Experimental Strategies for Increasing Knowledge

2014 ◽  
pp. 581-594
Keyword(s):  
Increasing Knowledge ◽  
Experimental Strategies

scholarly journals A roadmap for metagenomic enzyme discovery

2021 ◽  
Author(s):  
Serina L. Robinson ◽  
Jörn Piel ◽  
Shinichi Sunagawa
Keyword(s):  
Biosynthetic Enzymes ◽  
Functional Metagenomics ◽  
Enzyme Discovery ◽  
Experimental Strategies

Shotgun metagenomic approaches to uncover new enzymes are underdeveloped relative to PCR- or activity-based functional metagenomics. Here we review computational and experimental strategies to discover biosynthetic enzymes from metagenomes.

Experimental strategies on enhancing toxic gases uptake of metal–organic frameworks

2021 ◽  
Vol 430 ◽  
pp. 213738
Author(s):  
Ehsan Binaeian ◽  
El-Sayed M. El-Sayed ◽  
Mojtaba Khanpour Matikolaei ◽  
Daqiang Yuan
Keyword(s):  
Metal Organic Frameworks ◽  
Toxic Gases ◽  
Metal Organic ◽  
Experimental Strategies

scholarly journals 4367 Exploratory evaluation of an online educational intervention for JUUL use

2020 ◽  
Vol 4 (s1) ◽  
pp. 30-31
Author(s):  
Eleanor L S Leavens ◽  
Matthew J. Carpenter ◽  
Tracy T. Smith ◽  
Nikki Nollen
Keyword(s):  
Young Adults ◽  
Educational Intervention ◽  
Risk Perceptions ◽  
Educational Interventions ◽  
Product Knowledge ◽  
Motivation To Change ◽  
Individual Level ◽  
Increasing Knowledge ◽  
Readiness To Quit ◽  
Amazon's Mechanical Turk

OBJECTIVES/GOALS: Initiation of JUUL use by young adults is one of the most significant issues of concern within the debate on vaping. Despite the proliferation of products and the surge in prevalence, no studies have investigated individual-level interventions or prevention strategies for pod-mod use. METHODS/STUDY POPULATION: Participants (N = 947) were young adults (<30 years old) recruited from Amazon’s Mechanical Turk based on smoking (never, former, and current smokers) and JUUL use status (never and current users), resulting in 6 use groups. In a pre-post design, participants completed baseline assessments, were presented with a brief JUUL-specific educational intervention, and completed post-assessment measures. The one-page intervention provided basic information about JUUL and stated that JUUL is harmful to non-smokers but could be beneficial to smokers if they completely switch. Primary outcomes were changes in JUUL knowledge, perceived harmfulness, intentions for future use, and motivation to change. RESULTS/ANTICIPATED RESULTS: Participants (Mage = 26.1) were male (57%) and White (75%). Overall, the intervention increased JUUL-related knowledge, risk perceptions, commitment to quitting, and readiness to quit JUUL (ps<.01). Similarly, participants showed decreased interest in future JUUL use, interest in purchasing JUUL, and interest in future regular use (ps<.01). Non-JUUL users showed decreased interest in initiating JUUL use after viewing the intervention (p<.01). There were significant Time X Group interactions for JUUL-related knowledge (p<.001), with never JUUL/never smokers showing the greatest increase in product knowledge following the intervention. However, no other interaction effects were significant. DISCUSSION/SIGNIFICANCE OF IMPACT: The intervention was effective in increasing knowledge and risk perceptions while reducing intentions for future use. The intervention was most effective in increasing knowledge among non-users, suggesting that brief educational interventions may be useful tools for preventing pod-mod initiation. CONFLICT OF INTEREST DESCRIPTION: Dr. Carpenter has received consulting honoraria from Pfizer. All other authors have no conflicts to disclose.

scholarly journals Enabling Proteomics: The Need for an Extendable ‘Workbench’ for User-Configurable Solutions

2004 ◽  
Vol 5 (1) ◽  
pp. 52-55 ◽  
Author(s):  
Robert J. Beynon
Keyword(s):  
Data Analysis ◽  
Data Reduction ◽  
Quantitative Data ◽  
Data Gathering ◽  
Qualitative And Quantitative ◽  
Proteomics Tool ◽  
Experimental Strategies

Proteomics has the capability to generate overwhelming quantities of data in relatively short timescales, and it is not uncommon to see experimenters investing substantially more time in data analysis than in data gathering. Although several sophisticated tools for data reduction and analysis are available, they lack the flexibility to cope with increasingly innovative experimental strategies and new database resources that encode both qualitative and quantitative data. I will outline a specification of a flexible proteomics tool that could address many current bottlenecks and deficiencies.

Sign in / Sign up

Export Citation Format

Share Document