The Role of Phonological Awareness and Phonetic Radical Awareness in Acquiring Chinese Literacy Skills in Learners of Chinese as a Second Language

There is much research into the roles of phonological awareness and phonetic radical awareness in the development of Chinese character reading and writing skills in native-speaking children, but there is comparatively little work on the relationship between such metalinguistic skills and character literacy skills in adult learners of Chinese a second language (CSL). In this study, we explored this issue with 83 Arabic and English CSL learners who had studied Chinese in their home country. Their knowledge of phonological awareness, phonetic radical awareness, and Chinese character reading and writing was measured. There were two main findings. Firstly, the learners’ phonological awareness, but not their phonetic radical awareness, predicted the acquisition of character reading and writing skills directly or indirectly. Secondly, phonetic radical awareness did not mediate the effect of phonological awareness on character reading and writing skills. The results point to the different roles that phonological awareness and phonetic radical awareness play in the development of character literacy skills, and the still unclear relationship between phonological awareness and phonetic radical awareness. These findings are important for understanding the contribution of phonological awareness and phonetic radical awareness to the acquisition of character literacy skills for CSL learners

Hot spot prediction in protein-protein interactions by an ensemble system

© 2018 The Author(s). Background: Hot spot residues are functional sites in protein interaction interfaces. The identification of hot spot residues is time-consuming and laborious using experimental methods. In order to address the issue, many computational methods have been developed to predict hot spot residues. Moreover, most prediction methods are based on structural features, sequence characteristics, and/or other protein features. Results: This paper proposed an ensemble learning method to predict hot spot residues that only uses sequence features and the relative accessible surface area of amino acid sequences. In this work, a novel feature selection technique was developed, an auto-correlation function combined with a sliding window technique was applied to obtain the characteristics of amino acid residues in protein sequence, and an ensemble classifier with SVM and KNN base classifiers was built to achieve the best classification performance. Conclusion: The experimental results showed that our model yields the highest F1 score of 0.92 and an MCC value of 0.87 on ASEdb dataset. Compared with other machine learning methods, our model achieves a big improvement in hot spot prediction. Availability:http://deeplearner.ahu.edu.cn/web/HotspotEL.htm

KG-Hub-building and exchanging biological knowledge graphs.

MOTIVATION: Knowledge graphs (KGs) are a powerful approach for integrating heterogeneous data and making inferences in biology and many other domains, but a coherent solution for constructing, exchanging, and facilitating the downstream use of KGs is lacking. RESULTS: Here we present KG-Hub, a platform that enables standardized construction, exchange, and reuse of KGs. Features include a simple, modular extract-transform-load pattern for producing graphs compliant with Biolink Model (a high-level data model for standardizing biological data), easy integration of any OBO (Open Biological and Biomedical Ontologies) ontology, cached downloads of upstream data sources, versioned and automatically updated builds with stable URLs, web-browsable storage of KG artifacts on cloud infrastructure, and easy reuse of transformed subgraphs across projects. Current KG-Hub projects span use cases including COVID-19 research, drug repurposing, microbial-environmental interactions, and rare disease research. KG-Hub is equipped with tooling to easily analyze and manipulate KGs. KG-Hub is also tightly integrated with graph machine learning (ML) tools which allow automated graph ML, including node embeddings and training of models for link prediction and node classification. AVAILABILITY AND IMPLEMENTATION: https://kghub.org

Genotypic and phenotypic heterogeneity in Streptococcus mutans isolated from diabetic patients in Rome, Italy

Our study focuses on the antimicrobial susceptibility, genotypic and phenotypic heterogeneity, and serotype classification of the Streptococcus mutans isolated from type II diabetic patients (n = 25; age 42-68). Eighty-two percent of isolates were classified as serotype c. No serotype k was present. Macrorestriction analysis of genomic DNA of the isolates exhibited a clonal diversity that paralleled the phenotypic heterogeneity, which was also assessed in terms of biofilm forming ability. Isolates were susceptible to all the classes of antibiotics. In conclusion a great heterogeneity and no antimicrobial resistance were apparent in the considered S. mutans strains from diabetic patients

The Monarch Initiative in 2024: an analytic platform integrating phenotypes, genes and diseases across species.

Bridging the gap between genetic variations, environmental determinants, and phenotypic outcomes is critical for supporting clinical diagnosis and understanding mechanisms of diseases. It requires integrating open data at a global scale. The Monarch Initiative advances these goals by developing open ontologies, semantic data models, and knowledge graphs for translational research. The Monarch App is an integrated platform combining data about genes, phenotypes, and diseases across species. Monarch\u27s APIs enable access to carefully curated datasets and advanced analysis tools that support the understanding and diagnosis of disease for diverse applications such as variant prioritization, deep phenotyping, and patient profile-matching. We have migrated our system into a scalable, cloud-based infrastructure; simplified Monarch\u27s data ingestion and knowledge graph integration systems; enhanced data mapping and integration standards; and developed a new user interface with novel search and graph navigation features. Furthermore, we advanced Monarch\u27s analytic tools by developing a customized plugin for OpenAI\u27s ChatGPT to increase the reliability of its responses about phenotypic data, allowing us to interrogate the knowledge in the Monarch graph using state-of-the-art Large Language Models. The resources of the Monarch Initiative can be found at monarchinitiative.org and its corresponding code repository at github.com/monarch-initiative/monarch-app

SpxA1 Involved in Hydrogen Peroxide Production, Stress Tolerance and Endocarditis Virulence in Streptococcus sanguinis

Streptococcus sanguinis is one of the most common agents of infective endocarditis. Spx proteins are a group of global regulators that negatively or positively control global transcription initiation. In this study, we characterized the spxA1 gene in S. sanguinis SK36. The spxA1 null mutant displayed opaque colony morphology, reduced hydrogen peroxide (H2O2) production, and reduced antagonistic activity against Streptococcus mutans UA159 relative to the wild type strain. The ΔspxA1 mutant also demonstrated decreased tolerance to high temperature, acidic and oxidative stresses. Further analysis revealed that ΔspxA1 also exhibited a ∼5-fold reduction in competitiveness in an animal model of endocarditis. Microarray studies indicated that expression of several oxidative stress genes was downregulated in the ΔspxA1 mutant. The expression of spxB and nox was significantly decreased in the ΔspxA1 mutant compared with the wild type. These results indicate that spxA1 plays a major role in H2O2 production, stress tolerance and endocarditis virulence in S. sanguinis SK36. The second spx gene, spxA2, was also found in S. sanguinis SK36. The spxA2 null mutant was found to be defective for growth under normal conditions and showed sensitivity to high temperature, acidic and oxidative stresses

Oral Health in Women During Preconception and Pregnancy: Implications for Birth Outcomes and Infant Oral Health

The mouth is an obvious portal of entry to the body, and oral health reflects and influences general health and well being. Maternal oral health has significant implications for birth outcomes and infant oral health. Maternal periodontal disease, that is, a chronic infection of the gingiva and supporting tooth structures, has been associated with preterm birth, development of preeclampsia, and delivery of a small-for-gestational age infant. Maternal oral flora is transmitted to the newborn infant, and increased cariogenic flora in the mother predisposes the infant to the development of caries. It is intriguing to consider preconception, pregnancy, or intrapartum treatment of oral health conditions as a mechanism to improve women's oral and general health, pregnancy outcomes, and their children's dental health. However, given the relationship between oral health and general health, oral health care should be a goal in its own right for all individuals. Regardless of the potential for improved oral health to improve pregnancy outcomes, public policies that support comprehensive dental services for vulnerable women of childbearing age should be expanded so that their own oral and general health is safeguarded and their children's risk of caries is reduced. Oral health promotion should include education of women and their health care providers ways to prevent oral disease from occurring, and referral for dental services when disease is present

Early childhood caries in preschool children of Kosovo - a serious public health problem

<p>Abstract</p> <p>Background</p> <p>Even though it has been widely studied, early childhood caries (ECC) remains a serious public health problem, especially in countries where there is no national program of oral health assessment and no genuine primary oral health care, such as in Kosovo. The purpose of this study was to assess the prevalence of ECC and analyze caries risk factors.</p> <p>Methods</p> <p>The subjects were 1,008 preschool children, selected by stratified random cluster sampling, in the municipality of Prishtina, capital of Kosovo. Data were collected through clinical examination and interviews. Dmft data were recorded according to WHO criteria. Bacterial examination (CRT bacteria test) and plaque test of Greene-Vermillion were used.</p> <p>Results</p> <p>The mean dmft of preschool children was found to be 5.8. The prevalence of ECC was 17.36%, with a mean dmft of 11 ± 3.6. Streptococcus mutans prevalence in ECC children was 98%. A significant correlation between dmft and S mutans counts (≥10⁵CFU/mL saliva) was demonstrated. A correlation was also found between daily sweets consumption and dmft in children with ECC (<it>P </it>< 0.001). Comparing the dmft of ECC children and duration of bottle feeding showed a statistical correlation (<it>P </it>< 0.001). The mean plaque test was 1.52. None of the examined children had ever used fluoride.</p> <p>Conclusion</p> <p>The prevalence of ECC was high among preschool children in the municipality of Kosovo. We recommend increasing parents' knowledge of proper feeding habits and oral health practices, and increasing preschool children's accessibility to dental services.</p

Early Childhood Caries among a Bedouin community residing in the eastern outskirts of Jerusalem

<p>Abstract</p> <p>Background</p> <p>ECC is commonly prevalent among underprivileged populations. The Jahalin Bedouin are a severely deprived, previously nomadic tribe, dwelling on the eastern outskirts of Jerusalem. The aim of this study was to assess ECC prevalence and potentially associated variables.</p> <p>Methods</p> <p>102 children aged 12–36 months were visually examined for caries, mothers' anterior dentition was visually subjectively appraised, demographic and health behavior data were collected by interview.</p> <p>Results</p> <p>Among children, 17.6% demonstrated ECC, among mothers, 37.3% revealed "fairly bad" anterior teeth. Among children drinking bottles there was about twice the level of ECC (20.3%) than those breast-fed (13.2%). ECC was found only among children aged more than one year (p < 0.001); more prevalent ECC (55.6%) was found among large (10–13 children) families than among smaller families (1–5 children: 13.5%, 6–9 children: 15.6%) (p = 0.009); ECC was more prevalent among children of less educated mothers (p = 0.037); ECC was more prevalent among mothers with "fairly poor" anterior dentition (p = 0.04). Oral hygiene practices were poor.</p> <p>Conclusion</p> <p>ECC levels in this community were not very high but neither low. This changing population might be on the verge of a wider dental disease "epidemic". Public health efforts clearly need to be invested towards the oral health and general welfare of this community.</p