Search Results (2,329)

Biodegradable magnesium (Mg)-based implants represent a paradigm shift in orthopedic biomaterials, offering temporary mechanical support, inherent osteogenic bioactivity, and elimination of hardware removal surgery. These properties are particularly attractive for sports orthopedic applications, including anterior cruciate ligament (ACL) reconstruction, rotator cuff repair, meniscal fixation, and osteochondral fragment refixation, where young, active patients demand rapid return to function and where permanent metallic hardware poses long-term risks of stress shielding, imaging artifact, and reoperation. Despite extensive preclinical evidence demonstrating that Mg-based interference screws promote fibrocartilaginous enthesis regeneration, attenuate peri-tunnel bone loss, and achieve biomechanical fixation comparable to titanium, no human clinical trial has yet evaluated Mg fixation devices for soft-tissue reconstruction in sports medicine. Meanwhile, clinical fracture fixation data from over 468 patients across multiple trials and a meta-analysis confirm complication rates equivalent to those of titanium. This narrative review synthesizes the current evidence on Mg alloy design, surface engineering strategies, preclinical sports medicine applications, clinical translation in fracture fixation, imaging compatibility, and the remaining barriers to clinical adoption in sports orthopedic surgery. By mapping the translational gap between promising animal data and the absence of clinical sports medicine trials, this review aims to guide future research priorities and accelerate the pathway toward clinical application of Mg-based devices in sports orthopedics. Full article

Gold nanoparticles (AuNPs) have attracted considerable interest as emerging CT contrast agents; however, the influence of reconstruction parameters on their quantitative detectability remains insufficiently characterized, limiting the optimization of quantitative CT imaging. This study quantitatively compared the CT imaging performance of citrate-stabilized AuNPs, PEGylated AuNPs (PEG-AuNPs), and a conventional iodinated contrast agent (BMX) under different reconstruction conditions. AuNPs were synthesized by citrate reduction and PEGylated with SH-PEG5K-COOH, followed by physicochemical characterization using dynamic light scattering, zeta potential analysis, and ICP-OES. Contrast samples (≤10 mg/mL) were imaged using a micro-CT system (50 kV, 0.43 mA) with two angular sampling intervals (0.750° and 0.500°), Gaussian and Hann reconstruction kernels, and voxel sizes of 100, 160, and 200 µm. Quantitative performance was evaluated using sensitivity, coefficient of determination (R²), background noise, limit of detection (LOD), and limit of quantification (LOQ). PEG-AuNPs exhibited the highest sensitivity (80.55 HU/mg/mL) and the lowest detection limits (LOD: 0.53 mg/mL; LOQ: 1.61 mg/mL), outperforming bare AuNPs and BMX. Voxel size was the dominant reconstruction parameter, with optimal detectability achieved at 160 µm due to an optimal balance between spatial resolution and image noise, whereas reconstruction kernel and angular sampling had comparatively minor effects. These findings provide a quantitative framework for optimizing reconstruction parameters in nanoparticle-enhanced quantitative CT imaging. Full article

Background and Objectives: Shoulder disorders—including rotator cuff disease, glenohumeral osteoarthritis (GH OA), and adhesive capsulitis—are among the most prevalent musculoskeletal conditions and are frequently refractory to conservative management. Platelet-rich plasma (PRP) and bone marrow aspirate concentrate (BMAC) have attracted increasing clinical interest as regenerative alternatives to corticosteroid injection, but a comparative appraisal of these two principal biologics across the full spectrum of shoulder pathology is lacking. Materials and Methods: This narrative review is based on structured searches of MEDLINE, Embase, Cochrane CENTRAL, and Scopus for clinical studies (randomized controlled trials [RCTs], comparative studies, and prospective series) and evidence syntheses evaluating PRP or BMAC in shoulder disorders. Studies were synthesized narratively by biologic type and disorder; no formal systematic-review or scoping-review reporting protocol was applied. Current society guidelines and consensus statements were additionally examined to position each biologic, and PRP formulation subgroups (leukocyte-rich versus leukocyte-poor) were considered. Results: PRP has the larger shoulder-specific evidence base, supported by several RCTs and meta-analyses in rotator cuff tendinopathy and in adhesive capsulitis; however, results are heterogeneous, effect sizes are generally modest, and some trials show no advantage over saline or corticosteroid. BMAC shoulder evidence is sparse and is strongest as a biological augment to rotator cuff repair (supported chiefly by a case-controlled study) rather than as a standalone injection; standalone shoulder BMAC RCTs are essentially absent. No published RCT directly compares PRP with BMAC for a shoulder disorder; the only direct randomized head-to-head comparison available is in knee osteoarthritis, where the two were reported to be equivalent at two years. Where PRP formulation was examined, leukocyte-poor preparations were associated with better structural and pain outcomes and leukocyte-rich preparations with functional gains in the surgical setting; current society guidance (e.g., the 2025 American Academy of Orthopaedic Surgeons [AAOS] rotator cuff guideline) does not endorse routine PRP use, and BMAC is not yet incorporated into shoulder guideline recommendations. Conclusions: PRP rests on a larger but still heterogeneous evidence base for shoulder disorders, whereas BMAC is biologically promising but clinically under-evidenced in the shoulder. Neither biologic is established as superior. Standardized, shoulder-specific head-to-head RCTs—incorporating biologic characterization, structural (imaging) outcomes, and longer follow-up—represent the most important research priority in this field. Full article

Tourism has become a critical pathway for town construction, everyday-life improvement, and cultural revitalization. Yet, the mechanisms through which destination image is associated with town attraction remain insufficiently understood, particularly at the fine-grained town scale. Drawing on social media photographs and check-in records from 26 characteristic towns in Tianjin, China, this study deconstructs tourist destination image into image genes and examines their associations with town gravity. A VGG19-based image-recognition model was used to identify and aggregate 68 scene types into nine image-gene categories, while check-in data from Weibo and Little Red Book were used to measure destination gravity. The results show that uniqueness image, cultural custom genes, public space genes, sidewalk density, and POI mix are significantly and positively associated with town gravity, whereas animal genes exhibit a significant negative association. These findings provide an empirical basis for policymakers and planners to strengthen distinctive cultural representation, optimize public-space systems and service diversity, and promote the sustainable attractiveness of town destinations. Full article

Chengde, China, is famous for its Qing Dynasty imperial gardens, which are a World Heritage Site. In recent years, it has received increasing attention from heritage research scholars. From a tourism perspective, tourists’ visits are important for supporting economic benefits, heritage conservation, and sustainable development. This study integrated the four dimensions of the 4E heritage communication framework—experience, exchange, everyplace, and evangelism—with heritage interpretation quality to develop a model to uncover cultural heritage visiting behavior. Based on the survey data of 887 Chinese tourists who have visited Chengde’s cultural heritage sites, structural equation modeling (SEM) was employed. The results showed that experience, exchange, everyplace, and evangelism, together with heritage interpretation quality, were all positively associated with cultural heritage visiting behavior. Perceived destination image and perceived conservation both significantly predicted cultural heritage visiting behavior and served as significant mediators in most of the proposed indirect relationships; however, the indirect path of evangelism through perceived destination image was not supported. Source credibility strengthened the relationships between the five antecedents and cultural heritage visiting behavior. Therefore, this article encourages the development of high-quality, comprehensive marketing strategies to attract more people to learn about World Cultural Heritage, while simultaneously improving guided tour services and their quality. It also emphasizes building a more positive cultural tourism image and conducting precise public relations to ensure that World Cultural Heritage receives support and attention from governments, educational institutions, and travel agencies. Full article

In recent years, multimodal medical image fusion (MMIF) has attracted significant attention due to its ability to integrate complementary information from different medical imaging modalities and provide more comprehensive information for clinical analysis. By combining anatomical information from modalities such as computed tomography (CT) and magnetic resonance imaging (MRI) with functional information from positron emission tomography (PET) and single-photon emission computed tomography (SPECT), MMIF can improve image quality and support subsequent tasks such as disease analysis, lesion detection, image segmentation, and treatment planning. This review provides a comprehensive overview of MMIF from theoretical and technical perspectives. First, commonly used medical imaging modalities and publicly available medical image databases are summarized and compared. Subsequently, the general workflow, fusion levels, and quality requirements of MMIF are introduced. Representative fusion techniques are then systematically reviewed, including spatial-domain methods, transform-domain methods, sparse representation-based methods, deep learning-based methods, hybrid methods, and emerging Mamba-based approaches. In addition, commonly used image fusion quality assessment metrics are analyzed, and the reported quantitative performance of representative MMIF methods is compared and discussed. Finally, current challenges and future development trends of MMIF are presented, including robustness, clinical translation, and emerging multimodal learning paradigms. Full article

Protein aggregation strongly depends on the local environment, yet investigating it in compartmentalized, high-surface-area volumes remains challenging. Here, we present an optically controlled platform for inducing and monitoring protein aggregation in microliter droplets. Local pH changes are generated in situ via photoconversion of 2-nitrobenzaldehyde, enabling noninvasive environmental control without mechanical mixing or direct perturbation of the sample. By combining fluorescein-based pH measurements with Raster Image Correlation Spectroscopy (RICS), pH variations and protein diffusion were monitored. As a model system, we investigated β-lactoglobulin, whose association state strongly depends on pH. Light-induced acidification progressively shifted the protein toward its isoelectric region, resulting in a measurable decrease in the diffusion coefficient consistent with the formation of larger supramolecular species. Furthermore, modulation of electrostatic interactions through NaCl addition revealed the sensitivity of the system to environmental factors governing the balance between electrostatic repulsion and short-range attractive interactions. Under these conditions, the platform enabled the observation of aggregation behaviors that were significantly less pronounced in corresponding bulk conditions. Overall, this droplet-based approach allows for the precise manipulation of local chemistry and quantitative analysis of biomolecular self-assembly, making it readily extendable to various noninvasive, time-resolved monitoring applications. Full article

Automated inspection of electrical equipment has become increasingly important as utilities seek to replace inefficient manual processes in infrastructure management. Electrical-equipment nameplates contain critical technical information, but automatically extracting this information remains challenging. Although this topic has attracted growing research interest, the literature has not yet been systematically synthesized. This review addresses three research questions: (1) What real-world challenges affect the inspection and maintenance of electrical equipment, and what research gaps and opportunities remain? (2) Which computer vision and deep learning algorithms and architectures are used to extract text and digits from electrical equipment images? (3) Which metrics, datasets, and evaluation methodologies are used to assess these approaches? We conducted a systematic literature review in accordance with PRISMA 2020. Peer-reviewed English-language studies published between 2020 and 2026 were retrieved from IEEE Xplore, Scopus, ScienceDirect, SpringerLink, the ACM Digital Library, and complementary semantic-search sources; the final searches were conducted in May 2026. The screening and eligibility process reduced 19,760 initial records to 66 primary studies. Owing to substantial heterogeneity in tasks, datasets, and metrics, the evidence was synthesized narratively and in structured tables rather than through meta-analysis. DBNet and CRNN were among the most frequently used architectures for text detection and recognition, respectively, whereas integrated end-to-end systems emerged as a promising research direction. The scarcity of standardized public datasets remains a major barrier to objective comparison and cumulative progress in the field. Full article

Plasmonic biosensing technologies have emerged as powerful analytical tools for sensitive and label-free characterisation of biomolecular interactions and complex samples. The increasing demand for comprehensive molecular profiling has accelerated the development of multiplexing strategies that enable simultaneous analysis of multiple analytes and molecular interactions. This Feature Paper examines multiplexing through the complementary spatial, spectral, and temporal dimensions of multiplexing, together with their hybrid combinations and associated analytical trade-offs. Compared with other optical biosensing approaches, including interferometric, photonic, and fluorescence-based sensing platforms, plasmonic biosensors remain attractive owing to their combination of label-free detection, real-time interaction monitoring, sensitive interfacial analysis, and compatibility with multiplexed assay formats. This Feature Paper critically discusses current multiplexing strategies, focusing primarily on surface plasmon resonance (SPR), imaging SPR (SPRi), localised SPR (LSPR), surface-enhanced Raman scattering (SERS), and related nanoplasmonic biosensing approaches, together with recent advances in surface biofunctionalisation, antifouling interfaces, and molecular recognition strategies. Representative applications in biomedical diagnostics and non-clinical settings are highlighted, with examples such as liquid biopsy, glycoprofiling, extracellular vesicle profiling, and food and environmental analysis, alongside key challenges in reproducibility, standardisation, data interpretation, and clinical translation. In addition, selected non-plasmonic optical biosensing technologies are briefly discussed to position plasmonic biosensing within the broader landscape of multiplexed optical biosensing. This Feature Paper argues that the future of multiplexed plasmonic biosensing will depend less on further improvements in sensor performance than on robust, standardised analytical systems. Full article

Triple-negative breast cancer (TNBC) remains a highly aggressive malignancy with limited therapeutic options and frequent resistance to platinum-based chemotherapy. Rosmarinic acid (RA), a naturally occurring polyphenol, has attracted considerable interest as a potential chemosensitising agent. This study investigated the anticancer activity and the underlying mechanisms of RA combined with cisplatin (CDDP) in 4T1 breast cancer cells while assessing the cytotoxic responses of non-cancerous HaCaT keratinocytes as a preliminary indicator of differential treatment sensitivity. Cytotoxicity was assessed using the MTT assay, followed by calculation of the Combination Index (CI), Drug Reduction Index (DRI), and Selectivity Index (SI). The generation of intracellular reactive oxygen species (ROS) was evaluated by DCFH-DA fluorescence imaging, and the functional contribution of oxidative stress was examined using N-acetyl-L-cysteine (NAC) rescue experiments. Apoptosis was analysed by Annexin V/PI flow cytometry, NucBlue nuclear staining, and Calcein-AM/propidium iodide (PI) Live/Dead fluorescence imaging. Three-dimensional (3D) tumour spheroids were used to assess treatment-induced alterations in spheroid morphology, morphometric parameters, viability based on adenosine triphosphate (ATP), and Live/Dead staining. The expression of genes related to apoptosis was determined by RT-qPCR, and potential molecular mechanisms were explored using the construction of protein–protein interaction (PPI) networks together with Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analyses. The combination of RA + CDDP exhibited strong synergistic cytotoxicity in 4T1 cells while demonstrating comparatively lower toxicity toward HaCaT keratinocytes. Combination treatment markedly increased intracellular ROS generation, whereas NAC significantly reduced ROS accumulation and partially restored cell viability, indicating that oxidative stress is a major but not exclusive mediator of cytotoxicity. Combined treatment significantly enhanced apoptotic cell death, increased chromatin condensation and membrane damage, upregulated the expression of Bax, Casp9, Cycs, and Trp53, and downregulated Bcl2, consistent with transcriptional regulation of intrinsic apoptotic signalling. In 3D tumour spheroids, the combination markedly reduced spheroid size, disrupted structural integrity, decreased ATP-based viability, and substantially increased tumour cell death compared to monotherapy. Bioinformatic analyses identified central genes related to apoptosis and cell survival and predicted significant enrichment of PI3K/Akt, p53, MAPK, and apoptosis signalling pathways. RA significantly potentiates the antitumor efficacy of CDDP through synergistic induction of ROS-associated apoptotic signalling while showing a more favourable cytotoxic response in 4T1 breast cancer cells than in non-cancerous HaCaT keratinocytes. The integrated findings from two-dimensional (2D) and 3D models, NAC rescue experiments, molecular analyses, and bioinformatics collectively support the potential of RA as a promising chemosensitising adjuvant for CDDP-based breast cancer therapy and warrant further validation in preclinical in vivo models. Full article

One of the most widespread causes of mortality is cancer, and its early diagnosis is a key element of modern medicine. A crucial role is played by imaging techniques such as positron emission tomography (PET), single-photon emission computed tomography (SPECT), and computed tomography (CT), which require the use of appropriate radioactive isotope tracers to enable precise visualization of pathological changes. In recent years, hyperbranched dendrimers have attracted considerable attention due to their unique architecture and functionalization capacity, making them a promising platform for the delivery of radiotracers. The aim of this manuscript is to provide an overview of radiolabeled dendrimer conjugates, their functionalization methods, and the results of preclinical studies confirming their diagnostic potential. It pays particular attention to the stability and radiochemical purity of the systems, and their ability to overcome physiological barriers. The findings presented indicate that dendrimer-based radiotracers constitute a promising class of carriers for diagnostic imaging, although further studies are required to optimize their physicochemical and biological properties. Full article

Self-Supervised Learning (SSL) has attracted increasing attention in remote sensing image understanding because it can learn transferable representations from unlabeled images. However, two issues remain insufficiently examined in collaborative SSL for remote sensing. First, when high-ratio masking removes entire small objects or structurally informative regions, the remaining visible patches may provide insufficient evidence for semantically coherent reconstruction. Second, heterogeneous self-supervised objectives may exhibit different loss scales, gradient magnitudes, and convergence behaviors such that fixed coefficients can produce uneven branch contributions during training. To address these issues, this paper proposes Context-Consistency Enhanced Collaborative Self-Supervised Learning (C²DSSL) for remote sensing image understanding. C²DSSL introduces a teacher–student context-consistency constraint, in which multi-scale reconstruction features from the complete teacher observation serve as contextual targets for the student network when reconstructing the corresponding masked observation. In addition, gradient-sensitive dynamic weighting uses temporally smoothed loss-gradient magnitudes as empirical signals to adjust the relative contributions of heterogeneous self-supervised objectives. Under the evaluated settings, adding the context-consistency constraint improves KNN representation evaluation, UCMerced classification, Potsdam semantic segmentation, and DOTA oriented object detection, while maintaining the Baseline performance on the Million-AID subset. Dynamic weighting shows task-dependent effects, including a performance gain on the Million-AID subset classification task when combined with CCL. Full article

Recent generative art outputs across music, literature, painting and moving-image media have attracted extensive scholarly and public interest, yet evaluations of their creative capacities are mostly limited to informal observational accounts. Drawing on neuroaesthetic reasoning, this paper puts forward a dual-layer analytical framework that differentiates two distinct modes of aesthetic reception: Alignment, defined as statistical template matching, and evocation, referring to the novel association of scattered embodied memory fragments. Building on this binary categorization, the study introduces the tentative Ring Scale taxonomy—a figurative target-shooting metaphor rather than quantitative metric—as a purely descriptive tool for stratifying relative aesthetic evocation intensity. This framework further unpacks the neurocognitive underpinnings of auditory, visual and textual aesthetic pathways, alongside their combined multimodal interactions within film and television works. It tentatively accounts for why generative systems tend to deliver more cohesive aesthetic outcomes within the auditory domain, and hypothesises a present functional limitation of current large models: these systems perform comparatively well within Alignment-driven aesthetic effects, while layered high-order evocation remains constrained by inherent structural limitations of statistical training architectures. From this diagnostic observation, three directional paradigm shifts for human–AI collaborative creation are outlined: shifting from human substitution to human–machine complementarity, shifting from exhaustive template imagery generation to targeted latent fragment elicitation, and shifting from optimising figurative Ring-tier descriptive labels to pursuing transformative aesthetic fission effects. The study frames imaginative cognition as the central driving force behind fruitful human–AI co-creation, and positions prompt engineering as the actionable operational bridge connecting human imaginative thought to machine-executable generative parameters. Three tentative prompt design tactics are then elaborated: physiological arousal framing, multisensory scenario simulation prompts, and intentional strategic blank-leaving. Additionally, this work discusses the plausible constructive functions of model hallucination phenomena when viewed through the lens of high-tier aesthetic evocation, rather than merely framing such outputs as technical errors. All judgments and tier comparisons raised throughout the paper are framed as unvalidated observational hypotheses open to empirical testing. To facilitate follow-up empirical scrutiny, the paper collates a full set of testable hypotheses derived from its theoretical reasoning and outlines feasible experimental validation pipelines, with an open call for controlled empirical research to corroborate or refine the proposed qualitative framework. Full article

Non-small-cell lung cancer (NSCLC) is one of the most frequent cancer types and is responsible for the majority of cancer-related deaths worldwide. For this reason, initial diagnosis, prognosis, and targeted therapy of NSCLC represent very attractive areas of study. Aptamers are single-stranded nucleic acids (RNA or DNA) generated through Systematic Evolution of Ligands by Exponential Enrichment (SELEX); they are able to bind to a molecular target with high affinity and specificity. Thanks to their intrinsic nucleic acid properties, they can be easily modified and optimized to enhance target binding and their half-life; moreover, they exhibit no immunogenicity and toxicity. Due to this, many aptamers have just been selected against NSCLC biomarkers and provide specific imaging agents to improve the diagnosis of this type of cancer. However, despite the promising results in preclinical studies, the application of aptamers in NSCLC diagnosis is still in its early stages, mainly due to the limited literature in the research world, the dominance of antibodies in the pharmaceutical market and the challenge of target identification. Consequently, this appears to be a temporary issue, and aptamers could see increasing application in the future; thus, we performed a review aimed at summarizing current knowledge on the new promising DNA and RNA aptamer-based molecules for NSCLC diagnosis. All studies from 2000 were included and investigated. Our findings showed that several DNA and RNA aptamers are promising diagnostic tools for NSCLC management. Full article

Indigenous grains, such as pearl millet, can contribute to alleviating food insecurity in South Africa and addressing the health and well-being of consumers. Stigmatisation and a lack of consumer knowledge about indigenous grains have been found to stifle the consumption of these grains. Therefore, this study aimed to explore South African consumers’ perceived understanding and experience of pearl millet and the external product attributes that attract their attention and steer them towards purchasing and consuming this indigenous grain. This interpretivist phenomenological exploratory study used a qualitative methodology. Small synchronous online focus groups were used to gather the data. The thematic analyses revealed that consumers are generally perceived as uncertain about and lacking experience in the use and consumption of pearl millet, which results from factors such as product unfamiliarity, a lack of knowledge, the product being overlooked in stores, and various assumptions about the grain. Consumers’ perceived willingness to purchase pearl millet may be influenced by several product attraction indicators, including price, packaging, whether it is produced locally, retailer image, and quality-enhancement attributes, which marketers and product developers in South Africa should use to grow consumer interest. This study contributes towards changing the consumer perceived approach to pearl millet by identifying the factors that hamper and limit the choice of pearl millet consumption. South Africa can ill afford to neglect marketing and improving consumer awareness of pearl millet if the health and well-being of South African consumers are to be improved. Full article