Search Results (13,724)

Pancreatic cystic lesions (PCLs) represent a growing clinical challenge due to their diverse biological behaviors and the substantial overlap in imaging features between benign, premalignant, and malignant entities. Traditional diagnostic approaches relying on cross-sectional imaging or isolated morphologic criteria frequently fail to achieve adequate risk discrimination. Advances in endoscopic ultrasound (EUS) now permit detailed morphologic assessment complemented by cyst-fluid biochemical markers, proteomic signatures, and comprehensive genomic profiling using next-generation sequencing. Parallel progress in artificial intelligence (AI) further strengthens diagnostic precision by integrating EUS features with multimodal biomarker data to reduce subjectivity and support individualized clinical decision-making. This review introduces an EUS-based multimodal diagnostic framework of PCLs that integrates morphological evaluation, cyst-fluid biochemical testing, molecular profiling, and AI-assisted analysis. By synthesizing current evidence, we outline how the integrative approach enhances diagnostic accuracy, biological interpretability, and individualized risk stratification for PCLs. Full article

Wire Arc Additive Manufacturing (WAAM) is a cost-effective and scalable technique for producing large metallic components; however, coarse columnar microstructures, strong crystallographic texture, and significant residual stresses limit its widespread adoption. Hybrid WAAM processes that integrate deformation-based techniques have been developed to address these limitations. This review provides an analysis of deformation-assisted WAAM, covering interlayer rolling, friction stir processing (FSP), machine hammer peening, laser shock peening, and ultrasonic-vibration-assisted techniques. These hybrid techniques introduce additional thermomechanical parameters (strain, strain rate, and applied stress) that significantly influence microstructure evolution. The governing physical metallurgy mechanisms are discussed in detail, including dislocation accumulation, recovery, static and dynamic recrystallization, and severe plastic deformation. Studies from 2022 to 2025 are critically reviewed, highlighting the effectiveness of hybrid WAAM in promoting columnar-to-equiaxed grain transformation, reducing anisotropy, mitigating defects, and improving mechanical properties across aluminum, titanium, steels, and nickel-based alloys. The integration of auxiliary processes such as in situ machining and heat treatment is also discussed. This review establishes a process–structure–property framework for hybrid WAAM and provides guidance for the development of advanced additive manufacturing systems for the production of near-net-shape components, with reported yield-strength gains of 20–40%, elongation gains of 10–30%, and fatigue-life improvements of up to 60% relative to as-built WAAM. Full article

Food packaging constitutes a pivotal enabler within the contemporary food industry, requiring continuous innovation to address evolving challenges. Traditional packaging systems typically provide passive protection, which is inadequate for addressing dynamic microbial shifts and spoilage-induced microenvironmental instabilities. In contrast, corrective responsive food packaging (CRFP) takes a distinct approach through the integration of sensing capabilities and targeted active intervention. Upon detection of specific stimuli, CRFP systems precisely deliver bioactive agents to mitigate food deterioration. This review systematically summarizes recent advances in CRFP technology, offering a comprehensive overview of its core response mechanisms, functional materials, advanced carrier systems, and future research priorities. Special emphasis is given to (i) stimuli-responsive systems, including single-stimulus (pH, enzyme, humidity, temperature, and light) and multi-stimulus-responsive systems, detailing their triggering mechanisms and practical applications; and (ii) functional materials and carriers, exploring their synergistic effects for optimized bioactive release. This review aims to provide a structured framework for the design and implementation of CRFP, facilitating its translation from laboratory to industrial practice and contributing to the development of sustainable and efficient food preservation strategies. Full article

Anastomotic leakage (AL) is a significant complication associated with elevated morbidity and mortality rates following colorectal surgery. This complication primarily arises due to impaired wound healing. Anastomotic and intestinal wound healing is generally divided into three phases: inflammation, proliferation, and remodeling. The physiological transition between these phases is primarily orchestrated by macrophages, which are key regulators of inflammation and tissue repair. They undergo sequential phenotypic changes from pro-inflammatory to anti-inflammatory states and are involved in the phagocytosis of bacteria or debris, but also attract fibroblasts for collagen production and deposition. Importantly, they can promote local perfusion by secreting pro-angiogenic and growth factors. Failure of this transition from pro- to anti-inflammatory properties is associated with AL, scarring, and fibrosis. Intestinal macrophages represent the largest pool of resident myeloid cells and are promising cellular targets for therapeutic interventions. In this narrative review, we focus on intestinal and anastomotic wound healing, highlight the dichotomous role of macrophages, and discuss potential therapeutic strategies. A detailed understanding of macrophage polarization, recruitment, and targeted modulation may enhance wound healing and prevent complications such as AL. Full article

Introduction: Cardiovascular diseases (CVDs) are a vast and widespread problem around the world, responsible for around one third of global deaths, of which 85% were due to heart attack and stroke in 2022. There are a lot of well-established risk factors for CVDs, including smoking, diabetes mellitus, obesity, poor diet, alcohol use, and sedentary lifestyle. Psychiatric disorders, however, are not among those frequently cited. Over a billion people worldwide suffer from some kind of mental disorder, with anxiety and depression being among the leading causes of long-term disability. All-cause death is significantly elevated in individuals with all mental health disorders. Methods: This narrative review aims to provide details on the selected psychiatric disorders and their pharmacotherapy with regard to the risk of developing cardiac illness by reviewing the available literature and the 2025 ESC Clinical Consensus Statement on mental health and cardiovascular disease. Results: Primary and secondary prevention of cardiovascular complications in the psychiatric disease population is an essential component in clinical healthcare. Conclusions: Taking all into account, it is essential to underline the role of the activation of the sympathetic nervous system and chronic inflammation, ultimately leading to metabolic syndrome in individuals with mental disorders, as well as an increase in residual cardiovascular risk and the development of CVDs, thereby worsening their long-term prognosis. In view of risky lifestyle behaviors in this population, it is essential to screen proactively, mitigate risk factors, consider the role of pharmacotherapy, and, if needed, initiate appropriate treatment. Full article

The low water solubility of numerous drug candidates and phytochemicals continues to pose a significant challenge in pharmaceutical development, greatly limiting their bioavailability and therapeutic performance. This review presents a detailed overview of formulation strategies aimed at improving the solubility and dissolution of poorly aqueous-soluble compounds. The biopharmaceutics classification system and the relevance of in vitro–in vivo correlation, as well as key challenges in formulation development, are briefed. Solid-state and particle engineering approaches, including micronization, supercritical fluid technology, electrospinning, and cryogenic techniques, are discussed. Extensive critical examination of amorphous solid dispersions and their preparation methods, as well as crystallization inhibition strategies, is covered. Cocrystallization is highlighted as a promising approach, with emphasis on design principles and preparation methods. Various solubilization techniques, such as pH modification, cosolvency, hydrotropy, micellar solubilization, and cyclodextrin-based complexation, including advanced hybrid systems, are also explored. Emerging solvent platforms, such as deep eutectic systems and lipid-based and nanotechnology-driven approaches, are reviewed for their role in improving solubility and drug delivery. Additionally, enabling technologies such as liquisolid systems and hydrophilic polymers are addressed. Despite notable progress, limitations such as scalability, reproducibility, regulatory constraints, and long-term safety persist. Overall, this review provides integrated insights into formulation design approaches to enhance the solubility and therapeutic efficacy of poorly soluble drugs. Full article

Two-dimensional (2D) transition metal dichalcogenide (TMDC) nanoscrolls have attracted significant attention in recent years owing to their fascinating properties, including high specific surface area, unique electronic structure, and excellent optoelectronic performance. These properties arise from their intrinsic one-dimensional (1D) spiral scroll geometry. In this review, we systematically present the preparation methods, properties, and applications of TMDC nanoscrolls. For fabrication, we detail a variety of preparation strategies, both on substrates and in solution. Next, we discuss the characterization and physical properties of TMDC nanoscrolls. Finally, we summarize their applications in photodetection, the hydrogen evolution reaction (HER), optoelectronic synapses, and other related fields. Full article

Objective: Continuous pressure-flow cerebral bio-signals are critical for monitoring cerebrovascular dynamics but are often disrupted by missing data segments caused by artifacts from a variety of sources. These missing segments refer to segments of the signal that do not contain any valid physiological data. Such interruptions fragment the signals, resulting in discontinuities that compromise their overall integrity. Therefore, reconstructing missing values and preserving signal continuity are essential for ensuring the stable computation of signal trajectories and the accuracy of derived cerebrovascular indices. Methods: To address this issue, this systematic scoping review aimed to identify and synthesize existing interpolation and imputation strategies for handling missing segments in continuous pressure-flow cerebral bio-signals. Following the Cochrane and Preferred Reporting Items for Systematic Reviews and Meta-Analysis guidelines, a comprehensive search of five electronic databases was conducted from their inception to 24 September 2024, and updated on 16 June 2025, using a detailed search string. Results: The initial searches yielded 19,403 results, and 8 studies were filtered and included in the review. All included studies employed interpolation techniques, such as linear and spline interpolation algorithms, to correct distorted signal segments. However, none of the included studies directly utilized interpolation or imputation strategies to reconstruct or completely fill missing data segments. Conclusions: This reveals a critical knowledge gap, as no study has systematically addressed the utilization of interpolation or imputation strategies for missing segments in pressure-flow cerebral bio-signals. Therefore, this systematic review emphasizes the need for specialized methodologies and standardized frameworks to enable reliable recovery of missing data segments in pressure-flow cerebral bio-signals, which is critical for advancing real-time neurocritical care monitoring and experimental neuroscience/psychological research. Significance: This systematic review lays the groundwork for future research into physiologically informed interpolation and imputation strategies for pressure-flow cerebral bio-signals in clinical and research applications. Full article

Background: Pregnancy presents unique immunological and obstetrical challenges for women with Common Variable Immune Deficiency (CVID). No standardized guidelines currently exist to guide pregnancy management, as CVID is a rare diagnosis, with pregnancy outcomes limited to case reports and case series. Establishing a structured approach to care is important to optimize maternal and fetal outcomes. Methods: A narrative review of the literature with a structured search was performed to detail pregnancy outcomes in CVID and management strategies. A 10-year retrospective chart review of women with CVID who became pregnant while receiving care at the McGill University Health Centre between January 2015 and January 2025 was conducted to add to the existing clinical data. Results: Pregnancy outcomes were improved through pre-conception planning, regular serum Immunoglobulin G (IgG) monitoring, trimester-based immunoglobulin replacement dose adjustments, proactive management of autoimmune or infectious complications, and multidisciplinary care. Subcutaneous immunoglobulin may offer better flexibility and stability of IgG levels. Conclusions: In the available observational literature and our institutional experience, many patients with CVID have carried pregnancies to term with favorable maternal and neonatal outcomes when managed with IgRT and multidisciplinary coordination. We outline a stepwise multidisciplinary framework for clinicians caring for women with CVID who are planning or undergoing pregnancy, and we identify gaps in knowledge for future studies. Full article

Background/Objectives: The evaluation of cognition is central to many neurological conditions, including traumatic brain injury, Alzheimer’s disease, Lewy body disease, frontotemporal degeneration, and vascular disorders. In clinical practice, particularly in aging populations, cognitive complaints often arise in the context of mixed neurological processes, requiring careful integration of cognitive and non-cognitive findings. Despite this, there remains limited clarity regarding the respective roles of neurologists and clinical neuropsychologists and the distinction between cognitive and neuropsychological assessments, terms that are often used interchangeably despite important differences in methodology and scope. This lack of a shared framework has practical consequences. Cognitive test results, when interpreted in isolation for diagnosis, may be misconstrued as comprehensive measures of brain function, particularly when non-cognitive neurological features such as motor, cerebellar, or vestibular abnormalities should have been considered (but were not). Methods: In this narrative review, we synthesize clinical guidelines, consensus statements, regulatory sources, and representative empirical literature to articulate a competence-based framework in which cognitive assessment is a medically integrated process incorporating history, functional evaluation, neurological examination, and the targeted use of standardized neuropsychological instruments. Results: Neurologists are trained to establish medical diagnoses and integrate cognitive findings into the context of neurological disease, while neuropsychologists contribute detailed psychometric characterization, culturally and demographically informed interpretation, cognitive phenotyping, functional characterization, and validity assessment in complex clinical and medicolegal contexts. Although neuropsychologists are qualified to diagnose neurocognitive disorders using standardized diagnostic criteria, attribution to specific neurological etiologies requires a comprehensive medical evaluation that extends beyond cognitive testing alone. Conclusions: We outline a tiered approach to evaluation that aligns assessment methods with clinical questions and supports accurate diagnosis, interdisciplinary collaboration, and patient-centered care. Full article

Lesson planning is a core professional practice for pre-service teachers, yet opportunities for timely, individualized feedback are frequently constrained by educator workload. While generative AI has the potential to enhance planning processes and expand opportunities for individualized feedback, the provision of comprehensive lesson plans may lead to excessive reliance. This conceptual design paper details the development and theoretical underpinnings of an artificial intelligence-assisted feedback tool that provides self-efficacy-strengthening feedback on lesson plans for pre-service teachers. To promote constructive feedback, the AI-assisted feedback tool integrates principles from educational feedback research and structures feedback to foster teachers’ lesson-planning self-efficacy through mastery-oriented affirmations, vicarious examples, social persuasions, and emotional reassurance. Curriculum alignment is incorporated to support content validity and contextual appropriateness. While the initial implementation of the feedback tool focuses on Western Australian teacher education, an explicit transfer perspective is considered for the German vocational education context. The paper describes the iterative development process that follows a design-based research approach including platform evaluation, internal refinement, and expert review by teacher educators in Western Australia. The resulting system prompt architecture comprises 11 dimensions including general baselines, the interaction between the Lesson Planning Coach and PSTs and the theoretical foundations mentioned above. The tools’ environment, including examples for provided feedback on lesson plans, is presented and discussed. Finally, an outlook is given on the planned empirical research to evaluate the effectiveness of the tool. Full article

Adoptive cell therapy (ACT) using tumor-infiltrating lymphocytes (TILs) has achieved clinically and biologically relevant responses in patients with solid cancer. Clinical efficacy has been increasingly linked to a specific T-cell phenotype, particularly CD8⁺ TILs exhibiting a progenitor stem-cell-like profile (CD39⁻ CD69⁻). This review explores the critical role of the sphingosine-1-phosphate (S1P) axis in orchestrating these responses. We detail the biological antagonism between the activation marker CD69 and S1P receptor 1 (S1PR1), where mutual exclusivity dictates thymic selection, if T-cells are retained in tissues or allowed to recirculate and maintain long-term immune surveillance. The S1PR1:S1P axis is further recognized as a critical regulator of mitochondrial fitness, sustaining the high energetic demands of precursor T-cells. We examine the “double-edged sword” nature of S1P in the tumor microenvironment (TME), where it can drive pro-tumorigenic processes like angiogenesis and vascular mimicry (VM), be hijacked by cancer cells to create immune-excluded environments, or S1P can increase T-cell fitness. We summarize the current landscape of clinical trials (as of January 2026) that target S1P production or signaling to modulate anti-tumor responses or use S1P as a biologically relevant marker of treatment outcome. Full article

Recent advances in satellite missions, particularly the Landsat, Sentinel, and Gaofen series, have led to the rapid accumulation of high-quality remote sensing data with frequent revisits. As these data have become more widely available, Satellite Image Time Series (SITS) have become an important tool for monitoring Earth surface dynamics. SITS now supports a wide range of applications, including precision agriculture, Land Use/Cover Change (LULCC) monitoring, environmental management, and disaster response. This growth has also promoted the development of advanced SITS classification datasets. However, existing reviews have mainly focused on SITS classification algorithms or specific applications, while systematic comparisons of public SITS benchmark datasets remain limited. This lack of synthesis makes it difficult for researchers to navigate fragmented resources and select datasets that match specific scientific or operational tasks. To address this gap, this paper provides a comprehensive review and analysis of 29 publicly available medium-to-high-resolution SITS classification benchmark datasets released between 2017 and 2025. These datasets are intended for training, testing, and validating land-cover classification algorithms, rather than for direct use as operational map products. We conduct a detailed statistical and comparative analysis of these datasets, focusing on their key characteristics across spectral, temporal, and spatial dimensions, as well as their labeling systems. In addition, this review summarizes the SITS classification algorithms that have been developed and benchmarked using these datasets. Finally, we identify the main challenges in constructing and applying SITS classification datasets and discuss future research directions, particularly in data reconstruction, multimodal fusion, change analysis, and advanced model architectures. This survey provides the research community with a systematic overview of SITS classification benchmark datasets and aims to support continued progress in this rapidly developing field. Full article

Wildfire prediction using machine learning (ML) and deep learning (DL) has expanded rapidly, yet synthesis regarding algorithmic configurations, data practices, and transparency remains limited. This systematic review characterizes ML/DL applications in wildfire prediction (2020–2025) using a PRISMA-EcoEvo framework across 341 peer-reviewed studies, with detailed analysis of 110 articles from 2024. Publication output increased steadily, concentrated geographically in China and the United States. Methodologically, ensemble tree-based methods (26.7%) and deep learning architectures (59.4%) coexist, reflecting adaptation to diverse data modalities. Input data are dominated by vegetation/fuel characteristics (44.7%) and historical fire labels (41.2%), while socioeconomic variables remain marginal (1.2%). Evaluation practices distinguish classification and regression tasks, yet metric heterogeneity constrains cross-study comparability. Critically, only 7.7% of studies provided publicly accessible code, with a significant association between algorithm family and code availability (χ² = 78, p = 0.0012). Collectively, wildfire ML/DL research demonstrates technical advancement but remains geographically concentrated and constrained by limited transparency. Strengthening reporting standards, metric-task alignment, dataset documentation, and open-code practices is essential to translate computational innovation into globally robust, reproducible wildfire decision-support systems. Full article

This paper presents an outline of a historical stone: the Marble of Campiglia, from Tuscany (Italy). A comprehensive review of the literature and archival documents, combined with a new detailed field survey, allowed us to revise the geological setting and exploitation history of this cultural heritage marble, which has been sporadically utilized from Etruscan times to the present day. The Campiglia Marittima Marble (CMM) has a thermal-metamorphic origin associated with the intrusion of a granitic pluton dated to approximately 5.4 Ma. This process gave rise to a marble with peculiar textural, grain size, and fracturing characteristics that influenced extraction techniques and methodologies. The primary exploitation periods of the CMM as an ornamental stone were the Etruscan-Roman era, the Renaissance, and the nineteenth century; currently, it is used exclusively for industrial purposes. A significant number of ancient quarries are located on the western slope of Monte Rombolo, likely attributable to the high variety of commercial marble types available in the area and its strategic location, which facilitated transport routes to the Tyrrhenian Sea. This research aims to bring attention to this historical marble and may support, alongside the potential reopening of selected quarries for restoration purposes, the preservation of the authenticity of the historical artefacts in which it was employed. Full article