AIM: This case-control study investigated the effects of kimchi,soybean paste, fresh vegetables,nonfermented alliums, nonfermented seafood, nonfermented soybean foods, and the genetic polymorphisms of some metabolic e...AIM: This case-control study investigated the effects of kimchi,soybean paste, fresh vegetables,nonfermented alliums, nonfermented seafood, nonfermented soybean foods, and the genetic polymorphisms of some metabolic enzymes on the risk of gastric cancer in Koreans. METHODS: We studied 421 gastric cancer patients and 632 age- and sex-matched controls. Subjects completed a structured questionnaire regarding their food intake pattern. Polymorphisms of cytochrome P450 1A1 (CYP1A1), cytochrome P450 2E1 (CYP2E1), glutathione S-transferase mu 1 (GSTM1),glutathione S-transferase theta 1 (65777) and aldehyde dehydrogenase 2 (ALDH2) were investigated. RESULTS: A decreased risk of gastric cancer was noted among people with high consumption of nonfermented alliums and nonfermented seafood. On the other hand, consumption of kimchi, and soybean pastes was associated with increased risk of gastric cancer. Individuals with the CYP1A1 Ile/Val or Val/Val genotype showed a significantly increased risk for gastric cancer. Increased intake of kimchi or soybean pastes was a significant risk factor for the CYP1A1 lie/lie, the CYP2E1 c1/c1,the GSTM1 non-null, the GSTT1 non-null, or the ALDH2 *1/*1 genotype.In addition, eating soybean pastes was associated with the increased risk of gastric cancer in individuals with the GSTM1 null type. Nonfermented alliums were significant in individuals with the CYP1A1 lie/lie, the CYP2E1 c1/c2 or c2/c2, the GSTT1 null, the GSTT1 non-null, or the ALDH2 *1/*2 or *2/*2 genotype,nonfermented seafood was those with the CYP1A1 lie/lie,the CYP2E1 c1/c1, the ALDH2 *1/*1 genotype or any type of GSTM1 or GSTT1. In homogeneity tests, the odds ratios of eating kimchi for gastric cancer according to the GSTM1 or 65777 genotype were not homogeneous. CONCLUSION: Kimchi, soybean pastes, and the CYP1A1 Ile/Val or Val/Val are risk factors,and nonfermented seafood and alliums are protective factors against gastric cancer in Koreans. Salt or some chemicals contained in kimchi and soybean pastes, which are increased by fermentation,would play important roles in the carcinogenesis of stomach cancer.Polymorphisms of the CYP1A1, CYP2E1, GSTM1, GSTT1, and ALDH2 genes could modify the effects of some environmental factors on the risk of gastric cancer.展开更多
Soybean paste has been a prominent condiment in East Asia for millennia.Nonetheless,the current methodologies for comprehensively assessing the quality of commercially available soybean paste through sensory evaluatio...Soybean paste has been a prominent condiment in East Asia for millennia.Nonetheless,the current methodologies for comprehensively assessing the quality of commercially available soybean paste through sensory evaluation or traditional instruments present significant challenges.In this study,contemporary detection techniques and machine learning methodologies were employed to quantitatively characterize and evaluate the overall quality of soybean paste.Sensory evaluations were conducted on 33 varieties of commercial soybean paste using three types of sensors:a colorimeter,an electronic nose(E-nose),and an electronic tongue(E-tongue)for detection purposes.Subsequently,machine learning models,including support vector regression(SVR),random forest,extreme gradient boosting,Bayesian ridge regression,ridge regression,k-nearest neighbors,and artificial neural network,were developed based on the sensory evaluation data to characterize and assess the overall quality of the soybean paste.The findings from both sensory evaluations and sensor detection indicated notable differences between the various soybean pastes.Soybean pastes can be distinguished using three sensors.The quantitative characterization model informed by the sensor data revealed that the SVR model exhibited the highest coefficient of determination(R^(2))of 0.9998 for the training set and 0.9970 for the prediction set,which was close to the ideal value of 1.Additionally,the root mean square error for the prediction set was the lowest at 0.5359.These results suggest that SVR demonstrates superior performance in cross-validation and testing,aligning closely with human sensory perceptions,thereby establishing it as the most effective predictive model.This study underscores the potential of integrating sensor data with modern machine learning techniques to supplement traditional sensory evaluations for comprehensive characterization and assessment of soybean paste quality.The outcomes of this study offer significant insights and guidance for the advancement of the soybean paste industry and the enhancement of soybean paste quality.展开更多
This study aimed to investigate the changes in microbial diversity,and volatile compounds of traditional fermented soybean paste originated from Henan province of China using 16S rRNA sequencing,headspace solid phase ...This study aimed to investigate the changes in microbial diversity,and volatile compounds of traditional fermented soybean paste originated from Henan province of China using 16S rRNA sequencing,headspace solid phase microextraction-gas chromatography/mass spectrometry(HS-SPME-GC/MS),and electronic nose(E-nose).The amino acid nitrogen and reducing sugar contents ranged between 1.18 and 1.58 g/100 g and 2.29 and 3.74 mg/g,respectively.The results showed that fermented soybean paste exhibited the highest amount of glutamate and aspartate amino acids.Approximately 112 volatile compounds were detected in all SP samples comprising 10 alcohols,19 esters,10 acidic compounds,and 21 heterocyclic compounds.Furthermore,16S rRNA sequencing indicated that Enterobacter,Bacillus,Staphylococcus,and Enterococcus were the predominant bacteria in fermented soybean paste samples.Moreover,network analysis revealed that Klebsiella,Bacillus,and Lactobacillus positively correlated with H-fluorendimethyl,octenol,and benzaldehyde.These findings helped in understanding the formation of volatile flavoring compounds during SP fermentation.展开更多
基金Supported by the Korea Science and Engineering Foundation, No.2000-2-219-001-2
文摘AIM: This case-control study investigated the effects of kimchi,soybean paste, fresh vegetables,nonfermented alliums, nonfermented seafood, nonfermented soybean foods, and the genetic polymorphisms of some metabolic enzymes on the risk of gastric cancer in Koreans. METHODS: We studied 421 gastric cancer patients and 632 age- and sex-matched controls. Subjects completed a structured questionnaire regarding their food intake pattern. Polymorphisms of cytochrome P450 1A1 (CYP1A1), cytochrome P450 2E1 (CYP2E1), glutathione S-transferase mu 1 (GSTM1),glutathione S-transferase theta 1 (65777) and aldehyde dehydrogenase 2 (ALDH2) were investigated. RESULTS: A decreased risk of gastric cancer was noted among people with high consumption of nonfermented alliums and nonfermented seafood. On the other hand, consumption of kimchi, and soybean pastes was associated with increased risk of gastric cancer. Individuals with the CYP1A1 Ile/Val or Val/Val genotype showed a significantly increased risk for gastric cancer. Increased intake of kimchi or soybean pastes was a significant risk factor for the CYP1A1 lie/lie, the CYP2E1 c1/c1,the GSTM1 non-null, the GSTT1 non-null, or the ALDH2 *1/*1 genotype.In addition, eating soybean pastes was associated with the increased risk of gastric cancer in individuals with the GSTM1 null type. Nonfermented alliums were significant in individuals with the CYP1A1 lie/lie, the CYP2E1 c1/c2 or c2/c2, the GSTT1 null, the GSTT1 non-null, or the ALDH2 *1/*2 or *2/*2 genotype,nonfermented seafood was those with the CYP1A1 lie/lie,the CYP2E1 c1/c1, the ALDH2 *1/*1 genotype or any type of GSTM1 or GSTT1. In homogeneity tests, the odds ratios of eating kimchi for gastric cancer according to the GSTM1 or 65777 genotype were not homogeneous. CONCLUSION: Kimchi, soybean pastes, and the CYP1A1 Ile/Val or Val/Val are risk factors,and nonfermented seafood and alliums are protective factors against gastric cancer in Koreans. Salt or some chemicals contained in kimchi and soybean pastes, which are increased by fermentation,would play important roles in the carcinogenesis of stomach cancer.Polymorphisms of the CYP1A1, CYP2E1, GSTM1, GSTT1, and ALDH2 genes could modify the effects of some environmental factors on the risk of gastric cancer.
基金supported by the National Natural Science Foundation of China(32572526)Liaoning Revitalization Talents Program(XLYC2402005,XLYC2213026)+1 种基金introduction of Talents(high-level)Research Start-up Fund Project of Shenyang Agricultural University(2023YJRC002)the Shenyang Science and Technology innovation Platform Project(21-103-0-14,21-104-0-28).
文摘Soybean paste has been a prominent condiment in East Asia for millennia.Nonetheless,the current methodologies for comprehensively assessing the quality of commercially available soybean paste through sensory evaluation or traditional instruments present significant challenges.In this study,contemporary detection techniques and machine learning methodologies were employed to quantitatively characterize and evaluate the overall quality of soybean paste.Sensory evaluations were conducted on 33 varieties of commercial soybean paste using three types of sensors:a colorimeter,an electronic nose(E-nose),and an electronic tongue(E-tongue)for detection purposes.Subsequently,machine learning models,including support vector regression(SVR),random forest,extreme gradient boosting,Bayesian ridge regression,ridge regression,k-nearest neighbors,and artificial neural network,were developed based on the sensory evaluation data to characterize and assess the overall quality of the soybean paste.The findings from both sensory evaluations and sensor detection indicated notable differences between the various soybean pastes.Soybean pastes can be distinguished using three sensors.The quantitative characterization model informed by the sensor data revealed that the SVR model exhibited the highest coefficient of determination(R^(2))of 0.9998 for the training set and 0.9970 for the prediction set,which was close to the ideal value of 1.Additionally,the root mean square error for the prediction set was the lowest at 0.5359.These results suggest that SVR demonstrates superior performance in cross-validation and testing,aligning closely with human sensory perceptions,thereby establishing it as the most effective predictive model.This study underscores the potential of integrating sensor data with modern machine learning techniques to supplement traditional sensory evaluations for comprehensive characterization and assessment of soybean paste quality.The outcomes of this study offer significant insights and guidance for the advancement of the soybean paste industry and the enhancement of soybean paste quality.
基金financial support of the Key Scientific Research Project of Colleges in Henan Province of China(No.22A550016)Natural Science Foundation of Henan Province for Outstanding Youth(No.202300410365)+1 种基金the Program for Science&Technology Innovation Talents in Universities of Henan Province(No.22HASTIT037)the National Natural Science Foundation of China(No.81870093,31900296).
文摘This study aimed to investigate the changes in microbial diversity,and volatile compounds of traditional fermented soybean paste originated from Henan province of China using 16S rRNA sequencing,headspace solid phase microextraction-gas chromatography/mass spectrometry(HS-SPME-GC/MS),and electronic nose(E-nose).The amino acid nitrogen and reducing sugar contents ranged between 1.18 and 1.58 g/100 g and 2.29 and 3.74 mg/g,respectively.The results showed that fermented soybean paste exhibited the highest amount of glutamate and aspartate amino acids.Approximately 112 volatile compounds were detected in all SP samples comprising 10 alcohols,19 esters,10 acidic compounds,and 21 heterocyclic compounds.Furthermore,16S rRNA sequencing indicated that Enterobacter,Bacillus,Staphylococcus,and Enterococcus were the predominant bacteria in fermented soybean paste samples.Moreover,network analysis revealed that Klebsiella,Bacillus,and Lactobacillus positively correlated with H-fluorendimethyl,octenol,and benzaldehyde.These findings helped in understanding the formation of volatile flavoring compounds during SP fermentation.
