Search Results (9,768)

Respiratory disorders remain a major cause of morbidity and mortality in neonatal intensive care units, particularly among preterm infants. Advances in physiological monitoring, medical imaging, and electronic health records have enabled the growing application of artificial intelligence in neonatal respiratory care. This narrative review summarizes current applications and emerging directions of artificial intelligence in the diagnosis, monitoring, and management of neonatal respiratory disorders. Machine learning and deep learning approaches have demonstrated promising performance in respiratory distress syndrome, bronchopulmonary dysplasia, apnea of prematurity, ventilatory management, and severe respiratory complications. By integrating multimodal clinical, physiological, and imaging data, these methods support earlier detection of respiratory deterioration and improved clinical decision-making. However, challenges related to data quality, generalizability, interpretability, and limited prospective validation continue to constrain widespread clinical implementation, highlighting the need for careful integration into neonatal care workflows. Full article

This article presents an ontology-driven Digital Twin (DT) for hotel front-desk operations that fuses two real-time data streams: (i) physiological and activity signals from wrist-worn wearables assigned to staff, and (ii) 3D people-positioning and occupancy events captured by reception-area cameras using a proprietary implementation of Optical Camera Communication (OCC). Building on a previously proposed front-desk ontology, the semantic model is extended with positional events, zone semantics, and wearable-derived workload indices to estimate queue state, staff workload, and service demand in real time. A vendor-agnostic, property-based REST API specifies the DT interface in terms of observable properties, including authentication and authorization, idempotent ingestion, timestamp conventions, version negotiation, integrity protection for signed webhooks, rate limiting and backoff, pagination and filtering, and privacy-preserving identifiers, enabling any compliant backend to implement the specification. The proposed layered architecture connects ingestion, spatial reasoning, and decision services to dashboards and key performance indicators (KPIs). This article details the positioning pipeline (calibration, normalized 3D coordinates, zone mapping, and confidence handling), the wearable workload pipeline, and an evaluation protocol covering localization error, zone classification, queue-length estimation, and workload accuracy. The results indicate that a spatially aware, ontology-based DT can support more balanced staff allocation and improved guest experience while remaining technology-agnostic and privacy-conscious. Full article

The present work explores the effects of dental splints from a mechanical standpoint, aiming to provide a practical tool for the surgical decision-making process regarding splint cross-section dimensions. Our investigation centers on the anatomical structure of a pentamorphic dental arch encompassing central and lateral incisors and one canine on each side. Using parametric in silico models built up by means of an ad-hoc procedure, geometry, material properties, and boundary conditions are defined on a parametric anatomical model that can be tailored using RX-derived geometrical information. Two general cases have been considered, one with the splint and the other splintless, and a sensitivity analysis has been performed by varying the splint section height and thickness. The results show the diminishing mobility at the apex and basis of the diseased incisors, demonstrating the effectiveness of the periodontal treatment. Moreover, the stress due to physiological loads moves away from diseased teeth toward the healthy ones due to the splint effects, focusing on the splint–glue–canine contact zone and highlighting the crucial role played by the canine in fixing the entire dental structure. To establish a preliminary mechanical assessment of the dental structure’s safety and to confine its actual value within a mechanically reasonable range, a synthetic “traffic-light” indicator of stress-based failure risk is proposed. It is felt that the tool proposed in this study can help surgeons assess the pre-operative patient-specific mechanical effects of the splint treatment, driving the design and choice of periodontal splints. By linking splint geometry to mechanical safety via a stress-based indicator, the method supports the optimized design and selection of splints, improving treatment reliability while preserving comfort and clinical effectiveness. Full article

Hemostasis depends on the coordinated interaction between platelets, coagulation factors, endothelium, and shear forces. Current point-of-care (POC) assays evaluate isolated components of haemostasis or operate under nearly static conditions, limiting their ability to reproduce physiological thrombus formation. In this study, we performed the technical validation of Smart Clot, a fully automated, microfluidic POC platform that quantifies platelet aggregation, fibrin formation, and total thrombus growth under controlled arterial shear using unmodified whole blood. Recalcified citrated blood was perfused over collagen at $\dot{\gamma }$_w = 300 s⁻¹. Dual-channel epifluorescence microscopy acquired platelet and fibrin(ogen) signals at 1 frame per second. Integrated Density time-series were fitted with a five-parameter logistic model; first derivatives and their integrals yielded standardized pseudo-volumes for platelets, fibrin(ogen), and total thrombus. Sixty-two healthy donors established reference distributions; one-hundred-thirteen patients on antithrombotic therapy assessed pharmacodynamic sensitivity. Platelet-derived parameters were approximately normally distributed, whereas fibrin(ogen) and total thrombus values followed log-normal patterns. Anticoagulants and antiplatelet agents produced graded, mechanism-consistent inhibition of all thrombus components. Cardiopulmonary bypass samples showed profound but transient suppression of platelet and fibrin activity. Across activity ranges, multiple statistical assessments supported high analytical repeatability. Smart Clot provides rapid, reproducible, flow-aware quantification of platelet–fibrin dynamics, capturing pharmacological modulation and peri-operative impairment with high sensitivity. These results support its potential as a next-generation POC assay for physiological hemostasis assessment. Full article

Cauliflower (Brassica oleracea var. botrytis) curd formation is a highly complex developmental process governed by tightly coordinated genetic and physiological regulation. Here, we performed transcriptome sequencing of curd and peduncle tissues across multiple developmental stages, generating 171.52 Gb of high-quality data. Genes associated with photosynthesis and glucosinolate biosynthesis were strongly upregulated in the shoot apical meristem (SAM), highlighting substantial metabolic investment during the pre-initiation phase of curd morphogenesis. Key floral transition regulators, particularly AP2 and MADS-box transcription factors, were activated to drive the vegetative-to-reproductive switch and initiate curd primordia, ultimately giving rise to the arrested inflorescence architecture characteristic of cauliflower. Furthermore, hormone signaling pathways—including auxin (AUX), jasmonic acid (JA), and brassinosteroid (BR)—showed marked activation during SAM proliferation and peduncle elongation, underscoring their crucial roles in structural patterning. Collectively, our findings delineate an integrated regulatory network that links metabolic activity, hormone signaling, and developmental programs, providing novel molecular insights into curd formation and identifying potential breeding targets for the genetic improvement of Brassicaceae crops. Full article

Digital technologies that continuously quantify animal behavior, physiology, and production offer significant potential for the early identification of health and welfare disorders of dairy cows. In this study, a multimodal artificial intelligence (AI) framework is proposed for real-time health monitoring of dairy cows through the integration of physiological, behavioral, production, and thermal imaging data, targeting veterinarian-confirmed udder, leg, and hoof infections. Predictions are generated at the cow-day level by aggregating multimodal measurements collected during daily milking events. The dataset comprised 88 lactating cows, including veterinarian-confirmed udder, leg, and hoof infections grouped under a single ‘sick’ label. To prevent information leakage, model evaluation was performed using a cow-level data split, ensuring that data from the same animal did not appear in both training and testing sets. The system is designed to detect early deviations from normal health trajectories prior to the appearance of overt clinical symptoms. All measurements, with the exception of the intra-ruminal bolus sensor, were obtained non-invasively within a commercial dairy farm equipped with automated milking and monitoring infrastructure. A key novelty of this work is the simultaneous integration of data from three independent sources: an automated milking system, a thermal imaging camera, and an intra-ruminal bolus sensor. A hybrid deep learning architecture is introduced that combines the core components of established models, including U-Net, O-Net, and ResNet, to exploit their complementary strengths for the analysis of dairy cow health states. The proposed multimodal approach achieved an overall accuracy of 91.62% and an AUC of 0.94 and improved classification performance by up to 3% compared with single-modality models, demonstrating enhanced robustness and sensitivity to early-stage disease. Full article

Radish is a nutrient- and antioxidant-rich root vegetable whose growth is strongly affected by water availability, highlighting the need for strategies to enhance drought tolerance. Methyl jasmonate (MeJa) is a bioregulator involved in plant stress responses. This study evaluated the role of MeJa in alleviating water deficit effects in radish. Plants were maintained under well-watered conditions (80% water retention capacity) or subjected to total irrigation restriction from 15 to 30 days after sowing (DAS). Foliar applications of 100 µM MeJa or water were performed at 7, 14, and 21 DAS. Growth, gas exchange, chlorophyll fluorescence, photosynthetic pigments, relative water content, electrolyte leakage, and storage root quality were assessed. Water deficit reduced relative water content and increased electrolyte leakage, indicating oxidative damage, which impaired growth and gas exchange. MeJa application reduced electrolyte leakage but did not mitigate drought-induced reductions in growth or gas exchange. Notably, water deficit increased sugar, mineral, and antioxidant contents in roots, regardless of MeJa treatment. Overall, although MeJa modulated some stress-related physiological responses, enhancing antioxidant defenses, it was insufficient alone to improve drought tolerance in radish. Full article

Drought poses a major challenge for global agriculture, demanding strategies that improve crop resilience while safeguarding water and nutrient resources. Plant growth-promoting rhizobacteria (PGPR)-based biostimulants offer a sustainable approach to enhance resource-use efficiency under water-limited conditions. This study evaluated two commercial PGPR biostimulants applied to maize (Zea mays L.) and tomato (Solanum lycopersicum L.) seedlings grown under well-watered (80% field capacity) and water-stressed (40% field capacity) conditions. Both products improved plant growth and physiological performance, although responses were crop-specific. Inoculated tomato seedlings accumulated up to 35% more shoot biomass under optimal watering (1.6 g in non-inoculated seedlings compared with 2.5 g in inoculated seedlings), whereas maize maintained biomass production under drought, consistent with its higher intrinsic water-use efficiency, showing increases of approximately 50% (well-watered: 0.5 g versus 0.8 g; water-stressed: 0.3 g versus 0.7 g in non-inoculated and inoculated seedlings, respectively). Biostimulant application enhanced the acquisition and internal utilization of essential mineral resources, increasing leaf concentrations of (i) the macronutrients P (up to 300%), K (up to 70%), Mg (up to 220%), and Ca (up to 85%), and (ii) the micronutrients B (up to 400%), Fe (up to 260%), Mn (up to 240%), and Zn (up to 180%). Maximum nutrient increases were consistently observed in water-stressed maize seedlings inoculated with biostimulant 2. Antioxidant activities, particularly ascorbate peroxidase and catalase, increased by 20–40%, indicating more effective mitigation of oxidative stress. Principal component analysis revealed coordinated adjustments among growth, nutrient-use efficiency, and physiological traits in inoculated plants. Overall, PGPR-based biostimulants improved early drought tolerance and resource-use efficiency, supporting their potential as sustainable tools for climate-resilient agriculture. Field-scale studies remain necessary to confirm long-term agronomic benefits. Full article

Pancreatic cancer is characterized by an immunosuppressive tumor environment in which macrophages are recruited and reprogrammed to support tumor growth. Studying macrophage migration and polarization is crucial for understanding disease progression and identifying therapeutic targets. However, existing in vitro methods such as the transwell assay provide limited spatial resolution and do not allow visualization of cell movement or morphological changes. Here, we established and evaluated the Chamber Gap Assay, a modified two-compartment culture system that enables direct, time-resolved observation and quantification of macrophage migration toward pancreatic cancer cells as well as phenotypic alterations. Using murine and human macrophage–cancer cell models, we compared the performance of the Chamber Gap Assay with the transwell assay. We found that macrophage monocultures displayed substantial spontaneous migration in the transwell system, while cancer cells induced only modest additional macrophage recruitment. In contrast, the Chamber Gap Assay demonstrated clear and highly significant directional macrophage movement toward cancer cells, with distinct migration patterns and improved sensitivity for detecting group differences. The method also enabled visualization of cancer cell movement within the same system. Furthermore, CGA offers observations of morphological changes in immune cells under the influence of pancreatic cancer cells. Our findings indicate that the Chamber Gap Assay provides a robust and physiologically relevant method for studying tumor-induced immune cell recruitment and associated morphological changes. Full article

Cutaneous leishmaniasis (CL) is a neglected tropical disease for which current chemotherapeutic options are limited by systemic toxicity (such as hepato-nephrotoxicity, arrhythmia, nausea, vomiting) and difficult administration regimens. Pentamidine (PTM), although effective, exhibits severe dose-limiting adverse effects. Polymeric micelles based on Pluronic^® F127 (F127) offer an attractive strategy to improve PTM delivery by enhancing solubility, reducing cytotoxicity, and enabling controlled release. Here, we developed PTM-loaded F127 polymeric micelles and performed a multidisciplinary evaluation combining physicochemical characterization, in vitro biological assays, and gene expression profiling. Dynamic light scattering, UV–visible absorption, fluorescence spectroscopy, and NMR confirmed micelle formation, PTM–polymer interactions, and temperature-dependent assembly. PTM-loaded micelles exhibited biorelevant nanoscale dimensions and preserved stability under physiological conditions. Biological assays demonstrated that F127 micelles markedly reduced PTM cytotoxicity in RAW264.7 macrophages while maintaining potent antileishmanial activity against Leishmania major promastigotes. RT-qPCR analysis revealed modulation of key pathways involved in redox homeostasis, oxidative stress, calcium regulation, apoptosis-like responses, and drug resistance, suggesting that micellar encapsulation influences both PTM bioavailability and parasite stress responses. Overall, PTM-loaded F127 micelles significantly improved the therapeutic index of PTM in vitro. These findings support the potential of F127 polymeric micelles as a promising nanocarrier platform for safer and more effective CL therapy. Full article

Climate change is increasingly exposing sweet chestnut (Castanea sativa Mill.) to more frequent and prolonged drought events, which can compromise growth and nut production, particularly in Mediterranean environments. Understanding how trees respond physiologically to ecological and environmental constraints requires a detailed analysis of their architectures. The aim of this study was to investigate how the shoot vigour and leaf water status of mature chestnut trees vary with height within the canopy. Three mature chestnut trees with distinct crown architectures were selected in a traditional chestnut orchard in Central Italy; the differences in crown structure reflected individual tree development under comparable pruning practices. Morphological traits, leaf water status, and physiological parameters related to chlorophyll were measured directly within the canopy by professional tree climbers, allowing access to both lower and upper shoots during the growing season of 2020. One tree, called “Tree 1,” characterised by low bifurcation, with all epicormic shoot cluster (complexes) located on the two main branches and none on the main stem, showed partial vertical differences, mainly in water status and chlorophyll traits. “Tree 2”, characterised by high bifurcation and shoots running along the main stem, exhibited clear vertical gradients: lower-canopy shoots had larger leaf areas and more dry mass, higher relative water content, and better photosynthetic performance index e values than upper shoots. At the end, “Tree 3”, with the same architecture as Tree 1, displayed no consistent vertical trends. These findings indicate that individual tree architecture modulates hydraulic constraints and shoot vigour, even in hydraulically efficient epicormic branches. Although canopy access constraints limited the number of trees and measurements, this study—among the few to conduct in-canopy measurements on large, mature trees—provides valuable guidance for pruning and crown management, suggesting that lowering and simplifying the crown can enhance water-use efficiency, shoot vigour, and drought resilience in traditional and low-input chestnut orchards. Full article

Lactoferrin (Lf) occurs predominantly within milk, coexisting with measurable levels across different glandular products and body fluids. Lf exhibits variation in relative molecular mass, influenced by its biological source and glycosylation profile; nevertheless, it is a close to 80 kDa glycoprotein. Provided that its bioactive structure is preserved, Lf performs a spectrum of physiological roles, comprising antioxidant, antifungal, antiviral, antiapoptotic, and antimicrobial actions. To sustain its bioactivity after isolation and ensure its effectiveness in subsequent applications, optimal conditions must be established throughout the optimization protocol, since inadequate optimization of parameters such as pH, temperature, ion balance, and protease activity may lead to aggregation, denaturation, and deterioration in functional regions, including the iron-binding domains. This review offers a comprehensive framework that associates isolation methodologies with structural integrity, preservation of iron-binding domains, and antimicrobial performance. Ion-exchange, affinity-based, and membrane-based approaches are systematically evaluated from analytical and functional perspectives, thereby yielding a synthesis that facilitates procedure selection and optimization for Lf isolation. In addition, the objectives of analytical characterization techniques implemented following isolation and the broadening scope of biotechnological applications of Lf are outlined. Full article

Parkinson’s disease (PD) is characterized by alterations in movement dynamics that are difficult to quantify with conventional clinical assessment. This study proposes an integrated approach combining graph-based kinematic analysis with explainable machine learning to identify digital biomarkers of Parkinsonian motor impairment. Kinematic signals were acquired using Xsens inertial sensors from 51 patients with PD and 53 healthy controls. For each participant, subject-specific kinematic networks were constructed by modeling inter-segment similarities through Jensen–Shannon divergence, from which global and local graph-theoretical metrics were extracted. A machine learning pipeline incorporating voting feature selection, and XGBoost classification was evaluated using a nested cross-validation design. The model achieved robust performance (AUC = 0.87), and explainability analyses using SHAP identified a subset of 13 features capturing alterations in velocity, inter-segment connectivity, and network centrality. PD was characterized by increased positional variability, reduced distal limb velocity, and a redistribution of network centrality towards proximal body segments. These features were associated with clinical severity, confirming their physiological relevance. By integrating graph-theoretical modeling, explainable artificial intelligence, and machine learning methodology, this work provides a method of discovering quantitative biomarkers capturing alterations in motor coordination. These findings highlight the potential of ML and kinematic networks to support objective motor assessment in PD. Full article

Reliable vascular access remains a major clinical challenge for hemodialysis patients, as expanded polytetrafluoroethylene (PTFE) grafts exhibit poor patency and frequent complications driven by thrombosis and neointimal hyperplasia. Tissue-engineered vascular grafts offer a regenerative alternative but often lack the mechanical resilience required for high-flow arteriovenous (AV) environments. Here, we developed a reinforced, biofunctionalized coaxial electrospun graft comprising a poly(ε-caprolactone) mechanical core and a norbornene-functionalized poly(ethylene glycol) sheath incorporating pro-endothelialization cues. Circumferential PTFE rings were added to improve kink resistance. Grafts were implanted in a porcine AV configuration that recapitulates clinical hemodynamic conditions. Mechanical characterization included compliance, burst pressure, and kink resistance; host remodeling was assessed using histology, immunofluorescence, and multiphoton imaging at 4 weeks. Ring-reinforced electrospun grafts demonstrated a kink radius of 0.187 cm, compliance of 1.04 ± 0.29%/100 mmHg, and burst pressure of 1505 ± 565 mmHg, values all comparable to Gore-Tex PTFE and within industrial performance standards. In vivo, the electrospun grafts showed extensive host cell infiltration, collagen deposition, and formation of smooth muscle-like tissue, whereas PTFE controls remained largely acellular. Immunofluorescence confirmed intramural α-SMA⁺ and CD31⁺ cell populations, and multiphoton microscopy revealed significantly greater collagen and elastin content compared with PTFE (p < 0.05). Collectively, these findings demonstrate that the reinforced electrospun graft maintains mechanical integrity under physiological AV loading while supporting in situ endothelialization and extracellular matrix remodeling in a clinically relevant, large animal model. This work provides one of the first demonstrations of functional tissue regeneration within a fully synthetic, acellular scaffold in a porcine hemodialysis model and advances the translational development of durable, regenerative vascular access grafts that couple mechanical resilience with bioactive healing capacity. Full article

Background: Academic performance is related to cognitive functions and satisfied physiological needs such as proper sleep, a factor frequently overlooked by university students. Our aim was to investigate sleep-related variables, cognitive performance and stress level measured by heart rate variability among university students. Methods: A novel psychophysiological measurement system was used for data collection in which a screen-adapted questionnaire was used to collect data on sleep; gamified versions of standard psychological tests were used to assess cognitive performance, and ECG data were recorded by a wearable ECG sensor, all synchronized by a software. University students volunteered for anonymous testing that lasted approximately one hour. Results: Of the 107 students (mean age: 22.2 years, SD ± 2.22; 52% female), those who reported being well-rested achieved significantly higher overall cognitive performance (p = 0.024). Sleep duration did not correlate with cognitive performance but longer sleep duration was associated with feeling rested (rho = 0.326; p < 0.001). Cognitive performance showed significant association with two HRV parameters such as the Baevsky Stress Index (r = 0.195), higher values of which reflect higher autonomic stress load. Significant negative relation was found between cognitive performance and RMSSD (r = −0.195), another HRV parameter, higher values of which allude to higher parasympathetic activity (p = 0.050 for both). These findings suggest a link between mild arousal and performance. Conclusions: Being rested and lower autonomic stress load are positively correlated with cognitive performance. The novel psychophysiological measurement system integrating subjective and objective measurements of cognitive and physiological functions is feasible for assessing cognitive functions and stress levels in students. Full article