Objective:To evaluate the potential of Gracilaria changii extract in ameliorating the potential adverse effects of bisphenol A.Methods:The antioxidant capacity of Gracilaria changii extracted using different solvents(...Objective:To evaluate the potential of Gracilaria changii extract in ameliorating the potential adverse effects of bisphenol A.Methods:The antioxidant capacity of Gracilaria changii extracted using different solvents(methanol,ethanol,and aqueous)was studied.The mice were administered by oral gavage with bisphenol A(60 mg/kg body weight)for 6 weeks with or without Gracilaria changii aqueous extract.Thereafter,the mice were either euthanized for histology and immunohistochemistry studies or mated to evaluate the pregnancy rate.Results:Gracilaria changii aqueous extract showed the highest antioxidant properties compared with extract using methanol and ethanol.The aqueous extract of Gracilaria changii improved the uterus index and uterine lipid peroxidation after bisphenol A exposure,although the uterine expressions of estrogen receptors and complement C3 were not improved.Histological evaluation of the uterus during the estrus stage has revealed that the extract could mitigate bisphenol A-induced adverse effects in the uterus as there was a lower percentage of mice showing abnormalities like decreased eosin staining in the myometrium,and decrease in the number of eosinophil and endometrial glands in the endometrium.Besides,Gracilaria changii aqueous extract improved the pregnancy rate of mice administered with bisphenol A.Conclusions:Gracilaria changii extract protects against bisphenol A-induced female reproductive abnormalities in mice which may be mediated via modulation of eosinophil migration,endometrial gland formation,and protein expressions associated with prostaglandins in the myometrium.展开更多
In today’s digital era,the text may be in form of images.This research aims to deal with the problem by recognizing such text and utilizing the support vector machine(SVM).A lot of work has been done on the English l...In today’s digital era,the text may be in form of images.This research aims to deal with the problem by recognizing such text and utilizing the support vector machine(SVM).A lot of work has been done on the English language for handwritten character recognition but very less work on the under-resourced Hindi language.A method is developed for identifying Hindi language characters that use morphology,edge detection,histograms of oriented gradients(HOG),and SVM classes for summary creation.SVM rank employs the summary to extract essential phrases based on paragraph position,phrase position,numerical data,inverted comma,sentence length,and keywords features.The primary goal of the SVM optimization function is to reduce the number of features by eliminating unnecessary and redundant features.The second goal is to maintain or improve the classification system’s performance.The experiment included news articles from various genres,such as Bollywood,politics,and sports.The proposed method’s accuracy for Hindi character recognition is 96.97%,which is good compared with baseline approaches,and system-generated summaries are compared to human summaries.The evaluated results show a precision of 72%at a compression ratio of 50%and a precision of 60%at a compression ratio of 25%,in comparison to state-of-the-art methods,this is a decent result.展开更多
基金supported by the Universiti Tunku Abdul Rahman(UTAR)Research Fund(IPSR/RMC/UTARRF 2017-C1/K04)
文摘Objective:To evaluate the potential of Gracilaria changii extract in ameliorating the potential adverse effects of bisphenol A.Methods:The antioxidant capacity of Gracilaria changii extracted using different solvents(methanol,ethanol,and aqueous)was studied.The mice were administered by oral gavage with bisphenol A(60 mg/kg body weight)for 6 weeks with or without Gracilaria changii aqueous extract.Thereafter,the mice were either euthanized for histology and immunohistochemistry studies or mated to evaluate the pregnancy rate.Results:Gracilaria changii aqueous extract showed the highest antioxidant properties compared with extract using methanol and ethanol.The aqueous extract of Gracilaria changii improved the uterus index and uterine lipid peroxidation after bisphenol A exposure,although the uterine expressions of estrogen receptors and complement C3 were not improved.Histological evaluation of the uterus during the estrus stage has revealed that the extract could mitigate bisphenol A-induced adverse effects in the uterus as there was a lower percentage of mice showing abnormalities like decreased eosin staining in the myometrium,and decrease in the number of eosinophil and endometrial glands in the endometrium.Besides,Gracilaria changii aqueous extract improved the pregnancy rate of mice administered with bisphenol A.Conclusions:Gracilaria changii extract protects against bisphenol A-induced female reproductive abnormalities in mice which may be mediated via modulation of eosinophil migration,endometrial gland formation,and protein expressions associated with prostaglandins in the myometrium.
文摘In today’s digital era,the text may be in form of images.This research aims to deal with the problem by recognizing such text and utilizing the support vector machine(SVM).A lot of work has been done on the English language for handwritten character recognition but very less work on the under-resourced Hindi language.A method is developed for identifying Hindi language characters that use morphology,edge detection,histograms of oriented gradients(HOG),and SVM classes for summary creation.SVM rank employs the summary to extract essential phrases based on paragraph position,phrase position,numerical data,inverted comma,sentence length,and keywords features.The primary goal of the SVM optimization function is to reduce the number of features by eliminating unnecessary and redundant features.The second goal is to maintain or improve the classification system’s performance.The experiment included news articles from various genres,such as Bollywood,politics,and sports.The proposed method’s accuracy for Hindi character recognition is 96.97%,which is good compared with baseline approaches,and system-generated summaries are compared to human summaries.The evaluated results show a precision of 72%at a compression ratio of 50%and a precision of 60%at a compression ratio of 25%,in comparison to state-of-the-art methods,this is a decent result.
