Search Results (3,408)

Click chemistry has become a powerful and flexible approach for designing hydrogels used in tissue engineering thanks to its high specificity, fast reaction rates, and compatibility with biological systems. In this review, we introduce the core principles of click chemistry, including efficiency, orthogonality, and modularity, and highlight the main types of reactions commonly used in hydrogel formation, such as azide-alkyne c-cloadditions, thiol-ene/yne reactions, Diels–Alder cycloadditions, and tetrazine–norbornene couplings. These chemistries allow researchers to create covalently crosslinked hydrogels that are injectable, responsive to environmental stimuli, biodegradable, or multifunctional. We also explore strategies to enhance bioactivity, such as incorporating peptides, growth factors, or extracellular matrix components, and enabling precise spatial and temporal control over biological cues. Click-based hydrogels have shown promise across a wide range of tissue engineering applications, from cartilage and skin repair to neural regeneration, corneal healing, and cardiovascular scaffolds, as well as in 3D bioprinting technologies. Despite the many advantages of click chemistry such as mild reaction conditions and customizable material properties, some challenges remain, including concerns around copper toxicity, the cost of specialized reagents, and scalability. Finally, we discuss the status of clinical translation, regulatory considerations, and future directions, including integration with advanced bio fabrication methods, the design of dual-click systems, and the emerging role of in vivo click chemistry in creating next-generation biomaterials. Full article

This study optimizes the design and fabrication of an injection-molded Alvarez freeform lens using Moldex3D mold flow analysis and CODE V optical design simulations. The dual-software approach facilitates the transition between the manufacturing simulations and the optical design/verification process, thereby addressing the conversion issues between the two analysis modules. The optical quality of the designed lens is evaluated using spot diagram, distortion, and modulation transfer function (MTF) simulations. The Taguchi design methodology is first employed to identify the individual effects of the key injection molding parameters on the quality of the fabricated lens. The quality is then further improved by utilizing two multi-objective optimization methods, namely Gray Relational Analysis (GRA) and Robust Multi-Criteria Optimization (RMCO), to determine the optimal combination of the injection molding parameters. The results demonstrate that RMCO outperforms GRA, showing more substantial improvements in the optical quality of the lens. Overall, the proposed integrated method, incorporating Moldex3D, CODE V, Taguchi robust design, and RMCO analyses, provides an effective approach for optimizing the injection molding of Alvarez freeform lenses, thereby enhancing their quality. Future research could extend this methodology to other optical components and more complex optical systems. Full article

Bio field-effect transistors (BioFETs) have attracted attention for their ability to rapidly detect physiological data with a simple structure. While conventional BioFETs offer high sensitivity, they often require reference electrodes or involve complex fabrication processes. A recently proposed bulk junctionless BioFET (Bulk JL-BioFET) features a simple fabrication process to address these issues. This structure utilizes a depletion region formed by a p-n junction, as the active layer is directly in contact with a substrate of the opposite type. As a result, the device can operate effectively with only two terminals—drain and source—without the need for a reference electrode. In this study, we propose a novel Bulk JL-BioFET, incorporating a doped field stop layer and an asymmetric source/drain structure, and verify its performance through simulations. The doped field stop layer blocks the electric field expansion, enhancing channel modulation, while the asymmetric source/drain structure promotes electron injection, reducing the on-off swing voltage and turn-on voltage. This improves the electrical performance, enabling lower power consumption and higher sensitivity. Simulation results show that the combination of these two novel features results in a sensitivity increase of approximately 30-fold. Moreover, high sensitivity was observed below the turn-on voltage region for all the structures when analyzing the sensitivity with overdrive voltage, identifying the optimal operating conditions. This study suggests that the combination of the doped field stop layer and asymmetric source/drain structure is an effective design strategy to maximize the sensing performance of BioFETs while minimizing power consumption. Full article

Intra-articular injections form a substantial element of the temporomandibular joint disorder (TMD) therapy. Given the role played by IL-1β in pathology, the use of autologous conditioned serum (ACS) is well-founded. Despite years of effective use in different locations, data regarding the intra-articular administration of ACS in TMD is scarce, and the strategy itself is not routinely applied. This study aims to provide preliminary evidence on the therapeutic efficacy of administering intra-articular ACS in treating TMD. Patients with TMD who received intra-articular ACS were included. More invasive co-interventions, such as arthroscopy, were excluded. Final searches were conducted on 17 June 2025, using five databases (ACM, BASE, DOAJ, PubMed, and SciELO). Risk of bias was evaluated using the RoB 2 tool. The results were tabulated. Only one study met the inclusion criteria. When compared to dextrose prolotherapy in internal TMD, ACS therapy resulted in greater improvement in mouth opening, pain, and joint-sound reduction. The small sample size, head-to-head design, and limited blinding suggest a highly cautious interpretation of the findings. ACS is a promising, but still experimental, therapeutic strategy addressing critical mechanisms in TMD. However, the currently available data is insufficient to confirm the effectiveness and safety of such an approach, and further high-quality studies are needed. This study received no funding. PROSPERO registration number: CRD420251069310. Full article

Background: Herpes simplex virus (HSV) is a neurotropic virus that can be categorized into two serotypes: HSV-1 and HSV-2. HSV-1 causes symptoms such as herpes labialis, herpetic keratitis, genital ulcers, and encephalitis, and primarily establishes latent infection in the trigeminal ganglion. The complexity of membrane fusion mechanisms and potential infection in nerves allow HSV to easily evade recognition and clearance by host immune cells. Therefore, developing a vaccine that can prevent both primary and reactivated HSV-1 infection is critical. Currently, no preventive or therapeutic HSV-1 vaccines have been approved for marketing. Methods: In this study, we utilized the gC, gD, and gE proteins of HSV-1, which are associated with viral fusion and immune escape, to design a trivalent antigen vaccine that is capable of inducing a cellular immune response. Two formulations of the vaccine are available: a subunit vaccine incorporating oligodeoxynucleotides with CpG motifs (CpG ODNs) and QS-21 as adjuvants, as well as an mRNA vaccine. Mice were immunized via intramuscular injection to evaluate and compare the immunological responses and protective efficacy of the two vaccines. Results: After the challenge, the viral load in the tissues of both vaccine groups was significantly lower than that in the positive control group, indicating that both vaccines were able to control viral proliferation in the tissues. Conclusions: The findings indicated that both mRNA and subunit vaccines were capable of eliciting comparable humoral and cellular immune responses. Full article

Blepharospasm (BSP) is characterized by excessive orbicularis oculi muscle activity leading to abnormal blinking and involuntary eyelid closure. Botulinum neurotoxin (BoNT) injections are the main treatment for BSP, but they only partially and transiently relieve symptoms, leading to a waxing and waning therapeutic response. A patient-centered outcome (PCO) tool that measures BSP symptoms in a simple and efficient way could inform the development of better treatments. Using a stepwise modified Delphi approach, potential PCO items were first identified using the Dystonia Coalition Database with data from over 200 individuals with BSP who had provided responses to existing clinical assessment scales. These items were then analyzed for contribution to overall severity using a Random Forests approach, and redundant items were merged and revised in a series of iterative meetings with a specialist panel along with input from patient advocacy group representatives and focus groups. An online survey was conducted with 330 individuals with BSP to validate and verify the items’ relevance. Finally, the specialist panel provided content validity ratio, which was repeated until it showed good agreement for relevance and clarity of all items. In the end, an easy-to-use PCO tool designed for smartphones and tablets containing 17 items covering three symptom domains (motor, disability, and psychosocial/quality of life) was created. This novel PCO tool for BSP may be used to characterize the cyclical response that an individual patient experiences from BoNT treatments and provide a vital tool for future investigations of longer-acting BoNT preparations or adjunctive therapies. Full article

Osteoarthritis (OA) is a major cause of equine lameness, with few effective disease-modifying treatments. This systematic review, conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines, evaluated the efficacy of platelet-rich plasma (PRP) for equine OA by analyzing 11 studies (6 clinical, 5 experimental) identified through Web of Science, Scopus, and PubMed (2000–2024). The screening process identified 252 records, of which 136 were duplicates and 105 were excluded based on predefined criteria. The analysis showed that intra-articular PRP injections are generally safe, with transient synovial inflammation occurring mainly when PRP was activated with bovine thrombin. Both leukocyte-rich (L-PRP) and leukocyte-poor (P-PRP) formulations exhibited comparable efficacy, though optimal platelet concentrations (423–658 × 10³/μL) and dosing regimens remain undefined. A PRISMA-based quality assessment highlighted substantial variability in study design, with clinical trials constrained by small sample sizes and high risk of bias. Experimental studies confirmed PRP’s biological activity but showed inconsistencies in preparation methods. The findings indicate that PRP activation is unnecessary and may even be pro-inflammatory, that multiple injections could improve outcomes, and that reporting of cellular composition is inconsistent across studies. The PRISMA framework identified critical evidence gaps, particularly regarding long-term efficacy and protocol standardization. These results emphasize the need for PRISMA-compliant randomized controlled trials featuring standardized PRP protocols, validated outcome measures, and extended follow-up periods to establish evidence-based guidelines for managing equine OA. Full article

Monitoring the complete injection molding process is becoming critical for manufacturing high-quality polymer products, as it enhances product quality and process efficiency. This study presents the development of a virtual sensor designed to monitor critical parameters of the injection molding process that cannot be measured with existing sensors. The virtual sensor integrates both one-dimensional system simulations and data-driven models to accurately predict the behavior of the complete injection molding process, including the plasticizing steps. In our investigation, the virtual sensor was tested and demonstrated its ability in forecasting key process parameters, namely the injection pressure and the screw displacement. The sensor’s ability to provide real-time melt temperature or shear rate highlights its practical applicability and effectiveness in optimizing the injection molding process. Full article

In this paper, we report the design and verification methodology of a SystemVerilog-based I²C protocol Verification IP (VIP) based not only on assertion-based verification but also on the new checkout error injection techniques. The resulting VIP is designed as a set of loose-coupled modules for protocol description, transaction generation, and automatic protocol checking with SystemVerilog Assertions (SVAs). Timing, multi-master arbitration, and error recovery related to I²C protocol verification challenges are achieved using embedded assertion monitors and focused error injection scenarios on the testbench. The paper describes the inclusion of assertion-based monitors used for checking real-time protocol compliance as well as the ability for systematic error injection to expose corner-case bugs and verify the strength of the DUT and the verification environment. We present our experimental results that demonstrate the effectiveness of proposed strategies on coverage, bug leakage, and reduction in debug cycles. The approach also provides a useful guideline for verification engineers who need to build protocol VIPs or wish to improve the efficiency of their verification flow with assertion-led methods. Full article

A critical challenge in engine research lies in minimizing harmful emissions while optimizing the efficiency of internal combustion engines. Dual-fuel engines, operating with methanol and diesel, offer a promising alternative, but their combustion modeling remains complex due to the intricate thermochemical interactions involved. This study proposes a predictive framework that combines validated CFD simulations with deep learning techniques to estimate key combustion and emission parameters in a methanol–diesel dual-fuel engine. A three-dimensional CFD model was developed to simulate turbulent combustion, methanol injection, and pollutant formation, using the RNG k-ε turbulence model. A temporal dataset consisting of 1370 samples was generated, covering the compression, combustion, and early expansion phases—critical regions influencing both emissions and in-cylinder pressure dynamics. The optimal configuration identified involved a 63° spray injection angle and a 25% methanol proportion. A Gated Recurrent Unit (GRU) neural network, consisting of 256 neurons, a Tanh activation function, and a dropout rate of 0.2, was trained on this dataset. The model accurately predicted in-cylinder pressure, temperature, NOx emissions, and impact-related parameters, achieving a Pearson correlation coefficient of ρ = 0.997. This approach highlights the potential of combining CFD and deep learning for rapid and reliable prediction of engine behavior. It contributes to the development of more efficient, cleaner, and robust design strategies for future dual-fuel combustion systems. Full article

The rubber industry is evolving by incorporating innovative tools to improve production processes. A proper manufacturing process determines the behavior and service life of the resulting products. In this research, molecular dynamics simulations were used to study the effect of temperature in the cured structure on the resulting mechanical properties of EPDM. The results of the simulations at different temperatures of the crosslinked ethylene–propylene–diene monomer (EPDM) were then compared in terms of the radius of gyration, free volume, root mean square displacement, stress curves, viscosity, and gel point. Then, using the superposition principle, viscosity and tensile stress were evaluated. The molecular dynamics superposition results could reasonably predict the mechanical behavior of EPDM during and after the injection process. The results provide new insights into the molecular-level crosslinking mechanisms of amorphous polymers and their influence on mechanical behavior, which facilitates the design of the injection process for rubber component applications. The results show an increase in viscosity and a decrease in the critical gel point with increasing temperature. The hardness tests performed on an automotive component demonstrate that this has an impact on the resulting properties. Full article

This study evaluates the application of metal additive manufacturing—specifically the laser powder bed fusion (LPBF) process—for producing aluminium die-casting mould components, comparing 300-grade maraging steel inserts with conventional H13 tool steel. Efficient thermal management and mould durability are critical in aluminium injection moulding. Still, traditional machining limits the design of cooling channels, resulting in hot spots, accelerated wear, and a reduced service life. LPBF allows the fabrication of complex geometries, enabling conformal cooling channels to enhance thermal control. Component samples were manufactured using maraging steel via LPBF, machined to final dimensions, and subjected to duplex surface treatment (plasma nitriding + CrAlN PVD coating). Thermal performance, dimensional stability, mechanical properties, and wear resistance were experimentally assessed under conditions simulating industrial production. The results demonstrate that LPBF components with optimised cooling channels and surface engineering achieve higher thermal efficiency, an extended service life (up to 2.6×), improved hardness profiles (545 HV0.05 core, 1230 HV0.05 on nitrided surface and 2850 HV0.05 after PVD film deposition), and reduced maintenance frequencies compared to H13 inserts. The study confirms that additive manufacturing, combined with tailored surface treatments and optimised cooling design, overcomes the geometric and thermal limitations of conventional manufacturing, offering a reliable and productive solution for aluminium die-casting moulds. Full article

The fuel electro-hydraulic servo valve is a core component of the aero-engine fuel control system, playing a crucial role in engine performance. Due to the operational characteristics of the aviation fuel supply and injection system, fuel is directly sprayed through the nozzle for combustion after passing through the pipeline. The working environment and medium are subject to a wide temperature range, and the medium lacks a circulating filtration process, making it difficult to effectively remove impurities. As a result, the fuel contains a high concentration of contaminant particles. Under high-temperature conditions, colloidal particles precipitated from the fuel medium collide and adhere to metallic and other contaminant particles carried by the fuel, subsequently attaching to the internal surfaces of the fuel servo valve, causing valve sticking. This study aims to establish an adhesion criterion suitable for colloidal particles in fuel systems based on a traditional particle collision model. The adhesion criterion incorporates the viscoelastic and surface energy characteristics of colloidal particles, providing a more accurate description of their deposition behavior under the conditions studied. A particle–particle and particle–wall collision test apparatus was designed, and experiments were conducted. A comparison between experimental results and theoretical calculations shows that the overall error for collisions between colloidal particles and walls is controlled within 10%, validating the feasibility of the adhesion criterion. The Young’s modulus, Poisson’s ratio, and surface free energy of the colloidal particles were measured as 688 MPa, 0.39, and 77 mJ/m², respectively. These results provide theoretical and experimental foundations for particle migration and deposition processes in fuel systems. The analytical method clarifies the key mechanism of adhesion caused by colloidal particles, providing guidance for improving the reliability, safety, and maintenance of fuel servo valves in aero-engine applications. Full article

The GaN-on-Si virtual substrate is now an indispensable platform for the application of GaN in the fields of power devices, radio frequency, light-emitting devices, etc. Such applications are still in need of more effective stress balancing techniques to achieve higher quality and stress balance in GaN-on-Si at a lower thickness. In this study, three promising practical prototypes of highly effective stress-balancing structures are proposed to realize the concept of an ideal AlN interlayer (AlN-IL) featuring a completely relaxed lower AlN/GaN interface and a fully strained upper GaN/AlN interface. The first is a single-layer AlN interlayer grown via precursor pulsed-injection (PI-AlN-IL). The second combines a low-temperature AlN (LT-AlN) underlayer with a PI-AlN-IL. The third integrates LT-AlN with a high-temperature AlN cap. Compared with optimal conventional single-layer AlN interlayer references, all these designs more effectively induced compressive stress and strain in overlying GaN layers. This study opens new technical paths to balancing stress in GaN-on-Si systems at a reduced thickness more efficiently. Full article

The energy consumption issue of water injection systems has always been a key focus of energy conservation and consumption reduction in oilfield production. Optimizing the operational schemes of the water injection system is of great significance for achieving energy conservation and consumption reduction goals in oilfields. This article establishes a mathematical model for optimizing the operating parameters of oilfield water injection systems, with the operating parameters of water injection pumps as design variables and the objective function of minimizing water injection energy consumption. In the model, multiple constraints such as the balance of supply and demand of water within the station, pump flow rate, and injection well pressure are considered. Using the four defensive behaviors of the Crested Porcupine Optimizer (CPO) to optimize the Particle Swarm Optimization (PSO) Algorithm, a Multi-Mechanism Threat Response Strategy for Dynamic Parameter Adjustment is proposed to form a Hybrid Particle Swarm–Crested Porcupine Algorithm (PSCPA). Compared with the other nine algorithms, the PSCPA has better solving efficiency. Applying this method to a practical case of an old oilfield, the optimized water injection system scheme reduced power consumption by 11,719.23 KWh/d, increased the average pump efficiency of the system by 9.3%, and reduced system unit consumption by 0.37 KWh/d. Therefore, this algorithm has good practicality for optimizing the operation of large-scale and highly sensitive water injection systems. Full article