• Journal of Applied Biological Chemistry
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• 제65권1호
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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.

• Tuberculosis and Respiratory Diseases
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• 제80권3호
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• pp.255-264
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• 2017

Background:N-acetyl transferase (NAT) inactivates the pro-drug isoniazid (INH) to N-acetyl INH through a process of acetylation, and confers low-level resistance to INH in Mycobacterium tuberculosis (MTB). Similar to NAT of MTB, NAT2 in humans performs the same function of acetylation. Rapid acetylators, may not respond to INH treatment efficiently, and could be a potential risk factor, for the development of INH resistance in humans. Methods: To understand the contribution of NAT of MTB and NAT2 of humans in developing INH resistance using in silico approaches, in this study, the wild type (WT) and mutant (MT)-NATs of MTB, and humans, were modeled and docked, with substrates and product (acetyl CoA, INH, and acetyl INH). The MT models were built, using templates 4BGF of MTB, and 2PFR of humans. Results: On the basis of docking results of MTB-NAT, it can be suggested that in comparison to the WT, binding affinity of MT-G207R, was found to be lower with acetyl CoA, and higher with acetyl-INH and INH. In case of MT-NAT2 from humans, the pattern of score with respect to acetyl CoA and acetyl-INH, was similar to MT-NAT of MTB, but revealed a decrease in INH score. Conclusion: In MTB, MT-NAT revealed high affinity towards acetyl-INH, which can be interpreted as increased formation of acetyl-INH, and therefore, may lead to INH resistance through inactivation of INH. Similarly, in MT-NAT2 (rapid acetylators), acetylation occurs rapidly, serving as a possible risk factor for developing INH resistance in humans.

• KSII Transactions on Internet and Information Systems (TIIS)
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• 제18권4호
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• pp.826-842
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• 2024

As 5G and AI continue to develop, there has been a significant surge in the healthcare industry. The COVID-19 pandemic has posed immense challenges to the global health system. This study proposes an FL-supported edge computing model based on federated learning (FL) for predicting clinical outcomes of COVID-19 patients during hospitalization. The model aims to address the challenges posed by the pandemic, such as the need for sophisticated predictive models, privacy concerns, and the non-IID nature of COVID-19 data. The model utilizes the FATE framework, known for its privacy-preserving technologies, to enhance predictive precision while ensuring data privacy and effectively managing data heterogeneity. The model's ability to generalize across diverse datasets and its adaptability in real-world clinical settings are highlighted by the use of SHAP values, which streamline the training process by identifying influential features, thus reducing computational overhead without compromising predictive precision. The study demonstrates that the proposed model achieves comparable precision to specific machine learning models when dataset sizes are identical and surpasses traditional models when larger training data volumes are employed. The model's performance is further improved when trained on datasets from diverse nodes, leading to superior generalization and overall performance, especially in scenarios with insufficient node features. The integration of FL with edge computing contributes significantly to the reliable prediction of COVID-19 patient outcomes with greater privacy. The research contributes to healthcare technology by providing a practical solution for early intervention and personalized treatment plans, leading to improved patient outcomes and efficient resource allocation during public health crises.

• Genomics & Informatics
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• 제18권2호
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• pp.20.1-20.4
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• 2020

Accessible negative results are relevant for researchers and clinicians not only to limit their search space but also to prevent the costly re-exploration of research hypotheses. However, most biomedical relation extraction datasets do not seek to distinguish between a false and a negative relation among two biomedical entities. Furthermore, datasets created using distant supervision techniques also have some false negative relations that constitute undocumented/ unknown relations (missing from a knowledge base). We propose to improve the distinction between these concepts, by revising a subset of the relations marked as false on the phenotype-gene relations corpus and give the first steps to automatically distinguish between the false (F), negative (N), and unknown (U) results. Our work resulted in a sample of 127 manually annotated FNU relations and a weighted-F1 of 0.5609 for their automatic distinction. This work was developed during the 6th Biomedical Linked Annotation Hackathon (BLAH6).

• Genomics & Informatics
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• 제7권2호
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• pp.53-56
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• 2009

Recent evidence has strongly suggested that the CAP/TC10 pathway is involved in the trafficking, docking, and fusion of vesicles containing the insulin-responsive glucose transporter Glut4 to the plasma membrane. However, little is known about how the genes employed in the CAP/TC10 pathway are associated with the development of type 2 diabetes mellitus. In this study, we sequenced 4 genes of the CAP/TC10 pathway [SORBS1, CBL, CRK, and RHOQ] in 24 individuals to identify genetic variations in these loci. A total of 48 sequence variants were identified, including 23 novel variations. To investigate the possible association with type 2 diabetes mellitus, 3 single nucleotide polymorphisms from SORBS1, 3 from CBL, and 4 from RHOQ were genotyped in 1122 Korean type 2 diabetic patients and 1138 nondiabetic controls. Using logistic regression analysis, 1 significant association between SNP rs1376405 in RHOQ and type 2 diabetes mellitus [OR = 8.714 (C.I. 1.714-44.29), p = 0.009] was found in the recessive model. Our data demonstrate a positive association of the RHOQ gene in the CAP/TC10 pathway with T2DM in the Korean population.

• Genomics & Informatics
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• 제13권4호
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• pp.119-125
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• 2015

RNA is a polymeric molecule implicated in various biological processes, such as the coding, decoding, regulation, and expression of genes. Numerous studies have examined RNA features using whole transcriptome sequencing (RNA-seq) approaches. RNA-seq is a powerful technique for characterizing and quantifying the transcriptome and accelerates the development of bioinformatics software. In this review, we introduce routine RNA-seq workflow together with related software, focusing particularly on transcriptome reconstruction and expression quantification.

• Journal of Ginseng Research
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• 제41권1호
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• pp.1-9
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• 2017

Panax ginseng Meyer, belonging to the genus Panax of the family Araliaceae, is known for its human immune system-related effects, such as immune-boosting effects. Ginseng polysaccharides (GPs) are the responsible ingredient of ginseng in immunomodulation, and are classified as acidic and neutral GPs. Although GPs participate in various immune reactions including the stimulation of immune cells and production of cytokines, the precise function of GPs together with its potential receptor(s) and their signal transduction pathways have remained largely unknown. Animal lectins are carbohydrate-binding proteins that are highly specific for sugar moieties. Among many different biological functions in vivo, animal lectins especially play important roles in the immune system by recognizing carbohydrates that are found exclusively on pathogens or that are inaccessible on host cells. This review summarizes the immunological activities of GPs and the diverse roles of animal lectins in the immune system, suggesting the possibility of animal lectins as the potential receptor candidates of GPs and giving insights into the development of GPs as therapeutic biomaterials for many immunological diseases.

• Genomics & Informatics
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• 제19권3호
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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).

• Genomics & Informatics
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• 제11권4호
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• pp.200-210
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• 2013

Studying biological networks, such as protein-protein interactions, is key to understanding complex biological activities. Various types of large-scale biological datasets have been collected and analyzed with high-throughput technologies, including DNA microarray, next-generation sequencing, and the two-hybrid screening system, for this purpose. In this review, we focus on network-based approaches that help in understanding biological systems and identifying biological functions. Accordingly, this paper covers two major topics in network biology: reconstruction of gene regulatory networks and network-based applications, including protein function prediction, disease gene prioritization, and network-based genome-wide association study.

• Journal of Microbiology and Biotechnology
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• 제12권6호
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• pp.1022-1025
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• 2002

Club root is one of the major diseases that occur in crucifers. It is caused by Plasmodiophora brassicae. In order to discover microbial biopesticides against P. brassicae, forty-eight Streptomyces isolated from soil were screened. Among these, three strains showed excellent pesticidal activities. We report results on in vivo screening with fermentation broths of these strains and identification of the strain taxa.