Elevated neutrophil-lymphocyte ratio is associated with high rates of ICU mortality, length of stay, and invasive mechanical ventilation in critically ill patients with COVID-19 : NRL and severe COVID-19.

Neutrophil and lymphocyte ratio (NLR) has emerged as a complementary marker in intensive care. This study aimed to associate high NLR values with mortality as the primary outcome, and length of stay and need for invasive mechanical ventilation as secondary outcomes, in critically ill patients with COVID-19. A cross-sectional study encompassing 189 critically ill patients with COVID-19 was performed.

Genetic Ablation of the Inducible Form of Nitric Oxide in Male Mice Disrupts Immature Neuron Survival in the Adult Dentate Gyrus.

Inducible nitric oxide synthase (iNOS) is an enzyme upregulated in the brain during neuroimmune stimuli which is associated with an oxidative and pro-inflammatory environment in several brain regions, including the hippocampal formation and the prefrontal cortex. The dentate gyrus of the hippocampal formation is the site of a process known as adult hippocampal neurogenesis (AHN). Although many endogenous and extrinsic factors can modulate AHN, the exact participation of specific proinflammatory mediators such as iNOS in these processes remains to be fully elucidated.

Understanding and improving the quality and reproducibility of Jupyter notebooks.

Jupyter Notebooks have been widely adopted by many different communities, both in science and industry. They support the creation of literate programming documents that combine code, text, and execution results with visualizations and other rich media. The self-documenting aspects and the ability to reproduce results have been touted as significant benefits of notebooks.

PipelineProfiler: A Visual Analytics Tool for the Exploration of AutoML Pipelines.

In recent years, a wide variety of automated machine learning (AutoML) methods have been proposed to generate end-to-end ML pipelines. While these techniques facilitate the creation of models, given their black-box nature, the complexity of the underlying algorithms, and the large number of pipelines they derive, they are difficult for developers to debug. It is also challenging for machine learning experts to select an AutoML system that is well suited for a given problem.

Exploring Reproducibility in Visualization.

The American National Academies of Sciences, Engineering, and Medicine (NASEM) has recently released the report "Reproducibility and Replicability in Science." The report has prompted discussions within many disciplines about the extent of the current adoption of reproducibility and replicability, the challenges involved in publishing reproducible results as well as strategies for improving. We organized a panel at the IEEE VIS conference 2019 to start a discussion on the reproducibility challenges faced by the visualization community and how those challenges might be addressed.

Nutritional assay Pereskia spp.: unconventional vegetable.

Pereskia grandifolia Haworth (PGH) and Pereskia aculeata Miller (PAM) are recognized sources of proteins; dietary fiber; vitamins and minerals make this plant leaves, raw, cooked, and braised, an important ally against protein and micronutrient deficiencies. One of the main problems is the presence of antinutritional factors that may interfere in the digestibility and bioavailability of some nutrients. The objective was to evaluate the amino acid profile and the chemical score of the raw leaves and the effects of heating media and time on the total dietary fiber, minerals, trypsin inhibition, oxalic acid and tannins of leaves of PGH and PAM.

Spatio-Temporal Urban Data Analysis: A Visual Analytics Perspective.

Visual analytics systems can greatly help in the analysis of urban data allowing domain experts from academia and city governments to better understand cities, and thus enable better operations, informed planning and policies. Effectively designing these systems is challenging and requires bringing together methods from different domains. In this paper, we discuss the challenges involved in designing a visual analytics system to interactively explore large spatio-temporal data sets and give an overview of our research that combines visualization and data management to tackle these challenges.

ARIES: Enabling Visual Exploration and Organization of Art Image Collections.

Art historians have traditionally used physical light boxes to prepare exhibits or curate collections. On a light box, they can place slides or printed images, move the images around at will, group them as desired, and visual-ly compare them. The transition to digital images has rendered this workflow obsolete.

Visually Exploring Transportation Schedules.

Public transportation schedules are designed by agencies to optimize service quality under multiple constraints. However, real service usually deviates from the plan. Therefore, transportation analysts need to identify, compare and explain both eventual and systemic performance issues that must be addressed so that better timetables can be created.

Using Topological Analysis to Support Event-Guided Exploration in Urban Data.

The explosion in the volume of data about urban environments has opened up opportunities to inform both policy and administration and thereby help governments improve the lives of their citizens, increase the efficiency of public services, and reduce the environmental harms of development. However, cities are complex systems and exploring the data they generate is challenging. The interaction between the various components in a city creates complex dynamics where interesting facts occur at multiple scales, requiring users to inspect a large number of data slices over time and space.

Structured Open Urban Data: Understanding the Landscape.

A growing number of cities are now making urban data freely available to the public. Besides promoting transparency, these data can have a transformative effect in social science research as well as in how citizens participate in governance. These initiatives, however, are fairly recent and the landscape of open urban data is not well known.

Analysis of HFE genes C282Y, H63D, and S65D in patients with hyperferritinemia from northeastern Brazil.

Background: Hereditary hemochromatosis (HH) is a genetic disease caused by the high absorption and deposition of iron in several organs. This accumulation results in several clinical complications such as cirrhosis, arthritis, cardiopathies, diabetes, sexual disorders, and skin darkening. The H63D and C282Y mutations are well defined in the HH etiology.

Visual exploration of big spatio-temporal urban data: a study of New York City taxi trips.

As increasing volumes of urban data are captured and become available, new opportunities arise for data-driven analysis that can lead to improvements in the lives of citizens through evidence-based decision making and policies. In this paper, we focus on a particularly important urban data set: taxi trips. Taxis are valuable sensors and information associated with taxi trips can provide unprecedented insight into many different aspects of city life, from economic activity and human behavior to mobility patterns.

Banding cytogenetic analysis in pediatric patients with acute lymphoblastic leukemia (ALL) in a Brazilian population.

Background: Cytogenetic studies in Brazilian population about childhood acute lymphoblastic leukemia (ALL), the most common childhood malignancy, are scarce. Moreover, Brazilian race is very heterogeneous and is made by the confluence of people of several different origins, from the original Native Brazilians, with the influx of Portuguese colonizers, Black African slaves, and recent European, Arab and Japanese immigration. The purpose of this prospective, multicentric study was to assess the sociodemographic, clinic and cytogenetic characteristics of the children treated for ALL in the Northeast region of Brazil.

Flow cytometry immunophenotyping evaluation in acute lymphoblastic leukemia: correlation to factors affecting clinic outcome.

The authors conducted a flow cytometry immunophenotyping study in patients with acute lymphoblastic leukemia (ALL) from Natal, Rio Grande do Norte, Brazil. The patients (n = 126) were newly diagnosed using a panel of monoclonal antibodies: CD1a, CD2, CD3, CD4, CD7, CD8, CD10, CD13, CD33, CD14, CD19, CD22, CD79a, CD117, CD34, anti-IgM, anti-TdT, anti-HLA-Dr, and anti-human kappa and lambda light chains. Additional data, such as patients' age and gender, clinical and laboratory findings such as presence of tumor masses, lymphadenopathy, hepatomegaly, splenomegaly, leukemic infiltration in the central nervous system (CNS) were also investigated.

BirdVis: visualizing and understanding bird populations.

Birds are unrivaled windows into biotic processes at all levels and are proven indicators of ecological well-being. Understanding the determinants of species distributions and their dynamics is an important aspect of ecology and is critical for conservation and management. Through crowdsourcing, since 2002, the eBird project has been collecting bird observation records.

Clinical course of choroidal neovascularization secondary to angioid streaks treated with intravitreal bevacizumab.

Background And Objective: To evaluate visual acuity and anatomical outcomes of choroidal neovascularization (CNV) associated with angioid streaks after treatment with intravitreal bevacizumab injections.

Patients And Methods: Best-corrected visual acuity, optical coherence tomography measurements (OCT), fluorescein and indocyanine green angiography, and ophthalmoscope examination at baseline and at each follow-up visit were performed. Five patients with CNV associated with angioid streaks were treated with injections of intravitreal bevacizumab (1.

Novel Zn2+-binding sites in human transthyretin: implications for amyloidogenesis and retinol-binding protein recognition.

Human transthyretin (TTR) is a homotetrameric protein involved in several amyloidoses. Zn(2+) enhances TTR aggregation in vitro, and is a component of ex vivo TTR amyloid fibrils. We report the first crystal structure of human TTR in complex with Zn(2+) at pH 4.

VisMashup: streamlining the creation of custom visualization applications.

Visualization is essential for understanding the increasing volumes of digital data. However, the process required to create insightful visualizations is involved and time consuming. Although several visualization tools are available, including tools with sophisticated visual interfaces, they are out of reach for users who have little or no knowledge of visualization techniques and/or who do not have programming expertise.

VisComplete: automating suggestions for visualization pipelines.

Building visualization and analysis pipelines is a large hurdle in the adoption of visualization and workflow systems by domain scientists. In this paper, we propose techniques to help users construct pipelines by consensus--automatically suggesting completions based on a database of previously created pipelines. In particular, we compute correspondences between existing pipeline subgraphs from the database, and use these to predict sets of likely pipeline additions to a given partial pipeline.

Querying and creating visualizations by analogy.

While there have been advances in visualization systems, particularly in multi-view visualizations and visual exploration, the process of building visualizations remains a major bottleneck in data exploration. We show that provenance metadata collected during the creation of pipelines can be reused to suggest similar content in related visualizations and guide semi-automated changes. We introduce the idea of query-by-example in the context of an ensemble of visualizations, and the use of analogies as first-class operations in a system to guide scalable interactions.