Search Results (116)

In order to break through the difficulties with a very-low-frequency (VLF) miniaturized antenna with small power capacity and low radiation efficiency, this paper proposes a high-radiation-field-strength magnetic loop antenna based on a nanocrystalline alloy magnetic core. A high-permeability nanocrystalline toroidal core (μ_r = 50,000, B_s = 1.2 T) is used to optimize the thickness-to-diameter ratio (t = 0.08) and increase the effective permeability to 11,000. The Leeds wires, characterized by their substantial carrying capacity, are manufactured through a toroidal winding process. This method results in a 68% reduction in leakage compared to traditional radial winding techniques and enhances magnetic induction strength by a factor of 1.5. Additionally, this approach effectively minimizes losses, thereby facilitating support for kilowatt-level power inputs. A cascaded LC resonant network (resonant capacitance 2.3 μF) and ferrite balun transformer (power capacity 3.37 kW) realize a 20-times amplification of the input current. A series connection of a high-voltage isolation capacitor blocks DC bias noise, guaranteeing the stable transmission of 1200 W power, which is 6 times higher than the power capacity of traditional ring antenna. At 7.8 kHz frequency, the magnetic field strength at 120 m reaches 47.32 dBμA/m, and, if 0.16 pT is used as the threshold, the communication distance can reach 1446 m, which is significantly better than the traditional solution. This design marks the first instance of achieving kilowatt-class VLF effective radiation in a compact 51 cm-diameter magnetic loop antenna, offering a highly efficient solution for applications such as mine communication and geological exploration. Full article

Low-permittivity microwave dielectric ceramics are essential for high-frequency communication and radar systems, as they minimize signal delay and interference, thereby enabling compact and high-performance devices. In this study, LiAl_5−xNi_xO_8−0.5x (x = 0.1–0.5) ceramics were synthesized via a solid-state reaction method to investigate the effects of Ni²⁺ substitution on crystal structure, microstructure, and dielectric properties. X-ray diffraction and Rietveld refinement reveal a phase transition from the P4₃32 to the Fd$\stackrel{-}{3}$m spinel structure at x ≈ 0.3, accompanied by a systematic increase in the lattice parameter (7.909–7.975 Å), attributed to the larger ionic radius of Ni²⁺ compared to Al³⁺. SEM analysis confirms dense microstructures with relative densities exceeding 95% and grain size increases from less than 1 μm at x = 0.1 to approximately 2 μm at x = 0.5. Dielectric measurements show a decrease in permittivity (ε_r) from 8.24 to 7.77 and in quality factor (Q × f) from 34,605 GHz to 20,529 GHz with increasing Ni content, while the temperature coefficient of the resonant frequency (τ_f) shifts negatively from −44.8 to −69.1 ppm/°C. Impedance spectroscopy indicates increased conduction losses and reduced activation energy with higher Ni²⁺ concentrations. Full article

Peptides designed to interfere with specific steps of viral infection mechanisms have shown promising antiviral potential. In this study, we investigated the ability of a synthetic peptide (peptide 303), derived from the fusion protein sequence of the Infectious Salmon Anemia Virus (ISAV), to inhibit membrane fusion mediated by the ISAV fusion peptide (ISAV-FP1). To assess this, we employed a model membrane system consisting of large unilamellar vesicles (LUVs) composed of 1,2-dioleoyl-sn-glycero-3-phosphocholine (DOPC), dipalmitoylphosphatidylcholine (DPPC), and cholesterol. Membrane fusion kinetics were monitored via R18 fluorescence dequenching. Additionally, the interaction of peptide 303 with lipid membranes was evaluated using fluorescence anisotropy measurements. The potential direct interaction between peptide 303 and ISAV-FP1 was further examined through Förster Resonance Energy Transfer (FRET) assays. Our results demonstrate that peptide 303 effectively inhibits ISAV-FP1-mediated membrane fusion. Furthermore, peptide 303 was shown to interact with lipid bilayers and with ISAV-FP1 itself. These findings suggest a dual inhibitory mechanism in which peptide 303 both prevents ISAV-FP1 binding to the membrane and directly interacts with the fusion peptide, thereby disrupting its fusogenic activity. Full article

This article introduces a microwave sensor tailored for skin hydration monitoring. The design enables wireless operation by separating the sensing component from the reader, making it ideal for wearable devices like wristbands. The sensor consists of a semi-lumped $LC$ resonator coupled to an inductive coil reader, where the capacitive part of the sensing tag is in contact with the skin. The variations in the skin hydration level alter the dielectric properties of the skin, which, in turn, modify the resonances of the $LC$ resonator. Experimental in vivo measurements confirmed the sensor’s ability to distinguish between four hydration conditions: wet skin, skin treated with moisturizer, untreated dry skin, and skin treated with Vaseline, by measuring the resonance frequencies of the sensor. Measurement of the input reflection coefficient ($S_{11}$) using a vector network analyzer (VNA) revealed distinct reflection poles and zeros for each condition, demonstrating the sensor’s effectiveness in detecting skin hydration levels. The sensing principle was analyzed using an equivalent circuit model and validated through measurements of a fabricated sensor prototype. The results confirm in vivo skin hydration monitoring by detecting frequency shifts in the reflection response within the 50–200 MHz range. The measurements and data analysis show less than $0.037\%$ error in transmission zero ($f_z$) together with less than $1.5\%$ error in transmission pole ($f_p$) while being used to detect skin hydration status on individual human subjects. The simplicity of the detection method, focusing on key frequency shifts, underscores the sensor’s potential as a practical and cost-effective solution for non-invasive skin hydration monitoring. This advancement holds significant potential for skincare and biomedical applications, enabling detection without complex signal processing. Full article

Background/Objectives: Dihydromyricetin (DHM), a flavonoid with abundant natural sources, potent bioactivity, and high safety, holds promise for translational applications, particularly in mitigating skin aging. However, its role and underlying mechanisms in counteracting skin aging induced by advanced glycation end products (AGEs) remain unclear. Methods: Eight-week-old male Sprague-Dawley (SD) rats were subcutaneously injected with 500 mg/kg D-galactose and administered DHM via gavage for 11 weeks. Additionally, senescent human skin fibroblasts (HFF-1) induced by AGEs were used for further investigation. Results: DHM treatment significantly alleviated D-galactose-induced skin aging in rats, with the most pronounced effects observed in the moderate-dose group (100 mg/kg). Compared to the aging group, DHM enhanced skin elasticity and preserved collagen levels. Moreover, DHM promoted cell proliferation in the skin. Further studies on AGE-induced senescent fibroblasts revealed that DHM markedly reduced multiple senescence-associated markers and stimulated cell proliferation by approximately a 1.5-fold increase. Transcriptomic analysis indicated that DHM upregulated genes related to the cell cycle and DNA repair while suppressing AGE-RAGE signaling and its downstream pathways. Notably, DHM downregulated AGER, the gene encoding the receptor for AGEs (RAGE). Molecular docking analysis demonstrated that DHM shares a binding site with other known RAGE inhibitors. Surface plasmon resonance (SPR) analysis further confirmed the high binding affinity of DHM to RAGE (K_D = 28.7 μM), which was stronger and more stable than that of FPS-ZM1 (K_D = 40.7 μM). Conclusions: DHM may attenuate glycation-induced skin aging in rats by functioning as a RAGE inhibitor, thereby suppressing AGE-RAGE signaling, delaying cellular senescence, and promoting cell proliferation. Full article

N-acetylaspartate (NAA) is the second most abundant metabolite in the human brain. Quantifiable amounts of NAA are also present in the blood, but its role in the peripheral tissues is largely unknown. First, we determined the acute effects of insulin administration on NAA concentrations; second, we assessed whether circulating NAA levels associate with markers of central and peripheral insulin sensitivity. A total of 24 persons living with obesity and 19 healthy, lean controls, without neurological disorders, underwent a euglycemic hyperinsulinemic clamp combined with fluorodeoxyglucose positron emission tomography ([¹⁸F]FDG-PET) imaging of the brain, abdomen, and femoral area. Plasma concentrations of NAA were measured at baseline and ~2 h into the clamp using high-performance liquid chromatography coupled with tandem mass spectrometry (HPLC-MS-MS). Glucose uptake (GU) rates were analysed using a fractional uptake rate. Serum acetate levels were also assessed using nuclear magnetic resonance (NMR) metabolomics. From baseline to steady-state, insulin levels increased from a mean level of 66 to 447 pmol/L (p < 0.0001). Over this period, circulating NAA concentrations decreased by 5% (p = 0.01), similarly in both groups. The change in NAA was inversely related with the change in plasma acetate (r = −0.36, p = 0.048). Circulating NAA was associated with waist–hip ratio (rho = −0.54, p = 0.0002), steady-state free fatty acids (rho = −0.44, p = 0.003), and directly with HDL cholesterol (rho = 0.54, p = 0.0002), adiponectin (rho = 0.48, p = 0.003), and whole-body insulin sensitivity (rho = 0.34, p = 0.03). Circulating NAA was directly related with skeletal muscle (rho = 0.42, p = 0.01) and visceral adipose tissue GU (rho = 0.41, p = 0.02). Insulin administration leads to a small decrease in circulating NAA levels, and NAA associates consistently with markers of insulin sensitivity. While plasma NAA may be relevant to aspects of whole-body homeostasis, mechanistic insights are needed. Full article

Background/Objectives: Connectomics is an evolving branch of neuroscience that determines structural and functional connectivity in the brain. The objective of this prospective imaging study is to evaluate the effect of whole brain radiotherapy (WBRT) on the connectome. Methods: A combination of diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) was used to study the structural and functional connectivity of the brain, and a machine learning algorithm trained to analyze subject-specific data was applied to create individualized brain maps with 15 neuronal networks for each patient. These brain maps were compared to normal brains from the human connectome project, producing an anomaly matrix. Connectome analysis and multi-dimensional neurocognitive testing on a web-based platform were performed at baseline and 3 months post-WBRT. The change in anomaly frequency was co-related with neurocognitive outcomes. Results: At baseline, connectome analysis revealed that the multiple demand network had the most anomalies (46%). Pre- and post-WBRT comparison revealed increases in proportional anomaly frequency across multiple networks. Pearson correlation showed correlation between neurocognitive domain decline and anomaly changes: learning and memory domain with subcortical network [Verbal recall (Pearson coefficient −0.94; p < 0.01), verbal revision (Pearson coefficient −0.89; p = 0.01), and verbal recognition (Pearson coefficient −0.94; p < 0.01)]. Conclusions: This proof-of-concept study integrated data from DTI and fMRI in the form of connectome and revealed significant changes in brain connectivity, with WBRT that also correlated with neurocognitive outcomes. Further studies in a larger cohort are underway, and correlations with white matter changes and tumor locations/numbers will be performed. Full article

(1) Background: Neoadjuvant chemotherapy (NAC) is an integral part of breast cancer management, and response to NAC is an important prognostic factor associated with improved survival outcomes. However, the current standard for response assessment relies on post-surgical histopathological analysis, which limits early therapeutic decision-making and treatment personalization. This study aimed to develop and evaluate a machine learning model that integrates pre-treatment MRI radiomics and clinical features to predict response to NAC in breast cancer patients. (2) Methods: In this study, a machine learning model was developed to predict breast cancer response to NAC using pre-treatment magnetic resonance imaging (MRI) radiomics and clinical data. Radiomic features were extracted from contrast-enhanced T1-weighted (CE-T1) and T2-weighted (T2) MRI sequences using both intratumoral and peritumoral segmentations. Furthermore, this study uniquely examined two response assessment criteria: (1) pathologic complete response (pCR) versus non-pCR, and (2) clinical response versus non-response. A total of 254 patients with biopsy-confirmed breast cancer who completed NAC were included. Radiomic features (n = 400) and clinical features (n = 7) were analyzed to build a predictive model employing the XGBoost classifier. Performance was measured in terms of accuracy, precision, sensitivity, specificity, F1-score, and AUC. (3) Results: The integration of radiomic features with clinical data significantly enhanced the predictive performance. For pCR and non-pCR prediction, the combined features model achieved an accuracy of 80% and AUC of 0.85, outperforming both the clinical features model (Accuracy = 68%, AUC = 0.81) and radiomic features model (Accuracy = 66%, AUC = 0.60). Similarly, for the clinical response and non-response prediction, the combined features model achieved an Accuracy of 74% and AUC of 0.75, outperforming both the clinical features model (Accuracy = 63%, AUC = 0.68) and radiomic features model (Accuracy = 66%, AUC = 0.57). (4) Conclusions: These findings highlight the synergistic effect of integrating clinical data and MRI-based radiomics to improve pre-treatment NAC response prediction, which has the potential to enable more precise and personalized treatment strategies. Full article

The study of vibration isolation devices has become an emerging area of research in view of the extensive damage to buildings caused by earthquakes. The ability to effectively isolate seismic vibrations and maintain the stability of a building is thus addressed in this paper, which evaluates the effect of horizontal ground excitation on the response of a structure isolated by a coupled isolation system consisting of a non-linear damper (QZS) and a friction pendulum system (FPS). A single-degree-of-freedom system was used to model structures whose bases are subjected to seismic excitation in order to assess the effectiveness of the QZS–FPS coupling in reducing the structural response. The results obtained revealed significant improvements in structural performance when the QZS–FPS system uses a damper of optimum stiffness. A 30% reduction in displacement was recorded compared with QZS alone for two signals, one harmonic and the other stochastic. The response of the QZS–FPS system with soft stiffness to a harmonic pulse reveals amplitudes reaching around eight times those of the pulse at low frequencies and approaching zero at high frequencies. In comparison, the rigid QZS–FPS coupling has amplitudes 0.9 and 3.5 times higher than those of the harmonic signal. Thus, the resonance amplitudes observed for the QZS–FPS system are lower than those reported in other studies. This analysis highlights the performance differences between the two types of stiffness in the face of harmonic pulses, underlining the importance of the choice of stiffness in vibration management applications. The stochastic results show that on both hard and soft soils, the new QZS–FPS system causes structures to vibrate horizontally with maximum amplitudes of the order of 0.003 m and 0.007 m respectively. So, QZS–FPS coupling can be more effective than all other isolators for horizontal ground excitation. In addition, the study demonstrated that the QZS–FPS combination can offer better control of building vibration in terms of horizontal displacements. Full article

Acoustic temperature measurement (ATM) and sound source localization (SSL) are two important applications of acoustic sensors. The development of novel acoustic sensors capable of both ATM and SSL is an innovative research topic with great interest. In this work, an acoustic Fabry-Perot resonance detector (AFPRD) and its cross-shaped array were designed and fabricated, and the passive ATM function of the AFPRD and the SSL capability of the AFPRD array were simulated and experimentally verified. The AFPRD consists of an acoustic waveguide and a microphone with its head inserted into the waveguide, which can significantly enhance the microphone’s sensitivity via the FP resonance effect. As a result, the frequency response curve of AFPRD can be easily measured using weak ambient white noise. Based on the measured frequency response curve, the linear relationship between the resonant frequency and the resonant mode order of the AFPRD can be determined, the slope of which can be used to calculate the ambient sound velocity and air temperature. The AFPRD array was prepared by using four bent acoustic waveguides to expand the array aperture, which combined with the multiple signal classification (MUSIC) algorithm can be used for distant multi-target localization. The SSL accuracy can be improved by substituting the sound speed measured in real time into the MUSIC algorithm. The AFPRD’s passive ATM function was verified in an anechoic room with white noise as low as 17 dB, and the ATM accuracy reached 0.4 °C. The SSL function of the AFPRD array was demonstrated in the outdoor environment, and the SSL error of the acoustic target with a sound pressure of 35 mPa was less than 1.2°. The findings open up a new avenue for the development of multifunctional acoustic detection devices and systems. Full article

Background/Objectives: Advancements in biomedical imaging technologies over the past few decades have made it increasingly possible to measure the long-term effects of exercise on the central nervous system. This study aims to compare the brain morphology and functional connectivity of wrestlers and handball players, exploring sport-specific neural adaptations. Methods: Here, we examined 26 elite male athletes (13 wrestlers and 13 handball players) using anatomical and resting-state functional magnetic resonance imaging (fMRI) measurements. Connectivity maps are derived using the seed-based correlation analysis of resting-state fMRI, while voxel-based morphometry (VBM) is employed to identify anatomical differences. Additionally, the cortical thickness and global volumetric values of the segmented images are examined to determine the distinctions between elite wrestlers and handball players using non-parametric statistical tests. Results: Wrestlers exhibited greater grey matter volume (GMV) in the right middle temporal gyrus, left middle frontal gyrus, and right posterior cingulate gyrus (uncorr., p < 0.001). On the other hand, wrestlers showed increased functional connectivity in the left superior temporal gyrus, left parahippocampal gyrus, the left anterior orbital gyrus, and right superior frontal gyrus–medial frontal region (P(_FWE) < 0.05). In addition, wrestlers showed greater cortical thickness in several brain regions. Conclusions: The increased GMV, cortical thickness, and functional connectivity observed in wrestlers highlight the presence of sport-specific neural adaptations. While this research provides valuable insights into the neuroplastic effects of various athletic disciplines, further studies involving additional sports and control groups are needed for a more comprehensive understanding. Full article

Many antifungal agents, including isoconazole nitrate (ISN), suffer from low aqueous solubility and inconsistent dissolution kinetics, which limit their therapeutic potential. To address these challenges, this study aimed to enhance the solubility and stability of ISN through the development of inclusion complexes with hydroxypropyl-β-cyclodextrin (HP-β-CD). HP-β-CD inclusion complexes were prepared using a spray-drying technique and characterized through phase-solubility studies, scanning electron microscopy (SEM), Fourier transform infrared spectroscopy (FT-IR), proton nuclear magnetic resonance (¹H-NMR), and differential scanning calorimetry (DSC). The inclusion complex significantly improved ISN solubility, increasing from 0.5088 mg/mL to 3.6550 mg/mL. These complexes were incorporated into a thermosensitive, mucoadhesive in situ gel system using Pluronic^® F127 and hydroxypropyl methylcellulose (HPMC) to optimize vaginal drug delivery. The formulations were evaluated for gelation temperature, viscosity, swelling behavior, and pH, confirming their suitability for vaginal application. Antimicrobial studies demonstrated that the ISN/HP-β-CD gels exhibited superior activity against Candida albicans, C. glabrata, and C. krusei compared to ISN alone. In vitro release studies further revealed sustained drug release following Peppas-Sahlin kinetics, supporting enhanced bioavailability and prolonged therapeutic action. This study demonstrates that the ISN/HP-β-CD-loaded in situ gel system offers a promising and effective approach for improving the solubility, stability, and antifungal efficacy of ISN for the treatment of vaginal infections. Full article

Background: In neuroscience research about functional magnetic resonance imaging (fMRI), accurate inter-subject image registration is the basis for effective statistical analysis. Traditional fMRI registration methods are usually based on high-resolution structural MRI with clear anatomical structure features. However, this registration method based on structural information cannot achieve accurate functional consistency between subjects since the functional regions do not necessarily correspond to anatomical structures. In recent years, fMRI registration methods based on functional information have emerged, which usually ignore the importance of structural MRI information. Methods: In this study, we proposed a non-rigid cycle consistent bidirectional network with Transformer for unsupervised deformable functional MRI registration. The work achieves fMRI registration through structural MRI registration, and functional information is introduced to improve registration performance. Specifically, we employ a bidirectional registration network that implements forward and reverse registration between image pairs and apply Transformer in the registration network to establish remote spatial mapping between image voxels. Functional and structural information are integrated by introducing the local functional connectivity pattern, the local functional connectivity features of the whole brain are extracted as functional information. The proposed registration method was experimented on real fMRI datasets, and qualitative and quantitative evaluations of the quality of the registration method were implemented on the test dataset using relevant evaluation metrics. We implemented group ICA analysis in brain functional networks after registration. Functional consistency was evaluated on the resulting t-maps. Results: Compared with non-learning-based methods (Affine, Syn) and learning-based methods (Transmorph-tiny, Cyclemorph, VoxelMorph x2), our method improves the peak t-value of t-maps on DMN, VN, CEN, and SMN to 18.7, 16.5, 16.6, and 17.3 and the mean number of suprathreshold voxels (p < 0.05, t > 5.01) on the four networks to 2596.25, and there is an average improvement in peak t-value of 23.79%, 12.74%, 12.27%, 7.32%, and 5.43%. Conclusions: The experimental results show that the registration method of this study improves the structural and functional consistency between fMRI with superior registration performance. Full article

Patients diagnosed with multiple endocrine neoplasia type-1 (MEN1) often initially present with primary hyperparathyroidism (pHPT), and typically undergo surgical intervention. While laboratory tests are fundamental for diagnosis, imaging is crucial for localizing pathological parathyroids to aid in precise surgical planning. In this pictorial review, we will begin by comprehensively examining key imaging techniques and their established protocols, evaluating their effectiveness in detecting abnormal parathyroid glands. This analysis will emphasize both the advantages and potential limitations within the clinical context of MEN1 patients. Additionally, we will explore integrated imaging approaches that combine multiple modalities to enhance localization accuracy and optimize surgical planning—an essential component of holistic management in MEN1 cases. Various imaging techniques are employed for presurgical localization, including ultrasound (US), multiphase parathyroid computed tomography (CT) scanning (4D CT), magnetic resonance imaging (MRI), and nuclear medicine techniques like single photon emission computed tomography/CT (SPECT/CT) and positron emission tomography/CT (PET/CT). US is non-invasive, readily available, and provides high spatial resolution. However, it is operator-dependent and may have limitations in certain cases, such as intrathyroidal locations, the presence of bulky goiters, thyroid nodules, and previous thyroidectomy. Four-dimensional CT offers dynamic imaging, aiding in the identification of enlarged parathyroid glands, particularly in cases of ectopic or supernumerary glands. Despite concerns about radiation exposure, efforts are underway to optimize protocols and reduce doses, including the use of dual-energy CT. MR imaging offers excellent soft tissue contrast without radiation exposure, potentially providing superior differentiation between parathyroid glands and the surrounding structures. Radionuclide imaging, especially PET/CT using radiopharmaceuticals like [¹⁸F]FCH, shows promising results in localizing parathyroid tumors, particularly in patients with MEN1. [¹⁸F]FCH PET/CT demonstrates high sensitivity and may provide additional information compared to other imaging modalities, especially in cases of recurrent HPT. Full article

This study investigated the optimization of setpoint conditions used for the enhanced biofabrication of silver nanoparticles (H.C-AgNPs) using Helichrysum crispum extracts. A Box–Behnken Design (BBD) model was used to evaluate the effects of reaction time, temperature, an H. crispum extraction volume, and a 0.1 M AgNO₃ solution volume. A second-order polynomial regression equation was developed with a high R² of 0.9629, indicating that the model explained 96.29% of the variability in the data. The statistical significance of the model was confirmed with an F-value of 25.92 and a p-value of less than 0.0001. The optimal biofabrication conditions were determined to be a reaction time of 60 min, a temperature of 50 °C, an H. crispum extract volume of 10 mL, and a silver nitrate volume of 90 mL, achieving a peak absorbance of 3.007 a.u. The optimized conditions were experimentally validated, resulting in an absorbance of 3.386 a.u., reflecting a 12.6% increase. UV-Vis spectroscopy showed a distinct surface plasmon resonance (SPR) peak at 433 nm. XRD analysis confirmed a crystalline face-centered cubic (FCC) structure with a primary diffraction peak at 2θ = 38.44° (111 plane). SEM and EDS results confirmed a uniform size and high purity, while FTIR spectra confirmed the involvement of phytochemicals in nanoparticle stabilization. TEM analysis revealed a uniform particle size distribution with a mean size of 19.46 nm and a dispersity of 0.16%, respectively. These results demonstrate the importance of statistical tools in optimizing the setpoint conditions used in the biofabrication of AgNPs, which have applications in various fields. Full article