Search Results (5,577)

Idiopathic pulmonary fibrosis (IPF) and autoimmune usual interstitial pneumonia (aUIP) share overlapping clinico-radiological features, complicating differential diagnosis. Electronic nose (eNose) technology characterizes exhaled breath profiles (“breathprints”) and may offer a non-invasive diagnostic approach in fibrotic interstitial lung diseases. To evaluate whether eNose breathprint analysis can discriminate between IPF and aUIP. In this cross-sectional study of 60 patients (34 IPF, 26 aUIP), breathprints were analyzed using principal component analysis (PCA, retaining eigenvalues > 1). Group differences were assessed via independent t-tests. Linear discriminant analysis (LDA) with leave-one-out cross-validation evaluated the discriminatory performance of PC combinations. PCA identified four principal components, with PC1 explaining 96% of the total variance. PC1 scores were significantly higher in aUIP compared to IPF (mean difference −0.53; 95% CI −1.04 to −0.02; p = 0.04); PC2-PC4 showed no significant differences (p > 0.3). LDA utilizing PC1 and PC3 achieved a cross-validated classification accuracy of 73.3% (95% CI 60.7–84.4, p < 0.05). eNose-derived breathprints showed preliminary discriminatory potential between IPF and autoimmune UIP, supporting further validation of this non-invasive adjunctive approach. Breathomics represents a promising non-invasive adjunctive tool for phenotyping fibrotic interstitial lung diseases, though larger validation studies integrating clinical and biological data are warranted. Full article

Background: Small-cell lung cancer (SCLC) represents an aggressive malignancy associated with a poor prognosis, underscoring the critical demand for enhanced monitoring methodologies. Circulating tumor DNA (ctDNA) constitutes a promising non-invasive biomarker; however, reports employing highly sensitive tumor-informed assays in SCLC remain scarce. This investigation aimed to assess the clinical utility of a personalized ctDNA monitoring strategy for predicting therapeutic outcomes and resistance in SCLC patients. Methods: This prospective observational study enrolled patients diagnosed with unresectable SCLC. Whole exome sequencing was conducted on baseline tumor specimens to design customized 16-plex multiplex polymerase chain reaction (PCR) panels. Serial blood samples were obtained at baseline, at six-week intervals during treatment, and upon disease progression. Detection of ctDNA-based minimal residual disease (MRD) was performed using a tumor-informed assay (Huajianwei^® bespoke MRD) with ultra-deep sequencing. Results: Among seven evaluable patients, the baseline ctDNA-MRD positivity rate was 100%. A significant positive correlation was observed between the baseline ctDNA levels and radiographic tumor burden (r = 0.821, 95% confidence interval [CI] 0.179–0.973, p = 0.034). Longitudinal analysis indicated that patients exhibiting an early decline in MRD levels demonstrated a non-significant trend toward superior progression-free survival (PFS) compared to those with an MRD increase. Though this between-group difference did not reach conventional statistical significance, it represented a trend-level finding (p = 0.0665, hazard ratio [HR] = 0.24, 95% CI: 0.02–3.19), with no definitive prognostic association confirmed in this pilot cohort. Notably, an elevation in MRD preceded radiographic progression by as much as 135 days in certain instances. Conclusions: This study shows that dynamic tumor-informed ctDNA-based MRD monitoring reflects tumor burden changes and may correlate with clinical outcomes in SCLC, supporting its potential to guide personalized treatment and facilitate earlier therapeutic interventions compared to conventional imaging techniques. Prospective multicenter validation is needed to confirm its clinical utility. Full article

Arrhythmia is a common and potentially life-threatening cardiovascular condition. Photoplethysmography (PPG) has emerged as a noninvasive alternative to electrocardiography for cardiac rhythm monitoring, yet most PPG-based methods remain limited to binary classification. In this study, a new deep learning approach is suggested for categorizing six arrhythmia types from PPG data: sinus rhythm (SR), premature ventricular contraction (PVC), premature atrial contraction (PAC), ventricular tachycardia (VT), supraventricular tachycardia (SVT), and atrial fibrillation (AF). The raw PPG signal is enhanced by extracting its first and second derivatives to capture morphological features not readily apparent in the original signal. A hybrid architecture, VGG-BiLSTM, is utilized, merging VGG convolutional layers for spatial features extraction with bidirectional long short-term memory layers for modeling temporal dependencies. A stratified data splitting strategy is further adopted to address class imbalance across arrhythmia types. A publicly available dataset containing 46,827 PPG segments from 91 individuals was employed to assess the effectiveness of the suggested technique. The method yielded an overall accuracy, sensitivity, specificity and F1 score of 88.7%, 78.5%, 97.6% and 80.5% correspondingly. Full article

Background: The early detection of prostate and testicular tumors remains challenging as standard diagnostic tools often lack sensitivity and produce ambiguous results. Seminal fluid is a biologically rich medium that closely reflects the state of male reproductive tissues and has therefore emerged as a promising source of non-invasive molecular biomarkers. Objective: This study aimed to critically evaluate the evidence regarding cell-free DNA, RNA, proteins and metabolites in seminal fluid, and to assess their potential for improving the early detection of male reproductive cancers. Methods: A systematic review was performed according to PRISMA guidelines. Comprehensive searches of the PubMed and Scopus databases were conducted to identify original clinical studies analyzing molecular biomarkers in seminal fluid from patients with prostate or testicular tumors. For each study, data were extracted on biomarker types, cohort characteristics, analytical methods and diagnostic performance. Results: Forty-two eligible studies were included, covering multiple biomarker classes. Most were observational, single-center investigations classified as level 3b evidence. Across the different types of biomarkers, seminal fluid was associated with tumor-associated molecular changes. Alterations in the concentration, fragmentation and methylation patterns of cell-free DNA (e.g., GSTP1, RARβ2, LGALS3 and OCT3/4) distinguished malignant from benign conditions with sensitivities of up to 80–100%. RNA-based markers, including microRNAs, small non-coding RNAs, and tRNA fragments, showed improved performance in several studies, with multimarker models achieving areas under the curve (AUCs) of 0.85–0.93. Proteomic analyses identified high-specificity candidates such as TGM4, AMACR, PROS1 and DKK3. Metabolomic profiling further strengthened the diagnostic potential; reduced seminal citrate outperformed prostate-specific antigen (AUC 0.748 vs. 0.548), and reproducible shifts in amino acid and lipid profiles were observed in testicular tumors. However, substantial heterogeneity in study design, patient selection, and analytical platforms was observed. Risk of bias varied, and large prospective validation cohorts were lacking. Conclusions: Current evidence suggests that seminal fluid contains molecular signals associated with tumors that could be used for diagnosis. However, the available data are predominantly exploratory and methodologically heterogeneous. Before seminal fluid-based biomarkers can be considered for routine clinical implementation, robust prospective studies with standardized protocols are required. Full article

Background: Liver biopsy remains the gold standard for staging chronic hepatitis B (CHB), yet it is invasive, costly, and associated with potential complications. There is a critical need for non-invasive, cost-effective biomarkers to monitor disease progression. This study aimed to evaluate the correlation between the Prognostic Nutritional Index (PNI) and Systemic Immune–Inflammatory Index (SII) with histological fibrosis stages and the Histological Activity Index (HAI) in patients with CHB. Methods: This retrospective study analyzed 274 patients diagnosed with CHB (HBsAg positivity > 6 months) who underwent liver biopsy at the University of Health Sciences, Kanuni Sultan Süleyman Training and Research Hospital between February 2016 and February 2022. Histopathological findings were staged using the Ishak fibrosis score and HAI. PNI and SII were calculated from peripheral blood parameters. Statistical discrimination power was assessed using Area Under the Receiver Operating Characteristic (AUROC) curves. Results: The cohort comprised 119 females (43.4%) and 155 males (56.6%), with a mean age of 45.25 ± 11.2 years. Mean values were 55.83 ± 5.33 for PNI and 494.37 ± 336.86 for SII. Fibrosis distribution showed 56.2% at stages F0–F1 and 43.8% at ≥F2. For fibrosis staging, SII demonstrated statistically significant but limited predictive ability for Ishak scores ≥F2, while PNI was significant for identifying advanced fibrosis (≥F4) (p < 0.05). SII showed moderate diagnostic performance for severe inflammation (HAI ≥12; AUROC = 0.848), although this finding should be interpreted cautiously. For lower HAI thresholds (≥6), both PNI and SII demonstrated poor discriminative ability (AUROC 0.5–0.6). Conclusions: Both indices were associated with histological parameters but showed limited overall diagnostic performance. SII appeared relatively better; however, this was descriptively observed without formal statistical comparison. These markers may provide complementary information but should not be used as standalone diagnostic tools. Full article

Background: Ultrasonography (US) has emerged as a non-invasive method for anatomical and functional evaluation of upper airway structures in adult obstructive sleep apnea (OSA). However, its role in severity stratification, dynamic assessment, elastographic characterization, and therapeutic monitoring remain to be investigated. Background/Objectives: The goal herein is thus to systematically review and synthesize available evidence on US assessment in adults with OSA, including structural parameters, dynamic measurements, correlation with the apnea–hypopnea index (AHI), integration with artificial intelligence, and evaluation of myofunctional therapy outcomes. Methods: A PRISMA-compliant systematic review of 19 studies (2007–2025) was conducted, evaluating US in adult patients with polysomnography-diagnosed OSA. Observational, pilot, case–control, and exploratory studies were included. Risk of bias was assessed using the National Institutes of Health Quality Assessment Tool for observational studies. Due to methodological heterogeneity, a structured qualitative meta-analytic synthesis was performed. Results: The tongue base was the most frequently studied structure. Increased tongue thickness, area, and stiffness were consistently associated with higher AHI. Elastography revealed increased intrinsic rigidity in patients with OSA. Dynamic US correlated with drug-induced sleep endoscopy findings and hyoid displacement. Machine learning integration improved severity prediction. A single study evaluated anatomical changes following myofunctional therapy, representing a nascent research area. US may become a complementary, non-invasive tool for anatomical and functional assessment of upper airway structures in adult OSA. Conclusions: Further standardization of acquisition protocols and well-designed longitudinal studies are needed to clarify the clinical role of US in phenotyping and therapeutic monitoring. Full article

Digital biomarkers derived from eye-tracking and facial expression hold significant potential for the non-invasive screening of cognitive decline (CD). However, existing approaches predominantly rely on single-task or feature engineering-based unimodal methods, which struggle to capture complex temporal behavioral patterns. While deep learning (DL) excels at extracting hierarchical features and intricate temporal dynamics from behavioral sequences, its application in this specific multimodal sensing domain remains exploratory. Addressing this gap, this study designed an assessment system integrating five multi-dimensional cognitive paradigms and collected eye-tracking and facial expression data from 20 healthy controls (HC) and 20 individuals with CD. For these multimodal sequences, we propose a deep neural network capable of multi-scale representation learning. By utilizing subspace exploration and multi-scale convolutions, this architecture extracts deep representations directly from data and incorporates a decision fusion mechanism to enhance diagnostic robustness. Experimental results demonstrate that our method achieves a 90% classification accuracy, outperforming machine learning models. Furthermore, statistical analyses conducted in this study validated several features associated with CD and also explored some novel potential behavioral patterns. This study confirms the feasibility of a DL framework based on eye-tracking and facial expression signals for identifying CD, providing a reference for developing objective and efficient digital screening tools. Full article

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

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

Salt stress poses a major environmental challenge that leads to ecological imbalance and reduced agricultural productivity globally. Sapium sebiferum, a highly valued ornamental and perennial woody oil species, shows promise for saline land utilization due to its natural salt stress adaptability. However, the underlying mechanisms remain largely unexplored. This study investigated the responses of S. sebiferum to salt stress by integrating RNA sequencing and Non-invasive Micro-test Technology (NMT). Comparative transcriptome analysis identified 693, 1061, and 1851 differentially expressed genes at 1 h, 3 h and 6 h after salt treatment, respectively. Functional analysis of DEGs revealed that genes related to ion binding, transmembrane transport, and signal transduction were significantly enriched. Notably, genes involved in calcium (Ca²⁺) and phytohormone signaling were altered, activating stress-response pathways. Furthermore, the dynamic effects of salt stress on nitrate (NO₃⁻) and ammonium (NH₄⁺) uptake were assessed. After salinity stress (150 mM NaCl), an increase in the net influx of NO₃⁻ was observed under the conditions of the assay, while the net flux of NH₄⁺ did not show a significant change. The differential expression of NRT genes suggests that NO₃⁻ may play a multifaceted role in salinity tolerance, potentially contributing to nutrition, ion homeostasis, and signaling pathways. The coordinated signaling network likely allows S. sebiferum to effectively cope with salinity stress and sustain physiological functions under challenging conditions. These findings provide valuable insights into the molecular basis of salt tolerance in S. sebiferum, thereby supporting sustainable practices in saline environments. Full article