Search Results (17,599)

Hair loss, particularly androgenetic alopecia (AGA) and alopecia areata (AA), is a prevalent condition with widespread psychosocial impact. Recently, low-level laser therapy (LLLT) has emerged as a promising non-invasive therapeutic alternative due to its bioregulatory effects and favorable safety profile compared to conventional pharmacological treatments. In this study, we employed fluorescence lifetime imaging microscopy (FLIM) to investigate the effects of red-light irradiation on hair follicle dynamics and the cutaneous microenvironment in a C57BL/6 mouse model. A hair regeneration model was established to evaluate the efficacy of 650 nm red-light irradiation (bandwidth ± 20 nm). Then, the skin tissue was stained with hematoxylin and eosin (H&E) and followed by FLIM analysis to provide a multidimensional assessment of tissue morphology and metabolic status. Results showed that red-light irradiation significantly increased hair follicle numbers and enhanced adenosine triphosphate (ATP) levels in the skin tissue. FLIM analysis further revealed prolonged fluorescence lifetime values across different epidermal and dermal layers in the irradiated group, indicating significant alterations in the skin metabolic microenvironment. Furthermore, phasor plot analysis enabled precise differentiation between hair follicles and their surrounding skin structures, highlighting FLIM’s high sensitivity and accuracy in evaluating hair growth. In conclusion, this study has provided novel imaging-based insights into the mechanisms of LLLT-induced hair regeneration, highlighting the potential of FLIM as a powerful tool for characterizing the cutaneous microenvironment and quantitatively evaluating phototherapeutic efficacy in future translational applications. Full article

Background/Objectives: The Achilles tendon enthesis (ATE) is a key load-transmitting structure that is frequently affected in musculoskeletal disorders, including insertional tendinopathy, overuse injuries and inflammatory enthesopathies. Reliable non-invasive assessment of the enthesis structure is therefore of increasing clinical importance. This study evaluated the ability of advanced magnetic resonance (MR) microscopy to depict the ultrastructural organization of the ATE using histology as a reference standard. Methods: Five human ATEs from anatomical body donations were included. Two specimens were used for protocol development of the histological preparation, whereas three specimens underwent the full multimodal pipeline comprising undecalcified methyl methacrylate (MMA) thin-section histology with Giemsa staining, T2*-weighted 3D-variable echo time (vTE) MR microscopy at 7 Tesla, and microradiography. Results: Histological analysis demonstrated excellent preservation of fibrocartilage zones and mineralized interfaces. Corresponding MR microscopy data allowed the identification of major structural components of the enthesis, particularly mineralized regions, although fine ultrastructural details remained beyond the MR microscopy resolution. Microradiography supported interpretation of the mineralized tissue architecture and MR microscopy signal characteristics. Conclusions: These findings indicate that high-field MR microscopy can capture clinically relevant structural features of the Achilles tendon enthesis, while histology remains essential for detailed ultrastructural validation. The combined imaging approach provides a translational framework that may support improved diagnosis, monitoring and treatment evaluation in musculoskeletal disorders involving the osteotendinous junction. Full article

Euphorbia tirucalli, commonly known as Aveloz, is widely used in Brazilian folk medicine for its purported antibacterial, antiviral, and antitumoral properties. However, scientific evidence regarding its systemic in vivo effects, particularly on the cardiovascular system, remains limited. This study investigated the impact of oral E. tirucalli latex ingestion on cardiac hemodynamics and associated molecular alterations in normotensive Wistar rats. Animals received water (control) or E. tirucalli latex (13.47 mg/kg) by oral gavage for 15 days. Hemodynamic parameters were assessed through noninvasive blood pressure monitoring and direct measurements of left ventricular systolic (LVSP) and end-diastolic pressures (LVEDP), cardiac cycle duration, rates of pressure development (dP/dt_max and dP/dt_min), and the left ventricular relaxation constant (Tau). Oxidative stress and inflammation were evaluated by plasma advanced oxidation protein products (AOPP) and myeloperoxidase (MPO), respectively, while reactive oxygen species production and apoptosis were analyzed in isolated cardiomyocytes. Although systemic blood pressure remained unchanged, E. tirucalli increased LVSP, LVEDP, cardiac cycle duration, and dP/dt_max, while reducing Tau. These alterations were accompanied by elevated AOPP and MPO levels, increased cardiomyocyte hydrogen peroxide, and higher rates of early apoptosis, indicating that E. tirucalli latex alters cardiac hemodynamics and promotes oxidative and inflammatory cardiac injury. Full article

Continuous, non-invasive cardiopulmonary monitoring is receiving increasing attention as population aging and chronic diseases rise. Acoustic sensing provides diagnostically relevant information with relatively simple hardware. Yet, physiological body sounds span heterogeneous and partially overlapping spectra and are highly susceptible to environmental noise and motion artifacts, which limit conventional stethoscopes and fixed-frequency sensors. Frequency-Tunable Acoustic Sensors (FTAS) offer a promising route toward frequency-selective amplification and adaptive interference suppression by matching their resonance to target signals, thereby potentially supporting multi-site monitoring and personalized diagnostics on a single platform. This review starts with an overview of physiological sound generation and the evolution of auscultation, then surveys mainstream medical acoustic transducers (piezoelectric, capacitive microelectromechanical systems (MEMS), piezoresistive and triboelectric) and their limitations in frequency selectivity. Resonance-tuning strategies are classified into three paradigms: electrical tuning, material-based tuning, and geometric reconfiguration, and their tuning ranges, response characteristics, and representative implementations are comparatively discussed. Finally, this review discusses the potential translational value of FTAS in physiological acoustic signal monitoring, particularly in cardiovascular and respiratory assessment, and emphasizes the remaining challenges, including the trade-off between sensitivity and selectivity, as well as long-term biocompatibility. At the same time, this review highlights their development prospects in customizable acoustic sensing platforms. Full article

Background: One of the most debated scientific topics in recent years is the role of non-invasive respiratory support techniques in the treatment of de novo acute hypoxemic respiratory failure. Until pre-COVID-19, the most accredited guidelines did not make recommendations for or against the use of these techniques in this clinical condition, and the increased risk of adverse events for patients who failed the non-invasive approach was widely reported in the literature. The most recent guidelines recommend the use of HFNC as a first-line technique in the treatment of de novo acute hypoxemic respiratory failure to avoid the need for tracheal intubation. However, the strength of these recommendations remains weak, the quality of the underlying evidence is poor, and their usefulness in deciding which technique to apply to an individual patient is questionable. Aim: The aim of this review was to provide the reader with some critical tools to interpret the different indications regarding the choice of the best non-invasive support technique to be used in this setting. Methods: To this end, we analyzed the available literature on this topic, privileging the works that are most useful in correlating the practical indications to the pathophysiological assumptions. Results and Conclusions: The notable heterogeneity of the studies on which the current recommendations are based, as well as the affirmation of the concept of patient self-induced lung injury (P-SILI), highlights the importance of assessing each patient’s risk of developing this complication, individualizing treatment to the patient’s specific needs, and monitoring the patient during treatment. Full article

Background: The global aging population faces an increasing prevalence of type 2 diabetes mellitus (T2DM), often complicated by frailty, cognitive decline, and impaired manual dexterity. These factors make glucose self-monitoring particularly challenging. Minimally invasive glucose monitoring methods, particularly continuous glucose monitoring (CGM) as well as emerging non-invasive glucose monitoring technologies offer potential solutions, but remain insufficiently evaluated in older adults. Objective: To systematically review and synthesize available evidence on the advantages of continuous glucose monitoring (CGM) and non-invasive glucose monitoring methods in older adults aged ≥65 years, focusing on clinical efficacy, usability, adherence, and existing knowledge gaps. Methods: A systematic literature search was conducted across PubMed, Scopus, and Web of Science, including studies from 2020 to 2025. Eligible studies included participants aged ≥65 years and evaluated the clinical performance of CGM or other minimally invasive or non-invasive glucose monitoring technologies. The PRISMA framework guided screening and selection. Risk of bias was assessed using RoB 2 and ROBINS-I tools. Due to substantial heterogeneity among study designs and reported outcomes, a narrative synthesis approach was adopted. Results: A total of 426 records were identified, of which 13 met the predefined eligibility criteria after full-text screening. After risk of bias assessment, one study was excluded, resulting in 12 studies included in the final synthesis. No eligible studies evaluating completely non-invasive glucose monitoring technologies were identified, highlighting a significant research gap in this area specifically for older adults. CGM was associated with improved glycemic control, reduced hypoglycemia, and increased time in range among older adults. Usability was generally high, particularly with newer, user-friendly devices. Conclusions: CGM is associated with improved glycemic outcomes and favorable usability in adults aged ≥65 years. However, a significant gap exists in research on non-invasive glucose monitoring technologies in this population. Future studies should address the accuracy, feasibility, and usability of non-invasive glucose monitoring devices, while accounting for the physiological and behavioral complexities associated with aging. Full article

The evaluation of biomechanical parameters in four-beat gaited horses remains limited by the subjectiveness and complexity of current standard methods. Through a deep learning approach, we aimed to infer dissociation % using only acoustic signals. A total of 268 audio samples were extracted from publicly available videos featuring three Brazilian horse breeds (Mangalarga Marchador, Campolina, and Piquira) performing marcha batida and marcha picada. Acoustic features, including root mean square energy (RMS), zero-crossing rate (ZCR), and 13 Mel-frequency cepstral coefficients (MFCCs), were extracted and used to train a long short-term memory (LSTM) neural network. The model accurately predicted the time intervals between successive hoof–ground contacts (R² = 0.98; MAE = 0.0071), enabling the calculation of the dissociation %. While no significant differences were found between gait types and dissociation %, breed-related differences in both mean hoof–ground contact interval and dissociation were observed, with 8 acoustic features demonstrating discriminative power. Our results suggest that hoof–ground contact patterns can be quantified objectively from audio alone, offering a practical and non-invasive method for gait analysis. The approach holds potential for applications in breed standardization, selection, and digital locomotion phenotyping of horse populations. Full article

The conventional window for ultrasonic pregnancy diagnosis in sows is 22–25 days post-insemination, which often results in missed opportunities for the optimal re-insemination of non-pregnant sows and elevated production costs. This present study aimed to establish an early pregnancy detection method for sows at 12–18 days post-insemination, thereby providing a reference for efficient reproductive management. Saliva, urine and vaginal secretions were collected from sows during this period, and seven metabolites were quantified. Seven machine learning models were employed for data analysis, after which the optimal combination was determined, and the detection protocol was refined using recursive feature elimination. The results revealed that the majority of metabolites in saliva and urine differed significantly between pregnant and non-pregnant groups (p < 0.05). Among the models evaluated, the random forest algorithm exhibited the best predictive performance, with accuracy ranging from 0.59 to 1.00. Saliva sampled at 17 days post-insemination was identified as the optimal diagnostic medium, and 100% prediction accuracy was achieved by measuring only three metabolites: Glc, Ste, and Xan. The diagnostic approach established in this study allows pregnancy detection 5–8 days earlier than conventional methods, with the additional benefits of non-invasive sampling and minimal stress to sows. Accordingly, it provides a novel reference for enhancing the efficiency of swine production. Full article

Circulating long non-coding RNAs (lncRNAs) have emerged as promising non-invasive biomarkers for colorectal cancer (CRC) detection; however, data in Vietnamese populations remain limited. In this study, a total of 218 participants (106 CRC, 80 adenomas, and 32 healthy controls) were included. Relative expression levels and diagnostic performance of three circulating lncRNAs—CCAT1, HOTAIR, and NEAT1—were quantified using RT-qPCR and analyzed by the 2^−ΔΔCt method. Receiver operating characteristic (ROC) curve analysis was performed to assess the diagnostic accuracy of individual lncRNAs and their combinations. CCAT1, HOTAIR, and NEAT1 were significantly upregulated in CRC patients compared with adenoma patients and healthy controls (all p < 0.001). Expression levels were higher in advanced-stage (TNM III–IV) CRC than in early-stage disease. Among individual markers, HOTAIR demonstrated the highest diagnostic accuracy (AUC = 0.918), followed by CCAT1 (AUC = 0.908) and NEAT1 (AUC = 0.890). Combined biomarker models showed improved performance, with the CCAT1 + HOTAIR combination achieving the highest AUC (0.944). Overall, circulating CCAT1, HOTAIR, and NEAT1 demonstrated favorable diagnostic performance in a Vietnamese population and outperformed conventional markers (CEA and CA19-9). These findings support the potential utility of multi-lncRNA panels as non-invasive biomarkers for CRC detection, warranting further validation in larger, independent cohorts. Full article

Glaucoma is an increasing ocular disease and one of the major causes of irreversible blindness globally. Thus, it is of utmost importance to diagnose glaucoma accurately and in a timely manner for appropriate clinical intervention. Retinal fundus image analysis is a non-invasive approach for glaucoma screening. However, it is a tedious and subjective process for accurate glaucoma detection. In this work, a customized convolutional neural network (CNN) model is proposed for glaucoma classification using fundus images, and an attention mechanism is employed for improved discriminative feature learning. Experiments were carried out on two publicly available datasets, namely Drishti-GS1 and ACRIMA, for unbalanced and balanced datasets, respectively. Data augmentation and hyperparameter tuning were employed for improved model generalization. To increase model explainability and trust for accurate glaucoma screening, gradient-weighted class activation mapping (Grad-CAM) is employed for accurate glaucoma screening. For accurate glaucoma screening, the proposed model attained 90.32% and 96.45% accuracy on the Drishti-GS1 and ACRIMA datasets, respectively, with higher sensitivity and AUC scores. Thus, it is evident that the proposed model employing attention mechanisms and explainable AI attained higher accuracy for accurate glaucoma screening. Full article

We developed an automated system to address orchard crop damage caused by Formosan macaques, a problem where traditional deterrent methods have proven to be ineffective. The system integrates an Internet Protocol camera with a You Only Look Once version 5 (YOLOv5) object detection model, which was trained on an augmented 6000-image dataset featuring a simulated monkey puppet in an indoor setting to validate its real-time identification capability through simulation. Upon target detection, a high-power laser, controlled via the Message Queuing Telemetry Transport protocol, is actuated to perform dynamic and non-invasive repelling. A web-based Human–Machine Interface (HMI) is provided, allowing users to remotely monitor and adjust strategies. This system offers a low-cost, highly efficient, and scalable solution for smart agriculture, with potential for expansion to other scenarios requiring a high degree of security and defense, such as warehouses and construction sites. Full article

A non-invasive blood glucose monitoring system was developed in this study using near-infrared spectroscopy and an Arduino platform. Reflected signals from near-infrared-focused emissions to a user’s finger are captured via an infrared-tuned photodiode, digitally processed, and displayed on an Android-based application with logging, reminders, and cloud synchronization. Calibrated testing with 20 participants (10 diabetics and 10 non-diabetics) revealed that in the measurement of diabetics, the non-fasting readings showed high average accuracy (99.89%). Non-diabetic trials also demonstrated strong measurement acuity (92.18%), with improved accuracy in non-fasting measurements. The device demonstrates feasibility for affordable, portable, and cloud-connected smart non-invasive glucose tracking. Full article

Electrical Impedance Tomography (EIT) is a promising non-invasive sensing technique, yet its practical application in resource-constrained environments is often limited by the high computational cost of inverse image reconstruction. To address this challenge, we focus on specific sensing objectives rather than full image recovery. In this study, we propose a lightweight, task-oriented inference framework for object localization in EIT that bypasses the need to solve computationally expensive inverse reconstruction problems. This approach addresses the high computational demands and hardware complexity of conventional iterative methods, which often hinder real-time monitoring in resource-constrained edge computing environments. Training datasets were generated via finite element method (FEM) simulations for Opposite and Adjacent current injection configurations. A feedforward neural network was developed to independently estimate the radial and angular object positions as probability distributions. Our systematic evaluation revealed that the localization performance depends on the injection configuration and model depth; notably, the Opposite method achieved perfect classification accuracy (1.00) for radial estimation with an optimized architecture of four hidden layers, whereas the Adjacent method exhibited higher ambiguity. Results quantitatively evaluated using the Wasserstein distance show that the Opposite configuration produces more localized, unimodal probability distributions than the Adjacent configuration by utilizing current fields that traverse the entire domain. Compared with existing image-based reconstruction methods, including the conventional electrical impedance tomography and diffuse optical tomography reconstruction software (EIDORS ver.3.12), the proposed framework reduced energy consumption from 3.09 to 0.96 Wh, demonstrating an approximately 70% improvement in energy efficiency while maintaining a high localization accuracy without the need for iterative Jacobian updates. This task-oriented framework enables reliable, high-speed, and energy-efficient localization, making it well-suited for low-power EIT applications in mobile and embedded sensor systems. Full article

Background: We synthesized evidence from randomized clinical trials (RCTs) published between 2019 and 2025 on repetitive transcranial magnetic stimulation (rTMS) in post-stroke cognitive impairment (PSCI) and compared different stimulation parameters, cortical targets, and combinations with rehabilitation interventions. Methods: A systematic review according to PRISMA guidelines examined the RCTs applying rTMS in adults with PSCI compared with control or sham groups. The primary outcome was improvement in cognitive function and functional outcomes measured with standardized scales. Results: Fifteen studies, involving a total of 732 patients, were included. The most frequently investigated were high-frequency (≥10 Hz) stimulation protocols of the left dorsolateral prefrontal cortex, with treatment cycles ranging from 2 to 6 weeks. Overall, rTMS was generally safe and well tolerated, with rare and mild adverse events. Several studies reported improvements in cognitive performance following rTMS, although effects were variable across trials and need caution in light of heterogeneity in stimulation protocols, sample sizes, outcome measures, and methodological quality. In most cases, rTMS or intermittent theta burst stimulation combined with structured cognitive training yielded greater cognitive and functional gains than stimulation or rehabilitation alone. This suggests a positive interaction between rTMS and cognitive training, although current evidence does not yet allow definitive conclusions. Conclusions: rTMS appears to be a promising strategy for post-stroke cognitive rehabilitation, particularly for attention and executive functioning. However, heterogeneity in stimulation protocols and outcome measures, along with limited sample sizes and short follow-up, reduces the certainty and comparability of current evidence. The widespread reliance on global screening tools may further underestimate domain-specific effects. Future multicentre trials with standardized protocols and more sensitive cognitive assessments are needed to clarify efficacy and guide further clinical application of rTMS in PSCI. Full article

Colorectal cancer (CRC) is the second most common cancer in Europe. There is a need to explore and validate new blood-based tumor markers to improve the selection of patients who are likely to benefit from an early, non-invasive diagnosis of CRC. The purpose of this report is to present the test protocol and its verification. The study is planned in four phases. The first trial phase involves collecting material, consisting of healthy tissue, diseased tissue, and plasma, from 120 CRC patients over 50 years old during surgery. This phase also involves identifying microRNAs (miRNAs) and comparing their expressed levels in colorectal cancer cells with those in healthy tissue taken from a standard resection margin. We detected measurable levels of miRNAs in tissue samples taken from patients, confirming that the material was correctly removed for testing. Statistically significant differences were obtained between healthy and cancerous tissue for selected miRNAs. Some of the selected miRNAs have higher expression levels in CRC tissue and could be potential candidate biomarkers for laboratory-based colorectal cancer diagnosis. Full article