Search Results (52,993)

Colorectal cancer (CRC) remains one of the leading causes of cancer-related mortality worldwide. Compared with traditional two-dimensional (2D) models, patient-derived CRC organoids more faithfully preserve the genomic, transcriptomic, and architectural features of primary tumors, making them a powerful intermediate platform bridging basic discovery and clinical translation. Over the past several years, organoid systems have rapidly expanded beyond conventional epithelial-only cultures toward increasingly complex architectures, including immune-organoid co-culture models and mini-colon systems that enable long-term, spatially resolved tracking of tumor evolution. These advanced platforms, combined with high-throughput technologies and clustered regularly interspaced short palindromic repeats (CRISPR)-based functional genomics, have substantially enhanced our ability to dissect CRC mechanisms, identify therapeutic vulnerabilities, and evaluate drug responses in a physiologically relevant context. However, current models still face critical limitations, such as the lack of systemic physiology (e.g., gut–liver or gut–brain axes), limited standardization across platforms, and the need for large-scale, prospective clinical validation. These gaps highlight an urgent need for next-generation platforms and computational frameworks. The development of high-throughput multi-omics, CRISPR-based perturbation, drug screening technologies, and artificial intelligence-driven predictive approaches will offer a promising avenue to address these challenges, accelerating mechanistic studies of CRC, enabling personalized therapy, and facilitating clinical translation. In this perspective, we propose a roadmap for CRC organoid research centered on two major technical pillars: advanced organoid platforms, including immune co-culture and mini-colon systems, and mechanistic investigations leveraging multi-omics and CRISPR-based functional genomics. We then discuss translational applications, such as high-throughput drug screening, and highlight emerging computational and translational strategies that may support future clinical validation and precision medicine. Full article

To meet the requirements of non-mechanical beam scanning and acquisition in space laser communication, this study proposes a two-dimensional scanning and acquisition method based on a silicon-based optical phased array (OPA). The OPA utilizes thermo-optic phase modulation to achieve horizontal beam pointing, while vertical beam pointing is controlled by wavelength tuning. By combining the OPA with a rectangular spiral scanning strategy, non-mechanical scanning is realized and beam acquisition experiments are carried out. Experimental results demonstrate that for an 8° step signal, the horizontal and vertical rise times are 156.8 μs and 214.76 ms, respectively. A full scan of 440 points covering a ±4° field of view is completed in 8.119 s. Acquisition experiments were conducted assuming a Gaussian-distributed uncertainty region (standard deviation σ = 1°). Out of 106 independent trials, a success rate of 97.17% was achieved with an average acquisition time of 0.41 s. This work experimentally applies a rectangular spiral scanning strategy to an OPA-based acquisition system, addressing a capability that has been largely missing in previous studies. These results verify that the OPA technology has good scanning efficiency and acquisition robustness in space laser communication applications. Full article

Optical frames are used worldwide to correct visual impairments, protect from UV damage, or simply for fashion purposes. Optical frames are often made of poorly biodegradable and fossil-based materials, with designs not targeted to everyone’s tastes and requirements. Additive manufacturing processes allow personalisation of optical frames and the use of new sustainable biomaterials to replace fossil-based ones. This comprehensive review combines an extensive survey of the scientific literature, market trends, and information from other relevant sources, analysing the biomaterials currently used in additive manufacturing and identifying biomaterials (biopolymers, natural fibres, and natural additives) with the potential to be developed into biocomposites for printing optical frames. Requirements for optical devices were carefully considered, such as standards, regulations, and demands for manufacturing materials. By comparing with fossil-based analogues and by discussing the chemical, physical, and mechanical properties of each biomaterial, it was found that combining various materials in biocomposites is promising for achieving the desirable properties for printing optical frames. The advantages of the various techniques of this cutting-edge technology were also analysed and discussed for optical industry applications. This study aims to answer the central research question: which biopolymers and biocomposite constituents (natural fibres, plasticisers, and additives) have the ideal mechanical, thermal, physical, and chemical properties for combining into a biomaterial suitable for producing sustainable, customisable, and inclusive optical frames on demand, using additive manufacturing techniques. Full article

Solar energy is a widely available renewable source suitable for diverse applications, including residential, industrial and aerospace sectors. To maximize energy capture, solar tracking systems adjust panels to maintain perpendicular alignment with sunlight. Various tracking techniques are employed to adjust these trackers, such as sensors, predefined algorithms, deep learning, and image-processing techniques. Image processing-based trackers have gained prominence for their precision and accuracy. This approach uses cameras as sensors to capture real-time sky images and analyze them to detect the sun and its coordinates, orienting solar panels toward its center. This technology can be integrated with other techniques to enhance energy output with high accuracy, minimal tracking error, and low maintenance requirements. This review examines computer vision methods used in solar tracking systems, synthesizing findings from 26 studies published between 2009 and 2024. The paper discusses main system components, methods utilized, and results obtained. Findings demonstrate that the robustness and accuracy of these tracking systems have increased compared to other tracking systems, while tracking error has decreased. Full article

Regenerative medicine is increasingly leveraging the synergies between bioinspired conductive biomaterials and 3D/4D bioprinting to replicate the native electroactive and hierarchical microenvironments essential for functional tissue restoration. However, a critical gap remains in the intelligent integration of these technologies to achieve dynamic, responsive tissue regeneration. This review introduces a “bioinspired material–printing–function” triad framework to systematically synthesize recent advances in: (1) tunable conductive materials (polymers, carbon-based systems, metals, MXenes) designed to mimic the electrophysiological properties of native tissues; (2) advanced 3D/4D printing technologies (vat photopolymerization, extrusion, inkjet, and emerging modalities) enabling the fabrication of biomimetic architectures; and (3) functional applications in neural, cardiac, and musculoskeletal tissue engineering. We highlight how bioinspired conductive scaffolds enhance electrophysiological behaviors—emulating natural processes such as promoting axon regeneration cardiomyocyte synchronization, and osteogenic mineralization. Crucially, we identify multi-material 4D bioprinting as a transformative bioinspired approach to overcome conductivity–degradation trade-offs and enable shape-adaptive, smart scaffolds that dynamically respond to physiological cues, mirroring the adaptive nature of living tissues. This work provides the first roadmap toward intelligent electroactive regeneration, shifting the paradigm from static implants to dynamic, biomimetic bioelectronic microenvironments. Future translation will require leveraging AI-driven bioinspired design and organ-on-a-chip validation to address challenges in vascularization, biosafety, and clinical scalability. Full article

The use of instruments for recording neurophysiological metrics is increasingly prevalent in natural settings, driven by advances in portability, reduced invasiveness, and the advantages these technologies offer for objective assessment of cognitive processes. A key application is the investigation of cognitive processes underlying human learning. In this context, the use of electroencephalography (EEG) in educational settings has grown in recent years. This systematic review examines how EEG has been utilized over the past decade to study teaching and learning processes in higher education. Its objectives were to identify the purposes for which EEG has been employed, its integration with other instruments, the cognitive processes analyzed, and the main findings reported. Bibliographic sources included Scopus and Web of Science databases. Results indicate that EEG has been primarily used to investigate attention, memory, and cognitive load, often combined with other neurophysiological and behavioral instruments. This integration provides objective insights into learning while highlighting methodological limitations and the need for standardized approaches. Despite variations in study designs, devices, and analytical methods, EEG demonstrates substantial potential for exploring cognitive processes in both face-to-face and virtual learning environments. In conclusion, EEG is an effective tool for investigating learning-related cognitive processes in higher education, providing objective data to guide future research, and the development of innovative educational programs. This review offers a comprehensive overview of current research, supports the design of evidence-based educational strategies, and lays the groundwork for future studies aiming to enhance learning outcomes through neurophysiological methods. Full article

This study examines how AI development and the labor force’s gender structure jointly influence female employment and female’s economic contributions from a dual-sector firm–household perspective. Using panel data from 58 countries spanning 2000–2022, we construct a theoretical model and conduct empirical tests. Results indicate that the labor force’s gender imbalance significantly suppresses the scale of female employment and female economic contributions; at the current stage, AI generally exerts a negative impact on female employment and economic contributions, but exhibits a significant interaction with the labor force gender structure. In scenarios of severe gender imbalance, AI’s skill-restructuring effect partially mitigates these adverse impacts; AI also generates a limited “time-release effect” by reducing women’s time spent on household labor, indirectly promoting female employment. The gendered effects of AI exhibit pronounced institutional variations across different developmental stages and gender structure conditions. This study emphasizes that AI is not a gender-neutral technology; its fairness depends on institutional and structural environments. Accordingly, it proposes policy recommendations, including improving multi-tiered systems for female talent development, guiding gender-inclusive AI applications, and strengthening global gender–governance cooperation. Full article

Background: Assistive technologies (ATs) for individuals with tetraplegia have evolved from mechanical aids to complex neurotechnological, digital, and psychosocial systems. However, the evidence base remains fragmented, with heterogeneous methodologies and limited integration across domains. This review synthesizes recent review-level evidence to clarify current trends, gaps, and directions in ATs for tetraplegia. Methods: A narrative review of reviews was conducted following the ANDJ checklist. PubMed and Scopus were searched for systematic, scoping, and narrative reviews addressing assistive technologies relevant to tetraplegia. After screening, de-duplication, and quality appraisal, 20 reviews were included and synthesized narratively. Results: The included reviews clustered into four main domains: neural and regenerative interfaces, motor and biomechanical assistive systems, digital and adaptive rehabilitation ecosystems, and psychosocial and integrative frameworks. Across domains, evidence highlights a shift toward personalized, adaptive, and interoperable systems, supported by neurotechnologies, robotics, mobile health, and virtual reality. Common limitations include heterogeneous outcome measures, scarcity of longitudinal evidence, limited system interoperability, and persistent inequities in access and adoption. Emerging applications of artificial intelligence support adaptive control, monitoring, and personalization, though robust clinical validation remains limited. Conclusions: This synthesis provides a structured overview of review-level evidence on assistive technologies for tetraplegia. The findings underscore the need for coordinated, multidisciplinary approaches and more rigorous, longitudinal evaluation to support the development of inclusive, human-centered, and interoperable assistive ecosystems. Full article

Lignin, the most abundant renewable source of aromatic compounds, plays a pivotal role in advancing sustainable biorefineries and reducing dependence on fossil resources. Recent progress in integrated lignin valorization pathways has unlocked opportunities to convert this complex biopolymer into high-value chemicals, materials, and energy carriers, despite its structural heterogeneity and recalcitrance posing major challenges. This review highlights the significant advancements in depolymerization strategies, including catalytic, oxidative, and biological approaches, which are reinforced by innovations in catalyst design and reaction engineering that enhance selectivity and efficiency. It also discusses emerging technologies, such as hybrid chemo-enzymatic systems, solvent fractionation, and continuous-flow reactors, for their potential to improve scalability and sustainability. Furthermore, this review examines the integration of lignin valorization with upstream pretreatment and downstream recovery, emphasizing process intensification, co-product synergy, and techno-economic optimization to achieve commercial viability. Despite these developments, critical gaps remain in understanding the molecular complexity of lignin, developing universally applicable catalytic systems, and optimizing economic and environmental performance. To guide future research, it poses two key questions: how to design catalysts for selective depolymerization across diverse lignin sources, and how to configure biorefineries for maximum lignin utilization while ensuring sustainability? Addressing these challenges will be essential for lignin’s role in next-generation biorefineries and a circular bioeconomy. Full article

Objectives: The purpose of the current research is to examine and analyze the attitudes of healthcare service users towards the integration of remote medical services into ophthalmology in Bulgaria, including teleglaucoma. Methods: A cross-sectional survey study was conducted among 902 healthcare users during the period from May 2023 until December 2024. Descriptive statistics, parametric, and non-parametric tests for hypothesis testing were used. Results: The present study outlined predominantly positive attitudes towards the use of telemedicine services in ophthalmology, with 69.6% of respondents reporting a positive overall opinion in the final assessment. The greatest support was observed during remote consultations with a familiar doctor (77.4%) and during continuous follow-up of eye conditions (55.2%). Willingness to use such services was lower in emergencies or when contacting an unfamiliar specialist. A significant correlation was established between socio-demographic characteristics and attitudes—respondents with greater education levels (p = 0.006), men, and younger participants were more positive towards telemedicine (p < 0.05). The high level of awareness about glaucoma, particularly among those with university-level education, served as a positive prerequisite for the implementation of teleophthalmology services related to its monitoring. Mobile applications and digital solutions were evaluated as beneficial means of facilitating communication and increasing adherence to treatment. Regarding the use of artificial intelligence, certain skepticism and insufficient awareness levels were observed, which required additional efforts to increase trust and digital literacy among users. Conclusions: The implementation of telemedicine services into ophthalmology has potential but outlines the necessity of considering the individual attitudes of applying coherent quality and safety standards and of directed awareness campaigns, especially towards the groups of lower technological and healthcare literacy. Full article

Lanthanide coordination polymers have been developed at a fast rate during the past two decades due to their appealing applications in the modern field of materials science and emerging technologies like luminescence, magnetism, sensing, gas adsorption, and catalysis. The role of lanthanides in imparting specific properties to the coordination polymers has been fully documented in extensive studies carried out by numerous research groups. It has been shown that because lanthanide(III) ions possess a variable coordination number, they readily build two-dimensional and three-dimensional architectures with definite channels, permanent pores, and distinct surface areas. Due to their strong oxophilic propensity and hard Lewis acid character, lanthanides favor the construction of stable coordination polymers and MOF configurations by strongly binding the coordinating groups of the organic linkers. Associated with palladium complexes, the lanthanide ions provide synergistic effects with Lewis acid sites, beneficial to the catalytic activity. These attractive characteristics of lanthanides enabled them to be fruitfully applied in Pd-Ln coordination polymers with catalytic properties. This review covers an array of Pd-Ln coordination polymers applied as heterogeneous catalysts in Suzuki–Miyaura C(sp²)-C(sp²) cross-coupling reactions. The activity and chemoselectivity of Pd(II) ions and Pd nanoparticles associated in coordination polymers with different lanthanides from a selected array of rare earth elements (Eu, Sm, Eu, Gd, Pr, Nd, Ce, La, or Tb) is discussed. High yields (>99%) are attained under optimized reaction conditions. The specific role of lanthanides and organic ligands in creating sustainable and recyclable heterogeneous Pd catalysts is evidenced. Mechanistic aspects of the C(sp²)-C(sp²) cross-coupling reactions are considered. The synergistic interaction between lanthanides and palladium as well as with the organic ligands is highlighted. Full article

Background/Objectives: Artificial intelligence (AI) has gained substantial prominence in pediatric dentistry, offering new opportunities to enhance diagnostic precision and clinical decision-making. AI-based systems are increasingly applied in caries detection, early childhood caries (ECC) risk prediction, tooth development assessment, mesiodens identification, and other key diagnostic tasks. This systematic review and meta-analysis aimed to synthesize evidence on the diagnostic performance of AI models developed specifically for pediatric dental applications. Methods: A systematic search was conducted in PubMed, Scopus, Web of Science, and Embase following PRISMA-DTA guidelines. Studies evaluating AI-based diagnostic or predictive models in pediatric populations (≤18 years) were included. Reference screening, data extraction, and quality assessment were performed independently by two reviewers. Pooled sensitivity, specificity, and area under the receiver operating characteristic curve (AUC) were calculated using random-effects models. Sources of heterogeneity related to imaging modality, annotation strategy, and dataset characteristics were examined. Results: Thirty-two studies met the inclusion criteria for qualitative synthesis, and fifteen were eligible for quantitative analysis. For radiographic caries detection, pooled sensitivity, specificity, and AUC were 0.91, 0.97, and 0.98, respectively. Prediction models demonstrated good diagnostic performance, with pooled sensitivity of 0.86, specificity of 0.82, and AUC of 0.89. Deep learning architectures, particularly convolutional neural networks, consistently outperformed traditional machine learning approaches. Considerable heterogeneity was identified across studies, primarily driven by differences in imaging protocols, dataset balance, and annotation procedures. Beyond quantitative accuracy estimates, this review critically evaluates whether current evidence supports meaningful clinical translation and identifies pediatric domains that remain underrepresented in AI-driven diagnostic innovation. Conclusions: AI technologies exhibit strong potential to improve diagnostic accuracy in pediatric dentistry. However, limited external validation, methodological variability, and the scarcity of prospective real-world studies restrict immediate clinical implementation. Future research should prioritize the development of multicenter pediatric datasets, harmonized annotation workflows, and transparent, explainable AI (XAI) models to support safe and effective clinical translation. Full article

Metalloprotein-based nanomedicines integrate the multifunctionality of metal centers with the engineerability of proteins to construct advanced nanoplatforms for targeted delivery, diagnostic imaging, and multimodal therapy. In these nanomedicines, metal ions or clusters act as functional cores, enabling imaging contrast enhancement, catalytic reactions, and modulation of pathological microenvironments, while protein frameworks provide structural stability, intrinsic biocompatibility, and programmable bio-interfaces. This review summarizes the design principles of three major metalloprotein-based nanomedicines, including native metalloproteins, engineered metalloproteins, and metal–protein hybrid nanostructures, with a focus on ferritin, transferrin, and heme/cytochrome proteins in the contexts of cancer therapy, imaging diagnostics, antimicrobial, and anti-resistance applications. Through discussion of representative metal- and metalloprotein-based nanomedicine candidates, this review highlights the current challenges and outlines opportunities brought by emerging technologies such as artificial intelligence-guided protein design. Collectively, these advances underscore metal- and metalloprotein-based nanomedicines as multifunctional, tunable, and clinically promising platforms that are poised to become an important pillar of future nanomedicine. Full article

Triple-negative breast cancer (TNBC), which is characterized by a lack of the estrogen receptor, the progesterone receptor, and HER2 expression, is the most aggressive breast cancer subtype and has a poor prognosis and high recurrence rates because of frequent chemotherapy resistance. As a crucial epigenetic regulator, DNA methylation modulates gene expression through aberrant methylation patterns, contributing to tumor progression and therapeutic resistance. Early diagnosis and treatment of TNBC are vital for its prognosis. The development of DNA methylation testing technology and the application of liquid biopsy provide technological support for early diagnosis and treatment. Additionally, preclinical and early-phase clinical studies suggest that epigenetic therapies targeting DNA methylation may hold promise for TNBC treatment, pending larger clinical trials. Furthermore, research on DNA methylation-based prognostic models enables personalized precision treatment for patients, helping to reduce unnecessary therapies and improve overall survival. The emerging role of DNA methylation patterns in predicting the therapeutic response and overcoming drug resistance is highlighted. In this narrative review, we integrate current research findings and clinical perspectives. We propose that DNA methylation presents promising research prospects for the diagnosis, treatment and prognosis prediction of TNBC. Future efforts should focus on translating methylation-driven insights into clinically actionable strategies, ultimately advancing precision oncology for this challenging disease. Full article

Promoting the development of aerospace vehicles toward structural–functional integration and intelligent sensing is a key strategy for achieving lightweight, high-reliability, and autonomous operation and maintenance of next-generation aircraft. However, traditional external sensors face significant limitations because of their bulky size, installation challenges, and incompatibility with aerodynamic surfaces. These issues are particularly pronounced on complex, high-curvature substrates, where achieving conformal bonding is difficult, thus restricting their application in critical components. In this study, aerosol jet printing (AJP) was employed to directly fabricate silver nanoparticle-based temperature sensors with real-time monitoring capabilities on the surface of high-curvature stainless steel sleeves, which serve as typical engineering components. This approach enables the in situ manufacturing of high-precision conformal sensors. Through optimized structural design and thermal treatment, the sensors exhibit reliable temperature sensitivity. Microscopic characterization reveals that the printed sensors possess uniform linewidths and well-defined outlines. After gradient sintering at 250 °C, a dense and continuous conductive path is formed, ensuring strong adhesion to the substrate. Temperature-monitoring results indicate that the sensor exhibits a nearly linear resistance response (R² > 0.999) across a broad detection range of 20–200 °C. It also demonstrates high sensitivity, characterized by a temperature coefficient of resistance (TCR) of 2.15 × 10^−3/°C at 20 °C. In repeated thermal cycling tests, the sensor demonstrates excellent repeatability and stability over 100 cycles, with resistance fluctuations kept within 0.5% and negligible hysteresis observed. These findings confirm the feasibility of using AJP technology to fabricate high-performance conformal sensors on complex surfaces, offering a promising strategy for the development of intelligent structural components in next-generation aerospace engineering. Full article