Red Blood Cell Distribution Width (RDW) Predicts COVID-19 Severity: A Prospective, Observational Study from the Cincinnati SARS-CoV-2 Emergency Department Cohort

Since previous evidence has demonstrated that red blood cell distribution width (RDW) may be a useful prognostic parameter in many critical illnesses and infectious diseases, we investigated the utility of RDW for monitoring patients with coronavirus disease 2019 (COVID-19). The study population consisted of 49 COVID-19 patients, including 16 (32.6%) with severe illness, 12 (24.5%) with severe acute kidney injury (AKI), and 8 (16.3%) requiring renal replacement therapy (RRT). The predictive value of blood tests, performed during emergency department evaluation, was then addressed. A progressive increase of RDW was observed with advancing COVID-19 severity. The area under the curve (AUC) of RDW was 0.73 for predicting severe illness, 0.80 for severe AKI, and 0.83 for RRT, respectively. In multivariate analysis, elevated RDW was associated with 9-fold and 16-fold increased odds of severe COVID-19 and AKI, respectively. The results of this study suggest that RDW should be part of routine laboratory assessment and monitoring of COVID-19

Fluoride Intake through Consumption of Tap Water and Bottled Water in Belgium

There is a tendency to align higher levels of fluoride in natural mineral water with the existing higher levels in tap water. Treatment of natural mineral waters could harm the preservation of their natural character. In this study fluoride intake through bottled and tap water consumption in the Belgian adult population was assessed, taking into account regional differences. A deterministic approach was used whereby consumption quantities of tap water and different brands of bottled water were linked with their respective fluoride concentrations. Data from the national food consumption survey (2004) were used and the Nusser methodology was applied to obtain usual intake estimates

Tetris-inspired detector with neural network for radiation mapping

In recent years, radiation mapping has attracted widespread research attention and increased public concerns on environmental monitoring. In terms of both materials and their configurations, radiation detectors have been developed to locate the directions and positions of the radiation sources. In this process, algorithm is essential in converting detector signals to radiation source information. However, due to the complex mechanisms of radiation-matter interaction and the current limitation of data collection, high-performance, low-cost radiation mapping is still challenging. Here we present a computational framework using Tetris-inspired detector pixels and machine learning for radiation mapping. Using inter-pixel padding to increase the contrast between pixels and neural network to analyze the detector readings, a detector with as few as four pixels can achieve high-resolution directional mapping. By further imposing Maximum a Posteriori (MAP) with a moving detector, further radiation position localization is achieved. Non-square, Tetris-shaped detector can further improve performance beyond the conventional grid-shaped detector. Our framework offers a new avenue for high quality radiation mapping with least number of detector pixels possible, and is anticipated to be capable to deploy for real-world radiation detection with moderate validation.Comment: 29 pages, 20 figures. Ryotaro Okabe and Shangjie Xue contributed equally to this wor

Immunization With The Maebl M2 Domain Protects Against Lethal Plasmodium Yoelii Infection.

Malaria remains a world-threatening disease largely because of the lack of a long-lasting and fully effective vaccine. MAEBL is a type 1 transmembrane molecule with a chimeric cysteine-rich ectodomain homologous to regions of the Duffy binding-like erythrocyte binding protein and apical membrane antigen 1 (AMA1) antigens. Although MAEBL does not appear to be essential for the survival of blood-stage forms, ectodomains M1 and M2, homologous to AMA1, seem to be involved in parasite attachment to erythrocytes, especially M2. MAEBL is necessary for sporozoite infection of mosquito salivary glands and is expressed in liver stages. Here, the Plasmodium yoelii MAEBL-M2 domain was expressed in a prokaryotic vector. C57BL/6J mice were immunized with doses of P. yoelii recombinant protein rPyM2-MAEBL. High levels of antibodies, with balanced IgG1 and IgG2c subclasses, were achieved. rPyM2-MAEBL antisera were capable of recognizing the native antigen. Anti-MAEBL antibodies recognized different MAEBL fragments expressed in CHO cells, showing stronger IgM and IgG responses to the M2 domain and repeat region, respectively. After a challenge with P. yoelii YM (lethal strain)-infected erythrocytes (IE), up to 90% of the immunized animals survived and a reduction of parasitemia was observed. Moreover, splenocytes harvested from immunized animals proliferated in a dose-dependent manner in the presence of rPyM2-MAEBL. Protection was highly dependent on CD4(+), but not CD8(+), T cells toward Th1. rPyM2-MAEBL antisera were also able to significantly inhibit parasite development, as observed in ex vivo P. yoelii erythrocyte invasion assays. Collectively, these findings support the use of MAEBL as a vaccine candidate and open perspectives to understand the mechanisms involved in protection.833781-379

Immunization with the MAEBL M2 domain protects against lethal Plasmodium yoelii infection

FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOMalaria remains a world-threatening disease largely because of the lack of a long-lasting and fully effective vaccine. MAEBL is a type 1 transmembrane molecule with a chimeric cysteine-rich ectodomain homologous to regions of the Duffy binding-like erythrocyte binding protein and apical membrane antigen 1 (AMA1) antigens. Although MAEBL does not appear to be essential for the survival of blood-stage forms, ectodomains M1 and M2, homologous to AMA1, seem to be involved in parasite attachment to erythrocytes, especially M2. MAEBL is necessary for sporozoite infection of mosquito salivary glands and is expressed in liver stages. Here, the Plasmodium yoelii MAEBL-M2 domain was expressed in a prokaryotic vector. C57BL/6J mice were immunized with doses of P. yoelii recombinant protein rPyM2-MAEBL. High levels of antibodies, with balanced IgG1 and IgG2c subclasses, were achieved. rPyM2-MAEBL antisera were capable of recognizing the native antigen. Anti-MAEBL antibodies recognized different MAEBL fragments expressed in CHO cells, showing stronger IgM and IgG responses to the M2 domain and repeat region, respectively. After a challenge with P. yoelii YM (lethal strain)-infected erythrocytes (IE), up to 90% of the immunized animals survived and a reduction of parasitemia was observed. Moreover, splenocytes harvested from immunized animals proliferated in a dose-dependent manner in the presence of rPyM2-MAEBL. Protection was highly dependent on CD4(+), but not CD8(+), T cells toward Th1. rPyM2-MAEBL antisera were also able to significantly inhibit parasite development, as observed in ex vivo P. yoelii erythrocyte invasion assays. Collectively, these findings support the use of MAEBL as a vaccine candidate and open perspectives to understand the mechanisms involved in protection.Malaria remains a world-threatening disease largely because of the lack of a long-lasting and fully effective vaccine. MAEBL is a type 1 transmembrane molecule with a chimeric cysteine-rich ectodomain homologous to regions of the Duffy binding-like erythr831037813792FAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOFAPESP - FUNDAÇÃO DE AMPARO À PESQUISA DO ESTADO DE SÃO PAULOCNPQ - CONSELHO NACIONAL DE DESENVOLVIMENTO CIENTÍFICO E TECNOLÓGICOsem informaçãosem informaçã

Keras R-CNN: library for cell detection in biological images using deep neural networks

Background: A common yet still manual task in basic biology research, high-throughput drug screening and digital pathology is identifying the number, location, and type of individual cells in images. Object detection methods can be useful for identifying individual cells as well as their phenotype in one step. State-of-the-art deep learning for object detection is poised to improve the accuracy and efficiency of biological image analysis. Results: We created Keras R-CNN to bring leading computational research to the everyday practice of bioimage analysts. Keras R-CNN implements deep learning object detection techniques using Keras and Tensorflow (https://github.com/broadinstitute/keras-rcnn). We demonstrate the command line tool’s simplified Application Programming Interface on two important biological problems, nucleus detection and malaria stage classification, and show its potential for identifying and classifying a large number of cells. For malaria stage classification, we compare results with expert human annotators and find comparable performance. Conclusions: Keras R-CNN is a Python package that performs automated cell identification for both brightfield and fluorescence images and can process large image sets. Both the package and image datasets are freely available on GitHub and the Broad Bioimage Benchmark Collection

Fractional solubility of iron in mineral dust aerosols over coastal Namibia: a link to marine biogenic emissions?

This paper presents the first investigation of the solubility of iron in mineral dust aerosols collected at the Henties Bay Aerosol Observatory (HBAO), in Namibia, from April to December 2017. During the study period, 10 intense dust events occurred. Elemental iron reached peak concentrations as high as 1.5 µg m−3, significantly higher than background levels. These events are attributed to wind erosion of natural soils from the surrounding gravel plains of the Namib desert. The composition of the sampled dust is found to be overall similar to that of aerosols from northern Africa but is characterized by persistent and high concentrations of fluorine which are attributed to local fugitive dust. The fractional solubility of Fe (%SFe) for both the identified dust episodes and background conditions ranged between 1.3 % and 20 % and averaged at 7.9 % (±4.1 %) and 6.8 (±3.3 %), respectively. Even under background conditions, the %SFe was correlated with that of Al and Si. The solubility was lower between June and August and increased from September onwards during the austral spring. The relation to measured concentrations of particulate MSA (methane sulfonic acid), solar irradiance, and wind speed suggests a possible two-way interaction whereby marine biogenic emissions from the coastal Benguela upwelling to the atmosphere would increase the solubility of iron-bearing dust according to the photo-reduction processes. This first investigation points to the western coast of southern Africa as a complex environment with multiple processes and active exchanges between the atmosphere and the Atlantic Ocean, requiring further research