Search Results (5,500)

Flexible sensors have emerged as essential components in next-generation technologies such as wearable electronics, smart healthcare, soft robotics, and human–machine interfaces, owing to their outstanding mechanical flexibility and multifunctional sensing capabilities. Despite significant advancements, challenges such as the trade-off between sensitivity and detection range, and poor signal stability under cyclic deformation remain unresolved. To overcome the aforementioned limitations, this work introduces a high-performance soft sensor featuring a dual-layered electrode system, comprising silver nanoparticles (AgNPs) and a composite of multi-walled carbon nanotubes (MWCNTs) with carbon black (CB), coupled with a laser-engraved crack-gradient microstructure. This structural strategy facilitates progressive crack formation under applied strain, thereby achieving enhanced sensitivity (1.56 kPa⁻¹), broad operational bandwidth (50–600 Hz), fine frequency resolution (0.5 Hz), and a rapid signal response. The synergistic structure also improves signal repeatability, durability, and noise immunity. The sensor demonstrates strong applicability in health monitoring, motion tracking, and intelligent interfaces, offering a promising pathway for reliable, multifunctional sensing in wearable health monitoring, motion tracking, and soft robotic systems. Full article

Design Thinking (DT) has emerged as a relevant methodology for addressing global challenges aligned with the United Nations Sustainable Development Goals (SDGs). This study presents a systematic literature review, conducted following PRISMA 2020 guidelines, which analyzes 42 peer-reviewed publications from 2013 to 2023. Through inductive content analysis, 10 core DT principles—such as empathy, iteration, user-centeredness, and systems thinking—I identified and thematically mapped to specific SDGs, including goals related to health, education, innovation, and climate action. The study also presents five real-world cases from diverse sectors such as technology, healthcare, and urban planning, illustrating how DT has been applied to address practical challenges aligned with the SDGs. However, the review identifies persistent gaps in the field: the lack of standardized evaluation frameworks, limited integration across SDG domains, and weak adaptation of ethical and contextual considerations, particularly in vulnerable communities. As a response, this paper recommends the adoption of structured impact assessment tools (e.g., Cities2030, Responsible Design Thinking), integration of design justice principles, and the development of participatory, iterative ecosystems for innovation. By offering both conceptual synthesis and applied insights, this article positions Design Thinking as a strategic and systemic approach for driving sustainable transformation aligned with the 2030 Agenda. Full article

Sensor selection in IoT-based smart healthcare systems is a complex fuzzy decision-making problem due to the presence of numerous uncertain and interdependent evaluation criteria. Traditional fuzzy multi-criteria decision-making (MCDM) approaches often assume independence among criteria and rely on aggregation operators that impose sharp transitions between preference levels. These assumptions can lead to decision outcomes with insufficient differentiation, limited discriminatory capacity, and potential issues in consistency and sensitivity. To overcome these limitations, this study proposes a novel fuzzy decision-making framework by integrating Quasi-D-Overlap functions into the fuzzy MARCOS (Measurement of Alternatives and Ranking According to Compromise Solution) method. Quasi-D-Overlap functions represent a generalized extension of classical overlap operators, capable of capturing partial overlaps and interdependencies among criteria while preserving essential mathematical properties such as associativity and boundedness. This integration enables a more intuitive, flexible, and semantically rich modeling of real-world fuzzy decision problems. In the context of real-time health monitoring, a case study is conducted using a hybrid edge–cloud architecture, involving sensor tasks such as heartrate monitoring and glucose level estimation. The results demonstrate that the proposed method provides greater stability, enhanced discrimination, and improved responsiveness to weight variations compared to traditional fuzzy MCDM techniques. Furthermore, it effectively supports decision-makers in identifying optimal sensor alternatives by balancing critical factors such as accuracy, energy consumption, latency, and error tolerance. Overall, the study fills a significant methodological gap in fuzzy MCDM literature and introduces a robust fuzzy aggregation strategy that facilitates interpretable, consistent, and reliable decision making in dynamic and uncertain healthcare environments. Full article

The relationship between metabolic dysfunction and mental health disorders is complex and has received increasing attention. This review integrates current research to explore how stress-related growth differentiation factor 15 (GDF15) signaling, ceramides derived from gut microbiota, and mitochondrial dysfunction in the brain interact to influence both metabolic and psychiatric conditions. Evidence suggests that these pathways converge to regulate brain energy homeostasis through feedback mechanisms involving the autonomic nervous system and the hypothalamic–pituitary–adrenal axis. GDF15 emerges as a key stress-responsive biomarker that links peripheral metabolism with brainstem GDNF family receptor alpha-like (GFRAL)-mediated anxiety circuits. Meanwhile, ceramides impair hippocampal mitochondrial function via membrane incorporation and disruption of the respiratory chain. These disruptions may contribute to sustained pathological states such as depression, anxiety, and cognitive dysfunction. Although direct mechanistic data are limited, integrating these pathways provides a conceptual framework for understanding metabolic–psychiatric comorbidities. Furthermore, differences in age, sex, and genetics may influence these systems, highlighting the need for personalized interventions. Targeting mitochondrial function, GDF15-GFRAL signaling, and gut microbiota composition may offer new therapeutic strategies. This integrative perspective helps conceptualize how metabolic and psychiatric mechanisms interact for understanding the pathophysiology of metabolic and psychiatric comorbidities and highlights therapeutic targets for precision medicine. Full article

Highly pathogenic avian influenza (HPAI) remains a persistent threat to global poultry production and public health. Current vaccine platforms show limited cross-clade efficacy and often fail to induce mucosal immunity. Recent advances in microbiome research reveal critical roles for gut commensals in modulating vaccine-induced immunity, including enhancement of mucosal IgA production, CD8⁺ T-cell activation, and modulation of systemic immune responses. Engineered commensal bacteria such as Lactococcus lactis, Bacteroides ovatus, Bacillus subtilis, and Staphylococcus epidermidis have emerged as promising live vectors for antigen delivery. Postbiotic and synbiotic strategies further enhance protective efficacy through targeted modulation of the gut microbiota. Additionally, artificial intelligence (AI)-driven tools enable predictive modeling of host–microbiome interactions, antigen design optimization, and early detection of viral antigenic drift. These integrative technologies offer a new framework for mucosal, broadly protective, and field-deployable vaccines for HPAI control. However, species-specific microbiome variation, ecological safety concerns, and scalable manufacturing remain critical challenges. This review synthesizes emerging evidence on microbiome–immune crosstalk, commensal vector platforms, and AI-enhanced vaccine development, emphasizing the urgent need for One Health integration to mitigate zoonotic adaptation and pandemic emergence. Full article

Despite the widespread accessibility of vaccines and antivirals, seasonal influenza virus epidemics continue to pose a threat to public health. In this study, we constructed a recombinant replication-deficient simian adenovirus type 25 vector carrying the full-length hemagglutinin (HA) of the H1N1 influenza virus, named rSAd25-H1. Both systemic and mucosal humoral immune responses, as well as the protective efficacy, were assessed in mice immunized via the intramuscular (IM) or intranasal (IN) route. A single-dose IM or IN administration of rSAd25-H1 elicited a robust systemic IgG antibody response, including hemagglutination inhibition antibodies. As expected, only IN immunization was able to induce IgA production in serum and respiratory mucosa. Notably, a single dose of rSAd25-H1 at the highest dose (10¹⁰ viral particles) conferred complete protection against lethal homologous H1N1 challenge in mice despite the route of administration. These findings demonstrate the potential of simian adenovirus type 25-based vectors as a promising candidate for intranasal vaccine development targeting respiratory pathogens. Full article

This paper presents a distributed measurement system intended to effectively monitor the health status of switchgears under varying temperature conditions. In particular, thermocouples are deployed as temperature sensors for the continuous monitoring of a medium-voltage (MV) switchgear. Then, by integrating a low-cost microcontroller unit, the proposed system can implement previously trained unsupervised learning techniques for health status evaluation. This approach enables the early detection of potential faults by identifying anomalous temperature patterns, thus supporting predictive maintenance and extending the lifespan of switchgears. The results show strong clustering performance with low execution times, highlighting the suitability of the method for resource-constrained hardware. Furthermore, onboard temperature processing eliminates the need for data transmission to remote servers, reducing latency and communication overhead while improving system responsiveness. The paper includes a numerical analysis on synthetic data as well as a validation on real measurements. Overall, the presented distributed measurement system offers a scalable and cost-effective solution to enhance the reliability and safety of MV switchgears. Full article

Fumonisins, primarily produced by Fusarium spp. and Aspergillus section nigri, are common contaminants in maize, cereal grains, and other processed and derived products, representing a significant risk to food safety and public health. This study presents the development and optimisation of a high-performance liquid chromatography method with fluorescence detection (HPLC-FLD) for the quantification of fumonisin B1 (FB1) and B2 (FB2) in various food matrices. In contrast with conventional protocols employing potassium phosphate buffers as the mobile phase, the proposed method utilises formic acid, offering enhanced compatibility with liquid chromatography systems. An automated online precolumn derivatisation with o-phthaldialdehyde (OPA) was optimised through experimental design and response surface methodology, enabling baseline separation of FB1 and FB2 derivatives in less than 20 min. The method demonstrated high sensitivity, with limits of detection of 0.006 µg mL⁻¹ for FB1 and 0.012 µg mL⁻¹ for FB2, and excellent repeatability (intraday RSD values of 0.85% and 0.83%, respectively). Several solid-phase extraction (SPE) strategies were evaluated to enhance sample clean-up using a variety of food samples, including dried figs, raisins, dates, corn, cornmeal, wheat flour, and rice. FumoniStar Inmunoaffinity columns were the only clean-up method that provided optimal recoveries (70–120%) across all tested food matrices. However, the MultiSep™ 211 column yielded good recoveries for both fumonisins in dried figs and raisins. Additionally, the C18 cartridge achieved acceptable recoveries for both fumonisins in dried figs and wheat flour. Full article

The extensive use of pesticides has significant implications for public health and the environment. Breeding crop plants is the most effective and environmentally friendly approach to improve the plants’ resistance. However, it is time-consuming and costly, and it is sometimes difficult to achieve satisfactory results. Plants induce defense responses to natural elicitors by interpreting multiple genes that encode proteins, including enzymes, secondary metabolites, and pathogenesis-related (PR) proteins. These responses characterize systemic acquired resistance. Humic substances trigger positive local and systemic physiological responses through a complex network of hormone-like signaling pathways and can be used to induce biotic and abiotic stress resistance. This study aimed to assess the effect of humic substances on the activity of phenylalanine ammonia-lyase (PAL), peroxidase (POX), and β-1,3-glucanase (GLU) used as a resistance marker in various plant species, including orange, coffee, sugarcane, soybeans, maize, and tomato. Seedlings were treated with a dilute aqueous suspension of humic substances (4 mM C L⁻¹) as a foliar spray or left untreated (control). Leaf tissues were collected for enzyme assessment two days later. Humic substances significantly promoted the systemic acquired resistance marker activities compared to the control in all independent assays. Overall, all enzymes studied in this work, PAL, GLUC, and POX, showed an increase in activity by 133%, 181%, and 149%, respectively. Among the crops studied, citrus and coffee achieved the highest activity increase in all enzymes, except for POX in coffee, which showed a decrease of 29% compared to the control. GLUC exhibited the highest response to HS treatment, the enzyme most prominently involved in increasing enzymatic activity in all crops. Plants can improve their resistance to pathogens through the exogenous application of HSs as this promotes the activity of enzymes related to plant resistance. Finally, we consider the potential use of humic substances as a natural chemical priming agent to boost plant resistance in agriculture Full article

The rapid growth of electric vehicles (EVs) and new energy systems has put lithium-ion batteries at the center of the clean energy change. Nevertheless, to achieve the best battery performance, safety, and sustainability in many changing circumstances, major innovations are needed in Battery Management Systems (BMS). This review paper explores how artificial intelligence (AI) and digital twin (DT) technologies can be integrated to enable the intelligent BMS of the future. It investigates how powerful data approaches such as deep learning, ensembles, and models that rely on physics improve the accuracy of predicting state of charge (SOC), state of health (SOH), and remaining useful life (RUL). Additionally, the paper reviews progress in AI features for cooling, fast charging, fault detection, and intelligible AI models. Working together, cloud and edge computing technology with DTs means better diagnostics, predictive support, and improved management for any use of EVs, stored energy, and recycling. The review underlines recent successes in AI-driven material research, renewable battery production, and plans for used systems, along with new problems in cybersecurity, combining data and mass rollout. We spotlight important research themes, existing problems, and future drawbacks following careful analysis of different up-to-date approaches and systems. Uniting physical modeling with AI-based analytics on cloud-edge-DT platforms supports the development of tough, intelligent, and ecologically responsible batteries that line up with future mobility and wider use of renewable energy. Full article

Family empowerment is a key component of effective family-centered practices in healthcare, mental health, and educational services. The Family Empowerment Scale (FES) is the most commonly used instrument to evaluate empowerment in families raising children with emotional, behavioral, or developmental disorders. Despite its importance, the FES for diverse populations, especially Latinx parents, has rarely been evaluated using innovative psychometric approaches. In this study, we evaluated key dimensions and psychometric evidence of the Family Empowerment Scale (FES) for 96 Latinx parents of children with intellectual and developmental disabilities (IDD) in the United States using an exploratory graph analysis (EGA). The EGA identified a five-dimensional structure, and EGA models outperformed the original CFA 3-factor models for both parents of children with autism and other disabilities. This study identified distinct, meaningful dimensions of empowerment that reflect both shared and unique empowerment experiences across two Latinx parent groups. These insights can inform the design of culturally responsive interventions, instruments, and policies that more precisely capture and boost empowerment in Latinx families. This study contributes to closing a gap in the literature by elevating the voices and experiences of Latinx families by laying the groundwork for more equitable support systems in special education and disability services. Full article

Ultrafine bubbles (UFBs) represent an emerging technology with unique physicochemical properties. This study investigated the effects of air-filled UFBs infused in drinking water on gut microbiota composition and the associated health markers in Sprague Dawley rats over a 12-week period. Using a two-phase design, UFB concentration was increased from 1.7 × 10⁶ to 6.5 × 10⁹ UFBs/mL at week 7 to assess dose-dependent effects. Administration of UFBs in drinking water induced significant shifts in gut microbiome populations, characterized by increased Bacteroidetes (+122% weeks 8–12) and decreased Firmicutes (−43% weeks 8–12) compared to controls. These microbial shifts coincided with enhanced short-chain fatty acid production (butyrate +56.0%, p ≤ 0.001; valerate +63.1%, p ≤ 0.01) and reduced inflammatory markers (TNF-α −84.0%, p ≤ 0.05; IL-1β −41.0%, p ≤ 0.05; IL-10 −69.8%, p ≤ 0.05). UFB effects demonstrated systematic concentration-dependent threshold responses, with 85.7% of parameters exhibiting directional reversals between low (1.7 × 10⁶ UFBs/mL) and high (6.5 × 10⁹ UFBs/mL) concentration phases rather than linear dose–response relationships. The systematic nature of these threshold effects, with 71.4% of parameters achieving statistical significance (p ≤ 0.05), indicates concentration-dependent biological mechanisms rather than random effects on gut biology. Despite current metagenomic techniques identifying only 25% of the total gut microbiome, the observed changes in characterized species and metabolites demonstrate UFB technology’s therapeutic potential for conditions requiring microbiome modulation, providing new insights into UFB influence on complex biological systems. Full article

Autism Spectrum Disorder (ASD) is frequently accompanied by gastrointestinal disturbances, dietary selectivity, and altered stress responses, with growing evidence pointing to gut–brain axis involvement. While intestinal microbiota has been extensively studied, the role of the oral microbiota remains underexplored. This study investigates the associations between oral microbiota composition and behavioral, gastrointestinal, dietary, and neuroendocrine parameters in children with ASD. A total of 45 children aged 2–18 years comprised the study group. Data collection included oral swabs for 16S rRNA gene sequencing, salivary cortisol sampling, dietary records, and standardized behavioral assessments using the Vineland Adaptive Behavior Scale. A total of 363 microbial species across 11 phyla were identified. Significant correlations were observed between specific bacterial taxa and functional gastrointestinal disorders (FGIDs), dietary patterns, salivary cortisol rhythms, and functioning. Children with FGIDs, food selectivity, or macronutrient imbalances exhibited enriched pro-inflammatory taxa (e.g., Selenomonas, Megasphaera), whereas those with typical cortisol secretion or higher adaptive functioning showed greater microbial diversity and abundance of health-associated genera (e.g., Bifidobacterium dentium). These findings suggest that oral microbiota profiles may reflect systemic physiological and neurobehavioral traits in children with ASD. Further longitudinal studies are needed to clarify causal relationships and support the development of microbiota-targeted interventions. Full article

Cervical cancer represents a significant global health challenge. Photodynamic therapy (PDT) appears to be a promising, minimally invasive alternative to standard treatments. However, the clinical efficacy of PDT is sometimes limited by the low solubility and aggregation of photosensitizers, their non-selective distribution in the body, hypoxia in the tumor microenvironment, and limited light penetration. Recent advances in nanoparticle and nanocomposite platforms have addressed these challenges by integrating multiple functional components into a single delivery system. By encapsulating or conjugating photosensitizers in biodegradable matrices, such as mesoporous silica, organometallic structures and core–shell construct nanocarriers increase stability in water and extend circulation time, enabling both passive and active targeting through ligand decoration. Up-conversion and dual-wavelength responsive cores facilitate deep light conversion in tissues, while simultaneous delivery of hypoxia-modulating agents alleviates oxygen deprivation to sustain reactive oxygen species generation. Controllable “motor-cargo” constructs and surface modifications improve intratumoral diffusion, while aggregation-induced emission dyes and plasmonic elements support real-time imaging and quantitative monitoring of therapeutic response. Together, these multifunctional nanosystems have demonstrated potent cytotoxicity in vitro and significant tumor suppression in vivo in mouse models of cervical cancer. Combining targeted delivery, controlled release, hypoxia mitigation, and image guidance, engineered nanoparticles provide a versatile and powerful platform to overcome the current limitations of PDT and pave the way toward more effective, patient-specific treatments for cervical malignancies. Our review of the literature summarizes studies on nanoparticles and nanocomposites used in PDT monotherapy for cervical cancer, published between 2023 and July 2025. Full article

Cancer is a major global health issue, with rising incidence rates highlighting the urgent need for more effective treatments. Despite advances in cancer therapy, challenges such as adverse effects and limitations of existing treatments remain. Immunotherapy, which harnesses the body’s immune system to target cancer cells, offers promising solutions. Gamma delta (γδ) T cells are noteworthy due to their potent ability to kill various cancer cells without needing conventional antigen presentation. Recent studies have focused on the role of γδ T cells in α-galactosylceramide (α-GalCer)-mediated immunity, opening new possibilities for cancer immunotherapy. We engineered humanized T cell receptor (HuTCR)-T1 γδ mice by replacing mouse sequences with human counterparts. This study investigates the cytotoxic activity of humanized γδ T cells against several human cancer cell lines (A431, HT-29, K562, and Daudi) in vitro, aiming to elucidate mechanisms underlying their anticancer efficacy. Human cancer cells were co-cultured with humanized γδ T cells, with and without α-GalCer, for 24 h. The humanized γδ T cells showed enhanced cytotoxicity across all tested cancer cell lines compared to wild-type γδ T cells. Additionally, γδ T cells from HuTCR-T1 mice exhibited higher levels of anticancer cytokines (IFN-γ, TNF-α, and IL-17) and Granzyme B, indicating their potential as potent mediators of anticancer immune responses. Blocking γδ T cells’ cytotoxicity confirmed their γδ-mediated function. These findings represent a significant step in preclinical development of γδ T cell-based cancer immunotherapies, providing insights into their mechanisms of action, optimization of therapeutic strategies, and identification of predictive biomarkers for clinical application. Full article