Search Results (1,224)

This study investigates water-based gel and gel-like cleaning treatments on Superficie 553, an oil painting on canvas by Giuseppe Capogrossi, using portable NMR to assess their impact. The objective was to evaluate the effects of four cleaning systems composed of a buffer solution released in free form and combined with xanthan gum, a cross-linked silicone polymer gel, and an agar gel matrix. Two distinct NMR experiments were conducted. The first involved the acquisition of ¹H depth profiles to detect the distribution of the cleaning solution within the painted layer and the thickness variations resulting from cleaning procedures. The second employed the acquisition of relaxation times, facilitating the investigation of molecular mobility within the organic components of the paint layer. NMR results indicated that the agar gel system caused negligible structural changes, whereas the silicone gel induced rigidification, and the other systems permanently increased molecular mobility. These measurements provided insights into alterations in the dynamic behavior of the polymerized oil. A key strength of this investigation lies in the direct application of diagnostic methods on Superficie 553, made possible by the non-invasive nature and portability of the NMR-MOUSE system. Additionally, portable FTIR was used to detect residues and obtain chemical information, confirming that the silicone gel left detectable residues and identifying the agar gel as the most conservative cleaning method. This enabled in situ analysis of the original artwork without sampling or relocation—a crucial advantage given the difficulty of replicating the complex physicochemical conditions of historical paint surfaces under laboratory constraints. Such real-time, on-site monitoring ensured an authentic evaluation of the treatment effects, preserving the integrity of the artwork throughout the conservation process. Full article

Background: Vitreoretinal lymphoma (VRL) often presents with features resembling uveitis and is commonly associated with central nervous system lymphoma (CNSL). Intravitreal methotrexate (IVMTX) is widely used as local therapy; however, objective markers for treatment response and prognosis remain limited. This study investigated choroidal structural changes after IVMTX via enhanced depth imaging optical coherence tomography (EDI-OCT) and explored prognostic indicators for subsequent CNSL development. Methods: This retrospective study included 18 patients (27 eyes) with VRL treated with IVMTX at Tokushima University Hospital between 2006 and 2021. EDI-OCT was conducted at baseline and at 1 and 3 months after IVMTX. Choroidal thickness and luminal and stromal areas were quantified through image binarization. The stromal/choroidal area (S/C) ratio and its association with CNSL onset were statistically analyzed. Results: The mean number of IVMTX injections administered over 3 months was 5.9 ± 1.3. Foveal retinal thickness did not significantly change, whereas foveal choroidal thickness significantly decreased from 275.8 ± 15.8 µm at baseline to 257.5 ± 14.7 µm at 1 month (p < 0.01). Total choroidal and stromal areas, particularly in the outer choroidal layer, were significantly decreased after IVMTX (p < 0.0001), whereas the luminal area in the inner layer modestly reduced (p < 0.05). The S/C ratio significantly declined at 1 month post-treatment (p < 0.001). Patients who developed CNSL within 2 years of VRL onset demonstrated higher baseline S/C ratios (p < 0.05). Conclusions: IVMTX induces measurable reductions in choroidal areas and stromal proportion, indicating decreased inflammatory infiltration. The baseline S/C ratio observed on EDI-OCT is a potential noninvasive biomarker of VRL activity and a prognostic indicator for early CNSL development. Full article

Objective: Prolongation of the QTc interval (QTc) is a known risk factor for ventricular arrhythmias and sudden cardiac death (SCD). Although ankylosing spondylitis (AS) is associated with systemic inflammation and metabolic alterations, data on the relationship between noninvasive fibrosis markers and QTc are limited. This study aimed to investigate the association between the FIB-4 index and QTc in patients with AS. Methods: A total of 82 consecutive patients with AS were enrolled in the study. Demographic characteristics, comorbidities, laboratory parameters, and medication use were also recorded. The FIB-4 index was calculated for each patient in the study. Surface 12-lead electrocardiograms were obtained, and the QTc was measured. Correlation analyses and multivariable linear regression models were used to identify the independent predictors of QTc. Results: The mean age of the study population was 42.4 ± 11.7 years, and 57.3% of the patients were men. Correlation analysis revealed significant associations between QTc and age, sex, the FIB-4 index, body mass index (BMI), hypertension, hyperlipidemia, and cardiovascular medication use, whereas hemoglobin and estimated glomerular filtration rate (eGFR) were negatively correlated with QTc. In the multivariable analysis, only sex (β = −0.306, p = 0.001) and the FIB-4 index (β = 0.379, p < 0.001) remained independently associated with QTc. Conclusion: Our findings demonstrate that the FIB-4 index is independently associated with the QTc in patients with AS. These results suggest that noninvasive fibrosis markers may provide additional insights into cardiovascular risk stratification in this population. Full article

This study aimed to assess cytokine levels in blood plasma and serum, and saliva of juvenile pigs in response to acute systemic inflammation. The objectives were to: (1) validate an analytical method for quantifying cytokines in serum; (2) assess the reliability of serum compared to plasma for cytokine quantification; and (3) explore the potential of saliva as a non-invasive alternative for cytokine measurement. Changes in 13 cytokines (IFN-γ, TNF-α, IL-1α, IL-1β, IL-1ra, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12, IL-18 and GM-CSF) were analyzed in serum and saliva samples collected over a 72 h period following lipopolysaccharide (LPS) infusion to induce an acute inflammatory response in 10 juvenile pigs (~28 kg BW). EDTA plasma was collected over the same time period, and a subset of four cytokines (IL-1β, IL-6, IL-10 and IFN-γ) was analyzed to assess correlations with serum concentrations. A strong positive correlation was observed between serum and EDTA plasma levels of IL-1β, IL-6, IL-10 and IFN-γ (r = 0.91–1.00, p < 0.001), indicating that both serum and EDTA plasma can be used to obtain reliable measurements of cytokine concentrations in blood of juvenile pigs. Among the 13 analyzed cytokines in serum, TNF-α and IL-6 appeared as the most reliable cytokines during acute inflammation, peaking at 1 h and between 2 and 3 h post LPS infusion, respectively. In general, saliva did not correlate with serum for most cytokines, suggesting limited application of such a non-invasive matrix for systemic cytokine monitoring. However, IL-1α was detected at higher concentrations in saliva than in serum, suggesting that saliva may be useful for monitoring specific cytokines under certain inflammatory conditions. Further research is needed to clarify the origin and physiological role of salivary cytokines following LPS stimulation. Serum and plasma were suitable for cytokine analysis; however, serum may offer practical advantages by facilitating blood sample handling. Saliva may be useful for monitoring specific cytokines under certain inflammatory conditions. Full article

Land consolidation requires reliable and objective land valuation to ensure transparency and fairness in the reallocation process. This study introduces a data-driven method for assessing agricultural site productivity based on vegetation indices derived from multispectral imagery, supported by Sentinel satellite data and validated using handheld chlorophyll meter measurements. Site productivity, defined as the land’s ability to generate yield and biological value, is determined by natural and environmental factors that directly influence economic worth. Vegetation indices (NDVI, SAVI) obtained from UAV imagery showed a strong correlation with chlorophyll content, confirming the reliability of this non-invasive assessment. The analysis, conducted in Poland and Slovakia, demonstrated the method’s applicability under two different land consolidation systems: a market-based model in Poland and an ecologically oriented approach in Slovakia. The proposed framework proved easy to implement and provided consistent results even without the use of ground control points. By reducing fieldwork time and costs while improving valuation accuracy, this method enhances the objectivity and transparency of land consolidation procedures. The findings confirm the potential of vegetation indices to support data-driven and environmentally informed land valuation across diverse consolidation contexts. Full article

This work presents a compact refractometric system based on In-Line Digital Holography (ILDH) for the non-invasive characterization of transparent media, encompassing both liquids and high-refractive-index optical glasses. The core of the system is a cost-effective, lensless setup in which a 532 nm laser source and a microscope objective generate a divergent spherical wavefront that illuminates a 10 μm aluminum particle. The resulting diffraction pattern, modulated by samples in the optical path, is recorded by a CMOS sensor. The refractive index of the sample is determined by numerically locating the axial position of the particle-reconstructed image, which directly corresponds to the optical path difference introduced by the test medium. The optimal reconstruction plane is objectively located using an autofocus algorithm based on the Kurtosis metric, which identifies the sharpest image. The system successfully characterizes media across a broad refractive index range from 1.33 to 1.78, yielding linear calibration curves for both liquid and solid samples. The instrument achieves an axial reconstruction resolution of 30 μm and a refractive index precision of ±0.01 RIU. This ILDH approach offers a highly portable, cost-effective, and non-contact solution for refractive index measurement, demonstrating significant potential for industrial quality control and high-throughput point-of-care applications. Full article

Atrial fibrillation (AF) is the most prevalent sustained arrhythmia worldwide and is now increasingly regarded as a disease of chronic inflammation and progressive atrial fibrosis. Understanding of molecular mechanisms that mediate the linkage between systemic metabolic dysregulation, inflammation, and structural atrial changes is crucial for informing risk stratification and targeting of prevention strategies. This review provides evidence from 105 studies focusing on the contributions of transforming growth factor-β1 (TGF-β1), tumor necrosis factor-a (TNF-α), interleukin-6 (IL-6), galectin-3, and galectin-1 to cardiac fibrogenesis, atrial fibrosis, and AF pathogenesis. We also link metabolic syndrome to these biomarkers and to atrial remodeling, as well as echocardiographic correlates of fibrosis. TGF-β1 is established as the central profibrotic cytokine and promotes Smad-based fibroblast activation, collagen accumulation, and structural atrial remodeling. Its role is highly potentiated by thrombospondin-1 by turning latent TGF-β1 into its potent form. TNF-α and IL-6 also play an integral role in the inflammatory fibrotic continuum by activating NF-κB and STAT3 signaling, promoting fibroblast proliferation, electrical uncoupling, and extracellular matrix accumulation. Galectin-3 is a potent profibrotic mediator that promotes TGF-β signaling and is a risk factor for negative outcomes, whereas Gal-1 seems to regulate inflammation resolution and may exert context-dependent protective or maladaptive roles. Metabolic syndrome is strongly associated with excessive levels of these biomarkers, chronic low-grade inflammation, oxidative stress, and ventricular and atrial fibrosis. Chronic clinical findings show that metabolic syndrome (MetS) increases AF risk, exacerbates atrial dilatation, and is associated with worse postoperative outcomes. Echocardiographic data are connected to circulating biomarkers and are non-invasive for evaluating atrial remodeling. The evidence to date supports that atrial fibrosis should be considered an end point of systemic inflammation, metabolic dysfunction, and activation of profibrotic molecular pathways. Metabolic syndrome, due to its chronic low-grade inflammatory environment and prolonged levels of metabolic stress, manifests as an important upstream factor of fibrotic remodeling, which continuously promotes the release of cytokines, oxidative stress, and fibroblast activation. Circulating fibrotic biomarkers, in comparison with metabolic syndrome, serve separate yet interdependent pathways that help orchestrate atrial structural remodeling through the simultaneous process but can also provide a long-term indirect measure of ongoing profibrotic activity. The integration of these biomarkers with superior atrial imaging enables a broader understanding of the fibrotic substrate of atrial fibrillation. This combined molecular imaging approach can facilitate risk stratification, refine therapeutic decisions, and facilitate early identification of higher-risk metabolic phenotypes, thus potentially facilitating directed antifibrotic and anti-inflammatory therapy in atrial fibrillation. Full article

Three-phase induction motors (TIMs) are widely used in industrial applications, with bearings and rotors representing the most failure-prone components. Detecting incipient damage in these elements is particularly challenging. The associated signatures are weak and highly sensitive to variations, and their identification typically demands sophisticated filters, deep learning models, or high-cost sensors. In this context, the main goal of this work is to propose a new algorithm that reduces the dependence on such complex techniques while still enabling reliable detection of realistic faults using low-cost sensors. Therefore, the proposed Discriminative Band Energy Analysis (DBEA) algorithm operates on vibration signals acquired by low-cost accelerometers. The DBEA operates as a low-complexity filtering stage that is inherently robust to noise and variations in operating conditions, thereby enhancing discrimination among fault classes, without requiring neural networks or deep learning techniques. Moreover, the interaction of concurrent faults generates distinctive amplitude-modulated patterns in the vibration signal, making the AM demodulation-based algorithm particularly effective at separating overlapping fault signatures. The method was evaluated under a wide range of load and voltage conditions, demonstrating robustness to speed variations and measurement noise. The results show that the proposed DBEA framework enables non-invasive classification, making it suitable for implementation in compact and portable diagnostic systems. Full article

At Animals Asia’s Vietnam Bear Rescue Center (VBRC), 40% of the current population has been diagnosed with systemic hypertension. Systemic hypertension lesions have led to fatal consequences in the form of aortic aneurysm and rupture. Historically, veterinarians were only able to diagnose systemic hypertension by identifying validated secondary structural heart and retinal lesions during annual health checks of anesthetized bears. In 2021, the VBRC began training bears for cooperative conscious blood pressure measurements to increase monitoring frequency and expedite the diagnosis of systemic hypertension in affected bears. The objective of this study was to evaluate a noninvasive method of blood pressure measurement in trained, cooperative Asiatic black bears. Indirect blood pressure measurements, using the oscillometric technique, were validated with direct arterial measurements in nine bears (6 male, 3 female, ages 13–22 years) undergoing anesthesia for annual health checks. Eleven trained bears at the VBRC without secondary lesions of systemic hypertension (6 male, 5 female, ages 7–23 years) were used to develop normal systolic ranges for Asiatic black bears using the indirect technique. Mean blood pressure measurements for this group of trained bears (n = 11) were 180.65 +/− 37 mmHg (95% CI: 126–255) systolic. These results suggest that indirect blood pressures may be a useful tool to monitor blood pressure in cooperative conscious bears at the VBRC. Full article

Background/Objectives: Cardioneuroablation (CNA) is used to treat reflex syncope by parasympathetic denervation of the cardiac conduction system. Respiratory heart rate variability (RespHRV) constitutes an important physiological mechanism that optimizes lung perfusion. The impact of CNA on various components of RespHRV remains unclear. Methods: Eleven subjects (36.8 ± 14.1 years) undergoing CNA for the treatment of cardioinhibitory, vagally mediated syncope were enrolled. For the RespHRV assessment, we used continuous respiratory flow measurement and an electrocardiogram. RespHRV analysis included the following: (a) amplitude, reflecting the overall magnitude of changes in RR interval during the respiratory cycle (RespHRVpv, ms); and (b) efficiency, defined as the percentage of inspirations accompanied by RR shortening (short-RRi inspirations, %), and expirations accompanied by RR prolongation (long-RRi expirations, %). Baroreflex sensitivity (BRS, ms/mmHg) was assessed with a sequential method using a noninvasive hemodynamic monitor. Both RespHRV and BRS were captured 48 h apart, before and after CNA. Results: A significant reduction was observed in RespHRVpv (57 [30–131] vs. 13 [7–16] ms, p = 0.003), short-RRi inspirations (97.0 [77.8–100.0] vs. 36.0 [14.3–63.2] %, p = 0.003), and long-RRi expirations (88.0 [78.1–97.6] vs. 31.1 [21.4–65.8] %, p = 0.008). Moreover, we found a strong relationship between ΔBRS and ΔRespHRVpv (r = 0.77, p = 0.005) following CNA. Conclusions: Our results indicate a substantial role of the cardiac parasympathetic system in RespHRV development, including both its amplitude and efficiency. The marked decrease in key RespHRV measures after CNA highlights the need for further research into its long-term clinical effects. Full article

Background: Studies comparing systemic and salivary antibody responses against SARS-CoV-2 between children and adults show conflicting results. Furthermore, it is still unclear whether salivary antibody testing could be a non-invasive approach to evaluate the humoral immune response. Methods: anti-SARS-CoV-2 IgG antibodies were measured in blood and saliva sample pairs from vaccinated adults to investigate whether salivary antibody response could be a non-invasive assessment of immune response. Salivary antibody levels were also compared between vaccinated children and adults to investigate local antibody responses. Results: Salivary IgG antibody response against SARS-CoV-2 largely reflects the systemic response in vaccinated adults. Salivary and systemic antibody concentrations were higher in vaccinated adults who had been infected, received schemes including mRNA-based vaccines, had more exposures, and a shorter time from last exposure. Salivary antibody detection was associated with schemes including mRNA-based vaccines, time from last exposure, and systemic antibody concentrations. Vaccinated children showed higher salivary antibody concentrations than adults. This difference remained when comparing antibody levels between children and adults under equal conditions (vaccination schemes, number of exposures, time from last exposure, COVID-19 history). Younger age, number of exposures, schemes including mRNA-based vaccines, and shorter time from last exposure were associated with salivary antibody levels in a multivariable linear regression analysis (p < 0.0001). Conclusions: Salivary antibody determination against SARS-CoV-2 could be a non-invasive assessment of the short-term immune response in adults with multiple exposures. Furthermore, the stronger salivary antibody response in children suggests that local immune protection may differ between children and adults, contributing to different outcomes. Full article

Alzheimer’s disease (AD) is a progressive neurodegenerative disorder characterized by cognitive and motor decline. Early detection remains challenging, as traditional neuroimaging and neuropsychological assessments often fail to capture subtle, preclinical changes. Recent advances in digital health and artificial intelligence (AI) offer new opportunities to identify non-invasive biomarkers of cognitive impairment. In this study, we propose an AI-driven framework for early AD based on handwriting motion data captured using a sensor-integrated Smart Pen. The system employs an inertial measurement unit (MPU-9250) to record fine-grained kinematic and dynamic signals during handwriting and drawing tasks. Multiple machine learning (ML) algorithms—Logistic Regression, Support Vector Machine (SVM), Random Forest (RF), and k-Nearest Neighbors (kNN)—and deep learning (DL) architectures, including one-dimensional Convolutional Neural Networks (1D-CNN), Long Short-Term Memory (LSTM), and a hybrid CNN-BiLSTM network, were systematically evaluated. To address data scarcity, we implemented a Sim-to-Real Domain Adaptation strategy, augmenting the training set with physics-based synthetic samples. Results show that classical ML models achieved moderate diagnostic performance (AUC: 0.62–0.76), while the proposed hybrid DL model demonstrated superior predictive capability (accuracy: 0.91, AUC: 0.96). These findings underscore the potential of motion-based digital biomarkers for the automated, non-invasive detection of AD. The proposed framework represents a cost-effective and clinically scalable informatics solution for digital cognitive assessment. Full article

(1) Background: The use of wearable technology for assessing running biomechanics in field-based sports has increased in recent years. Inertial measurement units (IMUs) are low-cost, non-invasive devices capable of estimating spatiotemporal gait-related metrics during overground locomotion. This study evaluated the accuracy and concurrent validity of a foot-mounted IMU system for estimating sprinting kinematics. (2) Method: Twenty-five elite and sub-elite athletes completed four maximal 10-metre fly efforts, with their kinematics measured concurrently using a three-dimensional motion analysis system and IMUs. (3) Result: The foot-mounted IMU system’s root mean square errors for stride length and duration were 0.22 m and 0.04 s, respectively. Mean biases (95% level of agreement) were −0.67 $\mathrm{m} · {\mathrm{s}}^{-1}$ (−1.19; −0.14) for peak velocity, −0.51 $\mathrm{m} · {\mathrm{s}}^{-1}$ (−1.10; 0.09) for instantaneous velocity, and 0.17 $\mathrm{m} · {\mathrm{s}}^{-2}$ (−1.04; 1.37) for instantaneous acceleration. Stride length, duration, and cadence were −0.07 m (−0.36; 0.23), 0.02 s (−0.02; 0.06), and −4.64 strides $· {\min }^{-1}$ (−15.82; 6.53), respectively. (4) Conclusions: End users implementing this technology in research and practice should interpret this study’s findings relative to their analytical objectives, logistical resources, and operational constraints. Therefore, its adoption should be guided by the specific performance metrics of interest and the extent to which the system’s capabilities align with the outcomes the end user aims to achieve. Full article

Microrobots are emerging as transformative tools in minimally invasive medicine, with applications in non-invasive therapy, real-time diagnosis, and targeted drug delivery. Effective use of these systems critically depends on accurate detection and tracking of microrobots within the body. Among commonly used imaging modalities, including MRI, CT, and optical imaging, ultrasound (US) offers an advantageous balance of portability, low cost, non-ionizing safety, and high temporal resolution, making it particularly suitable for real-time microrobot monitoring. This study reviews current detection strategies and presents a comparative evaluation of six advanced AI-based multi-object detectors, including ConvNeXt, Res2NeXt-101, ResNeSt-269, U-Net, and the latest YOLO variants (v11, v12), being applied to microrobot detection in US imaging. Performance is assessed using standard metrics (AP50–95, precision, recall, F1-score) and robustness to four visual perturbations: blur, brightness variation, occlusion, and speckle noise. Additionally, feature-level sensitivity analyses are conducted to identify the contributions of different visual cues. Computational efficiency is also measured to assess suitability for real-time deployment. Results show that ResNeSt-269 achieved the highest detection accuracy, followed by Res2NeXt-101 and ConvNeXt, while YOLO-based detectors provided superior computational efficiency. These findings offer actionable insights for developing robust and efficient microrobot tracking systems with strong potential in diagnostic and therapeutic healthcare applications. Full article

This article attempts to develop hydrogel systems containing two polymers, chitosan and methylcellulose, with somatotropin as the active substance. The aim of the study was to obtain a hydrogel preparation for the skin that releases a sufficient amount of the hormone to achieve a satisfactory therapeutic effect. This innovative method of delivering the hormone to the body would allow for non-invasive administration of the drug, which would certainly ensure greater comfort for patients. The preparations were subjected to an assessment of physicochemical parameters such as pH measurement, texture analysis, rheological properties, and sensory evaluation. Somatotropin release studies demonstrated that the highest hormone release occurred from a matrix containing equal amounts of chitosan and methylcellulose, reaching 2%. The use of phosvitin as a carrier protein resulted in a prolonged release of somatotropin. Among the phosvitin concentrations tested, the formulation containing 0.005% phosvitin demonstrated the highest somatotropin availability. All preparations had good rheological and textural properties, allowing them to be easily spread over the skin surface. Full article