Understanding ourselves and the environment in which we live

This paper calls for a new methodological paradigm for understanding the adaptive human–nature relationship to achieve a sustainable global environment. It proposes three future research directions: theoretically framing societal processes in natural resources management; establishing a new methodological paradigm for understanding co-evolving human–nature systems; and developing system-scale experimental research

Data access for the 1,000 Plants (1KP) project

© 2014 Matasci et al.; licensee BioMed Central Ltd. The 1,000 plants (1KP) project is an international multi-disciplinary consortium that has generated transcriptome data from over 1,000 plant species, with exemplars for all of the major lineages across the Viridiplantae (green plants) clade. Here, we describe how to access the data used in a phylogenomics analysis of the first 85 species, and how to visualize our gene and species trees. Users can develop computational pipelines to analyse these data, in conjunction with data of their own that they can upload. Computationally estimated protein-protein interactions and biochemical pathways can be visualized at another site. Finally, we comment on our future plans and how they fit within this scalable system for the dissemination, visualization, and analysis of large multi-species data sets

Phylotranscriptomic analysis of the origin and early diversification of land plants

Reconstructing the origin and evolution of land plants and their algal relatives is a fundamental problem in plant phylogenetics, and is essential for understanding how critical adaptations arose, including the embryo, vascular tissue, seeds, and flowers. Despite advances inmolecular systematics, some hypotheses of relationships remain weakly resolved. Inferring deep phylogenies with bouts of rapid diversification can be problematic; however, genome-scale data should significantly increase the number of informative characters for analyses. Recent phylogenomic reconstructions focused on the major divergences of plants have resulted in promising but inconsistent results. One limitation is sparse taxon sampling, likely resulting from the difficulty and cost of data generation. To address this limitation, transcriptome data for 92 streptophyte taxa were generated and analyzed along with 11 published plant genome sequences. Phylogenetic reconstructions were conducted using up to 852 nuclear genes and 1,701,170 aligned sites. Sixty-nine analyses were performed to test the robustness of phylogenetic inferences to permutations of the datamatrix or to phylogeneticmethod, including supermatrix, supertree, and coalescent-based approaches, maximumlikelihood and Bayesian methods, partitioned and unpartitioned analyses, and amino acid versus DNA alignments. Among other results, we find robust support for a sister-group relationship between land plants and one group of streptophyte green algae, the Zygnematophyceae. Strong and robust support for a clade comprising liverworts and mosses is inconsistent with a widely accepted view of early land plant evolution, and suggests that phylogenetic hypotheses used to understand the evolution of fundamental plant traits should be reevaluated

Realising superoscillations: A review of mathematical tools and their application

Superoscillations are making a growing impact on an ever-increasing number of real-world applications, as early theoretical analysis has evolved into wide experimental realisation. This is particularly true in optics: the first application area to have extensively embraced superoscillations, with much recent growth. This review provides a tool for anyone planning to expand the boundaries in an application where superoscillations have already been used, or to apply superoscillations to a new application. By reviewing the mathematical methods for constructing superoscillations, including their considerations and capabilities, we lay out the options for anyone wanting to construct a device that uses superoscillations. Superoscillations have inherent trade-offs: as the size of spot reduces, its relative intensity decreases as high-energy sidebands appear. Different methods provide solutions for optimising different aspects of these trade-offs, to suit different purposes. Despite numerous technological ways of realising superoscillations, the mathematical methods can be categorised into three approaches: direct design of superoscillatory functions, design of pupil filters and design of superoscillatory lenses. This categorisation, based on mathematical methods, is used to highlight the transferability of methods between applications. It also highlights areas for future theoretical development to enable the scientific and technological boundaries to be pushed even further in real-world applications

Horizontal transfer of an adaptive chimeric photoreceptor from bryophytes to ferns

Ferns are well known for their shade-dwelling habits. Their ability to thrive under low-light conditions has been linked to the evolution of a novel chimeric photoreceptor-neochrome-that fuses red-sensing phytochrome and blue-sensing phototropin modules into a single gene, thereby optimizing phototropic responses. Despite being implicated in facilitating the diversification of modern ferns, the origin of neochrome has remained a mystery. We present evidence for neochrome in hornworts (a bryophyte lineage) and demonstrate that ferns acquired neochrome from hornworts via horizontal gene transfer (HGT). Fern neochromes are nested within hornwort neochromes in our large-scale phylogenetic reconstructions of phototropin and phytochrome gene families. Divergence date estimates further support the HGT hypothesis, with fern and hornwort neochromes diverging 179 Mya, long after the split between the two plant lineages (at least 400 Mya). By analyzing the draft genome of the hornwort Anthoceros punctatus, we also discovered a previously unidentified phototropin gene that likely represents the ancestral lineage of the neochrome phototropin module. Thus, a neochrome originating in hornworts was transferred horizontally to ferns, where it may have played a significant role in the diversification of modern ferns

A dual specificity kinase, DYRK1A, as a potential therapeutic target for head and neck squamous cell carcinoma

Despite advances in clinical management, 5-year survival rate in patients with late-stage head and neck squamous cell carcinoma (HNSCC) has not improved significantly over the past decade. Targeted therapies have emerged as one of the most promising approaches to treat several malignancies. Though tyrosine phosphorylation accounts for a minority of total phosphorylation, it is critical for activation of signaling pathways and plays a significant role in driving cancers. To identify activated tyrosine kinase signaling pathways in HNSCC, we compared the phosphotyrosine profiles of a panel of HNSCC cell lines to a normal oral keratinocyte cell line. Dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 1A (DYRK1A) was one of the kinases hyperphosphorylated at Tyr-321 in all HNSCC cell lines. Inhibition of DYRK1A resulted in an increased apoptosis and decrease in invasion and colony formation ability of HNSCC cell lines. Further, administration of the small molecular inhibitor against DYRK1A in mice bearing HNSCC xenograft tumors induced regression of tumor growth. Immunohistochemical labeling of DYRK1A in primary tumor tissues using tissue microarrays revealed strong to moderate staining of DYRK1A in 97.5% (39/40) of HNSCC tissues analyzed. Taken together our results suggest that DYRK1A could be a novel therapeutic target in HNSCC

Gene Expression Profiling of Liver Cancer Stem Cells by RNA-Sequencing

Background: Accumulating evidence supports that tumor growth and cancer relapse are driven by cancer stem cells. Our previous work has demonstrated the existence of CD90 + liver cancer stem cells (CSCs) in hepatocellular carcinoma (HCC). Nevertheless, the characteristics of these cells are still poorly understood. In this study, we employed a more sensitive RNA-sequencing (RNA-Seq) to compare the gene expression profiling of CD90 + cells sorted from tumor (CD90 +CSCs) with parallel non-tumorous liver tissues (CD90 +NTSCs) and elucidate the roles of putative target genes in hepatocarcinogenesis. Methodology/Principal Findings: CD90 + cells were sorted respectively from tumor and adjacent non-tumorous human liver tissues using fluorescence-activated cell sorting. The amplified RNAs of CD90 + cells from 3 HCC patients were subjected to RNA-Seq analysis. A differential gene expression profile was established between CD90 +CSCs and CD90 +NTSCs, and validated by quantitative real-time PCR (qRT-PCR) on the same set of amplified RNAs, and further confirmed in an independent cohort of 12 HCC patients. Five hundred genes were differentially expressed (119 up-regulated and 381 down-regulated genes) between CD90 +CSCs and CD90 +NTSCs. Gene ontology analysis indicated that the over-expressed genes in CD90 +CSCs were associated with inflammation, drug resistance and lipid metabolism. Among the differentially expressed genes, glypican-3 (GPC3), a member of glypican family, was markedly elevated in CD90 +CSCs compared to CD90 +NTSCs. Immunohistochemistry demonstrated that GPC3 was highly expressed in forty-two human liver tumor tissues but absent in adjacent non-tumorous liver tissues. Flow cytometry indicated that GPC3 was highly expressed in liver CD90 +CSCs and mature cancer cells in liver cancer cell lines and human liver tumor tissues. Furthermore, GPC3 expression was positively correlated with the number of CD90 +CSCs in liver tumor tissues. Conclusions/Significance: The identified genes, such as GPC3 that are distinctly expressed in liver CD90 +CSCs, may be promising gene candidates for HCC therapy without inducing damages to normal liver stem cells. © 2012 Ho et al.published_or_final_versio