Saved Queries

The combined effects of soil properties, zinc (Zn), and chloride ion (Cl⁻) concentrations on Zn distribution across soil fractions are poorly understood, even though zinc chloride (ZnCl₂) contamination in industrial soils is a major source of mobile Zn and poses significant environmental risks. This study aimed to (1) assess how the soil type, physicochemical properties, and Zn concentration affect Zn distribution in Community Bureau of Reference (BCR)-extracted fractions; (2) evaluate the impact of Cl⁻ on Zn mobility; and (3) develop predictive models for mobile and stable Zn fractions based on soil characteristics. Zn mobility was analyzed in 18 soils differing in Zn and Cl⁻, pH, specific surface area (SSA), organic matter (OM), and texture (sand, silt, clay (CLY)), using a modified BCR method. Zn fractions were measured by atomic absorption spectroscopy (AAS). Analysis of Covariance was used to assess Zn distribution across soil types, while Zn fractions were modeled using non-linear regression (NLR). The results showed that mobile Zn increased with the total Zn, and that the soil type and Zn levels influenced Zn distribution in soils contaminated with ZnCl₂ (Zn 304–2136 mg·kg⁻¹ d.m.; Cl⁻ 567–2552 mg·kg⁻¹; pH 3.5–7.5; CLY 11–22%; SSA 96–196 m²·g⁻¹; OM 0–4.8%). Although Cl⁻ enhanced Zn mobility, its effect was weaker than that of Zn. Predictive models based on the total Zn, SSA, and CLY accurately estimated Zn in mobile and stable fractions (R > 0.92), whereas the effects of the pH and OM, although noticeable, were not statistically significant. Full article

(This article belongs to the Special Issue Sustainable and AI-Driven Approaches to Managing the Soil-Water Complex in Agriculture)

►▼ Show Figures

Figure 1

14 pages, 2849 KB

Open AccessArticle

Bacteroides fragilis and Microbacterium as Microbial Signatures in Hashimoto’s Thyroiditis

by Artur Kovenskiy, Nurlubek Katkenov, Aigul Ramazanova, Elizaveta Vinogradova, Zharkyn Jarmukhanov, Zhussipbek Mukhatayev and Almagul Kushugulova

Int. J. Mol. Sci. 2025, 26(17), 8724; https://doi.org/10.3390/ijms26178724 (registering DOI) - 7 Sep 2025

Abstract

Hashimoto’s thyroiditis (HT) and alopecia areata (AA) are organ-specific autoimmune diseases that frequently co-occur, suggesting shared immunological and microbial pathways. The gut microbiome has emerged as a key modulator of immune function, yet disease-specific microbial signatures remain poorly defined. Fecal samples from 51 participants (HT: n = 16, AA: n = 17, healthy controls: n = 18) aged 18–65 years were analyzed using shotgun metagenomic sequencing followed by multivariate statistical analyses. While alpha and beta diversity did not differ significantly across groups, taxonomic profiling revealed disease-specific microbial patterns. Bacteroides fragilis was significantly enriched in HT, suggesting a potential role in immune modulation; although mechanisms such as polysaccharide A production and molecular mimicry have been proposed in previous studies, their involvement in HT remains to be confirmed. Microbacterium sp. T32 was elevated in both HT and AA, indicating its potential as a shared autoimmune marker. Functional analysis showed increased fermentation and amino acid biosynthesis in AA, contrasting with reduced metabolic activity and elevated carbohydrate biosynthesis in HT. HT and AA exhibit distinct gut microbial and metabolic signatures. Bacteroides fragilis and Microbacterium sp. T32 may serve as potential microbial correlates for autoimmune activity, offering new insights into disease pathogenesis and targets for microbiome-based interventions. Full article

(This article belongs to the Section Molecular Microbiology)

►▼ Show Figures

Figure 1

31 pages, 515 KB

Open AccessArticle

Forecasting Water Consumption for Sustainable Development in Saudi Arabia: A Copula-Based Approach

by Amwaj Falah AL-Rashidi, Dalia Kamal Alnagar and Hussein Eledum

Water 2025, 17(17), 2645; https://doi.org/10.3390/w17172645 (registering DOI) - 7 Sep 2025

Abstract

Effective water resource planning is essential for Saudi Arabia, where limited freshwater availability is challenged by rapid population growth, economic development, and climate variability. This study introduces a copula-based modeling framework for forecasting water demand across the country’s urban, industrial, and agricultural sectors. Copulas, compared to traditional models, effectively capture nonlinear and asymmetric relationships among essential variables, including population, temperature, GDP, and sectoral water consumption. Multivariate copula models (Gaussian, Clayton, Gumbel, Frank, t-Copula, and Vine structures) were fitted and evaluated using historical data from 2008 to 2024, obtained from national authorities, including the Ministry of Environment, Water, and Agriculture, the General Authority for Statistics, and the National Center for Meteorology. The 4D normal copula was developed as the most efficient method across all sectors, with MAPE values of 6.37% for urban, 17.51% for industrial, and 23.20% for agricultural consumption. Scenario-based forecasts, which include baseline, high-growth, and sustainability-focused trajectories, indicate that the sustainability scenario yields the best results, resulting in significant demand reductions (21.7% urban, 20.4% industrial, and 8.2% agricultural) with minimal climate impact (+0.4 °C) and the lowest risk levels. The study demonstrates the successful decoupling of water demand from population and economic growth through proper policy interventions, with conditional risk analysis offering actionable early warning capabilities for proactive management. These findings provide a valuable foundation for enhancing national water strategy planning in Saudi Arabia under Vision 2030 and contribute to methodological improvements applicable to water-scarce regions internationally. Full article

(This article belongs to the Section Water Use and Scarcity)

►▼ Show Figures

Figure 1

15 pages, 1105 KB

Open AccessArticle

Candida albicans Associated with Periodontal Disease Exhibits Different Clusters of Adhesion Gene and Protease Expression

by Gloria Luz Paniagua-Contreras, Alan Cano-Kobayashi, Ana María Fernández-Presas, Miguel Ruíz-De la Cruz, Héctor Martínez-Gregorio, Felipe Vaca-Paniagua and Eric Monroy-Pérez

Int. J. Mol. Sci. 2025, 26(17), 8721; https://doi.org/10.3390/ijms26178721 (registering DOI) - 7 Sep 2025

Abstract

C. albicans has recently been described as a secondary colonizer associated with periodontal infections. This study aimed to determine the expression patterns of ALS and SAP family genes in C. albicans strains isolated from patients with periodontal disease (n = 268), and a control group of healthy individuals without any clinical signs of periodontal disease (n = 100) was included. C. albicans and the ALS and SAP genes were identified using polymerase chain reaction (PCR). An in vitro infection model was used with the strains using the human gingival fibroblast cell line. RNA was extracted using a QIAcube robotic workstation (Qiagen). A QuantiTect Reverse Transcription Kit (Qiagen) was used for first-strand cDNA synthesis. ALS and SAP gene expression in the strains was determined using real-time PCR. A total of 82.5% (n = 66) of the C. albicans strains were isolated from patients with moderate periodontitis, 10% (n = 8) from patients with chronic periodontitis, and 7.5% (n = 6) from patients with gingivitis. In the group of healthy individuals, C. albicans was identified in 9% (9/100). Overall, the most frequently expressed ALS genes in the strains from the three diagnoses were ALS1 (77/80), ALS3 (67/80), ALS4 (67/80), ALS6 (77/80), ALS7 (62/80), and ALS9 (73/80), while the most frequently expressed SAP genes were SAP1 (76/80), SAP6 (57/80), SAP9 (78/80), and SAP10 (77/80). The overall frequencies of expression of the ALS4, ALS9, SAP2, SAP3, SAP6, and SAP genes in the strains were statistically different across the three diagnoses. We identified different profiles of expression of the ALS and SAP genes in the strains of C. albicans that contribute directly to the degree of periodontal disease. Therefore, our findings may contribute to improving our knowledge of the molecular mechanisms of C. albicans in the pathogenesis of periodontal disease. Full article

(This article belongs to the Collection Microbial Virulence Factors)

►▼ Show Figures

Figure 1

24 pages, 1799 KB

Open AccessArticle

Lubricant Performance in Wind Turbines: A Data Study in Real-Use Conditions

by A. E. Jiménez, H. J. Barajas, M. D. Avilés, I. J. Martínez-Mateo and F. J. Carrión-Vilches

Lubricants 2025, 13(9), 397; https://doi.org/10.3390/lubricants13090397 (registering DOI) - 7 Sep 2025

Abstract

An extensive statistical study was conducted on a 10-year dataset (2014–2023) containing the lubrication condition monitoring results from wind turbine gearboxes in the Iberian Peninsula. The dataset includes two mineral and two synthetic lubricants; all four were sampled and analyzed regularly in accordance with the ISO 14830-1 standard. This dataset comprises over 25,000 records across 24 distinct parameters, as defined by the standard maintenance procedure of lubricants in wind turbine gearboxes. To reduce dimensionality, the analysis begins with principal component analysis, followed by discussion of Spearman correlations and finishing with comparation of trends. Performance differences, correlations and typical trends will be evaluated and compared for mineral and synthetic lubricants. This data-driven study presents a significant contribution to supporting maintenance decision-making processes in wind farms. Despite the differences, P, Pb and K have been identified as having a major influence on the variance in the dataset for all the lubricants, although no significant correlations with these elements have been found. Mineral lubricants showed very few correlations between elements and lubricant parameters, with Fe as the major element to be considered. Meanwhile, synthetic lubricants showed several correlations between elements (Fe, Mn, Cu, Ba) and lubricant parameters denoting complex tribochemical reactions. Full article

►▼ Show Figures

Figure 1

23 pages, 7451 KB

Open AccessArticle

Comparing Machine Learning and Statistical Models for Remote Sensing-Based Forest Aboveground Biomass Estimations

by Shashika Himandi Gardeye Lamahewage, Chandi Witharana, Rachel Riemann, Robert Fahey and Thomas Worthley

Forests 2025, 16(9), 1430; https://doi.org/10.3390/f16091430 (registering DOI) - 7 Sep 2025

Abstract

Understanding the distribution of forest aboveground biomass (AGB) is pivotal for carbon monitoring. Field-based inventorying is time-consuming and costly for large-area AGB estimations. The integration of multimodal remote sensing (RS) observations with single-year, field-based forest inventory analysis (FIA) data has the potential to improve the efficiency of large-scale AGB modeling and carbon monitoring initiatives. Our main objective was to systematically compare the AGB prediction accuracies of machine learning algorithms (e.g., random forest (RF) and support vector machine (SVM)) with those of conventional statistical methods (e.g., multiple linear regression (MLR)) using multimodal RS variables as predictors. We implemented a method combining AGB estimates of actual FIA subplot locations with airborne LiDAR, National Agriculture Imagery Program (NAIP) aerial imagery, and Sentinel-2 satellite images for model training, validation, and testing. The hyperparameter-tuned RF model produced a root mean square error (RMSE) of 27.19 Mgha⁻¹ and an R² of 0.41, which outperformed the evaluation metrics of SVM and MLR models. Among the 28 most important explanatory variables used to build the best RF model, 68% of variables were derived from the LiDAR height data. The hyperparameter-tuned linear SVM model exhibited an R² of 0.10 and an RMSE of 32.17 Mgha⁻¹. Additionally, we developed an MLR using eight explanatory variables, which yielded an RMSE of 22.59 Mgha⁻¹ and an R² of 0.22. The linear ensemble model, which was developed using the predictions of all three models, yielded an R² of 0.79. Our results suggested that more field data are required to better generalize the ensemble model. Overall, our findings highlight the importance of variable selection methods, the hyperparameter tuning of ML algorithms, and the integration of multimodal RS data in improving large-area AGB prediction models. Full article

(This article belongs to the Special Issue Forest Inventory: The Monitoring of Biomass and Carbon Stocks)

►▼ Show Figures

Figure 1

27 pages, 3093 KB

Open AccessArticle

Injury Pattern According to Player Position in Male Amateur Football Players in Greece: A Retrospective Study

by Konstantinos Vassis, Ioannis Misiris, Spyridon Plakias, Athanasios Siouras, Savvas Spanos, Eleftherios Giamouridis, Zacharias Dimitriadis, Dimitrios Tsaopoulos and Ioannis A. Poulis

J. Clin. Med. 2025, 14(17), 6320; https://doi.org/10.3390/jcm14176320 (registering DOI) - 7 Sep 2025

Abstract

Background: Football has a high injury risk due to speed and contact, and injury patterns may vary by playing position. Positional roles affect physical and physiological demands and may influence injury characteristics. Although this has been examined in professionals, data from amateur players are scarce. This study examined the incidence, type, and severity of injuries among amateur footballers in Greece with respect to playing position. Methods: A retrospective epidemiological study analyzed musculoskeletal injuries in 222 amateur male football players during the 2022–2023 season. Data were collected via a CHERRIES-compliant online survey (SurveyMonkey^®) from May to July 2023. Eligible participants were active male athletes aged ≥18 years competing in amateur Greek leagues. Injuries were defined according to the FIFA–UEFA consensus and expressed as incidence rates per 1000 h of exposure. Statistical analyses used SPSS v25 with significance at p < 0.05. Results: Among players (mean age: 25.3 ± 5.7 years), injury prevalence ranged from 65.1% (DFs) to 79.3% (GKs) with no significant association between playing position and injury risk (p = 0.379). Injury incidence ranged from 4.5 to 5.7 per 1000 h, highest among MFs. Incidence rates ranged between 1.33 and 2.74 injuries/1000 h in matches versus 1.33 to 2.09/1000 h in training, with DFs, FWs, and MFs more prone to match injuries, whereas GKs had slightly higher training rates; however, the number of injuries did not significantly differ between games and training across positions (χ² = 5.21, p = 0.517). Muscle strains and lower-limb injuries predominated. Injury severity differed significantly by position (p = 0.001), but injury type and mechanism did not. Conclusions: GKs and MFs showed the highest prevalence and incidence, but position was not linked to overall risk. Severity differences highlight the need for position-specific prevention strategies. Full article

(This article belongs to the Special Issue New Insights into Physical Therapy)

►▼ Show Figures

Figure 1

14 pages, 428 KB

Open AccessArticle

Instrumented Functional Mobility Assessment in Elderly Patients Following Total Knee Arthroplasty: A Retrospective Longitudinal Study Using the Timed Up and Go Test

by Andrei Machado Viegas da Trindade, Leonardo Pinheiro Rezende, Helder Rocha da Silva Araújo, Rodolfo Borges Parreira and Claudia Santos Oliveira

Life 2025, 15(9), 1409; https://doi.org/10.3390/life15091409 (registering DOI) - 7 Sep 2025

Abstract

In the context of the rising demand for total knee arthroplasty (TKA) in older adults and persistent uncertainty about the quality of long-term functional recovery, this study evaluated elderly patients’ mobility after unilateral TKA via a transquadriceps approach using instrumented Timed Up and Go (TUG) tests. A total of 20 patients treated between 2022 and 2024 at a tertiary hospital were invited to participate in this observational, retrospective, descriptive study, and 19 met the inclusion criteria (age 50–80 and Kellgren–Lawrence ≥ 4). The participants performed two TUG trials at two postoperative time points (18 and 53 months), with an inertial measurement unit (G-sensor) capturing 15 kinematic variables. When comparing the postoperative time points, it was found that the total TUG duration remained stable (14.97 ± 3.48 vs. 15.47 ± 2.93 s; p = 0.58), while the mid-turning peak velocity increased significantly (106.44 ± 30.96 vs. 132.77 ± 30.82°/s; p = 0.0039; r = 0.88). The end-turning velocity and sit-to-stand parameters showed small-to-moderate effect size gains without statistical significance. These findings suggest that, in the first year following surgery, patients continue to experience difficulties with movement fluidity and motor control—especially during turning—underscoring the value of segmented, sensor-based assessments and the need for extended rehabilitation protocols that emphasize rotational control and balance. These findings provide clinically relevant parameters that can support future interventional studies and help guide rehabilitation planning after TKA. Full article

(This article belongs to the Special Issue Knee Bracing in Human Movement: Biomechanics, Artificial Intelligence, and Optimization)

►▼ Show Figures

Figure 1

25 pages, 436 KB

Open AccessArticle

Does Biodiversity Conservation Pay Off? An Empirical Analysis of Japanese Firms

by Sayaka Watanabe, Nobuyuki Isagawa and Tomoki Sekiguchi

Sustainability 2025, 17(17), 8051; https://doi.org/10.3390/su17178051 (registering DOI) - 7 Sep 2025

Abstract

This study investigates the bidirectional relationship between biodiversity conservation, an increasingly important dimension of corporate social responsibility (CSR), and corporate financial performance (CFP). Specifically, it compares the manufacturing sector, which has substantial environmental impact and close ties to ecosystems, and the nonmanufacturing sector. The analysis draws on 1079 firm-year observations of Japanese companies from 2017 to 2022, employing the ratio of biodiversity-related expenditures to total environmental costs as the independent variable. CFP is measured by return on assets (ROA) and the price-to-book ratio (PBR). The results show that the effects on ROA significantly differ between manufacturing and nonmanufacturing sectors, with more positive impacts in manufacturing. In contrast, no clear sectoral differences are identified for the PBR. The reverse analysis suggests that, in the nonmanufacturing sector, firms with a higher PBR tend to allocate less to biodiversity conservation, whereas in manufacturing firms, both ROA and the PBR indicate positive effects, although statistical significance was not established. These findings indicate that biodiversity conservation in the manufacturing sector can be regarded as a strategic investment that contributes to profitability, and that its effects differ across industries. The study further suggests that investors and policymakers should consider industry-specific characteristics when evaluating corporate initiatives and designing institutional frameworks. Full article

(This article belongs to the Section Social Ecology and Sustainability)

18 pages, 4279 KB

Open AccessArticle

Soil Compaction Prediction in Precision Agriculture Using Cultivator Shank Vibration and Soil Moisture Data

by Shaghayegh Janbazialamdari, Daniel Flippo, Evan Ridder and Edwin Brokesh

Agriculture 2025, 15(17), 1896; https://doi.org/10.3390/agriculture15171896 (registering DOI) - 7 Sep 2025

Abstract

Precision agriculture applies data-driven strategies to manage spatial and temporal variability within fields, aiming to increase productivity while minimizing pressure on natural resources. As interest in smart tillage systems expands, this study explores a central question: Can tillage tools be used to measure soil compaction during regular field operations? To investigate this, vibration data measurements were collected from a cultivator shank in the northeast of Kansas using the AVDAQ system. The test field soils were Reading silt loam and Eudora–Bismarck Grove silt loams. The relationship between shank vibrations, soil moisture (measured by a Hydrosense II soil–water sensor), and soil compaction (measured by a cone penetrometer) was evaluated using machine learning models. Both XGBoost and Random Forest demonstrated strong predictive performance, with Random Forest achieving a slightly higher correlation of 93.8% compared to 93.7% for XGBoost. Statistical analysis confirmed no significant difference between predicted and measured values, validating the accuracy and reliability of both models. Overall, the results demonstrate that combining vibration data with soil moisture data as model inputs enables accurate estimation of soil compaction, providing a foundation for future in situ soil sensing, reduced tillage intensity, and more sustainable cultivation practices. Full article

(This article belongs to the Section Agricultural Soils)

►▼ Show Figures

Figure 1

18 pages, 620 KB

Open AccessArticle

Unveiling the Synergy Between ESG Performance and Digital Transformation

by Feng Yan, Xiongwang Baihui and Yang Su

Systems 2025, 13(9), 786; https://doi.org/10.3390/systems13090786 (registering DOI) - 7 Sep 2025

Abstract

Against the backdrop of global sustainable development and the fast-growing digital economy, aligning corporate ESG practices with digital transformation is key for enterprises’ high-quality development, yet existing studies have not fully explored ESG’s directional impact on digital transformation. This study examines how corporate ESG performance drives digital transformation and the moderating roles of firm characteristics, industry types, and ownership structures, using 11,109 valid observations from Chinese A-share listed companies (2009–2022); it adopts the causal forest algorithm and supplements with OLS, quantile, and Poisson regressions for robustness tests. The results show that ESG significantly promotes digital transformation—with obvious positive effects from E and S dimensions, while G has no statistical impact—and further analysis reveals nonlinear moderation by firm characteristics and contextual differences: the positive effect is stronger in high-tech and private enterprises but weaker in traditional and state-owned enterprises (due to institutional constraints). These findings offer theoretical insights into ESG–digital synergies and practical guidance for targeted sustainability and digital strategies. Full article

(This article belongs to the Special Issue Sustainable Business Models and Digital Transformation)

►▼ Show Figures

Figure 1

19 pages, 7486 KB

Open AccessArticle

Quantifying the Impacts of Climate Change and Human Activities on Monthly Runoff in the Liuhe River Basin, Northeast China

by Jiyun Yao, Xiaomeng Song and Mingqian Li

Sustainability 2025, 17(17), 8050; https://doi.org/10.3390/su17178050 (registering DOI) - 7 Sep 2025

Abstract

Both climate change and human activities have had a significant impact on hydrological processes. Quantification of affecting factors on river regime changes is scientifically essential for understanding hydrological processes and sustainable water resources management in the basins. This study investigates the features of variations in meteorological and hydrological variables in the Liuhe River Basin (LRB) from 1956 to 2020 based on various observed records and statistical methods. It then quantitatively identifies the possible impacts of climate variability and human activities on runoff in the LRB using the empirical methods and the Budyko framework. The results show that (1) the runoff demonstrates a significantly decreasing trend over the past 65 years, but the rainfall has no obvious trend with significant interannual fluctuations, and potential evapotranspiration exhibits a weekly decreasing trend, particularly in summer. (2) The runoff series can be divided into two periods, i.e., the baseline (1956–1969) and change (1970–2020) periods, and the change period can also be divided into two stages, i.e., stage I (1970–1999) and stage II (2000–2020). (3) Human activities are the dominant factors in the runoff decline in the LRB, with the contribution rates being greater than 80% in the change period, particularly for stage II. The analysis of this study can provide a reference for the rational utilization of water resources in the LRB. Full article

(This article belongs to the Special Issue Advances in Hydrological and Hydrogeochemical Processes and Water–Rock Interactions under Complicated Conditions and Changing Environments)

►▼ Show Figures

Figure 1

13 pages, 728 KB

Open AccessArticle

Comparison of Two Low-Dose Regimens of Intravenous Fentanyl for Pain Relief During Labor: A Double-Blind Randomized Controlled Trial

by Veeraphol Srinil, Panjai Inphum and Sukanya Srinil

Healthcare 2025, 13(17), 2236; https://doi.org/10.3390/healthcare13172236 (registering DOI) - 7 Sep 2025

Abstract

Background: Concerns exist regarding the lowest effective dose of opioids in opioid-naïve pregnancies. This study aimed to compare the effectiveness of 25 µg vs. 50 µg fentanyl in relieving labor pain. Methods: In total, 122 term-singleton pregnant females, who planned vaginal delivery, were randomized to receive 25 µg or 50 µg intravenous fentanyl, followed by hourly doses—as needed—for labor pain relief. The primary outcome was the comparison of pain score reduction 30 min after treatment between these regimens. Secondary outcomes included maternal and neonatal safety, total fentanyl dose administered, maternal satisfaction with the fentanyl dosing regimen, and breastfeeding, which were analyzed using appropriate statistical tests. Results: Within-group analysis revealed significant pain score reduction 30 min after fentanyl injection: −1.57 (95% confidence interval, CI −2.1 to −1.1, p < 0.001) and −1.69 (95% CI −2.2 to −1.2, p < 0.001) for 25 µg and 50 µg fentanyl groups, respectively. No significant differences in the pain reduction were observed in between-group comparisons (0.3, 95% CI −0.6 to 1.2, p > 0.999), including secondary maternal and neonatal outcomes. Total fentanyl dose was significantly lower in the 25 µg group compared with the 50 µg group (32.8 ± 13.3 vs. 60.2 ± 22.1, p < 0.001). Conclusions: A 25 µg intravenous fentanyl dose can reduce VAS score, used for evaluating labor pain 30 min after treatment, and is comparable to a 50 µg intravenous fentanyl dose. Given the efficacy of the reduced dosage of fentanyl, this study suggests using 25 µg intravenous fentanyl as an alternative initial dosing for labor pain relief. Full article

(This article belongs to the Section Pain Management)

►▼ Show Figures

Figure 1

14 pages, 3549 KB

Open AccessArticle

The Use of Fibrin Clot During Meniscus Repair in Young Patients Reduces Clinical Symptom Rates at 12-Month Follow-Up: A Pilot Randomized Controlled Trial

by Viktorija Brogaitė Martinkėnienė, Donatas Austys, Andrius Brazaitis, Aleksas Makulavičius, Tomas Aukštikalnis, Ilona Dockienė and Gilvydas Verkauskas

Medicina 2025, 61(9), 1616; https://doi.org/10.3390/medicina61091616 (registering DOI) - 7 Sep 2025

Abstract

Background and Objectives: The menisci are crucial fibrocartilaginous structures of the knee joint and have to be repaired in case of a tear. However, not all meniscal tears heal, even in young patients. Fibrin clot (FC) started to be used to reduce the failure rates following meniscus repair. The purpose of this study is to evaluate and compare outcomes after isolated arthroscopic meniscal repair augmented with FC versus without FC. Materials and Methods: Fifty-nine patients aged under 19 with isolated meniscal tears were randomized into two groups: one group underwent the meniscal repair with FC (FC-augmented), and the other group did not receive FC (control). The evaluation and comparison between the groups based on FC augmentation included secondary arthroscopy rates, patient-reported outcome measures (Pedi-IKDC, Lysholm, and Tegner), and clinical and radiological (MRI) assessments at a median follow-up of 12 months. Results: No statistically significant difference was observed between FC-augmented and control groups in Pedi-IKDC, Lysholm, and TAG scores, or following clinical and radiological (MRI) evaluation. Patients in the FC-augmented group reported fewer clinical symptoms at the final follow-up across unstable and demanding (bucket-handle and complex) tear type subgroups (p = 0.012 and 0.041, respectively). Overall, nine revision arthroscopies occurred in both groups (2 and 7, respectively), all across bucket-handle and complex tears with no significant difference between the FC-augmented and control groups (p = 0.072). Conclusions: This pilot study found that FC usage during meniscal repair reduces clinical symptoms for patients with unstable, bucket-handle, or complex meniscal tears at the final follow-up of 12 months postoperatively. Nonetheless, no statistically significant differences were observed within the other outcome measures between the FC-augmented and control groups and subgroups based on meniscal tear types. Level of evidence: Level II. Full article

(This article belongs to the Special Issue Clinical Research in Orthopaedics and Trauma Surgery)

►▼ Show Figures

Figure 1

26 pages, 3804 KB

Open AccessArticle

Spatio-Temporal Patterns and Regional Differences in Carbon Emission Intensity of Land Uses in China

by Ming Zhang, Changhong Cai, Jun Guan, Jing Cheng, Changqing Chen, Yani Lai and Xiangsheng Chen

Sustainability 2025, 17(17), 8048; https://doi.org/10.3390/su17178048 (registering DOI) - 7 Sep 2025

Abstract

In recent years, the frequent occurrence of extreme weather events has prompted increased global attention to greenhouse gas emissions. This study analyzes the spatio-temporal evolution of carbon emission intensity (CEI) across land use types in China’s 30 provinces from 2009 to 2022. Based on the data from China Rural Statistical Yearbook, China City Statistical Yearbook, China Energy Statistical Yearbook, China Natural Resources Statistical Yearbook, and China Statistical Yearbook, this study aims to reveal the spatio-temporal differentiation patterns of CEI, analyze the decoupling status between development mode and carbon emissions, and establish a three-dimensional collaborative emission reduction framework. Firstly, employing the carbon emission factor method, provincial carbon emissions, sinks, and net emissions are calculated, with intensity levels derived from gross domestic product (GDP). Secondly, spatio-temporal trends and inter-provincial disparities are analyzed using the decoupling index. The spatial effects among the provinces are investigated based on Moran’s I index. The results show that while the overall CEI has declined since 2009, significant regional disparities persist, with the southern provinces showing lower carbon emission intensities compared to the northern and western regions. The spatial analysis reveals a strong aggregation effect, with provinces clustering into high-high (HH) and low-low (LL) regions regarding CEI. This study concludes with policy recommendations for emission reduction and climate change mitigation, emphasizing industrial structure adjustment, enhanced regional coordination, and optimized land use planning. Full article

(This article belongs to the Section Sustainable Urban and Rural Development)

►▼ Show Figures

Figure 1

Show export options Show export options

Select all

Export citation of selected articles as:

Error

Oops... you haven't selected anything for export.

Displaying article 1-50 on page 1 of 1867.

Go to page 1 2 3 4 5

Search Results (93,315)

Further Information

Guidelines

MDPI Initiatives

Follow MDPI