Search Results (556)

Endometriosis is a disease characterized by the presence of endometrial glands and stroma outside of the uterine corpus, often clinically presenting with pain and/or infertility. Ectopic lesions exhibit features characteristic of epithelial-to-mesenchymal transition (EMT), a process in which epithelial cells lose polarity and acquire mesenchymal traits, including migratory and invasive capabilities. During the process of EMT, epithelial traits are downregulated, while mesenchymal traits are acquired, with cells developing migratory ability, increasing proliferation, and resistance to apoptosis. EMT is promoted by exposure to hypoxia and stimulation by transforming growth factor-β (TGF-β), platelet-derived growth factor (PDGF), and estradiol. Signaling pathways that promote EMT are activated in most ectopic lesions and involve transcription factors such as Snail, Slug, ZEB-1/2, and TWIST-1/2. EMT-specific molecules present in the serum of women with endometriosis appear to have diagnostic potential. Strategies targeting EMT in animal models of endometriosis have demonstrated regression of ectopic lesions, opening the door for novel therapeutic approaches. This review summarizes the current understanding of the role of EMT in endometriosis and highlights potential targets for EMT-related diagnosis and therapeutic interventions. Full article

Understanding and forecasting energy consumption patterns is crucial for improving energy efficiency and human well-being, especially in diverse infrastructures like Spain. This research addresses a significant gap in energy demand forecasting across three building types by comparing six machine learning algorithms: Artificial Neural Networks, Random Forest, XGBoost, Radial Basis Function Network, Autoencoder, and Decision Trees. The primary aim is to identify the most effective model for predicting energy consumption based on historical data, contributing to the relationship between energy systems and urban well-being. The study emphasizes challenges in energy use and advocates for sustainable management practices. By forecasting energy demand over the next three years using linear regression, it provides actionable insights for energy providers, enhancing resilience in urban environments impacted by climate change. The findings deepen our understanding of energy dynamics across various building types and promote a sustainable energy future. Stakeholders will receive targeted recommendations for aligning energy production with consumption trends while meeting environmental responsibilities. Model performance is rigorously evaluated using metrics like Squared Mean Root Percentage Error (RMSPE) and Coefficient of Determination (R²), ensuring robust analysis. Training times for models in the LUCIA building ranged from 2 to 19 s, with the Decision Tree model showing the shortest times, highlighting the need to balance computational efficiency with model performance. Full article

Background: Gastric cancer (GC) is a highly heterogeneous disease and remains one of the major causes of cancer-related mortality worldwide. The vast majority of GC cases are adenocarcinomas including diffuse and intestinal GC that may differ in their incidence between Asian and non-Asian cohorts. The intestinal-subtype GC has declined over the past 50 years. In contrast to the intestinal-subtype adenocarcinoma, the incidence of diffuse-subtype GC, often associated with poor overall survival, has constantly increased in the USA and Europe. The aim of this study was to analyze the expression and clinical significance of steroid hormone receptors, two membrane-bound receptors (ERRγ and GPER), and several genes involved in epigenetic alterations. The findings may contribute to revealing events driving tumorigenesis and may aid prognosis. Methods: Using mRNA from diffuse and intestinal GC tumor samples, the expression level of 11 genes, including those coding for sex hormone receptors (estrogen receptors ERα and ERβ), progesterone receptor (PR) and androgen receptor (AR), and the putative relevant ERRγ and GPER receptor were determined by RT-qPCR. Results: In diffuse GC, the expression of ERα, ERβ, PR and AR differed from their expression in the intestinal subtype. The expression of ERα and ERβ was strongly increased in the diffuse subtype compared to the intestinal subtype (×1.90, p = 0.001 and ×2.68, p = 0.002, respectively). Overexpression of ERα and ERβ was observed in diffuse GC (15 and 42%, respectively). The expression levels of PR and AR were strongly decreased in the intestinal subtype as compared to diffuse GC (×0.48, p = 0.005 and ×0.25, p = 0.003, respectively; 37.5% and 56% underexpression). ERα, ERβ, PR and AR showed notable differences for clinicopathological correlation in the diffuse and intestinal GC. A significant decrease of ERα, ERβ, PR and AR in intestinal GC correlated with the absence of lymphatic invasion and lower TNM (I-II). In diffuse GC, among the hormone receptors, increases of ERs and PR mainly correlated with expression of growth factors and receptors (IGF1, FGF7 and FGFR1), and with genes involved in epithelial-mesenchymal transition (VIM and ZEB2) or cell migration (MMP2). Our results also report the strong decreased expression of ERRγ and GPER (two receptors that bind estrogen or xenoestrogens) in diffuse and intestinal subtypes. Conclusions: Our study identified new target genes, namely hormone receptors and membrane receptors (ERRγ and GPER), whose expression is associated with an aggressive phenotype of diffuse GC, and revealed the importance of epigenetic factors (EZH2, HOTAIR, H19 and DNMT1) in gastric cancers. Full article

The accurate measurement of the tree diameter is vital for forest inventories, urban tree quality assessments, the management of roadside and railway vegetation, and various other applications. It also plays a crucial role in evaluating tree growth dynamics, which are closely linked to tree health, structural stability, and vulnerability. Although a range of devices and methodologies are currently under investigation, the widespread adoption of laser scanners remains constrained by their high cost. This study therefore aimed to compare high-end laser scanners (Trimble TX8 and GeoSLAM ZEB Horizon) with cost-effective alternatives, represented by the Apple iPhone 14 Pro and the LA03 scanner developed by mapry Co., Ltd. (Tamba, Japan). It further sought to evaluate the feasibility of employing these more affordable devices, even for small-scale forest owners or managers. Given the growing availability of 3D-based forest inventory algorithms, a selection of such processing pipelines was used to assess the practical potential of the scanning devices. The tested low-cost device produced moderate results, achieving a tree detection rate of up to 78% and a relative root mean square error (rRMSE) of 19.7% in diameter at breast height (DBH) estimation. However, performance varied depending on the algorithms applied. In contrast, the high-end mobile laser scanning (MLS) and terrestrial laser scanning (TLS) systems outperformed the low-cost alternative across all metrics, with tree detection rates reaching up to 99% and DBH estimation rRMSEs as low as 5%. Nevertheless, the low-cost device may still be suitable for scanning small sample plots at a reduced cost and could potentially be deployed in larger quantities to support broader forest inventory initiatives. Full article

This article demonstrates how positioning residents as active co-designers fundamentally transforms both the process and outcomes of carbon-positive building development. Through structured collaborative workshops, shared decision-making protocols, and continuous partnership throughout the building lifecycle, the REN+HOMES Positive Carbon Building methodology challenges the conventional expert-driven approach to sustainable construction. Developed and validated through the H2020 REN+HOMES project, this resident-centered approach achieved remarkable technical performance—65.9% reduction in final energy demand—while simultaneously enhancing community ownership and long-term sustainability practices. By integrating participatory design with Zero Emissions Building (ZEB) criteria, renewable energy systems, and national carbon offset programs, the methodology proves that resident collaboration is not merely beneficial but essential for creating buildings that truly serve both environmental and human needs. This research establishes a new paradigm where technical excellence emerges from authentic partnership between residents and sustainability experts, offering a replicable framework for community-driven environmental regeneration. Full article

To address energy shortages and achieve carbon peaking/neutrality, this study develops a distributed renewable-based integrated energy system (IES) for rural active zero-energy buildings (ZEBs). Energy consumption patterns of typical rural houses are analyzed, guiding the design of a resource-tailored IES that balances economy and sustainability. Key equipment capacities are optimized to achieve net-zero/zero energy consumption targets. For typical daily cooling/heating/power loads, equipment output is scheduled using a dual-objective optimization model minimizing operating costs and CO₂ emissions. Results demonstrate that: (1) Net-zero-energy IES outperforms separated production (SP) and full electrification systems (FES) in economic-environmental benefits; (2) Zero-energy IES significantly reduces rural building carbon emissions. The proposed system offers substantial practical value for China’s rural energy transition. Full article

As climate change intensifies the frequency and severity of extreme weather events, the urgency for resilient and sustainable urban development becomes increasingly critical. This study investigates the role of digital twins in advancing climate-responsive urban strategies, with a focus on their integration into zero-energy buildings (ZEBs) and smart city frameworks. A systematic literature review was conducted following PRISMA guidelines, covering 1000 articles initially retrieved from Scopus and Web of Science between 2014 and 2024. After applying inclusion and exclusion criteria, 70 full-text articles were analyzed. Bibliometric analysis using VOSviewer revealed five key application areas of digital twins: energy efficiency optimization, renewable energy integration, design and retrofitting, real-time monitoring and control, and predictive maintenance. The findings suggest that digital twins can contribute to up to 30–40% improvement in building energy efficiency through enhanced performance monitoring and predictive modeling. This review synthesizes trends, identifies research gaps, and contextualizes the findings within the Middle Eastern urban landscape, where climate action and smart infrastructure development are strategic priorities. While offering strategic guidance for urban planners and policymakers, the study also acknowledges limitations, including the regional focus, lack of primary field data, and potential publication bias. Overall, this work contributes to advancing digital twin applications in climate-resilient, zero-energy urban development. Full article

Snail and Zeb1 have been suggested as markers for the hybrid/mixed epithelial (E)/mesenchymal (M) state of cancer cells. Such cancer cells co-express E- and M-specific transcripts and possess cancer stem cell properties. M13HS-2/-8 tumor hybrid clones derived from human M13SV1-EGFP-Neo breast epithelial cells and human HS578T-Hyg breast cancer cells exhibited co-expression of Snail and Zeb1. To explore the impact of Snail on stemness/epithelial-to-mesenchymal transition (EMT)-related properties in M13HS-2/-8 tumor hybrid clones, Snail was knocked out (KO) using CRISPR/Cas9. Mammosphere formation, colony formation, Western blot analyses, cell migration, and invasion assays were conducted for the characterization of Snail knockout cells. Interestingly, Snail-KO in M13SV1-EGFP-Neo cells resulted in the up-regulation of vimentin and N-cadherin, suggesting EMT induction, which was associated with a significantly enhanced colony formation capacity. In contrast, EMT marker pattern and colony formation capacities of M13HS-2/-8 Snail-KO tumor hybrid clones remained unchanged. Notably, the mammosphere formation capacities of M13HS-2/-8 Snail-KO tumor hybrid clones were significantly reduced. The migratory behavior of all Snail-KO cells was not altered compared with their wild-type counterparts. In contrast, M13HS-2 hybrids and their M13HS-2 Snail-KO variant exhibited a markedly enhanced invasive capacity. Therefore, Snail plays a role as a mediator of stemness properties rather than mediating EMT. Full article

Nearly zero-energy buildings (nZEBs) are central to global carbon reduction strategies, and Taiwan is actively promoting their adoption through building energy performance labeling, particularly in the retrofit of existing buildings. Under Taiwan’s nZEB framework, qualification requires both an A⁺ energy performance label and over 50% energy savings from retrofit technologies. This study proposes an integrated assessment framework for retrofitting small- to medium-sized office buildings into nZEBs, incorporating diagnostics, technical evaluation, policy alignment, and resource integration. A case study of a bank branch in Kaohsiung involved on-site energy monitoring and EnergyPlus V22.2 simulations to calibrate and assess the retrofit impacts. Lighting improvements and two HVAC scenarios—upgrading the existing fan coil unit (FCU) system and adopting a completely new variable refrigerant flow (VRF) system—were evaluated. The FCU and VRF scenarios reduced the energy use intensity from 141.3 to 82.9 and 72.9 kWh/m²·yr, respectively. Combined with rooftop photovoltaics and green power procurement, both scenarios met Taiwan’s nZEB criteria. The proposed framework demonstrates practical and scalable strategies for decarbonizing existing office buildings, supporting Taiwan’s 2050 net-zero target. Full article

This study presents a comprehensive comparison of static and SLAM (Simultaneous Localization and Mapping) laser scanners of both new and old generation in a controlled indoor environment of a standard commercial building with long, linear corridors and recesses. The aim was to assess both global and local accuracy, as well as noise characteristics, of each scanner. Methods: A highly accurate static scanner was used to generate a reference point cloud. Five devices were evaluated: two static scanners (Leica RTC 360 and Trimble X7) and three SLAM scanners (GeoSLAM ZEB Horizon RT, Emesent Hovermap ST-X, and FARO Orbis). Accuracy analysis included systematic and random error assessment, axis-specific displacement evaluation, and profile-based local accuracy measurements. Additionally, noise was quantified before and after data smoothing. Static scanners yielded superior accuracies, with the Leica RTC 360 achieving the best performance (absolute accuracy of 1.2 mm). Among SLAM systems, the Emesent Hovermap ST-X and FARO Orbis—both newer-generation devices—demonstrated significant improvements over the older-generation GeoSLAM ZEB Horizon RT. After smoothing, the noise levels of these new-generation SLAM scanners (approx. 2.1–2.2 mm) approached those of static systems. The findings underline the ongoing technological progress in SLAM systems, with the new-generation SLAM scanners becoming increasingly viable alternatives to static scanners, especially when speed, ease of use, and reduced occlusions are prioritized. This makes them well-suited for rapid indoor mapping applications, provided that the slightly lower accuracy is acceptable for the intended use. Full article

Uterine fibroids (leiomyomas) are benign tumors whose growth is influenced by estrogen and progesterone. This study aimed to compare the profiles of differentially expressed long non-coding RNAs (lncRNAs) in fibroids from postmenopausal and premenopausal women to identify hormone-responsive lncRNAs. RNA sequencing was performed on six pairs of fibroid (Fib) and adjacent myometrium (Myo) tissues from postmenopausal women. Out of 7876 normalized lncRNAs, 3684 were differentially expressed (≥1.5-fold), with 1702 upregulated and 1982 downregulated in Fib. Comparative analysis with a previously published premenopausal dataset identified 741 lncRNAs that were altered based on their menopausal status, including 62 lncRNAs that were uniquely dysregulated in postmenopausal samples. Overall, 9 lncRNAs were selected for validation by PCR in an expanded cohort of 31 postmenopausal and 84 premenopausal paired samples. Several lncRNAs, including LINC02433, LINC01449, SNHG12, H19, and HOTTIP, were upregulated in premenopausal Fib but not in postmenopausal ones, while ZEB2-AS1 displayed the opposite pattern. CASC15 and MIAT were elevated in Fib from both groups, although the increase was less pronounced in the postmenopausal group. LINC01117 was significantly downregulated in postmenopausal Fib, with no change observed in premenopausal samples. Additionally, analysis based on MED12 mutation status revealed that lncRNAs such as LINC01449, CASC15, and MIAT showed limited or reduced differential expression (mutation-positive vs. mutation-negative) in postmenopausal patients compared to the premenopausal group. These findings indicate that lncRNA expression in fibroids is modulated by menopausal status, likely reflecting hormonal influence. Hormone-responsive lncRNAs may play key roles in fibroid pathogenesis and represent potential targets for therapeutic intervention. Full article

Antlers exhibit exceptionally rapid growth, representing a rare biological phenomenon among mammals. In addition to their scientific significance, antlers are widely used in traditional medicine, and their yield directly impacts the economic efficiency of the deer farming industry. However, antler yield varies substantially among individuals, and the molecular mechanisms underlying this variation remain poorly understood. This study aimed to elucidate the transcriptomic and post-transcriptional mechanisms underlying antler yield variation by comparing gene and miRNA expression profiles across four distinct antler tissue layers—dermis (D), reserve mesenchyme (RM), pre-cartilage (PC), and cartilage (C)—in sika deer with different yields. RNA-seq and miRNA-seq were performed, followed by differential expression, GO and KEGG pathway enrichment, and miRNA–mRNA co-expression network analyses. Our results reveal layer-specific expression patterns and key regulatory genes and miRNAs associated with proliferation, chondrogenesis, angiogenesis, and mineralization. In particular, genes such as FBP2, TPT1, TFRC, ZEB1, and PHOSPHO1 were upregulated in high-yield deer across specific tissue layers, while NFATC2 was downregulated in these high-yield deer. Additionally, miRNAs such as miR-140, miR-296-3p, and let-7e exhibited layer-specific expression patterns linked to growth and differentiation. Our miRNA–mRNA regulatory network analysis highlighted significant interactions, particularly miR-296-3p–PHOSPHO1 and miR-296-3p–FBP2, as key regulators of antler growth. Enrichment of PI3K-Akt and TGF-β signaling pathways further suggests their involvement in promoting chondrogenesis and ossification. These findings provide novel insights into the molecular basis of antler growth and yield, which may inform future strategies for selective breeding in deer farming. Full article

Pancreatic ductal adenocarcinoma (PDAC) is one of the most lethal cancer types due to its late diagnosis, low survival rates, and high frequency of metastasis. Considering the molecular mechanism of PDAC development has not been fully elucidated, this study aimed to shed more light on the molecular regulatory signatures of circular RNAs (circRNAs) in PDAC progression and provide a different perspective to identify potential biomarkers as well as discover candidate repositioned drug molecules for the prevention or treatment of PDAC with network-based integrative analysis. The mRNA, miRNA, and circRNA expression profiles of PDAC were obtained from nine microarray datasets. Differentially expressed genes (DEGs), microRNAs (DEmiRNAs), and circular RNAs (DEcircRNAs) were identified. The competing endogenous RNA (ceRNA; DEG–DEmiRNA–DEcircRNA) regulatory network was constructed, which included 12 DEcircRNAs, 64 DEGs, and 6 miRNAs specific to PDAC. The ADAM12, MET, QKI, SEC23A, and ZEB2 were identified as hub genes and demonstrated significant survival probability for PDAC. In addition to providing novel biomarkers for diagnosis that can be detected non-invasively, the secretion levels of hub genes-associated proteins were found in plasma, serum, and oral epithelium. The drug repositioning analysis revealed vorinostat, meclocycline sulfosalicylate, and trichostatin A, which exhibited significant binding affinities to the hub genes compared to their inhibitors via molecular docking analysis. Full article

In the current context of the transition toward climate neutrality and the pressing need to reduce energy consumption in the construction sector, nZEBs have become a central benchmark in European sustainability policies. These buildings offer multiple benefits, such as reduced operational costs, enhanced thermal comfort, and improved indoor air quality. Achieving such performance requires the integration of advanced technological solutions, including passive façades with ventilated cavities. The primary objective of this study is to investigate the influence of cavity geometry on the thermal behavior of a passive façade, through numerical simulations conducted in ANSYS Fluent 17. The study focuses on comparing five distinct configurations with varying cavity widths, aiming to identify the optimal solution in terms of heat transfer efficiency. The main contribution lies in the analysis and correlation of air temperature and velocity distributions with the cavity’s geometric parameters, highlighting the impact of channel width on thermal performance. The configuration with a 12 cm wide air channel recorded the highest heat flux at the outlet, approximately 44 times greater than the façade with a 4 cm wide channel, making it the most efficient solution. The results indicate significantly higher thermal efficiency for the configuration with a larger cavity width, contrary to initial intuitive assumptions. These insights provide a valuable framework for the optimal design of passive façades in nZEB applications and highlight the need for further research, combining numerical and experimental approaches, to develop sustainable and energy-efficient building envelope solutions. Full article

Industry 5.0 is transforming energy demand by integrating sustainability into energy planning, ensuring market stability while minimizing environmental impact for future generations. There are several patterns for calculating energy consumption depending on whether it is measured daily, monthly, or annually through the integration of artificial intelligence approaches, particularly Artificial Neural Networks (ANNs) and Random Forests (RFs), and within the framework of Industry 5.0. This study employs machine learning techniques to analyze energy consumption data from two distinct buildings in Spain: the LUCIA facility in Valladolid and the FUHEM Building in Madrid. The implementation was conducted using custom MATLAB code developed in-house. Our approach systematically evaluates and compares the predictive performance of Artificial Neural Networks (ANNs) and Random Forests (RFs) for energy demand forecasting, leveraging each algorithm’s unique characteristics to assess their suitability for this application. The performances of both models are calculated using the Root Mean Square Percentage Error (RMSPE), Root Mean Square Relative Percentage Error (RMSRPE), Mean Absolute Percentage Error (MAPE), Mean Absolute Relative Percentage Error (MARPE), Kling–Gupta Efficiency (KGE), and also the coefficient of determination, R². Training times are validated using ANN and RF models. Lucia RF took 2.8 s, while Lucia ANN took 40 s; FUHEM RF took 0.3 s, compared to FUHEM ANN, which took 1.1 s. The performances of the two models are described in detail to show the effectiveness of each of them. Full article