Search Results (11,335)

Atrial fibrillation is the most frequent arrhythmia in elderly subjects. Cancer currently represents one of the most important causes of mortality and morbidity in the world. Often, the two pathologies coexist. Several pathophysiological mechanisms can lead to an increased risk of atrial fibrillation and cancer. Additionally, the same therapies used for cancer can increase the risk of developing atrial fibrillation. Our review aims to describe the pathophysiological mechanisms that promote the development of atrial fibrillation in cancer patients and explain the therapeutic opportunities and challenges of treating atrial fibrillation in patients with cancer. Full article

Large Language Models (LLMs) are reshaping recommendation systems through enhanced language understanding, reasoning, and integration with structured data. This systematic review analyzes 88 studies published between 2023 and 2025, categorized into three thematic areas: data processing, technical identification, and LLM-based recommendation architectures. Following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, the review highlights key trends such as the use of knowledge graphs, Retrieval-Augmented Generation (RAG), domain-specific fine-tuning, and robustness improvements. Findings reveal that while LLMs significantly advance semantic reasoning and personalization, challenges remain in hallucination mitigation, fairness, and domain adaptation. Technical innovations, including graph-augmented retrieval methods and human-in-the-loop validation, show promise in addressing these limitations. The review also considers the broader macroeconomic implications associated with the deployment of LLM-based systems, particularly as they relate to scalability, labor dynamics, and resource-intensive implementation in real-world recommendation contexts, emphasizing both productivity gains and potential labor market shifts. This work provides a structured overview of current methods and outlines future directions for developing reliable and efficient LLM-based recommendation systems. Full article

The increasing prevalence of chronic metabolic diseases poses a significant challenge in the modern world, impacting healthcare systems and individual life expectancy. The World Health Organization (WHO) recommends that older adults (65+ years) engage in 150–300 min of moderate-intensity or 75–150 min of vigorous-intensity physical activity, alongside muscle-strengthening and balance-training exercises at least twice a week. However, nearly one-third of the adult population (31%) is physically inactive, which increases the risk of developing obesity, type 2 diabetes, cardiovascular diseases, hypertension, and psychological issues. Physical activity in the form of aerobic exercise, resistance training, or a combination of both is effective in preventing and managing these metabolic diseases. In this review, we explored the effects of exercise training, especially on respiratory and pulmonary factors, including oxygen consumption, pulmonary ventilation, and blood gas analyses among adults. During exercise, oxygen consumption can increase up to 15-fold (from a resting rate of ~250 mL/min) to meet heightened metabolic demands, enhancing tidal volume and pulmonary efficiency. During exercise, the increased energy demand of skeletal muscle leads to increases in tidal volume and pulmonary function, while blood gases play a key role in maintaining the pH of the blood. In this review, we explored the influence of age, body composition (BMI and obesity), lifestyle factors (smoking and alcohol use), and comorbidities (diabetes, hypertension, neurodegenerative disorders) in the modulation of these physiological responses. We underscored exercise as a potent non-pharmacological intervention for improving cardiopulmonary health and mitigating the progression of metabolic diseases in aging populations. Full article

Aseptic abscess syndrome is a clinical entity that is being increasingly documented. Unfortunately, apart from the French registry, there are no other studies presenting collective data. In this review, we sought to analyze clinical and laboratory data from case reports published from the rest of the world. A total of 107 articles were found through our literature search in PubMed, Scopus, and Google, which contained 108 patients who met our eligibility criteria, including pediatric cases. The mean age at diagnosis was 39.1 years, and 54.6% of the patients were female. Cases were found affecting almost every organ, but the most common abscess locations were the spleen (51.9%), liver (35.2%), and lung (23.1%); 34.3% of the patients had multiorgan disease at diagnosis. An inflammatory syndrome was evident, with fever (79.6%), pain (66.7%), median white blood cell count of 16,200/μL, median C-reactive protein level of 15.5 mg/dL, and mean erythrocyte sedimentation rate of 79 mm/h. In total, 88.9% had an associated disease, with the most frequent being neutrophilic dermatosis (43.5%) and inflammatory bowel disease (31.5%); associated disease was inactive during abscess diagnosis in approximately one-quarter of patients. Moreover, 93.5% received corticosteroids with or without other agents, while 21.3% underwent excision surgery, which led to relapse if immunosuppressants were not concomitantly administered. No deaths were reported due to the syndrome, but 42.4% of cases that provided relevant data relapsed despite the relatively short follow-up period (median 1 year), either in the same or different organs. Combined immunomodulatory treatment, based on subgroup analysis, appeared protective against relapse in females and patients with splenic abscess or C-reactive protein >12 mg/dL (odds ratio 0.16 [95% CI 0.04–0.59]/p = 0.004, 0.09 [95% CI 0.01–0.62]/p = 0.008 and 0.23 [95% CI 0.06–0.92]/p = 0.03, respectively). Infection should always be the working diagnosis in patients with abscesses. However, if the infectious workup is negative, antimicrobials have failed, and no sepsis is present, then aseptic abscess syndrome should be considered; response to high-dose corticosteroids is a therapeutic criterion in almost all cases. Full article

Calcific aortic stenosis (CAS) is a newly emerging pandemic in elderly individuals due to the aging of the population in the world. Surgical Aortic Valve Replacement (SAVR) and Transcatheter Aortic Valve Replacement (TAVR) are the cornerstone of the management of severe aortic stenosis accompanied by one or more symptoms. Moreover, an appropriate interventional treatment of CAS, in elderly patients, is a very complex decision for heart teams, to avoid bad outcomes such as operative mortality, cardiovascular and all-cause death, hospitalization for heart failure, worsening of quality of life. In fact, CAS in the elderly is not only a focal valve disease, but a very complex clinical picture with different risk factors and etiologies, differing underlying pathophysiology, large phenotypic heterogeneity in a context of subjective biological, phenotypic and functional aging until frailty and disability. In this review, we analyzed separately and in a more integrated manner, the natural and prognostic histories of the progression of aortic stenosis, the phenotypes of myocardial damage and heart failure, within the metrics and aging trajectory. The aim is to suggest, during the clinical timing of valve disease, the best interval time for an appropriate and effective interventional treatment in each older patient, beyond subjective symptoms by integration of clinical, geriatric, chemical, and advanced imaging biomarkers. Full article

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

Sodium–glucose co-transporter-2 inhibitors (SGLT2is) and GLP-1 receptor agonists (GLP-1 RAs) are now established as cornerstone therapies for patients with type 2 diabetes mellitus (T2DM), given their cardiovascular and renal protective properties. However, their use in patients with peripheral artery disease (PAD) remains controversial due to concerns raised in early trials about potential increases in lower limb complications, particularly amputations. This narrative review examines current evidence on the association between SGLT2is and GLP-1 RAs in PAD-related outcomes, including limb events, amputation risk, and cardiovascular and renal endpoints. Drawing from randomized controlled trials, real-world cohort studies, and systematic reviews, we provide an integrated perspective on the safety and utility of SGLT2is and GLP-1 RAs in individuals with PAD, highlight patient selection considerations, and identify areas for future investigation. Full article

When there is an absence of disaster prevention measures, natural hazards can lead to disasters. An essential part of disaster risk management is the geospatial modeling of devastating hazards, where data sharing is of paramount importance in the context of early-warning systems. This research points out the usefulness of Spatial Data Infrastructures (SDIs) for disaster risk reduction through a literature review, focusing on the necessity of data unification and disposal. Initially, the principles of SDIs are presented, given the fact that this framework contributes significantly to the fulfilment of specific targets and priorities of the Sendai Framework for Disaster Risk Reduction 2015–2030. Thereafter, the challenges of SDIs are investigated in order to underline the main drawbacks stakeholders in emergency management have to come up against, namely the semantic misalignment that impedes efficient data retrieval, malfunctions in the interoperability of datasets and web services, the non-availability of the data in spite of their existence, and a lack of quality data, while also highlighting the obstacles of real case studies on national NSDIs. Thus, diachronic observations on disasters will not be made, despite these comprising a meaningful dataset in disaster mitigation. Consequently, the harmonization of national SDIs with international schemes, such as the Group on Earth Observations (GEO) and European Union’s space program Copernicus, and the usefulness of Artificial Intelligence (AI) and Machine Learning (ML) for disaster mitigation through the prediction of natural hazards are demonstrated. In this paper, for the purpose of disaster preparedness, real-world implementation barriers that preclude SDIs to be completed or deter their functionality are presented, culminating in the proposed future research directions and topics for the SDIs that need further investigation. SDIs constitute an ongoing collaborative effort intending to offer valuable operational tools for decision-making under the threat of a devastating event. Despite the operational potential of SDIs, the complexity of data standardization and coordination remains a core challenge. Full article

This systematic review examines how machine learning (ML) and generative AI (GenAI) have been integrated into learning analytics (LA) in higher education (2018–2025). Following PRISMA 2020, we screened 9590 records and included 101 English-language, peer-reviewed empirical studies that applied ML or GenAI within LA contexts. Records came from 12 databases (last search 15 March 2025), and the results were synthesized via thematic clustering. ML approaches dominate LA tasks, such as engagement prediction, dropout-risk modelling, and academic-performance forecasting, whereas GenAI—mainly transformer models like GPT-4 and BERT—is emerging in real-time feedback, adaptive learning, and sentiment analysis. Studies spanned world regions. Most ML papers (n = 75) examined engagement or dropout, while GenAI papers (n = 26) focused on adaptive feedback and sentiment analysis. No formal risk-of-bias assessment was conducted due to heterogeneity. While ML methods are well-established, GenAI applications remain experimental and face challenges related to transparency, pedagogical grounding, and implementation feasibility. This review offers a comparative synthesis of paradigms and outlines future directions for responsible, inclusive, theory-informed AI use in education. Full article

The shift from Internal Combustion Engine Vehicles (ICEVs) to Battery Electric Vehicles (BEVs) has accelerated global efforts to decarbonize transportation. However, battery degradation, high costs, and limited lifespan remain critical barriers. This review synthesizes recent innovations to extend Li-ion battery life in BEVs by exploring advances in degradation modeling, adaptive Battery Management Systems (BMSs), electronic component simulations, and real-world usage profiling. The authors have systematically analyzed over 80 recent studies using a PRISMA-guided review protocol. A novel comparative framework highlights gaps in current literature, particularly regarding real-world driving impacts, ripple current effects, and second-life battery applications. This review article critically compares model-driven, data-driven, and hybrid model approaches, emphasizing trade-offs in interpretability, accuracy, and deployment feasibility. Finally, the review links battery life extension to broader sustainability metrics, including circular economy models and predictive maintenance algorithms. This review offers actionable insights for researchers, engineers, and policymakers aiming to design longer-lasting and more sustainable electric mobility systems. Full article

Coffee is one of the most widely consumed beverages globally, with over 60% of Americans drinking it daily. This review examines coffee’s multifaceted impact on health and well-being, drawing on decades of research. Overall, the consensus is that moderate coffee intake is more beneficial than harmful across a wide range of health outcomes. Numerous large-scale, prospective cohort studies from around the world have consistently shown that moderate coffee consumption—typically three to five cups per day—is associated with reduced overall mortality and lower risk of major diseases such as cardiovascular diseases, diabetes, stroke, respiratory conditions, cognitive decline, and potentially several types of cancer, including liver and uterine cancers. Both caffeinated and decaffeinated coffee have shown benefits. The addition of sugar and cream to coffee may attenuate coffee’s positive health effects. Despite historical concerns, coffee consumption is not linked to increased risks of cancer, hypertension, or arrhythmia. However, some concerns remain. For pregnant women, coffee consumption should be limited to lower amounts, such that the daily intake of caffeine does not exceed 200 mg/day. Also, excessive caffeinated coffee intake may cause anxiety or sleep disturbances. Coffee’s health-promoting mechanisms include improved glucose balancing, increased physical activity, increased fat oxidation, improved lung function, and reduced inflammation. Beyond mortality and chronic diseases, coffee consumption affects many aspects of well-being: it supports hydration, boosts mental acuity, enhances physical performance, and may aid bowel recovery after surgery. While the field is well-studied via long-term observational cohorts, future research should focus on randomized controlled trials, Mendelian randomization studies, and granular analyses of coffee types and additives. Full article

Acute lymphoblastic leukemia (ALL) is a heterogeneous hematologic malignancy defined by the uncontrolled proliferation of lymphoid precursors. Accurate diagnosis and effective therapeutic strategies hinge on a comprehensive understanding of the genetic and molecular landscape of ALL. This review synthesizes the latest updates in cytogenetic and molecular classifications, emphasizing the 2022 World Health Organization (WHO) and International Consensus Classification (ICC) revisions. Key chromosomal alterations such as BCR::ABL1 and ETV6::RUNX1 and emerging subtypes including Ph-like ALL, DUX4, and MEF2D rearrangements are examined for their prognostic significance. Furthermore, we assess novel diagnostic tools, notably next-generation sequencing (NGS) and optical genome mapping (OGM). While NGS excels at identifying point mutations and small indels, OGM offers high-resolution structural variant detection with 100% sensitivity in multiple validation studies. These advancements enhance our grasp of leukemogenesis and pave the way for precision medicine in both B- and T-cell ALL. Ultimately, integrating these innovations into routine diagnostics is crucial for personalized patient management and improving clinical outcomes. Full article

The rapid advancement of underwater wireless communication technologies is critical to unlocking the full potential of marine resource exploration and environmental monitoring. This paper reviews recent progress in three primary modalities: underwater acoustic communication, radio frequency (RF) communication, and underwater optical wireless communication (UWOC), each designed to address specific challenges posed by complex underwater environments. Acoustic communication, while effective for long-range transmission, is constrained by ambient noise and high latency; recent innovations in noise reduction and data rate enhancement have notably improved its reliability. RF communication offers high-speed, short-range capabilities in shallow waters, but still faces challenges in hardware miniaturization and accurate channel modeling. UWOC has emerged as a promising solution, enabling multi-gigabit data rates over medium distances through advanced modulation techniques and turbulence mitigation. Additionally, bio-inspired approaches such as electric field communication provide energy-efficient and robust alternatives under turbid conditions. This paper further examines the practical integration of these technologies in underwater platforms, including autonomous underwater vehicles (AUVs), highlighting trade-offs between energy efficiency, system complexity, and communication performance. By synthesizing recent advancements, this review outlines the advantages and limitations of current underwater communication methods and their real-world applications, offering insights to guide the future development of underwater communication systems for robotic and vehicular platforms. Full article

Breast cancer is the leading cause of cancer-related mortality among women world-wide, and early screening is critical for improving patient survival. Medical imaging plays a central role in breast cancer screening, diagnosis, and treatment monitoring. However, conventional imaging modalities—including mammography, ultrasound, and magnetic resonance imaging—face limitations such as low diagnostic specificity, relatively slow imaging speed, ionizing radiation exposure, and dependence on exogenous contrast agents. Photoacoustic imaging (PAI), a novel hybrid imaging technique that combines optical contrast with ultrasonic spatial resolution, has shown great promise in addressing these challenges. By revealing anatomical, functional, and molecular features of the breast tumor microenvironment, PAI offers high spatial resolution, rapid imaging, and minimal operator dependence. This review outlines the fundamental principles of PAI and systematically examines recent advances in its application to breast cancer screening, diagnosis, and therapeutic evaluation. Furthermore, we discuss the translational potential of PAI as an emerging breast imaging modality, complementing existing clinical techniques. Full article

This research examines the compounding risks of global environmental change, including climate change, environmental law, biodiversity loss, and pollution, which threaten the stability of economic systems worldwide. While digital technology and global governance regulation are increasingly being proposed as solutions, their synergistic potential in advancing economic sustainability has been less explored. How can these technologies mitigate environmental risks while promoting sustainable and equitable development, aligning with the Sustainable Development Goals? We analyze policy global environmental data from the World Bank and the United Nations, as well as literature reviews on digital interventions, artificial intelligence, and smart databases. Global environmental change presents economic stability and rule of law threats, and innovative governance responses are needed. This study evaluates the potential for digital technology to be leveraged to enhance climate resilience and regulatory systems and address key implementation, equity, and policy coherence deficits. Policy recommendations for aligning economic development trajectories with planetary boundaries emphasize that proactive digital governance integration is indispensable for decoupling growth from environmental degradation. However, fragmented governance and unequal access to technologies undermine scalability. Successful experiences demonstrate that integrated policies, combining incentives, data transparency, and multilateral coordination, deliver maximum economic and environmental co-benefits, matching digital innovation with good governance. We provide policymakers with an action plan to leverage technology as a multiplier of sustainability, prioritizing inclusive governance structures to address implementation gaps and inform legislation. Full article