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25 pages, 1534 KiB  
Review
Recent Advances in Micro- and Nano-Enhanced Intravascular Biosensors for Real-Time Monitoring, Early Disease Diagnosis, and Drug Therapy Monitoring
by Sonia Kudłacik-Kramarczyk, Weronika Kieres, Alicja Przybyłowicz, Celina Ziejewska, Joanna Marczyk and Marcel Krzan
Sensors 2025, 25(15), 4855; https://doi.org/10.3390/s25154855 (registering DOI) - 7 Aug 2025
Abstract
Intravascular biosensors have become a crucial and novel class of devices in healthcare, enabling the constant real-time monitoring of essential physiological parameters directly within the circulatory system. Recent developments in micro- and nanotechnology have relevantly improved the sensitivity, miniaturization, and biocompatibility of these [...] Read more.
Intravascular biosensors have become a crucial and novel class of devices in healthcare, enabling the constant real-time monitoring of essential physiological parameters directly within the circulatory system. Recent developments in micro- and nanotechnology have relevantly improved the sensitivity, miniaturization, and biocompatibility of these devices, thereby enabling their application in precision medicine. This review summarizes the latest advances in intravascular biosensor technologies, with a special focus on glucose and oxygen level monitoring, blood pressure and heart rate assessment, and early disease diagnostics, as well as modern approaches to drug therapy monitoring and delivery systems. Key challenges such as long-term biostability, signal accuracy, and regulatory approval processes are critical considerations. Innovative strategies, including biodegradable implants, nanomaterial-functionalized surfaces, and integration with artificial intelligence, are regarded as promising avenues to overcome current limitations. This review provides a comprehensive roadmap for upcoming research and the clinical translation of advanced intravascular biosensors with a strong emphasis on their transformative impact on personalized healthcare. Full article
(This article belongs to the Section Biosensors)
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25 pages, 1054 KiB  
Review
Gut Feeling: Biomarkers and Biosensors’ Potential in Revolutionizing Inflammatory Bowel Disease (IBD) Diagnosis and Prognosis—A Comprehensive Review
by Beatriz Teixeira, Helena M. R. Gonçalves and Paula Martins-Lopes
Biosensors 2025, 15(8), 513; https://doi.org/10.3390/bios15080513 (registering DOI) - 7 Aug 2025
Abstract
Inflammatory Bowel Diseases (IBDs) are complex, multifactorial disorders with no known cure, necessitating lifelong care and often leading to surgical interventions. This ongoing healthcare requirement, coupled with the increased use of biological drugs and rising disease prevalence, significantly increases the financial burden on [...] Read more.
Inflammatory Bowel Diseases (IBDs) are complex, multifactorial disorders with no known cure, necessitating lifelong care and often leading to surgical interventions. This ongoing healthcare requirement, coupled with the increased use of biological drugs and rising disease prevalence, significantly increases the financial burden on the healthcare systems. Thus, a number of novel technological approaches have emerged in order to face some of the pivotal questions still associated with IBD. In navigating the intricate landscape of IBD, biosensors act as indispensable allies, bridging the gap between traditional diagnostic methods and the evolving demands of precision medicine. Continuous progress in biosensor technology holds the key to transformative breakthroughs in IBD management, offering more effective and patient-centric healthcare solutions considering the One Health Approach. Here, we will delve into the landscape of biomarkers utilized in the diagnosis, monitoring, and management of IBD. From well-established serological and fecal markers to emerging genetic and epigenetic markers, we will explore the role of these biomarkers in aiding clinical decision-making and predicting treatment response. Additionally, we will discuss the potential of novel biomarkers currently under investigation to further refine disease stratification and personalized therapeutic approaches in IBD. By elucidating the utility of biosensors across the spectrum of IBD care, we aim to highlight their importance as valuable tools in optimizing patient outcomes and reducing healthcare costs. Full article
(This article belongs to the Special Issue Feature Papers of Biosensors)
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24 pages, 639 KiB  
Review
A Systemic Perspective of the Link Between Microbiota and Cardiac Health: A Literature Review
by Ionica Grigore, Oana Roxana Ciobotaru, Delia Hînganu, Gabriela Gurau, Dana Tutunaru and Marius Valeriu Hînganu
Life 2025, 15(8), 1251; https://doi.org/10.3390/life15081251 - 7 Aug 2025
Abstract
Cardiovascular diseases (CVDs) are the leading global cause of death, with long-term hospitalization becoming increasingly frequent in advanced or chronic cases. In this context, the interplay between systemic factors such as lipid metabolism, circulating metabolites, gut microbiota, and oral health is gaining attention [...] Read more.
Cardiovascular diseases (CVDs) are the leading global cause of death, with long-term hospitalization becoming increasingly frequent in advanced or chronic cases. In this context, the interplay between systemic factors such as lipid metabolism, circulating metabolites, gut microbiota, and oral health is gaining attention for its potential role in influencing inflammation, cardiometabolic risk, and long-term outcomes. Despite their apparent independence, these domains are increasingly recognized as interconnected and influential in cardiovascular pathophysiology. Methods: This narrative review was conducted by analyzing studies published between 2015 and 2024 from databases including PubMed, Scopus, and Web of Science. Keywords such as “lipid profile,” “metabolomics,” “gut microbiota,” “oral health,” and “cardiovascular disease” were used. Original research, meta-analyses, and reviews relevant to hospitalized cardiac patients were included. A critical integrative approach was applied to highlight cross-domain connections. Results and Discussion: Evidence reveals significant interrelations between altered lipid profiles, gut dysbiosis (including increased TMAO levels), metabolic imbalances, and oral inflammation. Each component contributes to a systemic pro-inflammatory state that worsens cardiovascular prognosis, particularly in long-term hospitalized patients. Despite isolated research in each domain, there is a paucity of studies integrating all four. The need for interdisciplinary diagnostic models and preventive strategies is emphasized, especially in populations with frailty or immobilization. Conclusions: Monitoring lipid metabolism, metabolomic shifts, gut microbial balance, and oral status should be considered part of comprehensive cardiovascular care. Gut microbiota exerts a dual role in cardiac health: when balanced, it supports anti-inflammatory and metabolic homeostasis; when dysbiotic, it contributes to systemic inflammation and worsened cardiac outcomes. Future research should aim to develop integrative screening tools and personalized interventions that address the multifactorial burden of disease. A systemic approach may improve both short- and long-term outcomes in this complex and vulnerable patient population. Full article
(This article belongs to the Special Issue The Emerging Role of Microbiota in Health and Diseases)
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35 pages, 3289 KiB  
Review
Applications of Machine Learning Algorithms in Geriatrics
by Adrian Stancu, Cosmina-Mihaela Rosca and Emilian Marian Iovanovici
Appl. Sci. 2025, 15(15), 8699; https://doi.org/10.3390/app15158699 (registering DOI) - 6 Aug 2025
Abstract
The increase in the elderly population globally reflects a change in the population’s mindset regarding preventive health measures and necessitates a rethinking of healthcare strategies. The integration of machine learning (ML)-type algorithms in geriatrics represents a direction for optimizing prevention, diagnosis, prediction, monitoring, [...] Read more.
The increase in the elderly population globally reflects a change in the population’s mindset regarding preventive health measures and necessitates a rethinking of healthcare strategies. The integration of machine learning (ML)-type algorithms in geriatrics represents a direction for optimizing prevention, diagnosis, prediction, monitoring, and treatment. This paper presents a systematic review of the scientific literature published between 1 January 2020 and 31 May 2025. The paper is based on the applicability of ML techniques in the field of geriatrics. The study is conducted using the Web of Science database for a detailed discussion. The most studied algorithms in research articles are Random Forest, Extreme Gradient Boosting, and support vector machines. They are preferred due to their performance in processing incomplete clinical data. The performance metrics reported in the analyzed papers include the accuracy, sensitivity, F1-score, and Area under the Receiver Operating Characteristic Curve. Nine search categories are investigated through four databases: WOS, PubMed, Scopus, and IEEE. A comparative analysis shows that the field of geriatrics, through an ML approach in the context of elderly nutrition, is insufficiently explored, as evidenced by the 61 articles analyzed from the four databases. The analysis highlights gaps regarding the explainability of the models used, the transparency of cross-sectional datasets, and the validity of the data in real clinical contexts. The paper highlights the potential of ML models in transforming geriatrics within the context of personalized predictive care and outlines a series of future research directions, recommending the development of standardized databases, the integration of algorithmic explanations, the promotion of interdisciplinary collaborations, and the implementation of ethical norms of artificial intelligence in geriatric medical practice. Full article
(This article belongs to the Special Issue Diet, Nutrition and Human Health)
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7 pages, 337 KiB  
Proceeding Paper
Exposure to PM2.5 While Walking in the City Center
by Anna Mainka, Witold Nocoń, Aleksandra Malinowska, Julia Pfajfer, Edyta Komisarczyk and Pawel Wargocki
Environ. Earth Sci. Proc. 2025, 34(1), 2; https://doi.org/10.3390/eesp2025034002 - 6 Aug 2025
Abstract
This study investigates personal exposure to fine particulate matter (PM2.5) during walking commutes in Gliwice, Poland—a city characterized by elevated levels of air pollution. Data from a low-cost air quality sensor were compared with a municipal monitoring station and the Silesian [...] Read more.
This study investigates personal exposure to fine particulate matter (PM2.5) during walking commutes in Gliwice, Poland—a city characterized by elevated levels of air pollution. Data from a low-cost air quality sensor were compared with a municipal monitoring station and the Silesian University of Technology laboratory. PM2.5 concentrations recorded by the low-cost sensor (7.3 µg/m3) were lower than those reported by the stationary monitoring sites. The findings suggest that low-cost sensors may offer valuable insights into short-term peaks in PM2.5 exposure to serve as a practical tool for increasing public awareness of personal exposure risks to protect respiratory health. Full article
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19 pages, 487 KiB  
Review
Smart Clothing and Medical Imaging Innovations for Real-Time Monitoring and Early Detection of Stroke: Bridging Technology and Patient Care
by David Sipos, Kata Vészi, Bence Bogár, Dániel Pető, Gábor Füredi, József Betlehem and Attila András Pandur
Diagnostics 2025, 15(15), 1970; https://doi.org/10.3390/diagnostics15151970 - 6 Aug 2025
Abstract
Stroke is a significant global health concern characterized by the abrupt disruption of cerebral blood flow, leading to neurological impairment. Accurate and timely diagnosis—enabled by imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI)—is essential for differentiating stroke types and [...] Read more.
Stroke is a significant global health concern characterized by the abrupt disruption of cerebral blood flow, leading to neurological impairment. Accurate and timely diagnosis—enabled by imaging modalities such as computed tomography (CT) and magnetic resonance imaging (MRI)—is essential for differentiating stroke types and initiating interventions like thrombolysis, thrombectomy, or surgical management. In parallel, recent advancements in wearable technology, particularly smart clothing, offer new opportunities for stroke prevention, real-time monitoring, and rehabilitation. These garments integrate various sensors, including electrocardiogram (ECG) electrodes, electroencephalography (EEG) caps, electromyography (EMG) sensors, and motion or pressure sensors, to continuously track physiological and functional parameters. For example, ECG shirts monitor cardiac rhythm to detect atrial fibrillation, smart socks assess gait asymmetry for early mobility decline, and EEG caps provide data on neurocognitive recovery during rehabilitation. These technologies support personalized care across the stroke continuum, from early risk detection and acute event monitoring to long-term recovery. Integration with AI-driven analytics further enhances diagnostic accuracy and therapy optimization. This narrative review explores the application of smart clothing in conjunction with traditional imaging to improve stroke management and patient outcomes through a more proactive, connected, and patient-centered approach. Full article
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18 pages, 1056 KiB  
Article
Biomarkers of Metabolism and Inflammation in Individuals with Obesity and Normal Weight: A Comparative Analysis Exploring Sex Differences
by Eveline Gart, Jessica Snabel, Jelle C. B. C. de Jong, Lars Verschuren, Anita M. van den Hoek, Martine C. Morrison and Robert Kleemann
Int. J. Mol. Sci. 2025, 26(15), 7576; https://doi.org/10.3390/ijms26157576 - 5 Aug 2025
Abstract
Blood-based biomarkers allow monitoring of an individual’s health status and provide insights into metabolic and inflammatory processes in conditions like obesity, cardiovascular, and liver diseases. However, selecting suitable biomarkers and optimizing analytical assays presents challenges, is time-consuming and laborious. Moreover, knowledge of potential [...] Read more.
Blood-based biomarkers allow monitoring of an individual’s health status and provide insights into metabolic and inflammatory processes in conditions like obesity, cardiovascular, and liver diseases. However, selecting suitable biomarkers and optimizing analytical assays presents challenges, is time-consuming and laborious. Moreover, knowledge of potential sex differences remains incomplete as research is often carried out in men. This study aims at enabling researchers to make informed choices on the type of biomarkers, analytical assays, and dilutions being used. More specifically, we analyzed plasma concentrations of >90 biomarkers using commonly available ELISA or electrochemiluminescence-based multiplex methods, comparing normal weight (BMI < 25; n = 40) with obese (BMI > 30; n = 40) adult blood donors of comparable age. To help choose optimal biomarker sets, we grouped frequently employed biomarkers into biological categories (e.g., adipokines, acute-phase proteins, complement factors, cytokines, myokines, iron metabolism, vascular inflammation), first comparing normal-weight with obese persons, and thereafter exploratively comparing women and men within each BMI group. Many biomarkers linked to chronic inflammation and dysmetabolism were elevated in persons with obesity, including several adipokines, interleukins, chemokines, acute-phase proteins, complement factors, and oxidized LDL. Further exploration suggests sex disparities in biomarker levels within both normal-weight and obese groups. This comprehensive dataset of biomarkers across diverse biological domains constitutes a reference resource that may provide valuable guidance for researchers in selecting appropriate biomarkers and analytical assays for own studies. Moreover, the dataset highlights the importance of taking possible sex differences into account. Full article
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17 pages, 2283 KiB  
Article
A Remote Strawberry Health Monitoring System Performed with Multiple Sensors Approach
by Xiao Du, Jun Steed Huang, Qian Shi, Tongge Li, Yanfei Wang, Haodong Liu, Zhaoyuan Zhang, Ni Yu and Ning Yang
Agriculture 2025, 15(15), 1690; https://doi.org/10.3390/agriculture15151690 - 5 Aug 2025
Abstract
Temperature is a key physiological indicator of plant health, influenced by factors including water status, disease and developmental stage. Monitoring changes in multiple factors is helpful for early diagnosis of plant growth. However, there are a variety of complex light interference phenomena in [...] Read more.
Temperature is a key physiological indicator of plant health, influenced by factors including water status, disease and developmental stage. Monitoring changes in multiple factors is helpful for early diagnosis of plant growth. However, there are a variety of complex light interference phenomena in the greenhouse, so traditional detection methods cannot meet effective online monitoring of strawberry health status without manual intervention. Therefore, this paper proposes a leaf soft-sensing method based on a thermal infrared imaging sensor and adaptive image screening Internet of Things system, with additional sensors to realize indirect and rapid monitoring of the health status of a large range of strawberries. Firstly, a fuzzy comprehensive evaluation model is established by analyzing the environmental interference terms from the other sensors. Secondly, through the relationship between plant physiological metabolism and canopy temperature, a growth model is established to predict the growth period of strawberries based on canopy temperature. Finally, by deploying environmental sensors and solar height sensors, the image acquisition node is activated when the environmental interference is less than the specified value and the acquisition is completed. The results showed that the accuracy of this multiple sensors system was 86.9%, which is 30% higher than the traditional model and 4.28% higher than the latest advanced model. It makes it possible to quickly and accurately assess the health status of plants by a single factor without in-person manual intervention, and provides an important indication of the early, undetectable state of strawberry disease, based on remote operation. Full article
(This article belongs to the Section Artificial Intelligence and Digital Agriculture)
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20 pages, 2267 KiB  
Article
Mechanical Properties of Collagen Implant Used in Neurosurgery Towards Industry 4.0/5.0 Reflected in ML Model
by Marek Andryszczyk, Izabela Rojek and Dariusz Mikołajewski
Appl. Sci. 2025, 15(15), 8630; https://doi.org/10.3390/app15158630 (registering DOI) - 4 Aug 2025
Viewed by 123
Abstract
Collagen implants in neurosurgery are widely used due to their biocompatibility, biodegradability, and ability to support tissue regeneration, but their mechanical properties, such as low tensile strength and susceptibility to enzymatic degradation, remain challenging. Current technologies are improving these implants through cross-linking, synthetic [...] Read more.
Collagen implants in neurosurgery are widely used due to their biocompatibility, biodegradability, and ability to support tissue regeneration, but their mechanical properties, such as low tensile strength and susceptibility to enzymatic degradation, remain challenging. Current technologies are improving these implants through cross-linking, synthetic reinforcements, and advanced manufacturing techniques such as 3D bioprinting to improve durability and predictability. Industry 4.0 is contributing to this by automating production, using data analytics and machine learning to optimize implant properties and ensure quality control. In Industry 5.0, the focus is shifting to personalization, enabling the creation of patient-specific implants through human–machine collaboration and advanced biofabrication. eHealth integrates digital monitoring systems, enabling real-time tracking of implant healing and performance to inform personalized care. Despite progress, challenges such as cost, material property variability, and scalability for mass production remain. The future lies in smart biomaterials, AI-driven design, and precision biofabrication, which could mean the possibility of creating more effective, accessible, and patient-specific collagen implants. The aim of this article is to examine the current state and determine the prospects for the development of mechanical properties of collagen implant used in neurosurgery towards Industry 4.0/5.0, including ML model. Full article
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25 pages, 1751 KiB  
Review
Large Language Models for Adverse Drug Events: A Clinical Perspective
by Md Muntasir Zitu, Dwight Owen, Ashish Manne, Ping Wei and Lang Li
J. Clin. Med. 2025, 14(15), 5490; https://doi.org/10.3390/jcm14155490 - 4 Aug 2025
Viewed by 202
Abstract
Adverse drug events (ADEs) significantly impact patient safety and health outcomes. Manual ADE detection from clinical narratives is time-consuming, labor-intensive, and costly. Recent advancements in large language models (LLMs), including transformer-based architectures such as Bidirectional Encoder Representations from Transformers (BERT) and Generative Pretrained [...] Read more.
Adverse drug events (ADEs) significantly impact patient safety and health outcomes. Manual ADE detection from clinical narratives is time-consuming, labor-intensive, and costly. Recent advancements in large language models (LLMs), including transformer-based architectures such as Bidirectional Encoder Representations from Transformers (BERT) and Generative Pretrained Transformer (GPT) series, offer promising methods for automating ADE extraction from clinical data. These models have been applied to various aspects of pharmacovigilance and clinical decision support, demonstrating potential in extracting ADE-related information from real-world clinical data. Additionally, chatbot-assisted systems have been explored as tools in clinical management, aiding in medication adherence, patient engagement, and symptom monitoring. This narrative review synthesizes the current state of LLMs in ADE detection from a clinical perspective, organizing studies into categories such as human-facing decision support tools, immune-related ADE detection, cancer-related and non-cancer-related ADE surveillance, and personalized decision support systems. In total, 39 articles were included in this review. Across domains, LLM-driven methods have demonstrated promising performances, often outperforming traditional approaches. However, critical limitations persist, such as domain-specific variability in model performance, interpretability challenges, data quality and privacy concerns, and infrastructure requirements. By addressing these challenges, LLM-based ADE detection could enhance pharmacovigilance practices, improve patient safety outcomes, and optimize clinical workflows. Full article
(This article belongs to the Section Pharmacology)
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13 pages, 238 KiB  
Perspective
Leveraging and Harnessing Generative Artificial Intelligence to Mitigate the Burden of Neurodevelopmental Disorders (NDDs) in Children
by Obinna Ositadimma Oleribe
Healthcare 2025, 13(15), 1898; https://doi.org/10.3390/healthcare13151898 - 4 Aug 2025
Viewed by 156
Abstract
Neurodevelopmental disorders (NDDs) significantly impact children’s health and development. They pose a substantial burden to families and the healthcare system. Challenges in early identification, accurate and timely diagnosis, and effective treatment persist due to overlapping symptoms, lack of appropriate diagnostic biomarkers, significant stigma [...] Read more.
Neurodevelopmental disorders (NDDs) significantly impact children’s health and development. They pose a substantial burden to families and the healthcare system. Challenges in early identification, accurate and timely diagnosis, and effective treatment persist due to overlapping symptoms, lack of appropriate diagnostic biomarkers, significant stigma and discrimination, and systemic barriers. Generative Artificial Intelligence (GenAI) offers promising solutions to these challenges by enhancing screening, diagnosis, personalized treatment, and research. Although GenAI is already in use in some aspects of NDD management, effective and strategic leveraging of evolving AI tools and resources will enhance early identification and screening, reduce diagnostic processing by up to 90%, and improve clinical decision support. Proper use of GenAI will ensure individualized therapy regimens with demonstrated 36% improvement in at least one objective attention measure compared to baseline and 81–84% accuracy relative to clinician-generated plans, customize learning materials, and deliver better treatment monitoring. GenAI will also accelerate NDD-specific research and innovation with significant time savings, as well as provide tailored family support systems. Finally, it will significantly reduce the mortality and morbidity associated with NDDs. This article explores the potential of GenAI in transforming NDD management and calls for policy initiatives to integrate GenAI into NDD management systems. Full article
13 pages, 1060 KiB  
Article
Condition Changes Before and After the Coronavirus Disease 2019 Pandemic in Adolescent Athletes and Development of a Non-Contact Medical Checkup Application
by Hiroaki Kijima, Toyohito Segawa, Kimio Saito, Hiroaki Tsukamoto, Ryota Kimura, Kana Sasaki, Shohei Murata, Kenta Tominaga, Yo Morishita, Yasuhito Asaka, Hidetomo Saito and Naohisa Miyakoshi
Sports 2025, 13(8), 256; https://doi.org/10.3390/sports13080256 - 4 Aug 2025
Viewed by 162
Abstract
During the coronavirus 2019 pandemic, sports activities were restricted, raising concerns about their impact on the physical condition of adolescent athletes, which remained largely unquantified. This study was designed with two primary objectives: first, to precisely quantify and elucidate the differences in the [...] Read more.
During the coronavirus 2019 pandemic, sports activities were restricted, raising concerns about their impact on the physical condition of adolescent athletes, which remained largely unquantified. This study was designed with two primary objectives: first, to precisely quantify and elucidate the differences in the physical condition of adolescent athletes before and after activity restrictions due to the pandemic; and second, to innovatively develop and validate a non-contact medical checkup application. Medical checks were conducted on 563 athletes designated for sports enhancement. Participants were junior high school students aged 13 to 15, and the sample consisted of 315 boys and 248 girls. Furthermore, we developed a smartphone application and compared self-checks using the application with in-person checks by orthopedic surgeons to determine the challenges associated with self-checks. Statistical tests were conducted to determine whether there were statistically significant differences in range of motion and flexibility parameters before and after the pandemic. Additionally, items with discrepancies between values self-entered by athletes using the smartphone application and values measured by specialists were detected, and application updates were performed. Student’s t-test was used for continuous variables, whereas the chi-square test was used for other variables. Following the coronavirus 2019 pandemic, athletes were stiffer than during the pre-pandemic period in terms of hip and shoulder joint rotation range of motion and heel–buttock distance. The dominant hip external rotation decreased from 53.8° to 46.8° (p = 0.0062); the non-dominant hip external rotation decreased from 53.5° to 48.0° (p = 0.0252); the dominant shoulder internal rotation decreased from 62.5° to 54.7° (p = 0.0042); external rotation decreased from 97.6° to 93.5° (p = 0.0282), and the heel–buttock distance increased from 4.0 cm to 10.4 cm (p < 0.0001). The heel–buttock distance and straight leg raising angle measurements differed between the self-check and face-to-face check. Although there are items that cannot be accurately evaluated by self-check, physical condition can be improved with less contact by first conducting a face-to-face evaluation under appropriate guidance and then conducting a self-check. These findings successfully address our primary objectives. Specifically, we demonstrated a significant decline in the physical condition of adolescent athletes following pandemic-related activity restrictions, thereby quantifying their impact. Furthermore, our developed non-contact medical checkup application proved to be a viable tool for monitoring physical condition with reduced contact, although careful consideration of measurable parameters is crucial. This study provides critical insights into the long-term effects of activity restrictions on young athletes and offers a practical solution for health monitoring during infectious disease outbreaks, highlighting the potential for hybrid checkup approaches. Full article
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45 pages, 5594 KiB  
Article
Integrated Medical and Digital Approaches to Enhance Post-Bariatric Surgery Care: A Prototype-Based Evaluation of the NutriMonitCare System in a Controlled Setting
by Ruxandra-Cristina Marin, Marilena Ianculescu, Mihnea Costescu, Veronica Mocanu, Alina-Georgiana Mihăescu, Ion Fulga and Oana-Andreia Coman
Nutrients 2025, 17(15), 2542; https://doi.org/10.3390/nu17152542 - 2 Aug 2025
Viewed by 354
Abstract
Introduction/Objective: Post-bariatric surgery patients require long-term, coordinated care to address complex nutritional, physiological, and behavioral challenges. Personalized smart nutrition, combining individualized dietary strategies with targeted monitoring, has emerged as a valuable direction for optimizing recovery and long-term outcomes. This article examines how traditional [...] Read more.
Introduction/Objective: Post-bariatric surgery patients require long-term, coordinated care to address complex nutritional, physiological, and behavioral challenges. Personalized smart nutrition, combining individualized dietary strategies with targeted monitoring, has emerged as a valuable direction for optimizing recovery and long-term outcomes. This article examines how traditional medical protocols can be enhanced by digital solutions in a multidisciplinary framework. Methods: The study analyzes current clinical practices, including personalized meal planning, physical rehabilitation, biochemical marker monitoring, and psychological counseling, as applied in post-bariatric care. These established approaches are then analyzed in relation to the NutriMonitCare system, a digital health system developed and tested in a laboratory environment. Used here as an illustrative example, the NutriMonitCare system demonstrates the potential of digital tools to support clinicians through real-time monitoring of dietary intake, activity levels, and physiological parameters. Results: Findings emphasize that medical protocols remain the cornerstone of post-surgical management, while digital tools may provide added value by enhancing data availability, supporting individualized decision making, and reinforcing patient adherence. Systems like the NutriMonitCare system could be integrated into interdisciplinary care models to refine nutrition-focused interventions and improve communication across care teams. However, their clinical utility remains theoretical at this stage and requires further validation. Conclusions: In conclusion, the integration of digital health tools with conventional post-operative care has the potential to advance personalized smart nutrition. Future research should focus on clinical evaluation, real-world testing, and ethical implementation of such technologies into established medical workflows to ensure both efficacy and patient safety. Full article
(This article belongs to the Section Nutrition and Public Health)
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62 pages, 4641 KiB  
Review
Pharmacist-Driven Chondroprotection in Osteoarthritis: A Multifaceted Approach Using Patient Education, Information Visualization, and Lifestyle Integration
by Eloy del Río
Pharmacy 2025, 13(4), 106; https://doi.org/10.3390/pharmacy13040106 - 1 Aug 2025
Viewed by 175
Abstract
Osteoarthritis (OA) remains a major contributor to pain and disability; however, the current management is largely reactive, focusing on symptoms rather than preventing irreversible cartilage loss. This review first examines the mechanistic foundations for pharmacological chondroprotection—illustrating how conventional agents, such as glucosamine sulfate [...] Read more.
Osteoarthritis (OA) remains a major contributor to pain and disability; however, the current management is largely reactive, focusing on symptoms rather than preventing irreversible cartilage loss. This review first examines the mechanistic foundations for pharmacological chondroprotection—illustrating how conventional agents, such as glucosamine sulfate and chondroitin sulfate, can potentially restore extracellular matrix (ECM) components, may attenuate catabolic enzyme activity, and might enhance joint lubrication—and explores the delivery challenges posed by avascular cartilage and synovial diffusion barriers. Subsequently, a practical “What–How–When” framework is introduced to guide community pharmacists in risk screening, DMOAD selection, chronotherapeutic dosing, safety monitoring, and lifestyle integration, as exemplified by the CHONDROMOVING infographic brochure designed for diverse health literacy levels. Building on these strategies, the P4–4P Chondroprotection Framework is proposed, integrating predictive risk profiling (physicians), preventive pharmacokinetic and chronotherapy optimization (pharmacists), personalized biomechanical interventions (physiotherapists), and participatory self-management (patients) into a unified, feedback-driven OA care model. To translate this framework into routine practice, I recommend the development of DMOAD-specific clinical guidelines, incorporation of chondroprotective chronotherapy and interprofessional collaboration into health-professional curricula, and establishment of multidisciplinary OA management pathways—supported by appropriate reimbursement structures, to support preventive, team-based management, and prioritization of large-scale randomized trials and real-world evidence studies to validate the long-term structural, functional, and quality of life benefits of synchronized DMOAD and exercise-timed interventions. This comprehensive, precision-driven paradigm aims to shift OA care from reactive palliation to true disease modification, preserving cartilage integrity and improving the quality of life for millions worldwide. Full article
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24 pages, 3243 KiB  
Article
Design of Experiments Leads to Scalable Analgesic Near-Infrared Fluorescent Coconut Nanoemulsions
by Amit Chandra Das, Gayathri Aparnasai Reddy, Shekh Md. Newaj, Smith Patel, Riddhi Vichare, Lu Liu and Jelena M. Janjic
Pharmaceutics 2025, 17(8), 1010; https://doi.org/10.3390/pharmaceutics17081010 - 1 Aug 2025
Viewed by 235
Abstract
Background: Pain is a complex phenomenon characterized by unpleasant experiences with profound heterogeneity influenced by biological, psychological, and social factors. According to the National Health Interview Survey, 50.2 million U.S. adults (20.5%) experience pain on most days, with the annual cost of prescription [...] Read more.
Background: Pain is a complex phenomenon characterized by unpleasant experiences with profound heterogeneity influenced by biological, psychological, and social factors. According to the National Health Interview Survey, 50.2 million U.S. adults (20.5%) experience pain on most days, with the annual cost of prescription medication for pain reaching approximately USD 17.8 billion. Theranostic pain nanomedicine therefore emerges as an attractive analgesic strategy with the potential for increased efficacy, reduced side-effects, and treatment personalization. Theranostic nanomedicine combines drug delivery and diagnostic features, allowing for real-time monitoring of analgesic efficacy in vivo using molecular imaging. However, clinical translation of these nanomedicines are challenging due to complex manufacturing methodologies, lack of standardized quality control, and potentially high costs. Quality by Design (QbD) can navigate these challenges and lead to the development of an optimal pain nanomedicine. Our lab previously reported a macrophage-targeted perfluorocarbon nanoemulsion (PFC NE) that demonstrated analgesic efficacy across multiple rodent pain models in both sexes. Here, we report PFC-free, biphasic nanoemulsions formulated with a biocompatible and non-immunogenic plant-based coconut oil loaded with a COX-2 inhibitor and a clinical-grade, indocyanine green (ICG) near-infrared fluorescent (NIRF) dye for parenteral theranostic analgesic nanomedicine. Methods: Critical process parameters and material attributes were identified through the FMECA (Failure, Modes, Effects, and Criticality Analysis) method and optimized using a 3 × 2 full-factorial design of experiments. We investigated the impact of the oil-to-surfactant ratio (w/w) with three different surfactant systems on the colloidal properties of NE. Small-scale (100 mL) batches were manufactured using sonication and microfluidization, and the final formulation was scaled up to 500 mL with microfluidization. The colloidal stability of NE was assessed using dynamic light scattering (DLS) and drug quantification was conducted through reverse-phase HPLC. An in vitro drug release study was conducted using the dialysis bag method, accompanied by HPLC quantification. The formulation was further evaluated for cell viability, cellular uptake, and COX-2 inhibition in the RAW 264.7 macrophage cell line. Results: Nanoemulsion droplet size increased with a higher oil-to-surfactant ratio (w/w) but was no significant impact by the type of surfactant system used. Thermal cycling and serum stability studies confirmed NE colloidal stability upon exposure to high and low temperatures and biological fluids. We also demonstrated the necessity of a solubilizer for long-term fluorescence stability of ICG. The nanoemulsion showed no cellular toxicity and effectively inhibited PGE2 in activated macrophages. Conclusions: To our knowledge, this is the first instance of a celecoxib-loaded theranostic platform developed using a plant-derived hydrocarbon oil, applying the QbD approach that demonstrated COX-2 inhibition. Full article
(This article belongs to the Special Issue Quality by Design in Pharmaceutical Manufacturing)
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