Search Results (212)

Mycobacterium abscessus subsp. massiliense (Mabs) is an emerging nontuberculous mycobacterium associated with difficult-to-treat infections due to intrinsic antimicrobial resistance, intracellular persistence, biofilm formation, and limited responsiveness to currently available therapeutic regimens. In this context, adjuvant strategies targeting iron-dependent metabolic pathways and metal homeostasis may enhance the efficacy of conventional antimicrobials. This study investigated deferoxamine (DFO), a clinically approved iron chelator, as a potential adjuvant against Mabs using integrated in vitro and in silico approaches. Cytocompatibility was assessed using an MTT assay in RAW 264.7 macrophages and a hemolysis assay in human erythrocytes. Antimicrobial activity was evaluated through minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) assays, while interactions with clarithromycin (CLA) and amikacin (AMK) were assessed using the checkerboard method. Effects on virulence-associated phenotypes were examined through biofilm formation assays and protein quantification in extracellular vesicle-enriched fractions. Intracellular activity and modulation of inflammatory mediator gene expression were investigated in Mabs-infected RAW 264.7 macrophages through colony-forming unit (CFU) recovery and reverse transcription quantitative polymerase chain reaction (qPCR). DFO exhibited low cytotoxicity and negligible hemolytic activity under the tested conditions. Direct antimicrobial testing revealed a predominantly bacteriostatic profile (MIC = 9.75 µg/mL; MBC > 10 mg/mL), whereas checkerboard analysis suggested a synergistic interaction with CLA (FICI = 0.047), which requires further confirmation by time-kill or CFU-based combination assays. Furthermore, DFO reduced biofilm biomass, decreased protein levels in vesicle-enriched fractions, lowered intracellular bacterial burden, and modulated cytokine gene expression in infected macrophages. Molecular docking, ADME/Tox, and PASS analyses generated exploratory hypotheses regarding potential molecular interactions and pharmacological properties. Overall, these findings support DFO as a promising experimental adjuvant candidate for further investigation against Mabs, particularly in combination with clarithromycin. However, confirmation of a putative iron-restriction-associated mechanism and its translational relevance will require validation in additional clinical isolates, iron-rescue experiments, mature biofilm models, and in vivo studies. Full article

Anemia represents one of the most frequent systemic complications of inflammatory bowel disease (IBD), with a consistently higher prevalence reported in patients with Crohn’s disease (CD) compared with ulcerative colitis (UC). While chronic inflammation, impaired iron absorption, and intestinal blood loss are recognized contributors, microbiome-mediated mechanisms influencing host iron availability remain insufficiently explored. Emerging evidence indicates that CD-associated dysbiosis is characterized by an increased abundance of siderophore-producing bacteria, particularly members of the Enterobacteriaceae family. Because siderophores are high-affinity iron-chelating molecules capable of competing with host iron acquisition systems and partially escaping lipocalin-2-mediated sequestration, their expansion may contribute to reduced luminal iron bioavailability. In this systematic review, we analyzed comparative microbiome studies published between 2016 and 2026 that directly evaluated microbial differences between CD and UC. CD microbiota consistently demonstrated enrichment in siderophore-associated taxa relative to UC. Based on these findings, we propose that microbiome-driven iron competition may represent an additional mechanistic contributor to the increased prevalence and persistence of anemia observed in CD. Although direct in vivo quantification of siderophore activity in IBD remains limited, the convergence of ecological, functional, and strain-level microbiome evidence supports a biologically plausible interaction between microbial iron-scavenging strategies and host iron metabolism. Full article

Predictive maintenance in underground mining faces challenges due to severe conditions such as confined environments, high humidity, presence of silica dust, and restricted access. This study develops a predictive framework based on oil analysis and machine learning for multiple compartments of mining equipment (engine, hydraulic system, transmission, differential). Samples were processed under ASTM standards, integrating wear metal concentrations (Fe, Cu, Cr, Pb, Al), physicochemical properties (viscosity, TBN, soot), and contaminants (Si, Na). Based on tribology, interpretable ratios were constructed. Three algorithms (Random Forest, Gradient Boosting, and XGBoost) were evaluated using cross-validation. XGBoost achieved the best balance (F1 = 0.852, AUC = 0.975), with a recall of 94.5% for the critical class and only 3 false negatives out of 199 test samples, while Random Forest presented the highest global discrimination power (AUC = 0.978). SHAP revealed that viscosity at 100 °C is the most important predictor (SHAP ~0.9), surpassing iron. No temporal wear trend was found (R² = 0.000). Threshold optimization to 0.25 reduced false negatives by 67% (from 9 to 3). The framework provides interpretable predictions with uncertainty quantification for underground environments. Full article

Background: Magnetic particle imaging (MPI) is an emerging, tracer-based modality that directly detects superparamagnetic iron oxide nanoparticles (SPIONs) with exceptional sensitivity, quantitative signal behavior, and full immunity to air–tissue susceptibility artifacts. These features make MPI particularly well-suited for pulmonary imaging, where traditional techniques such as computed tomography (CT), magnetic resonance imaging (MRI), and nuclear medicine-based ventilation/perfusion (V/Q) imaging are limited by radiation exposure, low contrast, and motion-related signal degradation. Objective: This review synthesizes the current state of MPI for lung imaging, with emphasis on its physical principles, tracer development, preclinical applications, and its potential role in assessing pulmonary perfusion, vascular integrity, inflammation, and therapeutic responses. Methods: A systematic evaluation of preclinical studies was performed across three major application domains: pulmonary perfusion mapping, cell tracking and therapeutic monitoring, and vascular injury and permeability assessment. Study designs, SPION formulations, MPI acquisition strategies, and validation methods, including histopathology, biodistribution, broncho-alveolar lavage fluid (BALF) analysis, and Evans Blue assays, were examined to characterize methodological consistency and imaging performance. Results: MPI consistently demonstrated high-contrast, quantitative visualization of pulmonary blood flow, endothelial barrier disruption, inflammatory signaling, and transplanted or inhaled cell populations. Tracer engineering played a critical role: macroaggregated albumin superparamagnetic iron oxide nanoparticles (MAA-SPIONs) enabled capillary-level perfusion mapping, LS-008 improved temporal resolution and vascular delineation, Synomag/Synomag-D allowed quantification of vascular leakage in acute and chronic lung injury, and vascular cell adhesion molecule-1 (VCAM-1)-targeted probes provided molecular-level assessment of inflammation. Hybrid MPI-CT and MPI-MRI approaches further enhanced anatomic localization and enabled accurate pulmonary blood volume (PBV) estimation. Across studies, MPI measurements showed strong agreement with established biological assays and remained free of the artifacts that limit CT and MRI in the lung. Conclusions: Preclinical evidence demonstrates that MPI is a robust, radiation-free, and quantitatively precise modality for functional and molecular lung imaging. Its ability to map perfusion, track therapeutic agents, and noninvasively quantify vascular permeability positions MPI as a promising future alternative or complement to CT, MRI, and nuclear medicine for pulmonary assessment. Continued tracer optimization, system scaling, and clinical validation are key steps toward translating MPI into routine clinical use. Full article

Doxycycline (DOX) is a well-characterized antibiotic, and its pharmacokinetic behavior has recently attracted renewed scientific interest. Its absorption occurs mainly in the small intestine, while ions such as Fe³⁺ and Al³⁺ readily form complexes, particularly under acidic conditions, thereby reducing the fraction of free drug available for absorption. The present study provides a systematic investigation of how such interactions influence the dissolution and intestinal permeability of DOX. A dynamic in vitro protocol was implemented, incorporating an online transition from gastric to intestinal conditions in combination with Franz diffusion cells. This integrated system enables real-time monitoring of early DOX absorption-related processes, providing a more comprehensive understanding of potential pharmacokinetic interactions during its coadministration with iron or aluminum supplements. To ensure reliable quantification, a rapid, economical, and environmentally compatible HPLC-FLD method was developed and validated, employing a Hypersil Gold C18 column (50 mm × 4.6 mm, 5 μm; Thermo) and a mobile phase consisting of acetonitrile—20 mM NaH₂PO₄ (pH 2) 15:85 v/v. Overall, a practical and efficient framework was established for investigating factors that influence the bioavailability of doxycycline, supporting the broader evaluation of drug, excipient, and drug supplement interactions. Full article

Background. Nanoparticle-mediated radiotherapy is a promising approach to enhance tumor radiosensitivity while reducing damage to healthy tissues. Particularly, melanoma is a highly aggressive malignancy with an increasing global incidence and limited therapeutic options in advanced stages, due to its intrinsic radioresistance and narrow therapeutic window in metastatic settings. In this study, we developed a systematic library of gadolinium-doped iron oxide nanoparticles (Fe-Gd NPs) with controlled compositions (0–75% Gd) to investigate the functional and compositional determinants of radiosensitization in melanoma. Methods. The physicochemical properties of the Fe-Gd NPs, including the morphology, crystallinity, and composition, were thoroughly characterized and correlated with biological responses. The biological evaluation was performed using both 2D and tissue-relevant 3D melanoma models, integrating metabolic viability assays (MTT/MTS), mitochondrial function (ATP quantification, MitoTracker analysis), and clonogenic survival following low-energy X-Ray irradiation (150 kV, 4 Gy). In vivo systemic tolerance and response in non-tumor tissues were investigated in BALB/C mice. Results. Our results showed that radiosensitization did not increase linearly with the Gd content, with the 25% Fe-Gd NPs being identified as a therapeutic window and having the most pronounced effect in melanoma cell models, while maintaining good systemic safety in vivo. This study provides functional evidence that nanoparticle-mediated radiosensitization is not only determined by a high Z content, but also by tumor-specific metabolic adaptability and the nanoparticle composition. Conclusions. These findings support the rational design of Fe-Gd nanoparticles with optimized therapeutic windows and highlight the importance of metabolic and 3D tissue-relevant models in preclinical evaluation of nanoparticle-mediated radiotherapy. Full article

Background: Magnetic Particle Imaging (MPI) is an emerging biomedical imaging modality that detects superparamagnetic iron oxide nanoparticles (SPIONs), providing high contrast, sensitivity, and quantification capabilities without ionizing radiation, making it particularly suitable for cancer diagnostics. Considerable engineering efforts are underway to translate MPI technology to clinical settings. Most of these MPI scanners feature a cylindrical bore geometry similar to that of other clinical imaging modalities, which limits their potential application primarily to head scanning. Methods: We have developed a single-sided MPI scanner designed to expand the modality’s applicability to other regions of the human body through a unique hardware design developed in our previous work. Imaging experiments were performed on an anatomical breast phantom containing implanted SPION point sources placed at anatomically plausible locations for breast tumors. These point sources served as artificial tumors for evaluating the system’s suitability for breast imaging applications. Results: The scanner successfully detected and clearly resolved the implanted SPION tumors in two orthogonal imaging planes. Tumor positioning was independently validated by ultrasound imaging, confirming MPI’s accurate localization. In addition, sensitivity measurements demonstrated a detection limit of 4.0 $\mathsf{\mu }\mathrm{g}$ of iron, below the estimated 4.8 $\mathsf{\mu }\mathrm{g}$ sensitivity threshold required for breast tumor detection with electronic depth scanning up to 3.5 cm deep. Conclusions: Together, these results demonstrate the capability of a single-sided MPI geometry for breast imaging applications. Imaging an anatomical breast-shaped volume presents significant challenges for MPI due to the size and accessibility constraints of conventional hardware. The results presented highlight the advantages of this approach and support its potential to extend MPI from small-animal imaging to clinically relevant applications. Full article

Background/Objectives: Magnetic nanoparticles have emerged as powerful tools for biomedical imaging, targeted drug delivery, and hyperthermia therapy. Magnetic particle imaging (MPI) is among the most promising technologies built around its properties: a radiation-free, quantitative tomographic modality that detects superparamagnetic iron oxide nanoparticles (SPIONs) directly against a biologically silent background. This review synthesizes MPI’s physical principles, nanoparticle design strategies, and preclinical applications within the broader landscape of magnetic material engineering for biomedical use. Methods: A systematic review was conducted covering MPI signal generation and image reconstruction, nanoparticle core synthesis and surface coating approaches, and preclinical applications, spanning cell tracking, oncological imaging, vascular perfusion, neuroimaging, and MPI-guided theranostics. Studies were selected to provide quantitative benchmarks and direct comparisons with competing modalities where available. Results: MPI delivers signal-to-background ratios above 1000:1, iron-mass linearity at R² ≥ 0.99, regardless of tissue depth, and acquisition rates up to 46 volumes per second. Tracer architecture—encompassing single-core particles, multicore nanoflowers, and stimuli-responsive cluster designs—is the primary determinant of sensitivity, environmental robustness, and theranostic capability. Preclinical results include detection of cell populations in the low thousands, earlier ischaemia identification than diffusion-weighted MRI, real-time drug release quantification, and spatially confined tumour hyperthermia. Three translational bottlenecks are identified: the absence of a clinically approved tracer with optimal relaxation dynamics, hardware performance losses when scaling to human-bore systems, and overestimation of passive tumour accumulation in murine models. Conclusions: MPI illustrates how progress in magnetic material design directly expands clinical imaging and theranostic possibilities. Successful translation will require indication-driven, interdisciplinary development that integrates materials science, scanner engineering, and regulatory strategy in parallel. Full article

Non-exhaust particulate emissions are expected to remain a relevant source of traffic-related air pollution, including an increase in electrified vehicle fleets. Particle formation results from tribological interactions and is influenced by both operating conditions and friction material system. This study presents an extended measurement methodology under application-relevant tribological conditions for the reproducible quantification of PM₁₀ and PM_2.5 emissions from dry-running friction systems and applies it to a systematic investigation of operating parameter and friction pairing effects. A dry inertial brake test bench with an enclosed friction chamber and integrated aerosol measurement chain was used under controlled tribologically relevant conditions. Specific friction work and specific friction power were varied by adjusting sliding velocity, contact pressure, and inertial load. Six friction pairings, comprising four representative friction lining types combined with either C45 cast steel or GGG40 gray cast iron, were examined. In situ PM₁₀ and PM_2.5 measurements were complemented by gravimetric wear and microstructural analyses. The results show that specific friction work has a direct influence on PM₁₀ and PM_2.5 emissions, whereas the independent effect of contact pressure is secondary. Friction power exhibits material-dependent effects. Emissions also vary strongly with friction pairing, indicating that operating conditions and material system must be considered jointly when assessing low-emission brake systems. Full article

Purpose: This study aimed to assess the utility of native T1 mapping for the evaluation of myocardial iron overload in patients with Thalassemia Major. T1 was compared to T2*, which represents the gold standard for iron quantification in the heart and liver. Methods: Consecutive patients with Thalassemia Major who performed cardiac MRI at the University Hospital of Sassari between 2022 and 2024 were prospectively included. All patients underwent a 1.5 T MRI with the same scanner (Philips Ingenia). T2* and native T1 mapping (MOLLI) sequences were performed in all patients on a mid-ventricular single 8 mm short-axis slice of the left ventricle. A region of interest was manually drawn in the septal wall. A T2* value < 20 ms was considered indicative of significant myocardial iron overload. A normal lower limit value of 990 ms was adopted for native T1 mapping. Results: In total, 100 patients with Thalassemia Major were included (median age, 45 [range, 7–80] years; 55% were male). The median myocardial T2* value was 31.4 (range, 5.1–47) and median T1 was 941 ms (range, 557–1131). A total of 12 patients (12%) exhibited T2* values < 20 ms; the T1 values in these patients (median, 733.8 ms [range, 557–975]) were significantly lower compared to those with a T2* of 20 ms or greater (median, 961 ms [range, 820–1131]), p < 0.001. No patient with T2* < 20 ms had a T1 value greater than or equal to 990 ms. Among the 88 patients with T2* ≥ 20 ms, 56 (64%) had T1 < 990 ms (median, 939.2 ms [range, 820–986]). Using a T1 threshold of 990 ms, the sensitivity was 100%, but the specificity was only 36%. ROC analysis identified an optimal T1 value of 895.5 ms, corresponding to 92% sensitivity and 100% specificity. Conclusions: Native T1 mapping is highly sensitive for detecting myocardial iron overload in Thalassemia Major, but the standard 990 ms threshold generates many false-positive results. In our cohort, adopting an ROC-optimized threshold of 895.5 ms markedly improved specificity while preserving excellent sensitivity. Full article

Objective: To evaluate the utility of synovial iron quantification using Magnetic resonance imaging (MRI) in assessing structural joint damage in the knee of patients with rheumatoid arthritis (RA). Methods: This cross-sectional study employed a two-stage design. In the initial comparative stage, 6 patients with RA and 5 patients with osteoarthritis (OA) were recruited to compare synovial R2* values, a metric derived from iterative decomposition of water and fat with echo asymmetry and least-squares estimation quantitation (IDEAL-IQ) MRI sequences representing synovial iron content. Following this, the RA cohort was expanded to a total of 51 patients to investigate the association between R2* values and clinical parameters, including disease activity and bone erosion. Synovial fluid iron levels were measured with an Iron Assay Kit and synovial iron deposits were semi-quantified via Prussian blue staining. Associations between R2* and clinical and laboratory parameters, including inflammatory factors and joint damage indices, were analyzed using Spearman’s rank correlation. Univariate and multivariate ordered logistic regression models were employed to identify factors associated with bone erosion severity. An R2*-based nomogram was developed and validated using receiver operating characteristic (ROC) analysis and calibration curves. Results: Synovial R2* values were significantly higher in RA patients than those with osteoarthritis (53.66 S⁻¹ vs. 31.38 S⁻¹, p < 0.05), consistent with Prussian blue staining results. While synovial R2* values showed no significant correlation with systemic iron metabolic markers, inflammatory indicators, or the Disease Activity Score 28, they were positively correlated with bone erosion severity (ρ = 0.500, p < 0.001) and negatively associated with the joint space width (ρ = −0.307, p < 0.05). Multivariate analysis identified R2* as an independent indicator linked to bone erosion extent (OR = 2358.336, p < 0.001). The R2*-based nomogram demonstrated good discriminative performance. (AUC = 0.83). Conclusions: The R2* value derived from IDEAL-IQ MRI is a reliable tool for quantifying synovial iron and may represent a promising non-invasive imaging biomarker reflecting bone erosion in RA patients. Full article

Objectives: In Japan, smartphone applications are increasingly used for dietary recording in healthcare settings. This study aimed to examine the agreement between energy and nutrient intake estimates obtained using an artificial intelligence (AI)-based dietary recording application and those obtained using the weighed dietary record (WDR). Methods: The AI-based dietary recording method (FoodLog Athl method) was compared with WDR. Thirty-six university students (35 women and 1 man) simultaneously recorded their dietary intake using FoodLog Athl (FLA) and the WDR for 10 consecutive days. Energy and nutrient intakes were estimated using each method, and correlations and agreement between the two methods were evaluated. Results: Significant positive correlations were observed between the two methods for energy and most nutrients, except for iron, vitamin B1, and sodium chloride equivalent (p < 0.01). Compared with the WDR, the FLA method showed systematic overestimation of energy and major macronutrients (protein, fat, and carbohydrate) and underestimation of total dietary fiber. Bland–Altman analysis indicated fixed bias and relatively wide limits of agreement for several nutrients. Conclusions: The FLA method demonstrated moderate agreement with the WDR, with systematic bias observed for selected nutrients. These findings suggest that the application may be useful for monitoring overall dietary trends or relative intake over time, but caution is warranted when precise individual-level nutrient quantification is required. Professional review by registered dietitians may help improve estimation accuracy and reduce bias. Full article

Lithium-ion batteries are widely used across diverse applications due to their high energy density, long cycle life, and fast charging capabilities. As battery-powered systems become increasingly critical, accurate estimation of the Remaining Useful Life (RUL) is essential for ensuring reliability, safety, and effective maintenance planning. This work investigates Evidential Deep Learning (EDL) for data-driven RUL estimation and introduces a novel risk-aware loss function designed to enhance both predictive accuracy and uncertainty quantification in the End-of-Life (EoL) region, where precise and trustworthy predictions are most needed. Using a publicly available dataset of lithium iron phosphate (LFP) cells, we benchmark the proposed approach against a baseline Conv–LSTM model, Monte Carlo (MC) Dropout, and Deep Ensembles. The results show that integrating the risk-aware loss into the EDL framework substantially improves the calibration of predictive uncertainty while achieving state-of-the-art accuracy near EoL. Unlike MC Dropout and Deep Ensembles, which exhibit increasing or unstable uncertainty as degradation accelerates, the proposed EDL model demonstrates a consistent reduction in uncertainty and significantly higher reliability in late-stage predictions. The findings indicate that the risk-aware evidential framework offers a reliable and computationally efficient solution for battery RUL estimation, enabling more informed decision-making in both safety-critical and consumer-oriented applications. Full article

Background: Deep vein thrombosis (DVT) is one of the most common cardiovascular diseases and is especially prevalent in areas with environmental pollution. Bioaccumulation of toxic heavy metals may lead to deterioration of homeostasis with cellular change, endothelial dysfunction, DNA impairment and cellular signaling. The reason for this is usually the accumulation of thrombogenic toxins in the body as a result of long-term exposure or a lack of regulatory gene expression. In this study, we aimed to measure the minerals that potentially accumulate in the nail. The measurement method was laser-induced breakdown spectroscopy (LIBS), which is a form of atomic emission spectroscopy. It uses a highly energetic laser source to form a plasma of excited atoms emitting light of characteristic wavelengths. It provides accurate quantification and reveals the relationship between tissue accumulation of toxic heavy metals and DVT formation. Methods: Between January 2020 and December 2021, 100 patients diagnosed with lower-extremity deep vein thrombosis were screened in a single tertiary healthcare center. Among them, 50 patients who met the eligibility criteria and consented to participate were included in the study. An additional 50 age-matched healthy volunteers were enrolled as controls. Demographic and clinical characteristics were recorded. Nail samples were obtained from each participant, and elemental emission intensities were quantitatively analyzed using laser-induced breakdown spectroscopy (LIBS). Results: No difference in clinical characteristics was detected between the groups. While iron, calcium and silicon were found to be high in DVT patients, magnesium was found to be low. Regarding the magnesium emission, ROC analysis showed 76–90% specificity and 69–82% sensitivity, respectively. Conclusions: LIBS is a useful method because it is easy to use and can be used with a small sample. According to the results of our study, information about the pathogenesis of DVT was obtained through nail analysis. Therefore, we believe that LIBS analysis is a method that may be useful in determining the causes and predisposing factors for DVT. Full article

Magnetite-rich iron ores present analytical challenges due to mineralogical complexity, including titanium–vanadium (Ti-V) substitution within magnetite and variable silicate gangue contributions. Reliable iron (Fe) quantification in such systems is essential for accurate resource evaluation and beneficiation planning, particularly in layered intrusion-hosted deposits. This study compares fusion-based inductively coupled plasma optical emission spectroscopy (ICP-OES) and fused-bead X-ray fluorescence (XRF) methods for the determination of Fe and associated major elements in magnetite-bearing Fe ores from the Bushveld Igneous Complex, South Africa. Four representative ore samples and certified reference materials were analysed using both techniques. Comparative statistical parameters like the t-test and F-test exhibit no significant differences in either precision and mean concentration between fused-based ICP-OES and fused-based XRF methods for the determination of Fe and other elements. The results indicate that, despite the existence of titanomagnetite and lithologies that are rich in silicates, both fusion-based methods provide consistent and reliable bulk chemical analysis datasets. While both approaches show suitability for routine chemical analysis, fusion-based ICP-OES offers a practical advantage in terms of throughput and operational efficiency. This work emphasises the importance of matching analytical methods with mineral ore characterisation in order to ensure reliable Fe grade determination in complicated oxide deposits. Full article