Observatory: A Tool for Recording, Annotating and Reviewing Emotion-Related Data

2011 ◽  
Author(s):  
Paul Salvador Inventado ◽  
Roberto Legaspi ◽  
Masayuki Numao ◽  
Merlin Suarez
Keyword(s):  
Related Data

Integrated morphometrical and electron energy loss image analysis in cytochemistry

1989 ◽  
Vol 47 ◽  
pp. 402-403
Author(s):  
W.C. de Bruijn ◽  
A.A.W. de Jong ◽  
C.W.J. Sorber
Keyword(s):  
Image Analysis ◽  
Acid Phosphatase ◽  
Chemical Analysis ◽  
Active Form ◽  
List Type ◽  
Type Number ◽  
Enzyme Cytochemistry ◽  
Related Data ◽  
Endogenous Peroxidase ◽  
Electron Energy Loss

One aspect of enzyme cytochemistry is, whether all macrophage lysosomal hydrolytical enzymes are present in an active form, or are activated upon stimulation. Integrated morphometrical and chemical analysis has been chosen as a tool to illucidate that cytochemical problem. Mouse peritoneal resident macrophages have been used as a model for this complicated integration of morphometrical and element-related data. Only aldehyde-fixed cells were treated with three cytochemical reactions to detect different enzyme activities within one cell (for details see [1,2]). The enzyme-related precipitates anticipated to be differentiated, were:(1).lysosomal barium and sulphur from aryl sulphatase activity,(2).lysosomal cerium and phosphate from acid phosphatase activity and(3).platinum/di-amino-benzidine( D A B) complex from endogenous peroxidase activity.

Quality Control of Data in a Large-Scale Cancer Register Program

1966 ◽  
Vol 05 (02) ◽  
pp. 67-74 ◽  
Author(s):  
W. I. Lourie ◽  
W. Haenszeland
Keyword(s):  
United States ◽  
Quality Control ◽  
Cancer Patients ◽  
Large Scale ◽  
The United States ◽  
Newly Diagnosed ◽  
Related Data ◽  
Cancer Register ◽  
Independent Review ◽  
End Results

Quality control of data collected in the United States by the Cancer End Results Program utilizing punchcards prepared by participating registries in accordance with a Uniform Punchcard Code is discussed. Existing arrangements decentralize responsibility for editing and related data processing to the local registries with centralization of tabulating and statistical services in the End Results Section, National Cancer Institute. The most recent deck of punchcards represented over 600,000 cancer patients; approximately 50,000 newly diagnosed cases are added annually.Mechanical editing and inspection of punchcards and field audits are the principal tools for quality control. Mechanical editing of the punchcards includes testing for blank entries and detection of in-admissable or inconsistent codes. Highly improbable codes are subjected to special scrutiny. Field audits include the drawing of a 1-10 percent random sample of punchcards submitted by a registry; the charts are .then reabstracted and recoded by a NCI staff member and differences between the punchcard and the results of independent review are noted.

How toxicity of nanomaterials towards different species could be simultaneously evaluated: Novel multi-nano-read-across approach

2017 ◽  
Author(s):  
Natalia Sizochenko ◽  
Alicja Mikolajczyk ◽  
Karolina Jagiello ◽  
Tomasz Puzyn ◽  
Jerzy Leszczynski ◽  
...  
Keyword(s):  
Missing Values ◽  
Metal Oxide Nanoparticles ◽  
Machine Learning Techniques ◽  
Self Organizing Map ◽  
Related Data ◽  
Mammalian Cell Lines ◽  
Learning Techniques ◽  
Combination Of Methods ◽  
Map Analysis ◽  
Unique Chemical

Application of predictive modeling approaches is able solve the problem of the missing data. There are a lot of studies that investigate the effects of missing values on qualitative or quantitative modeling, but only few publications have been<br>discussing it in case of applications to nanotechnology related data. Current project aimed at the development of multi-nano-read-across modeling technique that helps in predicting the toxicity of different species: bacteria, algae, protozoa, and mammalian cell lines. In this study, the experimental toxicity for 184 metal- and silica oxides (30 unique chemical types) nanoparticles from 15 experimental datasets was analyzed. A hybrid quantitative multi-nano-read-across approach that combines interspecies correlation analysis and self-organizing map analysis was developed. At the first step, hidden patterns of toxicity among the nanoparticles were identified using a combination of methods. Then the developed model that based on categorization of metal oxide nanoparticles’ toxicity outcomes was evaluated by means of combination of supervised and unsupervised machine learning techniques to find underlying factors responsible for toxicity.

How toxicity of nanomaterials towards different species could be simultaneously evaluated: Novel multi-nano-read-across approach

2017 ◽  
Author(s):  
Natalia Sizochenko ◽  
Alicja Mikolajczyk ◽  
Karolina Jagiello ◽  
Tomasz Puzyn ◽  
Jerzy Leszczynski ◽  
...  
Keyword(s):  
Missing Values ◽  
Metal Oxide Nanoparticles ◽  
Machine Learning Techniques ◽  
Self Organizing Map ◽  
Related Data ◽  
Mammalian Cell Lines ◽  
Learning Techniques ◽  
Combination Of Methods ◽  
Map Analysis ◽  
Unique Chemical

Application of predictive modeling approaches is able solve the problem of the missing data. There are a lot of studies that investigate the effects of missing values on qualitative or quantitative modeling, but only few publications have been<br>discussing it in case of applications to nanotechnology related data. Current project aimed at the development of multi-nano-read-across modeling technique that helps in predicting the toxicity of different species: bacteria, algae, protozoa, and mammalian cell lines. In this study, the experimental toxicity for 184 metal- and silica oxides (30 unique chemical types) nanoparticles from 15 experimental datasets was analyzed. A hybrid quantitative multi-nano-read-across approach that combines interspecies correlation analysis and self-organizing map analysis was developed. At the first step, hidden patterns of toxicity among the nanoparticles were identified using a combination of methods. Then the developed model that based on categorization of metal oxide nanoparticles’ toxicity outcomes was evaluated by means of combination of supervised and unsupervised machine learning techniques to find underlying factors responsible for toxicity.

Opportunities for Qualitative Analysis of Social Media Platforms in Dietetic Research and Practice

2020 ◽  
pp. 1-5
Author(s):  
Meghan Lynch ◽  
Irena Knezevic ◽  
Kennedy Laborde Ryan
Keyword(s):  
Social Media ◽  
Low Cost ◽  
Online News ◽  
News Article ◽  
Discussion Forums ◽  
Research And Practice ◽  
The Public ◽  
Related Data ◽  
Social Media Platforms ◽  
Article Comment

To date, most qualitative knowledge about individual eating patterns and the food environment has been derived from traditional data collection methods, such as interviews, focus groups, and observations. However, there currently exists a large source of nutrition-related data in social media discussions that have the potential to provide opportunities to improve dietetic research and practice. Qualitative social media discussion analysis offers a new tool for dietetic researchers and practitioners to gather insights into how the public discusses various nutrition-related topics. We first consider how social media discussion data come with significant advantages including low-cost access to timely ways to gather insights from the public, while also cautioning that social media data have limitations (e.g., difficulty verifying demographic information). We then outline 3 types of social media discussion platforms in particular: (i) online news article comment sections, (ii) food and nutrition blogs, and (iii) discussion forums. We discuss how each different type of social media offers unique insights and provide a specific example from our own research using each platform. We contend that social media discussions can contribute positively to dietetic research and practice.

Is Alzheimer disease a failure of mobilizing immune defense? Lessons from cognitively fit oldest-old

2019 ◽  
Vol 21 (1) ◽  
pp. 7-19 ◽  
Keyword(s):  
Alzheimer Disease ◽  
Cognitive Aging ◽  
Oldest Old ◽  
Adaptive Immune Response ◽  
Effector T Cells ◽  
Immune Defense ◽  
Supporting Evidence ◽  
Therapeutic Approaches ◽  
Related Data ◽  
Adaptive Immune

Multifaceted evidence supports the hypothesis that inflammatory-immune mechanisms contribute to Alzheimer disease (AD) neuropathology and genetic association of several immune specific genes (TREM2, CR1, and CD33) suggests that maladaptive immune responses may be pivotal drivers of AD pathogenesis. We reviewed microglia-related data from postmortem AD studies and examined supporting evidence from AD animal models to answer the following questions: i) What is the temporal sequence of immune activation in AD progression and what is its impact on cognition? ii) Are there discordant, "primed", microglia responses in AD vs successful cognitive aging? iii) Does central nervous system (CNS) repair in aging depend on recruitment of the elements of cellular adaptive immune response such as effector T cells, and can the recruitment of systemic immune cells ameliorate AD neuropathology? iv) How effective are the immune-system-based therapeutic approaches currently employed for the treatment of AD?

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