This study assessed the feasibility of contrast-enhanced ultrasound (CEUS) for evaluating renal perfusion in horses and compared perfusion parameters between age groups. In a prospective study, eight healthy horses were divided into young (3-5 years, n=4) and old (16-17 years, n=4) groups. All animals underwent B-mode, Doppler ultrasonography, and CEUS of the right kidney after an intravenous bolus of SonoVue (0.02mL/kg). Qualitative analysis assessed contrast kinetics, whereas quantitative parameters (peak intensity, time to peak [TP], area under the curve, and wash-out time) were obtained from time-intensity curves in the renal cortex and medulla. The technique was safely performed in all horses, and the 0.02mL/kg dose proved optimal for achieving adequate renal enhancement and consistent quantitative measurements. Quantitative analysis revealed a significantly longer TP in the renal cortex of older horses compared to young ones (p=0.03), suggesting an age-related reduction in perfusion velocity. No other parameters showed significant differences. CEUS proved to be a feasible and safe method for assessing renal perfusion in horses. The prolonged cortical TP in older animals indicates that CEUS may be a sensitive tool for detecting early, subclinical perfusion changes associated with aging, warranting further investigation in horses with renal disease.

Surface-enhanced Raman scattering (SERS) is attractive for molecular diagnostics, but direct sensing in unprocessed whole blood is hindered by biofouling and poor operational stability. Here, we report a biomimetic-SERS platform integrating vancomycin-responsive structure-switching aptamers and a self-assembled lubricin (PRG-4) antifouling layer on a nanostructured plasmonic nanoslide. The aptamer provides molecular recognition, while the hydrated glycocalyx-mimicking lubricin layer suppresses nonspecific adsorption from blood and preserves access of vancomycin to the sensing interface. The sensor enables direct vancomycin detection in unprocessed whole blood with subnanomolar sensitivity and retains analytical performance after 3 weeks of storage. It also shows proof-of-concept operational stability, retaining 75% peak intensity across six measurement cycles over more than 5 weeks. Although repeated 20 min UV-Ozone cleaning reduces calibration sensitivity, the nanoslide maintains qualitative detection capability and SERS activity, supporting its potential for point-of-use therapeutic drug monitoring.

Thermoluminescence kinetics, time-dependent TL evolution and dosimetric performance of Tb3+-doped NaCa4(BO3)3: Effects of preheating and multi-trap structure.

Data-driven operational flexibility strategy for thermal power considering time-domain dynamic carbon intensity and deep peak shaving‌ in renewable-integrated system

High-order harmonic generation (HHG), as an important ultrafast light source, can be applied in different fields. In contrast to the HHG from gases, the technical extension to liquids remains challenging and recently receives growing attention. Here, we report an apparatus for extreme ultraviolet HHGs from a microfluidic liquid sheet by the excitation of intense femtosecond laser pulses. The liquid sheet is produced with a single-channel borosilicate glass chip, showing a size around 9mm (length) × 2mm (width) and a thickness around 1μm. The HHGs up to twenties eV are successfully produced from the liquid sheets of water, methanol, and ethanol. We scrutinize the HHG dependences on the central photon wavelength and peak intensity of the femtosecond laser pulses and the laser focusing position on the liquid sheet. Furthermore, we propose that the electron radiation-induced chemical reactions in the liquid, as recently explored with our time-delayed mass spectrometry, could be revealed more explicitly with HHG spectroscopy.

Comparative study of silver and gold nanoparticles derived from Sclerocarya birrea stem extract in forensic blood detection.

Loss of internal structural order induced by freezing and Lyophilization correlates with reduced in vitro activity of mRNA lipid nanoparticles.

A novel technique is presented to enhance the electrical characteristics of Silicon-On-Insulator Lateral Double-Diffused Metal-Oxide-Semiconductor Field-Effect Transistors (SOI-LDMOSFETs). The concentration of the electric field in localized regions of the drift area increases susceptibility to breakdown. The proposed technique employs a surface groove within the drift region to redistribute the electric field lines uniformly, thereby reducing peak field intensity. Figure-of-merit analysis reveals a 70% improvement with the Surface Groove SOI-LDMOSFET (SG-SOI-LDMOSFET), achieving 4.8 MW/cm2. These enhancements are demonstrated using the 2D device simulations. The technique improves device performance significantly without adding complexity to the fabrication process.

Transarterial radioembolization (TARE) treatment efficacy critically depends on the microsphere biodistribution in the liver. Current treatment planning protocols rely on a pre-treatment scout procedure to evaluate this biodistribution for a selected catheter configuration. However, replication of the catheter configuration during treatment is challenging and often results in suboptimal tumor targeting. Here we present and experimentally validate a concept to improve tumor targeting using dynamic contrast-enhanced ultrasound (DCE-US) imaging to predict the microsphere biodistribution in real-time, using ultrasound contrast microbubbles as microsphere precursors. DCE-US-guided TARE was performed in three ex vivo perfused porcine livers using a customized normothermic machine-perfusion platform. In each liver, one lobe was selected for targeting, and a 9L4 ultrasound transducer was fixed to image this location. A microcatheter was inserted in the hepatic artery under fluoroscopic guidance. Several catheter positions were analyzed in real-time using ultrasound contrast microbubbles and time-intensity curves (TICs). The catheter position was optimized based on peak TIC intensity, which was retained for subsequent injection of non-irradiated 165Ho-microspheres. The resulting microsphere biodistribution was evaluated by R2* mapping in MRI. Here we show that DCE-US can be used to identify feeding arteries, enabling optimization of the catheter placement to maximize peak intensity within the target lobe. MRI confirms the relative microsphere biodistribution as predicted by DCE-US in two quantifiable cases (Case 2: 99.2% [MRI] vs. 98% [DCE-US]; Case 3: 70.2% [MRI] vs. 80.9% [DCE-US]). DCE-US enables accurate prediction of microsphere biodistribution, providing real-time feedback for immediate intra-operative optimization of the catheter position during TARE.

Cyclic cataluminescence (CCTL) is an emerging strategy that extends the principles of cataluminescence (CTL). The catalyst constitutes a critical component in CTL sensing systems. Currently, the development of innovative sensing systems and the elucidation of sensing mechanisms to enhance CTL remain significant challenges. Herein, we designed a heterogeneous electron allocator catalyst and a circulating flow system-assisted CTL for enhancing sensitivity and response speed. MgO/Y2O3 heterogeneous catalysts were employed as electron allocators and decorated on CNTs, and the resulting MgO/Y2O3/CNT catalyst was coupled with the CCTL method for the catalytic detection of multiple aldehydes. By fitting the variation of the peak intensity (In) of CCTL with time (t), the characteristic attenuation coefficient (k) value was calculated, and the k value could be used for qualitative analysis. The comprehensive k values of aldehydes contained characteristic information of tea. The k values of 61 tea samples were obtained by the CCTL method, and the k values of different tea species and origins were different from 2.0 to 41. Moreover, linear discriminant analysis and hierarchical cluster analysis were used to further process the CCTL data. This research provided a new perspective on CTL through designing a heterogeneous electron allocator catalyst and a circulating flow system.

High-throughput assessment of microplastic (MP) contamination in complex waters remains challenging because particle-resolved methods are low-throughput and inherently limited by size-dependent detection, particularly for nanoplastics. Here we report a UV-triggered chemiluminescence (CL) bulk-screening assay in which microplastic-derived dissolved organic matter (MP-DOM) generated during controlled UV weathering is transduced into a quantitative luminol-H2O2 flow-injection CL (FIA-CL) readout. Each measurement requires only a 30 min pretreatment, 1 mL of sample, and a few-minute analysis. Polyethylene (PE) and polystyrene (PS) produced reproducible, time-resolved CL transients, and peak intensity responded linearly to MP loading over 0.1-0.5 g L-1 (R2 > 0.92) with polymer-dependent sensitivity. The assay performed optimally under near-neutral pH and 30 min irradiation conditions, while iron oxide (Fe2O3) was identified as a major interferent that markedly suppressed emission. Optical characterization (UV absorbance and EEM-PARAFAC) showed that CL intensity correlated with dissolved organic carbon and humic-like components (R2 = 0.43-0.60), suggesting that both the amount and composition of UV-generated MP-DOM contribute to signal generation. Application to urban streamwater and wastewater effluent demonstrated the assay's utility in realistic matrices. Overall, the UV-assisted FIA-CL approach provides a rapid, mechanistically supported complementary bulk-screening surrogate for comparative assessment of MP contamination across aquatic samples.

Cubic boron nitride (c-BN) is a promising catalyst or catalyst substrate with good thermal, chemical, and mechanical stability. However, the large bandgap (Eg) limits its photocatalytic activity under visible light, but it is able to work in the UV region or can be used as a composite with other narrow Eg semiconductors. In this theoretical study, we investigate the structural, electronic, optical, and thermodynamic properties of c-BN nanoparticles using density functional theory (DFT) calculations within the CASTEP and Dmol3 frameworks. The computed Raman, FTIR, and XRD spectra confirm a cubic zinc-blende-like structure of c-BN. Electronic structure calculations using generalized gradient approximations (GGA), B3LYP, and HSE06 functionals show a direct bandgap of 4.533 eV (GGA/PBE), 4.381 eV (B3LYP), and 4.507 eV (HSE06), consistent with UV-limited absorption, and illustrate its limited visible-light absorption. Density of states and electron localization function analyses highlight the polar covalent B─N bonding and charge distribution, revealing that boron p-orbital states are dominant in the conduction band (CB) while nitrogen p-orbital states are mostly available in the valance band (VB), and this inequality of state distribution makes B atoms good electron acceptors and N atoms good donors during the catalysis process. Thermodynamic properties also indicate thermal stability and suitability for high-temperature catalysis. Phonon dispersion analysis also confirms dynamical stability, with no imaginary frequencies. Optical property analysis shows a broad and intense absorption peak, high dielectric response, and low reflectivity, which suggests a favorable electron-hole separation. A wide band edge alignment of c-BN relative to water redox potentials suggests that c-BN can drive the generation of reactive oxygen species, which support its potential in photocatalysis, such as water splitting and pollutant degradation.

Sedentary behavior is a recognized and modifiable risk factor for cognitive decline and dementia across neurodegenerative conditions. This study used a smartwatch-based telemonitoring procedure combined with ecological cognitive assessment to examine whether step counts can capture sedentary behavior and its association with cognitive functioning in patients with mild cognitive impairment (ADMCI) and dementia (ADD) due to Alzheimer's disease. Then, 19 ADD, 28 ADMCI, and 23 cognitively unimpaired older adults (Nold) were consecutively recruited. Participants underwent clinical assessment, resting-state electroencephalography (rsEEG), and neuropsychological testing. They were then monitored at home for approximately one week using Samsung Galaxy Watch 4-6 devices recording step counts (total, purposeful, and incidental) and activity intensity (peak 30-min cadence), together with the unsupervised SmartMe&You-TELEMAIA serious videogame battery administered on a commercial tablet for cognitive assessment. The ADD group showed reduced step counts and lower peak cadence than both ADMCI and Nold participants, whereas rsEEG markers and cognitive measures discriminated the three groups with a graded pattern. Within the AD sample, smartwatch-derived activity metrics were associated with cognitive functioning as assessed by conventional neuropsychological testing and ecological serious videogame performance, but showed limited associations with rsEEG rhythms. EEG delta and alpha rhythms were also more abnormal in the ADD group than in the ADMCI group. Home-based daytime activity monitoring with commercial smartwatches indicated that step volume and intensity are associated with cognitive status in patients with ADMCI and ADD. These findings suggest that smartwatch-derived activity metrics may provide feasible and cost-effective markers of everyday functioning in Alzheimer's disease.

Delayed graft function (DGF) remains a relevant early complication after kidney transplantation (KT), and reliable non-invasive imaging markers may improve postoperative graft assessment. We retrospectively evaluated 381 KT recipients who underwent colour Doppler (CD) ultrasound (US) on postoperative day (POD) 1 and before discharge between January 2013 and February 2022. Resistive index (RI) measurements were analyzed in relation to DGF, defined as the need for at least one dialysis session within the first postoperative week. A prospective pilot subgroup of 25 recipients transplanted between February 2021 and February 2022 also underwent contrast-enhanced US (CEUS) between POD 1 and 3, with analysis of wash-in slope (WIS), time to peak (TTP), peak intensity (PI), and area under the curve (AUC). In the retrospective cohort, 71 (18.6%) developed DGF. Higher RI values on POD 1 and before discharge were significantly associated with DGF. In the CEUS pilot subgroup, 7 patients (28.0%) developed DGF. Among CEUS-derived parameters, AUC was significantly associated with DGF, with lower values in patients who developed DGF and a valuable ROC AUC of 0.794. These findings support a role for early postoperative CD in graft function assessment and suggest that CEUS-derived AUC may provide valuable complementary information in the early evaluation of grafts for DGF. However, the CEUS results are exploratory and require validation in larger prospective studies.

Baseline correction is a critical preprocessing step to eliminate non-Raman scattering backgrounds in the Raman/SERS spectrum, ensuring accurate peak positions and intensities for qualitative and quantitative analysis. Recently, various machine learning-based approaches have been proposed for automatic baseline correction. Nevertheless, their generalizability is constrained, since neither background physicochemical origins nor critical fitting parameters are fully understood. Therefore, we developed AirNet, an automated baseline correction algorithm that integrates deep learning with chemometrics to balance global smoothness and local fidelity. AirNet includes three steps: (1) Raman peaks and baselines are identified with initialized weights by a ResUnet-based model; (2) an optimal smoothing parameter is adaptively selected by a multi-indicator evaluation strategy; (3) a reliable baseline is achieved with refined weights by a dynamic and robust adaptive iteratively reweighted penalized least squares (Dr-airPLS) under optimized smoothness. On both simulated and experimental Raman spectra, AirNet outperforms algorithms like airPLS, OP-airPLS, and DIRAS in both accuracy and generalizability, with a speed of 0.3 s per spectrum. Furthermore, the Homologous Model of AirNet ensures consistent baseline correction across homologous spectra. The segmented fitting strategy applies a region-specific smoothing parameter, facing a Raman spectrum with drastically changed background gradients. AirNet extracts high-fidelity Raman spectral information, providing a solid basis for reliable spectrum-structure correlation.

After a chemical terrorist attack involving nonvolatile and persistent nerve agents with extremely high dermal toxicity, rapid identification of the contaminated area and confirmation of decontamination is important. A method for swabbing surfaces suspected of contamination and conducting screening analysis for the presence of nerve agents will facilitate rapid completion of decontamination activities. In this study, a commercially available nano liquid chromatograph/high-resolution mass spectrometer was modified at low cost to develop an ambient ionization mass spectrometer with atmospheric pressure corona discharge ionization (APCDI) capabilities. The detection performance of the system for nonvolatile nerve agents (VX, RVX, A-230, A-232, A-234, A-242, and A-262) was examined. Monoisotopic peaks of the protonated molecules and their characteristic product ion spectra were observed for all tested compounds. For VX, A-230, and A-242, the detection limits when monitoring the monoisotopic peaks ranged from 0.025 to 0.25 ng. Novichok compounds exhibited higher sensitivity than VX or RVX, although the calculated gas phase basicity values showed little difference among the compounds. Peak intensity reproducibility showed intraday variation of 4.32-31.1% and interday variation of 8.95-44.1%. For samples collected on foam polyethylene swabs, the detection limits of the protonated molecules of VX, A-230, and A-242 were 10-100 ng for samples collected from stainless steel surfaces. This detection limit range is sufficient for screening of contaminated areas. When investigating the sample stability on swabs after collection, we found VX and A-230 remained detectable for 7 days and A-242 remained detectable for 3 days after swabbing of 1000 ng from a stainless steel surface. This developed analytical system is considered suitable for off-site analysis.

Three-dimensional organ-resolved modeling of ultrasound-induced acoustic and thermal effects in the mouse abdomen.

We investigated the deformation mechanism of a phenyl urazole-functionalized polybutadiene elastomer crosslinked via hydrogen bonds (H-bonds) using rheo-optical near-infrared (NIR) spectroscopy and two-dimensional correlation spectroscopy (2D-COS). The elastomer sample experienced tensile deformation while being probed by a high-speed NIR spectrometer equipped with an acousto-optic tunable filter (AOTF). The main feature of the NIR spectra of the elastomer sample is a change in the intensity of a broad peak consisting of multiple sub-peaks each reflecting different states of H-bonding. The NIR spectra was then subjected to 2D-COS analysis to resolve overlapping H-bonding bands, enabling their sequential structural evolution to be determined. Asynchronous analysis suggested that the deformation of H-bonds in the soft matrix likely precedes the disruption of rigid aggregates. This study demonstrates the utility of 2D-COS-assisted rheo-optical NIR spectroscopy in revealing the behavior of H-bonds in elastomers under stress.

This study investigates the photoabsorption cross-section spectra of the atmospheric volatile organic compound acrolein in both gas and aqueous phases by incorporating nuclear quantum effects (NQEs) at the cost of classical molecular dynamics. Using adaptive quantum thermal bath (adQTB) method the zero point energy leakage (ZPEL) is treated, which has plagued standard quantum thermal bath (QTB) dynamics. The spectroscopic results obtained are in excellent agreement with quantum molecular dynamics (path-integral MD) method, experimental observation and previous works on photoabsorption spectrum of acrolein molecule. The adQTB approach was able to capture weak n → π* transitions and broadening in the gas phase, as well as the blue shift and reduced peak intensity due to solvent effects in the aqueous phase. The adQTB method is shown to perform─if not better─at par with PIMD in gas and solvent phase while being much superior to classical MD and standard QTB method particularly for solvated systems. This work shows that using adQTB method, it is possible to overcome the ZPEL and use the QTB-based method to study spectroscopic properties.

Fourier transform ion cyclotron resonance mass spectrometry (FT-ICR MS) enables nontargeted identification of molecular formulas in natural organic matter (NOM), yet molecular-level isotope analysis at natural abundance remains limited. Here, we present a comprehensive workflow for molecular formula–specific isotope analysis (MSIA) in NOM using FT-ICR MS, including calibration against universal reference materials (RMs). The central step of MSIA is an intensity-tuning strategy that, with sufficient spectral averaging, achieves sub–per mil (‰) precision and accuracy and enables robust isotopic comparison (Δδ13C) across samples. Between terrestrial and marine NOM, we observed Δδ13C values of 17.3, 8.8, and 10.1‰ for marine-enriched formulas C19H22O10, C20H26O9, and C20H24O9, respectively, whereas an invariant formula, C18H22O6, showed a nonsignificant difference (Δδ13C = 2.7‰, P = 0.296). Matrix effects for RMs spiked into NOM were within the method uncertainty, rendering existing RMs suitable for MSIA when matched in carbon number, peak intensity, and mass (<50 daltons). Under these conditions, molecular formula–level δ13C values were obtained, e.g., −46.8‰ for C18H22O6 in terrestrial NOM.