Search Results (176)

Accurate estimation of Body Carcass Fat (BCF) is essential for evaluating the physiological condition of ewes. Traditional assessment via Body Condition Score (BCS) through palpation is inaccurate and subjective. BCF can now be predicted more precisely using objective measurements. This study presents a comparative analysis of eight machine learning (ML) models for predicting BCF in Coopworth ewes, using weight and RGB-image-based body measurements. Four non-linear regression methods and four neural network architectures were evaluated using a dataset of 74 ewes with 13 independent variables. The dataset was partitioned into training (52 ewes), validation (11 ewes), and testing (11 ewes) sets. The Gradient Boosting Regression achieved the highest predictive accuracy with an R² value of 0.9434 using body weight and width, followed by Ensemble Neural Network (R² = 0.9371) using body weight. The findings demonstrate the effectiveness of the Gradient Boosting Regression, Ensemble Neural Network and Random Forest tree-based approaches for morphometric prediction tasks in biological applications. BCF values obtained from image analysis were validated against those derived from computerized tomography (CT), considered the gold standard. These findings highlight the potential of image-guided, ML-driven models for objective, non-invasive, cost-effective assessment of ewe body composition in modern livestock systems. Full article

The lemur tree frog (Agalychnis lemur), a critically endangered species, can benefit from ex situ conservation programs; however, managing amphibians under human care presents challenges, including the provision of appropriate nutrition. House crickets (Acheta domesticus), a common feeder insect, have an inverse calcium to phosphorus ratio (Ca:P; 0.15:1) and low calcium content (<0.3%). While gut-loading crickets with an 8% calcium diet can improve their calcium concentrations, no study has assessed the effects of dietary calcium on bone development in Agalychnis spp. Moreover, no study has examined how diet impacts the gut–skin axis and skin microbiome of these frogs. This study examined how crickets gut-loaded with either a 1.3% or 8% calcium diet affected lemur tree frog bone density and skin microbiome. We hypothesized that frogs consuming the 8% calcium diet would exhibit significantly higher Hounsfield units (HU; bone density) over time, as measured by micro-computed tomography (mCT), and that dietary calcium concentration would have no effect on skin bacterial and fungi microbiomes. Eleven juvenile lemur tree frogs underwent mCT scans at baseline and 90 and 180 days. Total body volume of interest analysis showed a significant increase in HU in the 8% calcium group compared to the 1.3% group (F = 9.9, p = 0.01). There was no significant difference noted in the alpha or beta diversities for the bacterial and fungal microbiomes between dietary groups. This study provides the first evidence of dietary calcium’s impact on bone density in lemur tree frogs, offering valuable insights for improving ex situ management of this species. Full article

Purpose: To explore the correlation between radiologic patterns on high-resolution computed tomography (HRCT) and circulating biomarkers of inflammation and endothelial activation in patients with COVID-19 pneumonia, with the aim of identifying imaging-biomarker phenotypes that may offer insights for clinical stratification. Materials and Methods: This prospective single-center study included 84 consecutive patients hospitalized with PCR-confirmed SARS-CoV-2 infection and respiratory failure. All underwent baseline HRCT, along with parallel biohumoral profiling, including inflammatory (IL-1Ra, IL-6, IL-10) and endothelial (Angiopoietin-2, sVCAM-1, sE-Selectin) biomarkers. HRCT scans were reviewed for parenchymal and vascular abnormalities (vascular tree-in-bud [TIB], vascular enlargement pattern [VEP]). Semi-quantitative scores were assigned for parenchymal (PS) and vascular (VS) involvement. Results: Patients with higher PS had significantly prolonged hospital stay (35 vs. 17 days; p = 0.014), increased ICU admission rates (68.8% vs. 21.4%; p = 0.003), and elevated serum levels of IL-1Ra, IL-6, and IL-10 (p < 0.05). At multivariable analysis, PS remained independently associated with ICU admission after adjustment for age, inflammatory burden, and comorbidities (p = 0.014). A high VS was associated with significantly increased Angiopoietin-2 levels (p = 0.036), although it did not directly correlate with ICU admission or mortality. A significant positive correlation was observed between PS and VS (r =0.392; p < 0.001). Conclusions: in this study, HRCT-based parenchymal and vascular patterns appear significantly correlated with biological processes occurring in severe COVID-19 pneumonia. These observations, although preliminary, may offer a conceptual basis for future studies exploring radiologic and biomarker-based stratification in severe respiratory infections. Full article

Background: Tracheobronchopathia osteochondroplastica (TO) is a rare benign disorder characterized by submucosal cartilaginous and osseous nodules of the tracheobronchial tree, typically sparing the posterior membranous wall. Involvement of the vocal cords is exceedingly rare and may result in critical airway obstruction. The underlying genetic and molecular mechanisms of TO remain largely unexplored. Case presentation: We report a rare case of TO extending from the vocal cords to the bronchi in a 76-year-old man who initially presented with pneumonia and later developed acute respiratory failure due to severe airway narrowing, necessitating emergency tracheostomy. Bronchoscopy and computed tomography revealed diffuse calcified nodules involving the anterior and lateral airway walls, including the subglottic region. Histopathology demonstrated chronic inflammatory cell infiltration with squamous metaplasia. To explore the molecular basis of this condition, whole-genome sequencing (WGS) was performed using peripheral blood samples—the first such application in TO. WGS identified 766 germline mutations (including 27 high-impact variants) and 66 structural variations. Candidate genes were implicated in coagulation and inflammation (KNG1), arachidonic acid metabolism and extracellular matrix remodeling (PLA2G4D), ciliary dysfunction and mineralization (TMEM67), vascular calcification (CDKN2B-AS1), smooth muscle function (MYLK4), abnormal calcification (TRPV2, SPRY2, BAZ1B), fibrotic signaling (AHNAK2), and mucosal barrier integrity (MUC12/MUC19). Notably, despite systemic germline mutations, calcification was restricted to the airway. Conclusions: This case highlights that TO with vocal cord involvement can progress beyond a benign course to cause life-threatening airway obstruction. Integrating clinical, histological, and genomic findings, we propose a novel pathophysiological model in which systemic genetic susceptibility interacts with local immune cell infiltration and fibroblast-driven extracellular matrix remodeling, resulting in airway-restricted dystrophic calcification. This first genomic characterization of TO provides new insights into its pathogenesis and suggests that multi-omics approaches may enable future precision medicine strategies for this rare airway disease. Full article

Background/Objectives: Accurate knowledge of tracheobronchial anatomy is essential for safe airway management, particularly during one-lung ventilation using double-lumen tubes (DLTs). However, population-specific morphometric data in Asian adults remain limited. We aimed to establish a comprehensive morphometric profile of the tracheobronchial tree in Korean adults using 2D and 3D computed tomography (CT), and evaluate the clinical implications for DLT sizing and right upper lobe (RUL) alignment. Methods: This retrospective observational study included 398 adults who underwent preoperative chest CT. Measurements included tracheal dimensions, bronchial lengths, bronchial diameters, and anteroposterior angle of the RUL orifice. Height tertiles and sex-stratified linear regression analyses were performed to evaluate height–bronchial diameter relationships. Results: Bronchial dimensions were larger in men; however, height was more closely related to bronchial diameter in women. In women, each 1 cm increase in height corresponded to a 0.071 mm increase in left and a 0.077 mm increase in right bronchial transverse diameter (p < 0.001 for both). The RUL orifice showed posterior deviation of 15.5 ± 12.2° in men and 9.9 ± 11.4° in women, with height and weight being independent but weak predictors (R² = 0.05). Bronchial diameter measurements showed consistent differences between 2D and 3D CT, with 2D images generally overestimating transverse diameters. Conclusions: The present analysis provides population-specific reference values for Korean adults. Our findings support the use of 2D CT as a practical tool for estimating bronchial dimensions and guiding DLT selection, and may serve as foundation for future airway devices tailored to Asian populations. Full article

The stem–branch junction in trees demonstrates exceptional structural design. This study examined two key features of the branch junction in common ash (Fraxinus excelsior L.) wood: the interlocked area (ILA) formed above a knot and the spatial arrangement of fibers in the junction. Bio-inspired by the microstructural features revealed by micro-computed tomography imaging, we developed 3D-printed models and compared their mechanical performance to standard symmetrical T-joints. We evaluated the models using mechanical tests and finite element modeling (FEM). Asymmetrical 3D-printed joints mimicking vessel and fiber distribution in the stem–branch junction were 2% stiffer in the elastic region than symmetrical joints and showed, on average, 10% lower deflection at failure. While the ILA had minimal effect on elastic stiffness, measured surface strain analysis indicated that it positively influenced the redistribution of shear strain in the junctions. Thanks to the bio-inspired design, the joints were stiffer and can be utilized in multiple design configurations while maintaining the same underlying principle. Full article

Secular trees have an important contribution to today’s communities, not only due to cultural or historical reasons but also to recreational aspects. Management of such species can be done after a thorough analysis is done related to their health status. In most cases, a visual inspection to determine the health status can lead to unsatisfactory results. Modern technology, such as computer tomography, has results that are accurate and valid. A total of 17 secular oak trees (Quercus robur) were sampled and analyzed with Arbotom 2D (Arbotom 2D, Rinn Tech, Heidelberg, Germany) by using sensors on the tree trunks. Besides this, it is imperative to compare the results in the field with the view of the community related to their local symbol. Results revealed severe internal decay (75%–80% damaged wood) in eight oaks, while in the core of the trunk (10%–50% damaged wood), it was seen in seven oaks. Only two oaks have good health status. Survey results indicated the oaks as moderate healthy; only 18.8% respondents from the community consider the oaks unhealthy or in visible decline. This can lead to serious injuries to bystanders. The results have demonstrated a great link between technical and social research so decision-making stakeholders can apply a tailored management for their area. Full article

Background/Objectives: The breast is a highly radiosensitive organ that is directly exposed to ionizing radiation during chest computed tomography (CT) examinations. Excessive radiation exposure increases the risk of radiation-induced malignancies, highlighting the importance of accurate and patient-specific dose estimation. This study aims to estimate the effective radiation dose absorbed by the breast during chest CT examinations using a machine learning (ML)-based personalized prediction approach. Methods: In this retrospective study, a total of 653 female patients who underwent both mammography and chest CT between 2020 and 2024 were included. A structured database was created incorporating demographic and anatomical parameters, including body weight, height, body mass index (BMI), and breast thickness (mm) obtained from mammography, along with dose length product (DLP) values from chest CT scans. Five regression-based ML algorithms—CatBoost, Gradient Boosting, Extra Trees, AdaBoost, and Random Forest—were implemented to predict breast radiation dose. Model performance was evaluated using Mean Squared Error (MSE), Mean Absolute Error (MAE), Mean Absolute Percentage Error (MAPE), and the Coefficient of Determination (R²). Results: Among the evaluated models, the CatBoost algorithm optimized with Particle Swarm Optimization (CatBoostPSO) achieved the best overall predictive performance, yielding the lowest MSE (0.3795), MAE (0.3846), and MAPE (4.37%), along with the highest R² value (0.9875). CatBoost and Gradient Boosting models demonstrated predictions most closely aligned with ground truth values, indicating that ensemble-based and dynamically optimized models are particularly effective for breast dose estimation. Conclusions: The proposed machine learning framework enables rapid, accurate, and clinically applicable estimation of breast radiation dose during chest CT examinations. This patient-specific approach has strong potential to support personalized radiation dose monitoring and optimization strategies, contributing to improved radiation safety in clinical practice. Full article

Within the current administrative boundaries of the city of Lublin, fragments of roadside tree avenues of various historical origins and periods of establishment have been preserved, including former tree-lined roads leading to rural and suburban residences from the 18th and 19th centuries. This avenue once led to the manor in Konstantynów and now serves as the main road through the campus of the John Paul II Catholic University of Lublin (Katolicki Uniwersytet Lubelski—KUL). As one of the last surviving elements of the former rural landscape, the Konstantynów avenue represents a symbolic link between past and future. The research combines acoustic tomography and chlorophyll fluorescence analysis, providing a precise and non-invasive evaluation of the internal structure and physiological performance of 34 small-leaved linden trees (Tilia cordata Mill.). This methodological approach allows for early detection of stress symptoms and structural degradation, offering a significant advancement over traditional visual assessments. The study area is an intensively used urban campus, where extensive surface sealing beneath tree canopies restricts rooting space. The degree of surface sealing (paving) directly beneath the tree canopies was also measured. Based on the statistical analysis, a weak a non-significant weak negative correlation (r = −0.117) was found between the proportion of sealed surfaces within the Tree Protection Zone (TPZ) and the Fv/Fm vitality index, indicating that higher levels of surface sealing may reduce tree vitality; however, this relationship was not statistically significant (p = 0.518). The study provides an evidence-based framework for conserving historic trees by integrating advanced diagnostic tools and quantifying environmental stress factors. It emphasizes the importance of improving rooting conditions, integrating heritage trees into urban planning strategies, and developing adaptive management practices to increase their resilience. The findings offer a model for developing innovative conservation strategies, applicable to historic green infrastructure across Europe and beyond. Full article

This study explores the health status of veteran Zelkova serrata trees (average age 300 years) in the Pohang region in the context of long-term climatic trends and local environmental variability. Eleven nationally designated veteran trees were monitored using physiological indicators Soil Plant Analysis Development (SPAD) values and live crown ratio (LCR), internal structural assessment (sonic tomography-derived decay ratio), and environmental parameters including meteorological records and Landsat-derived Land Surface Temperature (LST) data from 2000 to 2025. While recent years showed localized heat-extreme events, most sites displayed spatially heterogeneous yet gradually increasing LST trends, with 2024 recording the highest values at more than half the locations. Tree vitality differences were more strongly associated with site specific microclimatic conditions than with uniform long-term climate shifts: trees in cooler or less urbanized zones showed higher SPAD values and lower decay levels, whereas those in warmer, edge-influenced sites exhibited signs of physiological stress. The results indicate that rising summer surface temperature—and their interaction with atmospheric drying—intensify water-stress impacts, but the actual tree responses are modulated by local land-cover and soil stability contexts. These findings underscore the need for integrated, multi-scale assessment of veteran tree health and suggest that conservation practices should incorporate microclimate-based intervention strategies. Full article

Background/Objectives: Blood vessel tortuosity can complicate endovascular procedures such as endovascular thrombectomy in acute ischemic stroke. This study aimed to assess the morphometric characteristics of carotid arteries and investigate the association between the tortuosity of the carotid arteries and the technical aspects of endovascular thrombectomy, patient demographics and clinical characteristics, and treatment outcome. Methods: This retrospective study included 84 patients with ischemic stroke treated by endovascular thrombectomy at the newly established thrombectomy-capable stroke center. The following data were collected from prethrombectomy computed tomography angiography: aortic arch type, type of carotid artery tortuosity, and tortuosity index (TI). The technical aspects of the procedure, as well as patient demographics, were collected from the radiological information system. Results: Time from arterial puncture to the first pass was significantly shorter in patients with a nontortuous carotid artery compared to a tortuous one (p = 0.006). There were no significant differences in the number of passes, total duration of the procedure, and the difference in National Institutes of Health Stroke Scale (NIHSS) score before and after the procedure regarding the form of tortuosity. Patients with hypertension had significantly higher tortuosity index values compared to those without hypertension (p = 0.008), and patients with a nontortuous carotid tree were significantly younger compared to those with all forms of tortuosity (p = 0.003). Conclusions: The majority of patients had tortuous carotid arteries, which were associated with older age and hypertension. A high index of tortuosity was associated with a longer time from arterial puncture to the first pass, but not to the treatment outcome. Preprocedural recognition of carotid artery tortuosity may aid in endovascular thrombectomy procedural planning. Full article

Background: Differentiating Parkinson’s disease (PD) from essential tremor (ET) is often challenging, especially in early or atypical cases. Dopamine transporter (DAT) single-photon emission computed tomography (SPECT) with ¹²³I-Ioflupane supports diagnosis, and semi-quantitative tools such as DaTQUANT^® and BasGanV2™ provide objective measures. This study compared their diagnostic performance when integrated with supervised machine learning. Methods: We retrospectively analysed ¹²³I-Ioflupane SPECT scans from 169 patients (133 PD, 36 ET). Semi-quantitative analysis was performed using DaTQUANT^® v2.0 and BasGanV2™ v.2. Classification tree (ClT), k-nearest neighbour (k-NN), and support vector machine (SVM) models were trained and validated with stratified shuffle split (250 iterations). Diagnostic accuracy was compared between the two software packages. Results: All classifiers reliably distinguished PD from ET. DaTQUANT^® consistently achieved higher accuracy than BasGanV2™: 93.8%, 93.2%, and 94.5% for ClT, k-NN, and SVM, respectively, versus 90.9%, 91.7%, and 91.9% for BasGanV2™ (p < 0.001). Sensitivity and specificity were also consistently higher for DaTQUANT^® than BasGanV2. Class imbalance (PD > ET) was addressed using Synthetic Minority Over-sampling Technique (SMOTE). Conclusions: Machine learning analysis of ¹²³I-Ioflupane SPECT enhances differentiation between PD and ET. DaTQUANT^® outperformed BasGanV2™, suggesting greater suitability for AI-driven decision support. These findings support the integration of semi-quantitative and AI-based approaches into clinical workflows and highlight the need for harmonised methodologies in movement disorder imaging. Full article

The Republic of Korea, with 64% forest coverage, is increasingly vulnerable to large-scale wildfires. This study employed electrical resistance tomography (ERT) to diagnose internal damage in Pinus densiflora trees following a surface fire in spring 2023. Of the 30 monitored trees, 5 died in 2023 and 6 more had died by 2024. Dead trees showed a 41% higher Bark Scorch Index (BSI) and a 10%–15% lower DBH and circumference than survivors. From July, ERT detected significant increases in high- (ERT_R) and medium-resistance (ERT_Y) areas, while low-resistance (ERT_B) regions declined. By September, ERT_R and ERT_Y were 2.2 and 1.9 times higher in dead trees. Maximum resistivity (Rs_max) rose 6.1-fold to 3724 Ωm. One year post-fire, healthy areas in dead trees dropped below 18%. These findings indicate that internal defects develop gradually and accelerate in summer and winter, correlating with thermal and freeze–thaw stress. Early diagnosis within two months post-fire was unreliable, while post-summer assessments better distinguished trees at mortality risk. This study demonstrates ERT’s utility as a non-destructive tool for tracking post-fire damage and guiding forest restoration under increasing wildfire threats. Full article

This study investigated the effect of the number of sensors (8, 12, 16, and 20) on the measurement results of stress wave velocity in two-dimensional acoustic tomography of Hoop pine (Araucaria cunninghamii Sweet) trees and evaluated the method’s accuracy and operational efficiency in tree health diagnostics. Tests were conducted on five sample trees, two of which were confirmed to have internal damage using the drilling resistance method. The results showed that increasing the number of sensors improved image resolution and information completeness. However, differences in the average stress wave velocities among sensor configurations were not statistically significant (p ≥ 0.05), indicating limited overall velocity variation. In healthy trees, stress wave velocities measured with different sensor quantities (e.g., eight vs. twenty) exhibited weak linear correlations (R² = 0.06–0.58), reflecting a relatively uniform internal structure. In contrast, damaged trees showed strong consistency in velocity results (R² = 0.82–0.91, p < 0.01), with both minimum and average velocities being significantly lower than those in healthy trees. These findings demonstrate that acoustic tomography can effectively identify internal tree defects. Notably, even with only eight sensors, decay and cavities can still be accurately detected, which significantly enhances field inspection efficiency and reduces costs, thereby showing strong potential for practical applications. Full article

Recent advances in artificial intelligence (AI) have transformed ophthalmic diagnostics, particularly for retinal diseases. In this prospective, non-randomized study, we evaluated the performance of an AI-based software system against conventional clinical assessment—both quantitative and qualitative—of optical coherence tomography (OCT) images for diagnosing diabetic macular edema (DME). A total of 700 OCT exams were analyzed across 26 features, including demographic data (age, sex), eye laterality, visual acuity, and 21 quantitative OCT parameters (Macula Map A X-Y). We tested two classification scenarios: binary (DME presence vs. absence) and multiclass (six distinct DME phenotypes). To streamline feature selection, we applied paraconsistent feature engineering (PFE), isolating the most diagnostically relevant variables. We then compared the diagnostic accuracies of logistic regression, support vector machines (SVM), K-nearest neighbors (KNN), and decision tree models. In the binary classification using all features, SVM and KNN achieved 92% accuracy, while logistic regression reached 91%. When restricted to the four PFE-selected features, accuracy modestly declined to 84% for both logistic regression and SVM. These findings underscore the potential of AI—and particularly PFE—as an efficient, accurate aid for DME screening and diagnosis. Full article