Search Results (5,129)

Background: Coronary artery disease (CAD) is the leading cause of death worldwide. High-Density lipoprotein (HDL) is a well-established marker associated with CAD. The current research goes beyond the conventional HDL-C measurement in previous studies and dives into the functional intricacies of HDL. By understanding how HDL works, rather than just how much of it exists, we can better tailor diagnostic and therapeutic strategies for CAD and related conditions. Hence, the current study quantifies the serum levels of two novel HDL-associated markers, Paraoxonase-1 (PON-1) and Scavenger Receptor Class B Type 1 (SRB-1), in CAD cases vs. controls. Methods: A total of 92 subjects, including 69 CAD and 23 healthy controls, were included, based on the prevalence of the disease. Further, based on the severity of the disease, CAD cases were subcategorized as CAD-I, -II, and -III. Serum PON-1 and SRB-1 levels were measured and compared between patient and control groups. Results: The levels of PON-1 and SRB-1 (32.6 ng/mL and 12.49 ng/mL) were significantly lower in CAD patients vs. the healthy control, at 60.36 ng/mL and 15.85 ng/mL, respectively (p < 0.000). A further intergroup comparison showed a statistically significant difference between the CAT-I and -III for PON-1 (p < 0.025), the CAT-I and -III, and CAT-II and -III for SRB-1 (p < 0.000). The receiver operating characteristics (ROC) curve showed cutoff values of 48.20 ng/mL and 14.90 ng/mL for PON-1 and SRB-1. Conclusions: The current study found that serum levels of HDL-associated PON-1 and SRB-1 are significantly lower in CAD cases, and were also inversely related to the increasing severity of coronary artery disease. This inference implies that serum PON-1 and SRB-1 could be used as non-invasive tools for the identification of coronary atherosclerosis and risk assessment in CAD cases. Full article

BACKGROUND: Chronic hepatitis B and C infections are major causes of morbidity and mortality in end-stage kidney disease (ESKD) patients on hemodialysis (HD). The Fibrosis-4 (FIB-4) score is a non-invasive method to evaluate chronic liver disease. However, it is unclear whether there is a connection between the FIB-4 score and major adverse cardiovascular events (MACEs) and mortality in patients on HD. This study investigates the relationship between FIB-4 scores, MACEs, and mortality in HD patients. METHODS: A 5-year retrospective study included 198 HD patients with chronic hepatitis B and C from Chang Gung Memorial Hospital. FIB-4 scores were categorized into high (>2.071), middle (1.030~2.071), and low (<1.030) tertiles for cross-sectional analyses. MACEs and mortality were tracked longitudinally. RESULTS: Patients with high FIB-4 scores had lower hemoglobin and albumin levels. Cox multivariate analysis showed that high FIB-4 scores (aHR: 1.589) and diabetes mellitus (aHR: 5.688) were significant factors for all-cause mortality. The optimal FIB-4 score for 5-year mortality was 2.942. FIB-4 scores were not significant for predicting 5-year MACEs. CONCLUSIONS: High FIB-4 scores are associated with increased 5-year all-cause mortality risk in HD patients with chronic hepatitis virus infection. Full article

Decoding semantic concepts for imagination and perception tasks (SCIP) is important for rehabilitation medicine as well as cognitive neuroscience. Electroencephalogram (EEG) is commonly used in the relevant fields, because it is a low-cost noninvasive technique with high temporal resolution. However, as EEG signals contain a high noise level resulting in a low signal-to-noise ratio, it makes decoding EEG-based semantic concepts for imagination and perception tasks (SCIP-EEG) challenging. Currently, neural network algorithms such as CNN, RNN, and LSTM have almost reached their limits in EEG signal decoding due to their own short-comings. The emergence of transformer methods has improved the classification performance of neural networks for EEG signals. However, the transformer model has a large parameter set and high complexity, which is not conducive to the application of BCI. EEG signals have high spatial correlation. The relationship between signals from different electrodes is more complex. Capsule neural networks can effectively model the spatial relationship between electrodes through vector representation and a dynamic routing mechanism. Therefore, it achieves more accurate feature extraction and classification. This paper proposes a spatio-temporal capsule network with a self-correlation routing mechaninsm for the classification of semantic conceptual EEG signals. By improving the feature extraction and routing mechanism, the model is able to more effectively capture the highly variable spatio-temporal features from EEG signals and establish connections between capsules, thereby enhancing classification accuracy and model efficiency. The performance of the proposed model was validated using the publicly accessible semantic concept dataset for imagined and perceived tasks from Bath University. Our model achieved average accuracies of 94.9%, 93.3%, and 78.4% in the three sensory modalities (pictorial, orthographic, and audio), respectively. The overall average accuracy across the three sensory modalities is 88.9%. Compared to existing advanced algorithms, the proposed model achieved state-of-the-art performance, significantly improving classification accuracy. Additionally, the proposed model is more stable and efficient, making it a better decoding solution for SCIP-EEG decoding. Full article

The common octopus (Octopus vulgaris) is an excellent candidate for aquaculture diversification, due to its biological traits and high market demand. To ensure a high-quality product while maintaining welfare in captive environments, it is crucial to develop non-invasive methods for testing health biomarkers. Proteins found in skin mucus offer a non-invasive approach to monitoring octopus welfare. This study compares the protein profiles in the skin mucus of wild, aquarium-maintained, and senescent specimens to identify welfare biomarkers. A tandem mass tag (TMT) coupled with an Orbitrap Eclipse Tribrid mass spectrometer was used to create a reference dataset from octopus skin mucus, identifying 1496 non-redundant protein groups. Although similar profiles were observed, differences in relative abundances led to the identification of potential biomarkers, including caspase-3-like, protocadherin 4, deleted in malignant brain tumors, thioredoxin, papilin, annexin, cofilin and mucin-4 proteins. Some of these proteins also revealed potential as bioactive peptides. This investigation provides the most extensive analysis of the skin mucus proteome in the common octopus and is the first to explore how aquarium maintenance and senescence alter the mucus proteome. This research highlights the potential of skin mucus protein/peptides as non-invasive monitoring biomarkers in cultured animals. Full article

This study aimed to investigate the association between metabolic lipid computed tomography (CT) features and adipose differentiation-related protein (ADFP) expression in clear cell renal cell carcinoma (ccRCC), providing insights into non-invasive methods for assessing ADFP expression and tumor characteristics. This study utilized data from The Cancer Genome Atlas and the Cancer Imaging Archive to analyze genetic alterations and imaging characteristics in ccRCC patients. Tumoral Hounsfield units (HU) analysis and quantification of abdominal adipose tissue compartments were performed using CT images. Statistical analyses were conducted to compare tumoral HU values according to ADFP gene expression and World Health Organization/International Society of Urological Pathology (WHO/ISUP) tumor grade, as well as to explore correlations between tumoral HU values and adipose tissue quantification. Among the 174 identified patients, those with ADFP gene expression showed significantly lower minimum tumoral HU values in low-grade cancers compared to high-grade cancers. Similarly, patients with low-grade cancers expressing ADFP exhibited lower minimum tumoral HU values compared to those without ADFP expression. Negative correlations were observed between minimum tumoral HU values and visceral adipose tissue, subcutaneous adipose tissue, and total adipose tissue in both ccRCC patients with and without ADFP expression. This study reveals a significant association between metabolic lipid CT features and ADFP expression in ccRCC patients. Lower minimum tumoral HU values, suggestive of higher intracellular lipid accumulation, were observed in tumors with low WHO/ISUP grade and ADFP expression. Full article

Background/Objectives: Diabetic retinopathy (DR) is a common diabetes complication that can lead to blindness through vision-threatening complications like clinically significant macular edema and proliferative retinopathy. Identifying eyes at risk of progression using non-invasive methods could help develop targeted therapies to halt diabetic retinal disease progression. Methods: A set of 82 imaging and systemic features was used to characterize the progression of nonproliferative diabetic retinopathy (NPDR). These features include baseline measurements (static features) and those capturing the temporal dynamic behavior of these static features within one year (dynamic features). Interpretable models were trained to distinguish between eyes with Early Treatment Diabetic Retinopathy Study (ETDRS) level 35 and eyes with ETDRS levels 43–47. The data used in this research were collected from 109 diabetic type 2 patients (67.26 ± 2.70 years; diabetes duration 19.6 ± 7.26 years) and acquired over 2 years. Results: The characterization of the data indicates that NPDR progresses from an initial stage of hypoperfusion to a hyperperfusion response. The performance of the classification model using static features achieved an area under the curve (AUC) of the receiver operating characteristics equal to 0.84 ± 0.07, while the model using both static and dynamic features achieved an AUC of 0.91 ± 0.05. Conclusion: NPDR progresses through an initial hypoperfusion stage followed by a hyperperfusion response. Characterizing and automatically identifying this disease progression stage is valuable and necessary. The results indicate that achieving this goal is feasible, paving the way for the improved evaluation of progression risk and the development of better-targeted therapies to prevent vision-threatening complications. Full article

Polyethylene terephthalate (PET) is one of the most produced plastic materials in the world. The emergence of microplastics and nanoplastics (MPs/NPs) as a significant environmental contaminant has become a matter of increasing concern. While the toxicological effects of PET NPs have been widely researched, there is a lack of methodologies for studying their accumulation. The present study introduces a novel method to monitor the distribution of PET NPs in germinating wheat (Triticum aestivum L.) seeds. This involves the functionalization of superparamagnetic iron oxide nanoparticles (SPIONs) with PET NPs (PET–fSPIONs) coupled with magnetic resonance microimaging (µMRI) to provide insight into their distribution within the seed. The present study has demonstrated that PET–fSPIONs accumulate in specific regions of germinating wheat seeds, including the shoot apical meristem, the radicle, the coleoptile, the plumule, and the scutellum. Furthermore, the accumulation of PET–fSPIONs has been shown to exert a discernible effect on spin–spin relaxation (T₂), as observed via MRI and quantitative T₂ relaxation time analysis. The accumulation of PET NPs in embryo regions was also confirmed by SEM. Diffusion-weighted magnetic resonance imaging (DW-MRI) and non-invasive chemical shift imaging analyses demonstrated that PET NPs resulted in restricted diffusion within the highlighted areas, as well as an impact on lipid content. Our study reveals that using µMRI with fSPIONs provides a non-invasive method to monitor the biodistribution of PET nanoparticles in wheat seeds. Additionally, it offers valuable insights into the microstructural interactions of PET. Full article

Neuromodulatory subcortical systems (NSSs) are monoaminergic and cholinergic neuronal groups that are markedly and precociously involved in the pathogenesis of many neurodegenerative disorders (NDDs), including Parkinson’s and Alzheimer’s diseases. In humans, although many tools have been developed to infer information on these nuclei, encompassing neuroimaging and neurophysiological methods, a detailed and specific direct evaluation of their cellular features in vivo has been difficult to obtain until recent years. The development of induced pluripotent stem cell (iPSC) models has allowed research to deeply delve into the cellular and molecular biology of NSS neurons. In fact, iPSCs can be produced easily and non-invasively from patients’ fibroblasts or circulating blood monocytes, by de-differentiating those cells using specific protocols, and then be re-differentiated towards neural phenotypes, which may reproduce the specific features of the correspondent brain neurons (including NSS ones) from the same patient. In this review, we summarized findings obtained in the field of NDDs using iPSCs, with the aim to understand how reliably these might represent in vitro models of NSS. We found that most of the current literature in the field of iPSCs and NSSs in NDDs has focused on midbrain dopaminergic neurons in Parkinson’s disease, providing interesting results on cellular pathophysiology and even leading to the first human autologous transplantation. Differentiation protocols for noradrenergic, cholinergic, and serotoninergic neurons have also been recently defined and published. Thus, it might be expected that in the near future, this approach could extend to other NSSs and other NDDs. Full article

Endometrial cancer is becoming increasingly common, highlighting the need for improved diagnostic methods that are both effective and non-invasive. This study investigates the use of urinary fluorescence spectroscopy as a potential diagnostic tool for endometrial cancer. Urine samples were collected from endometrial cancer patients (n = 77), patients with benign uterine tumors (n = 23), and control gynecological patients attending regular checkups or follow-ups (n = 96). These samples were analyzed using synchronous fluorescence spectroscopy to measure the total fluorescent metabolome profile, and specific fluorescence ratios were created to differentiate between control, benign, and malignant samples. These spectral markers demonstrated potential clinical applicability with AUC as high as 80%. Partial Least Squares Discriminant Analysis (PLS-DA) was employed to reduce data dimensionality and enhance class separation. Additionally, machine learning models, including Random Forest (RF), Logistic Regression (LR), Support Vector Machine (SVM), and Stochastic Gradient Descent (SGD), were utilized to distinguish between controls and endometrial cancer patients. PLS-DA achieved an overall accuracy of 79% and an AUC of 90%. These promising results indicate that urinary fluorescence spectroscopy, combined with advanced machine learning models, has the potential to revolutionize endometrial cancer diagnostics, offering a rapid, accurate, and non-invasive alternative to current methods. Full article

Objectives: This systematic review aimed to analyse the published evidence for the use of non-invasive methods for the early detection of oral squamous cell carcinoma (OSCC) and oral potentially malignant disorders (OPMDs). Methods: The literature was systematically searched through several databases: PubMed, Cochrane Library, and Web of Science. Additional exploration was performed through cross-checks on the bibliographies of selected reviews. The inclusion criteria involved studies assessing the application of non-invasive tests on humans in the screening, diagnosis, or surveillance of OSCC or OPMDs and reporting sensitivity (SE) and specificity (SP). The Newcastle–Ottawa scale (NOS) was applied to assess the quality of the studies included. Results: The search strategy resulted in 8012 preliminary records. After a duplicate check, 116 titles remained. After abstract analysis, 70 papers remained. After full text analysis, only 54 of the 70 papers fit the inclusion criteria (28 were original articles and 26 were reviews). Those 26 reviews were used to manually search for further original articles. From this last search, 33 original articles were found. Thus, a total of 61 original studies were included and investigated. Findings from this systematic review indicate useful information, such as a description of the mechanisms, ease of use, limitations, and SE and SP values, to drive the choice of the optimal minimally invasive method to be utilized as an adjunctive tool to examine the suspicious lesions. Conclusions: Each of the analysed tools can be improved or implemented, considering their high SE and low SP. Despite advancements, incisional biopsy continues to be the gold standard for the definitive diagnosis of oral cancer and precancerous lesions. Further research and development are essential to improving the sensitivity, specificity, and reliability of non-invasive tools for widespread clinical application. Full article

The Varroa destructor is the most significant bee parasite and the greatest threat to bee health all around the world. Due to its hidden lifestyle, detection within the brood cell is only possible through invasive techniques. Enhancing detection methods is essential for advancing research on population dynamics, spread, selection efforts, and control methodologies against the mite. In our study, we employed infrared imaging to measure the thermal differences in parasite and intact Apis mellifera worker broods. Experiments were conducted over two years at the MATE Kaposvár Campus in Hungary involving five beehives in 2022 and five beehives in 2023. A FLIR E5-XT WIFI handheld infrared camera was used to create a heat map of capped brood frames. Our results indicate that the resolution of these cameras is sufficient to provide detailed IR images of a bee colony, making them suitable to detect temperature differences in intact and Varroa parasitized capped brood cells. Mite parasitism causes a time-dependent and sustained temperature increase in developing bee pupae, observable regardless of mite number. Our work demonstrates two different heating patterns: hotspot heating and heating cells that are responsible for the elevated temperature of the Varroa-infested cells as a social fever response by the worker bees. Based on our results, future research combined with AI-based image evaluation software could offer beekeepers and researchers practical and valuable tools for high-throughput, non-invasive Varroa detection in the field. Full article

Bacterial infections and cancers are important issues in public health around the world. Currently, Western medicine is the most suitable approach when dealing with these issues. “Antibiotics” and “Corticosteroids” are the Western medicines used for bacterial infection. “Chemotherapy drugs”, “surgery”, and “radiotherapy” are common techniques used to treat cancer. These are conventional treatments with many side effects. PDT is a non-invasive and effective therapy for bacterial infection and cancer diseases. Methods: Nine electronic databases, namely WanFang Data, PubMed, Science Direct, Scopus, Web of Science, Springer Link, SciFinder, and China National Knowledge Infrastructure (CNKI), were searched to conduct this literature review, without any regard to language constraints. Studies focusing on the photodynamic actions of hydrogel and Resveratrol were included that evaluated the effect of PDT against bacteria and cancer. All eligible studies were analyzed and summarized in this review. Results: Resveratrol has antibacterial and anticancer effects. It can also act as PS in PDT or adjuvant but has some limitations. This is much better when combined with a hydrogel to enhance the effectiveness of PDT in the fight against bacteria and cancer. Conclusions: Resveratrol combined with hydrogel is possible for PDT treatment in bacteria and cancer. They are compatible and reinforce each other to increase the effectiveness of PDT. However, much more work is required, such as cytotoxicity safety assessments of the human body and further enhancing the effectiveness of PDT in different environments for future investigations. Full article

Drug delivery to the ocular system is affected by anatomical factors like the corneal epithelium, blinking reflex, aqueous blood barrier, and retinal blood barrier, which lead to quick removal from the site and inefficient drug delivery. Developing a drug delivery mechanism that targets specific eye tissue is a major hurdle for researchers. Our study examines the challenges of drug absorption in these pathways. Hydrogels have been researched as a suitable delivery method to overcome some obstacles. These are developed alone or in conjunction with other technologies, such as nanoparticles. Many polymer hydrogel nanoparticle systems utilizing both natural and synthetic polymers have been created and investigated; each has pros and cons. The complex release mechanism of encapsulated agents from hydrogel nanoparticles depends on three key factors: hydrogel matrix swelling, drug-matrix chemical interactions, and drug diffusion. This mechanism exists regardless of the type of polymer. This study provides an overview of the classification of hydrogels, release mechanisms, and the role of controlled release systems in pharmaceutical applications. Additionally, it highlights the integration of nanotechnology in ocular disease therapy, focusing on different types of nanoparticles, including nanosuspensions, nanoemulsions, and pharmaceutical nanoparticles. Finally, the review discusses current commercial formulations for ocular drug delivery and recent advancements in non-invasive techniques. The objective is to present a comprehensive overview of the possibilities for enhancing ocular medication delivery through hydrogel nanoparticle systems. Full article

Cardiovascular diseases (CVD) remain the leading cause of mortality among older adults. Early detection is critical as the prognosis for advanced-stage CVD is often poor. Consequently, non-invasive diagnostic tools that can assess hemodynamic function, particularly of the aorta, are essential. Computational fluid dynamics (CFD) has emerged as a promising method for simulating cardiovascular dynamics efficiently and cost-effectively, using increasingly accessible computational resources. This study developed a CFD model to assess the aorta geometry using tetrahedral and polyhedral meshes. A healthy aorta was modeled with mesh sizes ranging from 0.2 to 1 mm. Key hemodynamic parameters, including blood pressure waveform, pressure difference, wall shear stress (WSS), and associated wall parameters like relative residence time (RRT), oscillatory shear index (OSI), and endothelial cell activation potential (ECAP) were evaluated. The performance of the CFD simulations, focusing on accuracy and processing time, was assessed to determine clinical viability. The CFD model demonstrated clinically acceptable results, achieving over 95% accuracy while reducing simulation time by up to 54%. The entire simulation process, from image construction to the post-processing of results, was completed in under 120 min. Both mesh types (tetrahedral and polyhedral) provided reliable outputs for hemodynamic analysis. This study provides a novel demonstration of the impact of mesh type in obtaining accurate hemodynamic data, quickly and efficiently, using CFD simulations for non-invasive aortic assessments. The method is particularly beneficial for routine check-ups, offering improved diagnostics for populations with limited healthcare access or higher cardiovascular disease risk. Full article

Digital holography has transformative potential for the measurement of stacked-chip microstructures due to its non-invasive, single-shot, full-field characteristics. However, significant light scattering and diffraction at steep edges in step microstructures cause the batwing effect, leading to measurement errors. Herein, we propose a standard-deviation-based adaptive median filter to eliminate batwing effects in step microstructure measurement using digital holography. The standard deviation determines the positions of the steps and the range of the batwing effect. During filtering, the filter window size varies: it adjusts according to the center’s position within the batwing effect range and reduces outside this range to prevent distortion in other regions. Filtering weights are set to maintain information integrity while using larger filter windows. Experiments on the Standard Resolution Target USAF 1951 and the standard step height target show that our method successfully eliminates batwings while preserving the integrity of the remaining profile. Full article