Fragments Speak: Reexamining the Rejected Pre-Du Yu Commentaries on the Zuozhuan

As this paper shows, though considered largely philological or lexical in nature,early medieval (1st–7th c. CE) commentaries on the Zuozhuan ?? (ca. 4th c. BCE), anearly Chinese historical narrative, not only bring to the fore ambiguities in the text itself, but also generate divergent literary scenarios and character judgments under-examined by modern Zuozhuan scholars. Commissioned by Tang Taizong’s ??? court (626–649 CE), the imperial compilers of the Zuozhuan zhengyi ???? (Corrected meaning of the Zuozhuan) adopted Du Yu’s ?? (222–284) commentary on the Zuozhuan and implicitly rejected Eastern Han (25–220 CE) commentaries. This article considers marginalized commentaries written before Du Yu’s time as particularly valuable because such earlier competing interpretations could destabilize—in our latter day perspective—the readings “fixed” by the early Tang authorization of Du Yu’s commentary

Application of object tracking in video recordings to the observation of mice in the wild

We give an overview of methods used to track moving objects in video and describe how information about animal behavior can be extracted from tracking data. We discuss how computer-aided observation can be used to identify and pre-select potentially interesting video sequences from large amounts of video data for further observation, as well as directly analyze extracted data. We examine how this analysis can be used to study animal behavior. As an example, we examine thermal video recorded from free-living, nocturnal, wild mice in the genus Peromyscus

Updating known distribution models for forecasting climate change impact on endangered species

To plan endangered species conservation and to design adequate management programmes, it is necessary to predict their distributional response to climate change, especially under the current situation of rapid change. However, these predictions are customarily done by relating de novo the distribution of the species with climatic conditions with no regard of previously available knowledge about the factors affecting the species distribution. We propose to take advantage of known species distribution models, but proceeding to update them with the variables yielded by climatic models before projecting them to the future. To exemplify our proposal, the availability of suitable habitat across Spain for the endangered Bonelli’s Eagle (Aquila fasciata) was modelled by updating a pre-existing model based on current climate and topography to a combination of different general circulation models and Special Report on Emissions Scenarios. Our results suggested that the main threat for this endangered species would not be climate change, since all forecasting models show that its distribution will be maintained and increased in mainland Spain for all the XXI century. We remark on the importance of linking conservation biology with distribution modelling by updating existing models, frequently available for endangered species, considering all the known factors conditioning the species’ distribution, instead of building new models that are based on climate change variables only.Ministerio de Ciencia e Innovación and FEDER (project CGL2009-11316/BOS

Proton Pump Inhibitors Inhibit Metformin Uptake by Organic Cation Transporters (OCTs)

Metformin, an oral insulin-sensitizing drug, is actively transported into cells by organic cation transporters (OCT) 1, 2, and 3 (encoded by SLC22A1, SLC22A2, or SLC22A3), which are tissue specifically expressed at significant levels in various organs such as liver, muscle, and kidney. Because metformin does not undergo hepatic metabolism, drug-drug interaction by inhibition of OCT transporters may be important. So far, comprehensive data on the interaction of proton pump inhibitors (PPIs) with OCTs are missing although PPIs are frequently used in metformin-treated patients. Using in silico modeling and computational analyses, we derived pharmacophore models indicating that PPIs (i.e. omeprazole, pantoprazole, lansoprazole, rabeprazole, and tenatoprazole) are potent OCT inhibitors. We then established stably transfected cell lines expressing the human uptake transporters OCT1, OCT2, or OCT3 and tested whether these PPIs inhibit OCT-mediated metformin uptake in vitro. All tested PPIs significantly inhibited metformin uptake by OCT1, OCT2, and OCT3 in a concentration-dependent manner. Half-maximal inhibitory concentration values (IC50) were in the low micromolar range (3–36 µM) and thereby in the range of IC50 values of other potent OCT drug inhibitors. Finally, we tested whether the PPIs are also transported by OCTs, but did not identify PPIs as OCT substrates. In conclusion, PPIs are potent inhibitors of the OCT-mediated metformin transport in vitro. Further studies are needed to elucidate the clinical relevance of this drug-drug interaction with potential consequences on metformin disposition and/or efficacy

TRY plant trait database - enhanced coverage and open access

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives

Shedding light on plant litter decomposition: Advances, implications and new directions in understanding the role of photodegradation

Litter decomposition contributes to one of the largest fluxes of carbon (C) in the terrestrial biosphere and is a primary control on nutrient cycling. The inability of models using climate and litter chemistry to predict decomposition in dry environments has stimulated investigation of non-traditional drivers of decomposition, including photodegradation, the abiotic decomposition of organic matter via exposure to solar radiation. Recent work in this developing field shows that photodegradation may substantially influence terrestrial C fluxes, including abiotic production of carbon dioxide, carbon monoxide and methane, especially in arid and semi-arid regions. Research has also produced contradictory results regarding controls on photodegradation. Here we summarize the state of knowledge about the role of photodegradation in litter decomposition and C cycling and investigate drivers of photodegradation across experiments using a meta-analysis. Overall, increasing litter exposure to solar radiation increased mass loss by 23% with large variation in photodegradation rates among and within ecosystems. This variation was tied to both litter and environmental characteristics. Photodegradation increased with litter C to nitrogen (N) ratio, but not with lignin content, suggesting that we do not yet fully understand the underlying mechanisms. Photodegradation also increased with factors that increased solar radiation exposure (latitude and litter area to mass ratio) and decreased with mean annual precipitation. The impact of photodegradation on C (and potentially N) cycling fundamentally reshapes our thinking of decomposition as a solely biological process and requires that we define the mechanisms driving photodegradation before we can accurately represent photodegradation in global C and N models. © 2012 US Government

Cohesin is required for higher-order chromatin conformation at the imprinted IGF2-H19 locus

Cohesin is a chromatin-associated protein complex that mediates sister chromatid cohesion by connecting replicated DNA molecules. Cohesin also has important roles in gene regulation, but the mechanistic basis of this function is poorly understood. In mammalian genomes, cohesin co-localizes with CCCTC binding factor (CTCF), a zinc finger protein implicated in multiple gene regulatory events. At the imprinted IGF2-H19 locus, CTCF plays an important role in organizing allele-specific higher-order chromatin conformation and functions as an enhancer blocking transcriptional insulator. Here we have used chromosome conformation capture (3C) assays and RNAi-mediated depletion of cohesin to address whether cohesin affects higher order chromatin conformation at the IGF2-H19 locus in human cells. Our data show that cohesin has a critical role in maintaining CTCF-mediated chromatin conformation at the locus and that disruption of this conformation coincides with changes in IGF2 expression. We show that the cohesin-dependent, higher-order chromatin conformation of the locus exists in both G1 and G2 phases of the cell cycle and is therefore independent of cohesin's function in sister chromatid cohesion. We propose that cohesin can mediate interactions between DNA molecules in cis to insulate genes through the formation of chromatin loops, analogous to the cohesin mediated interaction with sister chromatids in trans to establish cohesion

Machine Learning Approach for Prescriptive Plant Breeding

We explored the capability of fusing high dimensional phenotypic trait (phenomic) data with a machine learning (ML) approach to provide plant breeders the tools to do both in-season seed yield (SY) prediction and prescriptive cultivar development for targeted agro-management practices (e.g., row spacing and seeding density). We phenotyped 32 SoyNAM parent genotypes in two independent studies each with contrasting agro-management treatments (two row spacing, three seeding densities). Phenotypic trait data (canopy temperature, chlorophyll content, hyperspectral reflectance, leaf area index, and light interception) were generated using an array of sensors at three growth stages during the growing season and seed yield (SY) determined by machine harvest. Random forest (RF) was used to train models for SY prediction using phenotypic traits (predictor variables) to identify the optimal temporal combination of variables to maximize accuracy and resource allocation. RF models were trained using data from both experiments and individually for each agro-management treatment. We report the most important traits agnostic of agro-management practices. Several predictor variables showed conditional importance dependent on the agro-management system. We assembled predictive models to enable in-season SY prediction, enabling the development of a framework to integrate phenomics information with powerful ML for prediction enabled prescriptive plant breeding