Objective To establish a body composition analysis system based on chest CT,and to observe its value for evaluating content of chest muscle and adipose.Methods T7—T8 layer CT images of 108 pneumonia patients were col...Objective To establish a body composition analysis system based on chest CT,and to observe its value for evaluating content of chest muscle and adipose.Methods T7—T8 layer CT images of 108 pneumonia patients were collected(segmented dataset),and chest CT data of 984 patients were screened from the COVID 19-CT dataset(10 cases were randomly selected as whole test dataset,the remaining 974 cases were selected as layer selection dataset).T7—T8 layer was classified based on convolutional neural network(CNN)derived networks,including ResNet,ResNeXt,MobileNet,ShuffleNet,DenseNet,EfficientNet and ConvNeXt,then the accuracy,precision,recall and specificity were used to evaluate the performance of layer selection dataset.The skeletal muscle(SM),subcutaneous adipose tissue(SAT),intermuscular adipose tissue(IMAT)and visceral adipose tissue(VAT)were segmented using classical fully CNN(FCN)derived network,including FCN,SegNet,UNet,Attention UNet,UNET++,nnUNet,UNeXt and CMUNeXt,then Dice similarity coefficient(DSC),intersection over union(IoU)and 95 Hausdorff distance(HD)were used to evaluate the performance of segmented dataset.The automatic body composition analysis system was constructed based on optimal layer selection network and segmentation network,the mean absolute error(MAE),root mean squared error(RMSE)and standard deviation(SD)of MAE were used to evaluate the performance of automatic system for testing the whole test dataset.Results The accuracy,precision,recall and specificity of DenseNet network for automatically classifying T7—T8 layer from chest CT images was 95.06%,84.83%,92.27%and 95.78%,respectively,which were all higher than those of the other layer selection networks.In segmentation of SM,SAT,IMAT and overall,DSC and IoU of UNet++network were all higher,while 95HD of UNet++network were all lower than those of the other segmentation networks.Using DenseNet as the layer selection network and UNet++as the segmentation network,MAE of the automatic body composition analysis system for predicting SM,SAT,IMAT,VAT and MAE was 27.09,6.95,6.65 and 3.35 cm 2,respectively.Conclusion The body composition analysis system based on chest CT could be used to assess content of chest muscle and adipose.Among them,the UNet++network had better segmentation performance in adipose tissue than SM.展开更多
OBJECTIVE To investigate the effect of microRNA-32 on cold-induced thermogenesis and brown adipocyte energy metabolism.METHODS To apply the cold-induced thermogenesis model in mice,8-10 week old male C57Bl6 mice were ...OBJECTIVE To investigate the effect of microRNA-32 on cold-induced thermogenesis and brown adipocyte energy metabolism.METHODS To apply the cold-induced thermogenesis model in mice,8-10 week old male C57Bl6 mice were placed within a 6℃fridge for 7d.Control microRNA inhibitor or miR-32 inhibitor(10mg·kg-1)was administered via intraperitoneal injection 16 hbefore the mice were placed in the fridge.Daily core body temperatures were taken using a rectal temperature probe.Mice were euthanized after 7dand brown adipose tissue(BAT),inguinal and epididymal white adipose tissue(WAT),skeletal muscle and liver tissue analysed for changes in morphology and gene expression.RESULTS miR-32 inhibition in vivoinhibits the emergence of beige cells,which function like BAT cells,within WAT.In silico prediction and gene ontology analysis identified Tob1 as a likely target gene of miR-32.miR-32 inhibition led to increased expression of Tob1 whilst mutation of target sequence abolished this effect.Expression of brown adipose markers such as Ucp1,Pgc1α,Pparαand Prdm16 were significantly reduced in inguinal white adipose tissue(P<0.05).There was also a significant decrease in serumfgf21 levels due to the inhibition of Fgf21 expression in BAT(P<0.05).p38/MAPK signalling in brown adipose tissue was also significantly inhibited within brown adipose tissue leading to decreased fgf21 expression and secretion.CONCLUSION Our study shows that miR-32 plays a crucial role in stimulating beige cell emergence by activating p38/MAPK signalling during cold thermogenesis.miR-32 may prove effective as a treatment for obesity by activating cold-induced thermogenesis leading to increased energy metabolism.展开更多
Adipose tissue plays pivotal roles in the development of hypertension,including white and brown adipocytes.Immunity and inflammation provide a bridge between adipose dysfunction and hypertensive target organ damage.We...Adipose tissue plays pivotal roles in the development of hypertension,including white and brown adipocytes.Immunity and inflammation provide a bridge between adipose dysfunction and hypertensive target organ damage.We firstly found that perivascular adipose tissue(PVAT)expressed abundant C3,which stimulated adventitial fibroblast migration and phenotype trans-differentiation.Subsequently,we showed that C5a regulated M1/M2 macrophage polarization and inhibited adiponectin production in the PVAT,which contributed to vascular inflammation in hypertension.展开更多
2013年12月30日,哈佛大学医学院宋威博士应邀访问西南大学家蚕基因组生物学国家重点实验室,并为师生做了题为＂Activin signaling mediates muscle-to-adipose communication in a mitochondria dysfunction-mediated obesity model＂...2013年12月30日,哈佛大学医学院宋威博士应邀访问西南大学家蚕基因组生物学国家重点实验室,并为师生做了题为＂Activin signaling mediates muscle-to-adipose communication in a mitochondria dysfunction-mediated obesity model＂的精彩学术报告,重点介绍了果蝇肌肉中线粒体功能紊乱导致脂肪体中的线粒体功能也发生改变,并提出了肥胖形成过程中不同组织间线粒体功能的同步化模型。展开更多
Although body mass index(BMI)is widely used as a simple tool to assess obesity,it has certain limitations and inaccuracies.It is known that visceral adipose tissue is closely related to cardiometabolic risks and all-c...Although body mass index(BMI)is widely used as a simple tool to assess obesity,it has certain limitations and inaccuracies.It is known that visceral adipose tissue is closely related to cardiometabolic risks and all-cause mortality;however,precise measurement methods for visceral fat(magnetic resonance imaging and computed tomography)cannot be widely used.Thus,simple but accurate alternatives are valuable.Studies have shown that waist circumference-to-height ratio(WHtR)might be a superior and more accurate variable in assessing central or visceral adiposity as well as predicting risks of diabetes and other cardiometabolic diseases.Furthermore,WHtR cutoff values can be consistent across different races,age,and genders,making it a universal metric worth promoting and applying.展开更多
文摘Objective To establish a body composition analysis system based on chest CT,and to observe its value for evaluating content of chest muscle and adipose.Methods T7—T8 layer CT images of 108 pneumonia patients were collected(segmented dataset),and chest CT data of 984 patients were screened from the COVID 19-CT dataset(10 cases were randomly selected as whole test dataset,the remaining 974 cases were selected as layer selection dataset).T7—T8 layer was classified based on convolutional neural network(CNN)derived networks,including ResNet,ResNeXt,MobileNet,ShuffleNet,DenseNet,EfficientNet and ConvNeXt,then the accuracy,precision,recall and specificity were used to evaluate the performance of layer selection dataset.The skeletal muscle(SM),subcutaneous adipose tissue(SAT),intermuscular adipose tissue(IMAT)and visceral adipose tissue(VAT)were segmented using classical fully CNN(FCN)derived network,including FCN,SegNet,UNet,Attention UNet,UNET++,nnUNet,UNeXt and CMUNeXt,then Dice similarity coefficient(DSC),intersection over union(IoU)and 95 Hausdorff distance(HD)were used to evaluate the performance of segmented dataset.The automatic body composition analysis system was constructed based on optimal layer selection network and segmentation network,the mean absolute error(MAE),root mean squared error(RMSE)and standard deviation(SD)of MAE were used to evaluate the performance of automatic system for testing the whole test dataset.Results The accuracy,precision,recall and specificity of DenseNet network for automatically classifying T7—T8 layer from chest CT images was 95.06%,84.83%,92.27%and 95.78%,respectively,which were all higher than those of the other layer selection networks.In segmentation of SM,SAT,IMAT and overall,DSC and IoU of UNet++network were all higher,while 95HD of UNet++network were all lower than those of the other segmentation networks.Using DenseNet as the layer selection network and UNet++as the segmentation network,MAE of the automatic body composition analysis system for predicting SM,SAT,IMAT,VAT and MAE was 27.09,6.95,6.65 and 3.35 cm 2,respectively.Conclusion The body composition analysis system based on chest CT could be used to assess content of chest muscle and adipose.Among them,the UNet++network had better segmentation performance in adipose tissue than SM.
基金The project supported by Singapore Institute for Clinical Sciences(SICS)A*STAR Singapore and BMRC Young Investigator Grant
文摘OBJECTIVE To investigate the effect of microRNA-32 on cold-induced thermogenesis and brown adipocyte energy metabolism.METHODS To apply the cold-induced thermogenesis model in mice,8-10 week old male C57Bl6 mice were placed within a 6℃fridge for 7d.Control microRNA inhibitor or miR-32 inhibitor(10mg·kg-1)was administered via intraperitoneal injection 16 hbefore the mice were placed in the fridge.Daily core body temperatures were taken using a rectal temperature probe.Mice were euthanized after 7dand brown adipose tissue(BAT),inguinal and epididymal white adipose tissue(WAT),skeletal muscle and liver tissue analysed for changes in morphology and gene expression.RESULTS miR-32 inhibition in vivoinhibits the emergence of beige cells,which function like BAT cells,within WAT.In silico prediction and gene ontology analysis identified Tob1 as a likely target gene of miR-32.miR-32 inhibition led to increased expression of Tob1 whilst mutation of target sequence abolished this effect.Expression of brown adipose markers such as Ucp1,Pgc1α,Pparαand Prdm16 were significantly reduced in inguinal white adipose tissue(P<0.05).There was also a significant decrease in serumfgf21 levels due to the inhibition of Fgf21 expression in BAT(P<0.05).p38/MAPK signalling in brown adipose tissue was also significantly inhibited within brown adipose tissue leading to decreased fgf21 expression and secretion.CONCLUSION Our study shows that miR-32 plays a crucial role in stimulating beige cell emergence by activating p38/MAPK signalling during cold thermogenesis.miR-32 may prove effective as a treatment for obesity by activating cold-induced thermogenesis leading to increased energy metabolism.
文摘Adipose tissue plays pivotal roles in the development of hypertension,including white and brown adipocytes.Immunity and inflammation provide a bridge between adipose dysfunction and hypertensive target organ damage.We firstly found that perivascular adipose tissue(PVAT)expressed abundant C3,which stimulated adventitial fibroblast migration and phenotype trans-differentiation.Subsequently,we showed that C5a regulated M1/M2 macrophage polarization and inhibited adiponectin production in the PVAT,which contributed to vascular inflammation in hypertension.
文摘2013年12月30日,哈佛大学医学院宋威博士应邀访问西南大学家蚕基因组生物学国家重点实验室,并为师生做了题为＂Activin signaling mediates muscle-to-adipose communication in a mitochondria dysfunction-mediated obesity model＂的精彩学术报告,重点介绍了果蝇肌肉中线粒体功能紊乱导致脂肪体中的线粒体功能也发生改变,并提出了肥胖形成过程中不同组织间线粒体功能的同步化模型。
基金supported by the“1·3·5 Project”for Disciplines of Excellence,West China Hospital,Sichuan University,China(ZYGD18017)。
文摘Although body mass index(BMI)is widely used as a simple tool to assess obesity,it has certain limitations and inaccuracies.It is known that visceral adipose tissue is closely related to cardiometabolic risks and all-cause mortality;however,precise measurement methods for visceral fat(magnetic resonance imaging and computed tomography)cannot be widely used.Thus,simple but accurate alternatives are valuable.Studies have shown that waist circumference-to-height ratio(WHtR)might be a superior and more accurate variable in assessing central or visceral adiposity as well as predicting risks of diabetes and other cardiometabolic diseases.Furthermore,WHtR cutoff values can be consistent across different races,age,and genders,making it a universal metric worth promoting and applying.
