Metabolic reprogramming is one of the hallmarks of cancer.1 Ketone bodies behave as alternative fuel for cancer cells to support survival and proliferation.2 3-Oxoacid CoA-transferase 1 (OXCT1) is a key enzyme that ca...Metabolic reprogramming is one of the hallmarks of cancer.1 Ketone bodies behave as alternative fuel for cancer cells to support survival and proliferation.2 3-Oxoacid CoA-transferase 1 (OXCT1) is a key enzyme that catalyzes the first and rate-limiting step of ketolysis. Recently, several studies have revealed the significance of OXCT1 in cancer development, though the underlying mechanisms remain largely unknown.3 In this study, we revealed a novel regulatory mechanism for tumorigenesis that OXCT1 regulated SREBP1-TRIM21-p65 axis through ketone body homeostasis in non-small cell lung cancer (NSCLC). In terms of mechanism, we found that OXCT1 could activate NF-κB signaling pathway by suppressing transcriptional activity of the sterol regulatory element binding protein 1 (SREBP1). As a transcription factor, SREBP1 could bind to the promoter of E3 ubiquitin ligase TRIM21, which mediated the ubiquitination of p65. Furthermore, we demonstrated that OXCT1 could maintain the homeostasis of β-hydroxybutyrate (β-HB), which acted as a signaling metabolite to activate SREBP1. Thus, β-HB connected OXCT1 with SREBP1 to activate NF-κB signaling pathway and promoted tumor initiation and progression. Taken together, these findings highlight a previously unappreciated mechanism for activation of NF-κB signaling by OXCT1 and ketone body, and demonstrate that targeting OXCT1 can inhibit NSCLC tumorigenesis.展开更多
Background:Amblyopia(lazy eye)is one of the most common causes of monocular visual impairment.Intensive investigation has shown that amblyopes suffer from a range of deficits not only in the primary visual cortex but ...Background:Amblyopia(lazy eye)is one of the most common causes of monocular visual impairment.Intensive investigation has shown that amblyopes suffer from a range of deficits not only in the primary visual cortex but also the extra-striate visual cortex.However,amblyopic brain processing deficits in large-scale information networks especially in the visual network remain unclear.Methods:Through resting state functional magnetic resonance imaging(rs-fMRI),we studied the functional connectivity and efficiency of the brain visual processing networks in 18 anisometropic amblyopic patients and 18 healthy controls(HCs).Results:We found a loss of functional correlation within the higher visual network(HVN)and the visuospatial network(VSN)in amblyopes.Additionally,compared with HCs,amblyopic patients exhibited disruptions in local efficiency in the V3v(third visual cortex,ventral part)and V4(fourth visual cortex)of the HVN,as well as in the PFt,hIP3(human intraparietal area 3),and BA7p(Brodmann area 7 posterior)of the VSN.No significant alterations were found in the primary visual network(PVN).Conclusion:Our results indicate that amblyopia results in an intrinsic decrease of both network functional correlations and local efficiencies in the extra-striate visual networks.展开更多
The frequency offset and channel gain estimation problem for multiple-input multiple-output(MIMO)systems in the case of flat-fading channels is addressed.Based on the multiple signal classification(MUSIC)and the maxim...The frequency offset and channel gain estimation problem for multiple-input multiple-output(MIMO)systems in the case of flat-fading channels is addressed.Based on the multiple signal classification(MUSIC)and the maximum likelihood(ML)methods,a new joint estimation algorithm of frequency offsets and channel gains is proposed.The new algorithm has three steps.A subset of frequency offsets is first estimated with the MUSIC algorithm.All frequency offsets in the subset are then identified with the ML method.Finally,channel gains are calculated with the ML estimator.The algorithm is a one-dimensional search scheme and therefore greatly decreases the complexity of joint ML estimation,which is essentially a multi-dimensional search scheme.展开更多
基金supported by grants to Jian-Bin Wang,Caifeng Xie and Tianyu Han from the National Natural Science Foundation of China(No.82030086,81874043,82002761,and 81902346)Natural Science Foundation of Jiangxi Province(No.20192BAB215038,and 20192ACB20024)Major Discipline Academic and Technical Leaders Training Program of Jiangxi Province(No.20204BCJ23023).
文摘Metabolic reprogramming is one of the hallmarks of cancer.1 Ketone bodies behave as alternative fuel for cancer cells to support survival and proliferation.2 3-Oxoacid CoA-transferase 1 (OXCT1) is a key enzyme that catalyzes the first and rate-limiting step of ketolysis. Recently, several studies have revealed the significance of OXCT1 in cancer development, though the underlying mechanisms remain largely unknown.3 In this study, we revealed a novel regulatory mechanism for tumorigenesis that OXCT1 regulated SREBP1-TRIM21-p65 axis through ketone body homeostasis in non-small cell lung cancer (NSCLC). In terms of mechanism, we found that OXCT1 could activate NF-κB signaling pathway by suppressing transcriptional activity of the sterol regulatory element binding protein 1 (SREBP1). As a transcription factor, SREBP1 could bind to the promoter of E3 ubiquitin ligase TRIM21, which mediated the ubiquitination of p65. Furthermore, we demonstrated that OXCT1 could maintain the homeostasis of β-hydroxybutyrate (β-HB), which acted as a signaling metabolite to activate SREBP1. Thus, β-HB connected OXCT1 with SREBP1 to activate NF-κB signaling pathway and promoted tumor initiation and progression. Taken together, these findings highlight a previously unappreciated mechanism for activation of NF-κB signaling by OXCT1 and ketone body, and demonstrate that targeting OXCT1 can inhibit NSCLC tumorigenesis.
基金supported by the National Natural Science Foundation of China(grant numbers 81501942,81701665,81500754)by the Fundamental Research Funds for the Central Universities(grant number WK2100230016).
文摘Background:Amblyopia(lazy eye)is one of the most common causes of monocular visual impairment.Intensive investigation has shown that amblyopes suffer from a range of deficits not only in the primary visual cortex but also the extra-striate visual cortex.However,amblyopic brain processing deficits in large-scale information networks especially in the visual network remain unclear.Methods:Through resting state functional magnetic resonance imaging(rs-fMRI),we studied the functional connectivity and efficiency of the brain visual processing networks in 18 anisometropic amblyopic patients and 18 healthy controls(HCs).Results:We found a loss of functional correlation within the higher visual network(HVN)and the visuospatial network(VSN)in amblyopes.Additionally,compared with HCs,amblyopic patients exhibited disruptions in local efficiency in the V3v(third visual cortex,ventral part)and V4(fourth visual cortex)of the HVN,as well as in the PFt,hIP3(human intraparietal area 3),and BA7p(Brodmann area 7 posterior)of the VSN.No significant alterations were found in the primary visual network(PVN).Conclusion:Our results indicate that amblyopia results in an intrinsic decrease of both network functional correlations and local efficiencies in the extra-striate visual networks.
基金supported by the National Science Fund for Distinguished Young Scholars (No.60725105)the National Basic Research Program of China (No.2009CB320404)+4 种基金the National Natural Science Foundation of China (Grant No.60572146)The Research Fund for the Doctoral Program of Higher Education (No.20050701007)the Fund of Teaching and Research Award Program for Outstanding Young Teachers in Higher Education Institute of Chinathe Key Project of Science and Technologies Research of MOE (No.107103)the 111 Project (B08038).
文摘The frequency offset and channel gain estimation problem for multiple-input multiple-output(MIMO)systems in the case of flat-fading channels is addressed.Based on the multiple signal classification(MUSIC)and the maximum likelihood(ML)methods,a new joint estimation algorithm of frequency offsets and channel gains is proposed.The new algorithm has three steps.A subset of frequency offsets is first estimated with the MUSIC algorithm.All frequency offsets in the subset are then identified with the ML method.Finally,channel gains are calculated with the ML estimator.The algorithm is a one-dimensional search scheme and therefore greatly decreases the complexity of joint ML estimation,which is essentially a multi-dimensional search scheme.
