Improving Patch-Based Convolutional Neural Networks for MRI Brain Tumor Segmentation by Leveraging Location Information.

The manual brain tumor annotation process is time consuming and resource consuming, therefore, an automated and accurate brain tumor segmentation tool is greatly in demand. In this paper, we introduce a novel method to integrate location information with the state-of-the-art patch-based neural networks for brain tumor segmentation. This is motivated by the observation that lesions are not uniformly distributed across different brain parcellation regions and that a locality-sensitive segmentation is likely to obtain better segmentation accuracy. Toward this, we use an existing brain parcellation atlas in the Montreal Neurological Institute (MNI) space and map this atlas to the individual subject data. This mapped atlas in the subject data space is integrated with structural Magnetic Resonance (MR) imaging data, and patch-based neural networks, including 3D U-Net and DeepMedic, are trained to classify the different brain lesions. Multiple state-of-the-art neural networks are trained and integrated with XGBoost fusion in the proposed two-level ensemble method. The first level reduces the uncertainty of the same type of models with different seed initializations, and the second level leverages the advantages of different types of neural network models. The proposed location information fusion method improves the segmentation performance of state-of-the-art networks including 3D U-Net and DeepMedic. Our proposed ensemble also achieves better segmentation performance compared to the state-of-the-art networks in BraTS 2017 and rivals state-of-the-art networks in BraTS 2018. Detailed results are provided on the public multimodal brain tumor segmentation (BraTS) benchmarks

Precipitation, Circulation, and Cloud Variability Over the Past Two Decades

To better understand the variability of precipitation, circulation, and cloud, we examine the precipitation, vertical velocity, total cloud fraction, condensed water path, and ice water path from observations and 13 Coupled Model Intercomparison Project 5 (CMIP5) models over 1988–2008. All variables are averaged over wet areas and dry areas to investigate temporal variations of different variables over these regions. We found that all models demonstrate similar temporal variations of precipitation as the observational data from the Global Precipitation Climatology Project, with positive trend over wet areas (6.22 ± 3.75 mm/mon/decade) and negative trend over dry areas (−0.77 ± 0.54 mm/mon/decade). Positive trends of vertical velocity, total cloud fraction, condensed water path, and ice water path are also found in the observations and models over the wet areas. Observations also demonstrate decreasing trends of vertical velocity, total clouds, condensed water path, and ice water path over the dry areas, which can be simulated by most models with a few exceptions. The qualitatively consistent trends in these variables (i.e., vertical velocity, cloud, liquid, and ice water contents) as revealed from the observations and CMIPS models provide a clearer picture of the dynamics and physics behind the temporal variations of precipitation over different areas

Corrigendum: Improving Patch-Based Convolutional Neural Networks for MRI Brain Tumor Segmentation by Leveraging Location Information.

[This corrects the article DOI: 10.3389/fnins.2019.01449.]

Temporal and Spatial Variability of Precipitation from Observations and Models

Principal component analysis (PCA) is utilized to explore the temporal and spatial variability of precipitation from GPCP and a CAM5 simulation from 1979 to 2010. In the tropical region, the interannual variability of tropical precipitation is characterized by two dominant modes (El Niño and El Niño Modoki). The first and second modes of tropical GPCP precipitation capture 31.9% and 15.6% of the total variance, respectively. The first mode has positive precipitation anomalies over the western Pacific and negative precipitation anomalies over the central and eastern Pacific. The second mode has positive precipitation anomalies over the central Pacific and negative precipitation anomalies over the western and eastern Pacific. Similar variations are seen in the first two modes of tropical precipitation from a CAM5 simulation, although the magnitudes are slightly weaker than in the observations. Over the Northern Hemisphere (NH) high latitudes, the first mode, capturing 8.3% of the total variance of NH GPCP precipitation, is related to the northern annular mode (NAM). During the positive phase of NAM, there are negative precipitation anomalies over the Arctic and positive precipitation anomalies over the midlatitudes. Over the Southern Hemisphere (SH) high latitudes, the first mode, capturing 13.2% of the total variance of SH GPCP precipitation, is related to the southern annular mode (SAM). During the positive phase of the SAM, there are negative precipitation anomalies over the Antarctic and positive precipitation anomalies over the midlatitudes. The CAM5 precipitation simulation demonstrates similar results to those of the observations. However, they do not capture both the high precipitation anomalies over the northern Pacific Ocean or the position of the positive precipitation anomalies in the SH

Engineered yeast for enhanced CO2 mineralization

In this work, a biologically catalysed CO2 mineralization process for the capture of CO2 from point sources was designed, constructed at a laboratory scale, and, using standard chemical process scale-up protocols, was modelled and evaluated at an industrial scale. A yeast display system in Saccharomyces cerevisae was used to screen several carbonic anhydrase isoforms and mineralization peptides for their impact on CO2 hydration, CaCO3 mineralization, and particle settling rate. Enhanced rates for each of these steps in the CaCO3 mineralization process were confirmed using quantitative techniques in lab-scale measurements. The effect of these enhanced rates on the CO2 capture cost in an industrial scale CO2 mineralization process using coal fly ash as the CaO source was evaluated. The model predicts a process using bCA2-yeast and fly ash is [similar]10% more cost effective per tonne of CO2 captured than a process with no biological molecules, a savings not realized by wild-type yeast and high-temperature stable recombinant CA2 alone or in combination. The levelized cost of electricity for a power plant using this process was calculated and scenarios in which this process compares favourably to CO2 capture by MEA absorption process are presented.MIT Energy InitiativeEni S.p.A. (Firm)National Institutes of Health (U.S.) (NIH Biotechnology Training Program)Thomas and Stacey Siebel Foundatio

Precipitation, Circulation, and Cloud Variability Over the Past Two Decades

To better understand the variability of precipitation, circulation, and cloud, we examine the precipitation, vertical velocity, total cloud fraction, condensed water path, and ice water path from observations and 13 Coupled Model Intercomparison Project 5 (CMIP5) models over 1988–2008. All variables are averaged over wet areas and dry areas to investigate temporal variations of different variables over these regions. We found that all models demonstrate similar temporal variations of precipitation as the observational data from the Global Precipitation Climatology Project, with positive trend over wet areas (6.22 ± 3.75 mm/mon/decade) and negative trend over dry areas (−0.77 ± 0.54 mm/mon/decade). Positive trends of vertical velocity, total cloud fraction, condensed water path, and ice water path are also found in the observations and models over the wet areas. Observations also demonstrate decreasing trends of vertical velocity, total clouds, condensed water path, and ice water path over the dry areas, which can be simulated by most models with a few exceptions. The qualitatively consistent trends in these variables (i.e., vertical velocity, cloud, liquid, and ice water contents) as revealed from the observations and CMIPS models provide a clearer picture of the dynamics and physics behind the temporal variations of precipitation over different areas

State of the Science: Salivary Biomarker Utilization for Stress Research

The use of salivary biomarkers for stress research is increasing based on the convenience of collection, affordability and scientific merit. This short review provides an overview of the state of the science of salivary biomarkers utilized in research related to stress. Methods: An integrative review was conducted. Results: The trend of utilizing salivary biomarkers in stress research was reviewed, specifically, focusing on the use of endocrine and inflammatory biomarkers incorporated in previous stress research. Then, a review of sampling procedures for salivary biomarkers and the analytic methods is provided. Finally, a discussion on the strengths and areas for improvement in the use of salivary biomarkers in stress research is included. Conclusion: Salivary biomarkers as an alternative to blood biomarkers are increasingly being recognized as a legitimate source for analyzing the stress response in humans

Beta defensin-2 is reduced in central but not in distal airways of smoker COPD patients

Background: Altered pulmonary defenses in chronic obstructive pulmonary disease (COPD) may promote distal airways bacterial colonization. The expression/activation of Toll Like receptors (TLR) and beta 2 defensin (HBD2) release by epithelial cells crucially affect pulmonary defence mechanisms. Methods: The epithelial expression of TLR4 and of HBD2 was assessed in surgical specimens from current smokers COPD (s-COPD; n = 17), ex-smokers COPD (ex-s-COPD; n = 8), smokers without COPD (S; n = 12), and from non-smoker non-COPD subjects (C; n = 13). Results: In distal airways, s-COPD highly expressed TLR4 and HBD2. In central airways, S and s-COPD showed increased TLR4 expression. Lower HBD2 expression was observed in central airways of s-COPD when compared to S and to ex-s-COPD. s-COPD had a reduced HBD2 gene expression as demonstrated by real-time PCR on micro-dissected bronchial epithelial cells. Furthermore, HBD2 expression positively correlated with FEV1/FVC ratio and inversely correlated with the cigarette smoke exposure. In a bronchial epithelial cell line (16 HBE) IL-1β significantly induced the HBD2 mRNA expression and cigarette smoke extracts significantly counteracted this IL-1 mediated effect reducing both the activation of NFkB pathway and the interaction between NFkB and HBD2 promoter. Conclusions: This study provides new insights on the possible mechanisms involved in the alteration of innate immunity mechanisms in COPD. © 2012 Pace et al

A restatement of the natural science evidence base relevant to the control of bovine tuberculosis in Great Britain

This is the final version of the article. Available from the Royal Society via the DOI in this record.Bovine tuberculosis (bTB) is a very important disease of cattle in Great Britain, where it has been increasing in incidence and geographical distribution. In addition to cattle, it infects other species of domestic and wild animals, in particular the European badger (Meles meles). Policy to control bTB is vigorously debated and contentious because of its implications for the livestock industry and because some policy options involve culling badgers, the most important wildlife reservoir. This paper describes a project to provide a succinct summary of the natural science evidence base relevant to the control of bTB, couched in terms that are as policy-neutral as possible. Each evidence statement is placed into one of four categories describing the nature of the underlying information. The evidence summary forms the appendix to this paper and an annotated bibliography is provided in the electronic supplementary material.The project was funded by the Oxford Martin School (part of the University of Oxford), and though many groups were consulted, the project was conducted completely independently of any stakeholder