To What Extent Are Changes in Flood Magnitude Related to Changes in Precipitation Extremes?

Despite increasing evidence of intensification of extreme precipitation events associated with a warming climate, the magnitude of peak river flows is decreasing in many parts of the world. To better understand the range of relationships between precipitation extremes and floods, we analyzed annual precipitation extremes and flood events over the contiguous United States from 1980 to 2014. A low correlation (less than 0.2) between changes in precipitation extremes and changes in floods was found, attributable to a small fraction of co‐occurrence. The covariation between precipitation extremes and floods is also substantially low, with a majority of catchments having a coefficient of determination of less than 0.5, even among the catchments with a relatively high fraction of annual maxima precipitation that can be linked to floods. The findings indicate a need for more investigations into causal mechanisms driving a nonlinear response of floods to intensified precipitation extremes in a warming climate.Key PointsWe assess co‐occurrence and covariation between precipitation extremes and floods to explore the range of their relationshipsThe spatial pattern of changes in precipitation extremes explains less than 20% of the spatial pattern of changes in floodsMost catchments have a covariation of less than 0.5 between annual precipitation extremes and annual floodsPeer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/162716/2/grl61247_am.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/162716/1/grl61247.pd

Application of dispersive liquid–liquid microextraction and reversed phase-high performance liquid chromatography for the determination of two fungicides in environmental water samples

Dispersive liquid–liquid microextraction (DLLME) has been developed for the extraction and preconcentration of diethofencarb (DF) and pyrimethanil (PM) in environmental water. In the method, a suitable mixture of extraction solvent (50 μL carbon tetrachloride) and dispersive solvent (0.75 mL acetonitrile) are injected into the aqueous samples (5.00 mL) and the cloudy solution is observed. After centrifugation, the enriched analytes in the sediment phase were determined by HPLC-VWD. Different influencing factors, such as the kind and volume of extraction and dispersive solvent, extraction time and salt effect were investigated. Under the optimum conditions, the enrichment factors for DF and PM were both 108 and the limit of detection were 0.021 ng mL−1 and 0.015 ng mL−1, respectively. The linear ranges were 0.08–400 ng mL−1 for DF and 0.04–200 ng mL−1 for PM. The relative standard deviation (RSDs) were both almost at 6.0% (n = 6). The relative recoveries from samples of environmental water were from the range of 87.0 to 107.2%. Compared with other methods, DLLME is a very simple, rapid, sensitive (low limit of detection) and economical (only 5 mL volume of sample) method

Blood–brain barrier endothelial cells in neurodegenerative diseases: Signals from the “barrier”

As blood–brain barrier (BBB) disruption emerges as a common problem in the early stages of neurodegenerative diseases, the crucial roles of barrier-type brain endothelial cells (BECs), the primary part of the BBB, have been reported in the pathophysiology of neurodegenerative diseases. The mechanisms of how early vascular dysfunction contributes to the progress of neurodegeneration are still unclear, and understanding BEC functions is a promising start. Our understanding of the BBB has gone through different stages, from a passive diffusion barrier to a mediator of central-peripheral interactions. BECs serve two seemingly paradoxical roles: as a barrier to protect the delicate brain from toxins and as an interface to constantly receive and release signals, thus maintaining and regulating the homeostasis of the brain. Most previous studies about neurodegenerative diseases focus on the loss of barrier functions, and far too little attention has been paid to the active regulations of BECs. In this review, we present the current evidence of BEC dysfunction in neurodegenerative diseases and explore how BEC signals participate in the pathogenesis of neurodegenerative diseases

Graph Learning Indexer: A Contributor-Friendly and Metadata-Rich Platform for Graph Learning Benchmarks

Establishing open and general benchmarks has been a critical driving force behind the success of modern machine learning techniques. As machine learning is being applied to broader domains and tasks, there is a need to establish richer and more diverse benchmarks to better reflect the reality of the application scenarios. Graph learning is an emerging field of machine learning that urgently needs more and better benchmarks. To accommodate the need, we introduce Graph Learning Indexer (GLI), a benchmark curation platform for graph learning. In comparison to existing graph learning benchmark libraries, GLI highlights two novel design objectives. First, GLI is designed to incentivize \emph{dataset contributors}. In particular, we incorporate various measures to minimize the effort of contributing and maintaining a dataset, increase the usability of the contributed dataset, as well as encourage attributions to different contributors of the dataset. Second, GLI is designed to curate a knowledge base, instead of a plain collection, of benchmark datasets. We use multiple sources of meta information to augment the benchmark datasets with \emph{rich characteristics}, so that they can be easily selected and used in downstream research or development. The source code of GLI is available at \url{https://github.com/Graph-Learning-Benchmarks/gli}.Comment: Oral Presentation at LOG 202

Photon-noise limited sensitivity in titanium nitride kinetic inductance detectors

We demonstrate photon-noise limited performance at sub-millimeter wavelengths in feedhorn-coupled, microwave kinetic inductance detectors (MKIDs) made of a TiN/Ti/TiN trilayer superconducting film, tuned to have a transition temperature of 1.4~K. Micro-machining of the silicon-on-insulator wafer backside creates a quarter-wavelength backshort optimized for efficient coupling at 250~\micron. Using frequency read out and when viewing a variable temperature blackbody source, we measure device noise consistent with photon noise when the incident optical power is $>$~0.5~pW, corresponding to noise equivalent powers $>$~3$\times 10^{-17}$ W/$\sqrt{\mathrm{Hz}}$. This sensitivity makes these devices suitable for broadband photometric applications at these wavelengths

Active Immunization Against the Vascular Endothelial Growth Factor Receptor flk1 Inhibits Tumor Angiogenesis and Metastasis

The vascular endothelial growth factor (VEGF) receptor fetal liver kinase 1 (flk1; VEGFR-2, KDR) is an endothelial cell–specific receptor tyrosine kinase that mediates physiological and pathological angiogenesis. We hypothesized that an active immunotherapy approach targeting flk1 may inhibit tumor angiogenesis and metastasis. To test this hypothesis, we first evaluated whether immune responses to flk1 could be elicited in mice by immunization with dendritic cells pulsed with a soluble flk1 protein (DC-flk1). This immunization generated flk1-specific neutralizing antibody and CD8+ cytotoxic T cell responses, breaking tolerance to self-flk1 antigen. Tumor-induced angiogenesis was suppressed in immunized mice as measured in an alginate bead assay. Development of pulmonary metastases was strongly inhibited in DC-flk1–immunized mice challenged with B16 melanoma or Lewis lung carcinoma cells. DC-flk1 immunization also significantly prolonged the survival of mice challenged with Lewis lung tumors. Thus, an active immunization strategy that targets an angiogenesis-related antigen on endothelium can inhibit angiogenesis and may be a useful approach for treating angiogenesis-related diseases

Assimilation of Satellite-Based Snow Cover and Freeze/Thaw Observations Over High Mountain Asia

Toward qualifying hydrologic changes in the High Mountain Asia (HMA) region, this study explores the use of a hyper-resolution (1 km) land data assimilation (DA) framework developed within the NASA Land Information System using the Noah Multi-parameterization Land Surface Model (Noah-MP) forced by the meteorological boundary conditions from Modern-Era Retrospective analysis for Research and Applications, Version 2 data. Two different sets of DA experiments are conducted: (1) the assimilation of a satellite-derived snow cover map (MOD10A1) and (2) the assimilation of the NASA MEaSUREs landscape freeze/thaw product from 2007 to 2008. The performance of the snow cover assimilation is evaluated via comparisons with available remote sensing-based snow water equivalent product and ground-based snow depth measurements. For example, in the comparison against ground-based snow depth measurements, the majority of the stations (13 of 14) show slightly improved goodness-of-fit statistics as a result of the snow DA, but only four are statistically significant. In addition, comparisons to the satellite-based land surface temperature products (MOD11A1 and MYD11A1) show that freeze/thaw DA yields improvements (at certain grid cells) of up to 0.58 K in the root-mean-square error (RMSE) and 0.77 K in the absolute bias (relative to model-only simulations). In the comparison against three ground-based soil temperature measurements along the Himalayas, the bias and the RMSE in the 0–10 cm soil temperature are reduced (on average) by 10 and 7%, respectively. The improvements in the top layer of soil estimates also propagate through the deeper soil layers, where the bias and the RMSE in the 10–40 cm soil temperature are reduced (on average) by 9 and 6%, respectively. However, no statistically significant skill differences are observed for the freeze/thaw DA system in the comparisons against ground-based surface temperature measurements at mid-to-low altitude. Therefore, the two proposed DA schemes show the potential of improving the predictability of snow mass, surface temperature, and soil temperature states across HMA, but more ground-based measurements are still required, especially at high-altitudes, in order to document a more statistically significant improvement as a result of the two DA schemes

Regulatory T Cells and Plasmacytoid Dendritic Cells Within the Tumor Microenvironment in Gastric Cancer Are Correlated With Gastric Microbiota Dysbiosis: A Preliminary Study

Substantial evidence indicates that gastric microbiota dysbiosis, immune system dysfunction especially immune escape are critical for gastric cancer (GC) occurrence and progression. As two important elements of tumor microenvironment (TME), the relationship between gastric microbiota and tumor-immune microenvironment is still unclear. Our present study aimed to explore the correlation between gastric mucosal microbiota in different microhabitats and its corresponding gastric immunosuppressive cells such as regulatory T cells (Tregs) and plasmacytoid dendritic cells (pDCs) in the TME. A cohort of 64 GC patients without preoperative chemotherapy was enrolled retrospectively, and 60 normal, 61 peritumoral and 59 tumoral tissues were obtained for gastric mucosal microbiota analysis and immunohistochemistry analysis. From different microhabitats, BDCA2+pDCs and Foxp3+Tregs were observed positively correlated, and increased in tumoral and peritumoral tissues compared to normal ones. The diversity, composition and function of gastric mucosal microbiota also changed more significantly in tumoral tissues than those in normal and peritumoral ones. With pearson's correlation analysis, we found that several non-abundant genera such as Stenotrophomonas and Selenomonas were positively correlated with BDCA2+pDCs and Foxp3+Tregs, respectively, while Comamonas and Gaiella were negatively correlated with BDCA2+pDCs and Foxp3+ Tregs, respectively. The increased BDCA2+pDCs and Foxp3+Tregs might be modulated by gastric mucosal microbiota, both participated in the immunosuppression microenvironment of GC, which might provide evidence to establish new strategies in antitumor therapy targeting on gastric microbiota

Study on wound healing effect of low-carbon topical dressings with new green packaging

In order to verify the effect of the new green and low-carbon hydrogel dressing on promoting wound healing, this project applied a sodium alginate hydrogel dressing product containing Escherichia coli and taro toxin analgesic polypeptide (The specific ingredients of the dressing) to skin wounds in common rats. Effects of the hydrogel dressing on promoting skin wound healing was evaluated by observing the occurrence and frequency of behavioral changes in rats, observing wwhistological sections under a high-power microscope, changes in serum cytokine indicators, and Image J analysis of collagen fiber reconstruction ratios in tissue sections. Through comprehensive evaluation, it can be found that hydrogel dressing has analgesic, anti-inflammatory and anti-infection effects on rat wound surface, and acts on promoting wound healing, promoting the formation of new blood vessels in the damaged skin tissue area, promoting the growth of granulation tissue, and promoting the reconstruction of collagen fibers in wound tissue