Bio-inspired study of thermal effects on NACA0012 airfoil at Reynolds Number of 33,000

The amount of solar and background radiation absorbed by birds vary according to their wing shape, pigmentation, porosity, etc. Birds are equipped with unique features to thrive, including attracting opposite sex, regulating body temperatures, and soaring in the sky. The research focuses on solar/sky radiation by examining how NACA0012 airfoil, representing the wing of a bird, performs when its upper surface temperature is higher or lower than the surrounding air. This is realised by performing 2-dimensional simulations in OpenFOAM at a Reynolds Number of 33,000, where Spalart-Allmaras model is used to simulate the flow turbulence. The upper surface of the airfoil is warmed to 330 K and cooled to 270 K at a pressure of 1 atm, an ambient temperature of 300 K, and a Mach number of 0.0725. The results illustrate the airfoil with the cooler top surface exhibits a lower drag and higher lift than its warmer top surface counterpart. A maximum reduction of drag coefficient from 0.065 to 0.061 and increase in lift coefficient from 0.89 to 0.93 at an angle of attack 11° are achieved. In short, tuning the upper surface of NACA0012 airfoil to temperatures lower than the ambient provides better aerodynamic performance

An injectable bone marrow-like scaffold enhances T cell immunity after hematopoietic stem cell transplantation.

Allogeneic hematopoietic stem cell transplantation (HSCT) is a curative treatment for multiple disorders, but deficiency and dysregulation of T cells limit its utility. Here we report a biomaterial-based scaffold that mimics features of T cell lymphopoiesis in the bone marrow. The bone marrow cryogel (BMC) releases bone morphogenetic protein-2 to recruit stromal cells and presents the Notch ligand Delta-like ligand-4 to facilitate T cell lineage specification of mouse and human hematopoietic progenitor cells. BMCs subcutaneously injected in mice at the time of HSCT enhanced T cell progenitor seeding of the thymus, T cell neogenesis and diversification of the T cell receptor repertoire. Peripheral T cell reconstitution increased ~6-fold in mouse HSCT and ~2-fold in human xenogeneic HSCT. Furthermore, BMCs promoted donor CD4+ regulatory T cell generation and improved survival after allogeneic HSCT. In comparison to adoptive transfer of T cell progenitors, BMCs increased donor chimerism, T cell generation and antigen-specific T cell responses to vaccination. BMCs may provide an off-the-shelf approach for enhancing T cell regeneration and mitigating graft-versus-host disease in HSCT

Levels of protein C and soluble thrombomodulin in critically ill patients with acute kidney injury: a multicenter prospective observational study.

Endothelial dysfunction contributes to the development of acute kidney injury (AKI) in animal models of ischemia reperfusion injury and sepsis. There are limited data on markers of endothelial dysfunction in human AKI. We hypothesized that Protein C (PC) and soluble thrombomodulin (sTM) levels could predict AKI. We conducted a multicenter prospective study in 80 patients to assess the relationship of PC and sTM levels to AKI, defined by the AKIN creatinine (AKI Scr) and urine output criteria (AKI UO). We measured marker levels for up to 10 days from intensive care unit admission. We used area under the curve (AUC) and time-dependent multivariable Cox proportional hazard model to predict AKI and logistic regression to predict mortality/non-renal recovery. Protein C and sTM were not different in patients with AKI UO only versus no AKI. On intensive care unit admission, as PC levels are usually lower with AKI Scr, the AUC to predict the absence of AKI was 0.63 (95%CI 0.44-0.78). The AUC using log10 sTM levels to predict AKI was 0.77 (95%CI 0.62-0.89), which predicted AKI Scr better than serum and urine neutrophil gelatinase-associated lipocalin (NGAL) and cystatin C, urine kidney injury molecule-1 and liver-fatty acid-binding protein. In multivariable models, PC and urine NGAL levels independently predicted AKI (p=0.04 and 0.02) and PC levels independently predicted mortality/non-renal recovery (p=0.04). In our study, PC and sTM levels can predict AKI Scr but are not modified during AKI UO alone. PC levels could independently predict mortality/non-renal recovery. Additional larger studies are needed to define the relationship between markers of endothelial dysfunction and AKI

DPRP: a database of phenotype-specific regulatory programs derived from transcription factor binding data

Gene expression profiling has been extensively used in the past decades, resulting in an enormous amount of expression data available in public databases. These data sets are informative in elucidating transcriptional regulation of genes underlying various biological and clinical conditions. However, it is usually difficult to identify transcription factors (TFs) responsible for gene expression changes directly from their own expression, as TF activity is often regulated at the posttranscriptional level. In recent years, technical advances have made it possible to systematically determine the target genes of TFs by ChIP-seq experiments. To identify the regulatory programs underlying gene expression profiles, we constructed a database of phenotype-specific regulatory programs (DPRP, http://syslab.nchu.edu.tw/DPRP/) derived from the integrative analysis of TF binding data and gene expression data. DPRP provides three methods: the Fisher's Exact Test, the Kolmogorov-Smirnov test and the BASE algorithm to facilitate the application of gene expression data for generating new hypotheses on transcriptional regulatory programs in biological and clinical studies

AI for Interpretable Chemistry: Predicting Radical Mechanistic Pathways via Contrastive Learning

Deep learning-based reaction predictors have undergone significant architectural evolution. However, their reliance on reactions from the US Patent Office results in a lack of interpretable predictions and limited generalization capability to other chemistry domains, such as radical and atmospheric chemistry. To address these challenges, we introduce a new reaction predictor system, RMechRP, that leverages contrastive learning in conjunction with mechanistic pathways, the most interpretable representation of chemical reactions. Specifically designed for radical reactions, RMechRP provides different levels of interpretation of chemical reactions. We develop and train multiple deep-learning models using RMechDB, a public database of radical reactions, to establish the first benchmark for predicting radical reactions. Our results demonstrate the effectiveness of RMechRP in providing accurate and interpretable predictions of radical reactions, and its potential for various applications in atmospheric chemistry

The Burrell-Optical-Kepler-Survey (BOKS). I. Survey Description and Initial Results

We present the initial results of a 40 night contiguous ground-based campaign of time series photometric observations of a 1.39 deg^2 field located within the NASA Kepler Mission field of view. The goal of this pre-launch survey was to search for transiting extrasolar planets and to provide independent variability information of stellar sources. We have gathered a data set containing light curves of 54,687 stars from which we have created a statistical sub-sample of 13,786 stars between 14 < r < 18.5 and have statistically examined each light curve to test for variability. We present a summary of our preliminary photometric findings including the overall level and content of stellar variability in this portion of the Kepler field and give some examples of unusual variable stars found within. We present a preliminary catalog of 2,457 candidate variable stars, of which 776 show signs of periodicity. We also present three potential exoplanet candidates, all of which should be observable by the Kepler mission

DPRP: A Database of Phenotype-Specific Regulatory Programs Derived from Transcription Factor Binding Data

Gene expression profiling has been extensively used in the past decades, resulting in an enormous amount of expression data available in public databases. These data sets are informative in elucidating transcriptional regulation of genes underlying various biological and clinical conditions. However, it is usually difficult to identify transcription factors (TFs) responsible for gene expression changes directly from their own expression, as TF activity is often regulated at the posttranscriptional level. In recent years, technical advances have made it possible to systematically determine the target genes of TFs by ChIP-seq experiments. To identify the regulatory programs underlying gene expression profiles, we constructed a database of phenotype-specific regulatory programs (DPRP, http://syslab.nchu.edu.tw/DPRP/) derived from the integrative analysis of TF binding data and gene expression data. DPRP provides three methods: the Fisher’s Exact Test, the Kolmogorov–Smirnov test and the BASE algorithm to facilitate the application of gene expression data for generating new hypotheses on transcriptional regulatory programs in biological and clinical studies

Organic biogeochemistry in West Mata, NE Kau hydrothermal vent fields

Author Posting. © American Geophysical Union, 2021. This article is posted here by permission of American Geophysical Union for personal use, not for redistribution. The definitive version was published in Geochemistry, Geophysics, Geosystems 22(4), (2021): e2020GC009481, https://doi.org/10.1029/2020GC009481.The impact of submarine hydrothermal systems on organic carbon in the ocean—one of the largest fixed carbon reservoirs on Earth—could be profound. Yet, different vent sites show diverse fluid chemical compositions and the subsequent biological responses. Observations from various vent sites are to evaluate hydrothermal systems' impact on the ocean carbon cycle. A response cruise in May 2009 to an on-going submarine eruption at West Mata Volcano, northeast Lau Basin, provided an opportunity to quantify the organic matter production in a back-arc spreading hydrothermal system. Hydrothermal vent fluids contained elevated dissolved organic carbon, particulate organic carbon (POC), and particulate nitrogen (PN) relative to background seawater. The δ13C-POC values for suspended particles in the diffuse vent fluids (−15.5‰ and −12.3‰) are distinct from those in background seawater (−23 ± 1‰), indicative of unique carbon synthesis pathways of the vent microbes from the seawater counterparts. The first dissolved organic nitrogen concentrations reported for diffuse vents were similar to or higher than those for background seawater. Enhanced nitrogen fixation and denitrification removed 37%–89% of the total dissolved nitrogen in the recharging background seawater in the hydrothermal vent flow paths. The hydrothermal plume samples were enriched in POC and PN, indicating enhanced biological production. The total “dark” organic carbon production within the plume matches the thermodynamic prediction based on available reducing chemical substances supplied to the plume. This research combines the measured organic carbon contents with thermodynamic modeled results and demonstrates the importance of hydrothermal activities on the water column carbon production in the deep ocean.This project was supported by N.S.F. (OCE0929881, J. P. Cowen and K. H. Rubin), the NOAA PMEL VENTS (now Earth-Ocean Interactions) Program and the Joint Institute for the Study of the Atmosphere and Ocean (JISAO) under NOAA Cooperative Agreement No. NA10OAR4320148, and the UH NASA Astrobiology Institute. The Ministry of Science and Technology of Taiwan award (MOST 107-2611-M-002-002, and MOST 108-2611-M-002-006 to H.-T. Lin). Ministry of Education (M.O.E.) Republic of China (Taiwan) 109L892601 to H.-T. Lin. SOEST contributions no. 11285, C-DEBI contribution no. 563. PMEL contribution no. 3996, JISAO contribution 2183