• Title/Summary/Keyword: community informatics

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Mucin modifies microbial composition and improves metabolic functional potential of a synthetic gut microbial ecosystem

  • Mabwi, Humphrey A.;Komba, Erick V.G.;Mwaikono, Kilaza Samson;Hitayezu, Emmanuel;Mauliasari, Intan Rizki;Jin, Jong Beom;Pan, Cheol-Ho;Cha, Kwang Hyun
    • Journal of Applied Biological Chemistry
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    • v.65 no.1
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    • pp.63-74
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    • 2022
  • Microbial dysbiosis in the gut is associated with human diseases, and variations in mucus alter gut microbiota. Therefore, we explored the effects of mucin on the gut microbiota using a community of 19 synthetic gut microbial species. Cultivation of these species in modified Gifu anaerobic medium (GAM) supplemented with mucin before synthetic community assembly facilitated substantial growth of the Bacteroides, Akkermansia, and Clostridium genera. The results of 16S rRNA microbial relative abundance profiling revealed more of the beneficial microbes Collinsella, Bifidobacterium, Ruminococcus, and Lactobacillus. This increased acetate levels in the community cultivated with, rather than without (control), mucin. We identified differences in predicted cell function and metabolism between microbes cultivated in GAM with and without mucin. Mucin not only changed the composition of the gut microbial community, but also modulated metabolic functions, indicating that it could help to modulate microbial changes associated with human diseases.

Nursing Informatics Competencies of Public Health Nurses in Chungcheongnam-do (충청남도 보건소 간호사의 간호정보역량 실태)

  • Kim, Hyun;Kim, Miyoung
    • Research in Community and Public Health Nursing
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    • v.24 no.1
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    • pp.20-28
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    • 2013
  • Purpose: The aim of the study was to identify nursing informatics competencies of nurses working for public health centers in Chungcheongnam-do. Methods: Data were collected from June 10 to July 25, 2012 using the Nursing Informatics Competencies Questionnaire (NICQ). Data were analyzed by descriptive statistics, t-test, $x^2$-test, ANOVA and Pearson's correlation coefficient. Results: Nursing informatics competencies of the subjects showed a mean score of $3.3{\pm}1.0$ out of 5. As for scores of individual categories, the score for computer skills competencies was $3.3{\pm}1.0$, informatics knowledge competencies $3.4{\pm}0.9$, and informatics skills competencies $3.0{\pm}0.9$. Nursing informatics competencies were positively correlated with the subjects' ages (r=.65, p<.001), computer usage hours (r=.23, p = .015), levels of demand for informatics knowledge (r=.51, p<.001), and informatics skills education (r=.78, p<.001). Conclusion: Nursing informatics is required to be connected with job training or in-service education on account of its growing necessity for public health nurses. It is also essential to develop programs for strengthening informatics competencies reflecting sub-categories of educational needs.

Understanding the Use of Community Informatics: A Structural Equation Modeling Approach (지역정보 시스템 이용모형 개발을 위한 이론적 고찰 및 실증적 연구)

  • 권나현
    • Journal of the Korean Society for information Management
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    • v.21 no.2
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    • pp.23-44
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    • 2004
  • This study proposed a theoretical framework that could explain the service use of a community informatics. The proposed community informatics use model was developed based on three theoretical models: (1) Ajzen's Theory of Planned Behavior (TPB) from social psychology: (2) Uses and gratifications approaches from media use research; and (3) Technology Acceptance Model(TAM) from information technology use research. The proposed model consists of three basic components: expectations of the outcomes from use, approvals from important others, and perceivied controllability over using the service. The initially proposed model was assessed using structural equation modeling, and then re-sepcified in order to propose a better fitting model. The initially proposed and revised community informatics use models were discussed with their theoretical and practical implications.

Perspectives on Clinical Informatics: Integrating Large-Scale Clinical, Genomic, and Health Information for Clinical Care

  • Choi, In Young;Kim, Tae-Min;Kim, Myung Shin;Mun, Seong K.;Chung, Yeun-Jun
    • Genomics & Informatics
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    • v.11 no.4
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    • pp.186-190
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    • 2013
  • The advances in electronic medical records (EMRs) and bioinformatics (BI) represent two significant trends in healthcare. The widespread adoption of EMR systems and the completion of the Human Genome Project developed the technologies for data acquisition, analysis, and visualization in two different domains. The massive amount of data from both clinical and biology domains is expected to provide personalized, preventive, and predictive healthcare services in the near future. The integrated use of EMR and BI data needs to consider four key informatics areas: data modeling, analytics, standardization, and privacy. Bioclinical data warehouses integrating heterogeneous patient-related clinical or omics data should be considered. The representative standardization effort by the Clinical Bioinformatics Ontology (CBO) aims to provide uniquely identified concepts to include molecular pathology terminologies. Since individual genome data are easily used to predict current and future health status, different safeguards to ensure confidentiality should be considered. In this paper, we focused on the informatics aspects of integrating the EMR community and BI community by identifying opportunities, challenges, and approaches to provide the best possible care service for our patients and the population.

454 Pyrosequencing Analysis of Bacterial Diversity Revealed by a Comparative Study of Soils from Mining Subsidence and Reclamation Areas

  • Li, Yuanyuan;Chen, Longqian;Wen, Hongyu;Zhou, Tianjian;Zhang, Ting;Gao, Xiali
    • Journal of Microbiology and Biotechnology
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    • v.24 no.3
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    • pp.313-323
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    • 2014
  • Significant alteration in the microbial community can occur across reclamation areas suffering subsidence from mining. A reclamation site undergoing fertilization practices and an adjacent coal-excavated subsidence site (sites A and B, respectively) were examined to characterize the bacterial diversity using 454 high-throughput 16S rDNA sequencing. The dominant taxonomic groups in both the sites were Proteobacteria, Acidobacteria, Bacteroidetes, Betaproteobacteria, Actinobacteria, Gammaproteobacteria, Alphaproteobacteria, Deltaproteobacteria, Chloroflexi, and Firmicutes. However, the bacterial communities' abundance, diversity, and composition differed significantly between the sites. Site A presented higher bacterial diversity and more complex community structures than site B. The majority of sequences related to Proteobacteria, Gemmatimonadetes, Chloroflexi, Nitrospirae, Firmicutes, Betaproteobacteria, Deltaproteobacteria, and Anaerolineae were from site A; whereas those related to Actinobacteria, Planctomycetes, Bacteroidetes, Verrucomicrobia, Gammaproteobacteria, Nitriliruptoria, Alphaproteobacteria, and Phycisphaerae originated from site B. The distribution of some bacterial groups and subgroups in the two sites correlated with soil properties and vegetation due to reclamation practice. Site A exhibited enriched bacterial community, soil organic matter (SOM), and total nitrogen (TN), suggesting the presence of relatively diverse microorganisms. SOM and TN were important factors shaping the underlying microbial communities. Furthermore, the specific plant functional group (legumes) was also an important factor influencing soil microbial community composition. Thus, the effectiveness of 454 pyrosequencing in analyzing soil bacterial diversity was validated and an association between land ecological system restoration, mostly mediated by microbial communities, and an improvement in soil properties in coal-mining reclamation areas was suggested.

Developing a Smart Phone Application for the OMAHA System Guidelines (오마하 시스템 가이드라인의 스마트폰 애플리케이션 개발)

  • Hong, Hae-Sook;Lee, In-Keun;Hong, Sung-Jung;Kim, Hwa-Sun
    • Research in Community and Public Health Nursing
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    • v.21 no.4
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    • pp.512-521
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    • 2010
  • Purpose: The remarkable progress in information and communication technology has had a great effect on the healthcare delivery system. The development of smart phone applications is a new field. The aim of our research was to provide assistance in developing smart phone applications for community health nursing. Methods: Based on an informative approach, this study developed persona and site maps, followed by a storyboard as a way of analyzing users' requirements and designing responses in the context of smart phone application development methodology. Results: We developed persona, user interface and database design successfully, and then seven nurses selected four nursing problems (income, residence, pain, and digestion hydration). The search time in seconds for the 2005 English OMAHA guidelines to find three nursing interventions for these problems was used to evaluate the effectiveness of the smart phone application. The results showed that smart phone applications' search was 21 times faster on the average than book guidelines. Conclusion: An English version of the OMAHA system application was developed for the Android smart phone market. It is hoped that smart phone applications such as this will be used internationally for nursing education.

CONTINUOUS-TIME MARKOV MODEL FOR GERIATRIC PATIENTS BEHAVIOR. OPTIMIZATION OF T도 BED OCCUPANCY AND COMPUTER SIMULATION

  • Gorunescu, Marina;Gorunescu, Florin;Prodan, Augustin
    • Journal of applied mathematics & informatics
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    • v.9 no.1
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    • pp.185-195
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    • 2002
  • Previous research has shown that the flow of patients around departments of geriatric medicine and ex-patients in the community may be-modelled by the application of a mixed-exponential distribution. In this proper we considered a ave-compartment model using a continuous-time Markov process to describe the flow of patients. Using a M/ph/c queuing model, we present a way of optimizing the number of beds in order to maintain an acceptable delay probability a sufficiently low level. Finally, we constructed a Java computer simulation, using data from St George's Hospital, London.

A review of drug knowledge discovery using BioNLP and tensor or matrix decomposition

  • Gachloo, Mina;Wang, Yuxing;Xia, Jingbo
    • Genomics & Informatics
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    • v.17 no.2
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    • pp.18.1-18.10
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    • 2019
  • Prediction of the relations among drug and other molecular or social entities is the main knowledge discovery pattern for the purpose of drug-related knowledge discovery. Computational approaches have combined the information from different sources and levels for drug-related knowledge discovery, which provides a sophisticated comprehension of the relationship among drugs, targets, diseases, and targeted genes, at the molecular level, or relationships among drugs, usage, side effect, safety, and user preference, at a social level. In this research, previous work from the BioNLP community and matrix or matrix decomposition was reviewed, compared, and concluded, and eventually, the BioNLP open-shared task was introduced as a promising case study representing this area.

COVID-19 recommender system based on an annotated multilingual corpus

  • Barros, Marcia;Ruas, Pedro;Sousa, Diana;Bangash, Ali Haider;Couto, Francisco M.
    • Genomics & Informatics
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    • v.19 no.3
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    • pp.24.1-24.7
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    • 2021
  • Tracking the most recent advances in Coronavirus disease 2019 (COVID-19)-related research is essential, given the disease's novelty and its impact on society. However, with the publication pace speeding up, researchers and clinicians require automatic approaches to keep up with the incoming information regarding this disease. A solution to this problem requires the development of text mining pipelines; the efficiency of which strongly depends on the availability of curated corpora. However, there is a lack of COVID-19-related corpora, even more, if considering other languages besides English. This project's main contribution was the annotation of a multilingual parallel corpus and the generation of a recommendation dataset (EN-PT and EN-ES) regarding relevant entities, their relations, and recommendation, providing this resource to the community to improve the text mining research on COVID-19-related literature. This work was developed during the 7th Biomedical Linked Annotation Hackathon (BLAH7).