RESUMO
Chromosomes of four Miscanthus (Andersson, 1855) species including M. sinensis (Andersson, 1855), M. floridulus (Schumann & Lauterb, 1901), M. sacchariflorus (Hackel, 1882) and M. lutarioriparius (Chen & Renvoize, 2005) were analyzed using sequentially combined PI and DAPI (CPD) staining and fluorescence in situ hybridization (FISH) with 45S rDNA probe. To elucidate the phylogenetic relationship among the four Miscanthus species, the homology of repetitive sequences among the four species was analyzed by comparative genomic in situ hybridization (cGISH). Subsequently four Miscanthus species were clustered based on the internal transcribed spacer (ITS) of 45S rDNA. Molecular cytogenetic karyotypes of the four Miscanthus species were established for the first time using chromosome measurements, fluorochrome bands and 45S rDNA FISH signals, which will provide a cytogenetic tool for the identification of these four species. All the four have the karyotype formula of Miscanthus species, which is 2n = 2x = 38 = 34m(2SAT) + 4sm, and one pair of 45S rDNA sites. The latter were shown as strong red bands by CPD staining. A non-rDNA CPD band emerged in M. floridulus and some blue DAPI bands appeared in M. sinensis and M. floridulus. The hybridization signals of M. floridulus genomic DNA to the chromosomes of M. sinensis and M. lutarioriparius genomic DNA to the chromosomes of M. sacchariflorus were stronger and more evenly distributed than other combinations. Molecular phylogenetic trees showed that M. sinensis and M. floridulus were closest relatives, and M. sacchariflorus and M. lutarioriparius were also closely related. These findings were consistent with the phylogenetic relationships inferred from the cGISH patterns.
RESUMO
BACKGROUND: This study aimed to analyze the dynamic changes of the scientific research innovation efficiency of Guangzhou Institute of Respiratory Diseases (GIRD) during the year 2009-2013 to explore the reason for these changes and give some suggestions on how to improve the overall efficiency of the Institute. METHODS: The panel data used in this study were taken from 19 research teams of GIRD during 2009 to 2013. Data envelopment analysis (DEA) based on Malmquist index (MI) was used to analyze the performance of each research team in terms of productivity changes over time. Data were analyzed using DEAP 2.1 software. RESULTS: The annual average increase rate of total factor productivity (TFP), technological progress, technical efficiency, pure technical efficiency, and scale efficiency was 30.4%, 22.5%, 6.4%, 0.9%, and 5.4%, respectively from 2009 to 2013. The scientific research innovation efficiency of the GIRD was generally high and kept on growing. The increase of TFP was mainly caused by the progress of tech, the descending of TFP in some teams should be mainly attributable to the declining pure technical efficiency, and scale efficiency on the whole, maintaining a stable growth at a low speed. CONCLUSIONS: To achieve higher scientific research innovation, GIRD not only needs to further improve the management level and introduce advanced management mode, but also needs to focus on optimization of resource allocation, as well as to strengthen the talent introduction, and continue to maintain the absorption of new technologies and innovation.