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Inspired by the potential of architected materials for achieving biomimicking functionalities and the advancement of multi-material additive manufacturing to fabricate parts with complex structures and heterogeneous material distributions, this study investigates the feasibility of using a multi-material, flexible chain mail sheet for the design of an additively manufactured artificial spinal disc for reproducing patient-specific anisotropic and nonlinear rotational behaviors. The application of a chain mail-based structure is motivated by its similarities in behaviors compared with a natural disc's fiber network that likewise has negligible bending stiffness and shape-changing ability. The proposed approach for the chain mail sheet design includes an initial characterization of the uniaxial tensile responses of the chain mail unit cell defined as the basic building block of the chain mail sheet, modeling and response calculation, and material optimization. Results show that the additively manufactured chain mail sheet is not only able to exhibit a natural strain-stiffening rotational response but also is able to reproduce natural anisotropy of three natural disc specimens in the six most common rotational scenarios in daily life. This study shows the potential of additively manufactured mechanical-metamaterials-inspired structures for implant design to restore natural mechanics.

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This comprehensive review provides a deep exploration of the unique roles of single atom catalysts (SACs) in photocatalytic hydrogen peroxide (H2O2) production. SACs offer multiple benefits over traditional catalysts such as improved efficiency, selectivity, and flexibility due to their distinct electronic structure and unique properties. The review discusses the critical elements in the design of SACs, including the choice of metal atom, host material, and coordination environment, and how these elements impact the catalytic activity. The role of single atoms in photocatalytic H2O2 production is also analysed, focusing on enhancing light absorption and charge generation, improving the migration and separation of charge carriers, and lowering the energy barrier of adsorption and activation of reactants. Despite these advantages, several challenges, including H2O2 decomposition, stability of SACs, unclear mechanism, and low selectivity, need to be overcome. Looking towards the future, the review suggests promising research directions such as direct utilization of H2O2, high-throughput synthesis and screening, the creation of dual active sites, and employing density functional theory for investigating the mechanisms of SACs in H2O2 photosynthesis. This review provides valuable insights into the potential of single atom catalysts for advancing the field of photocatalytic H2O2 production.

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Although loop epitopes at protein-protein binding interfaces often play key roles in mediating oligomer formation and interaction specificity, their binding sites are underexplored as drug targets owing to their high flexibility, relatively few hot spots, and solvent accessibility. Prior attempts to develop molecules that mimic loop epitopes to disrupt protein oligomers have had limited success. In this study, we used structure-based approaches to design and optimize cyclic-constrained peptides based on loop epitopes at the human phosphoglycerate dehydrogenase (PHGDH) dimer interface, which is an obligate homo-dimer with activity strongly dependent on the oligomeric state. The experimental validations showed that these cyclic peptides inhibit PHGDH activity by directly binding to the dimer interface and disrupting the obligate homo-oligomer formation. Our results demonstrate that loop epitope derived cyclic peptides with rationally designed affinity-enhancing substitutions can modulate obligate protein homo-oligomers, which can be used to design peptide inhibitors for other seemingly intractable oligomeric proteins.

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Introduction: Prolonged exposure of train drivers to thermal discomfort can lead to occupational safety and health (OSH) risks, causing physical and mental injuries. Traditional method of treating human skin as a wall surface fail to observe accurate skin temperature changes or obtain human thermal comfort that adapts to the thermal environment. Methods: This study employs the Stolwijk human thermal regulation model to investigate and optimize the thermal comfort of train drivers. To minimize the time-consuming design optimization, a pointer optimization algorithm based on radial basis function (RBF) approximation was utilized to optimize the train cab ventilation system design and enhance drivers' thermal comfort. The train driver thermal comfort model was developed using Star-CCM+ and 60 operating conditions were sampled using an Optimal Latin Hypercube Design (Opt LHD). Results and Discussion: We analyzed the effects of air supply temperature, air supply volume, air supply angle, solar radiation intensity and solar altitude angle on the local thermal sensation vote (LTSV) and overall thermal sensation vote (OTSV) of the train driver. Finally, the study obtained the optimal air supply parameters for the Heating Ventilation and Air Conditioning (HVAC) in the train cabin under extreme summer conditions, effectively improving the thermal comfort of the driver.

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Over the last two decades, the capabilities of metasurfaces in light modulation with subwavelength thickness have been proven, and metasurfaces are expected to miniaturize conventional optical components and add various functionalities. Herein, various metasurface design strategies are reviewed thoroughly. First, the scalar diffraction theory is revisited to provide the basic principle of light propagation. Then, widely used design methods based on the unit-cell approach are discussed. The methods include a set of simplified steps, including the phase-map retrieval and meta-atom unit-cell design. Then, recently emerging metasurfaces that may not be accurately designed using unit-cell approach are introduced. Unconventional metasurfaces are examined where the conventional design methods fail and finally potential design methods for such metasurfaces are discussed.

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This comprehensive review focuses on the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and its impact as the cause of the COVID-19 pandemic. Its objective is to provide a cohesive overview of the epidemic history and evolutionary aspects of the virus, with a particular emphasis on its emergence, global spread, and implications for public health. The review delves into the timelines and key milestones of SARS-CoV-2's epidemiological progression, shedding light on the challenges encountered during early containment efforts and subsequent waves of transmission. Understanding the evolutionary dynamics of the virus is crucial in monitoring its potential for adaptation and future outbreaks. Genetic characterization of SARS-CoV-2 is discussed, with a focus on the emergence of new variants and their implications for transmissibility, severity, and immune evasion. The review highlights the important role of genomic surveillance in tracking viral mutations linked to establishing public health interventions. By analyzing the origins, global spread, and genetic evolution of SARS-CoV-2, valuable insights can be gained for the development of effective control measures, improvement of pandemic preparedness, and addressing future emerging infectious diseases of international concern.

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Antimicrobial peptides (AMPs) are a class of peptides widely existing in nature with broad-spectrum antimicrobial activity. It is considered as a new alternative to traditional antibiotics because of its unique mechanism of antimicrobial activity. The development and application of natural AMPs are limited due to their drawbacks such as low antimicrobial activity and unstable metabolism. Therefore, the design and optimization of derived peptides based on natural antimicrobial peptides have become recent research hotspots. In this paper, we focus on ribosomal AMPs and summarize the design and optimization strategies of some related derived peptides, which include reasonable primary structure modification, cyclization strategy and computer-aided strategy. We expect to provide ideas for the design and optimization of antimicrobial peptides and the development of anti-infective drugs through analysis and summary in this paper.

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Background and Objective: An auditory prosthesis refers to a device designed to restore hearing. Some parameters of the auditory prosthesis, such as mass, implanted position, and degree, need to be repeatedly designed and optimized based on the realistic geometry of the ear. Numerous auditory prostheses designs were based on animal or specimen experiments involving many complex instruments, and the experimental specimens had low repeatability. The finite element method (FEM) can overcome these disadvantages and be carried out on the computer with substantial flexibility in modifying the prosthetic parameters to optimize them. This narrative review aims to analyze the recent advances in the design and optimization of auditory prostheses using the FEM and provides suggestions for future development. Methods: The literature on the design of auditory prostheses using the FEM has been extensively studied using the PubMed and Web of Science databases, including different ear models and relevant parameters of different auditory prostheses that need to be designed and optimized. Key Content and Findings: The process of designing and optimizing a prosthesis using the FEM includes building an ear model and a prosthesis model to simulate the implantation process. The related parameters of the prosthesis can be designed and modified conveniently. The post-implantation response could be used as an indicator to evaluate the prosthesis's performance. Conclusions: The review concluded that the FEM had been widely studied in designing and optimizing middle ear implants and cochlear implants and obtained good results. FEM can be utilized to explore more effective directions for auditory prosthesis design and optimization in the future.

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Lyophilization process design still relies mainly on empirical studies with high experimental loads. In the regulatory demanded Quality by Design approach, process modeling is a key aspect. It allows process design, optimization and process control to ensure a safe process and product quality. A modeling approach is outlined that is able to predict the primary drying endpoint and temperature profile of distinct vials. Model parameters are determined by a reproducible determination concept. Simulated results are validated with a fractional factorial Design of Experiments (DoE) in pilot scale. The model shows higher accuracy and precision than the experiments and similar parameter interactions for both the endpoint and temperature determination. This approach can now be used to explore the primary design space in lyophilization process design. This paper proposes a distinct method for endpoint determination and product temperature prediction by a modeling approach based on Velardi et al. combined with a distinct model parameter determination according to Wegiel et al. and Tang et al.

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Antimicrobial peptides (AMPs) are a class of peptides widely existing in nature with broad-spectrum antimicrobial activity. It is considered as a new alternative to traditional antibiotics because of its unique mechanism of antimicrobial activity. The development and application of natural AMPs are limited due to their drawbacks such as low antimicrobial activity and unstable metabolism. Therefore, the design and optimization of derived peptides based on natural antimicrobial peptides have become recent research hotspots. In this paper, we focus on ribosomal AMPs and summarize the design and optimization strategies of some related derived peptides, which include reasonable primary structure modification, cyclization strategy and computer-aided strategy. We expect to provide ideas for the design and optimization of antimicrobial peptides and the development of anti-infective drugs through analysis and summary in this paper.

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Pichia pastoris is one of the most widely used host for the production of recombinant proteins. Expression systems that rely mostly on promoters from genes encoding alcohol oxidase 1 or glyceraldehyde-3-phosphate dehydrogenase have been developed together with related bioreactor operation strategies based on carbon sources such as methanol, glycerol, or glucose. Although, these processes are relatively efficient and easy to use, there have been notable improvements over the last twenty years to better control gene expression from these promoters and their engineered variants. Methanol-free and more efficient protein production platforms have been developed by engineering promoters and transcription factors. The production window of P. pastoris has been also extended by using alternative feedstocks including ethanol, lactic acid, mannitol, sorbitol, sucrose, xylose, gluconate, formate or rhamnose. Herein, the specific aspects that are emerging as key parameters for recombinant protein synthesis are discussed. For this purpose, a holistic approach has been considered to scrutinize protein production processes from strain design to bioprocess optimization, particularly focusing on promoter engineering, transcriptional circuitry redesign. This review also considers the optimization of bioprocess based on alternative carbon sources and derived co-feeding strategies. Optimization strategies for recombinant protein synthesis through metabolic modelling are also discussed.

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This study aims to develop methods to design and optimize the resonator in a resonant accelerometer based on mode and frequency analysis. First, according to the working principle of a resonant accelerometer, the resonator is divided into three parts: beam I, beam II, and beam III. Using Hamilton's principle, the undamped dynamic control equation and the ordinary differential dynamic equation of the resonant beam are obtained. Moreover, the structural parameters of the accelerometer are designed and optimized by using resonator mode and frequency analysis, then using finite element simulation to verify it. Finally, 1 g acceleration tumbling experiments are built to verify the feasibility of the proposed design and optimization method. The experimental results demonstrate that the proposed accelerometer has a sensitivity of 98 Hz/g, a resolution of 0.917 mg, and a bias stability of 1.323 mg/h. The research findings suggest that according to the resonator mode and frequency analysis, the values of the resonator structural parameters are determined so that the working mode of the resonator is far away from the interference mode and avoids resonance points effectively. The research results are expected to be beneficial for a practical resonant sensor design.

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Compact varifocal lenses are essential to various imaging and vision technologies. However, existing varifocal elements typically rely on mechanically actuated systems with limited tuning speeds and scalability. Here, an ultrathin electrically controlled varifocal lens based on a liquid crystal (LC) encapsulated dielectric metasurface is demonstrated. Enabled by the field-dependent LC anisotropy, applying a voltage bias across the LC cell modifies the local phase response of the silicon meta-atoms, in turn modifying the metalens focal length. In a numerical implementation, a voltage-actuated metalens with continuous zoom and up to 20% total focal shift is demonstrated. The LC-based metalens concept is experimentally verified through the design and fabrication of a bifocal metalens that facilitates high-contrast switching between two discrete focal lengths upon application of a 9.8 Vpp voltage bias. Owing to their ultrathin thickness and adaptable design, LC-driven dielectric metasurfaces open new opportunities for compact varifocal lensing in a diversity of modern imaging applications.

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Bioresorbable vascular scaffolds (BVS), made either from polymers or from metals, are promising materials for treating coronary artery disease through the processes of percutaneous transluminal coronary angioplasty. Despite the opinion that bioresorbable polymers are more promising for coronary stents, their long-term advantages over metallic alloys have not yet been demonstrated. The development of new polymer-based BVS or optimization of the existing ones requires engineers to perform many very expensive mechanical tests to identify optimal structural geometry and material characteristics. in silico mechanical testing opens the possibility for a fast and low-cost process of analysis of all the mechanical characteristics and also provides the possibility to compare two or more competing designs. In this study, we used a recently introduced material model of poly-l-lactic acid (PLLA) fully bioresorbable vascular scaffold and recently empowered numerical InSilc platform to perform in silico mechanicals tests of two different stent designs with different material and geometrical characteristics. The result of inflation, radial compression, three-point bending, and two-plate crush tests shows that numerical procedures with true experimental constitutive relationships could provide reliable conclusions and a significant contribution to the optimization and design of bioresorbable polymer-based stents.

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Rising demands for biopharmaceuticals and the need to reduce manufacturing costs increase the pressure to develop productive and efficient bioprocesses. Among others, a major hurdle during process development and optimization studies is the huge experimental effort in conventional design of experiments (DoE) methods. As being an explorative approach, DoE requires extensive expert knowledge about the investigated factors and their boundary values and often leads to multiple rounds of time-consuming and costly experiments. The combination of DoE with a virtual representation of the bioprocess, called digital twin, in model-assisted DoE (mDoE) can be used as an alternative to decrease the number of experiments significantly. mDoE enables a knowledge-driven bioprocess development including the definition of a mathematical process model in the early development stages. In this chapter, digital twins and their role in mDoE are discussed. First, statistical DoE methods are introduced as the basis of mDoE. Second, the combination of a mathematical process model and DoE into mDoE is examined. This includes mathematical model structures and a selection scheme for the choice of DoE designs. Finally, the application of mDoE is discussed in a case study for the medium optimization in an antibody-producing Chinese hamster ovary cell culture process.

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In lead optimization, protein crystallography is an indispensable tool to analyze drug binding. Binding modes and non-covalent interaction inventories are essential to design follow-up synthesis candidates. Two protocols are commonly applied to produce protein-ligand complexes: cocrystallization and soaking. Because of its time and cost effectiveness, soaking is the more popular method. Taking eight ligand hinge binders of protein kinase A, we demonstrate that cocrystallization is superior. Particularly for flexible proteins, such as kinases, and larger ligands cocrystallization captures more reliable the correct binding pose and induced protein adaptations. The geometrical discrepancies between soaking and cocrystallization appear smaller for fragment-sized ligands. For larger flexible ligands that trigger conformational changes of the protein, soaking can be misleading and underestimates the number of possible polar interactions due to inadequate, highly impaired positions of protein amino-acid side and main chain atoms. Thus, if applicable cocrystallization should be the gold standard to study protein-ligand complexes.

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Flow cytometry is a valuable tool in determining the phenotype and function of platelets accurately. The emergence of platelet flow cytometry in recent years provides an attractive alternative to other platelet analytical techniques, with advantages such as requiring small volumes and being highly sensitive to minimal changes in receptor function and expression. Here we present a methodical approach encompassing the stages in the development and optimization of platelet flow cytometry panels based on our extensive experience in this area.

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Lattice structures are known for their high strength-to-weight ratio, multiple functionalities, lightweight, stiffness, and energy absorption capabilities and potential applications in aerospace, automobile, and biomedical industry. To reveal the buckling (global and local) and post-buckling behavior of different lattice morphologies, both experimental and simulation-based studies were carried out. Additionally, a variable-density lattice structure was designed and analyzed to achieve the optimal value of critical buckling load. Latticed columns were fabricated using polyamide 12 material on multi jet fusion 3D printer. The results exhibited that the buckling in lattice columns depends on the distribution of mass, second moment of inertia I, diameter and position of vertical beams, number of horizontal or inclined beams, and location and angle of the beams that support the vertical beams. The number of horizontal and inclined beams and their thickness has an inverse relation with buckling; however, this trend changes after approaching a critical point. It is revealed that vertical beams are more crucial for buckling case, when compared with horizontal or inclined beams; however, material distribution in inclined or horizontal orientation is also critical because they provide support to vertical beams to behave as a single body to bear the buckling load. The results also revealed that the critical buckling load could be increased by designing variable density cellular columns in which the beams at the outer edges of the column are thicker compared with inner beams. However, post-buckling behavior of variable density structures is brittle and local when compared with uniform density lattice structures.

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Trial-and-error approach to formulation development is long and costly. With growing time and cost pressures in the pharmaceutical industry, the need for computer-based formulation design is greater than ever. In this project, emulgels were designed and optimized using Formulating for Efficacy™ (FFE) for the topical delivery of ibuprofen. FFE helped select penetration enhancers, design and optimize emulgels and simulate skin penetration studies. pH, viscosity, spreadability, droplet size and stability of emulgels were evaluated. Franz cell studies were performed to test in vitro drug release on regenerated cellulose membrane, drug permeation in vitro on Strat-M® membrane and ex vivo on porcine ear skin, a marketed ibuprofen gel served as control. Emulgels had skin compatible pH, viscosity and spreadability comparable to a marketed emulgel, were opaque and stable at 25 °C for 6 months. Oleyl alcohol (OA), combined with either dimethyl isosorbide (DMI) or diethylene glycol monoethyl ether (DGME) provided the highest permeation in 24 h in vitro, which was significantly higher than the marketed product (p < 0.01). OA + DGME significantly outperformed OA ex vivo (p < 0.05). The computer predictions, in vitro and ex vivo penetration results correlated well. FFE was a fast, valuable and reliable tool for aiding in topical product design for ibuprofen.

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OBJECTIVE: To develop a digital breast tomosynthesis (DBT) imaging system with optimizes imaging chain. METHODS: Based on 3D tomography and DBT imaging scanning, we analyzed the methods for projection data correction, geometric correction, projection enhancement, filter modulation, and image reconstruction, and established a hardware testing platform. In the experiment, the standard ACR phantom and high-resolution phantom were used to evaluate the system stability and noise level. The patient projection data of commercial equipment was used to test the effect of the imaging algorithm. RESULTS: In the high-resolution phantom study, the line pairs were clear without confusing artifacts in the images reconstructed with the geometric correction parameters. In ACR phantom study, the calcified foci, cysts, and fibrous structures were more clearly defined in the reconstructed images after filtering and modulation. The patient data study showed a high contrast between tissues, and the lesions were more clearly displayed in the reconstructed image. CONCLUSIONS: This DBT imaging system can be used for mammary tomography with an image quality comparable to that of commercial DBT systems to facilitate imaging diagnosis of breast diseases.

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