Search Results (107,441)

Background/Objectives: Early detection of undiagnosed prediabetes (PD) and type 2 diabetes (T2D) could prevent or delay the onset of diabetes and its complications. The dental setting has been suggested as a location for expanding diabetes screening in primary care. This study aimed to investigate behavioural factors that influence an oral healthcare professional’s (OHP) participation in diabetes screening and their decision to refer individuals at a high risk of diabetes for medical follow-up and confirmatory diagnosis. These factors provide targets for future interventions to encourage screening implementation and increase referral guideline compliance. Methods: This qualitative study utilised OHPs who had participated in a diabetes screening trial in Victoria, Australia. Qualitative, semi-structured interviews were conducted by telephone or videoconferencing and transcribed and analysed thematically. The themes identified were deductively mapped onto the Capability, Opportunity, Motivation, and Behaviour (COM-B) model and the Theoretical Domains Framework (TDF). Results: In total, eight interviews were conducted (seven dentists and one oral health therapist). Five COM-B domains were identified: reflective motivation, automatic motivation, social opportunity, physical opportunity, and psychological capability. Nine TDF domains were associated with issues related to knowledge, the environmental context and resources, memory, attention and decision processes, skills, social influences, beliefs about consequences, emotion, beliefs about capability, and social influence. Conclusions: This is the first study to investigate the factors influencing an OHP’s participation and decision making in diabetes screening and referral processes in the dental setting. The results demonstrate that OHPs need more education and training to screen for diabetes in dental clinics. This study represents the first step in developing interventions to target these factors and improve the effectiveness of diabetes screening in the dental setting. Full article

In the context of digital school development, the leadership practices of school leadership teams play a significant role. If leadership teams want to enact leadership practices effectively, they require strong connections to the entire teaching staff as well as close contact with other key actors in the digital process. Since little is known about these connection patterns of school leadership teams, this study aims to uncover them. The aim is to provide practical advice to school administrators and schools regarding digital school development, and to derive concrete recommendations for action concerning their relationships and management. To this end, we examined the social networks of the teaching staff of 13 German secondary schools (N = 817 teachers) by asking all the teachers to complete a questionnaire about their contacts in relation to digital school development. We conducted a social network analysis and extracted various network metrics pertaining to the school leadership teams of these institutions, considering not only their integration within the overall network but also their connections with a pivotal stakeholder: the digital coordinator. To contextualize our findings, we compared the network metrics of the two different professional target groups using t-tests. The results reveal significant variability in the connection patterns of school leadership teams across different schools. Furthermore, our analysis indicates that digital coordinators consistently exhibit higher levels of connectedness within the realm of digital school development than the members of the school leadership teams. These findings highlight the importance of close collaboration between school leadership teams and the digital coordinator in order to advance digital school development. It is also suggested that school leadership teams should consider delegating more responsibilities to the digital coordinator, particularly those necessitating close collaboration with the teaching staff. Full article

Background: Elevated Lp-PLA2 activity, a marker of inflammation and oxidative stress, is linked to increased cardiovascular disease (CVD) risk in type 2 diabetes mellitus (T2DM). Given that high Lp-PLA2 activity is a hallmark of metabolic-dysfunction-associated steatotic liver disease (MASLD), we aimed to investigate whether it contributes additional CVD risks when MASLD coexists with T2DM. Methods: This study included 1095 patients with T2DM, consecutively enrolled at the First Affiliated Hospital, Sun Yat-sen University, between June 2020 and November 2022. Liver steatosis and stiffness were assessed via abdominal ultrasound/CT and fibrosis-4 (FIB-4) scores, respectively. Carotid atherosclerosis (CAS) was defined as the presence of intima-media thickening or carotid plaque and was evaluated using high-resolution B-mode ultrasonography. Results: Among 674 MASLD patients, higher levels of Lp-PLA2 activity were observed compared to those in 421 non-MASLD individuals (573 ± 164 U/L vs. 540 ± 170 U/L, p = 0.002), while no association was found between steatosis degree and Lp-PLA2. Lp-PLA2 levels exceeding a threshold of 570 U/L were identified as a risk factor for CAS, with each one standard deviation increase in Lp-PLA2 corresponding to an odds ratio of 2.67 (95% confidence interval: 1.31–5.42, p = 0.007), while a similar association was not observed in patients with normal FIB-4 levels. Conclusions: Elevated Lp-PLA2 activity is associated with MASLD and insulin resistance in T2DM, while Lp-PLA2 was not related to the degree of liver steatosis. A threshold of 570 U/L is associated with CAS risk, specifically in those with concurrent advanced liver fibrosis, highlighting the potential role of Lp-PLA2 in cardiovascular risk stratification in this subset but within the limitations of a cross-sectional study. Full article

Pipeline exfiltration from damaged water-supply systems frequently causes soil erosion and ground subsidence, which jeopardizes the safety of pedestrians and vehicles and even causes casualties. Despite the severe consequences, it is difficult for engineers to give reliable assessments of pipeline exfiltration hazards. In this study, erosion processes were explored using model tests and coupled computational fluid dynamics–discrete element method (CFD-DEM) simulations. It was discovered that the erosion zone can be divided into two zones—the exfiltration zone and the seepage diffusion zone. When water pressure reached 2.412 × 10⁻² MPa, local porosity approached 1.0, indicating there were no soil particles remaining. As pipeline pressure increased from 2.122 × 10⁻³ MPa to 2.412 × 10⁻² MPa, ground failure transitioned from downward settlement to upward bulge, and the ground failure duration of the fractured prototype pipe was reduced by 22–28% (from 125 s to 98 s), with a standard deviation of less than 5. The established exponential decay model ($\mathrm{v}\left(\mathrm{t}\right)={\mathrm{v}}_0{\mathrm{e}}^{(-\mathsf{\alpha }\mathrm{t})},{\mathrm{R}}^2>0.89$) enabled prediction of erosion duration. Based on the erosion height curve, the erosion duration and erosion area in similar engineering environments can be estimated, providing a reference for evaluating the risk of ground collapse due to pipe exfiltration. Full article

A novel species of the genus Methylocystis is proposed based on polyphasic evidence from strain SC2^T, isolated from the heavily polluted Saale River near Wichmar, Germany. Digital DNA–DNA hybridization and phylogenomic analyses demonstrate that strain SC2^T represents a distinct species within the genus, clearly separated from its closest relatives, namely Methylocystis suflitae NLS-7^T, Methylocystis rosea SV97^T, Methylocystis silviterrae FS^T, and Methylocystis hirsuta CSC1^T. As is typical of the family Methylocystaceae, cells possess intracytoplasmic membranes arranged parallel to the cytoplasmic membrane, and the dominant fatty acids are C18:1ω8c and C18:1ω7c. The strain grows aerobically on methane as the primary carbon and energy source and expresses both low- and high-affinity particulate methane monooxygenase (pMMO), but lacks the soluble form. The species epithet reflects the strain’s ability to utilize hydrogen as an alternative energy source. A further feature is its use of asparagine as an osmoprotectant, enhancing salt tolerance. Genomic analysis reveals complete pathways for nitrogen fixation, denitrification, and hydrogen oxidation. These genetic and physiological characteristics support the designation of a novel species, for which the name Methylocystis hydrogenophila sp. nov. is proposed. The type strain is SC2^T (=DSM 114506 = NCIMB 15437). Full article

To counter the high unmet need for family planning in urban areas of Sindh province, Pakistan, Greenstar Social Marketing began implementation of The Challenge Initiative (TCI) in collaboration with the government departments of Population Welfare and Health in eight urban districts of Sindh province. This study aimed to assess the effectiveness of TCI’s Community Health Volunteers (CHVs) on public sector service provision of family planning services in eight urban districts of Sindh province, Pakistan. The Contraceptive Logistics Management Information System (cLMIS) and District Health Information System 2 (DHIS2) were used to obtain monthly contraceptive data from June 2022 to December 2024. CHVs began implementation at different time points in each district, starting from January 2023 to October 2023, when CHVs became operational in all eight districts. Descriptive statistics and two-sample t-tests were used for data analysis. CHVs significantly improved family planning service provision, particularly for short- and long-acting methods at the facility level, with greater change observed in Department of Health facilities. This study provides preliminary evidence of the effectiveness of CHVs in increasing public sector service provision of contraceptives, particularly for Department of Health facilities. CHVs bridge the gap between the community and the facility, particularly in areas uncovered by the government’s existing mobilization staff. Full article

High-precision semantic segmentation of remote sensing imagery is crucial in geospatial analysis. It plays an immeasurable role in fields such as urban governance, environmental monitoring, and natural resource management. However, when confronted with complex objects (such as winding roads and dispersed buildings), existing semantic segmentation methods still suffer from inadequate target recognition capabilities and multi-scale representation issues. This paper proposes a neural network model, LMVMamba (LoRA Multi-scale Vision Mamba), for semantic segmentation of remote sensing images. This model integrates the advantages of convolutional neural networks (CNNs), Transformers, and state-space models (Mamba) with a multi-scale feature fusion strategy. It simultaneously captures global contextual information and fine-grained local features. Specifically, in the encoder stage, the ResT Transformer serves as the backbone network, employing a LoRA fine-tuning strategy to effectively enhance model accuracy by training only the introduced low-rank matrix pairs. The extracted features are then passed to the decoder, where a U-shaped Mamba decoder is designed. In this stage, a Multi-Scale Post-processing Block (MPB) is introduced, consisting of depthwise separable convolutions and residual concatenation. This block effectively extracts multi-scale features and enhances local detail extraction after the VSS block. Additionally, a Local Enhancement and Fusion Attention Module (LAS) is added at the end of each decoder block. LAS integrates the SimAM attention mechanism, further enhancing the model’s multi-scale feature fusion capability and local detail segmentation capability. Through extensive comparative experiments, it was found that LMVMamba achieves superior performance on the OpenEarthMap dataset (mIoU 52.3%, OA 69.8%, mF1: 68.0%) and LoveDA (mIoU 67.9%, OA 80.3%, mF1: 80.5%) datasets. Ablation experiments validated the effectiveness of each module. The final results indicate that this model is highly suitable for high-precision land-cover classification tasks in remote sensing imagery. LMVMamba provides an effective solution for precise semantic segmentation of high-resolution remote sensing imagery. Full article

Background and Clinical Significance: Thoracic dorsal arachnoid web (DAW) is a rare intradural extramedullary condition characterized by a thin band of arachnoid tissue compressing the dorsal spinal cord. A hallmark imaging feature is the “scalpel sign”, which refers to anterior displacement of the thoracic spinal cord with dorsal cerebrospinal fluid (CSF) accumulation, producing a sagittal profile resembling a surgical scalpel. Although highly specific for DAW, this sign may also appear in other intradural conditions such as idiopathic ventral spinal cord herniation and arachnoid cysts. The clinical presentation is typically progressive and nonspecific, including lower limb weakness, sensory changes, gait disturbances, and, less frequently, sphincter dysfunction. Diagnosis is often delayed due to the subtle nature of the lesion and limited resolution of conventional Magnetic Resonance Imaging (MRI). High-resolution Three-Dimensional Constructive Interference in Steady State (3D-CISS) sequences improve diagnostic accuracy by highlighting indirect signs such as spinal cord deformation and dorsal CSF flow obstruction. Case Presentation: We report the case of a 57-year-old woman presenting with chronic cervico-dorsalgia, bilateral lower limb weakness, paresthesia, and progressive gait instability. Neurological examination revealed spastic paraparesis and hyperreflexia. Conventional MRI was inconclusive. However, sagittal T2-weighted and 3D-CISS sequences demonstrated the scalpel sign at the T4–T5 level, with anterior cord displacement and dorsal subarachnoid space enlargement. Surgical exploration confirmed the presence of a dorsal arachnoid web, which was resected. Postoperative follow-up showed clear improvement in motor function and gait. Conclusions: DAW should be considered in cases of unexplained thoracic myelopathy or cervico-dorsalgia with neurological signs. Early recognition of the scalpel sign using advanced MRI sequences is critical for timely diagnosis and surgical planning, which may lead to significant clinical improvement. Full article

Modern energy systems are undergoing a profound transformation characterized by the active replacement of conventional fossil-fuel-based power plants with renewable energy sources. This transition aims to reduce the carbon emissions associated with electricity generation while enhancing the economic performance of electric power market players. However, alongside these benefits come several challenges, including reduced overall inertia within energy systems, heightened stochastic variability in grid operation regimes, and stricter demands on the rapid response capabilities and adaptability of emergency controls. This paper presents a novel methodology for selecting effective control laws for low-inertia energy systems, ensuring their dynamic stability during post-emergency operational conditions. The proposed approach integrates advanced techniques, including feature selection via decision tree algorithms, classification using Random Forest models, and result visualization through the Mean Shift clustering method applied to a two-dimensional representation derived from the t-distributed Stochastic Neighbor Embedding technique. A modified version of the IEEE39 benchmark model served as the testbed for numerical experiments, achieving a classification accuracy of 98.3%, accompanied by a control law synthesis delay of just 0.047 milliseconds. In conclusion, this work summarizes the key findings and outlines potential enhancements to refine the presented methodology further. Full article

Background: Philadelphia-like acute lymphoblastic leukemia (Ph-like ALL) is a high-risk subtype of B-cell ALL characterized by a gene expression profile similar to BCR::ABL1-positive leukemia, but lacking the BCR::ABL1 fusion gene. It is frequently associated with kinase-activating alterations, such as CRLF2 rearrangements, JAK-STAT pathway mutations, and ABL-class fusions. Patients with Ph-like ALL typically experience poor outcomes with conventional chemotherapy, underscoring the need for intensified and targeted therapeutic approaches. Methods: This review summarizes current evidence regarding the role of hematopoietic stem cell transplantation (HSCT) in patients with Ph-like ALL. We analyzed retrospective cohort studies, registry data, and ongoing clinical trials, focusing on transplant indications, molecular risk stratification, measurable residual disease (MRD) status, timing of transplant, and post-transplant strategies. Results: Retrospective data suggest that HSCT in first complete remission (CR1) may improve survival in patients with high-risk molecular lesions or MRD positivity at the end of induction. However, the lack of prospective data specific to Ph-like ALL limits definitive conclusions. Post-transplant relapse remains a challenge, and novel strategies, including the use of tyrosine kinase inhibitors or JAK inhibitors as post-HSCT maintenance therapy, are being explored. Emerging immunotherapies, such as chimeric antigen receptor (CAR) T cells, may reshape the therapeutic landscape and potentially alter the indications for transplantation. Conclusions: HSCT remains a crucial therapeutic option for selected patients with Ph-like ALL, particularly those with poor molecular risk features or persistent MRD. However, further prospective studies are needed to evaluate the indication for HSCT in CR1 and the potential integration of transplantation with targeted and immunotherapeutic strategies. Personalized treatment approaches based on genomic profiling and MRD assessment are essential to improve outcomes in this high-risk subset. Full article

Fifty-two horses aged >15 years, diagnosed with pituitary pars intermedia dysfunction (PPID), and displaying hypertrichosis were recruited via an online survey of PPID horse owners. From mid-December, group T (n = 29) wore Equilume^® light masks extending photoperiod to 15 h daily, while group C1 (n = 23) remained under natural photoperiod. As 85% (44/52) of recruited study horses received pergolide medication, a second unmedicated PPID research herd (C2; n = 17) was recruited and remained under natural photoperiod. Hair coat samples, shedding and body condition scores were collected monthly by owners for 13 months and analysed by the research team. Data related to management, coat condition and PPID clinical signs were collected using bimonthly questionnaires (BMQ). Time (p < 0.001), group (p = 0.025) and time-by-group interaction (p = 0.005) affected hair length. Group differences were attributable to shorter hair lengths in C2, and no differences in hair length occurred between T and C1 (p > 0.05). Time affected shedding scores (p < 0.001) which was advanced by one month in T (p < 0.05). In group T, BMQ responses showed improved coat condition in April (p = 0.035), decreased fat coverage in April and June (p < 0.05), and increased energy/alertness in February (p = 0.022). Improvements in coat condition (p = 0.043), clinical signs of PPID (p = 0.018), and general quality of life (p = 0.035) were reported in T only in a final study questionnaire. Blue light treatment merits further investigation as a complementary treatment for PPID. Full article

Type 2 diabetes mellitus (T2DM) is associated with increased cardiovascular risk characterized by low-grade inflammation. The aim of this systematic review and meta-analysis was to assess the effects of resistance exercise training (RET) predominantly on cytokines, along with changes in glucose profile and body composition in T2DM patients. The present systematic review and meta-analysis was conducted utilizing PubMed, Web of Science, Embase, and the Cochrane Library databases from their inception up to July 2024 (PROSPERO; registration number CRD420251149352). We screened only for randomized controlled trials investigating the effects of systematic, supervised RET on C-reactive protein (CRP) and adipokines: adiponectin, interleukin 6 (IL-6), tumor necrosis factor-alpha (TNF-α), along with changes in anthropometric indices and glycemic control in adult T2DM patients. Pooled post-exercise weighted mean differences (WMDs) with 95% confidence intervals (CIs) were calculated for all outcomes of interest between exercise-treated patients and controls. Sixteen studies involving a total of 668 T2DM patients were retrieved from the databases for meta-analysis. We used the GRADE framework for assessing the certainty of evidence. Cochran Q-score (I²) was used to estimate heterogeneity among studies (level of significance p < 0.10) and risk of bias analysis was also performed. The cumulative results showed that post-RET inflammatory markers were lower in exercise-treated patients compared to controls regarding CRP (mg/L) (WMD: −0.63; 95%CIs: −1.05, −0.20; p < 0.001); adiponectin (μg/mL) (WMD: −0.94; 95%CIs: −1.49, −0.38; p < 0.001). The results from adiponectin are quite conflicting since they derived from only three studies, where one of them had the greater impact. In parallel, we noticed significant amelioration of fasting glucose and HbA1c (p < 0.001), while body weight remained unaltered. Our meta-analysis demonstrated non-significantly lower levels of IL-6 and TNF-α in RET vs. control group. RET can merely reduce the inflammatory burden in T2DM patients by ameliorating the circulating levels of CRP and adiponectin, while in the rest of the biomarkers, non-significant results were obtained. Hence, the overall clinical impact of those anti-inflammatory effects of RET needs to be determined. Full article

Bisphenol A (2,2-bis(4-hydroxyphenyl)propane, BPA), an endocrine-disrupting chemical with recognized adverse effects on human health and ecosystems, urgently requires convenient, sensitive, and accurate detection methods. In this study, a hierarchical heterostructure was fabricated by incorporating Ti₃C₂T_x MXene and mesoporous hollow carbon spheres (MHCs) to develop a high-performance electrochemical sensor for BPA. The nanocomposite was thoroughly characterized using SEM, TEM, and XRD, and then applied to modify a glassy carbon electrode (GCE). Under optimized conditions including pH and accumulation time, BPA detection was carried out via differential pulse voltammetry (DPV). The sensor exhibited a wide linear detection range from 10 to 200 μM and a low detection limit of 2.6 μM. Moreover, it was successfully applied to environmental water samples, demonstrating high accuracy and practicality for real-world BPA monitoring. Full article

This paper presents an automatic system for the classification of musical instruments from audio recordings. The project leverages deep learning (DL) techniques to achieve its objective, exploring three different classification approaches based on distinct input representations. The first method involves the extraction of Mel-Frequency Cepstral Coefficients (MFCCs) from the audio files, which are then fed into a two-dimensional convolutional neural network (Conv2D). The second approach makes use of mel-spectrogram images as input to a similar Conv2D architecture. The third approach employs conventional machine learning (ML) classifiers, including Logistic Regression, K-Nearest Neighbors, and Random Forest, trained on MFCC-derived feature vectors. To gain insight into the behavior of the DL model, explainability techniques were applied to the Conv2D model using mel-spectrograms, allowing for a better understanding of how the network interprets relevant features for classification. Additionally, t-distributed stochastic neighbor embedding (t-SNE) was employed on the MFCC vectors to visualize how instrument classes are organized in the feature space. One of the main challenges encountered was the class imbalance within the dataset, which was addressed by assigning class-specific weights during training. The results, in terms of classification accuracy, were very satisfactory across all approaches, with the convolutional models and Random Forest achieving around 97–98%, and Logistic Regression yielding slightly lower performance. In conclusion, the proposed methods proved effective for the selected dataset, and future work may focus on further improving class balance techniques. Full article

Background/Objectives: The prevalence of obesity globally has increased steadily in the past decades. Obesity, sarcopenic obesity (SO) and nonalcoholic fatty liver disease (NAFLD) commonly coexist. Ursolic acid (UA), a natural pentacyclic triterpenoid, has demonstrated potential anti-obesity properties. This study was designed to evaluate the anti-obesity efficacy of UA in a mouse model of high-fat diet (HFD)-induced obesity, with a particular focus on its impact on muscle function and NAFLD. Methods: Male C57BL/6J mice (6 weeks old) were randomly assigned to three groups (n = 20 per group): a control group (CON) fed a normal chow diet, a high-fat diet group (HFD), and a UA treatment group (UA). The HFD and UA groups received a high-fat diet for 10 weeks to induce obesity. Thereafter, mice in the UA group were administered UA orally once daily for 6 weeks. Results: In HFD-induced obese mice, UA administration significantly reduced body weight (BW), abdominal fat weight and liver weight; improved grip strength and muscle weight; and enhanced lipid profiles, including triglycerides, total cholesterol, low-density lipoprotein cholesterol and free fatty acid levels in serum. UA also improved histological changes in the liver and abdominal adipose tissues, regulated serum GH, IGF-1, T3, T4 and leptin levels and downregulated the inflammation-associated gene expression of TNF-α and IL-1β in abdominal adipose tissue. Conclusions: UA could enhance muscle strength, improve lipid metabolism and hepatic steatosis and might be considered a potential therapeutic agent for managing obesity and related metabolic diseases. Full article