Search Results (25,006)

This study is dedicated to the application of neural network technologies for determining aeration parameters in order to predict the efficiency of flotation separation. Within the framework of the research, digital technology solutions were actively employed, including a neural network for segmentation at the stage of determining the granulometric characteristics of bubbles and a convolutional neural network module for determining the froth layer height. An analysis was conducted to examine the variation in the statistical parameter d₃₂, which characterizes the bubble size distribution, as a function of flotation time and measurement height. The analysis revealed that the d₃₂ values determined by neural network processing remained within the range of acceptable dispersion and are therefore suitable for subsequent analytical procedures. Furthermore, a comparative evaluation of the obtained size distributions indicated the absence of statistically significant differences between the neural network measurements and manually labelled data with a p-value equal to 0.64. A neural network for object detection was used to record the height of the froth layer during the experiment to obtain a time series, that were subsequently processed with data processing approaches including Savitzky–Golay and Singular Spectra Analysis. Based on the analysis of the sum of the obtained dependences, a criterion is proposed and modeled for evaluating the selectivity of frother by connecting the diameter of bubble in pulp and bubble in froth. Based on the modeling results, it was determined that the optimal range of bubble sizes and froth size ratios for MIBC is constrained to d₃₂ values ranging from 1.058 to 1.089 mm, with the ratio of froth bubble radius to d₃₂ ranging from 1.302 to 2.098, depending on the floatability ratios of the respective fractions. When employing OPF, the values for d₃₂ fall within the interval of 0.868 to 1.113 mm, while the Dₓ parameter ranges from 0.559 to 0.931. Full article

Background: Bone Mineral Density (BMD) plays a crucial role in diagnosing osteoporosis, and early detection is essential to preventing complications such as osteoporotic fractures. However, access to dual-energy X-ray absorptiometry (DXA) screening remains limited in many healthcare settings. Objective: This study presents a fully automated artificial intelligence pipeline for BMD prediction from lumbar spine radiographs to enable opportunistic osteoporosis screening. Methods: The proposed system integrates automatic vertebral segmentation and a machine learning-based regression model for BMD prediction. A YOLO-based instance segmentation model was trained to automatically segment four lumbar vertebrae, achieving a high Intersection over Union (IoU) of 0.9. Radiomic features were extracted from the segmented vertebrae to capture advanced image characteristics and combined with clinical features from 2875 female patients. An eXtreme Gradient Boosting (XGBoost) regressor was trained to provide opportunistic BMD estimation. Results: The model achieved a mean absolute percentage error (MAPE) of 6% for BMD prediction. A classification model built from segmented vertebrae distinguished between osteoporosis, osteopenia, and normal bone with approximately 90% accuracy. Strong agreement between predicted and ground-truth BMD values was confirmed using Pearson correlation coefficient and Bland–Altman analysis. Conclusions: The proposed fully automated system demonstrates strong agreement with DXA measurements and potential for opportunistic osteoporosis screening in settings with limited DXA access. Further validation and refinement are needed to achieve clinical-grade precision for diagnostic applications. Full article

Background/Objectives: Trained innate immunity refers to the enhanced responsiveness of innate immune cells, particularly macrophages, following exposure to stimuli such as β-glucan or zymosan, enabling improved defense against unrelated pathogens. This phenomenon has been widely investigated to better understand host–pathogen interactions and to support the development of improved infection control strategies. This study evaluated whether these training stimuli could enhance the protective efficacy of attenuated or inactivated vaccine models against Brucella ovis and Listeria monocytogenes infection. Methods: Trained innate immunity was induced in vivo using β-glucan or zymosan, and seven days later mice were vaccinated with attenuated or gamma-irradiated formulations and subsequently challenged with B. ovis or L. monocytogenes. Vaccine-induced protection and immune responses were assessed through multiple experimental approaches. Results: β-glucan significantly reduced bacterial infection in vitro in bone-marrow-derived macrophages and in vivo in target organs compared with zymosan. Although β-glucan did not enhance the efficacy of the attenuated B. ovis ΔabcBA vaccine, it markedly reduced bacterial colonization in mice vaccinated with gamma-irradiated B. ovis. β-glucan also did not improve the efficacy of the gamma-irradiated L. monocytogenes vaccine; however, 50% of the trained and vaccinated mice showed no detectable bacterial recovery. Increasing the number of β-glucan doses negatively affected infection control, suggesting that overstimulation may impair trained immunity. Conclusion: Trained innate immunity enhances the protective effect of inactivated experimental vaccines against B. ovis and L. monocytogenes, while exerting a detrimental influence on the efficacy of a live attenuated B. ovis vaccine model. Full article

Background/Objectives: Hyperspectral imaging (HSI) facilitates noninvasive assessment of tissue perfusion in patients with peripheral arterial disease. However, available studies are either based on small cohorts and provide no comparison to standard methods or only one-time measurements. Methods: In this prospective cohort study, assessment of tissue perfusion with transcutaneous oxygen pressure (TcPO2) measurement and HSI before (1 day) and after revascularization (1–3 days) in patients with Rutherford category 3–6 was performed. The primary endpoint was change in tissue perfusion evaluated with the different methods. HSI and TcPO2 were correlated with clinical improvement after revascularization. Results: Significant improvement in the perfusion was detected by tissue oxygenation in the microcirculation (StO2; improvement +12%, mean difference 5 ± 15.9, p < 0.001) and near-infrared spectroscopy (NIR; improvement +9%, mean difference 3.7 ± 7.1, p < 0.001), but not with the tissue hemoglobin index (THI; mean difference +0.8 ± 10.3, p = 0.428). A high number of worse or unchanged HSI measurements despite successful revascularization was detected. A significant improvement of TcPO2 after revascularization (mean difference +16.2 ± 27.7 mmHg, p < 0.001), consistent with clinical improvement, was detected. No correlation of the HSI parameters with TcPO2 or clinical symptoms could be seen. Conclusions: Significant improvement of StO2, NIR and TcPO2 values was detected after successful revascularization; however, no correlation of HSI parameters with TcPO2 or clinical results could be observed. Furthermore, the substantial rate of lower or unchanged HSI parameters despite clinical improvement and higher TcPO2 values calls the validity and clinical relevance of TIVITA^®-based HSI measurements for postoperative tissue perfusion improvement into question. Full article

This paper introduces VERA (Vision Expert Real Analysis), a privacy-supporting cyber-physical framework designed for real-time data collection and visual analysis in healthcare environments. VERA limits exposure to identifiable RGB content by ensuring that annotators interact only with non-identifiable edge-based representations, while original images remain encrypted at rest using AES-CFB, with integrity verification performed before in-memory decryption. The system integrates edge-based obfuscation, secure annotation, in-memory decryption, and dynamic data augmentation to train YOLO-based person detection models without compromising patient privacy. Experimental results on a curated COCO subset show that VERA enables effective person detection, improving mean Average Precision (mAP) from an intentionally minimal baseline of 0.61 percent to 99.94 percent after full training and augmentation. This baseline is used solely to illustrate the contribution of the secure data preparation pipeline and is not intended to represent a fully optimized YOLO configuration. The results demonstrate that privacy-supportive workflows can maintain strong model performance while aligning with data protection practices common in regulated environments. Although this work focuses on person detection as a foundational stage, the VERA architecture is designed to support future extensions toward privacy-preserving Human Activity Recognition (HAR) tasks in clinical and assisted-living settings. Full article

Background/Objectives: Extranodal NK/T-cell lymphoma, nasal type (ENKTCL-NT), is a rare and extremely aggressive subtype of non-Hodgkin lymphoma that most frequently involves the nasal cavity and upper aerodigestive tract. Primary isolated oral manifestation is exceptionally uncommon and may mimic odontogenic or infectious diseases, delaying diagnosis. We report a case of ENKTCL-NT presenting initially as a destructive oral lesion without sinonasal involvement at diagnosis. Methods: A 32-year-old man with progressive palatal ulceration underwent clinical and imaging assessment (panoramic radiography and staging ^18F-FDG PET–CT) and repeated biopsies. Diagnosis was established using histopathology (H&E), immunohistochemistry (T-cell markers and cytotoxic profile), EBV detection by EBER in situ hybridization, and T-cell receptor gamma (TCRG) gene rearrangement analysis. Results: The lesion presented as a hemorrhagic, ulcerative palatal destruction covered by pseudomembranous exudate and was complicated by fungal infection, periostitis, and severe dental inflammatory foci, contributing to diagnostic delay. Histopathological examination revealed extensive necrosis with a dense atypical lymphoid infiltrate; angiocentric and angiodestructive growth was identified in one biopsy specimen. Tumor cells expressed T-cell markers (CD2, CD3, CD5, CD7; heterogeneous) and cytotoxic markers (TIA-1) and showed CD30 and CD56 positivity, with EBV positivity confirmed by EBER in situ hybridization. Molecular analysis demonstrated monoclonal TCRG rearrangement, and Ki-67 indicated high proliferative activity. Initial PET–CT demonstrated an intensely FDG-avid, locally invasive lesion without distant organ involvement. The patient was treated with L-asparaginase-based SMILE chemotherapy followed by radiotherapy (50 Gy), achieving marked initial clinical improvement and partial metabolic response; however, systemic relapse subsequently occurred with refractory disease despite salvage therapy and immunotherapy. Conclusions: This case highlights the substantial diagnostic challenge posed by isolated oral extranodal NK/T-cell lymphoma, nasal type, which may closely mimic benign inflammatory or infectious conditions and lead to significant diagnostic delay. Persistent, progressive, or therapy-resistant oral ulcerations should prompt early consideration of hematologic malignancy. Timely biopsy with comprehensive immunophenotyping, EBV testing, and close multidisciplinary collaboration are essential for accurate diagnosis and may contribute to earlier diagnosis and improved patient outcomes in these rare and atypical presentations. Full article

To address the periodic impacts and amplitude-modulated high-frequency resonance phenomena caused by bearing faults in rotating machinery, this paper proposes a detection method. The core innovation lies in: firstly, constructing a composite fault feature index (CFFI) that integrates normalized kurtosis and fuzzy entropy, which synchronously quantifies the fault impact intensity and periodic structure, and serves as an optimization objective; secondly, definining a spectral energy retention rate (SERR) that includes both the full spectrum and characteristic frequency bands to evaluate the denoising effect and fault feature retention, respectively. Based on this, the method adaptively determines the Variational Mode Decomposition (VMD) parameters through the Triangular Topology Aggregation Optimizer (TTAO), and uses Dynamic Weighted Center Clustering (DWCC) to screen key IMFs containing fault-envelope information. On the IMS bearing dataset, the SERR of the reconstructed signal is 0.21356, which is higher than the actual collected signal value of 0.22465, with a relative error of 4.9%, indicating a higher reconstruction accuracy. These quantitative results indicate that CFFI-guided optimization enhances impulsive and periodic fault components while maintaining stable feature-band retention. This approach is suitable for real-world equipment monitoring and exhibits strong engineering applicability. Full article

Neutrophils are the most numerous population of peripheral blood leukocytes and play a key role in innate immunity, participating in antibacterial, antifungal, antiviral, and antitumor responses. Their activity can be modulated by endogenous and exogenous factors, including pesticides, among which fungicides such as the commonly used imazalil (IMZ) constitute a significant group. The objective of this study was to assess the effect of IMZ (at an environmental dose of 0.07 ng/mL, as well as 10- and 100-fold higher doses) on selected functions of neutrophils. This study demonstrated that neutrophils incubated with IMZ at a dose detectable in the serum, exhibited lower phagocytotic capacity. In addition, at a 10-fold higher dose, this compound reduced the chemotactic capacity of neutrophils and led to increased activity of NADPH oxidase in these cells. Furthermore, it was observed that at the highest concentration used in this study IMZ intensified the production of nitric oxide. The exposure of neutrophils—the first line of defense—to IMZ affected their locomotion and pathogen-eliminating function. Moreover, the response of neutrophils was not proportionate to the concentration of IMZ used in the study. Full article

Background/Objectives: Deficits in auditory change detection are well-known in psychiatric disorders such as schizophrenia. An abrupt change in sound feature during periodic sounds elicits both evoked potentials and a transient change in neural oscillations. Both of these cerebral responses are thought to reflect the automatic change detection. However, the similarities and dissimilarities between these cerebral responses are unclear. To clarify them, we compared the temporal dynamics of evoked potentials and low gamma oscillations under a paired-pulse paradigm. Methods: Healthy adults (n = 21) participated. The stimulus was a 2 s sound consisting of a train of 25 ms pure tones. The sound pressure was increased by 15 dB twice within a 600 ms interval. Electroencephalographic signals were recorded from Fz and Cz electrodes referenced to linked mastoids. The peak (N100)-to-peak (P200) amplitude and the inter-trial phase coherence (ITPC) of low gamma oscillations were analyzed. Results: Auditory steady-state responses were evoked around 40 Hz. An abrupt change in sound pressure transiently decreased the ITPC of the oscillations at 40 Hz, whereas it increased the ITPC at the remaining frequencies. Unlike the change-related potentials, the degree of ITPC responses did not differ between the two changes. Conclusions: The synchrony of low gamma oscillations transiently responded to an abrupt increase in sound pressure but did not show paired-pulse suppression. This novel neurophysiological approach enables a focus on the neural change detection from multiple angles, which could be useful for investigations of psychiatric disorders. Full article

Background/Objectives: The aberrant epigenetic landscape of cancer cells has attracted wide attention, motivating the search for new epigenetically active drugs both for anticancer therapy and for overcoming the drug resistance promoted by epigenetic changes. The use of epi-drugs in cancer therapy requires consideration of the influence of applied treatment on epigenetic regulation of gene expression. Therefore, it is reasonable to screen epigenetically active compounds among the drugs widely used in clinical oncology. Methods: We applied the HeLa TI cell-based assay to analyze the epigenetic activity of 40 drugs including 22 chemotherapeutic, 2 immunotherapeutic, 13 targeted, and 3 palliative agents. Reactivation of the epigenetically silenced GFP reporter gene integrated into the genome of HeLa TI cells was assessed using flow cytometry. Results: Statistically significant increases in the proportions of GFP-positive cells were demonstrated for the alkylating agent chlorambucil; the antimetabolites cytarabine, fluorouracil, gemcitabine, and pemetrexed; the platinum-based compounds cisplatin, and oxaliplatin; the topoisomerase inhibitor topotecan; and the antimicrotubule agents docetaxel, vincristine, and eribulin. Epigenetic activity was also detected for the targeted-therapy agents AZD8055, wortmannin, and cetuximab, as well as for the corticosteroid dexamethasone. Thus, epigenetic activity was revealed for 15 drugs widely used in cancer therapy, which possess different modes of action. Conclusions: Our findings show that many anticancer therapy agents modulate the epigenetic landscape of cancer cells, providing a rationale for expanding their therapeutic applications and enhancing the efficacy of combination strategies by overcoming epigenetically driven chemoresistance. Full article

Background/Objectives: Diagnostic evaluation and management of nontraumatic osteonecrosis of the femoral head (ONFH) vary substantially. This systematic review was conducted to inform development of the Association Research Circulation Osseous (ARCO) clinical practice guideline for diagnosis and treatment of ARCO stages I to III ONFH. Methods: We searched MEDLINE, EMBASE, Web of Science, SCOPUS, Global Index Medicus, and the Cochrane Library for studies evaluating imaging modalities and treatments for adult ONFH. We assessed risk of bias using the QUADAS-2, the ROB-2, and the ROBINS-I tools; conducted meta-analyses using random-effects regression; and evaluated certainty of evidence using GRADE methodology. Results: Among 36 included studies, 18 addressed diagnostic test accuracy and 18 addressed comparative effectiveness of treatments. Magnetic resonance imaging (MRI) demonstrated the highest pooled sensitivity (0.91; 95% confidence interval (CI), 0.87 to 0.94) and specificity (0.96; 95% CI, 0.87 to 0.99) for ONFH diagnosis. Bone marrow edema and grade 2+ joint effusion on MRI differentiated symptomatic versus asymptomatic disease. Computed tomography and MRI better detected subchondral fractures than plain radiography. Very low-grade evidence suggested lower rates of femoral head collapse with core decompression plus bone marrow concentrate compared with core decompression alone (pooled relative risk [RR], 0.55; 95% CI, 0.36 to 0.83), and with vascularized versus non-vascularized bone grafting (RR, 0.35; 95% CI, 0.14 to 0.84) over a ≤5-year follow-up. Based on three non-comparative case series, osteotomies might have a lower risk of collapse over a 10- to 20-year follow-up, but this needs to be evaluated in future comparative research. Inconsistent outcome reporting hindered treatment outcome pooling. There were no comparative studies that evaluated observation only versus intervention in asymptomatic disease or strategies for monitoring treatment response. Conclusions: Evidence supporting optimal imaging modalities and early joint-preserving interventions remains limited and predominantly observational, underscoring the need for high-quality comparative studies with consistently defined core outcomes to guide clinical decision-making. Full article

Early identification of the risk of malignant transformation in oral potentially malignant disorders (OPMDs) is critical for improving outcomes in oral squamous cell carcinoma (OSCC). This comprehensive review examines immunological biomarkers obtained from minimally invasive oral cytobrush (OCB) specimens for the early detection of OSCC within a precision medicine framework. The objectives were to (1) identify and characterise key immunological biomarkers associated with early oral carcinogenesis; (2) evaluate the diagnostic utility of OCB sampling for detecting these biomarkers; and (3) explore the potential of OCB-based profiling to support personalised screening and patient management. The review highlights the potential advantages of OCB compared with conventional diagnostic methods, as reported in the literature, particularly its ability to capture early malignant changes through immunological analysis. Evidence is discussed for biomarker pathways related to cell-cycle and differentiation dysregulation (p53, Ki-67, CKs), inflammation-driven epithelial transformation (IL-1β, IL-6, IL-8, TNF-α), and immune suppression and checkpoint activation (PD-L1, B7-H6). OCB provides reliable and patient-friendly cyto-salivary samples that are suitable for immunological and molecular analyses. Aberrant biomarker expression detected in OCB specimens correlates with epithelial dysplasia and reflects early non-invasive neoplastic transformation, supporting the diagnostic value of integrated biomarker panels. Overall, OCB-based immunoanalysis represents a practical, non-invasive approach for the early detection of OSCC. Emerging technologies, including AI and multi-omics approaches, may further support the precision and predictive values of immunological analysis for OSCC. When combined with relevant biomarker pathways reflecting tumour biology and host immune responses, this strategy could offer a strong foundation for precision-medicine screening. It may also support personalised monitoring in patients with OPMDs. Full article

Small object detection remains a challenge in computer vision due to low pixel occupancy, feature scarcity, and susceptibility to background interference. Conventional single-backbone networks often struggle to balance deep semantic extraction with the preservation of shallow details. Deep down-sampling can lead to the loss of edge and texture information, while late-stage fusion may fail to recover these details effectively. To address these limitations, this paper proposes a Cross-Stage Fusion Network with a Dual Backbone (CSF-Net). Our network employs an asymmetric design: a shallow backbone maintains a higher resolution to preserve fine-grained details, while a deep backbone extracts contextual semantics. These two streams interact via progressive cross-stage connections, facilitating the early fusion of small object information. Experiments on the Micro RGB UAV dataset indicate that CSF-Net improves the mAP of the YOLOV8 baseline from 62.8% to 67.0%, validating the effectiveness of the proposed architecture in enhancing detection performance for small targets. Full article

Background/Objectives: This study explored the heterogeneous distribution pattern of translocator protein 18kDa (TSPO)-PET/MRI using radioligand [¹⁸F] DPA-714 in temporal lobe epilepsy patients and identified clinical factors influencing imaging outcomes. Methods: The TSPO imaging in individual patient was evaluated with both visual reading and quantitative assessment using an asymmetry index based on cerebellum-normalized standardized uptake values. The association between clinical factors and TSPO imaging outcomes was assessed. Pathological evaluation was conducted in three patients. Results: Twenty-nine TLE patients and ten healthy controls were enrolled. Visual evaluation revealed increased [¹⁸F] DPA-714 uptake in twenty patients as compared to controls, predominantly in a unilateral regional brain, while the remaining nine patients showed visually undetectable uptake of [¹⁸F] DPA-714. Consistently, quantitative analysis revealed that 69% (20/29) patients exhibited at least one brain area with significant asymmetry index, notably in the temporal lobe (85%, 17/20). A high asymmetry index could also be observed in the parietal (13.8%, 4/29) and occipital lobe (17.2%, 5/29). Significant associations were identified between the asymmetry index and seizure frequency (p = 0.045, OR = 7.994), and the interval from last seizure to PET scan (p = 0.033, OR = 6.712). Moreover, we confirmed the pathology in three patients via immunohistochemistry, which underscored the potential of TSPO-PET in detecting minor lesion. Conclusions: TSPO-PET reveals patient-specific and network-level neuroinflammatory heterogeneity in MRI-negative TLE, supporting its potential role as a complementary tool for presurgical evaluation. Full article

Background: Early detection of dental caries is essential for effective oral health management. Current diagnostic workflows rely heavily on radiographic imaging, which involves infrastructure requirements, workflow coordination, and resource considerations that may limit frequent use in high-throughput or resource-constrained settings. These contextual factors motivate exploration of adjunct screening concepts that could support front-end triage decisions within existing care pathways. This study evaluates, in simulation, whether modeled tooth-percussion response signals contain sufficient discriminative information to justify further translational and managerial investigation. Implementation costs, workflow optimization, and economic outcomes are not evaluated directly; rather, the objective is to assess whether the technical preconditions for a potentially scalable screening concept are satisfied under controlled in silico conditions. Methods: An in silico model of tooth percussion was developed in which enamel, dentin, and pulp/root structures were represented as a simplified layered mechanical system. Impulse responses generated from simulated tapping were used to compute the modeled surface-vibration response (enamel-layer displacement), which served as a proxy for a measurable percussion-related signal (e.g., contact vibration), rather than a recorded acoustic waveform. Carious conditions were simulated through depth-dependent reductions in stiffness and effective mass and increases in damping to represent enamel and dentin demineralization. A synthetic dataset of labeled simulated signals was generated under varying structural parameters and measurement-noise assumptions. Machine-learning models using Mel-frequency cepstral coefficient (MFCC) features were trained to classify healthy teeth, enamel caries, and dentin caries at a screening (triage) level. Results: Under baseline simulation conditions, the classifier achieved an overall accuracy of 0.97 with balanced macro-averaged F1-score (0.97). Misclassifications occurred primarily between healthy and enamel-caries categories, whereas dentin-caries cases were most consistently identified. When measurement noise and structural variability were increased, performance declined gradually, reaching approximately 0.90 accuracy under the most challenging simulated scenario. These results indicate that discriminative information is present within the modeled signals at a screening (triage) level, meaning that higher-risk categories can be distinguished probabilistically rather than with definitive diagnostic certainty. Sensitivity and specificity trade-offs were not optimized in this study, as the objective was to assess separability rather than to define clinical decision thresholds. Conclusions: Within the constraints of the in silico model, simulated tooth-percussion response signals demonstrated discriminative patterns between healthy, enamel caries, and dentin caries categories at a screening (triage) level. These findings establish technical plausibility under controlled simulation conditions and support further investigation of percussion-based screening as a potential adjunct to clinical assessment. From a healthcare management perspective, the present results address a prerequisite question—whether such signals contain sufficient information to justify translational research, rather than demonstrating workflow optimization, cost reduction, or system-level impact. Clinical validation, threshold optimization, and implementation studies are required before managerial or operational benefits can be evaluated. Full article