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Search Results (13,827)

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15 pages, 1476 KiB  
Systematic Review
Intramedullary Nailing vs. Plate Fixation for Trochanteric Femoral Fractures: A Systematic Review and Meta-Analysis of Randomized Trials
by Ümit Mert, Maher Ghandour, Moh’d Yazan Khasawneh, Filip Milicevic, Ahmad Al Zuabi, Klemens Horst, Frank Hildebrand, Bertil Bouillon, Mohamad Agha Mahmoud and Koroush Kabir
J. Clin. Med. 2025, 14(15), 5492; https://doi.org/10.3390/jcm14155492 (registering DOI) - 4 Aug 2025
Abstract
Background/Objectives: Trochanteric femoral fractures pose significant surgical challenges, particularly in elderly patients. Intramedullary nailing (IMN) and plate fixation (PF) are the primary operative strategies, yet their comparative efficacy and safety remain debated. This meta-analysis synthesizes randomized controlled trials (RCTs) to evaluate clinical, [...] Read more.
Background/Objectives: Trochanteric femoral fractures pose significant surgical challenges, particularly in elderly patients. Intramedullary nailing (IMN) and plate fixation (PF) are the primary operative strategies, yet their comparative efficacy and safety remain debated. This meta-analysis synthesizes randomized controlled trials (RCTs) to evaluate clinical, functional, perioperative, and biomechanical outcomes of IMN versus PF specifically in trochanteric fractures. Methods: A systematic search of six databases was conducted up to 20 May 2024, to identify RCTs comparing IMN and PF in adult patients with trochanteric femoral fractures. Data extraction followed PRISMA guidelines, and outcomes were pooled using random-effects models. Subgroup analyses examined the influence of fracture stability, implant type, and patient age. Risk of bias was assessed using the Cochrane RoB 2.0 tool. Results: Fourteen RCTs (n = 4603 patients) were included. No significant differences were found in reoperation rates, union time, implant cut-out, or mortality. IMN was associated with significantly reduced operative time (MD = −5.18 min), fluoroscopy time (MD = −32.92 s), and perioperative blood loss (MD = −111.68 mL). It also had a lower risk of deep infection. Functional outcomes and anatomical results were comparable. Subgroup analyses revealed fracture stability and nail type significantly modified operative time, and compression screws were associated with higher reoperation rates than IMN. Conclusions: For trochanteric femoral fractures, IMN and PF yield comparable results for most clinical outcomes, with IMN offering some advantages in surgical efficiency and perioperative morbidity, though functional outcomes were comparable. Implant selection and fracture stability influence outcomes, supporting individualized surgical decision making. Full article
(This article belongs to the Section Orthopedics)
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20 pages, 1801 KiB  
Article
Territorially Stratified Modeling for Sustainable Management of Free-Roaming Cat Populations in Spain: A National Approach to Urban and Rural Environmental Planning
by Octavio P. Luzardo, Ruth Manzanares-Fernández, José Ramón Becerra-Carollo and María del Mar Travieso-Aja
Animals 2025, 15(15), 2278; https://doi.org/10.3390/ani15152278 (registering DOI) - 4 Aug 2025
Abstract
This study presents the scientific and methodological foundation of Spain’s first national framework for the ethical management of community cat populations: the Action Plan for the Management of Community Cat Colonies (PACF), launched in 2025 under the mandate of Law 7/2023. This pioneering [...] Read more.
This study presents the scientific and methodological foundation of Spain’s first national framework for the ethical management of community cat populations: the Action Plan for the Management of Community Cat Colonies (PACF), launched in 2025 under the mandate of Law 7/2023. This pioneering legislation introduces a standardized, nationwide obligation for trap–neuter–return (TNR)-based management of free-roaming cats, defined as animals living freely, territorially attached, and with limited socialization toward humans. The PACF aims to support municipalities in implementing this mandate through evidence-based strategies that integrate animal welfare, biodiversity protection, and public health objectives. Using standardized data submitted by 1128 municipalities (13.9% of Spain’s total), we estimated a baseline population of 1.81 million community cats distributed across 125,000 colonies. These data were stratified by municipal population size and applied to national census figures to generate a model-ready demographic structure. We then implemented a stochastic simulation using Vortex software to project long-term population dynamics over a 25-year horizon. The model integrated eight demographic–environmental scenarios defined by a combination of urban–rural classification and ecological reproductive potential based on photoperiod and winter temperature. Parameters included reproductive output, mortality, sterilization coverage, abandonment and adoption rates, stochastic catastrophic events, and territorial carrying capacity. Under current sterilization rates (~20%), our projections indicate that Spain’s community cat population could surpass 5 million individuals by 2050, saturating ecological and social thresholds within a decade. In contrast, a differentiated sterilization strategy aligned with territorial reproductive intensity (50% in most areas, 60–70% in high-pressure zones) achieves population stabilization by 2030 at approximately 1.5 million cats, followed by a gradual long-term decline. This scenario prioritizes feasibility while substantially reducing reproductive output, particularly in rural and high-intensity contexts. The PACF combines stratified demographic modeling with spatial sensitivity, offering a flexible framework adaptable to local conditions. It incorporates One Health principles and introduces tools for adaptive management, including digital monitoring platforms and standardized welfare protocols. While ecological impacts were not directly assessed, the proposed demographic stabilization is designed to mitigate population-driven risks to biodiversity and public health without relying on lethal control. By integrating legal mandates, stratified modeling, and realistic intervention goals, this study outlines a replicable and scalable framework for coordinated action across administrative levels. It exemplifies how national policy can be operationalized through data-driven, territorially sensitive planning tools. The findings support the strategic deployment of TNR-based programs across diverse municipal contexts, providing a model for other countries seeking to align animal welfare policy with ecological planning under a multi-level governance perspective. Full article
(This article belongs to the Section Animal System and Management)
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22 pages, 1674 KiB  
Article
Air-STORM: Informed Decision Making to Improve the Success of Solar-Powered Air Quality Samplers in Challenging Environments
by Kyan Kuo Shlipak, Julian Probsdorfer and Christian L’Orange
Sensors 2025, 25(15), 4798; https://doi.org/10.3390/s25154798 (registering DOI) - 4 Aug 2025
Abstract
Outdoor air pollution poses a major global health risk, yet monitoring remains insufficient, especially in regions with limited infrastructure. Solar-powered monitors could allow for increased coverage in regions lacking robust connectivity. However, reliable sample collection can be challenging with these systems due to [...] Read more.
Outdoor air pollution poses a major global health risk, yet monitoring remains insufficient, especially in regions with limited infrastructure. Solar-powered monitors could allow for increased coverage in regions lacking robust connectivity. However, reliable sample collection can be challenging with these systems due to extreme temperatures and insufficient solar energy. Proper planning can help overcome these challenges. Air Sampler Solar and Thermal Optimization for Reliable Monitoring (Air-STORM) is an open-source tool that uses meteorological and solar radiation data to identify temperature and solar charging risks for air pollution monitors based on the target deployment area. The model was validated experimentally, and its utility was demonstrated through illustrative case studies. Air-STORM simulations can be customized for specific locations, seasons, and monitor configurations. This capability enables the early detection of potential sampling risks and provides opportunities to optimize monitor design, proactively mitigate temperature and power failures, and increase the likelihood of successful sample collection. Ultimately, improving sampling success will help increase the availability of high-quality outdoor air pollution data necessary to reduce global air pollution exposure. Full article
(This article belongs to the Special Issue Recent Trends in Air Quality Sensing)
14 pages, 278 KiB  
Review
Novel Biomarkers for Rejection in Kidney Transplantation: A Comprehensive Review
by Michael Strader and Sam Kant
J. Clin. Med. 2025, 14(15), 5489; https://doi.org/10.3390/jcm14155489 (registering DOI) - 4 Aug 2025
Abstract
Kidney transplantation is the treatment of choice for patients with end-stage kidney disease. Despite significant advances in graft survival, rejection continues to pose a major clinical challenge. Conventional monitoring tools, such as serum creatinine, donor-specific antibodies, and proteinuria, lack sensitivity and specificity for [...] Read more.
Kidney transplantation is the treatment of choice for patients with end-stage kidney disease. Despite significant advances in graft survival, rejection continues to pose a major clinical challenge. Conventional monitoring tools, such as serum creatinine, donor-specific antibodies, and proteinuria, lack sensitivity and specificity for early detection of graft injury. Moreover, while biopsy remains the current gold standard for diagnosing rejection, it is prone to confounders, invasive, and associated with procedural risks. However, non-invasive novel biomarkers have emerged as promising alternatives for earlier rejection detection and improved immunosuppression management. This review focuses on the leading candidate biomarkers currently under clinical investigation, with an emphasis on their diagnostic performance, prognostic value, and potential to support personalised immunosuppressive strategies in kidney transplantation. Full article
(This article belongs to the Special Issue Clinical Advancements in Kidney Transplantation)
21 pages, 733 KiB  
Systematic Review
The Effectiveness of Virtual Reality in Improving Balance and Gait in People with Parkinson’s Disease: A Systematic Review
by Sofia Fernandes, Bruna Oliveira, Sofia Sacadura, Cristina Rakasi, Isabel Furtado, João Paulo Figueiredo, Rui Soles Gonçalves and Anabela Correia Martins
Sensors 2025, 25(15), 4795; https://doi.org/10.3390/s25154795 (registering DOI) - 4 Aug 2025
Abstract
Background: Virtual reality (VR), often used with motion sensors, provides interactive tools for physiotherapy aimed at enhancing motor functions. This systematic review examined the effects of VR-based interventions, alone or combined with conventional physiotherapy (PT), on balance and gait in individuals with Parkinson’s [...] Read more.
Background: Virtual reality (VR), often used with motion sensors, provides interactive tools for physiotherapy aimed at enhancing motor functions. This systematic review examined the effects of VR-based interventions, alone or combined with conventional physiotherapy (PT), on balance and gait in individuals with Parkinson’s disease (PD). Methods: Following PRISMA guidelines, eight randomized controlled trials (RCTs) published between January 2019 and April 2025 were included. Interventions lasted between 5 and 12 weeks and were grouped as VR alone or VR combined with PT. Methodological quality was assessed using the PEDro Scale. Results: Of the 31 comparisons for balance and gait, 30 were favored by the experimental group, with 12 reaching statistical significance. Secondary outcomes (function, cognition, and quality of life) showed mixed results, with 6 comparisons favoring the experimental group (3 statistically significant) and 4 favoring the control group (1 statistically significant). Overall, the studies showed fair to good quality and a moderate risk of bias. Conclusions: VR-based interventions, particularly when combined with PT, show promise for improving balance and gait in PD. However, the evidence is limited by the small number of studies, heterogeneity of protocols, and methodological constraints. More rigorous, long-term trials are needed to clarify their therapeutic potential. Full article
20 pages, 949 KiB  
Review
Behavioural Cardiology: A Review on an Expanding Field of Cardiology—Holistic Approach
by Christos Fragoulis, Maria-Kalliopi Spanorriga, Irini Bega, Andreas Prentakis, Evangelia Kontogianni, Panagiotis-Anastasios Tsioufis, Myrto Palkopoulou, John Ntalakouras, Panagiotis Iliakis, Ioannis Leontsinis, Kyriakos Dimitriadis, Dimitris Polyzos, Christina Chrysochoou, Antonios Politis and Konstantinos Tsioufis
J. Pers. Med. 2025, 15(8), 355; https://doi.org/10.3390/jpm15080355 (registering DOI) - 4 Aug 2025
Abstract
Cardiovascular disease (CVD) remains Europe’s leading cause of mortality, responsible for >45% of deaths. Beyond established risk factors (hypertension, diabetes, dyslipidaemia, smoking, obesity), psychosocial elements—depression, anxiety, financial stress, personality traits, and trauma—significantly influence CVD development and progression. Behavioural Cardiology addresses this connection by [...] Read more.
Cardiovascular disease (CVD) remains Europe’s leading cause of mortality, responsible for >45% of deaths. Beyond established risk factors (hypertension, diabetes, dyslipidaemia, smoking, obesity), psychosocial elements—depression, anxiety, financial stress, personality traits, and trauma—significantly influence CVD development and progression. Behavioural Cardiology addresses this connection by systematically incorporating psychosocial factors into prevention and rehabilitation protocols. This review examines the HEARTBEAT model, developed by Greece’s first Behavioural Cardiology Unit, which aligns with current European guidelines. The model serves dual purposes: primary prevention (targeting at-risk individuals) and secondary prevention (treating established CVD patients). It is a personalised medicine approach that integrates psychosocial profiling with traditional risk assessment, utilising tailored evaluation tools, caregiver input, and multidisciplinary collaboration to address personality traits, emotional states, socioeconomic circumstances, and cultural contexts. The model emphasises three critical implementation aspects: (1) digital health integration, (2) cost-effectiveness analysis, and (3) healthcare system adaptability. Compared to international approaches, it highlights research gaps in psychosocial interventions and advocates for culturally sensitive adaptations, particularly in resource-limited settings. Special consideration is given to older populations requiring tailored care strategies. Ultimately, Behavioural Cardiology represents a transformative systems-based approach bridging psychology, lifestyle medicine, and cardiovascular treatment. This integration may prove pivotal for optimising chronic disease management through personalised interventions that address both biological and psychosocial determinants of cardiovascular health. Full article
(This article belongs to the Special Issue Personalized Diagnostics and Therapy for Cardiovascular Diseases)
28 pages, 15650 KiB  
Article
Unifying Flood‑Risk Communication: Empowering Community Leaders Through AI‑Enhanced, Contextualized Storytelling
by Michal Zajac, Connor Kulawiak, Shenglin Li, Caleb Erickson, Nathan Hubbell and Jiaqi Gong
Hydrology 2025, 12(8), 204; https://doi.org/10.3390/hydrology12080204 - 4 Aug 2025
Abstract
Floods pose a growing threat globally, causing tragic loss of life, billions in economic damage annually, and disproportionately affecting socio-economically vulnerable populations. This paper aims to improve flood-risk communication for community leaders by exploring the application of artificial intelligence. We categorize U.S. flood [...] Read more.
Floods pose a growing threat globally, causing tragic loss of life, billions in economic damage annually, and disproportionately affecting socio-economically vulnerable populations. This paper aims to improve flood-risk communication for community leaders by exploring the application of artificial intelligence. We categorize U.S. flood information sources, review communication modalities and channels, synthesize the literature on community leaders’ roles in risk communication, and analyze existing technological tools. Our analysis reveals three key challenges: the fragmentation of flood information, information overload that impedes decision-making, and the absence of a unified communication platform to address these issues. We find that AI techniques can organize data and significantly enhance communication effectiveness, particularly when delivered through infographics and social media channels. Based on these findings, we propose FLAI (Flood Language AI), an AI-driven flood communication platform that unifies fragmented flood data sources. FLAI employs knowledge graphs to structure fragmented data sources and utilizes a retrieval-augmented generation (RAG) framework to enable large language models (LLMs) to produce contextualized narratives, including infographics, maps, and cost–benefit analyses. Beyond flood management, FLAI’s framework demonstrates how AI can transform public service data management and institutional AI readiness. By centralizing and organizing information, FLAI can significantly reduce the cognitive burden on community leaders, helping them communicate timely, actionable insights to save lives and build flood resilience. Full article
13 pages, 1191 KiB  
Article
Linking Heart Function to Prognosis: The Role of a Novel Echocardiographic Index and NT-proBNP in Acute Heart Failure
by Dan-Cristian Popescu, Mara Ciobanu, Diana Țînț and Alexandru-Cristian Nechita
Medicina 2025, 61(8), 1412; https://doi.org/10.3390/medicina61081412 - 4 Aug 2025
Abstract
Background and Objectives: Risk stratification in acute heart failure (AHF) remains challenging, particularly in settings where biomarker availability is limited. Echocardiography offers valuable hemodynamic insights, but no single parameter fully captures the complexity of biventricular dysfunction and pressure overload. This study aimed to [...] Read more.
Background and Objectives: Risk stratification in acute heart failure (AHF) remains challenging, particularly in settings where biomarker availability is limited. Echocardiography offers valuable hemodynamic insights, but no single parameter fully captures the complexity of biventricular dysfunction and pressure overload. This study aimed to evaluate a novel echocardiographic index (ViRTUE IndexVTI-RVRA-TAPSE Unified Evaluation) integrating a peak systolic gradient between the right ventricle and right atrium (RV-RA gradient), tricuspid annular plane systolic excursion (TAPSE), the velocity–time integral in the left ventricular outflow tract (VTI LVOT), NT-proBNP (N-terminal pro–B-type Natriuretic Peptide) levels, and in-hospital mortality among patients with AHF. Materials and Methods: We retrospectively analyzed 123 patients admitted with AHF. Echocardiographic evaluation at admission included TAPSE, VTI LVOT, and the RV-RA gradient. An index was calculated as RVRA gradient TAPSE x VTI LVOT. NT-proBNP levels and in-hospital outcomes were recorded. Statistical analysis included correlation, logistic regression, and ROC curve evaluation. Results: The proposed index showed a significant positive correlation with NT-proBNP values (r = 0.543, p < 0.0001) and good discriminative ability for elevated NT-proBNP (AUC = 0.79). It also correlated with in-hospital mortality (r = 0.193, p = 0.032) and showed moderate prognostic performance (AUC = 0.68). Higher index values were associated with greater mortality risk. Conclusions: This novel index, based on standard echocardiographic measurements, reflects both systolic dysfunction and pressure overload in AHF. Its correlation with NT-proBNP and in-hospital mortality highlights its potential as a practical, accessible bedside tool for early risk stratification, particularly when biomarker testing is unavailable or delayed. Full article
(This article belongs to the Special Issue Updates on Prevention of Acute Heart Failure)
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86 pages, 96041 KiB  
Article
Sustainable Risk Mapping of High-Speed Rail Networks Through PS-InSAR and Geospatial Analysis
by Seung-Jun Lee, Hong-Sik Yun and Sang-Woo Kwak
Sustainability 2025, 17(15), 7064; https://doi.org/10.3390/su17157064 (registering DOI) - 4 Aug 2025
Abstract
This study presents an integrated geospatial framework for assessing the risk to high-speed railway (HSR) infrastructure, combining a persistent scatterer interferometric synthetic aperture radar (PS-InSAR) analysis with multi-criteria decision-making in a geographic information system (GIS) environment. Focusing on the Honam HSR corridor in [...] Read more.
This study presents an integrated geospatial framework for assessing the risk to high-speed railway (HSR) infrastructure, combining a persistent scatterer interferometric synthetic aperture radar (PS-InSAR) analysis with multi-criteria decision-making in a geographic information system (GIS) environment. Focusing on the Honam HSR corridor in South Korea, the model incorporates both maximum ground deformation and subsidence velocity to construct a dynamic hazard index. Social vulnerability is quantified using five demographic and infrastructural indicators, and a two-stage analytic hierarchy process (AHP) is applied with dependency correction to mitigate inter-variable redundancy. The resulting high-resolution risk maps highlight spatial mismatches between geotechnical hazards and social exposure, revealing vulnerable segments in Gongju and Iksan that require prioritized maintenance and mitigation. The framework also addresses data limitations by interpolating groundwater levels and estimating train speed using spatial techniques. Designed to be scalable and transferable, this methodology offers a practical decision-support tool for infrastructure managers and policymakers aiming to enhance the resilience of linear transport systems. Full article
(This article belongs to the Section Hazards and Sustainability)
26 pages, 20835 KiB  
Article
Reverse Mortgages and Pension Sustainability: An Agent-Based and Actuarial Approach
by Francesco Rania
Risks 2025, 13(8), 147; https://doi.org/10.3390/risks13080147 - 4 Aug 2025
Abstract
Population aging poses significant challenges to the sustainability of pension systems. This study presents an integrated methodological approach that uniquely combines actuarial life-cycle modeling with agent-based simulation to assess the potential of Reverse Mortgage Loans (RMLs) as a dual lever for enhancing retiree [...] Read more.
Population aging poses significant challenges to the sustainability of pension systems. This study presents an integrated methodological approach that uniquely combines actuarial life-cycle modeling with agent-based simulation to assess the potential of Reverse Mortgage Loans (RMLs) as a dual lever for enhancing retiree welfare and supporting pension system resilience under demographic and financial uncertainty. We explore Reverse Mortgage Loans (RMLs) as a potential financial instrument to support retirees while alleviating pressure on public pensions. Unlike prior research that treats individual decisions or policy outcomes in isolation, our hybrid model explicitly captures feedback loops between household-level behavior and system-wide financial stability. To test our hypothesis that RMLs can improve individual consumption outcomes and bolster systemic solvency, we develop a hybrid model combining actuarial techniques and agent-based simulations, incorporating stochastic housing prices, longevity risk, regulatory capital requirements, and demographic shifts. This dual-framework enables a structured investigation of how micro-level financial decisions propagate through market dynamics, influencing solvency, pricing, and adoption trends. Our central hypothesis is that reverse mortgages, when actuarially calibrated and macroprudentially regulated, enhance individual financial well-being while preserving long-run solvency at the system level. Simulation results indicate that RMLs can improve consumption smoothing, raise expected utility for retirees, and contribute to long-term fiscal sustainability. Moreover, we introduce a dynamic regulatory mechanism that adjusts capital buffers based on evolving market and demographic conditions, enhancing system resilience. Our simulation design supports multi-scenario testing of financial robustness and policy outcomes, providing a transparent tool for stress-testing RML adoption at scale. These findings suggest that, when well-regulated, RMLs can serve as a viable supplement to traditional retirement financing. Rather than offering prescriptive guidance, this framework provides insights to policymakers, financial institutions, and regulators seeking to integrate RMLs into broader pension strategies. Full article
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14 pages, 2532 KiB  
Article
Machine Learning for Spatiotemporal Prediction of River Siltation in Typical Reach in Jiangxi, China
by Yong Fu, Jin Luo, Die Zhang, Lingjia Liu, Gan Luo and Xiaofang Zu
Appl. Sci. 2025, 15(15), 8628; https://doi.org/10.3390/app15158628 (registering DOI) - 4 Aug 2025
Abstract
Accurate forecasting of river siltation is essential for ensuring inland waterway navigability and guiding sustainable sediment management. This study investigates the downstream reach of the Shihutang navigation power hub along the Ganjiang River in Jiangxi Province, China, an area characterized by pronounced seasonal [...] Read more.
Accurate forecasting of river siltation is essential for ensuring inland waterway navigability and guiding sustainable sediment management. This study investigates the downstream reach of the Shihutang navigation power hub along the Ganjiang River in Jiangxi Province, China, an area characterized by pronounced seasonal sedimentation and hydrological variability. To enable fine-scale prediction, we developed a data-driven framework using a random forest regression model that integrates high-resolution bathymetric surveys with hydrological and meteorological observations. Based on the field data from April to July 2024, the model was trained to forecast monthly siltation volumes at a 30 m grid scale over a six-month horizon (July–December 2024). The results revealed a marked increase in siltation from July to September, followed by a decline during the winter months. The accumulation of sediment, combined with falling water levels, was found to significantly reduce the channel depth and width, particularly in the upstream sections, posing a potential risk to navigation safety. This study presents an initial, yet promising attempt to apply machine learning for spatially explicit siltation prediction in data-constrained river systems. The proposed framework provides a practical tool for early warning, targeted dredging, and adaptive channel management. Full article
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14 pages, 1282 KiB  
Systematic Review
Actinic Cheilitis: A Systematic Review and Meta-Analysis of Interventions, Treatment Outcomes, and Adverse Events
by Matthäus Al-Fartwsi, Anne Petzold, Theresa Steeb, Lina Amin Djawher, Anja Wessely, Anett Leppert, Carola Berking and Markus V. Heppt
Biomedicines 2025, 13(8), 1896; https://doi.org/10.3390/biomedicines13081896 - 4 Aug 2025
Abstract
Introduction: Actinic cheilitis (AC) is a common precancerous condition affecting the lips, primarily caused by prolonged ultraviolet radiation exposure. Various treatment options are available. However, the optimal treatment approach remains a subject of debate. Objective: To summarize and compare practice-relevant interventions for AC. [...] Read more.
Introduction: Actinic cheilitis (AC) is a common precancerous condition affecting the lips, primarily caused by prolonged ultraviolet radiation exposure. Various treatment options are available. However, the optimal treatment approach remains a subject of debate. Objective: To summarize and compare practice-relevant interventions for AC. Materials and Methods: A pre-defined protocol was registered in PROSPERO (CRD42021225182). Systematic searches in Medline, Embase, and Central, along with manual trial register searches, identified studies reporting participant clearance rates (PCR) or recurrence rates (PRR). Quality assessment for randomized controlled trials (RCTs) was conducted using the Cochrane Risk of Bias tool 2. Uncontrolled studies were evaluated using the tool developed by the National Heart, Lung, and Blood Institute. The generalized linear mixed model was used to pool proportions for uncontrolled studies. A pairwise meta-analysis for RCTs was applied, using the odds ratio (OR) as the effect estimate and the GRADE approach to evaluate the quality of the evidence. Adverse events were analyzed qualitatively. Results: A comprehensive inclusion of 36 studies facilitated an evaluation of 614 participants for PCR, and 430 patients for PRR. Diclofenac showed the lowest PCR (0.53, 95% confidence interval (CI) [0.41; 0.66]), while CO2 laser showed the highest PCR (0.97, 95% CI [0.90; 0.99]). For PRR, Er:YAG laser showed the highest rates (0.14, 95% CI [0.08; 0.21]), and imiquimod the lowest (0.00, 95% CI [0.00; 0.06]). In a pairwise meta-analysis, the OR indicated a lower recurrence rate for Er:YAG ablative fractional laser (AFL)-primed methyl-aminolevulinate photodynamic therapy (MAL-PDT) (Er:YAG AFL-PDT) compared to methyl-aminolevulinate photodynamic therapy (MAL-PDT) alone (OR = 0.22, 95% CI [0.06; 0.82]). The CO2 laser showed fewer local side effects than the Er:YAG laser, while PDTs caused more skin reactions. Due to qualitative data, comparability was limited, highlighting the need for individualized treatment. Conclusions: This study provides a complete and up-to-date evidence synthesis of practice-relevant interventions for AC, identifying the CO2 laser as the most effective treatment and regarding PCR and imiquimod as most effective concerning PRR. Full article
(This article belongs to the Special Issue Skin Diseases and Cell Therapy)
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23 pages, 1799 KiB  
Systematic Review
Physical Training Protocols for Improving Dyspnea and Fatigue in Long COVID: A Systematic Review with Meta-Analysis
by Lisa Fernanda Mazzonetto, Jéssica Fernanda Correa Cordeiro, Igor Massari Correia, Alcivandro de Sousa Oliveira, Chimenny Moraes, Joana Brilhadori, Eurípedes Barsanulfo Gonçalves Gomide, Michal Kudlacek, Dalmo Roberto Lopes Machado, Jeferson Roberto Collevatti dos Anjos and André Pereira dos Santos
Healthcare 2025, 13(15), 1897; https://doi.org/10.3390/healthcare13151897 - 4 Aug 2025
Abstract
Objective: This study aimed to evaluate physical training protocols for alleviating long COVID symptoms, especially dyspnea and fatigue, through a systematic review with meta-analysis. Method: Data were collected from EMBASE, LILACS, PubMed, Scopus, CINAHL, Web of Science, and grey literature (Google Scholar, medRxiv). [...] Read more.
Objective: This study aimed to evaluate physical training protocols for alleviating long COVID symptoms, especially dyspnea and fatigue, through a systematic review with meta-analysis. Method: Data were collected from EMBASE, LILACS, PubMed, Scopus, CINAHL, Web of Science, and grey literature (Google Scholar, medRxiv). Studies evaluating dyspnea and/or fatigue before and after physical rehabilitation, using validated questionnaires, were included. Studies lacking pre- and post-assessments or physical training were excluded. Two reviewers independently extracted data on intervention type, duration, frequency, intensity, and assessment methods for dyspnea and fatigue. Bias risk was evaluated using the Cochrane tool. Results: Combined methods, such as respiratory muscle training with strength and aerobic exercise, were common for long COVID symptoms. Aerobic exercise notably improved dyspnea and/or fatigue. Among 25 studies, four had a low risk of bias. Meta-analysis of two studies found no significant reduction in fatigue. Conclusion: Combined training methods, particularly aerobic exercise, alleviate dyspnea and fatigue in long COVID. More high-quality studies are needed to confirm these findings. Full article
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56 pages, 1426 KiB  
Review
A Holistic Review of Cannabis and Its Potential Risks and Benefits in Mental Health
by Alejandro Borrego-Ruiz and Juan J. Borrego
Psychiatry Int. 2025, 6(3), 92; https://doi.org/10.3390/psychiatryint6030092 (registering DOI) - 4 Aug 2025
Abstract
Background: The dual nature of cannabis, as both a promising therapeutic tool and a widely used recreational substance with potential risks, raises important societal controversies, including its unclear impacts regarding mental health. This narrative review provides a comprehensive overview of cannabis, addressing (i) [...] Read more.
Background: The dual nature of cannabis, as both a promising therapeutic tool and a widely used recreational substance with potential risks, raises important societal controversies, including its unclear impacts regarding mental health. This narrative review provides a comprehensive overview of cannabis, addressing (i) its historical context; (ii) its chemical composition and pharmacokinetics; (iii) its pharmacological effects; (iv) its negative impacts on physiological and mental health; (v) its potential use as a drug for the treatment of neurological and psychiatric disorders; (vi) its relationship with the gut microbiome and how this interaction might influence mental functioning; (vii) the pathophysiology, prevalence, comorbidities, and treatment strategies of cannabis use disorder; and (viii) social perspectives on its legalization. Results: Cannabis presents a complex chemical profile and pharmacokinetics that show promise in treating numerous neurological, psychiatric, and psychological conditions. However, its use carries risks, which depend on factors such as compound concentration, dosage, consumption method, frequency of use, and individual vulnerability. Cannabis use disorder seems to be less severe than other substance use disorders, but it still constitutes a significant concern, as its manifestation is not uniform across all users. Conclusions: Cannabis demands a thorough understanding that goes beyond simplistic explanations and prejudices, standing as a plant of substantial clinical significance and highlighting the importance of personalized approaches to its use and increased awareness of how individuals respond to its effects. Full article
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22 pages, 5188 KiB  
Article
LCDAN: Label Confusion Domain Adversarial Network for Information Detection in Public Health Events
by Qiaolin Ye, Guoxuan Sun, Yanwen Chen and Xukan Xu
Electronics 2025, 14(15), 3102; https://doi.org/10.3390/electronics14153102 - 4 Aug 2025
Abstract
With the popularization of social media, information related to public health events has seen explosive growth online, making it essential to accurately identify informative tweets with decision-making and management value for public health emergency response and risk monitoring. However, existing methods often suffer [...] Read more.
With the popularization of social media, information related to public health events has seen explosive growth online, making it essential to accurately identify informative tweets with decision-making and management value for public health emergency response and risk monitoring. However, existing methods often suffer performance degradation during cross-event transfer due to differences in data distribution, and research specifically targeting public health events remains limited. To address this, we propose the Label Confusion Domain Adversarial Network (LCDAN), which innovatively integrates label confusion with domain adaptation to enhance the detection of informative tweets across different public health events. First, LCDAN employs an adversarial domain adaptation model to learn cross-domain feature representation. Second, it dynamically evaluates the importance of different source domain samples to the target domain through label confusion to optimize the migration effect. Experiments were conducted on datasets related to COVID-19, Ebola disease, and Middle East Respiratory Syndrome public health events. The results demonstrate that LCDAN significantly outperforms existing methods across all tasks. This research provides an effective tool for information detection during public health emergencies, with substantial theoretical and practical implications. Full article
(This article belongs to the Section Artificial Intelligence)
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