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To elucidate the atomic mechanisms of the chemical mechanical polishing (CMP) of silicon carbide (SiC), molecular dynamics simulations based on a reactive force field were used to study the sliding process of silica (SiO2) abrasive particles on SiC substrates in an aqueous H2O2 solution. During the CMP process, the formation of Si-O-Si interfacial bridge bonds and the insertion of O atoms at the surface can lead to the breakage of Si-C bonds and even the complete removal of SiC atoms. Furthermore, the removal of C atoms is more difficult than the removal of Si atoms. It is found that the removal of Si atoms largely influences the removal of C atoms. The removal of Si atoms can destroy the lattice structure of the substrate surface, leading the neighboring C atoms to be bumped or even completely removed. Our research shows that the material removal during SiC CMP is a comprehensive result of different atomic-level removal mechanisms, where the formation of Si-O-Si interfacial bridge bonds is widespread throughout the SiC polishing process. The Si-O-Si interfacial bridge bonds are the main removal mechanisms for SiC atoms. This study provides a new idea for improving the SiC removal process and studying the mechanism during CMP.

Background: Children affected by severe early childhood caries (S‐ECC) usually need comprehensive caries treatment due to the extensive of caries. How the oral microbiome changes after caries therapy within the short‐term warrant further study. Aim: This study aimed to investigate the short‐term impact of comprehensive caries treatment on the supragingival plaque microbiome of S‐ECC children. Design: Thirty‐three children aged 2–4 years with severe caries (dt > 7) were recruited. Comprehensive caries treatment was performed under general anesthesia in one session and included restoration, pulp treatment, extraction, and fluoride application. Supragingival plaque was sampled pre‐ and 1‐month posttreatment. The genomic DNA of the supragingival plaque was extracted, and bacterial 16S ribosomal RNA gene sequencing was performed. Results: Our data showed that the microbial community evenness significantly decreased posttreatment. Furthermore, comprehensive caries treatment led to more diverse microbial structures among the subjects. The interbacterial interactions reflected by the microbial community's co‐occurrence network tended to be less complex posttreatment. Caries treatment increased the relative abundance of Corynebacterium matruchotii, Corynebacterium durum, Actinomyces naeslundii, and Saccharibacteria HMT‐347, as well as Aggregatibacter HMT‐458 and Haemophilus influenzae. Meanwhile, the relative abundance of Streptococcus mutans, three species from Leptotrichia, Neisseria bacilliformis, and Provotella pallens significantly decreased posttreatment. Conclusion: Our results suggested that comprehensive caries treatment may contribute to the reconstruction of a healthier supragingival microbiome. [ABSTRACT FROM AUTHOR]

Urbanization and industrialization have escalated air pollution into a critical global issue, particularly in urban areas. Urban green infrastructures (GIs), such as parks and street trees, play a vital role in mitigating air pollution through dry deposition, the process by which air pollutants are removed by deposition onto plant surfaces or through plant uptake. However, existing studies on the dry-deposition capacity of urban green spaces are limited in their ability to reflect variations at the tree-species level, hindering comprehensive evaluations and effective management strategies. This study aims to quantitatively assess the dry-deposition capacity of the urban green spaces of Beijing and Shanghai for six major air pollutants in using an improved dry-deposition model and tree-species-specific data. Results showed that Shanghai's urban green spaces had a monthly average dry-deposition rate of 5.5 × 10−6 s m−1, slightly higher than Beijing's rate of 5.3 × 10−6 s m−1. Significant seasonal variations were observed, with summer showing the highest deposition rates due to favorable meteorological conditions. Broad-leaved species such as Zelkova serrata in Beijing and Photinia serratifolia in Shanghai exhibited superior dry-deposition capacities compared to coniferous species. Temperature significantly influenced dry-deposition rates for gaseous pollutants, while particulate-matter deposition was primarily affected by pollutant concentrations. This study provides critical insights into the air = purification functions of urban green spaces and underscores the importance of species selection and strategic green-space planning in urban air-quality management, informing the development of optimized urban-greening strategies for improved air quality and public health. [ABSTRACT FROM AUTHOR]

Aims and Objectives: This study aimed to investigate the current status of the core competencies and self‐directed learning ability of diabetes specialist nurses and to explore the relationship between these core competencies and their self‐directed learning ability. Design: A cross‐sectional survey design was used. Methods: This cross‐sectional study was conducted via a web‐based questionnaire platform in China from January 14 to April 24, 2023. The survey included a general information questionnaire, a diabetes specialist nurses' core competencies self‐assessment scale, and a nursing staff's self‐directed learning ability evaluation scale. The data was collected online. Descriptive, correlation and multiple linear regression analyses were conducted using SPSS 26.0 software. Results: 118 diabetes specialist nurses from 11 cities participated in this study. A positive correlation was observed between the core competencies of diabetes specialist nurses and their self‐directed learning ability. The characteristics affecting the core competencies of diabetes specialist nurses included age, participation in external learning and communication and self‐directed learning. Conclusions: The training of diabetes specialist nurses can focus on core competencies, and the ability to self‐direct learning can be used as an entry point to customize feasible theoretical and practical courses. The training system can further improve diabetes specialist nurses' core competencies and self‐directed learning abilities. Relevance to Clinical Practice: A reference can be established that nursing managers and nursing educators can use to develop training programs for specialist nurses by validating the link between their core competencies and self‐directed learning skills. Patient or Public Contribution: Participants were involved solely in the data collection process. No participant contributions were required for the study's design, outcome measurement or implementation. [ABSTRACT FROM AUTHOR]

Purpose: By using four national data sets, this study aimed to examine the changes in U.S. children's fundamental movement skills (FMS) from 1985 to 2019. Method: Three Tests Gross of Motor Development (TGMD) normative studies, i.e. TGMD-1 (N = 909, male% = 50), TGMD-2 (N = 1143, male% = 50) and TGMD-3 (N = 864, male% = 51), and the TGMD-2 data of the 2012 NHANES National Youth Fitness Survey (NNYFS-2012; raw N = 352, national represented population = 12,509,706, male% = 51) were used for analyses. Each item in TGMD-2/NNYFS and TGMD-3 was carefully examined, and these that did not match to TGMD-1 were deleted. Cohen's D effect size (ES) was utilized for the difference among year-to-year comparisons. Result: From 1985 to 2000, FMS in US children of 3–7 years old (90% increase & 10% no change) increased temporarily, but remained stable (17% increase & 83% no change) among 8–10 years old. Between 2000 and 2019, however, U.S. children began to demonstrate a slight/stable drop in FMS among 3–5 years old (22% decrease & 78% no change), and a distinct decline among 6–10 years old (80% decrease & 20% no change). While children with normal BMI showed the highest FMS score, the direct cause of reduction in FMS is still unknown. Conclusion: An overall up-and-down change was observed in U.S. children's FMS between 1985 and 2019, and more longitudinal studies with FMS-related variables are needed. [ABSTRACT FROM AUTHOR]

Amelogenesis imperfecta (AI) represents a group of clinically and genetically heterogeneous disorders that affect enamel formation and mineralization. Although AI is commonly considered a monogenic disorder, digenic inheritance is rarely reported. In this study, we recruited two nonconsanguineous Chinese families exhibiting diverse phenotypes of enamel defects among affected family members. Digenic variants were discovered in both probands. In family 1, the proband inherited a paternal frameshift variant in LAMA3 (NM_198129.4:c.3712dup) and a maternal deletion encompassing the entire AMELX gene. This resulted in a combined hypoplastic and hypomineralized AI phenotype, which was distinct from the parents' manifestations. In family 2, whole‐exome sequencing analysis revealed the proband carried a maternal heterozygous splicing variant in COL17A1 (NC_000010.11 (NM_000494.3): c.4156 + 2dup) and compound heterozygous variants in RELT (paternal: NM_032871.4:c.260A > T; maternal: NM_032871.4:c.521 T > G). These genetic changes caused the abundant irregular enamel defects observed in the proband, whereas other affected family members carrying heterozygous variants in both COL17A1 and RELT displayed only horizontal grooves as their phenotype. The pathogenicity of the novel COL17A1 splice site variant was confirmed through RT‐PCR and minigene assay. This study enhances our understanding by highlighting the potential association between the co‐occurrence of variants in two genes and variable phenotypes observed in AI patients. [ABSTRACT FROM AUTHOR]

Abstract Amelogenesis imperfecta (AI), characterized by a deficiency in the quantity and/or quality of dental enamel, is genetically heterogeneous and phenotypically variable. The most severe type, hypocalcified AI, is mostly caused by truncating mutations in the FAM83H gene. This study aimed to identify genetic mutations in four Chinese families with hypocalcified AI. We performed mutation analysis by sequencing the candidate FAM83H gene. Three novel mutations (c.931dupC, p.V311Rfs*13; c.1130_1131delinsAA, p.S377X; and c.1147 G > T, p.E383X) and one previously reported mutation (c.973 C > T, p.R325X) in the last exon of FAM83H gene were identified. Furthermore, constructs expressing Green fluorescent protein (GFP)-tagged wild-type and three novel mutant FAM83Hs were transfected into rat dental epithelial cells (SF2 cells). Wild-type FAM83H-GFP was localized exclusively in the cytoplasm, especially in the area surrounding the nucleus, while the mutant FAM83H-GFPs (p.V311Rfs*13, p.S377X, and p.E383X) were localized predominantly in the nucleus, with lower levels in the cytoplasm.

A concrete plastic-damage model, the extended Drucker–Prager model for rockfill, and acoustic elements for water were introduced and applied to the impact fracture analysis of a concrete-faced rockfill dam–water three-dimensional system. The plastic-damage dynamic analysis process was used in combination with the concrete compressive and tensile damage model. The 223-m high Shuibuya concrete-faced rockfill dam was analyzed using an explicit integration. Numerical simulations of the damage threshold, rockfill modeling, and interface processing were conducted to research the effect of the anti-explosion performance that occurs when a concrete slab is subjected to an underwater shock wave. The simulation results indicate that the main regions of weakness in the slabs during an underwater shock wave are determined by the tensile damage. The slab’s anti-knock weak areas appear in the right dam abutment and the top of the left dam. The anti-knock performance in the upper slab is inferior to that of the lower slab. Specific local optimization steps should be applied at these locations to improve the slabs’ anti-knock capabilities, which are important for designing concrete-faced rockfill dams.

Objectives: To investigate the detailed ultrastructural patterns of dental abnormalities affected by Axenfeld‐Rieger syndrome (ARS) with a heterozygous microdeletion involving paired‐like homeodomain 2 (PITX2) and explored the underlying molecular mechanisms driving enamel defects. Subjects and methods: Sanger sequencing, genomic quantitative PCR analysis, and chromosomal microarray analysis (CMA) were used to screen the disease‐causing mutation in one ARS proband. An exfoliated tooth from an ARS patient was analyzed with scanning electron microscopy and micro–computerized tomography. A stable Pitx2 knockdown cell line was generated to simulate PITX2 haploinsufficiency. Cell proliferation and ameloblast differentiation were analyzed, and the role of the Wnt/β‐catenin pathway in proliferation of ameloblast precursor cells was investigated. Results: An approximately 0.216 Mb novel deletion encompassing PITX2 was identified. The affected tooth displayed a thinner and broken layer of enamel and abnormal enamel biomineralization. PITX2 downregulation inhibited the proliferation and differentiation of inner enamel epithelial cells, and LiCl stifmulation partially reversed the proliferation ability after Pitx2 knockdown. Conclusions: Enamel formation is disturbed in some patients with ARS. Pitx2 knockdown can influence the proliferation and ameloblast differentiation of inner enamel epithelial cells, and PITX2 may regulate cell proliferation via Wnt/β‐catenin signaling pathway. [ABSTRACT FROM AUTHOR]

Most existing image deblurring methods are based on the estimation of blur kernels and end-to-end learning of the mapping relationship between blurred and sharp images. However, since different real-world blurred images typically have completely different blurring patterns, the performance of these methods in real image deblurring tasks is limited without explicitly modeling blurring as degradation representations. In this paper, we propose IDR 2 ENet , which is the Implicit Degradation Representations and Reblur Estimation Network, for real image deblurring. IDR 2 ENet consists of a degradation estimation process, a reblurring process, and a deblurring process. The degradation estimation process takes the real blurred image as input and outputs the implicit degradation representations estimated on it, which are used as the inputs of both reblurring and deblurring processes to better estimate the features of the blurred image. The experimental results show that whether compared with traditional or deep-learning-based deblurring algorithms, IDR 2 ENet achieves stable and efficient deblurring results on real blurred images. [ABSTRACT FROM AUTHOR]