搜索结果：Journal of biomedical physics & engineering

Gelatin is a valuable hydrocolloid produced by partial hydrolysis of collagen from mainly mammalian and fish sources. The rheological properties of fish gelatin differ from those of mammalian species in terms of gel strength, viscosity, and other rheological characteristics, even from different fish species and parts of the fish with different properties. Fish gelatin is sustainable for the environment and easy for people to accept for cultural reasons. Owing to these properties, gelatin is used across food, biomedical, pharmaceutical, and health sectors, where 3D printing enables customization and functional performance. Key determinants of print fidelity include gelatin concentration, rheological properties, temperature, gelling behavior, water content, and printing parameters. Suitability for 3D printing is typically assessed via physicochemical characterization, particularly rheology and gelling mechanisms/kinetics. Gelatin-based 3D printing systems offer various advantages due to their biocompatibility, low cost, and controllable rheological properties, and they have potential applications in the food, healthcare, biomedical, tissue engineering, and drug delivery system areas. Using gelatin in combination with other additives can improve printing accuracy and mechanical strength parameters, overcome the limitations of gelatin's inherent mechanical strength, and develop higher printing accuracy and performance systems. This allows for the development of functional, innovative, and high-value-added products while ensuring safe use.

Background: Modified Vaccinia Ankara (MVA) vectors are highly immunogenic vaccine platforms for the delivery of recombinant antigens. Efficient downstream processing is still challenging, particularly because substantial fractions of the virus remain intracellular. While chemical cell lysis that releases MVA particles into the supernatant before clarification can greatly enhance process efficiency and scalability, this step remains insufficiently characterized. Methods: This study assessed the compatibility of ionic, non-ionic, and zwitterionic detergents with the virus as purification target. Polysorbate 20 (Tween 20) was selected as a candidate detergent and evaluated across harvest times of 48-72 h post-infection (hpi) at concentrations of 0.01-0.5% (v/v). Results: The addition of 0.01% to 0.05% Tween 20 at 48 hpi resulted in a twofold increase in supernatant virus within one hour of application. Extended exposure to Tween 20, combined with a 650 mM mixture of NaCl, NaBr, and KCl, promoted virus particle release. However, Tween 20 concentrations above 0.1% reduced MVA infectivity. A filtration cascade using pore sizes of 5 µm and 1.2 µm achieved product yields of 77-83% at 48 hpi and 41-69% at 72 hpi, respectively. Host-cell DNA is an important contaminant during viral vector processing. However, the application of 0.05% (v/v) Tween 20 resulted in a 35% reduction of dsDNA released into the culture supernatant; the nuclei could not be preserved intact under high-salt conditions to avoid the release of cellular DNA. Conclusions: In summary, this comprehensive data demonstrated that non-ionic detergents can be used to induce cell lysis while maintaining infectious activity of enveloped MVA.

Extracellular vesicles (EVs), naturally secreted by cells as nanoscale lipid bilayer structures, have become a research hotspot in biomedicine owing to their excellent biocompatibility, low immunogenicity, and inherent ability to cross biological barriers. This review systematically summarizes recent advances in EVs as natural nanomaterials. The biogenesis mechanisms of EVs are outlined, followed by a comparative analysis of the advantages and limitations of mainstream isolation and purification methods, including ultracentrifugation, size-exclusion chromatography, and microfluidic technologies. The core guiding role of the MISEV 2023 guidelines in standardizing EV characterization is highlighted. Engineering strategies to enhance EV therapeutic efficacy-including parental cell modification, post-isolation physicochemical tailoring, and hybrid vesicle construction-are then reviewed, followed by a comparative analysis of mainstream isolation technologies, emphasizing the trade-offs between purity and yield. Distinct from conventional descriptive reviews, this article establishes a strong biomimetic framework to scrutinize engineering strategies, including parental cell genetic modification, post-isolation physicochemical tailoring, and the fabrication of hybrid bio-synthetic vesicles. The design principles governing targeted delivery, drug-loading physics, and in vivo pharmacokinetic stability are critically evaluated through the lens of biomimetic nanotechnology. Furthermore, we identify critical research gaps and technical bottlenecks impeding clinical translation, offering a forward-looking perspective on the evolution of EVs from natural messengers into standardized precision medicine platforms.

Superelastic Nickel Titanium (NiTi) exhibits nonlinear and path-dependent behavior that complicates accurate simulation of orthodontic appliances. Standard iterative finite element (FE) formulations often fail to maintain realistic stress evolution during simulations, leading to non-physiologic force predictions. This study introduced an Element-Iteration-Specific (EIS) material model implemented within the FE framework to incorporate the behavior of superelastic NiTi alloy into an iterative simulation, aiming to investigate the biomechanics of a molar uprighting spring and estimate the clinical treatment duration. A two-dimensional (2D) model was constructed representing a 30° mesially tilted mandibular second molar uprighted using a prefabricated superelastic NiTi spring. At each iteration, the EIS algorithm redefines the element specific material parameters of the spring according to the stress-strain state inherited from the preceding iteration, thereby preserving the continuity of its behavior and enabling realistic stress evolution and load transfer between the wire, brackets, and teeth. The simulation achieved 23.3° of molar uprighting with 3.0 mm of tangential distal and 2.4 mm of normal extrusive displacements, over an equivalent of 14-week clinical duration. The NiTi spring generated an initial 12.4 N·mm (~ 1265 g·mm) counter-clockwise moment and 0.9 N normal extrusive force. The mean PDL stress remained physiologic, decreasing from 20.3 KPa at wire activation to 13.3 KPa at the end of the simulation. The model successfully tracked the spatial and temporal evolution of the superelastic NiTi's stress-induced martensitic transformation during activation and uprighting. The EIS framework effectively reproduced the nonlinear and history-dependent response of superelastic NiTi, offering clinically representative predictions and establishing a validated computational foundation for optimizing NiTi-based orthodontic appliances and improving treatment outcomes.

Time-of-flight (TOF) resolution improves positron emission tomography (PET) by localizing annihilation events along the line of response, which reduces statistical noise and improves image quality. In open-geometry PET systems, improved TOF can compensate for limited angular sampling by reducing geometric distortions and reconstruction artifacts. This work quantitatively studies how TOF resolution and angular coverage together determine image quality in open-geometry PET. 
Approach: Using Monte Carlo simulations, we estimate the minimum angular coverage required to obtain reconstructions with minimal distortion for different TOF performance levels. An idealized PET scanner model is first used to isolate the effects of angular sampling and TOF, without detector-related blurring. Five angular coverages (60°, 90°, 120°, 150°, and 180°) and six coincidence timing resolutions (400, 200, 100, 75, 50, and 25 ps FWHM) are evaluated. Image quality is assessed using point sources, the Derenzo phantom, and the NEMA image quality phantom, reporting spatial resolution, contrast recovery, background variability, and geometric distortion quantified by ellipse fitting. 
Main results: The results show that TOF resolutions below approximately 100 ps are a key enabling factor for highly open PET geometries, substantially reducing limited-angle artifacts and allowing image quality to approach that of full-ring systems. The main trends are further validated using a realistic Monte Carlo model of the Siemens Biograph Vision PET/CT scanner. 
Significance: These results provide practical design guidance for next-generation open-geometry PET systems, showing that fast TOF performance can reduce required detector coverage while preserving image quality.

Thromboembolic diseases, which account for approximately one-third of global deaths, are characterized by thrombus embolization-the process whereby blood clots undergo cohesive/adhesive fracture under fluid-induced forces. Comprehensive numerical modeling of this multiphysics phenomenon has remained challenging, and robust computational frameworks are scarce. This work substantially advances the state-of-the-art of numerical models of thrombus embolization by presenting a framework that couples Lagrangian non-ordinary state-based peridynamics with Eulerian computational fluid dynamics. The formulation can (i) incorporate complex macroscale constitutive laws for a thrombus, (ii) capture delamination physics between a thrombus and a contacting surface, and (iii) couple thrombus structural dynamics with fluid flow discretized on arbitrary unstructured meshes. The latter capability is achieved through the development of a robust interpolation scheme for fast bi-directional data transfer between polyhedral meshes and peridynamic particle clouds. This also advances the literature of peridynamic coupled fluid numerical models, which are mostly limited to bond-based peridynamics and Cartesian meshes. The framework undergoes rigorous validation through five computationally unique benchmarks. The validated framework is then applied to reproduce reported experimental results of embolization of preformed thrombus within a polycarbonate cylindrical tube under varying flow rates. To demonstrate that the numerical framework can support spatially heterogeneous material properties (a capability absent in other approaches), a synthetic test case is reported. Unlike homogeneous assumptions that always predict leading-edge detachment, heterogeneous material properties enable trailing-edge detachment, thus elucidating this previously unexplained experimental observation.

To overcome low bioavailability and high trauma in inner ear therapies, targeted delivery across the round window membrane (RWM) via hollow microneedles (HMNs) offers a promising solution. However, the fabrication of high-aspect-ratio, small-size HMNs remains challenging. This study demonstrates the successful fabrication of small-outer-diameter HMNs using a 10 μm resolution digital light processing (DLP) system. Finite element analysis (FEA) identified a double tangent-arc transition as the optimal structural design for minimizing stress concentration. To manage the heightened parameter sensitivity at sub-feature-scale fabrication, a corrected curing index (CCI) model was established via a physics-informed regression approach incorporating polymerization kinetics and nonlinear spatial intensity distribution, achieving high fitting accuracy (R2 > 0.96). Under optimized parameters, the fabricated HMNs possessed mean dimensions of 805.13 μm in height, 37.54 μm in inner diameter, and 79.36 μm in outer diameter. Compressive tests exhibited a robust structural strength of up to 141 mN per needle following post-curing. Combined in silico and in vitro experiments demonstrated excellent penetration performance. Furthermore, the HMNs achieved stable, pressure-dependent delivery with volumetric flow rates rising from 0.14 mL∙min-1 to 0.39 mL∙min-1 as driving pressure escalated from 50 kPa to 300 kPa, validating their functional capacity for controlled drug administration.

High-frequency oscillations (HFOs) are a promising biomarker for localizing epileptogenic tissue, yet the extent to which recording duration and vigilance state influence their spatial distributions remains unclear. This study quantified the recording duration and vigilance state required to reliably capture HFO spatial distributions to guide surgical planning in epilepsy. We retrospectively analyzed long-term, continuous iEEG recordings from patients with drug-resistant epilepsy undergoing presurgical evaluation at the University of Michigan. Sleep stages were manually annotated, HFOs (80-500 Hz) were detected using a validated algorithm, and the correlations between HFOs and the seizure-onset zone (SOZ) were assessed across vigilance states. A novel similarity-based temporal padding approach was developed to measure the similarity of HFO distributions derived from data available up to a given time point with those derived from the full recording. Postsurgical outcome prediction was evaluated using a decision tree classifier based on the proportion of resected, top-ranked HFO-rate channels (critical resection percentage, CReP). Fifty-four patients were analyzed (30 female patients, mean age 32.8 [range, 6-66] years, mean recording duration 8.40 days [range, 3-22]). HFO-SOZ associations were present across all states but fluctuated over time; non-rapid eye movement (NREM) sleep showed the least temporal variability. HFO-SOZ associations were stronger in temporal lobe epilepsy and more stable in patients with frequent seizures. When analyzing only the HFOs during NREM, 21% of patients required more than 2 days of recording to capture its full distribution; however, all NREM data were insufficient to describe the full HFO distribution in 30% of patients. Across all vigilance states, 7 days of recording fully characterized HFO distributions in 98% of patients. Postsurgical outcome prediction using multiday aggregate CReP achieved more robust and accurate performance (AUC 0.86, 95% CI [0.70-1.00]) than analyses based on a random selection of single 5-minute NREM epoch (median AUC 0.42, IQR 0.23) or a single day (AUCs ranged 0.63-0.71 for different analyzed days). Short sampling period risks incomplete representation of the full HFO spatial profile. Future studies should consider multiday recordings to enable more reliable HFO characterization and improve HFO-based surgical outcome prediction.

Electrospinning (ES) can produce nonwoven fibrous mats with high surface area and interconnected porosity, making them attractive for biomedical and functional material applications. However, conventional ES often relies on volatile organic solvents, raising safety, environmental, and translational concerns. Fully aqueous ("green") ES offers an appealing alternative, although many water-soluble polymers remain difficult to spin and may show limited stability under hydrated conditions. In this study, two fully aqueous binary systems, poly(vinylpyrrolidone)-sodium alginate (PVP-SA) and poly(vinylpyrrolidone)-riboflavin (PVP-RF), were investigated to decouple the roles of sodium alginate (SA) and riboflavin (RF) on solution behaviour, fibre formation, morphology, dry-state mechanical properties, and surface chemistry. Aqueous PVP solutions (20% w/v; molecular weight 1.3 MDa) were blended with SA (1-5 wt% relative to PVP) or RF (1-10 wt% relative to PVP). Electrical conductivity and rheological properties were evaluated prior to ES under controlled conditions, with simultaneous ultraviolet (UV) exposure at 344 nm during fibre collection. RF did not significantly alter conductivity (~0.74-0.75 µS·cm-1), whereas SA increased conductivity up to 2.75 ± 0.03 µS·cm-1 at 5 wt%. All formulations exhibited shear-thinning behaviour, while 10 wt% RF increased the zero-shear viscosity relative to neat PVP. Morphological analysis showed that low SA contents produced uniform fibres, whereas higher SA levels (4-5 wt%) led to bead defects and reduced fibre diameter (down to 85 ± 25 nm). Dry-state mechanical performance decreased with increasing SA content, while 10 wt% RF improved tensile strength and toughness, reaching an ultimate tensile strength of 5.21 ± 0.15 MPa and toughness of 40.51 ± 1.53 MJ·m-3. Fourier transform infrared spectroscopy (FTIR) and X-ray photoelectron spectroscopy (XPS) indicated subtle UV-driven redistribution of surface chemical states, consistent with mild photo-oxidative microstructural modification rather than extensive covalent network formation. Because the UV irradiance was not directly measured and wet-state stability was not assessed, the UV-related findings are interpreted as preliminary chemical evidence rather than confirmation of stabilized fibre mats. Overall, this work establishes a solvent-free aqueous ES platform in which ionic and photoactive additives can be used to tailor fibre morphology, dry-state mechanical behaviour, and surface characteristics without toxic reagents.

Dual-energy X-ray absorptiometry (DXA) remains the clinical gold standard for assessing bone mineral density (BMD), guiding diagnosis and therapeutic decisions. However, conventional DXA analysis suffers from several limitations, including insensitivity to early microarchitectural changes, operator dependence, limited availability in primary care settings, and an insufficient ability to predict fracture risk when used alone. Artificial intelligence (AI), incorporating machine learning (ML) and deep learning (DL), offers transformative potential in enhancing DXA-based bone health assessment. The purpose of this review is to describe the integration of AI algorithms into DXA image interpretation, highlighting improvements in diagnostic accuracy, and fracture risk stratification beyond traditional methods. Using AI-driven models, complex features of DXA images can be extracted, increasing sensitivity to microstructural deterioration that is typically not detected by standard BMD measurements. A combination of quantitative image features and comprehensive demographic and clinical data enhance the early detection of osteoporosis and fracture susceptibility, enabling personalised treatment strategies. In comparison to classical DXA or fracture risk assessment tool (FRAX) algorithms, convolutional neural networks (CNNs) and ensemble methods demonstrate superior predictive performance, with average area under the curve (AUC) values often about 0.90. In addition to minimising inter-operator variability and improving reproducibility, AI improves DXA technical challenges such as region-of-interest selection and image segmentation. In addition to providing indirect measurements of bone microarchitecture, AI-enabled indices, such as the trabecular bone score (TBS), contribute to the improvement of fracture risk prediction. It has been demonstrated in large-scale clinical validations that AI-assisted DXA can enhance bone health diagnostic capability.

Second harmonic generation and third harmonic generation (SHG and THG) microscopy are nonlinear optical imaging techniques which have found a diverse range of applications in the investigation of both biological and synthetic nanostructures. Like all optical imaging techniques, the spatial resolution achievable using SHG and THG is limited by diffraction to around half of the excitation wavelength, a major impediment towards applications in nano imaging. Because of this, several groups have developed methods for super-resolution SHG and THG imaging, however these approaches have all involved the use of nonstandard microscope components which presents a technical and financial barrier to entry for those interested in applying these techniques. Here we investigate the application of several computational super-resolution techniques for SHG and THG imaging, with a focus on enabling super-resolution polarization-resolved SHG microscopy. We find that even though computational super-resolution was originally developed for incoherent imaging modalities such as fluorescence, it is able to provide a lateral resolution enhancement of up to 3.4× when imaging isolated nanostructures compared to a standard laser scanning harmonic generation microscope. While currently available CSR techniques are not able, in general, to correct for the inherent ambiguity between density of emitters and signal intensity within coherent imaging processes, we show that CSR can still provide improved localization in harmonic generation microscopy. We additionally show that two computational super-resolution techniques, super-resolution radial fluctuations and deblurring by pixel reassignment, preserve the polarization dependence of SHG signal, thereby allowing super-resolution polarization-resolved SHG measurements. These results are obtained with no modification to our microscope system and little change to the experimental workflow, and therefore present exciting opportunities for future applications of super-resolution SHG and THG microscopy.

Implantable sacral anterior root stimulators enable bladder emptying after spinal cord injury but do not prevent reflex incontinence. A closed-loop neuroprosthesis that detects and inhibits reflex bladder contractions could address this, but first, reliable detection of bladder fullness from the sacral roots. Further, the distribution of afferent bladder activity between sacral roots, and the relationship between efferent and afferent activity within each root, remains unclear and must be clarified to guide implant design. Electrode books were implanted on the S1-S3 extra-dural sacral roots bilaterally in six terminally anesthetized sheep. Afferent electroneurogram (ENG) was recorded concurrently from all implanted roots during filling cystometries and correlated with bladder pressure. Each root was individually electrically stimulated and the bladder pressure response recorded. Post-mortem morphometric analysis determined fiber size distribution in each root. Overall, S2 ENG activity showed the highest correlation with bladder pressure, and electrical stimulation of S2 and S3 produced the greatest increases in bladder pressure. Fiber size distribution did not correlate with either ENG activity or bladder pressure response. Significant variation was identified between individual sheep, but notably, in four of six sheep, a single sacral root had both the highest ENG correlation to bladder pressure and the greatest bladder response to stimulation. This study demonstrates reliable recording of bladder afferents from sacral roots using clinically applicable electrodes. It provides the first systematic recording of bladder ENG concurrently across three pairs of sacral roots in multiple animals, and the first characterization of signal distribution between roots. Significant individual variation is identified, impacting the design of future implantable sacral neuroprostheses for bladder control.

Physics-Informed Neural Networks (PINNs) have emerged as a key tool in Scientific Machine Learning since their introduction in 2017, enabling the efficient solution of ordinary and partial differential equations using sparse measurements. Over the past few years, significant advancements have been made in the training and optimization of PINNs, covering aspects such as network architectures, adaptive refinement, domain decomposition, and the use of adaptive weights and activation functions. A notable recent development is the Physics-Informed Kolmogorov-Arnold Networks (PIKANS), which leverage a representation model originally proposed by Kolmogorov in 1957, offeringa promising alternative to traditional PINNs. In this review, we provide a comprehensive overview of the latest advancements in PINNs, focusing on improvements in network design, feature expansion, optimization techniques, uncertainty quantification, and theoretical insights. We also survey key applications across a range of fields, including biomedicine, fluid and solid mechanics, geophysics, dynamical systems, heat transfer, chemical engineering, and beyond. Finally, we review computational frameworks and software tools developed by both academia and industry to support PINN research and applications.

For some patients, knee osteoarthritis is associated with excessive tibiofemoral joint loading, which contributes to cartilage degeneration. Modifying muscle coordination during walking, particularly between the soleus and medial gastrocnemius, may help reduce joint loading. Strength training of the soleus could further support this process by increasing muscle force generation capacity, potentially making new activation patterns more efficient and easier to learn. This study examined the effects of an 8-week neuromuscular coordination gait retraining program using real-time electromyography (EMG) biofeedback targeting the calf muscles in 30 healthy older adults, with gait retraining as the primary intervention. Half of the participants were randomly assigned to receive additional soleus strength training to assess its added value. During treadmill walking, participants received visual and auditory feedback designed to promote a more soleus-dominant coordination strategy. EMG and 3D motion capture data were collected before and after the intervention during baseline and feedback trials, and post-intervention during a retention trial without feedback. Participants showed a significant shift toward a soleus-dominant coordination pattern during feedback trials both before (0.460&#xa0;&#xb1;&#xa0;0.098 vs. 0.440&#xa0;&#xb1;&#xa0;0.098, p&#xa0;=&#xa0;0.002, Cohen's dz&#xa0;=&#xa0;0.64) and after (0.492&#xa0;&#xb1;&#xa0;0.086 vs. 0.464&#xa0;&#xb1;&#xa0;0.091, p&#xa0;<&#xa0;0.001, dz&#xa0;=&#xa0;1.05) the intervention. This pattern was partially retained without feedback, though to a lesser extent. Medial gastrocnemius activation generally remained elevated, indicating that many participants increased activation in both muscles. No substantial compensatory activity was observed in non-target muscles, and joint kinematics were largely unchanged. Strength training did not significantly influence any outcomes. These findings suggest that EMG biofeedback can facilitate learning of novel muscle coordination patterns in older adults, supporting the development of non-invasive gait-based strategies to modify joint loading.

Fingerprints are still one of the most effective means of forensic detection but degradation during the recovery process leads to a loss of contrast between ridge and background, making them difficult to visualize. In this study spinel copper aluminate (CuAl2O4) nanoparticles were synthesized by a facile and cost effective sol-gel method and evaluated for latent fingerprints (LFPs) development on both porous (paper, ceramic, wood) and non-porous (plastic, steel, glass) substrates. Structural characterizations revealed an average crystallite size of 24.5&#xa0;nm that was found to be smaller than the average particle size of 36.9&#xa0;nm confirming that the particles consists of nanoscale crystalline domains with some agglomeration. The developed fingerprint exhibited substrate-dependent contrast with normalized contrast ratios increasing from &#x223c;0.30 (paper) to &#x223c;0.60 (glass) under white light and further enhanced to &#x223c;0.74 under UV excitation. UV-assisted visualization enabled improved ridge clarity and facilitated the observation of Level 1 and Level 2 details, with partial enhancement towards finer features. Aging studies demonstrated that identifiable ridge patterns were retained up to 30 days, with improved visibility under UV illumination compared to white light conditions. These findings demonstrate that CuAl2O4 nanoparticles provide simple, cost-effective, and reliable approach for fingerprint development, combining surface adhesion and luminescent enhancement for improved forensic applicability.

Information encryption and security are the cornerstones of the digital era. However, traditional optical and electronic encryption techniques remain vulnerable to decryption due to deterministic material responses and predictable algorithms. In this study, we present a programmable multi&#x2011;modal information encryption system based on the dynamic wetting behavior of liquid metal. The system integrates an inclinometer sensor that utilizes the dynamic wetting characteristics of liquid metal, a probe&#x2011;driven transmission mechanism, and a three&#x2011;dimensional motion platform. Through the coupling of mechanical regulation and fluid dynamics, the system achieves secure physical information encoding with multidimensional and reconfigurable encryption capability. Proof&#x2011;of&#x2011;concept experiments demonstrate that the system exhibits high precision and stability in the encryption and decryption of image and textual information. The proposed framework employs four independent encryption parameters, and successful decoding requires deviations smaller than 0.02%. Overall, this research establishes a controllable and highly secure materials&#x2011;driven encryption framework, providing a promising route for advanced information protection and encryption technologies.

Tight junctions within simple epithelia are composed of networks of anastomosing strands at the apical end of the intercellular space. Members of the claudin family of proteins reside within TJ strands and either seal the paracellular space or assemble into charge and size-selective pathways. Functional studies suggest that claudin-mediated conductance pathways resemble traditional ion channels. However, postulated pores have not been directly visualized. Using claudin-deficient epithelia where exogenously introduced EGFP-CLDN15 is the principal claudin family member expressed, our investigation sheds light on the arrangement and structure of the putative claudin pores. Following correlative light and electron microscopical identification of TJs and cryo-electron tomography, we identified series of linearly distributed electron-lucent features that locate between two closely apposed plasma membranes of adjacent cells. In contrast, such features were not observed in claudin deficient epithelia with exogenous mCherry-ZO-1 expression. Morphometric analyses showed the median diameter of these features is 1.5 nm, with a median distance between adjacent features of 2.3 nm. These findings agree with the postulated and extensively modeled claudin pores formed within simple epithelia. This provides the first direct evidence of paracellular claudin pore organization and paves the way for future biophysical investigations.

Sol-gel process proved to be an effective approach to synthesize borosilicate-based bioactive glasses with significant crystallization induced during devitrification verified by Na2CaSiO4 phase. A progressive growth of hydroxyapatite (HA) phase in the size range of 17-26&#x2009;nm was observed. Fourier transform infra-red (FTIR) spectroscopy suggested the presence non-bridging oxygen (NBO) and BO3 groups that facilitated rapid ion exchange. While bands at 550-650&#x2009;cm-1 (PO43-) and 1524&#x2009;cm-1 (CO32-) confirmed the formation of carbonated HA. The porous architecture of bioactive glass facilitated rapid in-vitro mineralization while crystalline bioactive glass improved dimensional stability and controlled degradation which renders it ideal for hard tissue engineering scaffolds where structural integrity is important besides biological functions.

To assess the feasibility and diagnostic performance of radiation-free 0.55-T lung MRI for pulmonary sarcoidosis, combining morphological imaging with functional proton MRI ventilation/perfusion metrics, and to explore correlations with pulmonary function testing (PFT). In this prospective study, 15 patients with pulmonary sarcoidosis and 30 healthy volunteers underwent 0.55-T lung MRI (bSTAR morphology; matrix-pencil based functional proton MRI). CT served as the reference standard for morphological findings (majority vote of experienced readers). Functional maps yielded ventilation defect percentage (VDP), perfusion defect percentage (QDP), and ventilation-perfusion overlap (VQO); thresholds were derived from the healthy cohort. Group comparisons and correlations with PFT were performed. MRI achieved the highest sensitivity for consolidations (86%) and moderate performance for nodules (67%) as well as ground-glass opacities (70%), but lower sensitivity for reticulations (29%) and traction bronchiectases (27%) compared with CT. Inter-reader and inter-modality agreement were moderate. Functional MP-MRI revealed significantly higher VDP, QDP, and VQO in patients compared with volunteers (all p&#x2009;<&#x2009;0.01). Strong correlations were found between MRI-derived VDP and RV/TLC ratio (r&#x2009;=&#x2009;0.90, p&#x2009;<&#x2009;0.001) and between QDP and FEV1 (r&#x2009;=&#x2009;0.63, p&#x2009;=&#x2009;0.01). Low-field lung MRI provides complementary information in pulmonary sarcoidosis, enabling structural assessment free of ionizing radiation, with overall moderate agreement compared to CT, and adds valuable regional lung function analysis correlated with PFT. Question Can 0.55-T lung MRI supplement CT in pulmonary sarcoidosis by providing structural assessment plus regional ventilation and perfusion metrics linked to pulmonary function? Findings 0.55-T MRI showed high sensitivity for consolidations (86%) and revealed increased ventilation and perfusion defects that correlated strongly with the residual volume-to-total lung capacity ratio. Clinical relevance Low-field lung MRI enables radiation-free assessment of structural and functional lung involvement, offering additional regional information that may support longitudinal monitoring in selected patients with pulmonary sarcoidosis.