Search Results (7,782)

Preeclampsia (PE), pregnancy-associated high blood pressure linked to organ damage, affects 3–8% of all pregnancies and results worldwide in 70,000 maternal and 500,000 perinatal deaths each year. Untreated PE may progress to eclampsia with long-term health implications for both mother and child. Non-invasive prenatal diagnosis or screening applies cell-free DNA approaches and offers a less invasive and more economical method for early diagnosis and prediction of various pregnancy complications. Recently, cell-free assays, particularly blood-based cell-free DNA and RNA analysis, have shown great potential in early PE prediction and diagnosis. Here, we provide an updated review of the current understanding and discoveries of PE, focusing on recent publications (1 January 2019–30 December 2025) of liquid biopsy-derived circulating fetal cells (circulating trophoblasts and fetal nucleated red blood cells), cell-free DNA, cell-free RNA and small extracellular vesicles (i.e., exosomes). We aim to discuss the conceptual framework and technical evolution of liquid biopsy applications in preeclampsia pathogenesis, prediction and diagnosis. Progressing novel screening and diagnostic molecular biomarkers have high potential to facilitate early detection for patients at risk of PE. Liquid biopsy-based screening strategies may aid in providing timely intervention and treatment. Full article

This research-related study examines the relevance of mud pulse telemetry (MPT) systems and their intersection with drilling performance, focusing on data transmission signal propagation performance and overall operation under different drilling parameters conditions, with an additional focus on drilling fluid flow rate and downhole pressure conditions. The novelty of this study lies in the investigation of adjustments to drilling operating parameters that could potentially improve the transmission of telemetry signals during drilling, in real time, without requiring mechanical or functional modifications to the MPT system itself. Improvements on transmission performance in situations where the data rate may be limited are also addressed, presenting an alternative through possible propagation velocity improvements to counterbalance it. A detailed chronological technical scientific literature review details important parts on analyses of pressure pulse propagation velocities focused on data transmission. A systematic experimental approach was developed and put into practice to evaluate the MPT systems in regard to tendencies on transmission performances, emphasizing pressure pulse propagation velocity. The laboratory-scale experiments were conducted at the Institute of Drilling Engineering and Fluid Mining (IBF) from the Technical University Bergakademie Freiberg (TUBAF), namely the Flow-loop Research Facility, to assess the impact of fluid flow rate (and subsequent pressure) on data transmission efficiency. Experimental results demonstrate that increasing the flow rate significantly speeds up signal propagation. In the performed experiments, for the mud siren configuration, increasing the flow rate from 15 to 25 [m³/h] improved the data transmission performance by approximately, at minimum, 18%, while for the positive mud pulse system, an increase in flow rate from 11.5 to 14 [m³/h] resulted in a propagation velocity rise of about 19%. The results also showed that higher concentrations of glycerin in the working fluid reduced the propagation velocity, confirming the influence of the fluid’s rheological properties on telemetry performance. At the end, in the presented case study, for 6 [bps] data rate configurations and for a transmission of a 40-bit string, it was demonstrated that the propagation time from downhole to the surface could potentially represent approximately 40% of the total time demanded for transmitting the desired information (generation plus propagation time). It was verified that an increment of 0.02208 [m³/s] (350 [gpm]) could lead to shortening eventual surveying procedures by 1–2 [s], and that it could equally represent 1.137 [bps]. This is a relevant outcome, since, without any physical or functional alteration to the MPT system, one could have the data transmission performance improved, an approach not yet analyzed in the literature nor at the industrial park. These results, added to the detailed literature investigation and interaction with field personnel, indicate that the drilling fluid flow rate is a critical operational parameter affecting both the telemetry signal transmission speed and the overall drilling efficiency. Increasing the flow rate can reduce survey transmission time and decrease operational exposure to drilling hazards, such as drill string sticking. The results provide quantitative information applicable in optimizing measurement-drilling telemetry and help support the development of integrated drilling optimization strategies that balance drilling performance with real-time data transmission assurance in deep drilling operations. Full article

Brewer’s spent grain (BSG) is one of the major by-products of the brewing industry and an abundant lignocellulosic stream with potential for energy recovery and broader biorefinery use. This review evaluates the main BSG-to-energy pathways, including anaerobic digestion (AD), combustion/co-combustion, pyrolysis, gasification, and hydrothermal processes (HTC/HTL), with emphasis on technical performance, environmental aspects, implementation constraints, and integration into brewery systems. Particular attention is given to the effect of BSG heterogeneity, high moisture content, protein and ash composition, and storage instability on process selection and operability. In addition to summarizing pathway-specific evidence, the manuscript proposes a harmonized comparative framework and an integrated technical–economic–environmental interpretation of BSG valorization options. The analysis shows that wet-feed-compatible pathways, especially AD and hydrothermal processing, are generally better aligned with the intrinsic properties of fresh BSG, whereas thermochemical routes usually require more intensive feedstock conditioning and tighter control of ash-related and gas cleaning risks. The review also highlights that long-term operational reliability, scale-up constraints, and utility integration are as important as nominal conversion efficiency when assessing practical deployment. Current evidence suggests that the most realistic implementation strategies are context-dependent and should be selected according to brewery scale, energy demand profile, available heat integration, and acceptable operational risk. Future research should prioritize harmonized reporting, long-term industrial validation, and the development of robust hybrid systems and brewery-integrated biorefinery configurations. Full article

Marine turtles are key species for the stability of coastal and oceanic ecosystems; however, their conservation faces increasing pressures derived from climate change and anthropogenic activities. This study analyzes the perception of the academic and scientific community in biology, environmental sciences, and marine sciences regarding marine turtle conservation along the coast of Sinaloa, Mexico. A quantitative cross-sectional survey-based study with an exploratory approach was employed, using a Likert-scale questionnaire administered to 358 participants. The instrument demonstrated adequate internal consistency (α = 0.836; ω = 0.827). An exploratory factor analysis (EFA) using principal component extraction identified four components explaining 55.51% of the total variance, corresponding to four dimensions: (1) commitment to conservation, (2) environmental and climatic impacts on reproductive processes, (3) key factors and threats in the reproductive cycle, and (4) conservation practices and knowledge. Results suggest a general tendency toward agreement on the ecological importance of marine turtles and the threats affecting their reproductive success, particularly climate-related and habitat degradation factors. However, greater variability was observed in perceptions related to applied practices and technical knowledge, indicating differences in perceptions related to the implementation of conservation strategies. These findings suggest the potential relevance of strengthening applied training, interdisciplinary collaboration, and knowledge transfer mechanisms to enhance the effectiveness of conservation initiatives in priority nesting areas of Sinaloa. Full article

Parallel robots are widely applied in many fields because of their unique advantages. To ensure their operational safety and reduce maintenance costs, designing an accurate and reliable fault diagnosis method is essential. Focusing on the 2RRU-RRS parallel robot, this paper proposes an intelligent fault diagnosis method based on a multi-scale convolutional residual network integrated with an Efficient Channel Attention mechanism (MS-ECA-ResNet). Firstly, to fully retain the time-frequency features of the signals, the one-dimensional vibration signals are converted into two-dimensional images using the Continuous Wavelet Transform (CWT). Secondly, a multi-scale convolutional feature extraction structure is designed to enhance the model’s feature extraction ability at different time scales. Furthermore, the ECA mechanism is introduced into the residual network to reinforce important feature channels and suppress noise interference. Comparative experiments, noise environment experiments, and ablation experiments were conducted on a 2RRU-RRS parallel robot experimental platform with a vibration signal dataset. The results demonstrate that the proposed method achieves superior diagnostic accuracy and robustness compared to typical deep learning models, particularly in maintaining high performance under simulated noise conditions. This provides a preliminary validation of the method’s effectiveness in capturing fault-related impacts, offering a potential technical reference for the health monitoring of parallel robots in real-world scenarios. Full article

Spam consists of unsolicited messages, and the posting of such irrelevant messages often presents significant challenges in technical forums. Two particular challenges are the dynamic nature of spamming tactics and the inadequacy of adaptable spam databases for automated classifiers. Our work addresses the need for a robust spam classification solution that can be seamlessly integrated with database, SQL, and APEX applications. We developed a labeled spam database by asking experts to categorize 1916 posts as spam or regular posts to ensure accurate classification and then created an SVM-based spam classification model that achieves an average validation accuracy of 90%. Our research enhances the current understanding of spam in technical forums and represents a solution for embedding spam classifiers into widely used platforms with an accuracy of 98.1%. Furthermore, we explore the incorporation of generative topics into our approach by integrating generative topic modeling techniques, such as latent Dirichlet allocation. In our work, the spam classifier is dynamically updated to account for emerging spam patterns and topics based on a generative approach that improves the robustness of the classifier against new spamming tactics and enables nuanced, context-aware filtering of messages. In addition, our experiments highlight the potential of text SVM classifiers for real-time applications through the fine-tuning of text features. Full article

Background: This case report presents a 12-year-old male with vertically transmitted chronic hepatitis B virus (HBV) infection, exhibiting a rare pan-reactive serological profile (concurrent HBsAg, HBsAb, HBeAg, HBeAb, and HBcAb positivity) alongside fluctuating low-level viremia (HBV DNA: 1.06 × 10² IU/mL to undetectable). Rigorous exclusion of technical artifacts confirmed the authenticity of this atypical serologic pattern, observed in <0.001% of the general population. Methods: Liver biopsy and immunohistochemical staining were performed to evaluate hepatic inflammation and fibrosis. HBV serological markers and viral load were quantified using commercial diagnostic kits, with longitudinal monitoring for 18 months. Results: Liver biopsy revealed Grade 2 inflammation with focal HBsAg/HBcAg expression, supporting immune-active chronic hepatitis B (CHB) despite partial seroconversion. The patient’s clinical course highlights key challenges in pediatric HBV management: (1) delayed immune reconstitution (18-month longitudinal HBeAg/HBeAb dynamics), (2) non-linear virologic-ALT correlation, and (3) diagnostic ambiguity in pan-positive serology—potentially reflecting S-gene escape mutants or transitional immune responses. Initiation of tenofovir disoproxil fumarate (TDF) achieved sustained virologic suppression, underscoring the importance of early antiviral therapy in pediatric CHB with atypical markers. Conclusions: This case provides preliminary insights into the complex interplay between viral evolution and immature host immunity, advocating for refined monitoring protocols integrating high-sensitivity HBV DNA, quantitative serology, and non-invasive fibrosis assessment in pediatric HBV care. Full article

Rapid expansion of electric vehicle adoption has led to increased dependence on a charging infrastructure that is tightly integrated with energy distribution systems and digital communication networks. As electric vehicle charging stations evolve into complex cyber–physical systems, cybersecurity risks pose a growing threat to grid reliability and user trust. This paper presents a hybrid decision-support framework for cybersecurity risk assessment in EV charging infrastructure that advances beyond prior multi-criteria decision-making approaches by combining interpretability with data-driven validation. Specifically, the framework integrates the Analytic Hierarchy Process (AHP) for expert-driven weighting of cybersecurity attributes with PROMETHEE for flexible threat prioritization, enabling transparent and auditable risk rankings. The framework categorizes cybersecurity criteria across four infrastructure layers—transmission, distribution, consumer, and electric vehicle charging stations—and assigns relative weights through expert-driven pairwise comparisons. PROMETHEE is then applied to rank potential cyber threats based on these weights, allowing for flexible prioritization of cybersecurity interventions. The methodology is validated using the real-world WUSTL-IIoT-2018 SCADA dataset, which includes simulated reconnaissance (network scanning), device identification, and exploitation attacks. While this dataset does not natively include OCPP 2.0 or ISO 15118 protocols, the experimental results demonstrate strong discrimination power (AUC = 0.99, recall = 95%) and provide a basis for extension to modern EVSE communication standards. The results identify critical metrics such as anomalous source packet behavior and encryption reliability as key vulnerability markers, aligning with documented EV charging attack scenarios. By bridging expert judgment with empirical traffic data, the proposed framework offers both technical robustness and explainability, supporting grid operators, SOC teams, and infrastructure planners in systematically assessing risks, allocating resources, and enhancing the resilience of EV charging ecosystems against evolving cyber threats. Full article

Tomato (Solanum lycopersicum) is a widely consumed vegetable crop and an established model system for plant functional genomics and genetic research in dicotyledons. Salt stress is a major abiotic factor limiting tomato productivity worldwide. The WRKY transcription factor family, one of the largest and most conserved plant-specific transcription factor families, plays pivotal roles in stress responses. This review summarizes recent advances in understanding the functions of tomato WRKY genes under salt stress, focusing on the genomic basis and evolutionary characteristics of the WRKY family, the roles of core WRKY members under salt stress, and the multi-layered regulatory networks mediating WRKY-dependent salt and alkali tolerance. To date, approximately 10 core SlWRKY genes have been functionally validated to regulate tomato salt tolerance, mainly by maintaining ion homeostasis, regulating reactive oxygen species (ROS) balance, facilitating osmotic adjustment, and integrating hormone signaling pathways. Despite this progress, systemic regulatory hierarchies and epigenetic modulation remain poorly resolved. Furthermore, we discuss how specific WRKY members directly regulate downstream effector genes, such as SlSOS1 and SlNHX4. However, direct experimental evidence for the coordination between tomato WRKYs and mitogen-activated protein kinase (MAPK) cascades, as well as epigenetic modifiers under salt stress, is still scarce in current studies. This review provides a theoretical framework and outlines potential technical pathways for translating fundamental insights into tomato salt tolerance into practical applications for sustainable agriculture. Full article

Microplastic pollution in farmland soils has emerged as a global concern due to its potential to degrade soil health, inhibit crop growth, and enter the food chain. However, effective and environmentally friendly remediation strategies remain limited, particularly regarding the use of biochar to mitigate polyethylene microplastic (PE-MP) stress in agroecosystems. This study investigates whether tobacco stalk biochar (TSB) can alleviate PE-MPs stress in rice seedlings. A two-factor pot experiment was conducted to systematically analyze the responses of soil physicochemical properties, rice growth indicators, and antioxidant enzyme activities to the combined application of varying concentrations of PE-MPs (0, 0.5%, 1%, and 2% (w/w)) and TSB (0, 3%, 6%, and 9% (w/w)). The results show that TSB significantly increased soil pH and organic matter content, effectively mitigating the decline in available nitrogen, phosphorus, and potassium caused by PE-MPs (e.g., under the M3B3 treatment, available nitrogen and phosphorus contents increased by 68.7% and 226%, respectively, compared with those under the M3B0 treatment). Under low-concentration PE-MP (0.5%) stress, an appropriate amount of TSB (3%) resulted in the highest rice germination rate, vigor index, and stress tolerance index, while significantly inducing the activities of superoxide dismutase (SOD) and catalase (CAT) to alleviate oxidative damage. However, high-concentration combinations of TSB and PE-MPs exhibited an antagonistic effect. In conclusion, tobacco stalk biochar can synergistically mitigate microplastic stress on rice through multiple pathways, with its remediation effects exhibiting significant dose dependence and interactive complexity. These findings provide a theoretical and technical basis for the ecological remediation of microplastic pollution in farmland. Full article

Promoting pesticide reduction is a key step toward green vegetable production and ecological safety. Based on survey data collected from 356 leek growers in Weifang City—the largest facility-based vegetable production base in Shandong Province—this study empirically estimates the ecological compensation standard associated with pesticide-reduction behavior. The estimation employs a contingent valuation method (CVM) using non-parametric kernel density estimation for conditional value assessment, combined with the Heckman two-step model to address potential sample selection bias. The results show that 79.3% of respondents are willing to participate in an eco-compensation program for pesticide reduction; the main reason for refusal is “the higher reduction costs and lower profits”. The expected compensation level ranges from 614.94 to 620.57 yuan per mu (1 mu is approximately 0.165 acres) per year. Gender, share of Chinese chives (Allium tuberosum) income, trust in extension agents, and government penalties for excessive spraying significantly raise the required compensation, whereas age and knowledge of eco-compensation significantly lower it. Therefore, a sustainable compensation scheme co-driven by government and market should be established, combining cash, technical and in-kind support, and adopting tiered compensation schemes that reflect different reduction intensities. Full article

Antibiotic residues in aquatic products pose a serious food safety concern, whereas conventional laboratory methods often fail to meet the demand for on-site rapid screening. This study systematically reviews the research progress from 2021 to 2025 on both the risks of antibiotic residues in aquatic products and the development of rapid on-site detection technologies. First, based on a literature survey covering major aquatic products (e.g., fish, shrimp, and shellfish), the widespread occurrence of multiple antibiotics at high concentrations was documented, with quinolones and sulfonamides identified as the most frequently detected classes. To address the need for on-site testing, this review focuses on six rapid detection techniques: fluorescent sensor (FRS), lateral flow immunoassay (LFIA), surface-enhanced Raman scattering (SERS), enzyme-linked immunosorbent assay (ELISA), electrochemical sensor (ECRS), and colorimetric sensor (CRS). The core principles, technical advantages, recent application cases (e.g., integration with smartphones and novel nanomaterials), and development trends for each method are analyzed. Finally, it discusses the current challenges faced by existing on-site detection approaches and their potential solutions. Technology selection strategies tailored to different application scenarios (e.g., aquaculture farms, distribution channels, and consumer-level use) are also proposed. Full article

Construction and demolition activities generate over one-third of all waste produced within the European Union, with the largest fraction being mineral materials, and concrete representing up to 90% of this volume. In this context, the recycling of this type of waste is an important research topic with growing scientific and industrial relevance. While numerous studies have examined the influence of recycled concrete and other industrial waste on the technical performance of Portland cement-based composites, the antimicrobial resistance of these composites remains largely unexplored. Therefore, in this study we evaluate the effects of three different waste materials on the key properties of Portland cement mortar, as well as on its antimicrobial resistance; the investigated waste materials were fly ash (produced in thermal power plants), recycled concrete fines resulted from the mechanical processing of concrete waste generated in construction and demolition activities, as well as dried concrete slurry (a byproduct of concrete batching plants). The partial replacement of Portland cement with these concrete wastes slightly increased the mortar’s workability (up to 4.6%). However, it also led to an 11–12% reduction in compressive strength after 28 days of hardening. After 60 days of curing, the antimicrobial properties of these mortars were evaluated by assessing their effect on planktonic microbial growth and their anti-adherent capacity against the most common pathogenic strains (S. aureus, E. coli, P. aeruginosa, C. albicans, and C. parapsilosis). Antimicrobial assays were performed at two different concentrations of microbial suspensions, and the mortars exhibited significant antibiofilm properties against all strains, especially against E. coli. The study identified mortar formulations in which partial replacement of cement with construction, demolition, and industrial waste materials resulted in compressive strength and antimicrobial resistance comparable to those of conventional reference mortars. These findings highlight the potential to integrate recycled waste into Portland cement-based materials, supporting both structural integrity and microbial resistance and advancing sustainable construction practices. Full article

Artificial intelligence (AI) is increasingly transforming spine surgery, with expanding applications in diagnostics, intraoperative imaging, and surgical navigation. As the field advances toward greater precision and safety, machine learning (ML) and deep learning technologies are being integrated to augment surgeon expertise and optimize operative workflows. In particular, AI-driven innovations in image acquisition and navigation are reshaping intraoperative decision-making and technical execution. This narrative review provides an overview of AI applications relevant to intraoperative imaging and navigation in spine surgery. We begin by defining key concepts in AI, ML, and deep learning and briefly outline the historical evolution of AI within spine practice. We then examine current capabilities in image recognition and automated pathology detection, emphasizing their clinical relevance. Given the central role of imaging accuracy in modern navigation-assisted procedures, we review conventional acquisition platforms, including intraoperative computed tomography (CT) systems (e.g., O-arm, GE, Airo), surface-based registration to preoperative CT (Stryker, Medtronic), and optical surface mapping technologies (e.g., 7D Surgical). Emerging AI-optimized advancements are subsequently discussed, including low-dose intraoperative CT protocols, expanded scan windows, metal artifact reduction algorithms, integration of 2D fluoroscopy with preoperative CT datasets, and 3D reconstruction derived from 2D imaging. These developments aim to improve image quality, reduce radiation exposure, and enhance navigational accuracy. By synthesizing current evidence and technological progress, this review highlights how AI-enhanced imaging systems are redefining intraoperative spine surgery and shaping the future of precision-based care. The primary purpose of this review is to outline the applications of AI and its potential for perioperative and intraoperative optimization, including radiation exposure reduction, workflow streamlining, preoperative planning, robot-assisted surgery, and navigation. The secondary purpose is to define AI, machine learning, and deep learning within the medical context, describe image and pathology recognition, and provide a historical overview of AI in orthopedic spine surgery. Full article

The COVID-19 pandemic highlighted both the transformative potential of mRNA vaccines and the structural challenges associated with their supply chains. Unlike traditional vaccine platforms, mRNA vaccines depend on highly specialized raw materials, including plasmid DNA (pDNA), nucleotides, enzymes, and lipid nanoparticles (LNP), that are produced by a limited number of global suppliers. These dependencies, combined with platform-specific manufacturing processes and stringent cold chain requirements, introduce vulnerabilities across production, distribution, and regulatory oversight. This narrative review examines the distinctive features of mRNA vaccine supply chains and identifies key challenges and opportunities across three interconnected domains: manufacturing systems, logistics and distribution, and regulatory governance. Drawing on literature published between January 2021 and March 2026, the review synthesizes evidence on supply chain bottlenecks revealed during the COVID-19 pandemic, including upstream raw-material dependencies, limitations in manufacturing scale-up, cold chain constraints, and regulatory fragmentation. Particular attention is given to the implications of these challenges for low- and middle-income countries, where infrastructure, technical capacity, and regulatory resources may limit participation in mRNA vaccine production and deployment. The review also highlights emerging strategies to strengthen supply chain resilience, including diversification of input suppliers, development of regional manufacturing hubs, improvements in vaccine thermostability, regulatory harmonization initiatives, and the use of digital technologies for supply chain management. By integrating insights from manufacturing, logistics, and regulatory perspectives, this study contributes to a better understanding of the structural characteristics shaping mRNA vaccine supply chains and identifies priority areas for strengthening global preparedness for future health emergencies. Full article