Search Results (2,030)

Extracellular vesicles (EVs) have emerged as promising acellular tools for modulating immune responses for tissue engineering applications. This study explores the potential of human fibroblast-derived EVs delivered within a three-dimensional (3D) injectable scaffold composed of polycaprolactone (PCL) nanofibers and collagen (PNCOL) to reprogram macrophage behavior and support scaffold integrity under inflammatory conditions. EVs were successfully isolated from human fibroblasts using ultracentrifugation and characterized for purity, size distribution and surface markers (CD63 and CD9). Macrophage-laden PNCOL scaffolds were prepared under three conditions: macrophage-only (MP), fibroblast co-encapsulated (F-MP), and EV-encapsulated (EV-MP) groups. Structural integrity was assessed via scanning electron microscopy and Masson’s trichrome staining, while immunomodulatory effects were evaluated through metabolic assays, gene expression profiling, and immunohistochemistry for macrophage polarization markers (CD80, CD206). When co-encapsulated with pro-inflammatory (M1) macrophages in PNCOL scaffolds, fibroblast-derived EVs preserved scaffold structure and significantly enhanced macrophage metabolic activity compared to the control (MP) and other experimental group (F-MP). The gene expression and immunohistochemistry data demonstrated substantial upregulation of anti-inflammatory markers (TGF-β, CD163, and CCL18) and surface protein CD206, indicating a phenotypic shift toward M2-like macrophages for EV-encapsulated scaffolds relative to the other groups. The findings of this study demonstrate that fibroblast-derived EVs integrated into injectable PCL–collagen scaffolds offer a viable, cell-free approach to modulate inflammation, preserve scaffold structure, and support regenerative healing. This strategy holds significant promise for advancing immuno-instructive platforms in regenerative medicine, particularly in settings where conventional cell therapies face limitations in survival, cost, or safety. Full article

Titanium (Ti) alloys, renowned for their exceptional physicochemical properties and high biocompatibility, are widely utilized in orthopedic and dental implants; however, their lack of intrinsic antimicrobial activity significantly increases the risk of implant-associated infections, often leading to severe complications and implant failure. Developing antimicrobial coatings on Ti implants is therefore a promising strategy. In this study, tannic acid (TA) coatings were deposited by immersing Ti alloy surfaces—beforehand activated by low-temperature oxygen plasma—in TA solutions at 2, 5, and 8 wt%. Coatings were characterized by scanning electron microscopy (SEM), X-ray photoelectron spectroscopy (XPS), water contact angle (WCA) measurements, and Folin–Ciocalteu release assays, and their cytocompatibility and antimicrobial performance were assessed in vitro. Surface characterization confirmed the formation of uniform TA layers, and WCA measurements indicated enhanced hydrophilicity relative to unmodified Ti (82.0° ± 3.6°), with values decreasing as TA concentration increased (from 35.2° ± 3.2° for 2% TA to 26.6° ± 2.8° for 8% TA). TA release profiles exhibited an initial burst followed by sustained diffusion, with 5% and 8% coatings releasing significantly more TA than 2% coatings. Coatings containing ≥ 5% TA demonstrated bactericidal activity—achieving > 2-log₁₀ reductions—against Escherichia coli, Staphylococcus aureus, and Pseudomonas aeruginosa, and also showed inhibitory effects against Candida albicans. Importantly, all coatings remained cytocompatible with NIH/3T3 fibroblasts, and the released tannic acid hydrolysis products (particularly gallic acid) enhanced their proliferation. These findings indicate that plasma-activated titanium surfaces coated with ≥5 wt% tannic acid impart broad-spectrum antimicrobial efficacy and hold potential to reduce implant-associated infections and improve long-term outcomes in orthopedic and dental applications. Full article

The sparse iterative covariance-based estimation (SPICE) method has recently gained significant attraction in the field of scanning radar super-resolution imaging because of its angular resolution enhancement capability. However, it is unable to preserve the target profile, and the estimator is constrained by high computational complexity and memory consumption. In this paper, a grid-updating split SPICE-TV algorithm is presented. The method allows for the efficient updating of reconstruction results with both contour and resolution, and a recursive grid-updating implementation framework of the split SPICE-TV has the capability to reduce the computational complexity. First, the scanning radar angular super-resolution problem is transformed into a constrained optimization problem by simultaneously employing sparse covariance fitting criteria and TV regularization constraints. Then, the split Bregman method is employed to derive an efficient closed-form solution to the problem. Ultimately, the matrix inversion problem is transformed into an online iterative equation to reduce the computational complexity and memory consumption. The superiority of the proposed method is verified by simulation and experimental data. Full article

In this work, we report a green synthesis of zinc oxide (ZnO) nanoparticles using aqueous and ethanolic extracts of Tradescantia spathacea (purple maguey) as bioreducing and stabilizing agents, which are plant extracts not previously employed for metal oxide nanoparticle synthesis. This method provides an efficient, eco-friendly, and reproducible route to obtain ZnO nanoparticles, while minimizing environmental impact compared to conventional chemical approaches. The extracts were prepared following a standardized protocol, and their phytochemical profiles, including total phenolics, flavonoids, and antioxidant capacity, were quantified via UV-Vis spectroscopy to confirm their reducing potential. ZnO nanoparticles were synthesized using zinc acetate dihydrate as a precursor, with variations in pH and precursor concentration in both aqueous and ethanolic media. UV-Vis spectroscopy confirmed nanoparticle formation, while X-ray diffraction (XRD) revealed a hexagonal wurtzite structure with preferential (101) orientation and lattice parameters a = b = 3.244 Å, c = 5.197 Å. Scanning electron microscopy (SEM) showed agglomerated morphologies, and Fourier transform infrared spectroscopy (FTIR) confirmed the presence of phytochemicals such as quercetin, kaempferol, saponins, and terpenes, along with Zn–O bonding, indicating surface functionalization. Zeta potential measurements showed improved dispersion under alkaline conditions, particularly with ethanolic extracts. This study presents a sustainable synthesis strategy with tunable parameters, highlighting the critical influence of precursor concentration and solvent environment on ZnO nanoparticle formation. Notably, aqueous extracts promote ZnO synthesis at low precursor concentrations, while alkaline conditions are essential when using ethanolic extracts. Compared to other green synthesis methods, this strategy offers control and reproducibility and employs a non-toxic, underexplored plant source rich in phytochemicals, potentially enhancing the crystallinity, surface functionality, and application potential of the resulting ZnO nanoparticles. These materials show promise for applications in photocatalysis, in antimicrobial coatings, in UV-blocking formulations, and as functional additives in optoelectronic and environmental remediation technologies. Full article

Background/Objectives: Tegoprazan (TPZ) is a potassium-competitive acid blocker (P-CAB) used to treat conditions such as gastroesophageal reflux disease, peptic ulcer, and Helicobacter pylori infection. It exists in three solid forms: amorphous, Polymorph A, and Polymorph B. This study investigates the molecular basis of polymorph selection, focusing on conformational bias and solvent-mediated phase transformations (SMPTs). Methods: The conformational energy landscapes of two TPZ tautomers were constructed using relaxed torsion scans with the OPLS4 force field and validated by nuclear Overhauser effect (NOE)-based nuclear magnetic resonance (NMR). Hydrogen-bonded dimers were analyzed using DFT-D. Powder X-ray diffraction (PXRD), differential scanning calorimetry (DSC), solubility, and slurry tests were conducted using methanol, acetone, and water. Kinetic profiles were modeled with the Kolmogorov–Johnson–Mehl–Avrami (KJMA) equation. Results: Polymorph A was thermodynamically stable across all analyses. Both amorphous TPZ and Polymorph B converted to A in a solvent-dependent manner. Methanol induced direct A formation, while acetone showed a B → A transition. Crystallization was guided by solution conformers and hydrogen bonding. Conclusions: TPZ polymorph selection is governed by solution-phase conformational preferences, tautomerism, and solvent-mediated hydrogen bonding. DFT-D and NMR analyses showed that protic solvents favor the direct crystallization of stable Polymorph A, while aprotic solvents promote the transient formation of metastable Polymorph B. Elevated temperatures and humidity accelerate polymorphic transitions. This crystal structure prediction (CSP)-independent strategy offers a practical framework for rational polymorph control and the mitigation of disappearing polymorph risks in tautomeric drugs. Full article

The research investigated the influence of laser powder bed fusion (LPBF) parameters for NickelAlloy HX, a nickel-based superalloy, to achieve high-density components with superior mechanical properties. A systematic approach was employed, involving printing 40 cylindrical specimens with varying energy densities (50–240 J/mm³) to evaluate porosity, hardness, and anisotropy. Results revealed that energy density significantly influences relative density, with optimal parameters identified at 111 J/mm³ (900 mm/s scan speed, 120 W laser power). Microstructural examination revealed columnar grains aligned with the build direction in as-printed samples. The findings highlight the trade-offs between density, hardness, and microstructure in the additive manufacturing of nickel-based superalloys, providing actionable insights for industrial applications requiring specific property profiles. Full article

Carbon nanotubes (CNTs) and graphene nanoplatelets (GNPs) have attracted significant interest as hybrid reinforcements in epoxy (Ep) composites for enhancing mechanical performance in structural applications, such as aerospace and automotive. These 1D and 2D nanofillers possess exceptionally high aspect ratios and intrinsic mechanical properties, substantially improving composite stiffness and tensile strength. In this study, epoxy nanocomposites were fabricated with 0.1 wt.% and 0.3 wt.% of CNTs and GNPs individually, and with 1:1 CNT:GNP hybrid fillers at equivalent total loadings. Scanning electron microscopy of fracture surfaces confirmed that the CNTGNP hybrids dispersed uniformly, forming an interconnected nanostructured network. Notably, the 0.3 wt.% CNTGNP hybrid system exhibited minimal agglomeration and voids, preventing crack initiation and propagation. Mechanical testing revealed that the 0.3 wt.% CNTGNP/Ep composite achieved the highest tensile strength of approximately 84.5 MPa while maintaining a well-balanced stiffness profile (elastic modulus ≈ 4.62 GPa). The hybrid composite outperformed both due to its synergistic reinforcement mechanisms and superior dispersion despite containing only half the concentration of each nanofiller relative to the individual 0.3 wt.% CNT or GNP systems. In addition to mechanical performance, electrical conductivity analysis revealed that the 0.3 wt.% CNTGNP hybrid composite exhibited the highest conductivity of 0.025 S/m, surpassing the 0.3 wt.% CNT-only system (0.022 S/m), owing to forming a well-connected three-dimensional conductive network. The 0.1 wt.% CNT-only composite also showed enhanced conductivity (0.0004 S/m) due to better dispersion at lower filler loadings. These results highlight the dominant role of CNTs in charge transport and the effectiveness of hybrid networks in minimizing agglomeration. These findings demonstrate that CNTGNP hybrid fillers can deliver optimally balanced mechanical enhancement in epoxy matrices, offering a promising route for designing lightweight, high-performance structural composites. Further optimization of nanofiller dispersion and interfacial chemistry may yield even greater improvements. Full article

This study addresses the challenge of chitosan (CS) being difficult to dissolve in water due to its highly ordered crystalline structure. Chitosan is modified with chloroacetic acid to reduce its crystallinity and enhance its water solubility. Through single-factor experiments, the optimal conditions for preparing carboxymethyl chitosan film (CMCS) were determined: under conditions of 50 °C, a cellulose substrate (CS) concentration of 18.75 g/L, a NaOH concentration of 112.5 g/L, and a chloroacetic acid concentration of 18.75 g/L, the reaction proceeded for 5 h. Under these conditions, the resulting carboxymethyl chitosan film exhibited the best flocculation effect, forming chitosan films in water that had flocculation activity toward mung bean starch protein wastewater. The successful introduction of carboxyl groups at the N and O positions of the chitosan molecular chain, which reduced the crystallinity of chitosan and enhanced its water solubility, was confirmed through analysis using scanning electron microscopy (SEM), X-ray diffraction (XRD), and Fourier transform infrared spectroscopy (FTIR). The prepared carboxymethyl chitosan film (CMCS) was applied in the flocculation recovery of protein. Through single-factor and response surface experiments, the optimal process conditions for flocculating and recovering protein with CMCS were determined: a CMCS dosage of 1.1 g/L, a reaction time of 39.6 min, a reaction temperature of 42.7 °C, and a pH of 5.2. Under these conditions, the protein recovery rate reached 56.97%. The composition and amino acid profile of the flocculated product were analyzed, revealing that the mung bean protein flocculated product contained 62.33% crude protein. The total essential amino acids (EAAs) accounted for 52.91%, non-essential amino acids (NEAAs) for 47.09%, hydrophobic amino acids for 39.56%, and hydrophilic amino acids for 12.67%. The ratio of aromatic to branched-chain amino acids was 0.31, and the ratio of basic to acidic amino acids was 1.68. These findings indicate that the recovered product has high surface activity and good protein stability, foaming ability, and emulsifying properties. Full article

This study investigates measurement methods for and the distribution characteristics of normal stress within tire–road contact areas. A novel measurement method, integrating 3D scanning technology with bearing area curve (BAC) analysis, is proposed. This method quantifies the rubber penetration depth and calculates contact stress based on rubber deformation. The key innovation of this method lies in this integrated methodology for high-precision stress mapping. In the spatial domain, stress distribution is characterized by the percentage of area occupied by different stress intervals, while in the frequency domain, stress levels are analyzed at various frequencies. The results demonstrate that as the Mean Profile Depth (MPD) of the road texture increases, the areas under stress greater than 1.0 MPa increase, while the areas under stress less than 0.8 MPa decrease. However, when the MPD exceeds 0.7 mm, this effect becomes less pronounced. Higher loads and harder rubber reduce the proportion of areas under lower stress and increase the proportion under higher stress. Low-frequency (<800 1/m) stress components increase with an MPD up to 0.7 mm, beyond which they exhibit diminished sensitivity. Stress at the same frequency is not significantly affected by load variation but increases markedly with increasing rubber hardness. This research provides crucial insights into contact stress distribution, establishing a foundation for analyzing road friction and optimizing surface texture design oriented towards high-friction pavements. Full article

The objective of the current research is to investigate the role of Neusilin US2 as a porous carrier for improving the drug loading and stability of Ezetimibe (EZB) by hot melt extrusion (HME). The amorphous solid dispersions (ASDs) were developed from 10–40% of drug loading using Kollidon VA 64 (Copovidone) as a polymer matrix and Neusilin US2 as a porous carrier. The solid-state characterization of EZB was studied using differential scanning calorimetry (DSC), powder X-ray diffraction (PXRD), and Fourier transform infrared spectroscopy (FTIR). The formulation blends were characterized for flow properties, and CTC (compressibility, tabletability, compactibility) profile. The in-vitro drug release profiles were studied in 0.1 N HCl (pH 1.2). The incorporation of Neusilin US2 has facilitated the development of ASDs up to 40% of drug loading. The CTC profile has demonstrated excellent tabletability for the ternary (EZB, copovidone and Neusilin) dispersions over binary dispersion (EZB and copovidone) formulations. The tablet formulations with binary (20%) and ternary (30% and 40%) dispersions have demonstrated complete dissolution of the drug in 30 min in 0.1 N HCl (pH 1.2). The incorporation of copovidone has prevented the recrystallization of the drug in the solution state. Upon storage of formulations at accelerated conditions, the stability of ternary dispersion tablets was preserved attributing to the entrapment of the drug within Neusilin pores thereby inhibiting molecular mobility. Based on the observations, the current research concludes that it is feasible to incorporate Neusilin US2 to improve the drug loading and stability of ASD systems. Full article

Introduction: This manuscript addresses the limitations of traditional orthognathic surgery in achieving both functional and aesthetic correction in patients with Class II malocclusion and severe mandibular retrusion. Current techniques often struggle to simultaneously address mandibular deficiency and inadequate transverse dimension, leading to unsatisfactory outcomes. Methods: Seven male patients underwent bimaxillary osteotomy with mandibular advancement. A novel surgical plate, Implate, was used, which was designed to facilitate precise osteotomy and stabilization. Pre-surgical planning included CBCT scanning, 3D modeling, and surgical simulation. Postoperative assessments included clinical examinations, CT and OPT scans. Results: Implate successfully addressed the challenges of conventional techniques, minimizing the formation of bony steps and achieving a more harmonious facial profile. The minimally invasive procedure, with careful periosteal and muscle management, contributed to stable outcomes, and no complications were reported. At the 6-month follow-up, OPT analysis showed a mean mandibular width increase of 18.1 ± 6.2 mm and vertical ramus height gains of 6.0 ± 3.1 mm (left) and 5.8 ± 1.7 mm (right). Conclusions: According to our preliminary experience, the integration of Implate into surgical practice offers a significant improvement in treating complex Class II malocclusions. By simultaneously correcting mandibular retrusion and width while minimizing complications, Implate provides a superior solution compared to traditional methods. This innovative approach highlights the potential of combining advanced surgical techniques with personalized 3D-printed implants to achieve optimal functional and aesthetic outcomes. Further prospective studies with controls and longer follow-up are needed to validate the efficacy and reproducibility of Implate in wider clinical use. Full article

Background: This Phase 2 trial evaluated the efficacy, tolerability, and safety of [¹⁷⁷Lu]Lu-PSMA-617 (¹⁷⁷Lu-PSMA-617) in patients with ≥1 measurable lesion and progressive prostate-specific membrane antigen-positive (PSMA+) metastatic castration-resistant prostate cancer (mCRPC) in Japan. Methods: This study comprises four parts; data from three parts are presented here. Part 1 evaluated safety and tolerability; Parts 2 (post-taxane) and 3 (pre-taxane/taxane-naive) assessed the overall response rate (ORR; primary endpoint), overall survival (OS), radiographic progression-free survival (rPFS), disease control rate (DCR), PFS, and safety; and Part 4 is the expansion part. Patients received 7.4 GBq (±10%) ¹⁷⁷Lu-PSMA-617 Q6W for up to six cycles. Results: Of the 35 patients who underwent a [⁶⁸Ga]Ga-PSMA-11 (⁶⁸Ga-PSMA-11) PET/CT scan, 30 received ¹⁷⁷Lu-PSMA-617 (post-taxane, n = 12; pre-taxane, n = 18). No dose-limiting toxicity was noted in Part 1 (n = 3). Post- and pre-taxane patients had a median of three and five cycles, respectively. The primary endpoint, ORR, met the pre-specified threshold, with the lower limit of the 90% confidence interval (CI) above the threshold of 5% for post-taxane and 12% for pre-taxane. Post- and pre-taxane patients had an ORR of 25.0% (90% CI: 7.2–52.7) and 33.3% (90% CI: 15.6–55.4), respectively. In post- and pre-taxane patients, the DCR was 91.7% and 83.3%, the median rPFS was 3.71 and 12.25 months, and the median PFS was 3.71 and 5.59 months, respectively. The median OS was 14.42 and 12.94 months in post- and pre-taxane patients, respectively. The most common adverse events were constipation, decreased appetite, decreased platelet count, anemia, and nausea. Conclusions: The primary endpoint (ORR) was met. The safety profile of ¹⁷⁷Lu-PSMA-617 was consistent with the VISION and PSMAfore studies, with no new safety signals in the Japanese patients with mCRPC. Full article

Assessing building fire safety risks during the early design phase is vital for developing practical solutions to minimize loss of life and property. This study aims to identify research trends and provide a guiding framework for researchers by systematically reviewing the literature on integrating machine learning-based predictive methods into building fire safety design using bibliometric methods. This study evaluates machine learning applications in fire safety using a comprehensive approach that combines bibliometric and content analysis methods. For this purpose, as a result of the scan without any year limitation from the Web of Science Core Collection-Citation database, 250 publications, the first of which was published in 2001, and the number has increased since 2019, were reached, and sample analysis was performed. In order to evaluate the contribution of qualified publications to science more accurately, citation counts were analyzed using normalized citation counts that balanced differences in publication fields and publication years. Multiple regression analysis was applied to support this metric’s theoretical basis and determine the impact levels of variables affecting the metric’s value (such as total citation count, publication year, and number of articles). Thus, the statistical impact of factors influencing the formation of the normalized citation count was measured, and the validity of the approach used was tested. The research categories included evacuation and emergency management, fire detection, and early warning systems, fire dynamics and spread prediction, fire load, and material risk analysis, intelligent systems and cyber security, fire prediction, and risk assessment. Convolutional neural networks, artificial neural networks, support vector machines, deep neural networks, you only look once, deep learning, and decision trees were prominent as machine learning categories. As a result, detailed literature was presented to define the academic publication profile of the research area, determine research fronts, detect emerging trends, and reveal sub-themes. Full article

Background/Objectives: Myasthenia Gravis (MG) and myasthenic syndrome (MSyn) are neurological disorders induced by different types of autoantibodies, characterized by generalized muscle weakness, sometimes involving the respiratory muscles and necessitating ventilatory support. One therapeutic option for severe Myasthenia Gravis (MG) is total plasma exchange (TPE). This procedure reduces the concentration of autoantibodies by extracting the patient’s plasma and replacing it with donor plasma. The TPE efficacy varies among different types of MG, and patient response to TPE is evaluated solely through clinical markers, such as muscle strength. So far, no laboratory method is available for monitoring TPE treatment progress. Objective: In this study, we aimed to determine whether differential scanning calorimetry (DSC) of blood plasma from myasthenic patients is an appropriate tool to monitor and evaluate their condition and the TPE effect. Methods: We performed DSC prior to and after TPE course on blood plasma from three patients with different types of MG: Case 1. Patient with Acetylcholine Receptor Myasthenia Gravis (AChR MG); Case 2. Patient with Muscle-specific tyrosine kinase Myasthenia Gravis (MuSK MG); Case 3. Patient with Myasthenic syndrome (MSyn). Results: DSC thermogram examination revealed increased plasma protein fractions, primarily immunoglobulins (IG), as well as to some extent fibrinogen, relative to a suppressed serum albumin fraction. Successive TPE procedures resulted in IG fraction decline in AChR MG (Case 1) and MSyn (Case 3), and upsurge of the IG fraction in MuSK MG (Case 2). These findings aligned with the clinical presentation of all three cases. Conclusions: DSC revealed distinct, very significant differences in the heat capacity profiles of blood plasma from MG patients relative to healthy controls, as well as strong TPE influence on the plasma thermal behavior. DSC showed promise as a reliable and informative technique for the monitoring of myasthenia and TPE effects across diverse myasthenic patient populations. Further research is needed to confirm and expand on these findings. Full article

Gear whine noise is governed not only by intentional microgeometry modifications but also by unavoidable pitch (indexing) deviation. This study presents a workflow that couples a tooth-resolved surface scan with a calibrated pitch-deviation table, both imported into a multibody dynamics (MBD) model built in MSC Adams View. Three operating scenarios were evaluated—ideal geometry, measured microgeometry without pitch error, and measured microgeometry with pitch error—at a nominal speed of 1000 r min⁻¹. Time domain analysis shows that integrating the pitch table increases the mean transmission error (TE) by almost an order of magnitude and introduces a distinct 16.66 Hz shaft order tone. When the measured tooth topologies are added, peak-to-peak TE nearly doubles, revealing a non-linear interaction between spacing deviation and local flank shape. Frequency domain results reproduce the expected mesh-frequency side bands, validating the mapping of the pitch table into the solver. The combined method therefore provides a more faithful digital twin for predicting tonal noise and demonstrates why indexing tolerances must be considered alongside profile relief during gear design optimization. Full article