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Culture Medium Profiling and Design Assisted by Machine Learning
Massaki KONISHI 한국생물공학회 2021 한국생물공학회 학술대회 Vol.2021 No.10
Production media for microbial cultivation is a significant factor to perform efficient cell growth and production. In industrial fermentation processes, raw materials including yeast, malt, and meat extracts, peptone, molasses, and the other agricultural and industrial waste are often used. The compositions can be varied in seasonal and geological varieties, brands, and production-lots, and influence microbial growth and material production. To understand the varieties of medium components, we have suggested that an analytical method assisted by metabolomics-like finger printing using gas-chromatogram mass spectrometry (Tachibana et al. 2019), and by deep neural networks (DNN) architecture (Tachibana et al. 2021) can apply to culture medium profiling. In the study, it was analyzed as a typical microbial cultivation that various brands of yeast extract were influenced to Escherichia coli growth and green fluorescent protein (GFP), a model of foreign protein production. According to our procedure, the bacterial growth and protein production was accurately estimated from the initial medium components profiles measured by GC-MS. Furthermore, significant components were estimated by a permutation algorithm using DNN model. The results indicated that the initial medium components can sufficiently explain the cultivation results including growth and protein production. As well, bioethanol production can be explained by the composition of toxic materials in lignocellulosic hydrolysates (Watanabe et al. 2019; Konishi 2020). To design optimal culture medium for engineered E. coli producing GFP, L81 Latin square design with 3 levels was applied to minimal medium M9 with supplemental components including amino acids and vitamins. To compare suitable machine learning algorithms for estimating GFP production, 12 algorithms, linear regression (LR), Ridge regression (Ridge), Lasso regression (Lasso), support vector machine (SVM), partial least square regression (PLS), decision tree regression (dtree), random forest regression (RFR), neural networks (NN), deep neural networks (DNN), Gradient tree boosting regression (gbr), K neighbor regression (kbr), and voting regression (vtr) were applied. According to evaluate the algorithms by cross validation (supervised: 85% and validation: 15%), although mean square errors between measured and estimated values of test data (MSEtest) were approximately 1.0-1.5 in case of LR, Ridge, Lasso, SVM, and PLS, those of dtree, RFR, gbr, NN, and DNN were in range below 0.06. On the other hand, considering interaction terms of independent variables, the data accurately fit to the all tested algorithms. The MSEtest were in range between 0.03 and 0.07. The results meant that interaction among medium components were strongly influenced to GFP production. Gaussian process optimization using trained DNN model as objective function were applied to exploring the optimal medium composition for GFP production. Based on the experimental confirmation, the improved composition increased GFP fluorescence to 117% against the best in the original experimental dataset in fact. The machine-learning-associated optimization of culture medium can provide high-throughput explore of the optimal medium compositions for not only microbial culture but also mammalian culture in theoretically. Furthermore, the idea will contribute to promote digital transformation for wide range of bioproductions. This research was partly supported by New Energy and Industrial Technology Development Organization (NEDO) project of Ministry of Economy, Trade and Industry (METI), Japan.
< 구두-B-10 > 일본 산소동위원소연대기를 이용한 울산 반구동 유적 출토 고목재의 연대측정
최은비,김요정,( Massaki Sano ),박준희,서정욱 한국목재공학회 2018 한국목재공학회 학술발표논문집 Vol.2018 No.1
국내에서 연륜폭을 기반으로 작성된 최장 대표연륜연대기는 약 900년(1126년-현재)으로 소나무(Pinusdensiflora) 고목재와 현생목을 이용하여 구축된 것이다. 따라서 13세기 이전의 고목재 연대를 표준연륜 연대기를 활용하여 분석하는 것이 불가능한 현실이다. 이러한 이유로 13세기 이전의 고목재 연대측정은 방사성탄소동위원소 분석에 의존하고 있다. 최근 발표된 연구에 의하면 목재의 각 연륜에서 측정한 산소동위원소의 비율(δ<sup>18</sup>O)로 작성한 연대기는 연륜폭으로 작성된 연대기보다 수종 간, 개체 간 일치도가 높으며, 더 나아가 일본 북서지방의 산소동위원소연대기와도 유사한 패턴을 가진 것으로 확인되었다 (Seo et al., 2017). 본 연구는 울산 반구동에서 출토된 13세기 이전으로 추정되는 고목재의 산소동위원소비연대기를 작성하여 일본의 산소동위원소비연대기와 비교하여 정확한 연대측정이 가능한지를 확인하고자 실시되었다. 연구에 사용된 고목재는 울산 반구동 유적에서 출토된 중심목주이다. 울산 반구동 유적은 대형 목책시설로, 고대의 목책구조를 그대로 보여주고 있어 그 의미가 매우 크다. 방사성탄소동위원소 분석으로 확인된 반구동 유적에 위치한 목축조성시기는 A.D. 879±50년(신뢰구간 95.4%)이었다(정아름, 2011).
PIV measurement of oscillatory flow in a micro-channel as a bronchiole model
Won-je LEE,Massaki KAWAHASHI,Hiroyuki HIRAHARA 한국가시화정보학회 2004 KOREA-JAPAN Joint Seminar on Particle Image Veloci Vol.- No.-
The improvement of artificial respiration method has brought about the decrease in mortality of pulmonary diseases patients. Various respiratory curative methods, inclusive of HFOV (High Frequency Oscillatory Ventilation), have been developed for more effectual and less harmful management of acute respiratory failure. However, the mechanism of gas transfer and diffusion in a bronchiole has not yet been clarified in detail. As a first approach to the problem, we measured oscillatory flows in a Y-shaped micro-channels as bronchiole model by micro Particle Image Velocimetry(micro PIV). In order to establish the fundamental technique of PIV measurements on oscillatory air flow in a micro-channel, we used about 500-㎚ -diameter incense smoke particles, a diode laser, a high speed camera including an objective lens, and a HFOV, which is effective technique for medical care of pulmonary disease patients, especially, infants. The bronchiole model size is that parent tube is 500㎛ width and 500㎛ depth, and daughter tubes are 450㎛ width and 500㎛ depth. From this study made on the phenomenon of fluid in micro size bronchus branch of a lung, we succeeded to get time series velocity distribution in a micro scale bronchial mode. The experimental results of velocity distribution changing with time obtained by micro PIV can give fundamental knowledge on oscillatory airflow in micro-channel.
제주도산 넓적송장벌레(딱정벌레목: 송장벌레과)에 대한 분류학적 검토
조영복,최세웅,권용정,Massaki Nishikawa 한국동물분류학회 2004 Animal Systematics, Evolution and Diversity Vol.20 No.1
The clustering analysis and comparison of male genitalia of Silpha perforatacomplex were carried out to decide the taxonomic status of the population fromJejudo Is., Korea. One hundred and five individuals from Korea, Japan, and Chinawere examined for the present study. Based on the result, the population of JejudoIs. was treated as intraspecies of Silpha perforatawith a morphological variation.