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Related Concept Videos

Sampling Continuous Time Signal01:11

Sampling Continuous Time Signal

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In signal processing, a continuous-time signal can be sampled using an impulse-train sampling technique, followed by the zero-order hold method. Impulse-train sampling involves the use of a periodic impulse train, which consists of a series of delta functions spaced at regular intervals determined by the sampling period. When a continuous-time signal is multiplied by this impulse train, it generates impulses with amplitudes corresponding to the signal's values at the sampling points.
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Contaminants and Errors01:16

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Effective sample preparation is crucial for accurate and reliable laboratory analysis. During this process, two significant sources of error can arise: concentration bias from improper sample splitting and contamination caused by methods used to reduce particle size, such as grinding or homogenization. Identifying and minimizing these potential errors is crucial to ensuring the validity of the analysis.
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Noncompartmental Analysis: Mean Residence Time01:05

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According to statistical moment theory, mean residence time (MRT) is an important measure in pharmacokinetics. MRT can be defined as the expected mean of a probability density function distribution. It provides valuable insights into drug disposition in the body.
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Sample preparation is an essential step in the analytical process. It involves preparing a sample so that it can be analyzed accurately. The goal is to extract the analyte, the substance you want to measure, from the sample while removing any components that may interfere with the analysis. Sample preparation techniques vary depending on the physical state of the sample.
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When drugs are administered extravascularly, a comprehensive evaluation through noncompartmental analysis becomes imperative. This analytical approach considers various parameters that play a crucial role in understanding the pharmacokinetics of these drugs.
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Laboratory contamination over time during low-biomass sample analysis.

Laura S Weyrich1,2, Andrew G Farrer1, Raphael Eisenhofer1,2

  • 1Australian Centre for Ancient DNA, University of Adelaide, Adelaide, South Australia, Australia.

Molecular Ecology Resources
|March 20, 2019
PubMed
Summary

Laboratory contaminants can outnumber target microbes in low-biomass samples. This study characterized long-term bacterial contamination in ancient DNA and molecular labs, finding unique profiles and seasonal variations. Commercial kits showed higher diversity than homemade methods.

Keywords:
ancient DNAcontaminantcontaminationmetagenomicsmicrobiomemicrobiota

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Area of Science:

  • Microbiology
  • Genomics
  • Environmental Science

Background:

  • Bacteria are ubiquitous and diverse, posing challenges in low-biomass sample analysis.
  • Contaminants can outnumber endogenous microorganisms in sensitive studies.
  • Understanding laboratory contamination is crucial for high-throughput studies.

Purpose of the Study:

  • To characterize long-term bacterial contaminant diversity in molecular and ultraclean ancient DNA laboratories.
  • To compare contaminant profiles between a homemade and a commercial DNA extraction kit.
  • To provide strategies for mitigating laboratory contamination in metagenomic studies.

Main Methods:

  • Analysis of 144 negative control samples (extraction blanks, no-template controls) over 5 years.
  • Comparison of contaminant profiles from typical molecular labs and an ultraclean ancient DNA lab.
  • Evaluation of contaminant content from a homemade silica-based extraction versus a commercial kit.

Main Results:

  • The ultraclean ancient DNA lab exhibited a unique contaminant profile, varying by researcher, month, and season.
  • The commercial DNA extraction kit contained higher microbial diversity and human-associated taxa compared to the homemade kit.
  • Contaminant diversity was characterized over a 5-year period.

Conclusions:

  • Laboratory contaminant profiles differ between specialized and general molecular labs.
  • Extraction methods significantly impact the diversity and type of detected contaminants.
  • Implementing extraction blank controls and reporting contamination assessments are recommended for low-biomass metagenomic studies.