Grassland biomass is essential for maintaining grassland ecosystems. Moreover, biomass is an important characteristic of grassland. In this study, we combined field sampling with remote sensing data and calculated five vegetation indices (VIs). Using this combined information, we quantified a remote sensing estimation model and estimated biomass in a temperate grassland of northern China. We also explored the dynamic spatio-temporal variation of biomass from 2006 to 2012. Our results indicated that all VIs investigated in the study were strongly correlated with biomass (α < 0.01). The precision of the model for estimating biomass based on ground data and remote sensing was greater than 73%. Additionally, the results of our analysis indicated that the annual average biomass was 11.86 million tons and that the average yield was 604.5 kg/ha. The distribution of biomass exhibited substantial spatial heterogeneity, and the biomass decreased from the eastern portion of the study area to the western portion. The highest coefficient of variation was found for the desert steppe, followed by the typical steppe and the meadow steppe.

Identification of effective prognostic biomarkers and targets are of crucial importance to the management of estrogen receptor positive (ER+) breast cancer. CCNA2 (also known as CyclinA2) belongs to the highly conserved cyclin family and is significantly overexpressed in various cancer types. In this study, we demonstrated that CCNA2 had significant predictive power in distant metastasis free survival, disease free survival, recurrence free survival and overall survival of ER+ breast cancer patients. We also found that CCNA2 was closely associated with tamoxifen resistance. In addition, gene set enrichment analysis (GSEA) revealed that its expression was positively associated with genes overexpressed in endocrine therapy resistant samples. Finally, though CCNA2-Drug interaction network, we demonstrated the interactions between CCNA2 and several available cancer drugs. Overall, we suggest that CCNA2 is a biomarker for the prognosis of ER+ breast cancer and monitoring of tamoxifen efficacy. It's also a promising target for developing new strategies to prevent or even reverse tamoxifen resistance. Moreover, CCNA2 expression may help monitoring tamoxifen efficacy and directing personalized therapies. Nevertheless, in vivo and in vitro experiments and multi-center randomized controlled clinical trials are still needed before its application in clinical settings.

Comprising more than 25 000 species, the Sunflower Family (Compositae or Asteraceae) is the largest family of flowering plants. Many of its lineages have experienced recent and rapid radiations, and the family has a deep and widespread history of large-scale gene duplications and polyploidy. Many of the most important evolutionary questions about the family's diversity remain unanswered due to poor resolution and lack of support for major nodes of the phylogeny. Our group has employed a phylogenomics approach using Hyb-Seq that includes sequencing 1000 low-copy number nuclear markers, plus partial plastomes for large numbers of species. Here we discuss our progress to date and present two phylogenies comprising nine subfamilies and 25 tribes using concatenated and coalescence-based analyses. We discuss future plans for incorporating high-quality reference genomes and transcriptomes to advance systematic and evolutionary studies in the Compositae. While we have made great strides toward developing tools for employing phylogenomics and resolving relationships within Compositae, much work remains. Recently formed global partnerships will work to solve the unanswered evolutionary questions for this megafamily.