• 한국가금학회지
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• 제48권4호
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• pp.239-253
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• 2021

본 연구는 Cobb종 및 Ross 308종 육계가 동물복지 사육환경에 따라 나타내는 대사체학적 변화를 연구하기 위하여 수행되었다. 일반농장과 동물복지농장(사육면적, 사육밀도, 암모니아 농도, 볏짚 등 제공)에 1일령의 Cobb종 및 Ross종 육계를 35일간 사육하고, 도계 후 가슴육과 다리육을 채취하여 분석에 이용하였다. 대사체 분석은 one-dimensional ¹H 핵자기공명분광법을 이용하였고, 직교부분최소자승판별분석(OPLS-DA)과 대사경로 분석을 함께 수행하였다. OPLS-DA 결과 육계 가슴육은 Ross종에 한하여 사육농장간 뚜렷한 구분이 가능하였다. 동물복지농장 유래 Ross종 육계 가슴육은 acetate, anserine, creatine, inosine monophosphate 함량이 일반농장 닭가슴육에 비해 유의적으로 높았다(P<0.05). 반면 육계 다리육은 OPLS-DA 결과 Cobb종 육계에서만 사육농장에 따른 구분이 뚜렷하게 나타났는데, glucose와 lactate를 포함한 5종의 대사체 함량은 동물복지농장에서 사육된 경우에 높았으나 7종의 유리아미노산을 포함한 9종의 대사체 함량은 낮았다(P<0.05). 대사경로 분석 결과 Ross종 육계 가슴육에서는 4종, Cobb종 육계 다리육에서는 glycolysis/gluconeogenesis를 포함한 20종의 대사경로에서 사육농장 간 유의적인 차이(P<0.05)가 나타났다. 동물복지농장에서 사육된 Ross종 육계 가슴육과 Cobb종 육계 다리육은 일반농장에서 사육된 경우와는 다른 대사체학적 특성을 나타냈으며, 특히 풍미 물질에의 뚜렷한 차이를 보여 관능적 특성에 영향을 미칠 수 있으리라 사료된다.

• Journal of Ginseng Research
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• 제38권3호
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• pp.187-193
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• 2014

Background: White ginseng (Panax ginseng Meyer) is commonly distributed as a health food in food markets. However, there is no practical method for distinguishing Korean white ginseng (KWG) from Chinese white ginseng (CWG), except for relying on the traceability system in the market. Methods: Ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry combined with orthogonal partial least squares discrimination analysis (OPLS-DA) was employed to discriminate between KWG and CWG. Results: The origins of white ginsengs in two test sets ($1.0{\mu}L$ and $0.2{\mu}L$ injections) could be successfully discriminated by the OPLS-DA analysis. From OPLS-DA S-plots, KWG exhibited tentative markers derived from ginsenoside Rf and notoginsenoside R3 isomer, whereas CWG exhibited tentative markers derived from ginsenoside Ro and chikusetsusaponin Iva. Conclusion: Results suggest that ultra-performance liquid chromatography quadrupole time-of-flight mass spectrometry coupled with OPLS-DA is an efficient tool for identifying the difference between the geographical origins of white ginsengs.

• 한국약용작물학회지
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• 제24권2호
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• pp.93-100
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• 2016

Background: A set of logical criteria that can accurately identify and verify the cultivation region of raw materials is a critical tool for the scientific management of traditional herbal medicine. Methods and Results: Volatile compounds were obtained from 19 and 32 samples of Angelica gigas Nakai cultivated in Korea and China, respectively, by using steam distillation extraction. The metabolites were identified using GC/MS by querying against the NIST reference library. Data binning was performed to normalize the number of variables used in statistical analysis. Multivariate statistical analyses, such as Principal Component Analysis (PCA), Partial Least Squares-Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares-Discriminant Analysis (OPLS-DA) were performed using the SIMCA-P software. Significant variables with a Variable Importance in the Projection (VIP) score higher than 1.0 as obtained through OPLS-DA and those that resulted in p-values less than 0.05 through one-way ANOVA were selected to verify the marker compounds. Among the 19 variables extracted, styrene, ${\alpha}$-pinene, and ${\beta}$-terpinene were selected as markers to indicate the origin of A. gigas. Conclusions: The statistical model developed was suitable for determination of the geographical origin of A. gigas. The cultivation regions of six Korean and eight Chinese A. gigas. samples were predicted using the established OPLS-DA model and it was confirmed that 13 of the 14 samples were accurately classified.

• 분석과학
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• 제29권1호
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• pp.1-9
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• 2016

생약의 원산지를 판별하는 논리적인 일련의 기준을 개발한다면, 현재 유통되는 한약을 좀 더 과학적으로 관리 할 수 있을 것이다. 이러한 노력은 전통적인 한약 산업 발전에 기여할 것이라고 사료된다. 산수유의 원산지 판별법을 개발하기 위해, 본 연구에서는 우선 국산 산수유와 중국산 산수유를 각각 수증기 증류하고 이 때 얻은 휘발성분을 GC/MS를 이용하여 분석하였다. NIST mass spectral library의 데이터베이스로부터 정성분석한 결과를 바탕으로 데이터를 범주화(binning)하여 변수를 얻고, 이에 대하여 PCA, OPLS-DA 등 다변량 통계 분석을 수행함으로써 신속, 정확하게 국산 산수유와 중국산 산수유의 산지를 판별할 수 있는 산지 판별모델을 확립하였다. 산지 판별모델 개발을 위해서 학습집합(n=53)을 분석하여 산지 판별모델을 수립한 후, 검증집합(n=12)을 산지 판별모델에 적용함으로써 그 타당성을 확인하였다. 더불어 1-ethylbutyl-hydroperoxide, nonadecane, butylated hydroxytoluene, 5β,7βH,10α-Eudesm-11-en-1α-ol, 7,9-bis (2-methyl-2-propanyl)-1-oxaspiro[4.5]deca-6,9-diene-2,8-dione, 그리고 2-decyldodecyl-benzene 등 6개의 마커성분을 선정할 수 있었다. 최근에 NMR을 활용한 산수유 원산지 판별에 대한 보고는 있었으나, GC/MS를 기반으로 한 대사체학 연구기법을 이용하여 산지판별 모델을 제시하는 것은 최초의 보고로서 그 의미가 크다. 본 연구결과를 활용하여 한약의 원산지 판별모델 확립과 산수유 원산지의 과학적인 관리에 적용할 수 있으리라 사료된다.

• Journal of the Korean Wood Science and Technology
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• 제48권5호
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• pp.591-607
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• 2020

This study was aimed to investigate the changes of chemical composition of the volatile organic compounds (VOCs) emitted from red pine needles in the process of needle abscission or senescence. The VOCs in intact, senescent, and litter red pine needle samples were analyzed by headspace-solid phase microextraction gas chromatography-mass spectrometry (HS-SPME-GC/MS). And then, multivariate statistical interpretation of the processed data sets was conducted to investigate similarities and dissimilarities of the needle samples. Principal component analysis (PCA) and orthogonal partial least squares discriminant analysis (OPLS-DA) were used to investigate the dataset structure and discrimination between samples, respectively. From the data preview, the levels of major components of VOCs from needles were not significantly different between needle samples. By PCA investigation, the data reduction according to classification based on the chlorophyll a / chlorophyll b (Ca/Cb) ratio were found to be ideal for differentiating intact, senescent, and litter needles. The following OPLS-DA taking Ca/Cb ratio as y-variables showed that needle samples were well grouped on score plot and had the significant discriminant compounds, respectively. Several compounds had significantly correlated with Ca/Cb ratio in a bivariate correlation analysis. Notably, the litter needles had a higher content of oxidized compounds than the intact needles. In summary, we found that chemical compositions of VOCs between intact, senescent, and litter needles are different each other and several compounds reflect characteristic of needle.

• Biomolecules & Therapeutics
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• 제19권1호
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• pp.38-44
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• 2011

Cisplatin is widely used for various types of cancers. However, its side effects, most notably, renal toxicity often limit its clinical utility. Although previous metabolomic studies reported possible toxicity markers, they used small number of animals and statistical approaches that may not perform best in the presence of intra-group variation. Here, we identified urinary biomarkers associated with renal toxicity induced by cisplatin using NMR-based metabolomics combined with Orthogonal Projections to Latent Structures-Discriminant Analysis (OPLS-DA). Male Sprague-Dawley rats (n=22) were treated with cisplatin (10 mg/kg single dose), and the urines obtained before and after treatment were analyzed by NMR. Multivariable analysis of NMR data presented clear separation between non-treated and treated groups. The OPLS-DA statistical results revealed that 1,3-dimethylurate, taurine, glucose, glycine and branched-chain amino acid (isoleucine, leucine and valine) were significantly elevated in the treated group and that phenylacetylglycine and sarcosine levels were decreased in the treated group. To test the robustness of the approach, we built a prediction model for the toxicity and were able to predict all the unknown samples (n=14) correctly. We believe the proposed NMR-based metabolomics with OPLS-DA approach and the resulting urine markers can be used to augment the currently available blood markers.

• 약학회지
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• 제60권1호
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• pp.29-35
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• 2016

Traditional Korean medicines may be managed more scientifically, through the development of logical criterion to verify their cultivation region. It contributes to advance the industry of traditional herbal medicines. Volatile compounds were obtained from 14 samples of domestic Taeksa and 30 samples of Chinese Taeksa by steam distillation. The metabolites were identified by NIST mass spectral library in the obtained gas chromatography/mass spectrometer (GC/MS) data of 35 training samples. The multivariate statistical analysis, such as Principal Component Analysis (PCA), Partial Least Squares Discriminant Analysis (PLS-DA), and Orthogonal Partial Least Squares Discriminant Analysis (OPLS-DA), were performed based on the qualitative and quantitative data. Finally trans-(2,3-diphenylcyclopropyl)methyl phenyl sulfoxide (47.265 min), 1,2,3,4-tetrahydro-1-phenyl-naphthalene (47.781 min), spiro[4-oxatricyclo[5.3.0.0.(2,6)]decan-3-one-5,2'-cyclohexane] (54.62 min), 6-[7-nitrobenzofurazan-4-yl]amino-morphinan-4,5-epoxy (54.86 min), p-hydroxynorephedrine (55.14 min) were determined as marker metabolites to verify candidates for the origin of Taeksa. The statistical model was well established to determine the origin of Taeksa. The cultivation areas of test samples, each 3 domestic and 6 Chinese Taeksa were predicted by the established OPLS-DA model and it was confirmed that all 9 samples were precisely classified.

• 분석과학
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• 제33권2호
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• pp.98-107
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• 2020

Methamphetamine (MA) is currently the most abused illicit drug in Korea. MA is produced by chemical synthesis, and the final target drug that is produced contains small amounts of the precursor chemicals, intermediates, and by-products. To identify and quantify these trace compounds in MA seizures, a practical and feasible approach for conducting chromatographic fingerprinting with a suite of traditional chemometric methods and recently introduced machine learning approaches was examined. This was achieved using gas chromatography (GC) coupled with a flame ionization detector (FID) and mass spectrometry (MS). Following appropriate examination of all the peaks in 71 samples, 166 impurities were selected as the characteristic components. Unsupervised (principal component analysis (PCA), hierarchical cluster analysis (HCA), and K-means clustering) and supervised (partial least squares-discriminant analysis (PLS-DA), orthogonal partial least squares-discriminant analysis (OPLS-DA), support vector machines (SVM), and deep neural network (DNN) with Keras) chemometric techniques were employed for classifying the 71 MA seizures. The results of the PCA, HCA, K-means clustering, PLS-DA, OPLS-DA, SVM, and DNN methods for quality evaluation were in good agreement. However, the tested MA seizures possessed distinct features, such as chirality, cutting agents, and boiling points. The study indicated that the established qualitative and semi-quantitative methods will be practical and useful analytical tools for characterizing trace compounds in illicit MA seizures. Moreover, they will provide a statistical basis for identifying the synthesis route, sources of supply, trafficking routes, and connections between seizures, which will support drug law enforcement agencies in their effort to eliminate organized MA crime.

• Toxicological Research
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• 제34권3호
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• pp.199-210
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• 2018

Skeletal muscle can be ultrastructurally damaged by eccentric exercise, and the damage causes metabolic disruption in muscle. This study aimed to determine changes in the metabolomic patterns in urine and metabolomic markers in muscle damage after eccentric exercise. Five men and 6 women aged 19~23 years performed 30 min of the bench step exercise at 70 steps per min at a determined step height of 110% of the lower leg length, and stepping frequency at 15 cycles per min. $^1H$ NMR spectral analysis was performed in urine collected from all participants before and after eccentric exercise-induced muscle damage conventionally determined using a visual analogue scale (VAS) and maximal voluntary contraction (MVC). Urinary metabolic profiles were built by multivariate analysis of principal component analysis (PCA) and orthogonal partial least square-discriminant analysis (OPLS-DA) using SIMCA-P. From the OPLS-DA, men and women were separated 2 hr after the eccentric exercise and the separated patterns were maintained or clarified until 96 hr after the eccentric exercise. Subsequently, urinary metabolic profiles showed distinct trajectory patterns between men and women. Finally, we found increased urinary metabolites (men: alanine, asparagine, citrate, creatine phosphate, ethanol, formate, glucose, glycine, histidine, and lactate; women: adenine) after the eccentric exercise. These results could contribute to understanding metabolic responses following eccentric exercise-induced muscle damage in humans.

• 한국자기공명학회논문지
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• 제22권4호
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• pp.149-157
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• 2018

Diabetes is known to be one of common causes for several types of peripheral nerve damage. Diabetic neuropathy (DN) is a significant complication lowering the quality of life that can be frequently found in diabetes patients. In this study, the metabolomic characteristic of DN and Diabetes was investigated with NMR spectroscopy. The sera samples were collected from DN patients, Diabetes patients, and healthy volunteers. Based on the pair-wise comparison, three metabolites were found to be noticeable: glucose, obviously, was upregulated both in DN patients (DNP) and Diabetes. Citrate is also increased in both diseases. However, the dietary nutrient and biosynthesized metabolite from glucose, ascorbate, was elevated only in DNP, compared to healthy control. The multivariate model of OPLS-DA clearly showed the group separation between healthy control-DNP and healthy control-Diabetes. The most significant metabolites that contributed the group separation included glucose, citrate, ascorbate, and lactate. Lactate did not show the statistical significance of change in t-test while it tends to down-regulated both in DNP and Diabetes. We also conducted the ROC curve analysis to make a multivariate model for discrimination of healthy control and diseases with the identified three metabolites. As a result, the discrimination model between healthy control and DNP (or Diabetes) was successful while the model between DNP and Diabetes was not satisfactory for discrimination. In addition, multiple combinations of lactate and citrate in the OPLS-DA model of healthy control and diabetes group (DNP + Diabetes patients) gave good ROC value of 0.952, which imply these two metabolites could be used for diagnosis of Diabetes without glucose information.