Search Results (622)

Alzheimer’s disease is a devastating progressive neurodegenerative disorder characterized by extracellular amyloid-beta plaques and intracellular tau tangles. Despite recent advancements in amyloid-beta-targeting immunotherapies, achieving safe and definitive disease control remains a profound clinical challenge. The CRISPR/Cas9 system has emerged as a powerful technology for precision neurogenetics, offering significant potential to address the fundamental questions behind Alzheimer’s disease. This comprehensive review delineates the trajectory of CRISPR applications in Alzheimer’s disease research and therapeutics. First, we explore the integration of CRISPR in engineering high-fidelity in vitro models, such as isogenic induced pluripotent stem cells and three-dimensional cerebral organoids, alongside advanced in vivo mammalian models. Second, we examine how these platforms facilitate unbiased high-throughput genetic screening to uncover molecular underpinnings regulating tau, lipid metabolism, and neuroinflammation. Third, we critically evaluate precision editing strategies targeting core risk genes (APP, MAPT, APOE, and TREM2), explicitly highlighting the severe physiopathological trade-offs between therapeutic efficacy and loss-of-function toxicity. Finally, we address the ultimate translational bottlenecks impeding clinical application. By dissecting the packaging limits of adeno-associated viral vectors and the physical barricade of the blood–brain barrier, we underscore the necessity of transitioning toward next-generation base editors and non-viral lipid nanoparticles to realize safe and efficacious in vivo clinical gene therapies against Alzheimer’s disease. Full article

Automated customer service and algorithmic governance are common in digital marketplaces, yet trust can erode when logistics, refunds, and escalation fail. Complaint-based risk and trust narratives in Turkey’s e-commerce marketplaces are analyzed for January 2019–December 2025 using 118,173 de-identified Turkish and English texts from Şikayetvar, a leading Turkish online consumer-complaint portal, and reviews of official marketplace apps on Google Play and the Apple App Store. BERTopic is implemented in Python with multilingual transformer embeddings, UMAP, HDBSCAN, and c-TF-IDF representations. The selected model identifies 35 micro-topics grouped into five macro-themes: fulfillment disruptions, remediation frictions, product-integrity risks, escalation failures, and governance threats. Monthly probability-weighted prevalence is estimated, and marketplace differences are evaluated with divergence measures, permutation tests, and multinomial regression controlling for time and language. Changepoint tests indicate a shift toward fulfillment grievances in April 2020, rising governance threats from June 2022, and increasing escalation failures linked to automated support from February 2023. These patterns suggest that barriers to human escalation convert operational incidents into platform-level trust judgments, offering monitoring signals for service recovery, marketplace governance, and AI oversight. By isolating escalation failures as a distinct complaint domain, the study links service automation to procedural justice mechanisms that translate operational breakdowns into platform-level trust and risk judgments. Full article

Research on information and communication technologies (ICTs) in sustainable agriculture has largely been technocentric, focusing on effectiveness, efficiency, and adoption, with limited consideration of end-user perceptions in practice. This study addresses this gap by examining perceptions of mobile gardening apps as accessible ICT tools that may support sustainable behaviours. Based on over 180,000 user reviews from Google Play and the Apple App Store, Contextualized Topic Modeling (CTM) was used to identify key themes and interpret them within the Theory of Consumption Value (TCV) framework. This approach allows for the analysis of functional, emotional, and epistemic dimensions of user experiences based on large-scale, real-world data. The results indicate that functional aspects, such as reliability and usability, dominate app evaluation, but emotional engagement and knowledge acquisition also play a significant role. By combining a data-driven approach with a well-established behavioural framework, this study bridges the gap between technological and user perspectives. It simultaneously extends the application of the TCV to the field of ICT solutions supporting sustainable development and provides practical guidance for designing more effective gardening apps. Full article

Physical inactivity is a major preventable cause of non-communicable disease and premature mortality. Mobile health interventions can promote physical activity, but their effectiveness depends on the ability to adapt to user’s context and motivation. Reinforcement learning (RL), particularly contextual bandits (CBs), offers a promising framework for such adaptive personalization. However, in practice, RL-based models face the cold start problem (CSP), due to the lack of initial training data. This study examines whether theory-driven simulated data can mitigate the CSP in training RL systems for personalized physical activity recommendations. A scoping review of 18 empirical studies on the Integrated Behavioral Change Model (IBC) provided population parameters for key constructs, used to simulate 2000 virtual users via multivariate modeling and structural equation calibration. A CB algorithm with an ε-greedy policy was trained with this dataset and compared with data from real world pilot using the Apptivate mHealth web-app (n = 588). Results showed close alignment between simulated and real behaviors. Our findings demonstrate that behaviorally informed synthetic data can effectively be used to train RL algorithms, offering an interpretable, sustainable, scalable, and privacy-safe solution to the CSP in personalized digital health interventions. Full article

The rapid expansion of market-driven software product development has led to the increasing use of User-Generated Content (UGC), such as mobile application user reviews, as a valuable source of requirements. However, unlike the traditional requirements engineering (RE) process, data-driven RE introduces several challenges, particularly in requirements elicitation and prioritization. Traditional requirements prioritization techniques typically rely on stakeholders’ involvement; however, in data-driven and market-driven development contexts, explicit stakeholders are often absent. Thus, we propose a DAta-driven Requirements Prioritization (DARP) framework that integrates Natural Language Processing (NLP), topic modeling, and Large Language Models (LLMs) to automate requirements prioritization in a data-driven development context. The proposed framework utilizes BERTopic to identify latent topics in user reviews and incorporates Hierarchical Density-Based Spatial Clustering of Applications with Noise (HDBSCAN) to group semantically related requirements. The proposed framework introduces a robust and automated prioritization applied to mobile app reviews. The scope of the proposed framework is user-perspective prioritization. Our objective is to detect insights from app reviews to reflect the voice of the customer. The results indicate that leveraging NLP and topic modeling techniques provides an effective data-driven approach to requirements prioritization. Full article

The rapid expansion of mobile healthcare (mHealth) applications has transformed health-related e-commerce, creating new challenges for understanding and responding to user needs. This study proposes a data-driven framework to systematically identify and prioritize unmet user requirements from negative reviews of Chinese mHealth applications. Using a dataset of 31,124 user reviews collected between 2019 and 2025, the framework integrates sentiment analysis, topic modeling, and machine learning regression to uncover six key areas of user concern and examine their temporal evolution. Among several predictive models linking user concerns to app ratings, the k-nearest neighbors (KNN) model demonstrated superior performance. Subsequent SHAP-based interpretability analysis reveals that account authentication, system accessibility, and application stability have the most significant impact on user ratings, highlighting the critical roles of trust and technical reliability in health e-commerce. This research not only provides actionable insights for platform governance but also contributes a generalizable methodology for leveraging user-generated content to inform evidence-based management and policy decisions in mobile digital services. Full article

Background: Chronic kidney disease (CKD) and end-stage renal disease (ESRD) represent a growing global health burden, affecting nearly one in ten adults worldwide. CKD is associated with high morbidity, premature mortality, reduced quality of life and enormous healthcare costs, and is primarily driven by dialysis and kidney transplantation. The silent and progressive nature of CKD means that most patients are diagnosed late, when irreversible damage has already occurred and costly kidney replacement therapies (KRT) become necessary. Dialysis services are resource-intensive, requiring significant infrastructure, specialized staff, and consumables, which makes them especially challenging to sustain in low- and middle-income countries. Traditional models of nephrology, care center-based dialysis and fragmented follow-up are increasingly inadequate in meeting the demands of a rising CKD population. These challenges highlight the urgent need for innovative approaches that enhance efficiency, improve patient outcomes, and expand access. Objective: This review aims to analyze the current landscape of information and communication technology (ICT) applications in nephrology and to evaluate how digital innovations are reconfiguring kidney therapy. Specifically, it seeks to identify the major ICT tools that are currently in use, assess their clinical and operational impact, and discuss their role in creating more sustainable, patient-centered kidney care models. This study reviews and analyzes ICT tools that are reconfiguring nephrology, including remote monitoring, AI, wearables, patient engagement apps and data dashboards. Methods: Narrative and scoping review of recent innovations in nephrology, including remote patient monitoring (RPM), telehealth, artificial intelligence (AI) analytics, wearable sensors, and clinical decision support platforms. Results: ICT tools such as Sharesource, Versia, telenephrology platforms, medical assistant for Chronic Care Service (MACCS), AI-based predictive analytics, wearable devices and patient engagement apps have improved patient outcomes, adherence, and early detection of complications. Key metrics include technique survival, hospitalization rate, patient-reported outcomes, workflow efficiency, and prediction accuracy. The relevant literature describing the potential of digital health technologies, including ICT platforms, artificial intelligence tools, and remote monitoring systems, to transform nephrology care was retrieved and screened for inclusion in this narrative review. Conclusions: ICT has shifted nephrology from reactive to proactive care, enhancing accessibility, patient empowerment and clinical efficiency. Future directions include precision nephrology, fully wearable kidneys, AI integration and large language models for education and triage. Challenges include digital divide, regulatory heterogeneity, cost and the need for long-term evidence. Full article

Rapid access to building intelligence is critical for emergency response, yet paper fire safety instructions (FSi) often provide limited utility under stress. This structured narrative review addresses the “information gap” between unit arrival and decision-making by analyzing the legal admissibility, technological requirements, and security risks of digital FSi across Poland, Germany, France, Belgium, and Hungary. While no explicit prohibition of digital forms was identified, enforcement practices prioritize paper as the evidentiary master. Consequently, we propose a hybrid model: a paper master for compliance and redundancy, supplemented by a digital operational overlay accessed via “zero-install” offline-first progressive web apps (PWA). The review defines a minimum operational dataset (MOD)—prioritizing critical data like utility shut-offs and hazards over full documentation—and addresses cybersecurity threats, specifically QR-phishing (“quishing”). We conclude that the hybrid model minimizes legal and operational risks while significantly reducing time-to-information, provided that strict content identity and change management protocols are maintained. Full article

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder and the leading cause of dementia, for which there is currently no cure. The causes of AD are still not well understood, although 5% of cases are known to have a genetic origin, associated with pathogenic genetic variants of the APP and PSEN1/2 genes. There is growing evidence that both APP and PSEN1/2 are also essential for proper human brain development and neural/neuronal function. This implies that abnormalities in early brain development could increase neuronal vulnerability to AD later in life. Human cerebral organoids (hCOs), generated from induced pluripotent stem cells (iPSCs) from AD patients, provide an exceptional model for better understanding the cellular and molecular mechanisms involved in human brain development, as well as early neurological alterations in the evolution of AD. This review compiles the main studies in which hCOs are used as a model for studying AD and for the discovery of new biomarkers. We also discuss the advantages and applications of these hCOs for studying the early stages of AD from a neurodevelopmental perspective. Finally, we mention the main current challenges in the use of hCOs for future research into AD. Full article

Food safety can be regarded as a critical aspect of consumer protection, and there is a clear need for related research within the context of food delivery apps. In addition, food safety is a multidimensional concept, and its definition may vary depending on the specific context in which it is examined. Therefore, this work investigates food safety in the case of food delivery apps from the perspective of consumers in the Korean market. Food safety was conceptualized through four sub-dimensions: food healthiness, eco-friendly packaging, review information, and hygiene. The study examined the effects of these four factors on trust in food delivery apps and the influence of trust on continuance intention. Also, this work inspects the moderating role of hygiene in the relationship between trust and continuance intention. The survey participants were recruited via an online survey conducted through a professional research firm, yielding 300 valid responses. Hypotheses were tested using structural equation modeling and Hayes’ Process Macro Model 1. The results show that trust is positively influenced by eco-friendly packaging, review information, and hygiene. Additionally, trust significantly affects continuance intention, with hygiene demonstrating a significant moderating effect. This research contributes to the literature by clarifying the definition of food safety in food delivery apps and elucidating the relationships among its key sub-dimensions. Full article

The article aimed to review the current literature analysing the complexity of an exercise-induced acute phase response in athletic horses undergoing intense training and endurance competitions. Since the endurance discipline demands physical fitness, exceptional health and excellent adaptation to an increasing workload, diagnostic methods of assessing the factors mentioned above are highly required. Athletic horses in endurance training undergo numerous metabolic but also immune adaptations, including changes in pro-inflammatory and anti-inflammatory cytokine levels. The inflammatory reaction resembles typical inflammation only to some extent; therefore, the term exercise-induced acute phase response (APR) has been introduced. Among many biomarkers, acute phase proteins (APPs), like serum amyloid A (SAA) and different types of cytokines, especially interleukin 1 (IL-1), interleukin 6 (IL-6), and tumour necrosis factor α (TNF-α), appear to play a key role. These markers may be modulated by many factors; however, proper training seems to result in the occurrence of an “anti-inflammatory state”, which is beneficial for the horse’s health and highly required in high-performance equine athletes. Further understanding of the inflammatory reaction associated with extreme physical effort is crucial for ensuring the long-term career and welfare of endurance horses. Full article

Female sports science has historically relied on evidence derived largely from male cohorts, despite known menstrual-cycle-related hormonal effects on thermoregulation, metabolism, and performance in women. We developed an Android application to support female athletes in documenting menstrual health alongside self-rated sports performance, addressing an underexplored area in current mobile health tools. The app was built in the Massachusetts Institute of Technology’s App Inventor following a rapid application development process (requirements determination, user design, construction, and implementation). Implemented features include period-date recording and prediction, health and performance logging, record review, basic personalization, and phase-specific, non-personalized training and nutrition tips. Unit test results verified core functions, including date recording, period prediction, navigation, and record retrieval, and a small-sample usability assessment (n = 5) using the system usability scale indicated above-average usability. In conclusion, the application offers a practical tool for period-date and symptom tracking with integrated performance self-logging. Full article

Background/Objectives: Promoting healthy and sustainable food choices is critical to address environmental and public health challenges, prevent health issues and enhance psychological well-being. Technological tools have shown promising results in supporting the adoption of many sustainable practices and in improving dysfunctional eating behaviors in clinical psychological settings. However, their potential to encourage healthy and sustainable eating choices in the general population through psychological or behavioral strategies remains understudied and unsystematically observed. Methods: A systematic review was conducted following PRISMA guidelines to (1) investigate digital tools and interventions aimed at improving healthy and sustainable eating behaviors, and (2) categorize the psychological or behavioral strategies they implemented. Four databases (PsycINFO, PsycArticles, PubMed, ProQuest) were searched combining keywords on sustainable diets (e.g., “sustainable diet,” “food sustainability”) and technological tools (e.g., “virtual reality,” “mobile app,” “web app”). Results: N = 16 studies were included. N = 7 (44%) used mobile app-based tools, n = 6 (38%) were virtual reality, n = 2 (12%) were web platforms, and n = 1 (6%) was an instant-messaging system. Digital tools and interventions were useful in promoting healthy and sustainable eating behaviors by implementing psychological or behavioral strategies like awareness (n = 10, 63%), decision-making (n = 6, 38%), emotion regulation (n = 3, 19%), nudging (n = 5, 31%), self-efficacy (n = 5, 31%) and self-monitoring (n = 4, 25%). Only a few studies included follow-ups (n = 5, 31%). Conclusions: Findings suggest that digital technologies have the potential to improve healthy and sustainable eating behaviors in the general population. However, given heterogeneity and methodological issues of studies, more longitudinal and rigorous research is needed to confirm the effectiveness and long-term benefits of different technological tools. Full article

Despite advancements in navigation apps for wheelchair users, there is no consensus on which environmental factors to prioritize for personalized accessible routes. This scoping review synthesizes factors influencing wheelchair mobility in urban settings, evaluates measurement methods, and assesses their integration into routing algorithms. Following Arksey and O’Malley’s framework and PRISMA-ScR guidelines, we analyzed six databases for English-language articles from 2005 to 2023, supplemented by an updated search covering 2023 to 2026. Two reviewers screened 6966 records and examined 79 full-text articles, with 24 meeting the inclusion criteria for data extraction. Environmental factors were categorized into static and dynamic factors affecting mobility. Key components included sidewalks (96%), ramps (63%), curb cuts (54%), stairs (50%), crosswalks (50%), and streets (38%). Common factors examined were length, slope, width, and surface properties. Data collection methods varied: 42% relied on measurements, 8% used user assessments and sensors, while 50% combined both approaches. Recent studies (2023–2026) demonstrate increasing adoption of AI and machine learning techniques, including crowdsourced smartphone data and generative AI for feature detection. This review identifies essential factors for wheelchair navigation and highlights significant gaps in dynamic factor assessment and real-time data integration. Full article

Hydrotherapy tourism is a significant and long-standing area of interest, with countries worldwide employing innovative strategies to attract tourists. It not only offers desirable benefits but also plays a role in the development of tourist destinations. This research aims to identify critical success factors for tourist attraction in a prominent destination in northwest Iran, particularly in Ardabil Province (Sareyn county). It utilizes a mixed-method approach, employing the Partially Mixed Sequential Dominant Status Design methodology across three phases: qualitative, qualitative, and quantitative. The study employs sequential methods including scoping review, Delphi, and surveys to achieve its objectives. Data collection involved utilizing reputable scientific databases in the initial phase. Subsequently, 15 experts underwent purposeful selection for interviews and three rounds of Delphi surveys in the second phase. In the third phase, data collection was conducted through a questionnaire tool. Initially, approximately 141 relevant studies were identified, narrowed down to 11 primary ones using the scoping review checklist. Then, experts utilized the qualitative Delphi method to confirm and extract effective indices, resulting in 6 components and 50 indices. Finally, 61 experts provided feedback on confirming or rejecting these components and indices in the quantitative survey phase. The quantitative survey highlighted key factors influencing hydrotherapy tourism in Sareyn, such as supportive services, community backing, and smart destination management. Prioritizing healthcare, safety, reputation enhancement, and digital initiatives, like modern infrastructure, specialized apps, and social media engagement, is essential. These elements significantly impact tourist satisfaction and engagement, shaping Sareyn County’s hydrotherapy tourism. Strengthening these factors can boost its appeal, economic contribution, and status as a leading tourist destination in Ardabil Province and beyond. Full article