Search Results (2,184)

Canada is a top producer and exporter of crude oil but also has many in-land freshwater ecosystems that need protection using non-invasive remediation methods that are effective in sensitive environments. To assess the efficacy of enhanced monitored natural recovery (eMNR) as a secondary remediation strategy for freshwater oil spills, we conducted controlled spills of conventional heavy crude oil (CHV) in a freshwater lake at the IISD-Experimental Lakes Area in northwestern Ontario, Canada, in 2021. Three shoreline enclosures (5 × 10 m) were deployed on a wetland shoreline and treated with ~1.5 kg of weathered CHV. Four days later primary recovery of oil was conducted using shoreline washing followed by secondary remediation of residual oil using eMNR. Three unoiled, reference enclosures were also treated with shoreline washing but not secondary remediation. Polycyclic aromatic compounds (PAC) in water and sediment, and general water quality were monitored in the enclosures for 412 days after oiling. Total PACs in the water, mostly of 2- and 3-ring alkylated compounds, peaked three days after oiling (1188 ± 251 ng/L), declined to half of initial concentrations 8.26–11.75 days later and to near background levels by day 73. Total PACs were elevated in sediment of the oiled enclosures until day 70 likely due to sorption or settling oil but were heterogenous and influenced by pyrogenic compounds. Results from this study suggest that eMNR may be an effective remediation method following primary recovery efforts at sensitive aquatic sites where mechanical recovery is contraindicated. Full article

Hepatitis B virus (HBV) pregenomic RNA (pgRNA), transcribed directly from nuclear covalently closed circular DNA (cccDNA), is an essential component in viral replication. The synthesis and encapsidation of pgRNA depend significantly on the transcriptional activity of cccDNA, making serum pgRNA a recently recognized non-invasive biomarker for evaluating cccDNA activity. However, its clinical application is limited by factors including preanalytical variables, methodological inconsistencies in detection, and a lack of standardization in quantification. This review provides an overview of the biological origins of pgRNA and its critical role in the HBV replication cycle, highlighting the stability challenges encountered during the collection, processing, and storage of plasma/serum samples. Furthermore, it analyzes recent significant advancements in pgRNA detection technologies, encompassing modified reverse transcription quantitative polymerase chain reaction (RT-qPCR), nucleocapsid-captured methodologies, automated testing platforms, multiplex digital PCR, isothermal amplification, and clustered regularly interspaced short palindromic repeats-based assays. A comparison of these technologies revealed that discrepancies in pgRNA quantification arise primarily from variations in sample processing and measurement systems, rather than from inherent biological limitations. Therefore, establishing standardized sample handling procedures, harmonized detection methods, and unified measurement systems is imperative before pgRNA can be reliably applied to monitor treatment, guide cessation decisions, or evaluate cure in chronic hepatitis B. Full article

Advanced glycation end products (AGEs) are important biomarkers associated with diabetes and metabolic disorders; yet existing detection methods are invasive and unsuitable for frequent monitoring. This study aimed to develop a non-invasive and portable AGEs detection device, optimize strategies for mitigating pigmentation-related interference, and evaluate its feasibility for metabolic assessment. The proposed system employs a 365 nm ultraviolet LED excitation source, an optical filter assembly integrated into an ergonomic dark chamber, and an eyelid-signal-based algorithm to suppress ambient light and skin pigmentation interference. Simulation experiments were conducted to evaluate the influence of different pigment colors and skin tones on fluorescence measurements. A clinical study was performed in 200 participants, among whom 42 underwent concurrent serum AGEs measurement as the reference standard. Predictive models combining corneal fluorescence signals and body mass index (BMI) were constructed and evaluated. The results indicated that purple and blue pigments introduced greater interference, whereas green and pink pigments had minimal effects. Device-derived AGEs estimates demonstrated good agreement with serum AGEs, with a mean error below 8%. A hybrid model incorporating BMI achieved improved predictive accuracy compared with single-parameter models. Participants with high-AGE dietary habits exhibited elevated fluorescence signals and BMI. These findings suggest that the proposed device enables stable and accurate non-invasive AGEs assessment, with potential utility for metabolic monitoring. Incorporating lifestyle-related parameters may further enhance predictive performance and expand clinical applicability. Full article

Background: Impedance pneumography (IP) is a non-invasive technique for assessing tidal breathing in young children and enables home-based recordings without active patient cooperation. By deriving tidal breathing flow–volume (TBFV) curves and indices such as the expiratory variability index (EVI), IP has been proposed as a tool for identifying obstructive breathing patterns and monitoring airway function in early childhood. However, its clinical role in asthma and wheezing disorders has not been systematically evaluated. This review aimed to assess the evidence of IP in differentiating healthy children from those with asthma or recurrent wheeze, in reflecting treatment-related changes or acute bronchial obstruction, and in relation to other lung function tests. Methods: A systematic literature search of PubMed, Medline, Embase, and the Cochrane Library databases was conducted on 5 January 2026. Original studies using IP in children aged 0–7 years with asthma or wheeze were eligible. Study selection followed PRISMA guidelines, and risk of bias (RoB) was assessed using the Newcastle–Ottawa Scale (NOS). Due to substantial heterogeneity in study design, populations, and outcome measures, results were synthesized narratively. Results: Five studies were included, with a total of 376 participants aged 0.5–7.0 years. Three studies reported significantly lower EVI values and TBFV profile variation in children with asthma or recurrent wheeze compared with healthy controls. Two studies found an association between EVI and markers of airway obstruction. Changes in IP measures following inhaled corticosteroid treatment or medication withdrawal were reported, suggesting sensitivity to treatment-related changes. However, study quality was moderate to low, with small sample sizes, heterogeneous outcome definitions, and limited diagnostic validation. Conclusions: Current evidence suggests that IP-derived indices, particularly EVI, capture clinically relevant features of obstructive breathing patterns in young children and may be useful for longitudinal monitoring of airway function. However, evidence supporting a diagnostic role for IP in childhood asthma remains limited. Larger, independent, and methodologically robust studies are needed before IP can be integrated into routine clinical practice. Full article

Background: Extubation failure increases morbidity and mortality. Non-invasive ventilation (NIV), including high-flow nasal cannula (HFNC), can reduce reintubation rates. Current practice often involves prophylactic use of NIV post-extubation. Electrical Impedance Tomography (EIT) provides real-time monitoring of pulmonary distribution and ventilation. Recent adult studies suggest that EIT has potential in extubation failure prediction, but evidence in children is limited. Our objectives were to evaluate peri-extubation regional lung volume/distribution and to explore EIT-derived physiological changes and on post-extubation respiratory support patterns in critically ill children. Methods: A prospective observational study included intubated patients aged 1 month to 18 years in the PICU who were intubated for over 24 h. Vital signs and chest EIT were recorded pre-extubation (H0), immediately post-extubation (H1), at 30 min (H2), and at 4 h (H3). Patients were categorized by chest X-ray findings into abnormal or normal groups. Results: Among 209 ventilated patients, 54 were included. End-expiratory lung impedance (∆EELI), tidal impedance (TID), and the global inhomogeneity index (GI) demonstrated significant changes across predefined peri-extubation time points. Thirty-eight (70.4%) patients received HFNC or NIV immediately after extubation. No extubation failures occurred, precluding evaluation of extubation failure predictors. In the subgroup analyzed based on chest X-ray findings, differences in TID and ODCL were observed between patients with normal and abnormal chest X-rays immediately after extubation. Conclusions: The ∆EELI, TID, and GI demonstrated significant changes across predefined peri-extubation time points. In the absence of extubation failure events, the ability of EIT monitoring to evaluate extubation failure could not be assessed. The frequent use of prophylactic NIV support after extubation may have influenced post-extubation physiology. Full article

In this study, we describe a non-invasive approach to objectively assess fragrance-induced emotions using multiplex salivary biomarker profiling. Traditional self-reports, physiological monitoring, and neuroimaging remain limited by subjectivity, invasiveness, or poor temporal resolution. Saliva offers an advantageous alternative, reflecting rapid neuroendocrine changes linked to emotional states. We combined four key salivary biomarkers, cortisol, alpha-amylase, dehydroepiandrosterone, and oxytocin, to capture multidimensional emotional responses. Two clinical studies (n = 30, n = 63) and one user study (n = 80) exposed volunteers to six fragrances, with saliva collected before and 5 and 20 min after olfactory stimulation. Subjective emotional ratings were also obtained through questionnaires or an implicit approach. Rigorous analytical validation accounted for circadian variation and sample stability. Biomarker patterns revealed fragrance-induced emotional profiles, highlighting subgroups of participants whose biomarker dynamics correlated with particular emotional states. Increased oxytocin and decreased cortisol levels aligned with happiness and relaxation; in comparison, distinct biomarker combinations were associated with confidence or dynamism. Classification and Regression Trees (CART) analysis results demonstrated high sensitivity for detecting these profiles. Validation in an independent cohort using an implicit association test confirmed concordance between molecular profiles and behavioral measures, underscoring the robustness of this method. Our findings establish salivary biomarker profiling as an objective tool for decoding real-time emotional responses. Beyond advancing affective neuroscience, this approach holds translational potential in personalized fragrance design, sensory marketing, and therapeutic applications for stress-related disorders. Full article

Non-invasive electrocardiogram (ECG) and respiratory signals are easy to acquire via low-cost sensors, making them promising alternatives for sleep staging. However, existing methods using these signals often yield insufficient accuracy. To address this challenge, we incrementally optimized the sleep staging model by designing a structured experimental workflow: we first preprocessed respiratory and ECG signals, then extracted fused features using an enhanced feature selection technique, which not only reduces redundant features, but also significantly improves the class discriminability of features. The resulting fused features serve as a reliable feature subset for the classifier. In the meantime, we proposed a hybrid optimization algorithm that integrates the snake optimization algorithm (SO) and ant colony optimization algorithm (ACO) for automated hyperparameter optimization of support vector machines (SVMs). Experiments were conducted using two PSG-derived public datasets, the Sleep Heart Health Study (SHHS) and MIT-BIH Polysomnography Database (MIT-BPD), to evaluate the classification performance of multimodal features compared with single-modal features. Results demonstrate that the bimodal staging using SHHS multimodal signals significantly outperformed single-modal ECG-based methods, and the overall accuracy of the SHHS dataset was improved by 12%. The SVM model optimized using the hybrid Snake–ACO algorithm achieved an average accuracy of 89.6% for wake versus sleep classification on the SHHS dataset, representing a 5.1% improvement over traditional grid search methods. Under the subject-independent partitioning experiment, the wake versus sleep classification task maintained good stability with only a 1.8% reduction in accuracy. This study provides novel insights for non-invasive sleep monitoring and clinical decision support. Full article

Foreign matter accumulating on catheters during ascites paracentesis in cancer patients can interfere with the procedure. The paracentesis site must be visually inspected by patients or medical staff. We propose a monitoring method using sensors, as they enable real-time, automatic status detection. The proposed design integrates a sensor into the drainage tube to detect liquid flow using the Lorentz force. The sensor consists of a permanent magnet, a yoke, and a signal processing circuit. Mu-metal shields the magnet to prevent interference with surrounding circuits. Physiological saline solution is used as a substitute for bodily fluids. Sensor performance was evaluated via finite element analysis. The Lorentz force generated an average voltage of 11.07 μV when liquid was present, enabling detection of the flow status. The proposed sensor is non-invasive and features a clip design, allowing attachment and detachment from the drainage tube for reuse. Non-invasiveness ensures safety from infection, and reusability can reduce medical costs. This study proposes a sensor for monitoring peritoneal puncture status. By detecting liquid flow using the Lorentz force, the system enables real-time monitoring during the procedure. Full article

Background: Emergency rescuers frequently carry heavy equipment for extended periods, making musculoskeletal disorders a major occupational concern. Loading type and road slope play important roles in inducing physical fatigue; however, the assessment of physical fatigue under these conditions remains limited. Aim: This study aims to investigate physical fatigue under different loading types and road slope conditions using both electromyography (EMG) and eye movement metrics. In particular, this work focuses on eye movement metrics as a non-contact data source in comparison with EMG, which remains largely unexplored for physical fatigue assessment. Method: Prolonged load-bearing walking was simulated to replicate the physical demands experienced by emergency rescuers. Eighteen male participants completed experimental trials incorporating four loading types and three road slope conditions. Results: (1) Loading type and road slope significantly affected EMG activity, eye movement metrics, and perceptual responses. (2) Saccade time (ST), saccade speed (SS), and saccade amplitude (SA) exhibited significant differences in their rates of change across three stages defined by perceptual fatigue. ST, SS, and SA showed strong correlations with subjective fatigue throughout the entire load-bearing walking process, whereas pupil diameter demonstrated only a moderate correlation with subjective ratings. (3) Eye movement metrics were incorporated into multivariate quadratic regression models to quantify physical fatigue under different loading types and road slope conditions. Conclusions: These findings enhance the understanding of physical fatigue mechanisms by demonstrating the potential of eye movement metrics as non-invasive indicators for multidimensional fatigue monitoring in work environments involving varying loading types and road slopes. Full article

Breast cancer continues to be the most frequently diagnosed cancer among women worldwide and remains a leading cause of cancer-related mortality. Despite advances in imaging and biopsy-based approaches, current diagnostic methods are invasive, costly, and often insufficient to capture the molecular heterogeneity of tumors. Extracellular vesicles (EVs) have emerged as promising non-invasive biomarkers owing to their role in intercellular communication and their enrichment with tumor-specific cargo. This study conducted a systematic review and meta-analysis of published literature to investigate proteomic alterations in EVs derived from breast cancer samples. From an initial 1097 records screened, four eligible studies were identified, reporting 628 differentially expressed proteins, of which 38 were consistently observed across multiple datasets. Functional enrichment analyses revealed predominant localization of these proteins to vesicle-associated compartments and significant involvement in biological processes related to cell growth, immune regulation, and tumor progression. Pathway analysis further highlighted integrin-mediated interactions, platelet activation, and hemostasis pathways as key molecular mechanisms represented within breast cancer EVs. Overall, the findings reveal a distinct EV proteomic signature in breast cancer that could support early detection and patient monitoring through minimally invasive testing. Future large-scale and standardized studies are needed to validate these candidate proteins and advance EV proteomics toward clinical application in breast cancer management. Full article

Core body temperature is a critical physiological indicator for assessing and diagnosing animal health status. In bovines, continuously monitoring this metric enables accurate evaluation of their physiological condition; however, traditional rectal measurements are labor-intensive and cause stress in animals. To achieve intelligent, contactless temperature monitoring in cattle, we proposed a non-invasive method based on thermal imaging combined with environmental data fusion. First, thermal infrared images of the cows’ faces were collected, and the You Only Look Once (YOLO) object detection model was used to locate the head region. Then, the YOLO segmentation network was enhanced with the Online Convolutional Re-parameterization (OREPA) and High-level Screening-feature Fusion Pyramid Network (HS-FPN) modules to perform instance segmentation of the eye socket area. Finally, environmental variables—ambient temperature, humidity, wind speed, and light intensity—were integrated to compensate for eye socket temperature, and a random forest algorithm was used to construct a predictive model of rectal temperature. The experiments were conducted using a thermal infrared image dataset comprising 33,450 frontal-view images of dairy cows with a resolution of 384 × 288 pixels, along with 1471 paired samples combining thermal and environmental data for model development. The proposed method achieved a segmentation accuracy (mean average precision, mAP_50–95) of 86.59% for the eye socket region, ensuring reliable temperature extraction. The rectal temperature prediction model demonstrated a strong correlation with the reference rectal temperature (R² = 0.852), confirming its robustness and predictive reliability for practical applications. These results demonstrate that the proposed method is practical for non-contact temperature monitoring of cattle in large-scale farms, particularly those operating under confined or semi-confined housing conditions. Full article

The operational reliability of Insulated Gate Bipolar Transistor (IGBT) modules in demanding transportation applications, such as traction systems, is critically challenged by solder layer and bond wire failures under cyclic thermal stress. To address this, this paper proposes a novel health monitoring framework that innovatively synergizes micro-scale spatial thermal analysis with microsecond electrical dynamics inversion. The method requires only non-invasive temperature measurements on the module baseplate and utilizes standard electrical signals (load current, duty cycle, switching frequency, DC-link voltage) readily available from the converter’s controller, enabling simultaneous diagnosis without dedicated voltage or high-bandwidth current sensors. First, a non-invasive assessment of solder layer fatigue is achieved by correlating the normalized thermal gradient ($\nabla T_{\mathrm{P}}$) on the baseplate with the underlying thermal impedance ($Z_{\mathrm{JC}}$). Second, for bond wire aging, a cost-effective inversion algorithm estimates the on-state voltage ($V_{\mathrm{ce},\mathrm{on}}$) by calculating the total power loss from temperature, isolating the conduction loss ($P_{\mathrm{cond}}$) with the aid of a Foster-model-based junction temperature ($T_{\mathrm{J}}$) estimate, and finally computing $V_{\mathrm{ce},\mathrm{on}}$ at a unique current inflection point ($I_{\mathrm{C},\inf }$) to nullify $T_{\mathrm{J}}$ dependency. Third, the health states from both failure modes are fused for comprehensive condition evaluation. Experimental validation confirms the method’s accuracy in tracking both degradation modes. This work provides a practical and economical solution for online IGBT condition monitoring, enhancing the predictive maintenance and operational safety of transportation electrification systems. Full article

Background: Cellulite is a highly prevalent condition with dermal and subcutaneous alterations poorly captured by visual grading systems. Ultrasound has emerged as a non-invasive imaging modality capable of objectively quantifying morphological features relevant to cellulite. This systematic review evaluated the evidence on ultrasound for the diagnosis, structural characterization, and treatment monitoring of cellulite, identifying methodological limitations and research gaps. Methods: This systematic review (PROSPERO:CRD420251185486) followed the PRISMA statement. Searches were conducted in PubMed, Scopus, and CENTRAL up to November 2025. Risk of bias was evaluated using ROBINS-I and the Newcastle–Ottawa Scale. Results: Nine studies involving 785 participants were included. Ultrasound frequencies ranged from 12 to 35 MHz, with some scanners operating across broader bandwidths. Despite variability in devices, acquisition protocols, and clinical comparators, all studies consistently demonstrated that ultrasound quantifies key structural characteristics of cellulite. Diagnostic investigations reported moderate-to-strong correlations (r ≈ 0.31–0.64) between ultrasound-derived measures and clinical severity scores. Interventional studies showed measurable reductions in dermal and subcutaneous thickness, decreased adipose protrusion height, and improved dermal echogenicity across multiple treatment modalities. Ultrasound frequently detected microstructural remodeling not readily visible on clinical examination. Conclusions: Ultrasound is a valuable imaging modality for objectively characterizing cellulite and monitoring treatment-induced tissue remodeling. Standardized acquisition protocols, validated analytic criteria, and larger controlled studies are needed to support integration into routine dermatologic and esthetic practice. The quantitative and reproducible nature of ultrasound-derived parameters also provides a suitable foundation for future integration with data-driven and artificial intelligence–based image analysis frameworks. Full article

Angiostrongylus cantonensis (A. cantonensis) is the primary causative agent of human angiostrongyliasis and is widely distributed in Southeast Asia and China, with increasing reports from the Americas. Achatina fulica (A. fulica), Pomacea canaliculata (P. canaliculata), and slugs constitute established intermediate hosts of A. cantonensis, whereas Camaena hainanensis (C. hainanensis) has been newly reported as a host species in Hainan. A TaqMan quantitative PCR (qPCR) method assay targeting a novel genomic region of A. cantonensis was developed to detect infection in 150 snails collected from Hainan Province, China. The assay was employed to detect the parasite larvae across various snail tissues (lung sac, mucus, and foot), and its performance was compared with conventional lung sac microscopy. Out of the 120 A. fulica examined, 75 tested positive using the qPCR assay, yielding a significantly higher detection rate than lung-sac examination (p < 0.05). Significant differences were also observed in the positivity rates across the three snail tissues (lung sac, mucus, and foot) (p < 0.05), with the lung sac showing the highest rate of infection. Importantly, the detection of A. cantonensis DNA in snail mucus highlights its potential for development as a non-invasive diagnostic sample. Additionally, C. hainanensis was identified as a new host of A. cantonensis in Hainan, suggesting its possible contribution to parasite transmission. The newly developed qPCR assay demonstrated superior sensitivity (reflected by lower Ct values) compared with previously published TaqMan qPCR methods. The established qPCR method provides a sensitive and non-invasive tool for detecting A. cantonensis in snails, and can be applied for monitoring and early warning of parasite prevalence and transmission. Full article

Background: Brain–Computer Interfaces (BCIs) based on Steady-State Visually Evoked Potentials (SSVEPs) and Extended Reality (XR) offer promising solutions for highly wearable applications, but their classification performance can be affected by systematic effects in stimulus presentation. Novelty: This study introduces a novel online compensation method to compensate for systematic effects in the Refresh Rate (RR) of XR displays, enhancing SSVEP classification without requiring additional training or invasive measurements. Methods: A non-invasive monitoring module was incorporated into the developed BCI pipeline to measure frame rate variations in the XR display, allowing deviations between nominal RR and measured values to be automatically detected and compensated for. Classification performance was evaluated using Filter Bank Canonical Correlation Analysis (FBCCA). Statistical significance was assessed using Student’s t-test. Materials: Two datasets were used: a dataset based on Moverio BT-350, including 9 subjects, and a dataset based on HoloLens 2, including 30 subjects, all collected by the authors. Results: The proposed compensation method led to significant improvements in SSVEP classification accuracy, proportional to the magnitude of fps deviations. In some cases, classification accuracy increased by up to 300% relative to its original value. Statistical analyses confirmed the reliability of the results across subjects and datasets. Conclusions: These findings show that the proposed method effectively enhances SSVEP-based BCIs in XR environments and provides a robust foundation for practical applications requiring high reliability. Full article