In this study, the practical accuracy (PA) of optical facial scanners for facial deformity patients in oral clinic was evaluated. Ten patients with a variety of facial deformities from oral clinical ...were included in the study. For each patient, a three-dimensional (3D) face model was acquired, via a high-accuracy industrial "line-laser" scanner (Faro), as the reference model and two test models were obtained, via a "stereophotography" (3dMD) and a "structured light" facial scanner (FaceScan) separately. Registration based on the iterative closest point (ICP) algorithm was executed to overlap the test models to reference models, and "3D error" as a new measurement indicator calculated by reverse engineering software (Geomagic Studio) was used to evaluate the 3D global and partial (upper, middle, and lower parts of face) PA of each facial scanner. The respective 3D accuracy of stereophotography and structured light facial scanners obtained for facial deformities was 0.58±0.11 mm and 0.57±0.07 mm. The 3D accuracy of different facial partitions was inconsistent; the middle face had the best performance. Although the PA of two facial scanners was lower than their nominal accuracy (NA), they all met the requirement for oral clinic use.
There is an urgent need for vaccines against coronavirus disease 2019 (COVID-19) because of the ongoing SARS-CoV-2 pandemic. Among all approaches, a messenger RNA (mRNA)-based vaccine has emerged as ...a rapid and versatile platform to quickly respond to this challenge. Here, we developed a lipid nanoparticle-encapsulated mRNA (mRNA-LNP) encoding the receptor binding domain (RBD) of SARS-CoV-2 as a vaccine candidate (called ARCoV). Intramuscular immunization of ARCoV mRNA-LNP elicited robust neutralizing antibodies against SARS-CoV-2 as well as a Th1-biased cellular response in mice and non-human primates. Two doses of ARCoV immunization in mice conferred complete protection against the challenge of a SARS-CoV-2 mouse-adapted strain. Additionally, ARCoV is manufactured as a liquid formulation and can be stored at room temperature for at least 1 week. ARCoV is currently being evaluated in phase 1 clinical trials.
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•Development of LNP-encapsulated mRNA vaccine (ARCoV) targeting the RBD of SARS-CoV-2•ARCoV induces neutralizing antibodies and T cell immunity in mice and NHPs•ARCoV vaccination confers full protection against SARS-CoV-2 challenge in mice•ARCoV is a thermostable vaccine candidate for phase I studies
ARCoV is an LNP-encapsulated mRNA vaccine platform that is highly immunogenic and safe in mice and non-human primates, conferring protection against challenge with a SARS-CoV-2 mouse-adapted strain.
Many infections and stress signals can rapidly activate the NLRP3 inflammasome to elicit robust inflammatory responses. This activation requires a priming step, which is thought to be mainly for ...upregulating NLRP3 transcription. However, recent studies report that the NLRP3 inflammasome can be activated independently of transcription, suggesting that the priming process has unknown essential regulatory steps. Here, we report that JNK1-mediated NLRP3 phosphorylation at S194 is a critical priming event and is essential for NLRP3 inflammasome activation. We show that NLRP3 inflammasome activation is disrupted in NLRP3-S194A knockin mice. JNK1-mediated NLRP3 S194 phosphorylation is critical for NLRP3 deubiquitination and facilitates its self-association and the subsequent inflammasome assembly. Importantly, we demonstrate that blocking S194 phosphorylation prevents NLRP3 inflammasome activation in cryopyrin-associated periodic syndromes (CAPS). Thus, our study reveals a key priming molecular event that is a prerequisite for NLRP3 inflammasome activation. Inhibiting NLRP3 phosphorylation could be an effective treatment for NLRP3-related diseases.
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•Phosphorylation of NLRP3 at S194 is a key priming event for inflammasome activation•JNK1 directly phosphorylates NLRP3•S194 phosphorylation facilitates the self-association of NLRP3•Inhibiting NLRP3 phosphorylation could be a treatment for NLRP3-related diseases
The NLRP3 inflammasome activation requires a priming process; however, the mechanism remains obscure. Song et al. demonstrate that JNK1-mediated NLRP3 phosphorylation is a key molecular priming event that poises NLRP3 for its self-association and inflammasome assembly. This study suggests that inhibiting NLRP3 phosphorylation could be utilized in treating NLRP3-related diseases.
Single-atom catalysts (SACs) have attracted considerable attention in the catalysis community. However, fabricating intrinsically stable SACs on traditional supports (N-doped carbon, metal oxides, ...etc.) remains a formidable challenge, especially under high-temperature conditions. Here, we report a novel entropy-driven strategy to stabilize Pd single-atom on the high-entropy fluorite oxides (CeZrHfTiLa)O
(HEFO) as the support by a combination of mechanical milling with calcination at 900 °C. Characterization results reveal that single Pd atoms are incorporated into HEFO (Pd
@HEFO) sublattice by forming stable Pd-O-M bonds (M = Ce/Zr/La). Compared to the traditional support stabilized catalysts such as Pd@CeO
, Pd
@HEFO affords the improved reducibility of lattice oxygen and the existence of stable Pd-O-M species, thus exhibiting not only higher low-temperature CO oxidation activity but also outstanding resistance to thermal and hydrothermal degradation. This work therefore exemplifies the superiority of high-entropy materials for the preparation of SACs.
The presence of DNA in the cytoplasm is normally a sign of microbial infections and is quickly detected by cyclic GMP-AMP synthase (cGAS) to elicit anti-infection immune responses. However, chronic ...activation of cGAS by self-DNA leads to severe autoimmune diseases for which no effective treatment is available yet. Here we report that acetylation inhibits cGAS activation and that the enforced acetylation of cGAS by aspirin robustly suppresses self-DNA-induced autoimmunity. We find that cGAS acetylation on either Lys384, Lys394, or Lys414 contributes to keeping cGAS inactive. cGAS is deacetylated in response to DNA challenges. Importantly, we show that aspirin can directly acetylate cGAS and efficiently inhibit cGAS-mediated immune responses. Finally, we demonstrate that aspirin can effectively suppress self-DNA-induced autoimmunity in Aicardi-Goutières syndrome (AGS) patient cells and in an AGS mouse model. Thus, our study reveals that acetylation contributes to cGAS activity regulation and provides a potential therapy for treating DNA-mediated autoimmune diseases.
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•Acetylation suppresses cGAS activity•Aspirin directly acetylates cGAS•Aspirin inhibits cGAS-mediated interferon production•Aspirin alleviates DNA-induced autoimmunity in AGS mouse models and patient cells
Activation of the DNA sensor cGAS requires a deacetylation step, and its aspirin-induced acetylation can limit innate immune responses.
One of the major challenges of solving Big Data optimization problems via traditional multi-objective evolutionary algorithms (MOEAs) is their high computational costs. This issue has been ...efficiently tackled by non-dominated sorting genetic algorithm, the third version, (NSGA-III). On the other hand, a concern about the NSGA-III algorithm is that it uses a fixed rate for mutation operator. To cope with this issue, this study introduces an adaptive mutation operator to enhance the performance of the standard NSGA-III algorithm. The proposed adaptive mutation operator strategy is evaluated using three crossover operators of NSGA-III including simulated binary crossover (SBX), uniform crossover (UC) and single point crossover (SI). Subsequently, three improved NSGA-III algorithms (NSGA-III SBXAM, NSGA-III SIAM, and NSGA-III UCAM) are developed. These enhanced algorithms are then implemented to solve a number of Big Data optimization problems. Experimental results indicate that NSGA-III with UC and adaptive mutation operator outperforms the other NSGA-III algorithms.
•An adaptive mutation operator is introduced to enhance the performance of NSGA-III.•The proposed adaptive mutation operator strategy is evaluated on three crossover operators of NSGA-III.•Three improved NSGA-III algorithms are developed.•The proposed NSGA-III algorithms are implemented to solve an array of Big Data optimization problems.
Abstract
For any storage ring-based large-scale scientific facility, one of the most important performance parameters is the dynamic aperture (DA), which measures the motion stability of charged ...particles in a global manner. To date, long-term tracking-based simulation is regarded as the most reliable method to calculate DA. However, numerical tracking may become a significant issue, especially when a plethora of candidate designs of a storage ring need to be evaluated. In this paper, we present a novel machine learning-based method, which can reduce the computation cost of DA tracking by approximately one order of magnitude, while keeping sufficiently high evaluation accuracy. Moreover, we demonstrate that this method is independent of concrete physical models of a storage ring. This method has the potential to be applied to similar problems of identifying irregular motions in other complex dynamical systems.
•The performance of three crossover operators of NSGA-III algorithm on big data optimization problems are investigated.•By introducing the concept of Stud, several improved crossover operators of ...SBX, UC, and SI have been designed.•Ten variants of NSGA-III algorithms are proposed.•The performance of ten NSGA-III variants are further verified on big data optimization problems.
Traditional multi-objective optimization evolutionary algorithms (MOEAs) do not usually meet the requirements for online data processing because of their high computational costs. This drawback has resulted in difficulties in the deployment of MOEAs for multi-objective, large-scale optimization problems. Among different evolutionary algorithms, non-dominated sorting genetic algorithm-the third version (NSGA-III) is a fairly new method capable of solving large-scale optimization problems with acceptable computational requirements. In this paper, the performance of three crossover operators of the NSGA-III algorithm is benchmarked using a large-scale optimization problem based on human electroencephalogram (EEG) signal processing. The studied operators are simulated binary (SBX), uniform crossover (UC), and single point (SI) crossovers. Furthermore, enhanced versions of the NSGA-III algorithm are proposed through introducing the concept of Stud and designing several improved crossover operators of SBX, UC, and SI. The performance of the proposed NSGA-III variants is verified on six large-scale optimization problems. Experimental results indicate that the NSGA-III methods with UC and UC-Stud (UCS) outperform the other developed variants.
This study presents a robust optimization algorithm based on hybridization of krill herd (KH) and artificial bee colony (ABC) methods and the information exchange concept. The global optimal ...solutions found by the proposed hybrid KH and ABC (KHABC) algorithm are considered as a neighbor food source for onlooker bees in ABC. Thereafter, a local search is performed by the onlooker bees in order to find a better solution around the given neighbor food source. Both the methods—the KH and ABC—share the globally best solutions through the information exchange process between the krill and bees. Based on the results, the exchange process significantly improves exploration and exploitation of the hybrid method. Besides, a focused elitism scheme is introduced to enhance the performance of the developed algorithm. The validity of the KHABC method is verified using thirteen unconstrained benchmark functions, twenty-one CEC 2017 constrained real-parameter optimization problems, and ten CEC 2011 real world problems. The proposed method clearly demonstrates its ability to be a competitive optimization tool towards solving benchmark functions and real world problems.
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