Q Chen A / Y Wang (@5.5) vs M Kawamura / F Kozaki (@1.12)
10-09-2019

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M Kawamura / F Kozaki will win
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Q Chen A / Y Wang – M Kawamura / F Kozaki Match Prediction | 10-09-2019 02:30

Bioactives such as polyphenols and isoflavones found naturally in our food are increasingly being recognised as regulators of interest. We carried out a literature review wherein we assessed the impact of three dietary compounds, namely butyrate, genistein and quercetin, on miRNA expression followed by an in silico study utilising DIANA-miRPathv3 software. These compounds can regulate cancer pathways through microRNAs which are critical in modulating expression of various genes. Diet plays a major role in regulating cancer. The in silico analysis identified key pathways of interest such as bladder cancer which had significant interactions with the miRNAs modulated by the dietary compounds. Our literature search found that miR-34a, miR-200a-3p and miR-200b-3p were modulated by all three compounds while miR-221, miR-222, miR-29a, miR-3935 and miR-574-3p were modulated by both genistein and butyrate and let-7b, miR-194, miR-96-5p and miR-424 were modulated by butyrate and quercetin.

Chuang, T.-I. 27. Jia, J. Paik and J.A. Braun, Y.G. Fan, Y.W. Kang, C. Zhang, H.Y. Stretchable Batteries with Self-Similar Serpentine Interconnects and Integrated Wireless Recharging Systems [pdf] [demovideo] S. Su, J. Zhang, J. Huang, U. Xu, Y.H. Petrov, P.V. Su, H.G. Lee, X. Huang, L. Yu, C. Cheng, B.W. Dagdeviren, I. Shigeta, S. Cho, J.H. Kim, T. Song, K. Lu, C.J.

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We aimed to effectively evaluate the strength of evidence from the available literature regarding the usefulness of dietary bioactives whilst, simultaneously demonstrating the features of the DIANA software and its ability to synergistically strengthen data from the literature. To conclude, dietary bioactives modulate miRNA which in turn have effects on cancer development and progression. Rather than seeking a needle in a haystack, we liken the use of DIANA software together with Tarbase, as dramatically reducing the size of the miRNA pool to be investigated, to something more manageable from a logistical and financial point of view. Such evidence sourced from experimentally supported interactions as seen in Tarbase v7.0, implies that we can be relatively confident, keeping the limitations in mind, that the information provided can be applied in the laboratory to investigate diet-miRNA interactions in the context of cancers.

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The data presented in Table 1 were used to create a Venn diagram shown in Figure 1. Interestingly, there were no miRNAs modulated only by genistein and quercetin. Based on the quantity of literature found, data on butyrate and genistein was abundant while studies using quercetin were few. The literature search results were as follows: nine miRNAs modulated by two bioactives and three that were modulated by all three (as seen in the centre of the Venn diagram (Figure 1) indicated by the overlapping, darker blue regions). Most of the modulated miRNAs were only modulated by a specific bioactive while others were modulated by more than one.

Yan, X. Xu, M. Xie, A. Liu, J.W. Feng, S. Battery-free, Stretchable Optoelectronic Systems for Wireless Optical Characterization of the Skin [pdf]J. Sheng, Y.H. Zimmerman, J. Fabiani, G. Heo, K.Y. 42. Kim, L.Q. Jang, S.Y. Salvatore, H. Kim, G.A. Araki, A.M. Huang, U. Luo, B. Gratton, Y.G. Cho, H.Y. Banks, X. Chiarelli, Z.Q. Paik and J.A. Lee, K.-I.

Ultimately DIANA software is reliant on the strength of the data within the database upon which it utilises. When lists have to be broken up, they are seen as separate entities and this restricts the ability to form large networks of miRNA relationships and interactions. The modulation of miR-34a by quercetin demonstrates an important point, namely that bioactives may in reality modulate miRNAs differently in different tissues. The strength of this programme is in the prediction and visualisation of networks between various miRNA and relevant pathways. It is not clear how DIANA software utilises contradictory information. If different tissues result in different activities of miRNA, we cannot assume that the assumption the software makes of this miRNA truly captures the nature of its activity. This restricts the possibility of large miRNA studies as they have to be broken up into smaller sets. Interestingly, Sun et al. The effects of down-regulation or up-regulation of certain miRNA as seen in our literature review is not taken into consideration by the algorithm and thus the effects of this cannot be presented. Hu et al. (2009) found that quercetin both up-regulated and down-regulated miR-34a 26. Firstly, there is a limit of 100miRNAs that can be input at any one time. Although there are many trengths associated with the programme, there were several factors which vastly limited its applicability. Secondly, the software is limited in the information that it can provide. (2013) found that genistein had antagonist effects, up-regulating its expression 25. This is important as our review found that different bioactives had antagonistic effects on miR-34a. While its algorithms can show the degree of significance of interaction between a miRNA and a pathway, this is where it is limited too. (2011) found that butyrate down-regulated the expression of miR-34a 17 while Hirata et al.

Both these options allow for the user to tailor and specify the miRNAs for investigation when looking into different pathways. The details option in the DIANA software allows the user to see which miRNAs were predicted to have statistical significance with each pathway. The results from the DIANA software revealed our miRNA lists had statistically significant interactions with pathways such as fatty acid biosynthesis and fatty acid metabolism. The software also predicted other more specific pathways of interest such as prostate cancer, colorectal cancer, bladder cancer and many others. Such results mutually strengthen both the evidence from literature of dietary modulated miRNAs and also the accuracy of prediction. This reduces the time needed to find miRNAs of interest. prostate cancer and generates a list of statistically significant miRNA interactions from the Tarbase v7.0 database. Other pathways such as proteoglycans in cancer and miRNAs in cancer consistently ranked among the most statistically significant pathways (Table 2 - Table 4). Furthermore, a reverse search option allows the user to input a pathway of interest, i.e. Interestingly, such pathways, which may seem irrelevant, have been shown in several studies to over-activate in cancers, causing increased energy uptake and metabolism whilst promoting clinically aggressive behaviour in tumours, tumour cell-growth and survival 68, 69, 70, 71, 72. Usually vast assays of miRNAs are assessed in order to see which have been altered, however the software does this for the researcher and thus decreases the need for time and resources for such assays. However, the software brings to light the need for further exploration under the lens of miRNA. While we focussed on cancer, other physiological pathways of interest could follow a similar model. When we consider the implications of this software, one of its strengths is in its vast database of experimentally supported interactions.

The aims of conducting this in silico study were to effectively evaluate the strength of evidence for miRNA modulation by dietary bioactives. However, despite this knowledge, we are still only scratching the surface with respect to understanding how miRNAs are regulated, how they act individually and synergistically to modulate gene expression and in finding novel therapeutic treatments that are effective in regulating miRNA. There is no doubt from the plethora of evidence that miRNAs play a crucial role in cancer development.

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Li, S.H. Zhou, Y. Chen, Y.S. Sternini, Q.F. Lee, Z.L. Zhang, N.H. Teng, W.B. Zhou, M. 49.Stretchable Ultrasonic Transducer Arrays for Three-dimensional Imaging on Complex Surfaces [pdf]H.J. Guo, Y. Wang, L. Kim, Y.X. Wang, Y. Huang, R.M. Li, A. Gu, Y.M. Chen, Z.Y. Pharr, F. Zhu, C.H. Hu, X. Nomoto, S. Zhang, X.S. Lei, T.J. Chen, C.F. Lanza di Scalea and S.

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