Fecal microbiome shifts by different forms of copper supplementations in growing pigs

( Minji Kim ),( Jae Hyoung Cho ),( Pil-nam Seong ),( Hyunjung Jung ),( Jin Young Jeong ),( Sheena Kim ),( Hyeri Kim ),( Eun Sol Kim ),( Gi Beom Keum ),( Robin B. Guevarra ),( Hyeun Bum Kim ) 한국축산학회 2021 한국축산학회지 Vol.63 No.6

Copper is an essential mineral for pigs, thus it is used as a feed additive in the forms of copper sulfate. Therefore, this study aimed at characterizing the fecal microbiota shifts in pigs as fed by different forms of copper supplementation. 40 growing pigs aged 73 ± 1 days with an average weight of 30.22 ± 1.92kg were randomly divided into 5 groups. The control group (CON) fed with basal diet, while treatment groups were fed a basal diet supplemented with 100 ppm/kg of copper sulfate (CuSO₄), Cu-glycine complex (CuGly), Cu-amino acid complex (CuAA), and Cu-hydroxy(4methylthio)butanoate chelate complex (CuHMB) for 28 days of trial, respectively. The data presented the comparison between inorganic and organic copper supplementation through gut microbiota in growing pigs. Alpha and Beta diversity anaylsis resulted in copper supplementation did shifted gut microbioal community structure. At the phylum level, Firmicutes and Bacteroidetes were the most abundant phyla at all times regardless of treatment. At the genus level, the relative abundances of Prevotella, Lactobacillus, Megasphaera, and SMB53 of the CuGly and CuHMB groups were significantly higher than those of copper sulfate and basal diet groups. Overall, this study may provide the potential role of organic copper replacing inorganic copper, resulting in increased beneficial bacteria in the pig gut.

Role of Probiotics in Human Gut Microbiome-Associated Diseases

( Seon-kyun Kim ),( Robin B. Guevarra ),( You-tae Kim ),( Joongi Kwon ),( Hyeri Kim ),( Jae Hyoung Cho ),( Hyeun Bum Kim ),( Ju-hoon Lee ) 한국미생물생명공학회(구 한국산업미생물학회) 2019 Journal of microbiology and biotechnology Vol.29 No.9

Probiotics, including bacteria and yeast, are live microorganisms that have demonstrated beneficial effects on human health. Recently, probiotic bacteria are constantly being studied and their applications are also being considered in promising adjuvant treatments for various intestinal diseases. Clinical trials and in vivo experiments have extended our current understanding of the important roles that probiotics play in human gut microbiome-associated diseases. It has been documented through many clinical trials that probiotics could shape the intestinal microbiota leading to potential control of multiple bowel diseases and promotion of overall wellness. In this review, we focused on the relationship between probiotics and the human gut microbiota and its roles in gut microbiome-associated diseases. Here, we also discuss future directions and research areas that need further elucidation in order to better understand the roles of probiotics in the treatment of intestinal diseases.

System identification of an in-service railroad bridge using wireless smart sensors

Kim, Robin E.,Moreu, Fernando,Spencer, Billie F. Techno-Press 2015 Smart Structures and Systems, An International Jou Vol.15 No.3

Railroad bridges form an integral part of railway infrastructure throughout the world. To accommodate increased axel loads, train speeds, and greater volumes of freight traffic, in the presence of changing structural conditions, the load carrying capacity and serviceability of existing bridges must be assessed. One way is through system identification of in-service railroad bridges. To dates, numerous researchers have reported system identification studies with a large portion of their applications being highway bridges. Moreover, most of those models are calibrated at global level, while only a few studies applications have used globally and locally calibrated model. To reach the global and local calibration, both ambient vibration tests and controlled tests need to be performed. Thus, an approach for system identification of a railroad bridge that can be used to assess the bridge in global and local sense is needed. This study presents system identification of a railroad bridge using free vibration data. Wireless smart sensors are employed and provided a portable way to collect data that is then used to determine bridge frequencies and mode shapes. Subsequently, a calibrated finite element model of the bridge provides global and local information of the bridge. The ability of the model to simulate local responses is validated by comparing predicted and measured strain in one of the diagonal members of the truss. This research demonstrates the potential of using measured field data to perform model calibration in a simple and practical manner that will lead to better understanding the state of railroad bridges.

Synchronized sensing for wireless monitoring of large structures

Robin E. Kim,Jian Li,Billie F. Spencer, Jr,Tomonori Nagayama,Kirill A. Mechitov 국제구조공학회 2016 Smart Structures and Systems, An International Jou Vol.18 No.5

Advances in low-cost wireless sensing have made instrumentation of large civil infrastructure systems with dense arrays of wireless sensors possible. A critical issue with regard to effective use of the information harvested from these sensors is synchronized sensing. Although a number of synchronization methods have been developed, most provide only clock synchronization. Synchronized sensing requires not only clock synchronization among wireless nodes, but also synchronization of the data. Existing synchronization protocols are generally limited to networks of modest size in which all sensor nodes are within a limited distance from a central base station. The scale of civil infrastructure is often too large to be covered by a single wireless sensor network. Multiple independent networks have been installed, and post-facto synchronization schemes have been developed and applied with some success. In this paper, we present a new approach to achieving synchronized sensing among multiple networks using the Pulse-Per-Second signals from low-cost GPS receivers. The method is implemented and verified on the Imote2 sensor platform using TinyOS to achieve 50 us synchronization accuracy of the measured data for multiple networks. These results demonstrate that the proposed approach is highly-scalable, realizing precise synchronized sensing that is necessary for effective structural health monitoring.

Meta-Review of Protein Network Regulating Obesity Between Validated Obesity Candidate Genes in the White Adipose Tissue of High-Fat Diet-Induced Obese C57BL/6J Mice

Kim, Eunjung,Kim, Eun Jung,Seo, Seung-Won,Hur, Cheol-Goo,McGregor, Robin A,Choi, Myung-Sook Taylor Francis 2014 Critical reviews in food science and nutrition Vol.54 No.7

Physical interpretation of concrete crack images from feature estimation and classification

Robin Eunju Kim,Eunbyul Koh,Seung-Seop Jin 국제구조공학회 2022 Smart Structures and Systems, An International Jou Vol.30 No.4

Detecting cracks on a concrete structure is crucial for structural maintenance, a crack being an indicator of possible damage. Conventional crack detection methods which include visual inspection and non-destructive equipment, are typically limited to a small region and require time-consuming processes. Recently, to reduce the human intervention in the inspections, various researchers have sought computer vision-based crack analyses: One class is filter-based methods, which effectively transforms the image to detect crack edges. The other class is using deep-learning algorithms. For example, convolutional neural networks have shown high precision in identifying cracks in an image. However, when the objective is to classify not only the existence of crack but also the types of cracks, only a few studies have been reported, limiting their practical use. Thus, the presented study develops an image processing procedure that detects cracks and classifies crack types; whether the image contains a crazing-type, single crack, or multiple cracks. The properties and steps in the algorithm have been developed using field-obtained images. Subsequently, the algorithm is validated from additional 227 images obtained from an open database. For test datasets, the proposed algorithm showed accuracy of 92.8% in average. In summary, the developed algorithm can precisely classify crazing-type images, while some single crack images may misclassify into multiple cracks, yielding conservative results. As a result, the successful results of the presented study show potentials of using vision-based technologies for providing crack information with reduced human intervention.

Association of a c.1084A>G (p.Thr362Ala)Variant in the DCTN4 Gene with Wilson Disease

Robin Dong-Woo Lee,Jae-Jung Kim,Joo-Hyun Kim,Jong-Keuk Lee,Han-Wook Yoo 대한의학유전학회 2011 대한의학유전학회지 Vol.8 No.1

목적: 윌슨병은 간조직에 구리의 과도한 침착으로 발병하는 상염색체 열성 유전질환이다. 지금까지 ATP7B 유전자가 유일한 원인유전자로 알려져 왔다. 그러나, 약 15%의 환자에서는 ATP7B 유전자 돌연변이가 발견되지 않는다. 본 연구는 ATP7B 유전자의 돌연변이가 발견되지 않은 윌슨병 환자를 대상으로 새로운 원인 유전자를 발견하기 위하여 시행되었다. 대상 및 방법: ATP7B 돌연변이가 발견되지 않은 12명의 윌슨병 환자를 대상으로 ATP7B 와 상호작용을 하는 것으로 알려진 ATOX1, COMMD1, GLRX, DCTN4와 ZBTB16 유전자의 전사부위와 엑손-인트론 경계부위의 염기서열을 분석하였다. 결과: DCTN4 유전자의 12번 엑손에 존재하는 c.1084A>G(p.Thr362Ala)를 포함하는 3가지의 변이가 환자에서 발견되었다. in silico 분석을 통해 3가지 변이 중 c.1084A>G가 유일하게 단백질 기능 변화를 일으킬 것으로 예측되었다. 176명의 윌슨병 환자와 414명의 정상인을 대상으로 이 변이의 빈도를 조사한 결과, 정상인보다 윌슨병 환자에서 더 높은 빈도를 나타내었다(상대비, odds ratio [OR]=3.14, 95% 신뢰도=1.36-7.22, P=0.0094). 결론: 본 연구의 결과는 ATP7B 와 상호작용하는 DCTN4 유전자의 c.1084A>G (p.Thr362Ala) 다형성이 윌슨병의 발병과 연관이 있음을 시사한다. Purpose: Wilson disease is an autosomal recessive disorder which causes excessive copper accumulation in the hepatic region. So far, ATP7B gene is the only disease-causing gene of Wilson disease known to date. However, ATP7B mutations have not been found in ~15% of the patients. This study was performed to identify any causative gene in Wilson disease patients without an ATP7B mutation in either allele. Materials and Methods: The sequence of the coding regions and exon-intron boundaries of the five ATP7B-interacting genes, ATOX1, COMMD1, GLRX, DCTN4, and ZBTB16, were analyzed in the 12 patients with Wilson disease. Results: Three nonsynonymous variants including c.1084A>G (p.Thr362Ala) in the exon 12 of the DCTN4 gene were identified in the patients examined. Among these, only p.Thr362Ala was predicted as possibly damaging protein function by in silico analysis. Examination of allele frequency of c.1084A>G (p.Thr362Ala) variant in the 176 patients with Wilson disease and in the 414 normal subjects revealed that the variant was more prevalent in the Wilson disease patients (odds ratio [OR]=3.14, 95% confidence interval=1.36-7.22, P =0.0094). Conclusion: Our result suggests that c.1084A>G (p.Thr362Ala) in the ATP7B-interacting DCTN4 gene may be associated with the pathogenesis of Wilson disease.

T-cell responses to versican in ankylosing spondylitis

Kim, Tae-Jong,Kim, Tae-Hwan,Lee, Hyun-Joo,Lee, Bitnara,Robin Poole, A.,Inman, Robert D. Springer-Verlag 2011 Rheumatology International Vol.31 No.2

System identification of an in-service railroad bridge using wireless smart sensors

Robin E. Kim,Fernando Moreu,Billie F. Spencer, Jr 국제구조공학회 2015 Smart Structures and Systems, An International Jou Vol.15 No.3

Railroad bridges form an integral part of railway infrastructure throughout the world. Toaccommodate increased axel loads, train speeds, and greater volumes of freight traffic, in the presence ofchanging structural conditions, the load carrying capacity and serviceability of existing bridges must beassessed. One way is through system identification of in-service railroad bridges. To dates, numerousresearchers have reported system identification studies with a large portion of their applications beinghighway bridges. Moreover, most of those models are calibrated at global level, while only a few studiesapplications have used globally and locally calibrated model. To reach the global and local calibration, bothambient vibration tests and controlled tests need to be performed. Thus, an approach for systemidentification of a railroad bridge that can be used to assess the bridge in global and local sense is needed. This study presents system identification of a railroad bridge using free vibration data. Wireless smartsensors are employed and provided a portable way to collect data that is then used to determine bridgefrequencies and mode shapes. Subsequently, a calibrated finite element model of the bridge provides globaland local information of the bridge. The ability of the model to simulate local responses is validated bycomparing predicted and measured strain in one of the diagonal members of the truss. This researchdemonstrates the potential of using measured field data to perform model calibration in a simple andpractical manner that will lead to better understanding the state of railroad bridges.

Analysis of Microbiota in Bellflower Root, Platycodon grandiflorum, Obtained from South Korea

( Daeho Kim ),( Sanghyun Hong ),( Hongjun Na ),( Jihwan Chun ),( Robin B. Guevarra ),( You-tae Kim ),( Sangryeol Ryu ),( Hyeun Bum Kim ),( Ju-hoon Lee ) 한국미생물생명공학회(구 한국산업미생물학회) 2018 Journal of microbiology and biotechnology Vol.28 No.4

Bellflower root (Platycodon grandiflorum), which belongs to the Campanulaceae family, is a perennial grass that grows naturally in Korea, northeastern China, and Japan. Bellflower is widely consumed as both food and medicine owing to its high nutritional value and potential therapeutic effects. Since foodborne disease outbreaks often come from vegetables, understanding the public health risk of microorganisms on fresh vegetables is pivotal to predict and prevent foodborne disease outbreaks. We investigated the microbial communities on the bellflower root (n = 10). 16S rRNA gene amplicon sequencing targeting the V6-V9 regions of 16S rRNA genes was conducted via the 454-Titanium platform. The sequence quality was checked and phylogenetic assessments were performed using the RDP classifier implemented in QIIME with a bootstrap cutoff of 80%. Principal coordinate analysis was performed using the weighted Fast UniFrac distance. The average number of sequence reads generated per sample was 67,192 sequences. At the phylum level, bacterial communities from the bellflower root were composed primarily of Proteobacteria, Firmicutes, and Actinobacteria in March and September samples. Genera Serratia, Pseudomonas, and Pantoea comprised more than 54% of the total bellflower root bacteria. Principal coordinate analysis plots demonstrated that the microbial community of bellflower root in March samples was different from those in September samples. Potential pathogenic genera, such as Pantoea, were detected in bellflower root samples. Even though further studies will be required to determine if these species are associated with foodborne illness, our results indicate that the 16S rRNA gene-based sequencing approach can be used to detect pathogenic bacteria on fresh vegetables.