studies in precision viticulture, a domain often constrained by seasonal dependencies and environmental variability. Specifically, the detection of Lobesia botrana in sticky traps and the classification of grapevine foliar symptoms associated with black rot, ESCA, and leaf blight are addressed. The results suggest that the proposed approach potentially accelerates the deployment of preliminary DL models by comprehensively automating the production of context-aware datasets roughly inspired by specific challenge-driven operational settings, thereby mitigating the need for time-consuming and labor-intensive processes, from image acquisition to annotation. Although models trained on such synthetic datasets require further refinement—for example, through active learning—the approach offers a scalable and functional solution that reduces human involvement, even in scenarios of data scarcity, and supports the effective transition of laboratory-developed AI to real-world deployment environments. Full article

Background: Esophageal cancer (EC), including esophageal adenocarcinoma (EAC) and esophageal squamous cell carcinoma (ESCC), remains a lethal malignancy with limited molecularly tailored treatment options. Due to substantial histologic and transcriptomic differences between subtypes, therapeutic responses often vary, underscoring the need for subtype-stratified analysis and precision drug discovery. Methods: We integrated transcriptomic data from GEO and TCGA to identify differentially expressed genes (DEGs) specific to EAC, ESCC, and their shared profiles. Functional enrichment (GO, KEGG) and protein–protein interaction (PPI) network analyses were conducted to extract hub genes using DAVID, STRING, and Cytoscape. Survival associations were evaluated using TCGA-ESCA and UALCAN. Drug repurposing was performed using L1000FWD, L1000CDS2, and SigCom LINCS. Results: We identified 79, 59, and 17 hub genes in the DEG-EAC, DEG-ESCC, and DEG-EAC&ESCC datasets, respectively. In EAC, 16 novel hub genes including SCARB1, SERPINH1, and DSC2 were discovered, which had not been previously implicated in this subtype. These genes were significantly enriched in pathways related to extracellular matrix (ECM) remodeling and epithelial structure. In addition, shared hub genes across EAC and ESCC—such as COL1A1, SPARC, and MMP1—were enriched in ECM organization and cell adhesion processes, highlighting convergent tumor–stroma interactions. Drug repositioning analysis consistently prioritized MEK inhibitors, trametinib and selumetinib, as potential therapeutic candidates across all DEG datasets. Conclusions: This study presents a comprehensive, subtype-stratified transcriptomic framework for EC, identifying both unique and shared hub genes with potential functional relevance to ECM dynamics. Our findings suggest that ECM remodelers may serve as therapeutic targets, and highlight MEK inhibition as a promising, yet exploratory, repurposing strategy. While these results offer a molecular foundation for future precision oncology efforts in EC, further validation through proteomic analysis, functional studies, and clinical evaluation is warranted. Full article

In this work, we show the probability density functions (PDFs) and cumulative density functions (CDFs) of the nonnormalized field components and the associated powers received inside coupled reverberation chambers (CRCs), considering two canonical cases of single electrically small coupling apertures (ESCAs). These two cases involve one-dimensional (1D) and two-dimensional (2D) single electrically small CAs, respectively. We achieve normalized statistics from the nonnormalized ones for both field components and associated powers. We show that the comparison of the mean square values (MSVs) of the nonnormalized PDFs of the field components to the mean values (MVs) of the related nonnormalized PDFs of the powers is a proper method to corroborate the accuracy of the same achieved theoretical distributions, when they are achieved in an independent way. The achieved theoretical results are also validated by measurements. Moreover, for the sake of completeness and rigor of published results, we show two useful cases of the results from the measurements using two electrically large CAs. Full article