A Survey of Mucilaginous Testa in \u3ci\u3eChamaesyce\u3c/i\u3e

Seeds of Chamaesyce were studied for presence of mucilaginous testa. Samples were selected to represent all major systematic sections within the genus. Observations were made with a dissecting microscope following brief hydration of seeds; additional SEM observations of both intact and fractured dry seeds were made for selected species. With few exceptions, most of Boissier\u27s subsections test positively for seed mucilage; however, mucilage is generally absent in subsections Gymnadeniae and Sclerophyllae , for which absence of mucilage is regarded as secondary loss from mucilagionus ancestors. Although mucilage production is associated with a well-defined subepidermal layer of macroesclereids, it is the surface layer of cells that actually secrete mucilage. Mucilage secreting cells and macroesclereids of mature testa are interpretted to develop from the epidermal layers of outer and inner integuments, respectively. Seed mucilages may play a role in seed hydration and/or seed dispersal

Requirements of SLP76 tyrosines in ITAM and integrin receptor signaling and in platelet function in vivo

Src homology 2 domain–containing leukocyte phosphoprotein of 76 kD (SLP76), an adaptor that plays a critical role in platelet activation in vitro, contains three N-terminal tyrosine residues that are essential for its function. We demonstrate that mice containing complementary tyrosine to phenylalanine mutations in Y145 (Y145F) and Y112 and Y128 (Y112/128F) differentially regulate integrin and collagen receptor signaling. We show that mutation of Y145 leads to severe impairment of glycoprotein VI (GPVI)–mediated responses while preserving outside-in integrin signaling. Platelets from Y112/128F mice, although having mild defects in GPVI signaling, exhibit defective actin reorganization after GPVI or αIIbβ3 engagement. The in vivo consequences of these signaling defects correlate with the mild protection from thrombosis seen in Y112/128F mice and the near complete protection observed in Y145F mice. Using genetic complementation, we further demonstrate that all three phosphorylatable tyrosines are required within the same SLP76 molecule to support platelet activation by GPVI

Inactivation of c-Cbl Reverses Neonatal Lethality and T Cell Developmental Arrest of SLP-76–deficient Mice

c-Cbl is an adaptor protein that negatively regulates signal transduction events involved in thymic-positive selection. To further characterize the function of c-Cbl in T cell development, we analyzed the effect of c-Cbl inactivation in mice deficient in the scaffolding molecule SLP-76. SLP-76–deficient mice show a high frequency of neonatal lethality; and in surviving mice, T cell development is blocked at the DN3 stage. Inactivation of c-cbl completely reversed the neonatal lethality seen in SLP-76–deficient mice and partially reversed the T cell development arrest in these mice. SLP-76−/− Cbl−/− mice exhibited marked expansion of polarized T helper type (Th)1 and Th2 cell peripheral CD4+ T cells, lymphoid infiltrates of parenchymal organs, and premature death. This rescue of T cell development is T cell receptor dependent because it does not occur in recombination activating gene 2−/− SLP-76−/− Cbl−/− triple knockout mice. Analysis of the signal transduction properties of SLP-76−/− Cbl−/− T cells reveals a novel SLP-76– and linker for activation of T cells–independent pathway of extracellular signal–regulated kinase activation, which is normally down-regulated by c-Cbl

Differential Requirement for SLP-76 Domains in T Cell Development and Function

AbstractThe hematopoietic cell-specific adaptor protein, SLP-76, is critical for T cell development and mature T cell receptor (TCR) signaling; however, the structural requirements of SLP-76 for mediating thymopoiesis and mature T cell function remain largely unknown. In this study, transgenic mice were generated to examine the requirements for specific domains of SLP-76 in thymocytes and peripheral T cells in vivo. Examination of mice expressing various mutants of SLP-76 on the null background demonstrates a differential requirement for specific domains of SLP-76 in thymocytes and T cells and provides new insight into the molecular mechanisms underlying SLP-76 function

The requirements for natural Th17 cell development are distinct from those of conventional Th17 cells

A distinct population of Th17 cells develops in the thymus with innate immune cell characteristics, different selection requirements, and skewed TCR gene usage compared with peripheral Th17 cells

Exploiting Large Neuroimaging Datasets to Create Connectome-Constrained Approaches for more Robust, Efficient, and Adaptable Artificial Intelligence

Despite the progress in deep learning networks, efficient learning at the edge (enabling adaptable, low-complexity machine learning solutions) remains a critical need for defense and commercial applications. We envision a pipeline to utilize large neuroimaging datasets, including maps of the brain which capture neuron and synapse connectivity, to improve machine learning approaches. We have pursued different approaches within this pipeline structure. First, as a demonstration of data-driven discovery, the team has developed a technique for discovery of repeated subcircuits, or motifs. These were incorporated into a neural architecture search approach to evolve network architectures. Second, we have conducted analysis of the heading direction circuit in the fruit fly, which performs fusion of visual and angular velocity features, to explore augmenting existing computational models with new insight. Our team discovered a novel pattern of connectivity, implemented a new model, and demonstrated sensor fusion on a robotic platform. Third, the team analyzed circuitry for memory formation in the fruit fly connectome, enabling the design of a novel generative replay approach. Finally, the team has begun analysis of connectivity in mammalian cortex to explore potential improvements to transformer networks. These constraints increased network robustness on the most challenging examples in the CIFAR-10-C computer vision robustness benchmark task, while reducing learnable attention parameters by over an order of magnitude. Taken together, these results demonstrate multiple potential approaches to utilize insight from neural systems for developing robust and efficient machine learning techniques.Comment: 11 pages, 4 figure

Novel Genetic Variants for Cartilage Thickness and Hip Osteoarthritis

Osteoarthritis is one of the most frequent and disabling diseases of the elderly. Only few genetic variants have been identified for osteoarthritis, which is partly due to large phenotype heterogeneity. To reduce heterogeneity, we here examined cartilage thickness, one of the structural components of joint health. We conducted a genome-wide association study of minimal joint space width (mJSW), a proxy for cartilage thickness, in a discovery set of 13,013 participants from five different cohorts and replication in 8,227 individuals from seven independent cohorts. We identified five genome-wide significant (GWS, P≤5·0×10−8) SNPs annotated to four distinct loci. In addition, we found two additional loci that were significantly replicated, but results of combined meta-analysis fell just below the genome wide significance threshold. The four novel associated genetic loci were located in/near TGFA (rs2862851), PIK3R1 (rs10471753), SLBP/FGFR3 (rs2236995), and TREH/DDX6 (rs496547), while the other two (DOT1L and SUPT3H/RUNX2) were previously identified. A systematic prioritization for underlying causal genes was performed using diverse lines of evidence. Exome sequencing data (n = 2,050 individuals) indicated that there were no rare exonic variants that could explain the identified associations. In addition, TGFA, FGFR3 and PIK3R1 were differentially expressed in OA cartilage lesions versus non-lesioned cartilage in the same individuals. In conclusion, we identified four novel loci (TGFA, PIK3R1, FGFR3 and TREH) and confirmed two loci known to be associated with cartilage thickness.The identified associations were not caused by rare exonic variants. This is the first report linking TGFA to human OA, which may serve as a new target for future therapies

OpenET : filling a critical data gap in water management for the western United States.

The lack of consistent, accurate information on evapotranspiration (ET) and consumptive use of water by irrigated agriculture is one of the most important data gaps for water managers in the western United States (U.S.) and other arid agricultural regions globally. The ability to easily access information on ET is central to improving water budgets across the West, advancing the use of data-driven irrigation management strategies, and expanding incentive-driven conservation programs. Recent advances in remote sensing of ET have led to the development of multiple approaches for field-scale ET mapping that have been used for local and regional water resource management applications by U.S. state and federal agencies. The OpenET project is a community-driven effort that is building upon these advances to develop an operational system for generating and distributing ET data at a field scale using an ensemble of six well-established satellite-based approaches for mapping ET. Key objectives of OpenET include: Increasing access to remotely sensed ET data through a web-based data explorer and data services; supporting the use of ET data for a range of water resource management applications; and development of use cases and training resources for agricultural producers and water resource managers. Here we describe the OpenET framework, including the models used in the ensemble, the satellite, meteorological, and ancillary data inputs to the system, and the OpenET data visualization and access tools. We also summarize an extensive intercomparison and accuracy assessment conducted using ground measurements of ET from 139 flux tower sites instrumented with open path eddy covariance systems. Results calculated for 24 cropland sites from Phase I of the intercomparison and accuracy assessment demonstrate strong agreement between the satellite-driven ET models and the flux tower ET data. For the six models that have been evaluated to date (ALEXI/DisALEXI, eeMETRIC, geeSEBAL, PT-JPL, SIMS, and SSEBop) and the ensemble mean, the weighted average mean absolute error (MAE) values across all sites range from 13.6 to 21.6 mm/month at a monthly timestep, and 0.74 to 1.07 mm/day at a daily timestep. At seasonal time scales, for all but one of the models the weighted mean total ET is within ±8% of both the ensemble mean and the weighted mean total ET calculated from the flux tower data. Overall, the ensemble mean performs as well as any individual model across nearly all accuracy statistics for croplands, though some individual models may perform better for specific sites and regions. We conclude with three brief use cases to illustrate current applications and benefits of increased access to ET data, and discuss key lessons learned from the development of OpenET