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BackgroundIn order to maintain high yields while saving water and preserving non-renewable resources and thus limiting the use of chemical fertilizer, it is crucial to select plants with more efficient root systems. This could be achieved through an optimization of both root architecture and root uptake ability and/or through the improvement of positive plant interactions with microorganisms in the rhizosphere. The development of devices suitable for high-throughput phenotyping of root structures remains a major bottleneck.ResultsRhizotrons suitable for plant growth in controlled conditions and non-invasive image acquisition of plant shoot and root systems (RhizoTubes) are described. These RhizoTubes allow growing one to six plants simultaneously, having a maximum height of 1.1 m, up to 8 weeks, depending on plant species. Both shoot and root compartment can be imaged automatically and non-destructively throughout the experiment thanks to an imaging cabin (RhizoCab). RhizoCab contains robots and imaging equipment for obtaining high-resolution pictures of plant roots. Using this versatile experimental setup, we illustrate how some morphometric root traits can be determined for various species including model (Medicago truncatula), crops (Pisum sativum, Brassica napus, Vitis vinifera, Triticum aestivum) and weed (Vulpia myuros) species grown under non-limiting conditions or submitted to various abiotic and biotic constraints. The measurement of the root phenotypic traits using this system was compared to that obtained using “classic” growth conditions in pots.ConclusionsThis integrated system, to include 1200 Rhizotubes, will allow high-throughput phenotyping of plant shoots and roots under various abiotic and biotic environmental conditions. Our system allows an easy visualization or extraction of roots and measurement of root traits for high-throughput or kinetic analyses. The utility of this system for studying root system architecture will greatly facilitate the identification of genetic and environmental determinants of key root traits involved in crop responses to stresses, including interactions with soil microorganisms.

Transition-based top-down parsing with pointer networks has achieved state-of-the-art results in multiple parsing tasks, while having a linear time complexity.However, the decoder of these parsers has a sequential structure, which does not yield the most appropriate inductive bias for deriving tree structures. In this paper, we propose hierarchical pointer network parsers, and apply them to dependency and sentence-level discourse parsing tasks. Our results on standard benchmark datasets demonstrate the effectiveness of our approach, outperforming existing methods and setting a new state-of-the-art.

Models pretrained with self-supervised objectives on large text corpora achieve state-of-theart performance on English text summarization tasks. However, these models are typically fine-tuned on hundreds of thousands of data points, an infeasible requirement when applying summarization to new, niche domains. In this work, we introduce a novel and generalizable method, called WikiTransfer, for fine-tuning pretrained models for summarization in an unsupervised, dataset-specific manner. WikiTransfer fine-tunes pretrained models on pseudo-summaries, produced from generic Wikipedia data, which contain characteristics of the target dataset, such as the length and level of abstraction of the desired summaries. WikiTransfer models achieve state-ofthe-art, zero-shot abstractive summarization performance on the CNN-DailyMail dataset and demonstrate the effectiveness of our approach on three additional diverse datasets. These models are more robust to noisy data and also achieve better or comparable few-shot performance using 10 and 100 training examples when compared to few-shot transfer from other summarization datasets. To further boost performance, we employ data augmentation via round-trip translation as well as introduce a regularization term for improved few-shot transfer. To understand the role of dataset aspects in transfer performance and the quality of the resulting output summaries, we further study the effect of the components of our unsupervised fine-tuning data and analyze few-shot performance using both automatic and human evaluation.

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BACKGROUND: Hemophilia A (HA) can result in bleeding events because of low or absent clotting factor VIII (FVIII). Prophylactic treatment for severe HA includes replacement FVIII infusions and emicizumab, a bispecific factor IXa-and factor X-directed antibody. OBJECTIVE:To develop an economic model to predict the short-and longterm clinical and economic outcomes of prophylaxis with emicizumab versus short-acting recombinant FVIII among persons with HA in the United States.METHODS: A Markov model was developed to compare clinical outcomes and costs of emicizumab versus FVIII prophylaxis among persons with severe HA from U.S. payer and societal perspectives. Patients started prophylaxis at age 1 year in the base case. Mutually exclusive health states considered were "no arthropathy," "arthropathy," "surgery," and "death." Serious adverse events, breakthrough bleeds, and inhibitor development were simulated throughout the modeled time horizon. In addition to the prophylaxis drug costs, patients could incur other direct costs related to breakthrough bleeds treatment, serious adverse events, development of inhibitors, arthropathy, and orthopedic surgery. Indirect costs associated with productivity loss (i.e., missed work or disabilities) were applied for adults. Model inputs were obtained from the HAVEN 3 trial, published literature, and expert opinion. The model used a lifetime horizon, and results for 1 year and 5 years were also reported. Deterministic sensitivity analyses and scenario analyses were conducted to assess robustness of the model. RESULTS: Over a lifetime horizon, the cumulative number of all treated bleeds and joint bleeds avoided on emicizumab versus FVIII prophylaxis were 278.2 and 151.7, respectively. Correspondingly, arthropathy (mean age at onset: 12.9 vs. 5.4 years) and FVIII inhibitor development (mean age at development: 13.9 vs. 1.1 years) were delayed. Total direct and indirect costs were lower for emicizumab versus FVIII prophylaxis for all modeled time horizons

Ceritinib is cost-effective compared to crizotinib and chemotherapy in the treatment of previously untreated ALK-positive metastatic NCSLC in the US.

The root system plays an essential role in the development and physiology of the plant, as well as in its response to various stresses. However, it is often insufficiently studied, mainly because it is difficult to visualize. For grapevine, a plant of major economic interest, there is a growing need to study the root system, in particular to assess its resistance to biotic and abiotic stresses, understand the decline that may affect it, and identify new ecofriendly production systems. In this context, we have evaluated and compared three distinct growing methods (hydroponics, plane, and cylindric rhizotrons) in order to describe relevant architectural root traits of grapevine cuttings (mode of grapevine propagation), and also two 2D- (hydroponics and rhizotron) and one 3D- (neutron tomography) imaging techniques for visualization and quantification of roots. We observed that hydroponics tubes are a system easy to implement but do not allow the direct quantification of root traits over time, conversely to 2D imaging in rhizotron. We demonstrated that neutron tomography is relevant to quantify the root volume. We have also produced a new automated analysis method of digital photographs, adapted for identifying adventitious roots as a feature of root architecture in rhizotrons. This method integrates image segmentation, skeletonization, detection of adventitious root skeleton, and adventitious root reconstruction. Although this study was targeted to grapevine, most of the results obtained could be extended to other plants propagated by cuttings. Image analysis methods could also be adapted to characterization of the root system from seedlings.