Search Results (576)

Primary hyperparathyroidism (PHPT) in the pediatric population is a rare but clinically important endocrine disorder that poses significant diagnostic and therapeutic challenges. In contrast to adult PHPT, which is often detected incidentally, pediatric patients are frequently symptomatic at diagnosis, with manifestations reflecting prolonged exposure to hypercalcemia and elevated parathyroid hormone levels. Neonatal forms, particularly neonatal severe hyperparathyroidism, represent life-threatening conditions requiring prompt biochemical recognition and urgent intervention. The heterogeneity of clinical presentation and the rarity of the disease contribute to delayed diagnosis and increased risk of end-organ complications. Although hereditary syndromes are proportionally more frequent in children than in adults, sporadic PHPT remains the most common etiology in pediatric patients and is typically caused by a single parathyroid adenoma. Genetically determined forms, including multiple endocrine neoplasia syndromes, hyperparathyroidism–jaw tumor syndrome, and calcium-sensing receptor-related disorders, are often associated with multiglandular disease, earlier onset, and a higher risk of persistence or recurrence. Biochemical confirmation remains the cornerstone of PHPT diagnosis, while diagnostic imaging plays an important role in preoperative localization and surgical planning. High-resolution cervical ultrasound is the preferred first-line imaging modality in pediatric patients due to its excellent diagnostic performance and absence of ionizing radiation. Functional and advanced cross-sectional imaging techniques should be applied in a stepwise manner in selected cases with inconclusive first-line imaging or suspected ectopic disease, balancing diagnostic yield against radiation exposure. Surgical management remains the definitive treatment for pediatric PHPT. The extent of surgery is determined by disease etiology, localization findings, and intraoperative assessment, with focused parathyroidectomy favored in sporadic single-gland disease and more extensive approaches required in genetically determined forms. This review highlights a structured diagnostic and therapeutic pathway for pediatric PHPT, emphasizing the integration of biochemical testing, imaging strategies, genetic evaluation, and individualized surgical management to optimize outcomes and reduce long-term morbidity. Full article

Dielectric barrier discharge (DBD) plasma actuators (PAs) are devices used to control airflow. DBD actuators generate an electric field that accelerates ionized air particles, inducing localized flow modifications. Among other applications, they are particularly effective for enhancing cooling, for aerodynamic drag reduction, and for lift enhancement, therefore capable of improving stall characteristics. In addition, they offer several distinct advantages, such as rapid response time, low power consumption, and no moving parts. The present review paper aims to summarize the main governing equations associated with the most common phenomenological PA Computational Fluid Dynamics (CFD) models, Shyy and Suzen-Huang, as well as highlight the major applications to flat plates, wind turbine airfoils and entire wind turbines. The application of DBD plasma actuators on individual wind turbine blades, as well as dynamic horizontal and vertical axis wind turbines, is reviewed, drawing from key numerical and experimental investigations. The simulated performance of various configurations of single and multiple PAs on representative airfoils at different chordwise locations is discussed. The overall findings indicate that the chordwise location of the actuators on airfoils and their optimum spanwise placement on small and large wind turbine blades, along with the geometry and excitation parameters of the actuators, play a crucial role in their performance, affecting the boundary layer and the flow pattern. The reader shall obtain an overall idea of the most recent aerodynamic applications of PAs as well as their expected efficiency. Full article

The intelligent surgical knife (iKnife), based on rapid evaporative ionization mass spectrometry (REIMS), represents a transformative advance in intraoperative tissue characterization. By integrating mass spectrometry with electrosurgical dissection, the iKnife enables real-time differentiation between cancerous and healthy tissues through molecular fingerprinting of the aerosol generated during cutting. This innovation significantly shortens operative time by eliminating delays associated with conventional histopathological analysis and enhances surgical precision by providing continuous feedback on tissue composition. Since its inception by Zoltán Takáts and colleagues, the iKnife has demonstrated remarkable diagnostic accuracy across multiple cancer types, including breast, ovarian, and colorectal malignancies, with reported sensitivities and specificities > 90% in selected tumour types. Beyond oncology, REIMS technology also shows promise for microbial identification and metabolomic profiling. This review provides a comprehensive overview of the iKnife’s development, underlying principles, clinical validation, and emerging applications, as well as its integration into surgical workflows and the challenges remaining for widespread clinical adoption. Future perspectives include miniaturization, AI-driven spectral interpretation, and expansion into robotic and image-guided surgery. Full article

FLASH radiotherapy requires real-time, non-invasive beam monitoring systems capable of operating under ultra-high dose rate (UHDR) conditions without perturbing the therapeutic beam. In this work, we characterized the extraction system of Supersonic Gas Curtain-based Ionization Profile Monitor (SGC-IPM) for its capabilities as a transverse beam profile and position monitor for FLASH protons. The monitor utilizes a tilted gas curtain intersected by the incident beam, leading to the generation of ions that are extracted through a tailored electrostatic field, and detected using a two stage microchannel plate (MCP) coupled to a phosphor screen and CMOS camera. CST Studio Suite was employed to conduct electrostatic and particle tracking simulations evaluating the ability of the extraction system to measure both beam profile and position. The ion interface, at the interaction region of proton beam and gas curtain, was modeled with realistic proton beam parameters and uniform gas curtain density distributions. The ion trajectory was tracked to evaluate the performance across multiple beam sizes. The simulations suggest that the extraction system can reconstruct transverse beam profiles for different proton beam sizes. Simulations also supported the system’s capability as a beam position monitor within the boundary defined by the beam size, the dimensions of the extraction system, and the height of the gas curtain. Some simulation results were benchmarked against experimental data of 28 MeV proton beam with 70 nA average beam current. This study will further help to optimize the design of the extraction system to facilitate the integration of SGC-IPM in medical accelerators. Full article

We aimed to establish a rapid and precise method for identifying and quantifying multi-species vegetable oil (corn oil, olive oil (OLO), soybean oil, and sunflower oil (SUO)) adulterations in camellia oil (CAO), using soft ionization by chemical reaction in transfer–high-resolution mass spectrometry (SICRIT-HRMS) and machine learning methods. The results showed that SICRIT-HRMS could effectively characterize the volatile profiles of pure and adulterated CAO samples, including binary, ternary, quaternary, and quinary adulteration systems. The low m/z region (especially 100–300) exhibited importance to oil classification in multiple feature-selection methods. For qualitative detection, binary classification models based on convolutional neural networks (CNN), Random Forest (RF), and gradient boosting trees (GBT) algorithms showed high accuracies (98.70–100.00%) for identifying CAO adulteration under no dimensionality reduction (NON), principal component analysis (PCA), and uniform manifold approximation and projection (UMAP) strategies. The RF algorithm exhibited relatively high accuracy (96.25–99.45%) in multiclass classification. Moreover, the five models, including CNN, RF, support vector machines (SVM), logistic regression (LR), and GBT, exhibited different performances in distinguishing pure and adulterated CAO. Among 1093 blind oil samples, under NON, PCA, and UMAP: 10, 5, and 67 samples were misclassified by CNN model; 6, 7, and 41 samples were misclassified by RF model; 8, 9, and 82 samples were misclassified by SVM model; 17, 18, and 78 samples were misclassified by LR model; 7, 9, and 43 samples were misclassified by GBT model. For quantitative prediction, the PCA-CNN model performed optimally in predicting adulteration levels in CAO, especially with respect to OLO and SUO, exhibiting a high coefficient of determination for calibration ($R_C^2$, 0.9664–0.9974) and coefficient of determination for prediction ($R_p^2$, 0.9599–0.9963) values, low root mean square error of calibration (RMSEC, 0.9–5.3%) and root mean square error of prediction (RMSEP, 1.1–5.8%) values, and RPD (5.0–16.3) values greater than 3.0. These results indicate that SICRIT-HRMS combined with machine learning can rapidly and accurately identify and quantify multi-species vegetable oil adulterations in CAO, which provides a reference for developing non-targeted and high-throughput detection methods in edible oil authenticity. Full article

Protein phosphorylation is a crucial post-translational modification that regulates protein activity, cellular signaling, transcriptional regulation, and cell cycle control. However, the analysis of phosphoproteins in biological samples is often compromised by complex sample matrices and interference from high-abundance proteins. While the top-down phosphoproteomics strategy enables comprehensive analysis of post-translational modifications based on intact proteins, its requirement for higher protein purity due to low protein ionization efficiency poses stern challenges. Consequently, developing appropriate enrichment methods for phosphoproteins in practical samples becomes essential. Immobilized metal ion affinity chromatography (IMAC) represents a common strategy for phosphorylated protein separation and enrichment. Among metal ions, Ti⁴⁺ has gained widespread application as IMAC chelating ligands due to its capacity to form multiple coordination networks and its high selectivity for phosphorylated protein enrichment, leveraging the strong chelating ability of phosphate groups toward metal ions. This paper presents the design and preparation of a novel magnetic Ti-IMAC nanocomposite, MNP@MPTMS–VPA–Ti(IV). The material is modified with phosphate groups via facile thiol-ene click chemistry and then immobilizes Ti⁴⁺, enabling selective enrichment of intact phosphoproteins through IMAC affinity. The efficiency of enrichment was evaluated using subsequent matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) for detection and analysis. This Ti-IMAC material-based magnetic solid-phase extraction (MSPE)-MALDI-TOF MS protocol has been successfully applied to enrich intact phosphoproteins in milk and eel mucus with high selectivity, sensitivity, and suitability. Full article

Background/Objectives: Therapeutic drug monitoring (TDM) of β-lactams (BL), BL/β-lactamase inhibitor (BLI) combinations (BL/BLIc), and of fosfomycin may play a key role in optimizing antimicrobial therapy and in preventing resistance development, especially when used by continuous infusion in critically ill or immunocompromised patients. Unfortunately, analytical methods for simultaneously quantifying multiple BL/BLIc in plasma are still lacking. Methods: The aim of this study was to develop and validate two rapid, sensitive, and accurate UPLC–qTOF–MS/MS methods for the simultaneous quantification of five novel β-lactam or β-lactam/β-lactamase inhibitor combinations (ceftolozane/tazobactam, ceftazidime/avibactam, meropenem/vaborbactam, cefiderocol, and ceftobiprole) along with fosfomycin. Methods: Human plasma samples were prepared by protein precipitation using methanol containing isotopically labeled internal standards. Chromatographic separation was achieved within 10–12 min using two Agilent Poroshell columns (EC-C18 and PFP) under positive and negative electrospray ionization modes. The method was validated according to the EMA guidelines by assessing selectivity, linearity, precision, accuracy, matrix effects, extraction recovery, and stability. Results: The methods exhibited excellent linearity (R² ≥ 0.998) across the calibration ranges for all of the analytes (1.56–500 µg/mL), with limits of quantification ranging from 1.56 to 15.62 µg/mL. Intra- and inter-day precision and accuracy were always within ±15%. Extraction recovery always exceeded 92%, and the matrix effects were effectively corrected through isotopic internal standards. No carry-over or isobaric interferences were observed. All the analytes were stable for up to five days at 4 °C, but the BL and BL/BLIc stability was affected by multiple freeze–thaw cycles. Conclusions: These UPLC-qTOF-MS/MS multi-analyte methods enabled a simultaneous, reliable quantification in plasma of five novel beta-lactams and of fosfomycin. Robustness, high throughput, and sensitivity make these multi-methods feasible for real-time TDM, supporting personalized antimicrobial dosing and improved therapeutic outcomes in patients with severe or multidrug-resistant infections. Full article

The characterization of environmental Pseudomonas spp. from pharmaceutical industries is a relatively underexplored area of research. This study used 40 isolates of Pseudomonas from a pharmaceutical company that had been presumptively identified as Pseudomonas aeruginosa by VITEK^®2. The isolates were characterized using 16S rRNA sequencing, Multilocus Sequence Typing (MLST), Matrix-Assisted Laser Desorption Ionization–Time of Flight Mass (MALDI–TOF MS), Fourier Transform Infrared (FT-IR) spectroscopy, ERIC-PCR, antimicrobial susceptibility profiling, and biofilm formation assessment on stainless steel surfaces. Twenty isolates were confirmed as P. aeruginosa. Sixteen isolates were only identified to the genus level of Pseudomonas, and the remaining four isolates were identified as Enterococcus faecalis (n = 2), Proteus spp. (n = 1), and Staphylococcus saprophyticus subsp. bovis/S. edaphicus/S. saprophyticus subsp. saprophyticus/S. pseudoxylosus/S. xylosus/S. caeli/S. ureilyticus. Typing of the 20 P. aeruginosa strains yielded 18 distinct FT-IR profiles and 19 ERIC-PCR profiles. The MLST analysis identified eight new sequence types (ST4292–ST4299). All strains were classified as multidrug-resistant (MDR), exhibiting resistance to multiple antimicrobial classes. Biofilm formation was observed in 28 (77.8%) Pseudomonas spp. strains on polystyrene surfaces, classified as moderately or strongly adherent, while all P. aeruginosa strains formed biofilms on stainless steel. Of the three disinfectants tested, sodium hypochlorite at 0.01% showed the best performance, reducing or eliminating biofilm formation in 24 (85.7%) strains. The regular evaluation of disinfection effectiveness in pharmaceutical industries is essential, as the presence of biofilm-forming strains can compromise production and contaminate final products. Full article

High-entropy ceramic (HEC) thin films generally refer to multi-component solid solutions composed of multiple metallic and non-metallic elements, existing in forms such as carbides, nitrides, and borides. Benefiting from the high-entropy effect, lattice distortion, sluggish diffusion, and cocktail effect of high-entropy systems, HEC thin films form simple amorphous or nanocrystalline structures while exhibiting high hardness/elastic modulus, excellent tribological properties, and thermal stability. Although the mixing entropy increases with the number of elements in the system, a higher number of elements does not guarantee improved performance. In addition to system configuration, the regulation of preparation methods and processes is also a key factor in enhancing performance. Arc ion plating (AIP) has emerged as one of the mainstream techniques for fabricating high-entropy ceramic (HEC) thin films, which is attributed to its high ionization efficiency, flexible multi-target configuration, precise control over process parameters, and high deposition rate. Through rational design of the compositional system and optimization of key process parameters—such as the substrate bias voltage, gas flow rates, and arc current—HEC thin films with high hardness/toughness, wear resistance, high-temperature oxidation resistance, and electrochemical performance can be fabricated, and several of these properties can even be simultaneously achieved. Against the backdrop of AIP deposition, this review focuses on discussions grounded in the thermodynamic principles of high-entropy systems. It systematically discusses how process parameters influence the microstructure and, consequently, the mechanical, tribological, electrochemical, and high-temperature oxidation behaviors of HEC thin films under various complex service conditions. Finally, the review outlines prospective research directions for advancing the AIP-based synthesis of high-entropy ceramic coatings. Full article

Due to the strong electronegativity of oxygen ions, the valence band maximum (VBM) that is derived from the O 2p orbital leads to strong localization, as well as further heavy hole mass and low hole mobility, which makes it extremely difficult to obtain high-conductivity p-type transparent conductive materials. Herein, we propose the strategy of multiple anions through the introduction of weaker electronegative nitrogen, in consideration of the delocalization on VBM, as well as the stability of octahedral anion cages. As such, first-principles calculations in the framework of density functional theory (DFT) are used for this work. Crystal structure prediction software USPEX (version 2023.0) was adopted to investigate the N-O appropriate ratio in CaTiO_3−xN_x (0 ≤ x ≤ 1) to balance the high transmission of light and highly favorable dispersion at the VBM. Furthermore, the p-type TCO performance of CaTiO_3-xN_x was evaluated based on the hole effective mass, hole mobility, and conductivity. The effectiveness of modulating p-type TCO through N-O multiple anions was also evaluated through defect formation energy and ionization energy. Ultimately, the construction of a CaTiO_3-xN_x/Si heterojunction and band alignment were considered for practical application. This approach attempts to boost the diversity of p-type perovskite-based TCOs and opens a new perspective for engineering and innovative material design for sustainable TCOs demand. Full article

Eutrophication has emerged as a critical threat to water quality degradation and ecosystem health on a global scale, calling for prompt management actions. Remote sensing enables the monitoring of eutrophication by detected changes in ocean color caused by fluctuations in chlorophyll a (chl a). Although chl a is a crucial indicator of phytoplankton biomass and nutrient overloading, it reflects the outcome of eutrophication rather than its cause. Nutrients, the primary “drivers” of eutrophication, are essential indicators for predicting the potential phytoplankton growth in water bodies, allowing adoption of effective preventive measures. Long-term monitoring of nutrients combined with multiple water quality indicators using remotely sensed data could lead to a more precise assessment of the trophic state. Retrieving non-optically active constituents, such as nutrients and DO, remains challenging due to their weak optical characteristics and low signal-to-noise ratios. This work is an attempt to review the current progress in the retrieval of un-ionized ammonia (NH₃), ammonium (NH₄⁺), ammoniacal nitrogen (AN), nitrite (NO₂⁻), nitrate (NO₃⁻), dissolved inorganic nitrogen (DIN), phosphate (PO₄³⁻), dissolved inorganic phosphorus (DIP), silicate (SiO₂) and dissolved oxygen (DO) using remotely sensed data. Most studies refer to Case II highly nutrient-enriched water bodies. The commonly used spaceborne and airborne sensors, along with the selected spectral bands and band indices, per study area, are presented. There are two main model categories for predicting nutrient and DO concentration: empirical and artificial intelligence (AI). Comparative studies conducted in the same study area have shown that ML and NNs achieve higher prediction accuracy than empirical models under the same sample size. ML models often outperform NNs when training data are limited, as they are less prone to overfitting under small-sample conditions. The incorporation of a wider range of conditions (e.g., different trophic state, seasonality) into model training needs to be tested for model transferability. Full article

Background/Objectives: Pregnancy represents a unique physiological state marked by extensive metabolic adaptations, particularly in lipid pathways essential for maternal adjustments, fetal development, and postpartum recovery. This study aimed to explore these changes through untargeted lipidomic profiling. Methods: This observational, comparative, non-interventional clinical study included 107 women, of which 65 were in the third trimester of pregnancy (mean age 27.9 ± 5 years) and 42 were in the early postpartum period (≤7 days, mean age 28.9 ± 5.9 years). Inclusion criteria were singleton, term pregnancies (37–41 weeks) with neonates weighing > 2500 g and no associated pregnancy-related pathologies; exclusion criteria included multiple gestation, use of lipid-altering medications, maternal age > 40 years, or diagnosed pregnancy complications. Plasma samples were analyzed using High-Performance Liquid Chromatography–Quadrupole Time-Of-Flight–Electrospray Ionization (positive mode)–Mass Spectrometry, data were processed with MetaboAnalyst 6.0 using multivariate and univariate analyses (Partial Least Squares–Discriminant Analysis, Volcano Plot, Random Forest, Receiver Operating Characteristic analysis), with statistical significance set at p < 0.05. Results: Multivariate analysis demonstrated a clear separation between groups with high predictive accuracy as reflected by strong classification metrics (Accuracy = 0.90, R² = 0.75, Q² = 0.68). Several discriminative lipids were consistently identified across statistical models, including 2-Methoxyestrone (AUC = 0.861), Eicosanedioic acid (AUC = 0.854), and Pregnenolone sulfate (AUC = 0.843). These biomarkers were further categorized into five major lipid classes: steroid hormones, long-chain fatty acids, lysophospholipids, ceramides/sphingolipids, and glycerolipids. Conclusions: Untargeted lipidomic profiling revealed distinct metabolic signatures that differentiate late pregnancy from early post-partum states. The identification of robust lipid biomarkers with high discriminative performance highlights their potential utility in maternal health monitoring, obstetric risk assessment, and postpartum recovery surveillance. Full article

This work presents the simulation and design of 3C-SiC power MOSFETs, focusing on critical parameters including avalanche impact ionization, breakdown voltage, bulk and channel mobilities, and the trade-off between on-resistance and breakdown voltage. The device design is carried out by evaluating the blocking voltage of scaled structures as a function of the blocking layer’s doping concentration. To mitigate edge-effect breakdown at the p-well/n-drift interface, a step-profile doping strategy is employed. Multiple transistor layouts with varying pitches are developed using a commercially available device simulator. Results are benchmarked against a one-dimensional analytical model, validating the on-state resistance, current–voltage behavior, and overall accuracy of the simulation approach. For the selected material properties, simulations predict that a 600 V 3C-SiC MOSFET achieves an on-state resistance of 0.8 mΩ·cm², corresponding to a 7 μm drift layer with a doping concentration of 1 × 10¹⁶ cm⁻³. Full article

Lead halide perovskites, exemplified by methylammonium (MA) lead iodide (MAPbI₃), combine strong optical absorption, long carrier diffusion lengths, and defect-tolerant electronic structure with facile processing, making them attractive for photovoltaics and radiation detection. Yet, their behavior under electron irradiation remains insufficiently understood, limiting deployment in space and dosimetry contexts. Here, we employ Monte Carlo simulations (Geant4) to model electron interactions with MAPbI₃ across energies from 0.1 to 100 MeV and absorber thicknesses from 10 μm to 1 cm. We quantify deposited energy, event statistics, energy per interaction, non-ionizing energy loss, and dominant radiation effects. The results reveal strong thickness-dependent regimes: thin photovoltaic-type layers (~hundreds of nanometers) are largely transparent to MeV electrons, minimizing bulk damage but allowing localized ionization, exciton self-trapping, and photoexcitation-driven ion migration. Although localized excitations can temporarily improve carrier collection under short-term exposure, their cumulative effect drives ionic rearrangement and defect growth, ultimately reducing device stability. In contrast, thicker detector-type films (10–100 μm) sustain multiple scattering and ionization cascades, enhancing sensitivity but accelerating defect accumulation. At centimeter scales, energy deposition saturates, enabling bulk-like absorption for high-flux dosimetry. Overall, electron irradiation in MAPbI₃ is dominated by electronic excitation rather than ballistic displacements, underscoring the need to optimize thickness and composition to balance efficiency, sensitivity, and durability. Full article

Phenetole derivatives are widely used in various fields, and the presence of the ethoxy group, with its longer alkyl chain, suggests the possibility of multiple rotamers. In particular, diethoxybenzene derivatives, containing two ethoxy groups, exhibit an even greater number of rotameric forms. In this study, we report the first investigation of the stable structures, vibronic spectra, and cationic spectra of different rotamers of m-diethoxybenzene (MDEB). Resonance-enhanced multiphoton ionization (REMPI) spectra of the rotamers were identified via hole-burning (HB) experiments, while mass-analyzed threshold ionization (MATI) spectra provided precise adiabatic ionization energies (IEs) of the observed rotamers, as well as the active vibrations of their corresponding cations. Density functional theory (DFT) calculations predicted thirteen rotamers of MDEB, but only two rotamers were observed in the supersonic molecular beam. The band origins of the S₁ ← S₀ transition and the adiabatic IEs of the down–up and down–down rotamers of MDEB were determined to be 36,091 ± 2 cm⁻¹ and 36,165 ± 2 cm⁻¹ and 62,419 ± 5 cm⁻¹ and 63,378 ± 5 cm⁻¹, respectively. Franck–Condon spectral simulations for the S₁ ← S₀ and D₀ ← S₁ transitions were performed based on DFT calculations, and the theoretical results showed good agreement with the experimental data. Vibrational features observed in the S₁ and D₀ states were assigned by comparing the experimentally measured spectra with the simulated spectra as well as the previously reported vibrational spectra of structurally similar molecules. Finally, several key findings and molecular characteristics are discussed in detail. Full article