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25 pages, 4069 KiB  
Article
Forest Volume Estimation in Secondary Forests of the Southern Daxing’anling Mountains Using Multi-Source Remote Sensing and Machine Learning
by Penghao Ji, Wanlong Pang, Rong Su, Runhong Gao, Pengwu Zhao, Lidong Pang and Huaxia Yao
Forests 2025, 16(8), 1280; https://doi.org/10.3390/f16081280 - 5 Aug 2025
Abstract
Forest volume is an important information for assessing the economic value and carbon sequestration capacity of forest resources and serves as a key indicator for energy flow and biodiversity. Although remote sensing technology is applied to estimate volume, optical remote sensing data have [...] Read more.
Forest volume is an important information for assessing the economic value and carbon sequestration capacity of forest resources and serves as a key indicator for energy flow and biodiversity. Although remote sensing technology is applied to estimate volume, optical remote sensing data have limitations in capturing forest vertical height information and may suffer from reflectance saturation. While LiDAR data can provide more detailed vertical structural information, they come with high processing costs and limited observation range. Therefore, improving the accuracy of volume estimation through multi-source data fusion has become a crucial challenge and research focus in the field of forest remote sensing. In this study, we integrated Sentinel-2 multispectral data, Resource-3 stereoscopic imagery, UAV-based LiDAR data, and field survey data to quantitatively estimate the forest volume in Saihanwula Nature Reserve, located in Inner Mongolia, China, on the southern part of Daxing’anling Mountains. The study evaluated the performance of multi-source remote sensing features by using recursive feature elimination (RFE) to select the most relevant factors and applied four machine learning models—multiple linear regression (MLR), k-nearest neighbors (kNN), random forest (RF), and gradient boosting regression tree (GBRT)—to develop volume estimation models. The evaluation metrics include the coefficient of determination (R2), root mean square error (RMSE), and relative root mean square error (rRMSE). The results show that (1) forest Canopy Height Model (CHM) data were strongly correlated with forest volume, helping to alleviate the reflectance saturation issues inherent in spectral texture data. The fusion of CHM and spectral data resulted in an improved volume estimation model with R2 = 0.75 and RMSE = 8.16 m3/hm2, highlighting the importance of integrating multi-source canopy height information for more accurate volume estimation. (2) Volume estimation accuracy varied across different tree species. For Betula platyphylla, we obtained R2 = 0.71 and RMSE = 6.96 m3/hm2; for Quercus mongolica, R2 = 0.74 and RMSE = 6.90 m3/hm2; and for Populus davidiana, R2 = 0.51 and RMSE = 9.29 m3/hm2. The total forest volume in the Saihanwula Reserve ranges from 50 to 110 m3/hm2. (3) Among the four machine learning models, GBRT consistently outperformed others in all evaluation metrics, achieving the highest R2 of 0.86, lowest RMSE of 9.69 m3/hm2, and lowest rRMSE of 24.57%, suggesting its potential for forest biomass estimation. In conclusion, accurate estimation of forest volume is critical for evaluating forest management practices and timber resources. While this integrated approach shows promise, its operational application requires further external validation and uncertainty analysis to support policy-relevant decisions. The integration of multi-source remote sensing data provides valuable support for forest resource accounting, economic value assessment, and monitoring dynamic changes in forest ecosystems. Full article
(This article belongs to the Special Issue Mapping and Modeling Forests Using Geospatial Technologies)
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21 pages, 432 KiB  
Review
Interplay Between Depression and Inflammatory Bowel Disease: Shared Pathogenetic Mechanisms and Reciprocal Therapeutic Impacts—A Comprehensive Review
by Amalia Di Petrillo, Agnese Favale, Sara Onali, Amit Kumar, Giuseppe Abbracciavento and Massimo Claudio Fantini
J. Clin. Med. 2025, 14(15), 5522; https://doi.org/10.3390/jcm14155522 - 5 Aug 2025
Abstract
Inflammatory bowel disease (IBD) is characterized by chronic inflammation of the gastrointestinal tract. Although the aetiology of IBD remains largely unknown, several studies suggest that an individual’s genetic susceptibility, external environmental factors, intestinal microbial flora, and immune responses are all factors involved in [...] Read more.
Inflammatory bowel disease (IBD) is characterized by chronic inflammation of the gastrointestinal tract. Although the aetiology of IBD remains largely unknown, several studies suggest that an individual’s genetic susceptibility, external environmental factors, intestinal microbial flora, and immune responses are all factors involved in and functionally linked to the pathogenesis of IBD. Beyond the gastrointestinal manifestations, IBD patients frequently suffer from psychiatric comorbidities, particularly depression and anxiety. It remains unclear whether these disorders arise solely from reduced quality of life or whether they share overlapping biological mechanisms with IBD. This review aims to explore the bidirectional relationship between IBD and depressive disorders (DDs), with a focus on four key shared mechanisms: immune dysregulation, genetic susceptibility, alterations in gut microbiota composition, and dysfunction of the hypothalamic–pituitary–adrenal (HPA) axis. By examining recent literature, we highlight how these interconnected systems may contribute to both intestinal inflammation and mood disturbances. Furthermore, we discuss the reciprocal pharmacologic interactions between IBD and DDs: treatments for IBD, such as TNF-alpha and integrin inhibitors, have demonstrated effects on mood and anxiety symptoms, while certain antidepressants appear to exert independent anti-inflammatory properties, potentially reducing the risk or severity of IBD. Overall, this review underscores the need for a multidisciplinary approach to the care of IBD patients, integrating psychological and gastroenterological assessment. A better understanding of the shared pathophysiology may help refine therapeutic strategies and support the development of personalized, gut–brain-targeted interventions. Full article
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12 pages, 245 KiB  
Article
Examining the Relationship Between Increased Vegetable Consumption and Lifestyle Characteristics Among School-Aged Children: A Descriptive Study
by Konstantinos D. Tambalis, Dimitris Tampalis, Demosthenes B. Panagiotakos and Labros S. Sidossis
Appl. Sci. 2025, 15(15), 8665; https://doi.org/10.3390/app15158665 (registering DOI) - 5 Aug 2025
Abstract
The purpose of this study was to examine vegetable consumption and its relationship with lifestyle characteristics among children and adolescents. Data from a health survey administered to a representative sample of 177,091 schoolchildren between the ages of 8 and 17 were employed in [...] Read more.
The purpose of this study was to examine vegetable consumption and its relationship with lifestyle characteristics among children and adolescents. Data from a health survey administered to a representative sample of 177,091 schoolchildren between the ages of 8 and 17 were employed in this observational, cross-sectional investigation. Physical activity level, screen time, and sleeping patterns were assessed using self-completed questionnaires. Vegetable consumption and dietary habits were analyzed using the Mediterranean Diet Quality Index for Children and Adolescents. Participants consuming vegetables more than once daily were categorized as consumers vs. non-consumers. Physical education teachers measured anthropometric and physical fitness factors. Descriptive statistics and binary logistic regression analysis were conducted, and the odds ratio with the corresponding 95% confidence interval was calculated and adjusted for confounders. Vegetables were consumed once or more times a day by more females than males (25.5% vs. 24.0%, p < 0.001). In both sexes, vegetable consumers slept more, ate healthier, spent less time on screens, and had better anthropometric and aerobic fitness measurements than non-consumers. Healthy eating practices, such as regularly consuming fruits, legumes, nuts, and dairy products, were strongly correlated with vegetable intake. For every one-year increase in age, the odds of being a vegetable consumer decreased by 8% and 10% in boys and girls, respectively. Overweight/obese participants had lower odds of being a vegetable consumer by 20%. Increased screen time, inadequate physical activity, and insufficient sleeping hours decreased the odds of being a vegetable consumer by 22%, 30%, and 25%, respectively (all p-values < 0.001). Overall, a healthier lifestyle profile was associated with higher vegetable intake for both sexes among children and adolescents. Full article
(This article belongs to the Special Issue Potential Health Benefits of Fruits and Vegetables—4th Edition)
17 pages, 590 KiB  
Article
Regional Differences in Awareness of Oral Frailty and Associated Individual and Municipal Factors: A Cross-Sectional Study
by Nandin Uchral Altanbagana, Koichiro Irie, Wenqun Song, Shinya Fuchida, Jun Aida and Tatsuo Yamamoto
Healthcare 2025, 13(15), 1916; https://doi.org/10.3390/healthcare13151916 - 5 Aug 2025
Abstract
Background/Objectives: Despite growing interest in oral frailty as a public health issue, no nationwide study has assessed regional differences in oral frailty awareness, and the factors associated with such differences remain unclear. This study investigated regional differences in oral frailty awareness among [...] Read more.
Background/Objectives: Despite growing interest in oral frailty as a public health issue, no nationwide study has assessed regional differences in oral frailty awareness, and the factors associated with such differences remain unclear. This study investigated regional differences in oral frailty awareness among older adults in Japan and identified the associated individual- and municipal-level factors, focusing on local policy measures and community-based oral health programs. Methods: A cross-sectional analysis was conducted using data from the 2022 wave of the Japan Gerontological Evaluation Study. The analytical sample comprised 20,330 community-dwelling adults aged ≥65 years from 66 municipalities. Awareness of oral frailty was assessed via self-administered questionnaires. Individual- and municipal-level variables were analyzed using multilevel Poisson regression models to calculate prevalence ratios (PRs). Results: Awareness of oral frailty varied widely across municipalities, ranging from 15.3% to 47.1%. Multilevel analysis showed that being male (PR: 1.10), having ≤9 years (PR: 1.10) or 10 to 12 years of education (PR: 1.04), having oral frailty (PR: 1.04), and lacking civic participation (PR: 1.06) were significantly associated with lack of awareness. No significant associations were found with municipal-level variables such as dental health ordinances, volunteer training programs, or population density. Conclusions: The study found substantial regional variation in oral frailty awareness. However, this variation was explained primarily by individual-level characteristics. Public health strategies should focus on enhancing awareness among socially vulnerable groups—especially men, individuals with low educational attainment, and those not engaged in civic activities—through targeted interventions and community-based initiatives. Full article
(This article belongs to the Special Issue Oral Health and Rehabilitation in the Elderly Population)
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18 pages, 2150 KiB  
Article
Machine-Learning Insights from the Framingham Heart Study: Enhancing Cardiovascular Risk Prediction and Monitoring
by Emi Yuda, Itaru Kaneko and Daisuke Hirahara
Appl. Sci. 2025, 15(15), 8671; https://doi.org/10.3390/app15158671 (registering DOI) - 5 Aug 2025
Abstract
Monitoring cardiovascular health enables continuous and real-time risk assessment. This study utilized the Framingham Heart Study dataset to develop and evaluate machine-learning models for predicting mortality risk based on key cardiovascular parameters. Some machine-learning algorithms were applied to multiple machine-learning models. Among these, [...] Read more.
Monitoring cardiovascular health enables continuous and real-time risk assessment. This study utilized the Framingham Heart Study dataset to develop and evaluate machine-learning models for predicting mortality risk based on key cardiovascular parameters. Some machine-learning algorithms were applied to multiple machine-learning models. Among these, XGBoost achieved the highest predictive performance, each with an area under the curve (AUC) value of 0.83. Feature importance analysis revealed that coronary artery disease, glucose levels, and diastolic blood pressure (DIABP) were the most significant risk factors associated with mortality. The primary contribution of this research lies in its implications for public health and preventive medicine. By identifying key risk factors, it becomes possible to calculate individual and population-level risk scores and to design targeted early intervention strategies aimed at reducing cardiovascular-related mortality. Full article
(This article belongs to the Special Issue Smart Healthcare: Techniques, Applications and Prospects)
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12 pages, 884 KiB  
Article
Anatomical Risk Patterns for Patellofemoral Instability in Skeletally Immature Patients: A Sex-Stratified MRI Study
by René Schroedter, Amir Koutp, Bernhard Guggenberger, Martin Svehlik, Sebastian Tschauner and Tanja Kraus
J. Clin. Med. 2025, 14(15), 5519; https://doi.org/10.3390/jcm14155519 - 5 Aug 2025
Abstract
Background/Objectives: Lateral patellar dislocation (LPD) is a common pathology of the adolescent knee and a major predisposing factor for patellofemoral instability (PFI). The pathogenesis of PFI involves a combination of anatomical and biomechanical contributors, with increasing evidence pointing to sex-specific differences in knee [...] Read more.
Background/Objectives: Lateral patellar dislocation (LPD) is a common pathology of the adolescent knee and a major predisposing factor for patellofemoral instability (PFI). The pathogenesis of PFI involves a combination of anatomical and biomechanical contributors, with increasing evidence pointing to sex-specific differences in knee morphology. Despite this, the developmental course of these parameters and their variation between sexes remain insufficiently characterized. This study aims to investigate sex-related differences in patellofemoral joint geometry among skeletally immature patients with a history of PFI, focusing on how these anatomical variations evolve with increasing knee size, as represented by femoral condylar width. Methods: A total of 315 knee MRIs from patients under 18 years with documented PFI were retrospectively analyzed. Trochlear morphology, patellar tilt, axial positioning, and sagittal alignment were assessed using established MRI-based parameters. All measurements were normalized to bicondylar width to account for individual knee size. Sex-specific comparisons were performed using independent t-tests and linear regression analysis. Results: Females exhibited significantly smaller femoral widths, shallower trochlear depth (TD), shorter tibial tubercle–posterior cruciate ligament (TTPCL) distances, and lower patellar trochlear index (PTI) values compared to males (p < 0.05). In males, increasing femoral width was associated with progressive normalization of patellar tilt and sagittal alignment parameters. In contrast, these alignment parameters in females remained largely unchanged or worsened across different femoral sizes. Additionally, patellar inclination angle and PTI were significantly influenced by knee size in males (p < 0.05), whereas no such relationship was identified in females. Conclusions: Sex-specific morphological differences in patellofemoral geometry are evident early in development and evolve distinctly with growth. These differences may contribute to the higher prevalence of PFI in females and underscore the importance of considering sex and knee size in anatomical assessments. Full article
(This article belongs to the Special Issue Recent Research Progress in Pediatric Orthopedic Surgery)
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40 pages, 2757 KiB  
Article
Water User Associations in Drained and Irrigated Areas for More Sustainable Land and Water Management: Experiences from Poland and Ukraine
by Roman Kuryltsiv, Małgorzata Stańczuk-Gałwiaczek and Robert Łuczyński
Sustainability 2025, 17(15), 7100; https://doi.org/10.3390/su17157100 - 5 Aug 2025
Abstract
The level of participation and performance of water user associations (WUAs) in drained and irrigated areas is influenced by many factors. This paper aims to identify the main challenges to the functioning and performance of these associations in Poland and Ukraine using the [...] Read more.
The level of participation and performance of water user associations (WUAs) in drained and irrigated areas is influenced by many factors. This paper aims to identify the main challenges to the functioning and performance of these associations in Poland and Ukraine using the methodology of international comparative analysis. We examined legal, organizational, and financial framework of WUAs performance in Poland and Ukraine based on selected case study areas. The results of the study indicate that creation of WUAs in both countries can be assessed as beneficial for sustainable water development in general. However, it is found that the actions intended to bring benefits can actually exacerbate the problem of drought and water shortages. Research shows that the lack of complete documentation on the layout of the drainage networks plays a huge constraint factor that can lead to problems with controlling the reconstruction of drainage networks and significant deterioration of water relations. Another significant problem is the restriction of the scope of WUA activities in Poland to those types of actions subsidized by the state, while lacking financial resources for other necessary activities. Full article
(This article belongs to the Section Social Ecology and Sustainability)
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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35 pages, 3601 KiB  
Article
Carbon Emissions and Influencing Factors in the Areas Along the Belt and Road Initiative in Africa: A Spatial Spillover Perspective
by Suxin Yang and Miguel Ángel Benedicto Solsona
Sustainability 2025, 17(15), 7098; https://doi.org/10.3390/su17157098 - 5 Aug 2025
Abstract
The carbon dioxide spillover effects and influencing factors of the “Belt and Road Initiative” (BRI) in African countries must be assessed to evaluate the effectiveness, promote low-carbon transmissions in African countries, and provide recommendations for achieving the 2030 Sustainable Development Goals. This novel [...] Read more.
The carbon dioxide spillover effects and influencing factors of the “Belt and Road Initiative” (BRI) in African countries must be assessed to evaluate the effectiveness, promote low-carbon transmissions in African countries, and provide recommendations for achieving the 2030 Sustainable Development Goals. This novel study employs carbon dioxide emission intensity (CEI) and per capita carbon dioxide emissions (PCE) as dual indicators to evaluate the spatial spillover effects of 54 BRI African countries on their neighboring countries’ carbon emissions from 2007 to 2023. It identifies the key factors and mechanisms affecting these spillover effects using the spatial differences-in-differences (SDID) model. Results indicate that since the launch of the BRI, the CEI and PCE of BRI African countries have significantly increased, largely due to trade patterns and industrialization structures. Greater trade openness has further boosted local economic development, thereby increasing carbon dioxide’s spatial spillover. Government management and corruption control levels show some heterogeneity in the spillover effects, which may be attributed to long-standing issues of weak institutional enforcement in Africa. Overall, this study reveals the complex relationship between BRI African economic development and environmental outcomes, highlighting the importance of developing sustainable development strategies and establishing strong differentiated regulatory regimes to effectively address environmental challenges. Full article
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11 pages, 468 KiB  
Article
Association of Therapeutic Plasma Exchange-Treated Thrombotic Thrombocytopenic Purpura with Improved Mortality Outcome in End-Stage Renal Disease
by Brenna S. Kincaid, Kiana Kim, Jennifer L. Waller, Stephanie L. Baer, Wendy B. Bollag and Roni J. Bollag
Diseases 2025, 13(8), 247; https://doi.org/10.3390/diseases13080247 - 5 Aug 2025
Abstract
Background/Objectives: Thrombotic thrombocytopenic purpura (TTP) is a microangiopathic hemolytic anemia exhibiting 90% mortality without prompt treatment. The aim of this study was to investigate the association of therapeutic plasma exchange (TPE)-treated TTP in end-stage renal disease (ESRD) patients with mortality, demographics, and [...] Read more.
Background/Objectives: Thrombotic thrombocytopenic purpura (TTP) is a microangiopathic hemolytic anemia exhibiting 90% mortality without prompt treatment. The aim of this study was to investigate the association of therapeutic plasma exchange (TPE)-treated TTP in end-stage renal disease (ESRD) patients with mortality, demographics, and clinical comorbidities. We queried the United States Renal Data System for ESRD patients starting dialysis between 1 January 2005 and 31 December 2018, using International Classification of Diseases (ICD)-9 and ICD-10 codes for thrombotic microangiopathy, with a TPE procedure code entered within 7 days. Methods: Cox proportional hazards models were used to assess mortality, adjusting for demographic and clinical factors. Results: Among 1,155,136 patients, increased age [adjusted odds ratio (OR) = 0.96, 95% confidence interval (CI): 0.94–0.96]; black race (OR = 0.67, CI: 0.51–0.89); and Hispanic ethnicity (OR = 0.43, CI: 0.28–0.66) were associated with a lower risk of TPE-treated TTP diagnosis, whereas female sex (OR = 1.59, CI: 1.25–2.02) and tobacco use (OR = 2.08, CI: 1.58–2.75) had a higher risk. A claim for TPE-treated TTP carried a lower risk of death (adjusted hazard ratio = 0.024, CI: 0.021–0.028). Female sex, black race, Hispanic ethnicity, and hypothyroidism were also associated with decreased all-cause mortality. Conclusions: These findings suggest that ESRD patients with TPE-treated TTP are significantly protected from mortality compared with ESRD patients without this diagnosis. Full article
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17 pages, 545 KiB  
Article
Concordance Index-Based Comparison of Inflammatory and Classical Prognostic Markers in Untreated Hepatocellular Carcinoma
by Natalia Afonso-Luis, Inés Monescillo-Martín, Joaquín Marchena-Gómez, Pau Plá-Sánchez, Francisco Cruz-Benavides and Carmen Rosa Hernández-Socorro
J. Clin. Med. 2025, 14(15), 5514; https://doi.org/10.3390/jcm14155514 - 5 Aug 2025
Abstract
Background/Objectives: Inflammation-based markers have emerged as potential prognostic tools in hepatocellular carcinoma (HCC), but comparative data with classical prognostic factors in untreated HCC are limited. This study aimed to evaluate and compare the prognostic performance of inflammatory and conventional markers using Harrell’s [...] Read more.
Background/Objectives: Inflammation-based markers have emerged as potential prognostic tools in hepatocellular carcinoma (HCC), but comparative data with classical prognostic factors in untreated HCC are limited. This study aimed to evaluate and compare the prognostic performance of inflammatory and conventional markers using Harrell’s concordance index (C-index). Methods: This retrospective study included 250 patients with untreated HCC. Prognostic variables included age, BCLC stage, Child–Pugh classification, Milan criteria, MELD score, AFP, albumin, Charlson comorbidity index, and the inflammation-based markers neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), Systemic Inflammation Response Index (SIRI), and Systemic Immune-inflammation Index (SIII). Survival was analyzed using Cox regression. Predictive performance was assessed using the C-index, Akaike Information Criterion (AIC), and likelihood ratio tests. Results: Among the classical markers, BCLC showed the highest predictive performance (C-index: 0.717), while NLR ranked highest among the inflammatory markers (C-index: 0.640), above the MELD score and Milan criteria. In multivariate analysis, NLR ≥ 2.3 remained an independent predictor of overall survival (HR: 1.787; 95% CI: 1.264–2.527; p < 0.001), along with BCLC stage, albumin, Charlson index, and Milan criteria. Including NLR in the model modestly improved the C-index (from 0.781 to 0.794) but significantly improved model fit (Δ–2LL = 10.75; p = 0.001; lower AIC). Conclusions: NLR is an accessible, cost-effective, and independent prognostic marker for overall survival in untreated HCC. It shows discriminative power comparable to or greater than most conventional predictors and may complement classical stratification tools for HCC. Full article
(This article belongs to the Section General Surgery)
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18 pages, 616 KiB  
Article
Noninvasive Assessment of Arterial Wall and Soluble ST2 in Patients with Type 2 Diabetes and Coronary Artery Disease
by Edyta Radzik, Marcin Schulz, Brygida Przywara-Chowaniec and Andrzej Tomasik
Int. J. Mol. Sci. 2025, 26(15), 7561; https://doi.org/10.3390/ijms26157561 (registering DOI) - 5 Aug 2025
Abstract
Diabetes-related pathophysiological processes contribute to endothelial dysfunction, arterial stiffening (AS), hypertension, vascular remodeling, and impaired myocardial perfusion. This study aimed to assess the relationship between arterial wall parameters and sST2 concentration as potential risk factors in type 2 diabetes (T2DM) and investigate sex-related [...] Read more.
Diabetes-related pathophysiological processes contribute to endothelial dysfunction, arterial stiffening (AS), hypertension, vascular remodeling, and impaired myocardial perfusion. This study aimed to assess the relationship between arterial wall parameters and sST2 concentration as potential risk factors in type 2 diabetes (T2DM) and investigate sex-related differences. To achieve this, we enrolled 100 patients with suspected or exacerbated coronary artery disease (CAD) and divided them into a T2DM group (n = 58) and a control group (n = 42). Endothelial reactivity (lnRHI), ABI, sST2 levels, and carotid–femoral (cfPWV) and carotid–radial pulse wave velocity (crPWV) were assessed. Coronary angiography was performed in every patient, and epicardial flow and myocardial perfusion were evaluated using QuBE and FLASH. Our results showed that the coronary angiographic findings were similar in both groups. However, T2DM patients had a significantly higher central AS (cfPWV 10.8 ± 2 vs. 9.9 ± 2.7 m/s, p < 0.05) and vascular age (70.0 ± 12.3 vs. 61.3 ± 15.4 years, p < 0.05), while peripheral AS, RHI, and ABI showed no differences. CfPWV correlated with renal function; higher HbA1c and sST2 levels were additionally associated with advanced vascular age. Notably, central AS and vascular age were higher in men with T2DM but not in women. These findings indicate that T2DM patients exhibit increased central AS and vascular aging, influenced by sST2 levels, suggesting fibrosis as a target for precision medicine in T2DM. Full article
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22 pages, 7171 KiB  
Article
Distribution Characteristics, Mobility, and Influencing Factors of Heavy Metals at the Sediment–Water Interface in South Dongting Lake
by Xiaohong Fang, Xiangyu Han, Chuanyong Tang, Bo Peng, Qing Peng, Linjie Hu, Yuru Zhong and Shana Shi
Water 2025, 17(15), 2331; https://doi.org/10.3390/w17152331 - 5 Aug 2025
Abstract
South Dongting Lake is an essential aquatic ecosystem that receives substantial water inflows from the Xiangjiang and Zishui Rivers. However, it is significantly impacted by human activities, including mining, smelting, and farming. These activities have led to serious contamination of the lake’s sediments [...] Read more.
South Dongting Lake is an essential aquatic ecosystem that receives substantial water inflows from the Xiangjiang and Zishui Rivers. However, it is significantly impacted by human activities, including mining, smelting, and farming. These activities have led to serious contamination of the lake’s sediments with heavy metals (HMs). This study investigated the distribution, mobility, and influencing factors of HMs at the sediment–water interface. To this end, sediment samples were analyzed from three key regions (Xiangjiang River estuary, Zishui River estuary, and northeastern South Dongting Lake) using traditional sampling methods and Diffusive Gradients in Thin Films (DGT) technology. Analysis of fifteen HMs (Pb, Bi, Ni, As, Se, Cd, Sb, Mn, Zn, V, Cr, Cu, Tl, Co, and Fe) revealed significant spatial heterogeneity. The results showed that Cr, Cu, Pb, Bi, Ni, As, Se, Cd, Sb, Mn, Zn, and Fe exhibited high variability (CV > 0.20), whereas V, Tl, and Co demonstrated stable concentrations (CV < 0.20). Concentrations were found to exceed background values of the upper continental crust of eastern China (UCC), Yangtze River sediments (YZ), and Dongting Lake sediments (DT), particularly at the Xiangjiang estuary (XE) and in the northeastern regions. Speciation analysis revealed that V, Cr, Cu, Ni, and As were predominantly found in the residual fraction (F4), while Pb and Co were concentrated in the oxidizable fraction (F3), Mn and Zn appeared primarily in the exchangeable fractions (F1 and F2), and Cd was notably dominant in the exchangeable fraction (F1), suggesting a high potential for mobility. Additionally, DGT results confirmed a significant potential for the release of Pb, Zn, and Cd. Contamination assessment using the Pollution Load Index (PLI) and Geoaccumulation Index (Igeo) identified Pb, Bi, Ni, As, Se, Cd, and Sb as major pollutants. Among these, Bi and Cd were found to pose the highest risks. Furthermore, the Risk Assessment Code (RAC) and the Potential Ecological Risk Index (PERI) highlighted Cd as the primary ecological risk contributor, especially in the XE. The study identified sediment grain size, pH, electrical conductivity, and nutrient levels as the primary influencing factors. The PMF modeling revealed HM sources as mixed smelting/natural inputs, agricultural activities, natural weathering, and mining/smelting operations, suggesting that remediation should prioritize Cd control in the XE with emphasis on external inputs. Full article
(This article belongs to the Section Water Quality and Contamination)
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25 pages, 956 KiB  
Review
Sexual Health Education in Nursing: A Scoping Review Based on the Dialectical Structural Approach to Care in Spain
by Mónica Raquel Pereira-Afonso, Raquel Fernandez-Cézar, Victoria Lopezosa-Villajos, Miriam Hermida-Mota, Maria Angélica de Almeida Peres and Sagrario Gómez-Cantarino
Healthcare 2025, 13(15), 1911; https://doi.org/10.3390/healthcare13151911 - 5 Aug 2025
Abstract
Sexual health constitutes a fundamental aspect of overall well-being, with direct implications for individual development and the broader social and economic progress of communities. Promoting environments that ensure sexual experiences free from coercion, discrimination, and violence is a key public health priority. Sexuality, [...] Read more.
Sexual health constitutes a fundamental aspect of overall well-being, with direct implications for individual development and the broader social and economic progress of communities. Promoting environments that ensure sexual experiences free from coercion, discrimination, and violence is a key public health priority. Sexuality, in this regard, should be understood as an inherent dimension of human experience, shaped by biological, cultural, cognitive, and ideological factors. Accordingly, sexual health education requires a holistic and multidimensional approach that integrates sociocultural, biographical, and professional perspectives. This study aims to examine the level of knowledge and training in sexual health among nursing students and healthcare professionals, as well as to assess the extent to which sexual health content is incorporated into nursing curricula at Spanish universities. A scoping review was conducted using the Dialectical Structural Model of Care (DSMC) as the theoretical framework. The findings indicate a significant lack of knowledge regarding sexual health among both nursing students and healthcare professionals, largely due to educational and structural limitations. Furthermore, sexual health education remains underrepresented in nursing curricula and is frequently addressed from a narrow, fragmented biomedical perspective. These results highlight the urgent need for the comprehensive integration of sexual health content into nursing education. Strengthening curricular inclusion is essential to ensure the preparation of competent professionals capable of delivering holistic, inclusive, and empowering care in this critical area of health. Full article
(This article belongs to the Special Issue Advances in Sexual and Reproductive Health)
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35 pages, 4098 KiB  
Article
Prediction of Earthquake Death Toll Based on Principal Component Analysis, Improved Whale Optimization Algorithm, and Extreme Gradient Boosting
by Chenhui Wang, Xiaotao Zhang, Xiaoshan Wang and Guoping Chang
Appl. Sci. 2025, 15(15), 8660; https://doi.org/10.3390/app15158660 (registering DOI) - 5 Aug 2025
Abstract
Earthquakes, as one of the most destructive natural disasters, often cause significant casualties and severe economic losses. Accurate prediction of earthquake fatalities is of great importance for pre-disaster prevention and mitigation planning, as well as post-disaster emergency response deployment. To address the challenges [...] Read more.
Earthquakes, as one of the most destructive natural disasters, often cause significant casualties and severe economic losses. Accurate prediction of earthquake fatalities is of great importance for pre-disaster prevention and mitigation planning, as well as post-disaster emergency response deployment. To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). The method first employs PCA to reduce the dimensionality of the influencing factor data, eliminating redundant information and improving modeling efficiency. Subsequently, the IWOA is used to intelligently optimize key hyperparameters of the XGBoost model, enhancing the prediction accuracy and stability. Using 42 major earthquake events in China from 1970 to 2025 as a case study, covering regions including the west (e.g., Tonghai in Yunnan, Wenchuan, Jiuzhaigou), central (e.g., Lushan in Sichuan, Ya’an), east (e.g., Tangshan, Yingkou), north (e.g., Baotou in Inner Mongolia, Helinger), northwest (e.g., Jiashi in Xinjiang, Wushi, Yongdeng in Gansu), and southwest (e.g., Lancang in Yunnan, Lijiang, Ludian), the empirical results showed that the PCA-IWOA-XGBoost model achieved an average test set accuracy of 97.0%, a coefficient of determination (R2) of 0.996, a root mean square error (RMSE) and mean absolute error (MAE) reduced to 4.410 and 3.430, respectively, and a residual prediction deviation (RPD) of 21.090. These results significantly outperformed the baseline XGBoost, PCA-XGBoost, and IWOA-XGBoost models, providing improved technical support for earthquake disaster risk assessment and emergency response. Full article
(This article belongs to the Section Earth Sciences)
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