Slightly acidic electrolyzed water(SAEW)has proven to be an efficient and novel sanitizer in food and agriculture field.This study assessed the efficacy of SAEW(30 mg/L)at 40℃on the inactivation of foodbome pathogens...Slightly acidic electrolyzed water(SAEW)has proven to be an efficient and novel sanitizer in food and agriculture field.This study assessed the efficacy of SAEW(30 mg/L)at 40℃on the inactivation of foodbome pathogens and detachment of multi-resistant Staphylococcus aureus(MRSA)biofilm.Furthermore.the underlying mechanism of MRS A biofilm under heated SAEW at 40℃treatment on metabolic profiles was investigated.The results showed that the heated SAEW at 40℃significantly effectively against foodbome pathogens of 1.96-7.56(lg(CFU/g))reduction in pork,chicken,spinach,and lettuce.The heated SAEW at 40℃treatment significantly reduced MRS A biofilm cells by 2.41(lg(CFU/cm^(2))).The synergistic effect of SAEW treatment showed intense anti-biofilm activity in decreasing cell density and impairing biofilm cell membranes.Global metabolic response of MRSA biofilms,treated by SAEW at 40℃,revealed the alterations of intracellular metabolites,including amino acids,organic acid,fatty acid,and lipid.Moreover,signaling pathways involved in amino acid metabolism,energy metabolism,nucleotide synthesis,carbohydrate metabolites,and lipid biosynthesis were functionally disrupted by the SAEW at 40℃treatment.As per our knowledge,this is the first research to uncover the potential mechanism of heated SAEW treatment against MRSA biofilm on food contact surface.展开更多
The occurrence of lightning-induced forest fires during a time period is count data featuring over-dispersion （i.e., variance is larger than mean） and a high frequency of zero counts. In this study, we used six gene...The occurrence of lightning-induced forest fires during a time period is count data featuring over-dispersion （i.e., variance is larger than mean） and a high frequency of zero counts. In this study, we used six generalized linear models to examine the relationship between the occurrence of lightning-induced forest fires and meteorological factors in the Northern Daxing＇an Mountains of China. The six models included Poisson, negative binomial （NB）, zero- inflated Poisson （ZIP）, zero-inflated negative binomial （ZINB）, Poisson hurdle （PH）, and negative binomial hurdle （NBH） models. Goodness-of-fit was compared and tested among the six models using Akaike information criterion （AIC）, sum of squared errors, likelihood ratio test, and Vuong test. The predictive performance of the models was assessed and compared using independent validation data by the data-splitting method. Based on the model AIC, the ZINB model best fitted the fire occurrence data, followed by （in order of smaller AIC） NBH, ZIP, NB, PH, and Poisson models. The ZINB model was also best for pre- dicting either zero counts or positive counts （〉1）. The two Hurdle models （PH and NBH） were better than ZIP, Poisson, and NB models for predicting positive counts, but worse than these three models for predicting zero counts. Thus, the ZINB model was the first choice for modeling the occurrence of lightning-induced forest fires in this study, which implied that the excessive zero counts of lightning- induced fires came from both structure and sampling zeros.展开更多
基金supported by Brain Korea (BK)21 Plus Project (4299990913942)funded by the Korean Government,Koreathe Collabo Project funded by the Ministry of SMEs and Startups (C1016120-01-02)the National Research Foundation of Korea (NRF) (2018007551)。
文摘Slightly acidic electrolyzed water(SAEW)has proven to be an efficient and novel sanitizer in food and agriculture field.This study assessed the efficacy of SAEW(30 mg/L)at 40℃on the inactivation of foodbome pathogens and detachment of multi-resistant Staphylococcus aureus(MRSA)biofilm.Furthermore.the underlying mechanism of MRS A biofilm under heated SAEW at 40℃treatment on metabolic profiles was investigated.The results showed that the heated SAEW at 40℃significantly effectively against foodbome pathogens of 1.96-7.56(lg(CFU/g))reduction in pork,chicken,spinach,and lettuce.The heated SAEW at 40℃treatment significantly reduced MRS A biofilm cells by 2.41(lg(CFU/cm^(2))).The synergistic effect of SAEW treatment showed intense anti-biofilm activity in decreasing cell density and impairing biofilm cell membranes.Global metabolic response of MRSA biofilms,treated by SAEW at 40℃,revealed the alterations of intracellular metabolites,including amino acids,organic acid,fatty acid,and lipid.Moreover,signaling pathways involved in amino acid metabolism,energy metabolism,nucleotide synthesis,carbohydrate metabolites,and lipid biosynthesis were functionally disrupted by the SAEW at 40℃treatment.As per our knowledge,this is the first research to uncover the potential mechanism of heated SAEW treatment against MRSA biofilm on food contact surface.
基金funded by Asia–Pacific Forests Net(APFNET/2010/FPF/001)National Natural Science Foundation of China(Grant No.31400552)
文摘The occurrence of lightning-induced forest fires during a time period is count data featuring over-dispersion （i.e., variance is larger than mean） and a high frequency of zero counts. In this study, we used six generalized linear models to examine the relationship between the occurrence of lightning-induced forest fires and meteorological factors in the Northern Daxing＇an Mountains of China. The six models included Poisson, negative binomial （NB）, zero- inflated Poisson （ZIP）, zero-inflated negative binomial （ZINB）, Poisson hurdle （PH）, and negative binomial hurdle （NBH） models. Goodness-of-fit was compared and tested among the six models using Akaike information criterion （AIC）, sum of squared errors, likelihood ratio test, and Vuong test. The predictive performance of the models was assessed and compared using independent validation data by the data-splitting method. Based on the model AIC, the ZINB model best fitted the fire occurrence data, followed by （in order of smaller AIC） NBH, ZIP, NB, PH, and Poisson models. The ZINB model was also best for pre- dicting either zero counts or positive counts （〉1）. The two Hurdle models （PH and NBH） were better than ZIP, Poisson, and NB models for predicting positive counts, but worse than these three models for predicting zero counts. Thus, the ZINB model was the first choice for modeling the occurrence of lightning-induced forest fires in this study, which implied that the excessive zero counts of lightning- induced fires came from both structure and sampling zeros.
