Assessment of microstructural and elemental changes in mango tissue induced by pulsed magnetic field pretreatment and freezing using SEM–EDS

The article documents the cause of a sharp decrease in the fracture toughness of HR3C austenitic steel intended for heat exchange surfaces of supercritical energy blocks during its exposure to elevated temperature. The documentation of the cause of the decrease in fracture toughness is based on a combination of fractographic observation of the fracture surfaces of the tested samples, linked through ongoing precipitation changes in the steel to the fracture toughness of the steel. The result is a description of the decrease in fracture toughness in relation to the Larson-Miller parameter and subsequently the change in fracture toughness in relation to the precipitation changes in HR3C steel. This dependence provides a tool for numerical calculations and simulations of heat exchange surfaces of power plants made of HR3C steel and the simulation of their behavior when cracks are present.

The heart undergoes substantial structural changes in response to new physiological demands, which occur with the rapid opening of pulmonary circulation immediately after birth. The dependence on pulmonary circulation causes an immediate increase in ventricular workload, resulting in microstructural changes that serve to maintain overall physiological homeostasis. Ageing continues to evolve the heart's structure due to increased myocardial tissue stress and strain, initiating the formation of a new extracellular matrix to facilitate the physiology of an adult. Quantifying the region-specific and age-dependent microstructural changes in tissue due to ageing is pivotal for the development of constitutive models for computational simulations. This study aimed to determine the microstructure of porcine ventricles at four time points from neonatal to adulthood. The three-dimensional microstructure was investigated using diffusion-tensor magnetic resonance imaging, two-photon excited fluorescence and second-harmonic generation microscopy to quantify fibre tractography, fractional anisotropy (FA), spherical measure, rotation and dispersion of cardiomyocytes and collagen fibrils. The results revealed that the left ventricle possessed greater FA than the right. Adult hearts demonstrated smaller FA than the young. The anterior left and right ventricles exhibited greater cardiomyocyte and collagen fibril rotation and dispersion than the posterior. The adult hearts possessed greater cardiomyocyte and collagen fibril rotation and dispersion than young hearts. The right ventricle demonstrated greater cardiomyocyte rotation in the younger hearts, and the Left in the adult. This study provides baseline data that should prove useful to bioengineers, researchers, and mathematicians in developing region-specific and age-dependent constitutive models to enhance the accuracy and bio-fidelity of computational simulations.

Wire arc directed energy deposition (WA-DED) is a cost-efficient additive manufacturing process with high deposition rates, yet the prediction of resulting mechanical properties remains challenging due to repeated thermal cycling and associated microstructural changes. Accordingly, this work aims to validate a hardness prediction model for DIN SG2 by Härtel et al. For this purpose, a demonstrator was designed, manufactured, and simulated using a thermal finite element model in the standard software Simufact Welding 2025. Since the DED module of the software used does not adequately represent active interlayer cooling, four substitute models for the convective heat transfer coefficient were implemented and evaluated. In addition, the original hardness prediction model was refined to consider complex path planning, remelting effects and a material-dependent lower temperature limit for tempering or heat treating the material. Using a substitute model that adjusts the convective heat transfer coefficient over time, the improved hardness prediction the adjusted hardness prediction model achieved an accuracy of ±5% for 81 of 88 evaluated measurement points. In order to enable an efficient and reproducible comparison between simulation and experiment, a Python evaluation script was developed. This tool automatically identifies relevant temperature peaks, correlates them with hardness data, creates individual evaluation diagrams and a comparison diagram, and exports all processed data to an Excel file.

Previous investigations into neurodegenerative diseases demonstrated the utility of cortical diffusivity metrics in assessing microstructural changes. The objective of this study was to explore cortical diffusivity metrics in genetic Parkinson's disease (PD) with glucocerebrosidase 1 (GBA1) and Leucine-rich repeat kinase 2 (LRRK2) mutations, encompassing both nonmanifest carriers (NMCs) and manifest PD, and healthy control subjects (HCs). T1-structural and diffusion magnetic resonance imaging (MRI) scans were analyzed to calculate diffusion metrics related to cortical columnar structure (angle between the radial minicolumnar axis and the principal diffusion direction [AngleR], parallel diffusivity [ParlPD], perpendicular diffusivity of multiple components [PerpPD+]) and cortical mean diffusivity for 143 participants (60 HCs, 19 NMC GBA1, 30 NMC LRRK2, 11 PD GBA1, and 23 PD LRRK2) from the Parkinson's Progression Markers Initiative (PPMI). The first available time point including both T1-weighted and diffusion MRI acquisitions was used for each participant. Whole-brain, regional, and functional hierarchy macroregional values were used to investigate group differences. Results are reported after multiple comparison correction. Grouped together, results indicated significantly lower ParlPD values in manifest PD compared with the NMC group in whole-brain analysis. Regional analyses showed a progressive reduction in cortical ParlPD across the genetic groups, primarily in mesocortex (Braak stage 4) for NMC cases, extending to neocortex (Braak stage 5) for manifest genetic PD. Subgroup analyses demonstrated a more pronounced pattern of cortical alterations in subjects with GBA1 mutations compared with patients with LRRK2 mutations. Cortical diffusivity metrics effectively capture cortical architectural changes across clinical stages of genetic PD, supporting their use as microstructural markers of neurodegeneration in PD. © 2026 International Parkinson and Movement Disorder Society.

As a typical industrial solid waste-based concrete material, activated coal gangue cementitious concrete is prone to the freeze-thaw cycle in cold-region engineering applications, leading to durability degradation that severely limits its service performance. In this paper, freeze-thaw cycle tests were designed to reveal the influence of different ratio designs on the freeze resistance of materials. Scanning electron microscopy and nuclear magnetic resonance spectroscopy were employed to observe the microstructural changes in the internal pores of activated coal gangue cementitious concrete after freeze-thaw degradation. The optimal replacement ratio for activated coal gangue powder was analyzed. The results showed that, as the number of freeze-thaw cycles increased, the pore structure within the activated coal gangue cemented concrete deteriorated significantly, though the degree of deterioration varied. With the gangue powder content increasing, both the number of pores and porosity within the concrete initially decrease and then increase. According to the test results, when the activated coal gangue powder content was 35% in the concrete mix, the freeze-thaw resistance performance was optimal. This mixture maintained a good pore structure and superior porosity, indicating that the concrete with 35% activated coal gangue powder content was the best mix design. The result provides a reference for enhancing the freeze-thaw resistance of activated coal gangue cementitious concrete in cold environments.

Odor identification impairment is an early marker of Alzheimer's disease (AD) that predicts memory decline, yet its underlying microstructural basis remains unclear. We hypothesized that mild cognitive impairment (MCI) involves early myelin and lipid disruption within olfactory and limbic circuits, detectable using a synthetic MRI derived contrast that provides complementary sensitivity to myelin volume fraction (MVF). Methods: Thirty three older adults (healthy controls [HC], n = 16; mild cognitive impairment [MCI], n = 17) completed olfactory and cognitive testing and underwent 3T brain MRI using a QALAS sequence. An MVF map and synthetic FLAIR and DIR images were generated, and a FLAIR and DIR derived metric (FD) was computed as FD = (FLAIR - DIR) / FLAIR. We investigated ROI-based group differences in olfactory and limbic gray-matter regions and associated white matter tracts, voxel wise regressions investigating FD odor identification associations, and ROI based MCI vs HC classification using cross validated logistic regression models. Compared with HC, MCI showed significantly lower FD across olfactory and limbic gray matter regions and white matter pathways including hippocampus, amygdala, orbitofrontal cortex, thalamus, and corpus callosum whereas MVF differences were more limited. FD achieved moderate discrimination, with baseline performance comparable to MVF. Voxel wise analyses revealed that better odor identification was associated with higher FD in the hippocampus/parahippocampal and insula; the association persisted after adjusting for voxel wise MVF. MVF also showed significant positive voxel-wise associations with odor identification in the insula and genu of the corpus callosum. FD is a practical, myelin- and lipid-sensitive contrast derived from routinely acquired synthetic FLAIR & DIR images that complement quantitative MVF. It captures behaviorally relevant variance beyond local myelin content and may improve detection of early olfactory and limbic microstructural changes in MCI. These findings support FD as a scalable candidate marker linking early network disruption to olfactory symptoms across the AD continuum.

Warm‐stamped medium‐Mn steels have emerged as promising alternatives to conventional hot‐stamped boron steels for automotive structural applications due to their high strength and formability. This study investigates the resistance spot welded joints of a 2.0 GPa grade warm‐stamped medium‐Mn steel, focusing on microstructural evolution and mechanical property changes induced by paint baking (PB). Microstructural analysis revealed the coexistence of lath martensite and twinned martensite, along with dense dislocation tangles, in the fusion zone (FZ) of the as‐welded (AW) joint. Under cross‐tension testing, cracks initiated and partially propagated through the FZ of the AW joint, resulting in partial interfacial failure (PIF) with a peak load of approximately 3.65 kN and energy absorption of about 11.93 J. Following PB treatment, low‐temperature tempering was activated, as evidenced by the precipitation of fine cementite particles within the FZ, which enhanced toughness. Consequently, crack propagation resistance increased significantly, shifting the failure mode to complete pullout failure (PF). This transition was accompanied by substantial increases in peak load of approximately 101% and energy absorption of about 291% relative to the AW joint. In contrast, RSW joints of an equivalent‐strength 2.0 GPa hot‐stamped boron steel exhibited much smaller PB‐induced improvements. The superior PB response of the medium‐Mn steel is attributed to its lower martensite‐start ( Ms ) temperature (~295°C), which suppresses auto‐tempering during welding and preserves effective low‐temperature tempering capacity.

With global population aging and increased life expectancy, bone diseases affect a substantial proportion of individuals worldwide, imposing a significant socioeconomic burden. Although X-ray-based imaging techniques remain the clinical standard for bone assessment, they are constrained by ionizing radiation exposure and poor soft-tissue contrast. Magnetic resonance imaging (MRI) has emerged as a promising radiation-free alternative, enabling detailed evaluation of tissue properties, bone microstructure, functional status, and pathological changes. However, the intrinsically low proton density and rapid transverse relaxation of bone tissue present fundamental technical challenges. Over the past decades, numerous MRI-based techniques have been developed to address these limitations. Yet, the literature remains fragmented. This review synthesizes recent advancements in bone MRI, covering conventional sequences (e.g., T1-weighted and T2-weighted imaging), advanced sequences (e.g., ultrashort echo time and zero echo time), metabolic imaging sequences (e.g., magnetic resonance spectroscopy and dynamic contrast-enhanced MRI), and hardware innovations (e.g., ultra-high-field MRI at 7/14 T). The strengths and limitations of these techniques are discussed, and their roles are highlighted in early diagnosis, therapeutic monitoring, and management of diverse bone disorders, including osteoporosis, osteoarthritis, osteosarcoma, and osteonecrosis. Furthermore, we explore how artificial intelligence, particularly deep learning models, enhances MRI capabilities by reducing scanning time, adding synthetic contrasts like synthetic CT, improving image quality, and increasing diagnostic accuracy. Finally, we outline challenges and future directions to advance bone assessment. This comprehensive review may guide preclinical research and accelerate clinical translation of bone MRI techniques, ultimately improving musculoskeletal disease management. LEVEL OF EVIDENCE: 4. TECHNICAL EFFICACY: Stage 2.

Glauconite is an iron- and potassium-rich mineral of the mica family. It evolves at the soil-water interface through chemical exchange, its maturity linked to exposure duration at the seafloor and source element availability. Glauconite sands have been discovered at offshore wind lease areas along the U.S. Atlantic Outer Continental Shelf, leading to uncertainties in pile foundation installation and long-term performance. This paper describes site characterization activities from the Piling in Glauconitic Sand (PIGS) Joint Industry Project test site, located along the New Jersey Coastal Plain. In situ testing, laboratory-based geological, microstructure, and soil index testing, and advanced soil behavior measurements are presented in detail. Comparisons to selected silica sand-based cone penetration testing (CPT) correlations are made, highlighting the cautions needed for deriving soil parameters in this unique material. The measured properties and observed behavior exhibit a transition from sand-like to clay-like behavior during particle crushing due to compression and shear stresses from impact pile driving, which deviate from conventional sedimentary clays and sands. This transition can lead to changes in soil microstructure, plasticity, strength, and permeability, among others. The extensive dataset provides a reference for geotechnical practioners and researchers encountering other glauconite sand deposits or similar transitional sediments.

We use a minimal model for a dense suspension undergoing thickening and thinning to investigate microstructural changes in 2d simulations. Our simulations show that in steady flow the contact network contains distinct building blocks which are clearly signaled by sharp peaks in the radial distribution function, similar to what is observed in granular jamming. These structures deform during thinning. Non-Gaussian stress fluctuations that only emerge during thickening are associated to power law tails in the distribution of local contact forces, which tend to emerge when the flow-induced building blocks form large spanning assemblies. The subset of the contact network characterized by strong contact forces and connectivity large enough to be rigid or over-constrained is increasingly likely to percolate as the system starts to thicken, and to percolate over larger strain windows during thickening. The tendency of these structures to span the sample and to persist is dramatically reduced during thinning, where instead their deformation allows for a more homogeneous spatial redistribution of contact forces, significantly reducing the fluctuations of the macroscopic stress over time.

Abstract Laser Powder Bed Fusion (LPBF) research on aluminum alloys has predominantly focused on commercial Al–Si–Mg systems with modest Mg 2 Si contents, leaving the heat-treatment response of Mg 2 Si-rich compositions largely unexplored. This study investigates, for the first time, the hardness response of an LPBF-tailored aluminum alloy containing 3.94 ma% Mg 2 Si—over twice the equilibrium solid-state solubility limit—and identifies an optimized post-processing route to enhance mechanical performance. Three heat-treatment conditions were investigated: direct aging, solution annealing (SA), and combined solution annealing plus artificial aging (SA + A). Hardness mapping revealed that direct aging at 190 °C for 330 min achieved the highest hardness of 164 HBW2.5/67.5. The as-built and direct aged conditions were investigated using SEM, EBSD, and TEM to provide a comparative perspective of the microstructural changes that explain the increase in specimen hardness between the two conditions. The as-built state revealed a highly supersaturated α-Al matrix concentrated with early stage Al-, Mg- rich clusters and a refined Si network. In the direct aged condition, nanoscale precipitates were observed, consistent with the precipitation of Mg- and Si-rich phases responsible for the hardening response. The results indicate that the supersaturated solid solution generated during LPBF processing renders a solution-annealing step unnecessary, offering significant reductions in energy consumption. By correlating the heat-treatment routes with the resulting hardness and investigating the increase in hardness by microstructural investigations, this work provides a comprehensive comparison of post-processing routes and offers new insights into designing efficient, and sustainable thermal treatments for high performance aluminum alloys.

BackgroundNeonatal hypoglycemia (NH) is a common metabolic disorder that has been closely linked to abnormal neurodevelopment and brain injury. However, microstructural alterations in white matter among infants with transient NH remain poorly characterized. This study employed diffusion tensor imaging (DTI) to investigate whether transient NH induces microstructural white matter injury and to examine its correlation with blood glucose fluctuations.MethodsIn this retrospective cohort study, we enrolled 20 infants with transient NH and 22 sex- and gestational age (GA)-matched normoglycemic controls. All participants underwent 3-T DTI and had more than 13 blood glucose measurements within the first 48 hours of life between February 16, 2020, and October 17, 2023. To compare fractional anisotropy (FA) values between the two groups of regions of interest (ROIs), statistical significance was assessed using the Wilcoxon rank-sum test. Perinatal history and relevant clinical data were analyzed, and their association with FA values was assessed using partial correlation analysis, controlling for potential confounders.ResultsFA values in the splenium of the corpus callosum (sCC)—a marker of white matter integrity—were significantly lower in infants with transient NH compared to the control group (P=0.03). After adjustment for confounders, a significant positive correlation was observed between the lowest blood glucose (LBG) levels and sCC FA values across the cohort (P=0.013, r=0.408).ConclusionsOur findings indicate that FA values are sensitive to microstructural white matter alterations in infants with NH, potentially serving as an early indicator of subtle brain changes that warrant further investigation as a biomarker. The sCC appears to be particularly vulnerable to hypoglycemic injury, suggesting a potential pattern of early neurologic impairment. Furthermore, our findings indicate that the degree of white matter alteration is associated with the severity of hypoglycemia, as indicated by the lowest recorded blood glucose level.

ABSTRACT Conventional chemical dyeing of decorative wood products often relies on synthetic colorants and energy-intensive processes. Further, producing precise target patterns sustainably remains challenging. This study developed a targeted bio-dyeing strategy for poplar veneers by co-infecting Fusarium decemcellulare and Lasiodiplodia theobromae along predefined inoculation paths. Three pattern types (linear, slash, and curve) were designed, followed by incubation under controlled temperature and humidity conditions. Targeted infection was quantified using image-based similarity analysis, and chromaticity was evaluated using CIE Lab parameters, color difference (ΔE*), K/S values, and reflectance. Surface roughness, dynamic contact angle, gloss and scanning electron microscopy were used to characterize changes in surface properties and microstructure. The co-infection system produced colonization along the designed routes and achieved high similarity (84.97%–87.56%) between the target patterns and the dyed veneers, with significant color contrasts between the two fungal infection regions. Surface roughness exhibited minimal change, whereas wettability increased substantially and gloss decreased moderately, indicating that the process primarily affected surface chemistry and microporosity without causing notable damage. These findings show that multi-fungal targeted infection is a feasible, environmentally friendly method for generating desired patterns on poplar veneers and provide a scientific basis for advancing bio-dyeing for high-value decorative wood products.

Abstract Shape memory alloys (SMAs), particularly nickel–titanium (NiTi)-based systems, are widely recognized for their shape memory effect and superelastic behavior, governed by reversible martensitic phase transformations. In this study, a nonstoichiometric quaternary Ni39Ti49Cu8Ag4 (at.%) shape memory alloy was synthesized and characterized to elucidate the effect of uniaxial pressure cycling on phase stability, microstructure, and transformation thermodynamics. The selected Cu–Ag co-alloying strategy was adopted to enable functional tailoring of NiTi-based transformation behavior: Cu is used to tune transformation characteristics (including hysteresis-related behavior), while Ag is introduced to enhance corrosion resistance and impart antibacterial functionality relevant to biomedical and high-reliability components. The alloy was fabricated via arc melting under argon and subsequently subjected to uniaxial compressive pressures of 0, 100, 200, 300, and 400 MPa. Structural, microstructural, and thermal responses were evaluated using X-ray diffraction (XRD), scanning electron microscopy coupled with energy-dispersive X-ray spectroscopy (SEM–EDX), and differential scanning calorimetry (DSC). The findings clarify how pressure cycling and targeted minor alloying jointly influence phase transformation behavior and microstructural integrity, supporting the design of pressure-tunable NiTi-based SMAs for actuator-, sensor-, and biomedical-relevant applications.

ABSTRACTBackgroundPost‐traumatic stress disorder (PTSD) is the most common mental disorder following traumatic experiences. Environmental disasters such as super typhoons can severely disrupt daily life and may trigger PTSD in exposed individuals. White matter alterations have been observed in patients with PTSD. Fixel‐based analysis (FBA), a recently developed diffusion MRI technique, allows detailed assessment of white matter microstructure. This study aimed to evaluate the potential of FBA as an imaging biomarker in typhoon survivors, reducing the subjective bias associated with clinical symptom scales.MethodsWhole‐brain diffusion MRI data from the PTSD group (n = 27), trauma‐exposed controls (TEC, n = 33), and healthy controls (HC, n = 30) were analyzed to identify white matter fiber tracts showing abnormalities in FBA metrics, including fiber density (FD), fiber cross‐section (FC), and fiber density–cross section (FDC). The study then examined whether these FBA‐derived features, when combined with machine learning, could improve the identification of potential PTSD biomarkers.ResultsCompared with the HC group, patients with PTSD showed increased fiber density (FD) in the right frontopontine tract and right middle longitudinal fascicle, as well as higher fiber density–cross section (FDC) values in the bilateral frontopontine tract and left thalamo‐premotor tract (Bonferroni correction, p < 0.05/18 = 0.003). To differentiate PTSD from TEC, binary and multiclass machine learning models with five‐fold cross‐validation were developed. The binary model (PTSD vs. TEC) achieved high performance (accuracy = 0.89, sensitivity = 0.97, specificity = 0.71, precision = 0.87, AUC = 0.95), whereas the multiclass model (PTSD vs. TEC vs. HC) demonstrated excellent results (macro‐averaged precision = 0.99, recall = 0.99, F1‐score = 0.99). The top 20 contributing features of the optimal model were analyzed using Shapley additive explanation (SHAP) values to illustrate model interpretability.ConclusionMost typhoon‐exposed individuals with PTSD may exhibit structural alterations in brain white matter. By combining fixel‐based analysis (FBA) with machine learning, this study identified diffusion markers within specific white matter tracts and demonstrated their potential diagnostic value for distinguishing PTSD from trauma‐exposed controls. These findings enhance our understanding of microstructural white matter changes and their spatial distribution in PTSD and also suggest potential imaging biomarkers for its diagnosis.

Developing flexible conductors that combine high conductivity, stable MHz-range electrical behavior, and mechanical durability remains a challenge. This is primarily because conventional bulk-type metals suffer from frequency-dependent AC-resistance increases, while standard composites often exhibit poor interfacial integrity. Here, we address these limitations through the synergistic integration of a biscrolling architecture with a rapid and efficient self-incandescent heating (SIH) post-treatment. The biscrolled structure promotes a uniform 3D distribution of copper, while SIH is associated with local Cu reorganization/reflow-like restructuring, grain growth, and interfacial consolidation within the carbon nanotube (CNT) framework. These microstructural changes are consistent with the formation of a more densified conductive network, leading to a 68.8% enhancement in electrical conductivity (up to 3.63 × 104 S/cm) and a metallic temperature coefficient of resistance (TCR = 3.32 × 10- 3 °C- 1) approaching that of bulk copper. Notably, the yarns exhibit weak frequency dependence of resistance within the measured range (up to 10MHz), indicating a reduced frequency-dependent increase in resistance compared with solid copper wire. By combining exceptional mechanical resilience under extreme deformation with stable high-frequency performance, SIH-treated biscrolled Cu/CNT yarns emerge as a robust material platform for next-generation flexible conductors andinterconnects.

Microstructural and diffusion tensor imaging of clozapine for treatment-resistant schizophrenia.

We report temperature-induced morphological transitions of smectic liquid crystal (LC) microstructures from fibers to disc- and umbrella-like structures. We used two systems based on 4-cyano-4'-n-octyloxybiphenyl (8OCB): an 8OCB/decanol system and an 8OCB/cetyltrimethylammonium bromide (CTAB) system. In both systems, LC fiber structures grew from the droplets upon cooling. The LC fiber structures in both systems underwent similar morphological transitions into umbrella-like structures via an intermediate disc-like structure. Furthermore, we observed that repeated temperature cycling induced reversible morphological transitions between umbrella- and disc-like structures. We developed a simple free-energy model, based on elastic and topological defect energies, that explains these morphological changes. These findings suggest design principles for stimuli-responsive smectic LC microstructures and may provide physical insight into the deformation of phase-separated, membraneless organelles.

This study employed diffusion kurtosis imaging (DKI) and proton magnetic resonance spectroscopy (1H-MRS) on an MPTP-induced mouse model of Parkinson's disease (PD) to examine microstructural changes linked to neuroinflammation and neurodegeneration. MPTP (20 mg/kg, i.p.) was given for 4 days, and behavioral assessment, MRI imaging, and immunohistochemistry were performed at 24 h and 72 h after last MPTP treatment. At 24 h, DKI showed higher diffusivity metrics in the hippocampus and thalamus, while 1H-MRS identified reduced Glu/tCr and Glx/tCr ratios in the striatum of MPTP-treated mice compared to saline-treated mice. Behavioral tests at 72 h revealed motor impairment and DKI showed increased diffusivity in the somatosensory cortex, thalamus, and striatum in MPTP-treated mice. Notably, at 72 h, the hippocampus showed partial recovery in diffusivity, suggesting adaptive changes or partial restoration. Higher diffusivity was observed in the cortex, striatum, and thalamus in MPTP-treated mice. Furthermore, 1H-MRS detected a higher Tau/tCr in the striatum, while in the hippocampus, lower Gln/tCr and NAA/tCr and higher Cho/NAA were observed at 72 h in MPTP-treated mice, indicating persistent neuronal death and membrane deterioration. Immunofluorescence staining at 72 h confirmed these findings, showing a decrease in NeuN+ neurons and an increase in GFAP+ glial cells in the striatum and hippocampus, indicating neurodegeneration and gliosis. Additionally, MPTP caused a loss of dopaminergic neurons in the substantia nigra and striatum, which likely explains the higher diffusivity shown by DKI. These findings demonstrate DKI and 1H-MRS are sensitive, non-invasive modalities for detecting and monitoring neurodegenerative microstructural and neurochemical changes, enhancing the understanding of PD-related pathology and progression.