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Quality Control01:05

Quality Control

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Quality control is one of the three cyclical quality assurance activities that help keep a system under statistical control. Typical quality control activities include creating quality control charts, conducting proficiency testing, and documenting and archiving results.
Quality control helps track data, visualize trends, and identify variations, making it easier to detect deviations that may affect the accuracy of an analysis. One way to do this is by generating a quality control chart, which...
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When the quality of water for concrete preparation is uncertain, its impact on the setting time of cement and compressive strength of mortar is assessed by comparison with de-ionized or distilled water benchmarks. American Society for Testing and Materials (ASTM) C1602 requires the setting times to be within 90 minutes of the control, British Standard (BS) 3146:1980 allows a 30-minute variance in the initial setting, while British Standards European Norm (BS EN) 1008 specifies initial setting...
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Hypothesis testing is a fundamental statistical tool that begins with the assumption that the null hypothesis H0 is true. During this process, two types of errors can occur: Type I and Type II. A Type I error refers to the incorrect rejection of a true null hypothesis, while a Type II error involves the failure to reject a false null hypothesis.
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Uncertainty in Measurement: Accuracy and Precision03:37

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Scientists typically make repeated measurements of a quantity to ensure the quality of their findings and to evaluate both the precision and the accuracy of their results. Measurements are said to be precise if they yield very similar results when repeated in the same manner. A measurement is considered accurate if it yields a result that is very close to the true or the accepted value. Precise values agree with each other; accurate values agree with a true value. 
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Base complementarity between the three base pairs of mRNA codon and the tRNA anticodon is not a failsafe mechanism. Inaccuracies can range from a single mismatch to no correct base pairing at all. The free energy difference between the correct and nearly correct base pairs can be as small as 3 kcal/ mol. With complementarity being the only proofreading step, the estimated error frequency would be one wrong amino acid in every 100 amino acids incorporated. However, error frequencies observed in...
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Reagent Tracker Dyes Permit Quality Control for Verifying Plating Accuracy in ELISPOT Tests.

Alexander Lehmann1, Zoltan Megyesi2, Anna Przybyla3,4

  • 1Research and Development Department, CTL, Shaker Heights, OH 44122, USA. alexander.lehmann@immunospot.com.

Cells
|January 6, 2018
PubMed
Summary

Enzyme-linked immune spot (ELISPOT) assays track T cell immunity but lack wet lab audit trails. A new dye-based platform enhances ELISPOT transparency by tracking reagent use and preventing errors.

Keywords:
CD4 cellsCD8 cellsImmunoSpot®RT dyesT cellsantigen screeningaudit trails for ELISPOTdeterminant mappingregulated ELISPOT

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Area of Science:

  • Immunology
  • Cellular Assays
  • Biotechnology

Background:

  • ELISPOT assays are crucial for quantifying antigen-specific T cells and assessing immune responses in various clinical settings.
  • Regulatory requirements necessitate robust audit trails for immune monitoring, including ELISPOT analysis.
  • Current ELISPOT methods lack comprehensive audit trails for the critical wet laboratory procedures, particularly pipetting.

Purpose of the Study:

  • To introduce a novel dye-based reagent tracking platform for ELISPOT assays.
  • To address the existing gap in audit trails for the wet laboratory phase of ELISPOT.
  • To enhance the transparency and reliability of ELISPOT test results.

Main Methods:

  • Development and implementation of a dye-based reagent tracking system.
  • Integration of the tracking platform into the ELISPOT assay workflow.
  • Validation of the platform's ability to monitor reagent handling and detect errors.

Main Results:

  • The dye-based platform successfully tracks reagent usage throughout the ELISPOT assay.
  • The system provides an audit trail for the wet laboratory steps, ensuring documentation of pipetting.
  • Increased transparency and assurance against pipetting errors in ELISPOT analysis.

Conclusions:

  • The developed reagent tracking platform significantly improves the integrity of ELISPOT assays.
  • This innovation addresses a critical limitation in regulated immune monitoring.
  • The platform enhances the overall reliability and regulatory compliance of ELISPOT data.