Background Hesperidin is a citrus flavonoid with anti-inflammatory and antioxidant potential. However, its protective effects on bovine mammary epithelial cells(b MECs) exposed to oxidative stress have not been elucid...Background Hesperidin is a citrus flavonoid with anti-inflammatory and antioxidant potential. However, its protective effects on bovine mammary epithelial cells(b MECs) exposed to oxidative stress have not been elucidated.Results In this study, we investigated the effects of hesperidin on H_(2)O_(2)-induced oxidative stress in b MECs and the underlying molecular mechanism. We found that hesperidin attenuated H_(2)O_(2)-induced cell damage by reducing reactive oxygen species(ROS) and malondialdehyde(MDA) levels, increasing catalase(CAT) activity, and improving cell proliferation and mitochondrial membrane potential. Moreover, hesperidin activated the Keap1/Nrf2/ARE signaling pathway by inducing the nuclear translocation of Nrf2 and the expression of its downstream genes NQO1 and HO-1, which are antioxidant enzymes involved in ROS scavenging and cellular redox balance. The protective effects of hesperidin were blocked by the Nrf2 inhibitor ML385, indicating that they were Nrf2 dependent.Conclusions Our results suggest that hesperidin could protect b MECs from oxidative stress injury by activating the Nrf2 signaling pathway, suggesting that hesperidin as a natural antioxidant has positive potential as a feed additive or plant drug to promote the health benefits of bovine mammary.展开更多
In CRYPTO 2019,Gohr opens up a new direction for cryptanalysis.He successfully applied deep learning to differential cryptanalysis against the NSA block cipher SPECK32/64,achieving higher accuracy than traditional dif...In CRYPTO 2019,Gohr opens up a new direction for cryptanalysis.He successfully applied deep learning to differential cryptanalysis against the NSA block cipher SPECK32/64,achieving higher accuracy than traditional differential distinguishers.Until now,one of the mainstream research directions is increasing the training sample size and utilizing different neural networks to improve the accuracy of neural distinguishers.This conversion mindset may lead to a huge number of parameters,heavy computing load,and a large number of memory in the distinguishers training process.However,in the practical application of cryptanalysis,the applicability of the attacks method in a resourceconstrained environment is very important.Therefore,we focus on the cost optimization and aim to reduce network parameters for differential neural cryptanalysis.ln this paper,we propose two cost-optimized neural distinguisher improvement methods from the aspect of data format and network structure,respectively.Firstly,we obtain a partial output difference neural distinguisher using only 4-bits training data format which is constructed with a new advantage bits search algorithm based on two key improvement conditions.In addition,we perform an interpretability analysis of the new neural distinguishers whose results are mainly reflected in the relationship between the neural distinguishers,truncated differential,and advantage bits.Secondly,we replace the traditional convolution with the depthwise separable convolution to reduce the training cost without affecting the accuracy as much as possible.Overall,the number of training parameters can be reduced by less than 50%by using our new network structure for training neural distinguishers.Finally,we apply the network structure to the partial output difference neural distinguishers.The combinatorial approach have led to a further reduction in the number of parameters(approximately 30% of Gohr's distinguishers for SPECK).展开更多
Integration of oncogenic DNA viruses into the human genome is a key step in most virusinduced carcinogenesis.Here,we constructed a virus integration site(VIS)Atlas database,an extensive collection of integration break...Integration of oncogenic DNA viruses into the human genome is a key step in most virusinduced carcinogenesis.Here,we constructed a virus integration site(VIS)Atlas database,an extensive collection of integration breakpoints for three most prevalent oncoviruses,human papillomavirus,hepatitis B virus,and Epstein-Barr virus based on the next-generation sequencing(NGS)data,literature,and experimental data.There are 63,179 breakpoints and 47,411 junctional sequences with full annotations deposited in the VIS Atlas database,comprising 47 virus genotypes and 17 disease types.The VIS Atlas database provides(1)a genome browser for NGS breakpoint quality check,visualization of VISs,and the local genomic context;(2)a novel platform to discover integration patterns;and(3)a statistics interface for a comprehensive investigation of genotypespecific integration features.Data collected in the VIS Atlas aid to provide insights into virus pathogenic mechanisms and the development of novel antitumor drugs.展开更多
基金supported by the Strategic Priority Research Program of the Chinese Academy of Sciences (Grant No. XDA26040304)。
文摘Background Hesperidin is a citrus flavonoid with anti-inflammatory and antioxidant potential. However, its protective effects on bovine mammary epithelial cells(b MECs) exposed to oxidative stress have not been elucidated.Results In this study, we investigated the effects of hesperidin on H_(2)O_(2)-induced oxidative stress in b MECs and the underlying molecular mechanism. We found that hesperidin attenuated H_(2)O_(2)-induced cell damage by reducing reactive oxygen species(ROS) and malondialdehyde(MDA) levels, increasing catalase(CAT) activity, and improving cell proliferation and mitochondrial membrane potential. Moreover, hesperidin activated the Keap1/Nrf2/ARE signaling pathway by inducing the nuclear translocation of Nrf2 and the expression of its downstream genes NQO1 and HO-1, which are antioxidant enzymes involved in ROS scavenging and cellular redox balance. The protective effects of hesperidin were blocked by the Nrf2 inhibitor ML385, indicating that they were Nrf2 dependent.Conclusions Our results suggest that hesperidin could protect b MECs from oxidative stress injury by activating the Nrf2 signaling pathway, suggesting that hesperidin as a natural antioxidant has positive potential as a feed additive or plant drug to promote the health benefits of bovine mammary.
基金supported by the National Natural Science Foundation of China[Grant number 62206312].
文摘In CRYPTO 2019,Gohr opens up a new direction for cryptanalysis.He successfully applied deep learning to differential cryptanalysis against the NSA block cipher SPECK32/64,achieving higher accuracy than traditional differential distinguishers.Until now,one of the mainstream research directions is increasing the training sample size and utilizing different neural networks to improve the accuracy of neural distinguishers.This conversion mindset may lead to a huge number of parameters,heavy computing load,and a large number of memory in the distinguishers training process.However,in the practical application of cryptanalysis,the applicability of the attacks method in a resourceconstrained environment is very important.Therefore,we focus on the cost optimization and aim to reduce network parameters for differential neural cryptanalysis.ln this paper,we propose two cost-optimized neural distinguisher improvement methods from the aspect of data format and network structure,respectively.Firstly,we obtain a partial output difference neural distinguisher using only 4-bits training data format which is constructed with a new advantage bits search algorithm based on two key improvement conditions.In addition,we perform an interpretability analysis of the new neural distinguishers whose results are mainly reflected in the relationship between the neural distinguishers,truncated differential,and advantage bits.Secondly,we replace the traditional convolution with the depthwise separable convolution to reduce the training cost without affecting the accuracy as much as possible.Overall,the number of training parameters can be reduced by less than 50%by using our new network structure for training neural distinguishers.Finally,we apply the network structure to the partial output difference neural distinguishers.The combinatorial approach have led to a further reduction in the number of parameters(approximately 30% of Gohr's distinguishers for SPECK).
基金supported by the National Science and Technology Major Project of the Ministry of Science and Technology of China(Grant No.2018ZX10301402)the National Natural Science Foundation of China(Grant No.81761148025)+6 种基金the Major Projects of Guangzhou Science and Technology Bureau,China(Grant No.201704020093)the National Ten Thousands Plan for Young Top Talents,Young Pearl River Scholar,International Cooperation and Exchange Projects of the National Natural Science Foundation of China(China&Russian)(Grant No.17-54-80078)the Major Projects of Wuhan Municipal Health Commission of China(Grant No.WX19M02)the Major Projects of Hubei Provincial Health Commission of China(Grant No.WJ2019H312)the Dongguan Social Development Key Project of China(Grant No.202050715007221)the Regional Joint Fund Project of Guangdong Basic and Applied Basic Research Foundation of China(Regional Cultivation Project,Grant No.2021B1515140063)the Dongguan Social Development Key Project of China(Grant No.20221800905772).
文摘Integration of oncogenic DNA viruses into the human genome is a key step in most virusinduced carcinogenesis.Here,we constructed a virus integration site(VIS)Atlas database,an extensive collection of integration breakpoints for three most prevalent oncoviruses,human papillomavirus,hepatitis B virus,and Epstein-Barr virus based on the next-generation sequencing(NGS)data,literature,and experimental data.There are 63,179 breakpoints and 47,411 junctional sequences with full annotations deposited in the VIS Atlas database,comprising 47 virus genotypes and 17 disease types.The VIS Atlas database provides(1)a genome browser for NGS breakpoint quality check,visualization of VISs,and the local genomic context;(2)a novel platform to discover integration patterns;and(3)a statistics interface for a comprehensive investigation of genotypespecific integration features.Data collected in the VIS Atlas aid to provide insights into virus pathogenic mechanisms and the development of novel antitumor drugs.
