The application of data mining in astronomical surveys,such as the Large Sky Area MultiObject Fiber Spectroscopic Telescope(LAMOST)survey,provides an effective approach to automatically analyze a large amount of compl...The application of data mining in astronomical surveys,such as the Large Sky Area MultiObject Fiber Spectroscopic Telescope(LAMOST)survey,provides an effective approach to automatically analyze a large amount of complex survey data.Unsupervised clustering could help astronomers find the associations and outliers in a big data set.In this paper,we employ the k-means method to perform clustering for the line index of LAMOST spectra with the powerful software Astro Stat.Implementing the line index approach for analyzing astronomical spectra is an effective way to extract spectral features for low resolution spectra,which can represent the main spectral characteristics of stars.A total of 144 340 line indices for A type stars is analyzed through calculating their intra and inter distances between pairs of stars.For intra distance,we use the definition of Mahalanobis distance to explore the degree of clustering for each class,while for outlier detection,we define a local outlier factor for each spectrum.Astro Stat furnishes a set of visualization tools for illustrating the analysis results.Checking the spectra detected as outliers,we find that most of them are problematic data and only a few correspond to rare astronomical objects.We show two examples of these outliers,a spectrum with abnormal continuum and a spectrum with emission lines.Our work demonstrates that line index clustering is a good method for examining data quality and identifying rare objects.展开更多
OBJECTIVE To clarify the role of translocator protein 18 ku(TSPO)on cecum liga⁃tion and puncture(CLP)induced sepsis associat⁃ed encephalopathy(SAE)mice,which consis⁃tently demonstrated astrocyte activation and neu⁃roi...OBJECTIVE To clarify the role of translocator protein 18 ku(TSPO)on cecum liga⁃tion and puncture(CLP)induced sepsis associat⁃ed encephalopathy(SAE)mice,which consis⁃tently demonstrated astrocyte activation and neu⁃roinflammation.Background SAE,a brain dys⁃function,caused by systemic infection without clinical or laboratory evidence of direct infection.Most patients have symptoms such as long-term cognitive dysfunction.As the pathogenesis of SAE is very complex,neuroinflammation for SAE is one of the causes of the disease.TSPO as a marker of neuroinflammation that has the poten⁃tial to regulate neuroinflammation and SAE.METHODS The animal model of SAE was in⁃duced by CLP.TSPO ligands and TSPO knock⁃out mice were used for behavioral and molecular biology research.Survival rate of mice within 120 h on CLP mice was observed.The changes of cog⁃nitive function in mice were observed by Morris water maze and open field test.The changes of proinflammatory factors(IL-1β,TNF-α,IL-6)in hippocampus were observed by ELISA;Astro⁃cyte activation,marked by GFAP,in hippocam⁃pal was analyzed by tissue immunofluorescence and Western blotting.RESULTS Pretreatment with the TSPO ligands,XBD173 or PK11195,sig⁃nificantly improved the survival rate of CLP mice.The results of Morris water maze showed that TSPO ligands significantly increased the number of crossing the platform and the target quadrant time on CLP mice,suggesting that TSPO ligands may improve the learning and memory ability of CLP mice.Subsequent experiments revealed that TSPO ligands can reduce the inflammatory factors(IL-1β,TNF-α,IL-6)and astrocyte activa⁃tion in hippocampus of CLP mice.Similar results were also confirmed in TSPO knockout CLP mice,suggesting intervention of TSPO can reduce neuroinflammatory response and play a protec⁃tive role on SAE mice.CONCLUSION TSPO may play a critical role on SAE mice.Targeting TSPO by pharmacological means may improve the survival rate and cognitive function on CLP mice,which may through inhibiting astrocyte acti⁃vation and neuroinflammation in hippocampal.展开更多
基金supported by the Joint Research Fund in Astronomy (U1631239) under cooperative agreement between the National Natural Science Foundation of China (NSFC) and Chinese Academy of Sciences (CAS)supported by the International Science and Technology Cooperation Program of China (2014DFE10030)the Basic Science and Engineering Special Project of Heilongjiang Province Education Department (135109219)
文摘The application of data mining in astronomical surveys,such as the Large Sky Area MultiObject Fiber Spectroscopic Telescope(LAMOST)survey,provides an effective approach to automatically analyze a large amount of complex survey data.Unsupervised clustering could help astronomers find the associations and outliers in a big data set.In this paper,we employ the k-means method to perform clustering for the line index of LAMOST spectra with the powerful software Astro Stat.Implementing the line index approach for analyzing astronomical spectra is an effective way to extract spectral features for low resolution spectra,which can represent the main spectral characteristics of stars.A total of 144 340 line indices for A type stars is analyzed through calculating their intra and inter distances between pairs of stars.For intra distance,we use the definition of Mahalanobis distance to explore the degree of clustering for each class,while for outlier detection,we define a local outlier factor for each spectrum.Astro Stat furnishes a set of visualization tools for illustrating the analysis results.Checking the spectra detected as outliers,we find that most of them are problematic data and only a few correspond to rare astronomical objects.We show two examples of these outliers,a spectrum with abnormal continuum and a spectrum with emission lines.Our work demonstrates that line index clustering is a good method for examining data quality and identifying rare objects.
基金Joint Funds for the Innovation of Science and Technology of Fujian Province(2019Y9009)and Natural Science Foundation of Fujian Province(2020J01618)。
文摘OBJECTIVE To clarify the role of translocator protein 18 ku(TSPO)on cecum liga⁃tion and puncture(CLP)induced sepsis associat⁃ed encephalopathy(SAE)mice,which consis⁃tently demonstrated astrocyte activation and neu⁃roinflammation.Background SAE,a brain dys⁃function,caused by systemic infection without clinical or laboratory evidence of direct infection.Most patients have symptoms such as long-term cognitive dysfunction.As the pathogenesis of SAE is very complex,neuroinflammation for SAE is one of the causes of the disease.TSPO as a marker of neuroinflammation that has the poten⁃tial to regulate neuroinflammation and SAE.METHODS The animal model of SAE was in⁃duced by CLP.TSPO ligands and TSPO knock⁃out mice were used for behavioral and molecular biology research.Survival rate of mice within 120 h on CLP mice was observed.The changes of cog⁃nitive function in mice were observed by Morris water maze and open field test.The changes of proinflammatory factors(IL-1β,TNF-α,IL-6)in hippocampus were observed by ELISA;Astro⁃cyte activation,marked by GFAP,in hippocam⁃pal was analyzed by tissue immunofluorescence and Western blotting.RESULTS Pretreatment with the TSPO ligands,XBD173 or PK11195,sig⁃nificantly improved the survival rate of CLP mice.The results of Morris water maze showed that TSPO ligands significantly increased the number of crossing the platform and the target quadrant time on CLP mice,suggesting that TSPO ligands may improve the learning and memory ability of CLP mice.Subsequent experiments revealed that TSPO ligands can reduce the inflammatory factors(IL-1β,TNF-α,IL-6)and astrocyte activa⁃tion in hippocampus of CLP mice.Similar results were also confirmed in TSPO knockout CLP mice,suggesting intervention of TSPO can reduce neuroinflammatory response and play a protec⁃tive role on SAE mice.CONCLUSION TSPO may play a critical role on SAE mice.Targeting TSPO by pharmacological means may improve the survival rate and cognitive function on CLP mice,which may through inhibiting astrocyte acti⁃vation and neuroinflammation in hippocampal.
