Search Results (61,767)

Laser technology has recently gained renewed interest in hysteroscopic surgery due to advances in fiber-optic delivery systems, device miniaturization, and the growing adoption of office-based procedures. In this context, laser energy represents a potential alternative to conventional mechanical and electrosurgical techniques, particularly in settings where precision and tissue preservation are clinically relevant. This narrative review provides a comprehensive and clinically oriented overview of the role of laser technology in modern hysteroscopy. A literature search was conducted in PubMed, Scopus, and Web of Science up to December 2025, focusing on studies addressing technical aspects, clinical applications, safety, and outpatient feasibility of laser-assisted hysteroscopy. Different laser systems, including Nd:YAG, diode, CO₂, Ho:YAG, and KTP lasers, are discussed in terms of physical properties and tissue interaction. Current clinical applications include the management of intrauterine adhesions, submucous myomas, endometrial polyps, septate uterus, and selected cases of endometrial ablation. Available evidence suggests that modern diode laser platforms are particularly suited for office-based procedures due to their combined cutting and coagulative effects and compatibility with small-caliber hysteroscopes. However, most of the current literature is based on small, heterogeneous studies, and robust comparative data with standard hysteroscopic techniques remain limited. As a result, laser hysteroscopy cannot yet be considered a standard approach across indications. To move beyond a purely technical appraisal, this review also frames laser hysteroscopy as a potential translational platform in which laser–tissue interaction, biomarker-informed patient selection, endometrial repair biology, fertility outcomes, and adhesion-formation mechanisms may be integrated into future functional precision medicine pathways. In conclusion, laser technology represents a promising and evolving tool in operative hysteroscopy, with potential advantages in selected clinical scenarios. Further prospective and comparative studies are required to better define its role and to support its broader integration into routine clinical practice. Full article

Photovoltaic (PV) technology is now one of the main options for expanding the power of low-carbon electricity generation. However, in practical operation, PV systems still face several persistent difficulties, including the variability of solar irradiance, gradual performance degradation, fault occurrence, suboptimal control, and the growing complexity of grid-connected operation. These issues explain why artificial intelligence (AI) has become increasingly relevant in PV research, not only as a prediction tool, but also to improve monitoring, control, diagnosis, and decision-making. This review investigates the applications of AI in the major stages of the PV system lifecycle: solar resource assessment, power forecasting, fault detection, condition monitoring, system sizing, maximum power point tracking (MPPT), and grid integration. Rather than treating these applications as separate research topics, the review attempts to connect them through the common factors that determine their practical value: data quality, sensing configuration, model complexity, physical operating conditions, and deployment constraints. The reviewed studies indicate that AI-based MPPT methods can achieve tracking efficiencies close to 99%, while recent forecasting models, particularly LSTM, CNN–LSTM, and transformer-based architectures, can reduce prediction errors under changing weather conditions. At the same time, PV fault detection is moving beyond electroluminescence image classification toward more practical multimodal strategies that combine infrared thermography, RGB and drone imagery, electrical measurements, and SCADA/IoT data. Nevertheless, the progress reported in the literature should be interpreted with caution. Many proposed models are still evaluated on limited or non-standardized datasets, and their performance may decrease when they are transferred to different PV technologies, climates, fault severities, or operating conditions. Other recurring limitations include class imbalance, high computational cost, weak generalization, and the limited interpretability of deep-learning models. For this reason, hybrid neural networks, explainable AI, physics-informed learning, edge-AI, federated learning, and quantum machine learning are discussed as possible directions for making AI-based PV solutions more reliable and deployable. This review aims to critically synthesize recent advances and remaining gaps in order to support the practical integration of AI into efficient, reliable, and sustainable PV systems. Full article

Photovoltaic (PV)/biomass systems offer stable/continuous power by overcoming solar-energy intermittency with biomass dispatchable energy. Considering gaps in the scientific literature, this article sets out to present information on PV/biomass installations and the eco-profiles of different feedstocks for biogas generation. To this end, this article is split into two parts. The first one outlines some key elements of the literature on PV/biomass systems, highlighting factors that determine feasibility and performance. The second one presents the eco-profiles of three feedstocks. The methodology is based on literature review and Life-Cycle Assessment (LCA). Regarding the first part, the results show that the majority of the prior research placed emphasis on techno-economic analysis and the design/modelling of PV/biomass systems, and there is a dearth of LCA studies on PV/biomass installations. As for the second part, the findings demonstrate that, among the feedstocks examined (manure; waste cooking oil; grass), in most categories, animal waste shows the highest environmental impacts. For instance, considering the total impact of these three feedstocks and based on Environmental Product Declaration (EPD), the results indicate that, in many categories, manure surpasses the percentage values of 40%. Grass exhibits minor percentage shares, with the exception of the “Eutrophication” (54%) and “Acidification” (33%) categories. Full article

Rubber extrusion has evolved through overlapping advances in equip design, rheological characterization, numerical modeling, sensing, and control. This structured critical narrative review synthesizes 180 sources published from 1972 to 2026, assembled through iterative keyword searching and backward and forward citation tracing. The conventional three-zone theory of solid conveying, compression, and metering is used as a bounded analytical framework, while the literature is organized into four overlapping analytical periods spanning empirical design, constitutive and numerical modeling, engineering-scale simulation, and multiphysics and data-enabled methods. Evidence is distinguished among direct rubber-extrusion validation, rubber-material or rheological studies, transferable general polymer extrusion studies, and enabling computational, sensing, or control research. Five persistent challenges are identified: formulation-dependent nonlinear rheology; incomplete representation of filler-network evolution and wall slip; limited cross-machine and cross-formulation validation; high computational cost; and the lack of standardized datasets and reporting protocols. Digital twins, physics-informed neural networks, and neural operators are promising but remain insufficiently validated for industrial rubber extrusion. Priorities include transparent benchmark datasets, evidence-graded, uncertainty- and latency-aware validation, multimodal sensing, transferable reduced-order and learned models, and measurable sustainability indicators. Together, these priorities define a validation-oriented roadmap for more reliable, transferable, and sustainable rubber-extrusion modeling and control. Full article

Background/Objectives: Metformin is a prominent candidate for cancer drug repurposing, backed by preclinical and epidemiological evidence showing reduced cancer incidence in diabetic patients. Its pleiotropic effects include AMPK activation, protein synthesis inhibition, and metabolic alterations. This review integrates global preclinical data via a comprehensive tabular overview alongside a cross-analysis of specific investigations of hamster fibrosarcoma. Since head-to-head comparisons of metformin-based combinations on hamster fibrosarcoma remain limited, this work performs an integrated cross-study evaluation to establish a clear comparative hierarchy of various repurposed adjuvants combined with metformin. Methods: A literature review and cross-study re-analysis of peer-reviewed preclinical studies were conducted, focusing on in vivo therapeutic outcomes within the BHK-21/C13-induced hamster fibrosarcoma model. Treatment regimens from distinct primary studies were evaluated side-by-side using tumor endpoint data expressed as a percentage of control mean (± SD). Only statistically significant pairwise differences (p < 0.05) determined the comparative hierarchy. Results: Integrated analysis identified disulfiram and diclofenac as the most promising adjuvants among compared metformin combinations, showing the highest statistical significance across all evaluated endpoints. The statistical ranking of the metformin-based combinations followed a descending order: disulfiram, diclofenac, nitroglycerin, itraconazole, and caffeine. Conclusions: By synthesizing previously fragmented primary data into a unified comparative framework, these findings provide a strong, consolidated preclinical rationale for metformin-based combination strategies. The established hierarchy of adjuvant potency resolves structural ambiguity and supports further translational and clinical investigation to evaluate their therapeutic potential in fibrosarcoma and other malignancies. Full article

Autonomous vehicles are a flagship technology of the smart city, yet smartness and sustainability are distinct goals. Automated urban mobility can be both smart and sustainable, one without the other, or neither, and which outcome a city reaches depends on how people adopt and use it. This article reports a systematic review of the human paradoxes of automated urban mobility. Drawing on a synthesis of the literature on automated mobility and the governance of sustainable mobility, it covers twenty recurring paradoxes and organises them into five families according to what generates them. Mapping the corpus shows where the evidence is dense and where it is thin, and it shows that work on the attractiveness of automated travel outweighs work on zero-occupancy running by more than an order of magnitude. It also shows that the direction of reported findings depends on how a study was conducted. Models tend to report benign outcomes for the quantity they optimise and adverse outcomes for quantities they only represent, so appraisals drawing on a single study design will be biased in a predictable direction. The paradoxes are not inherent to the technology. They hinge on human choice and governance, and automated mobility reaches the smart and sustainable quadrant only where adoption is shared, well matched to need, sequenced with care, and steered by explicit public choices. The article sets out the CalmMobility paradigm as that steering framework, maps each tension to the instruments that decide its outcome, and offers testable propositions and a research agenda for the tensions that remain thinly evidenced. Full article

Low back pain (LBP) is one of the most common causes of medical consultation worldwide and is typically attributed to degenerative spinal disorders. However, a subset of patients presents with LBP related to extra-spinal conditions, including disorders of the lumbar plexus. These conditions are often underrecognized and may mimic lumbar radiculopathy, leading to delayed diagnosis or inappropriate management. The lumbar plexus, formed by the anterior rami of L1–L4 nerve roots, lies deep within the psoas muscle and can be affected by a wide range of pathological processes, including traumatic, compressive, inflammatory, infectious, and neoplastic conditions. A targeted literature search of the PubMed/MEDLINE database was performed to identify relevant English-language articles on lumbar plexus disorders, their imaging features, and diagnostic strategies published from inception to June 2026; representative imaging examples were selected from the co-authors’ clinical archives. The review summarizes the relevant anatomy, clinical presentation, and key imaging features of the most common plexus pathologies, including retroperitoneal tumors, psoas hematomas, inflammatory plexopathies, and iatrogenic injuries. Advances in imaging techniques, particularly magnetic resonance imaging (MRI) and magnetic resonance neurography (MRN), have significantly improved the ability to visualize the lumbar plexus and detect pathological changes involving peripheral nerves and surrounding structures. Additionally, a practical diagnostic imaging approach is proposed to assist radiologists and clinicians in recognizing lumbar plexus involvement in patients with atypical low back pain. Full article

Cancer prevention through dietary intervention utilizing bioactive natural compounds has garnered significant attention due to the therapeutic limitations of conventional cancer treatments. These plant-derived active compounds, including polyphenols, terpenoids, organosulfur compounds, bioactive peptides, and alkaloids, possess potent anticancer properties. This systemic review addresses a critical gap in the scientific literature by elucidating the precise multitargeted oncogenic regulatory mechanisms of these molecules. A comprehensive methodology was employed, involving a systematic literature search across major electronic databases (including PubMed, Web of Science, Embase, and SCOPUS) to identify relevant original peer-reviewed studies. The evidence gathered demonstrates that these active compounds deliver significant health benefits and protect cells by modulating crucial molecular targets involved in cell cycle regulation, apoptosis, oncogenic signaling, epigenetic control, angiogenesis, oxidative stress, and inflammation. Specifically, they operate via multi-targeted cascades, such as inhibiting the PI3K/Akt, NF-κB, and STAT3 pathways. To provide a clear structural overview, these active compounds are categorized comprehensively based on their botanical and structural origins, including spices, fruits, and rhizomes. However, despite their promising bioactivities, these compounds have not yet been fully translated into clinical therapy due to challenges such as low bioavailability, rapid metabolism, limited systematic exposure, and a lack of convincing evidence from large-scale clinical trials. Although most current evidence remains rooted in in vitro and experimental animal models, clinical validation through high-quality trials is still required. Ultimately, this review underscores the potential of these active compounds and highlights how advances in formulation and nano delivery strategies offer promising solutions for effective cancer prevention. Full article

Nomadism and the tent tradition constitute foundational pillars of Anatolia’s vernacular building culture, yet the spatial continuity between nomadic dwelling practices and their urban coastal adaptations remains underexplored in the literature. This study examines how nomadic spatial strategies were reproduced in Antalya’s coastal oba settlements, evaluating them as architectural expressions of indigenous material culture and collective building knowledge rather than provisional structures. Employing a qualitative approach, the research synthesizes data from literature reviews, archival analysis, and semi-structured interviews with former residents, utilizing Lefebvre’s Rhythmanalysis as an analytic framework to examine how seasonal cycles, recurring daily rituals, and patterns of collective occupation shaped the spatial logic of these now-vanished settlements. Findings reveal three distinct oba typologies with traceable morphological continuities to the nomadic tent tradition, particularly in semi-open spatial configurations, modular organization, and the flexible adaptation of indigenous materials to coastal conditions. Interpreted through the lens of cultural landscape, the oba emerges as a site where tangible building practice and intangible cultural heritage converge. The study concludes that Antalya’s coastal obas represent a significant yet under documented chapter of vernacular architectural heritage, one whose physical erasure under post-1980 tourism-driven development has rendered its preservation in collective and embodied memory all the more urgent. By transitioning from physical fabric to intangible heritage, these settlements persist as a critical representational field for cultural and social sustainability discourse. Full article

The global oil-processing industry generates substantial quantities of by-products and secondary streams, including oilseed cakes, pomaces, hulls, and wastewaters, which remain largely underutilized despite being rich sources of high-value bioactive compounds. The development of sustainable strategies for the valorization of these residues is increasingly recognized as a key component of circular bioeconomy and biorefinery frameworks. In this context, deep eutectic solvents (DESs) have attracted considerable attention as a new generation of designer solvents owing to their tunable physicochemical properties, low vapor pressure, ease of synthesis, and potential environmental compatibility. This review critically discusses the current state of knowledge regarding the application of DESs in the processing and valorization of oil industry by-products. Particular emphasis is placed on the relationship between DES composition, physicochemical characteristics, and extraction performance. Recent advances in the recovery of phenolic compounds, proteins, saccharides, and tocopherols from oilseed-derived residues are comprehensively examined, including the integration of DESs with intensified extraction techniques such as microwave-, ultrasound-, and ohmic-assisted extraction. Furthermore, the role of DESs in oil purification processes and the treatment of technological waste stream is evaluated. Emerging evidence indicates that DES-based systems not only enhance extraction efficiency and selectivity but may also improve the stability, bioaccessibility, and purity of the recovered compounds. Finally, the opportunities and challenges associated with the implementation of DES-based technologies within integrated biorefinery schemes are discussed, including solvent recovery, product scalability, sensory acceptability, and regulatory considerations. The available literature demonstrates that DESs constitute a versatile platform for the sustainable valorization of oil-processing residues, supporting the transition from conventional waste management approaches toward resource-efficient and circular production systems. Full article

Acne vulgaris is an inflammatory cutaneous condition that disproportionately affects the pediatric population. While there are several risk factors, emerging evidence suggests that ultra-processed foods (UPFs), as part of Western dietary patterns, may contribute to acne pathophysiology through activation of inflammatory pathways, such as mTORC1. This comprehensive review synthesizes current evidence regarding acne pathogenesis in conjunction with diet-associated inflammatory cascades to better illustrate the potential role of diet as an adjunct to clinical management in pediatric patients. The current literature suggests that increased insulin/IGF-1 levels may contribute to alterations in the skin and gut microbiota. Additionally, components commonly found in UPFs have been proposed to activate the mechanistic target of rapamycin complex (mTORC1) through insulin/IGF-1-dependent and -independent mechanisms, perpetuating inflammatory pathways that give rise to acne pathogenesis. However, the majority of available evidence is derived from adult cohorts; pediatric-specific evidence remains limited. While studies have demonstrated clinical significance in acne severity with dietary interventions, future high-quality studies are required. Through understanding the relationship between diet and acne pathogenesis, future therapeutic and preventative strategies may be developed to improve pediatric acne clinical outcomes. Full article

Geotechnical hazards such as landslides, subsidence, slope instability, and infrastructure deformation threaten rapidly urbanising and environmentally stressed regions worldwide, intensifying the need for scalable and intelligent monitoring systems capable of continuously observing complex Earth surface dynamics. Although multisensor remote sensing fusion has substantially expanded the observational capabilities of modern geotechnical monitoring through the integration of Synthetic Aperture Radar (SAR), optical imagery, Light Detection and Ranging (LiDAR), and environmental data, existing fusion pipelines remain subject to several well-documented constraints, including weak semantic alignment, limited temporal reasoning, and poor transferability across heterogeneous environmental conditions. This review synthesises the emerging transition from conventional sensor-centric fusion toward intelligent geospatial monitoring architectures centred on deep multimodal representation learning, transformer-based temporal reasoning, self-supervised learning, and geospatial foundation models. Particular emphasis is placed on how recent architectures are designed to better preserve coherent spatial, temporal, and contextual environmental relationships within unified latent representation spaces rather than through downstream handcrafted integration. The review further examines the growing role of multimodal transformers, masked autoencoders, contrastive learning, and large-scale geospatial foundation models in enabling scalable environmental reasoning, adaptive multimodal learning, and transferable geospatial intelligence across sensing modalities and geographic domains. Finally, remaining challenges involving uncertainty, explainability, computational scalability, and environmental generalisation are discussed alongside future research directions involving continual learning, physics-aware artificial intelligence, and autonomous geotechnical monitoring systems. Together, the reviewed literature suggests that multimodal Earth observation is evolving from passive environmental sensing toward adaptive geospatial intelligence systems capable of scalable hazard reasoning and autonomous environmental understanding. Full article

Background: Malakoplakia is a rare chronic granulomatous inflammatory disorder characterized by defective macrophage phagolysosomal activity and accumulation of Michaelis–Gutmann bodies on histopathology. It occurs predominantly in immunocompromised individuals and may mimic infectious, inflammatory, or neoplastic processes, creating significant diagnostic challenges. We describe four cases of malakoplakia occurring in distinct immunocompromised states and review the published literature to better characterize its clinical spectrum, management, and outcomes. Methods: We conducted a retrospective case series of four patients diagnosed with histologically confirmed malakoplakia at our institution. Cases occurred in the setting of liver transplantation, kidney transplantation, relapsed acute myeloid leukemia, and ulcerative colitis treated with immunosuppressive therapy. A literature review was performed using PubMed and Google Scholar to identify published cases of malakoplakia in immunocompromised hosts. Demographic, clinical, microbiological, therapeutic, and outcome data were extracted and analyzed descriptively. Results: Four patients with malakoplakia involving the gastrointestinal tract or renal allograft were identified. Clinical presentations ranged from incidental endoscopic findings and tumor-like colonic masses to recurrent bacteremia and graft dysfunction. Histopathologic examination demonstrated characteristic Michaelis–Gutmann bodies in all cases. Management included antimicrobial therapy, observation, and surgical intervention when necessary. Two patients achieved complete clinical and histologic resolution, one required transplant nephrectomy because of persistent allograft infection, and one died from progressive acute myeloid leukemia. Combined with 48 cases identified in the literature, 52 patients were analyzed. The gastrointestinal tract was the most frequently affected site (76.9%), followed by the genitourinary tract (19.2%). Malignancy (32.7%), solid-organ transplantation (26.9%), and autoimmune disease (21.2%) were the most common underlying conditions. Conclusions: Malakoplakia should be considered in the differential diagnosis of mass lesions, persistent infections, and inflammatory lesions in immunocompromised patients, particularly those with malignancy or receiving immunosuppressive therapy. Early histopathologic diagnosis is essential to distinguish malakoplakia from malignancy and guide appropriate management. Our findings highlight the heterogeneous clinical manifestations and outcomes of this uncommon condition and emphasize the importance of multidisciplinary evaluation in affected patients. Full article

Elastography is an ultrasound-based technique that enables the non-invasive assessment of tissue stiffness. In endoscopic ultrasound (EUS), elastography was initially introduced as a strain-based method, providing qualitative or semi-quantitative information on tissue deformation. More recent technological developments have enabled the integration of shear-wave-based elastography into EUS platforms, including shear-wave measurement (SWM), point shear-wave elastography (pSWE), and two-dimensional shear-wave elastography (2D-SWE). Unlike strain elastography, shear-wave techniques provide quantitative estimates of tissue stiffness by measuring shear-wave velocity or a derived elastic modulus. This invited narrative review summarizes the technical principles, terminology, quality-control requirements, and current clinical evidence for EUS-guided shear-wave-based elastography in pancreatic and hepatobiliary diseases. Because much of the available EUS literature derives from EUS-SWM or point SWE rather than true 2D-SWE, acquisition mode is a central determinant when interpreting clinical evidence and clinical readiness. Current data suggest that EUS-guided shear-wave-based elastography is technically feasible and biologically plausible, but its clinical maturity remains indication-specific. Evidence is most encouraging in chronic pancreatitis, early chronic pancreatitis, autoimmune pancreatitis activity monitoring, and selected endo-hepatology settings, particularly liver fibrosis assessment in patients in whom transabdominal techniques may be suboptimal. In contrast, available evidence does not support EUS-guided shear-wave-based elastography as a standalone diagnostic test for differentiating solid pancreatic lesions, including pancreatic ductal adenocarcinoma, because absolute stiffness values often overlap among malignant lesions, inflammatory masses, and background parenchyma. Before routine clinical implementation, standardized acquisition protocols, disease-specific cut-offs, multicenter reproducibility data, and evidence of incremental clinical value beyond established diagnostic pathways are required. Full article

The increasing demand for lightweight and corrosion-resistant structures has accelerated the use of AA5083 aluminium alloy in automotive, aerospace, marine and transportation industries owing to its excellent corrosion resistance, weldability and favourable strength-to-weight ratio. However, the fabrication of complex AA5083 components remains challenging because of limited formability, localised thinning, fracture and springback associated with conventional forming processes. Robotic incremental sheet forming (RISF) has emerged as a promising dieless manufacturing technology capable of producing complex and customised components with reduced tooling requirements. Recent developments in assisted RISF, particularly heating-assisted and hydro-assisted approaches, have further enhanced process capability. The reviewed literature consistently demonstrates that heating-assisted RISF improves formability by reducing flow stress and fracture tendency, whereas hydro-assisted RISF provides superior thickness distribution, deformation stability and dimensional accuracy. Despite these advances, significant challenges remain, including the lack of standardised processing conditions, limited comparative studies between cold and assisted RISF, insufficient understanding of hydro-assisted RISF for AA5083, and the absence of comprehensive process–structure–performance correlations. This review critically summarises the principles of ISF, RISF and assisted RISF technologies, evaluates their technical developments, industrial potential and economic considerations, and identifies the major research gaps limiting industrial implementation. Future research should focus on standardised processing methodologies, predictive modelling, integrated process optimisation and comprehensive material characterisation to facilitate the wider adoption of assisted RISF for manufacturing advanced lightweight AA5083 components. Full article