Hepatocellular carcinoma(HCC)is characterized by its highly invasive andmetastatic potential,aswell as a propensity for recurrence,contributing to treatment failure and increased mortality.Under physiological conditio...Hepatocellular carcinoma(HCC)is characterized by its highly invasive andmetastatic potential,aswell as a propensity for recurrence,contributing to treatment failure and increased mortality.Under physiological conditions,the liver maintains a balance in lipid biosynthesis,degradation,storage,and transport.HCC exhibits dysregulated lipid metabolism,driving tumor progression and therapeutic resistance.This review aims to elucidate the roles of fatty acid,sphingolipid,and cholesterol metabolism in HCC pathogenesis and explore emerging therapeutic strategies targeting these pathways.Key findings demonstrate that upregulated enzymes like fatty acid synthase(FASN),acetyl-CoA carboxylase(ACC),enhance de novo lipogenesis andβ-oxidation,and promote HCC proliferation,invasion,and apoptosis evasion.Sphingolipids exert dual functions:ceramides suppress tumors,while sphingosine-1-phosphate(S1P)drives oncogenic signaling.Aberrant cholesterolmetabolism,mediated byHMG-CoA reductase(HMGCR),liver X receptorα(LXRα),and sterol regulatory element-binding protein 1(SREBP1),contributes to immunosuppression and drug resistance.Notably,inducing ferroptosis by disrupting lipid homeostasis represents a promising approach.Pharmacological inhibition of key nodes—such as FASN(Orlistat,TVB-3664),sphingomyelin synthase(D609),or cholesterol synthesis(statins,Genkwadaphnin)—synergizes with sorafenib/lenvatinib and overcomes resistance.We conclude that targeting lipid metabolic reprogramming,alone or combined with conventional therapies,offers significant potential for novelHCC treatment strategies.Future efforts should focus on overcoming metabolic plasticity and optimizing combinatorial regimens.展开更多
Diatoms are important contributors to global net primary productivity,and play a crucial role in the biogeochemical cycles of carbon,phosphorus,nitrogen,iron,and silicon.Currently in some regions in the ocean,there’s...Diatoms are important contributors to global net primary productivity,and play a crucial role in the biogeochemical cycles of carbon,phosphorus,nitrogen,iron,and silicon.Currently in some regions in the ocean,there’s a trend that carbon content is high while oxygen concentration is low,and the underlying mechanisms of diatoms’response to low oxygen environments are worth investigating.Phaeodactylum tricornutum is a model diatom whose genome has been sequenced;it provides a universal molecular toolbox and a stable transgenic expression system.Therefore,the study of the responses of P.tricornutum to low oxygen has not only fundamental research significance but also important ecologic al significance.In this study,growth rates were determined and proteomic analysis and metabolomic analysis were performed to examine P.tricornutum responses under different oxygen concentrations(2%oxygen concentration for hypoxic condition and 21%oxygen concentration for the normal condition(sterilized air)).Results show that the hypoxic environment inhibited the growth of P.tricornutum.In the hypoxic conditions,P.tricornutum could reset its metabolism pathways,including enhancement in lipid utilization,replenishment of tricarboxylic acid(TCA)cycle through the glyoxylic acid cycle,and down-regulation of photorespiration to reduce energy waste.Additionally,the stress resistance mechanism was activated to facilitate the adaptation to low oxygen conditions.This study helps to reveal the different metabolic changes to hypoxia of diatom from that of higher plants,which might be ascribed to their different habitats and needs further exploration in the future.展开更多
Fine-grained visual classification(FGVC)is a very challenging task due to distinguishing subcategories under the same super-category.Recent works mainly localize discriminative image regions and capture subtle inter-c...Fine-grained visual classification(FGVC)is a very challenging task due to distinguishing subcategories under the same super-category.Recent works mainly localize discriminative image regions and capture subtle inter-class differences by utilizing attention-based methods.However,at the same layer,most attention-based works only consider large-scale attention blocks with the same size as feature maps,and they ignore small-scale attention blocks that are smaller than feature maps.To distinguish subcategories,it is important to exploit small local regions.In this work,a novel multi-scale attention network(MSANet)is proposed to capture large and small regions at the same layer in fine-grained visual classification.Specifically,a novel multi-scale attention layer(MSAL)is proposed,which generates multiple groups in each feature maps to capture different-scale discriminative regions.The groups based on large-scale regions can exploit global features and the groups based on the small-scale regions can extract local subtle features.Then,a simple feature fusion strategy is utilized to fully integrate global features and local subtle features to mine information that are more conducive to FGVC.Comprehensive experiments in Caltech-UCSD Birds-200-2011(CUB),FGVC-Aircraft(AIR)and Stanford Cars(Cars)datasets show that our method achieves the competitive performances,which demonstrate its effectiveness.展开更多
基金funded by grants from Guangxi Natural Science Foundation(2022JJA140639,2022JJA140776)the National Natural Science Foundation of China(82060662,82560721)Guangxi University Student Innovation and Entrepreneurship Training Program Project(S202410601137,S202510601106).
文摘Hepatocellular carcinoma(HCC)is characterized by its highly invasive andmetastatic potential,aswell as a propensity for recurrence,contributing to treatment failure and increased mortality.Under physiological conditions,the liver maintains a balance in lipid biosynthesis,degradation,storage,and transport.HCC exhibits dysregulated lipid metabolism,driving tumor progression and therapeutic resistance.This review aims to elucidate the roles of fatty acid,sphingolipid,and cholesterol metabolism in HCC pathogenesis and explore emerging therapeutic strategies targeting these pathways.Key findings demonstrate that upregulated enzymes like fatty acid synthase(FASN),acetyl-CoA carboxylase(ACC),enhance de novo lipogenesis andβ-oxidation,and promote HCC proliferation,invasion,and apoptosis evasion.Sphingolipids exert dual functions:ceramides suppress tumors,while sphingosine-1-phosphate(S1P)drives oncogenic signaling.Aberrant cholesterolmetabolism,mediated byHMG-CoA reductase(HMGCR),liver X receptorα(LXRα),and sterol regulatory element-binding protein 1(SREBP1),contributes to immunosuppression and drug resistance.Notably,inducing ferroptosis by disrupting lipid homeostasis represents a promising approach.Pharmacological inhibition of key nodes—such as FASN(Orlistat,TVB-3664),sphingomyelin synthase(D609),or cholesterol synthesis(statins,Genkwadaphnin)—synergizes with sorafenib/lenvatinib and overcomes resistance.We conclude that targeting lipid metabolic reprogramming,alone or combined with conventional therapies,offers significant potential for novelHCC treatment strategies.Future efforts should focus on overcoming metabolic plasticity and optimizing combinatorial regimens.
基金Supported by the National Natural Science Foundation of China(Nos.41876158,31770024)the Natural Science Foundation of Hainan Province(No.420QN219)+3 种基金the Biology and Biochemistry ESI Cultivation Discipline Open Project of Qilu University of Technology(No.ESIBBC202004)the Innovation and Development Joint Fund of Natural Science Foundation from Shandong Province(No.ZR2021LSW022)the Young Taishan Scholarship to Xuekui XIA(No.tsqn202103100)the Start-up Fund Project of Hainan University(No.KYQD(ZR)20060)。
文摘Diatoms are important contributors to global net primary productivity,and play a crucial role in the biogeochemical cycles of carbon,phosphorus,nitrogen,iron,and silicon.Currently in some regions in the ocean,there’s a trend that carbon content is high while oxygen concentration is low,and the underlying mechanisms of diatoms’response to low oxygen environments are worth investigating.Phaeodactylum tricornutum is a model diatom whose genome has been sequenced;it provides a universal molecular toolbox and a stable transgenic expression system.Therefore,the study of the responses of P.tricornutum to low oxygen has not only fundamental research significance but also important ecologic al significance.In this study,growth rates were determined and proteomic analysis and metabolomic analysis were performed to examine P.tricornutum responses under different oxygen concentrations(2%oxygen concentration for hypoxic condition and 21%oxygen concentration for the normal condition(sterilized air)).Results show that the hypoxic environment inhibited the growth of P.tricornutum.In the hypoxic conditions,P.tricornutum could reset its metabolism pathways,including enhancement in lipid utilization,replenishment of tricarboxylic acid(TCA)cycle through the glyoxylic acid cycle,and down-regulation of photorespiration to reduce energy waste.Additionally,the stress resistance mechanism was activated to facilitate the adaptation to low oxygen conditions.This study helps to reveal the different metabolic changes to hypoxia of diatom from that of higher plants,which might be ascribed to their different habitats and needs further exploration in the future.
基金jointly supported by the National Science and Technology Major Project(2022ZD0117103)the National Natural Science Foundations of China(62272364)+2 种基金the provincial Key Research and Development Program of Shaanxi(2024GH-ZDXM-47)the Research Project on Higher Education Teaching Reform of Shaanxi Province(23JG003)the Natural Science Basic Research Program of Shaanxi(2024JC-YBQN0639).
文摘Fine-grained visual classification(FGVC)is a very challenging task due to distinguishing subcategories under the same super-category.Recent works mainly localize discriminative image regions and capture subtle inter-class differences by utilizing attention-based methods.However,at the same layer,most attention-based works only consider large-scale attention blocks with the same size as feature maps,and they ignore small-scale attention blocks that are smaller than feature maps.To distinguish subcategories,it is important to exploit small local regions.In this work,a novel multi-scale attention network(MSANet)is proposed to capture large and small regions at the same layer in fine-grained visual classification.Specifically,a novel multi-scale attention layer(MSAL)is proposed,which generates multiple groups in each feature maps to capture different-scale discriminative regions.The groups based on large-scale regions can exploit global features and the groups based on the small-scale regions can extract local subtle features.Then,a simple feature fusion strategy is utilized to fully integrate global features and local subtle features to mine information that are more conducive to FGVC.Comprehensive experiments in Caltech-UCSD Birds-200-2011(CUB),FGVC-Aircraft(AIR)and Stanford Cars(Cars)datasets show that our method achieves the competitive performances,which demonstrate its effectiveness.
