Search Results (2,211)

Microwave Breast Imaging (MWBI) is an emerging imaging modality aiming to detect breast lesions, which are dielectrically contrasted against the background healthy tissue, in the microwave frequency spectrum. MWBI holds potential to outperform X-ray mammography’s low sensitivity in young and dense breasts, thus supporting timelier detection of interval cancers, as a supplemental screening or diagnostic imaging method. The specificity of MWBI remains unknown, however, as management of false positives has not been systematically addressed yet. An earlier First-In-Human clinical investigation on 24 symptomatic patients provided proof-of-concept for the Wavelia MWBI sectorized multi-static radar imaging technology, which generates clinically meaningful 3D images of the breast, performs semi-automated detection of breast lesions and extracts diagnostic features to distinguish malignant from benign lesions. This paper focuses on a set of technological upgrades, accessories and data processing modules, designed and implemented in the 2nd generation prototype of Wavelia, to handle the diversity in breast geometry, tissue consistency and deformability, in a larger clinical investigation reporting on the bilateral MWBI scan of 62 patients. The presented add-on modules contribute to enhanced quality of scan and a more valid reference reporting space for the MWBI imaging outputs, with a direct positive impact on overall specificity. Full article

Background: Depression is one of the most common mental disorders among undergraduate students, particularly those in medical training, who face high academic demands and emotional burdens. Biological factors such as lipid abnormalities have been proposed as contributors to depressive symptoms, although evidence in this group is scarce. Therefore, we aimed to evaluate the association between triglyceride and total cholesterol levels and depressive symptoms in medical students. Methods: We conducted a cross-sectional study including 219 medical students from a public university in Mexico. Depressive symptoms were assessed using the CESD-7 scale, validated in the Mexican population. Fasting triglyceride and total cholesterol concentrations were measured with the Accutrend Plus analyzer. Prevalence ratios (PRs) and 95% confidence intervals (CIs) were estimated using robust Poisson regression, adjusting for potential confounders. Results: Overall, 38.8% of students presented depressive symptoms. In adjusted continuous models, each 10 mg/dL increase in triglycerides was associated with a 4% higher prevalence of depression (PR = 1.04, 95% CI 1.03–1.06), while each 10 mg/dL increase in total cholesterol was associated with a 13% higher prevalence (PR = 1.13, 95% CI 1.05–1.21). Analyses using clinically relevant cutoffs confirmed these associations: triglycerides ≥ 150 mg/dL (PR = 1.76, 95% CI 1.24–2.48) and cholesterol ≥ 200 mg/dL (PR = 1.66, 95% CI 1.19–2.31). Conclusions: Dyslipidemias may play a relevant role in the mental health of young adults and highlight the importance of incorporating metabolic risk assessment into strategies to prevent and address depression in medical students. Full article

Background/Objectives: The presence of distant metastases is the main cause of death in medullary thyroid carcinoma (MTC). However, due to the rarity of this cancer, few studies have thoroughly analyzed the variables influencing the development of distant metastases. The objective of this study was to evaluate, in patients with MTC, the factors associated with the occurrence of synchronous and metachronous distant metastases. Methods: An analytical, observational, retrospective cohort study was conducted at a tertiary hospital. Patients with histologically confirmed MTC, both sporadic and familial (MEN2 syndrome), were included. The influence of epidemiological variables, heredity, complementary tests, surgical factors, histological features, staging, and disease progression was assessed. A univariate comparative analysis was first performed, followed by a multivariate analysis using logistic regression. Results: This study included 146 patients, of whom 75% (n = 109) had familial MTC. Lymph node involvement at diagnosis was observed in 36% (n = 52). During follow-up, distant metastases developed in 14% (n = 21) of patients, including five cases present at the time of diagnosis. The median follow-up was 214 months (IQR 106–289). The presence of distant metastases was associated with an increased risk of mortality. Factors associated with distant metastases included age, calcitonin level, hereditary status, lymph node involvement, and overall stage. In multivariate analysis, the lymph node ratio (LNR) remained the only significant predictor (OR 29.124). Conclusions: Several variables were related to the presence of distant metastases. Among them, the LNR emerged as the independent predictor of both synchronous and metachronous distant metastases. Full article

The transition to decarbonized and distributed energy systems has increased interest in flexibility markets as a key tool to manage variability and coordinate distributed energy resources. However, the fast growth and conceptual fragmentation of this field hinder the building of coherent models and scalable solutions. This paper presents a scoping review of 243 peer-reviewed articles published between 2013 and 2025, applying the TEAM Framework and Business Model Canvas. Through a structured data matrix of 35 variables, we analyze how flexibility is defined and modelled, the coordination mechanisms applied, and how business dimensions are integrated. The results reveal major inconsistencies in terminology, actor roles, price formation, and interoperability modelling. We identify critical gaps in cost modelling and business model integration, especially in low-TRL studies. This review provides a comprehensive and cross-cutting synthesis of existing approaches, offering a reference framework for future research, policy design, and market implementation of distributed flexibility mechanisms. Full article

Climate change poses a significant threat to crop production, particularly in tropical and semi-arid regions. Sorghum (Sorghum bicolor (L.) Moench), a resilient C₄ cereal, has high photosynthetic efficiency and abiotic stress tolerance, making it a key crop for food, fodder, and feed security. This study evaluated agronomic and physiological traits influencing the yield performance of 20 sorghum varieties under field conditions in Kerala, India. The data were analyzed using a randomized block design (RBD) in GRAPES software, and a principal component analysis was performed in R. Variety CSV 17 exhibited the highest grain yield (GY) (3760 kg ha⁻¹) and harvest index (HI) (43), with early flowering, early maturity, a high chlorophyll content (CHL), and minimal nitrogen (N), phosphorus (P), and potassium uptake. Conversely, CSV 20 produced the highest stover yield (22.5 t ha⁻¹), associated with greater leaf thickness (LT), lower canopy temperature, taller plant height (PH), increased leaf number (LN), and extended maturity. Leaf temperature (T_leaf) was negatively correlated with the quantum yield of photosystem II (ΦPSII) and panicle length (PL), which were strong predictors of grain weight. The principal component analysis revealed that PC1 and PC2 explained 21% and 19% of the variation in the grain and stover yield, respectively. Hierarchical partitioning identified the potassium content (K%), CHL, T_leaf, leaf area index (LAI), ΦPSII, and LT as key contributors to the GY, while the SY was primarily influenced by the LN, nitrogen content (N%), maturity duration, PH, and ΦPSII. These findings highlight the potential of exploiting physiological traits for enhancing sorghum productivity under summer conditions in Kerala and similar environments. Full article

Dumping Syndrome (DS) is a significant complication following bariatric surgery, particularly Roux-en-Y gastric bypass (RYGB). This condition is characterised by gastrointestinal and vasomotor symptoms resulting from altered anatomy and hormonal dysregulation, notably accelerated gastric emptying and an exaggerated release of gut peptides. Based on the timing of symptom onset after food ingestion, DS is classified as early (EDS) or late (LDS). The critical roles of peptides such as GLP-1, GIP, insulin, and YY peptide are highlighted, along with the involvement of neuroendocrine pathways in symptom manifestation. Diagnosis relies on a combination of clinical evaluation and dynamic testing, with the oral glucose tolerance test (OGTT) often considered a key reference standard for diagnosis. Initial management involves dietary modifications, emphasising the glycaemic index of foods and meal distribution. In cases where nutritional interventions are insufficient, pharmacotherapy with agents such as acarbose, somatostatin analogues (octreotide and pasireotide), GLP-1 receptor agonists (liraglutide), calcium channel blockers (verapamil), and emerging therapies, including herbal medicine, may be considered. For refractory cases, surgical options like bypass reversal or partial pancreatectomy are reserved, although their efficacy can be variable. Despite advancements in understanding and treating DS, further large-scale, randomised controlled trials are essential to validate novel strategies and optimise long-term management. This review provides an updated and comprehensive overview of the aetiology, pathophysiological mechanisms, diagnostic approaches, and current management strategies for DS. Full article

In Santiago, Chile, urban plants are highly vulnerable to drought or climate change. We hypothesize that would find high growth and survival rates in conditions of water scarcity among native species of central Chile. The goal was to determine the effect of the year season and an irrigation gradient on the survival and growth of native plant, in order to evaluate potential plant for use in urban green areas of central Chile. Four plots of 20 m² were located in the Santiago center. In June 2024 twelve species were planted and from November 2024 to March 2025 were irrigated with 13.3, 10.1, 1.7 and 1.4 L/m²/day. The GLM and Kaplan–Meier survival analyses were used. Shoot growth rate was highly variable among species, among irrigation treatments applied, and among year seasons. Eight species showed water-related growth and shoot growth during the winter was very small and higher in spring. Two species showed evidence of water-related survival; in the other 10 species, no significant differences were found between irrigation treatments. Winter was the season with the highest survival rates for eleven species. In conclusion, the results suggest that native plants can achieve high survival rates with limited irrigation. This highlights their potential for use in the urban area in Mediterranean-type climates where rainfall is expected to be low due to climate change. Full article

Small landslides, though frequent, are often overlooked despite their significant potential impact on human-affected areas. This study presents an analysis of the Bella Orxeta landslide in Alicante, Spain, a rotational landslide event that occurred in March 2017 following intense and continued rainfall. Utilizing multitemporal datasets, including LiDAR from 2009 and 2016 and drone-based photogrammetry from 2021 and 2023, we generated high-resolution digital terrain models (DTMs) to assess morphological changes, estimate displaced volumes of approximately 3500 cubic meters, and monitor slope activity. Our analysis revealed substantial mass movement between 2016 and 2021, followed by relatively minor changes between 2021 and 2023, primarily related to fluvial erosion. This study demonstrates the effectiveness of UAV and DTM differencing techniques for landslide detection, volumetric analysis, and long-term monitoring in urbanized settings. Beyond its scientific contributions, the Bella Orxeta case offers pedagogical value across academic disciplines, supporting practical training in geomorphology, geotechnical assessment, GIS, and risk planning. It also highlights policy gaps in existing territorial risk plans, particularly regarding the integration of modern monitoring tools for small-scale but recurrent geohazards. Given climate change projections indicating more frequent high-intensity rainfall events in Mediterranean areas, the paper advocates for the systematic documentation of local landslide cases to improve hazard preparedness, urban resilience, and geoscience education. Full article

This study investigated the efficacy of agave bagasse biochar and zeolite as filter materials for the removal of boron from water using a continuous flow column system. Experiments were conducted with varying initial boron concentrations and contact times. The results showed moderate boron removal capabilities, with agave biochar slightly outperforming zeolite. Maximum removal percentages of 29.31% for zeolite and 33.12% for agave biochar were achieved at the lowest initial boron concentration. Factorial analysis revealed significant effects of concentration, contact time, and column material on boron removal, with contact time having the largest impact. The interaction between concentration and column material suggests the potential for optimization. While removal percentages were lower compared to some chemically modified materials, the use of low-cost, natural filter media offers sustainability advantages. These materials show promise for treating water with lower boron levels or as part of a multi-step treatment process. Future research should focus on optimizing experimental conditions and exploring material modifications to enhance boron removal efficiency. Full article

This study introduces a non-destructive computer vision method for estimating postharvest quality parameters of oranges, including maturity index, soluble solid content (expressed in degrees Brix), and firmness. A novel image-based descriptor, termed Citrus Color Index—Gray Level Co-occurrence Matrix Texture Features (CCI–GLCM-TF), was developed by integrating the Citrus Color Index (CCI) with texture features derived from the Gray Level Co-occurrence Matrix (GLCM). By combining contrast, correlation, energy, and homogeneity across multiscale regions of interest and applying geometric calibration to correct image acquisition distortions, the descriptor effectively captures both chromatic and structural information from RGB images. These features served as input to an Adaptive Neuro-Fuzzy Inference System (ANFIS), selected for its ability to model nonlinear relationships and gradual transitions in citrus ripening. The proposed ANFIS models achieved R-squared values greater than or equal to 0.81 and root mean square error values less than or equal to 1.1 across all quality parameters, confirming their predictive robustness. Notably, representative models (ANFIS 2, 4, 6, and 8) demonstrated superior performance, supporting the extension of this approach to full-surface exploration of citrus fruits. The results outperform methods relying solely on color features, underscoring the importance of combining spectral and textural descriptors. This work highlights the potential of the CCI–GLCM-TF descriptor, in conjunction with ANFIS, for accurate, real-time, and non-invasive assessment of citrus quality, with practical implications for automated classification, postharvest process optimization, and cost reduction in the citrus industry. Full article

Population ageing and the increase in life expectancy have heightened the demand for long-term care in residential facilities. In Spain, it is projected that by 2054 the functional dependency rate among those aged 65 and over will exceed 53.0%, posing significant challenges for person-centred care. This study aims to examine institutionalised older adults’ perceptions of care in relation to their functional dependency, and how these perceptions shape their dignity and participation in residential life. A qualitative study with a phenomenological approach was conducted in a residential facility located in the north-east of Andalusia, Spain, involving eight residents with varying degrees of autonomy and dependency. Data were collected through individual semi-structured interviews and analysed using Colaizzi’s phenomenological method. The findings revealed that, as dependency increases, care is perceived as more impersonal, generating feelings of diminished dignity and greater exclusion. In addition, limitations were observed in communication and participation in residential life. Respect for privacy and personal preferences was particularly relevant for women. The study concludes that the care received is conditioned by the degree of dependency and the resources available. It is recommended to enhance staff training, increase staffing levels, and promote the active participation of residents. Full article

Background/Objectives: Gestational diabetes mellitus (GDM) is characterized by a systemic inflammatory response and the expression of inflammatory factors in visceral adipose tissue (VAT). However, the association between these two inflammatory processes has not been fully elucidated. Therefore, this study aimed to (1) investigate whether whole blood counts, the neutrophil–lymphocyte ratio (NLR), the monocyte–lymphocyte ratio (MLR), serum adiponectin levels, and the mRNA expression of inflammatory genes (TLR2, TLR4, pro-inflammatory cytokines: IL-1β, IL-6, and TNF-α, anti-inflammatory cytokines: IL-1RA, IL-10, and adiponectin) in VAT are altered in women with GDM in comparison to pregnant women with normal glucose tolerance (NGT), and (2) determine the correlations between systemic and local VAT inflammation in all, GDM, and NGT women. Methods: Study of 50 GDM and 50 women with NGT with a cross-sectional design. Standard biochemical and hematological tests were conducted and relative mRNA expression in VAT was measured by RT-qPCR. Results: Women with GDM showed higher neutrophil, monocyte, NLR, MLR, and VAT TNF-α/IL-10 mRNA expression ratios while lymphocyte and eosinophil counts, serum adiponectin, and mRNA local VAT inflammatory markers such as TLR2, TLR4, IL-1β, IL-6, IL-1RA, and IL-10 were lower in women with GDM relative to women with NGT. Additionally, the circulating monocyte count were associated with TLR2 and TLR-4 VAT mRNA expression levels and eosinophils count were associated with IL-1β, IL-6, IL-10, and IL-1RA VAT expression levels in women with GDM. Conclusions: GDM is characterized by systemic inflammation, and some circulating immune cells, such as monocytes and eosinophils, are associated with the expression of inflammatory markers in VAT. Full article

The use of magnetic materials, such as ferrofluids, is of great importance in biomedical applications, and as a result, interest in studying their magneto-optical properties has grown significantly in recent years. Therefore, in this work, magnetic nanoparticles were synthesized with chitosan coating, leaving the product as a ferrofluid in aqueous solution. Structural, morphological, magnetic, and optical characterization was carried out obtaining a cubic structure centered on the faces, a spherical morphology with a size distribution of 10–14 nm according to TEM images and a magnetic saturation of 53 emu/g. In the optical properties, the effect of chitosan shell on the forbidden band was studied, showing a blue-shifting effect, due to reduction on the inner magnetic nanoparticles size. Full article

Background: Speech and Language Impairment (SLI) significantly affects children’s communication skills, limiting their social and academic development. Case Information: This single-case study evaluates the effects of a personalized intervention in a 9-year-old child diagnosed with SLI, integrating linguistic and cognitive strategies to remediate core deficits typically observed in children with SLI. Two main objectives were established: (1) to assess the child’s psycholinguistic competencies and cognitive processes and (2) to analyze the impact of the intervention on skills such as phonology, semantics, syntax, executive functions, and emotional well-being. The longitudinal and personalized design included pre- and post-intervention assessments conducted over two and a half years using tools such as the ITPA and Peabody Vocabulary Test. The intervention sessions were structured into linguistic and cognitive activities, with a frequency of two weekly language sessions and one cognitive functions session. Statistical analysis included ANOVA to evaluate significant changes. Conclusions: The results showed significant improvements in linguistic areas such as auditory comprehension (from 3–5 to 10 years) and verbal expression (from 5–10 to 9–6), as well as in cognitive aspects such as visuomotor sequential memory and visual comprehension, which exceeded the expected values for the child’s age. However, skills such as grammatical integration and auditory association did not show significant progress. This demonstrates that personalized and multidisciplinary interventions can considerably improve linguistic and cognitive abilities in children with SLI, although some areas require more specific approaches. The findings highlight implications for designing tailored intervention strategies, emphasizing the need for further research with larger samples and control groups to generalize the results. This case reaffirms the importance of comprehensive approaches in the treatment of SLI to maximize the academic and social development of affected children. Full article

While traditional ensemble methods have dominated tabular intrusion detection systems (IDSs), recent advances in foundation models present new opportunities for enhanced cybersecurity applications. This paper presents a comprehensive multi-modal evaluation of foundation models—specifically TabPFN (Tabular Prior-Data Fitted Network), TabICL (Tabular In-Context Learning), and large language models—against traditional machine learning approaches across three cybersecurity datasets: CIC-IDS2017, N-BaIoT, and CIC-UNSW. Our rigorous experimental framework addresses critical methodological challenges through model-appropriate evaluation protocols and comprehensive assessment across multiple data variants. Results demonstrate that foundation models achieve superior and more consistent performance compared with traditional approaches, with TabPFN and TabICL establishing new state-of-the-art results across all datasets. Most significantly, these models uniquely achieve non-zero recall across all classes, including rare threats like Heartbleed and Infiltration, while traditional ensemble methods—despite achieving >99% overall accuracy—completely fail on several minority classes. TabICL demonstrates particularly strong performance on CIC-IDS2017 (99.59% accuracy), while TabPFN maintains consistent performance across all datasets, suggesting robust generalization capabilities. Both foundation models achieve these results using only fractions of the available training data and requiring no hyperparameter tuning, representing a paradigm shift toward training-light, hyperparameter-free adaptive IDS architectures, where TabPFN requires no task-specific fitting and TabICL leverages efficient in-context adaptation without retraining. Cross-dataset validation reveals that foundation models maintain performance advantages across diverse threat landscapes, while traditional methods exhibit significant dataset-specific variations. These findings challenge the cybersecurity community’s reliance on tree-based ensembles and demonstrate that foundation models offer superior capabilities for next-generation intrusion detection systems in IoT environments. Full article