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Related Concept Videos

Interpreting Run Charts01:25

Interpreting Run Charts

Run charts, essentially line graphs plotted over time, serve as fundamental yet effective tools for process analysis. They chronicle data sequentially, facilitating the identification of trends, shifts, or cyclical movements. This graphical representation is instrumental in determining whether a process is stable or exhibits signs of potential instability indicative of special cause variation. In the healthcare domain, run charts depict infection rates over time, enabling hospitals to monitor...
Run Charts01:12

Run Charts

Run charts serve as an essential instrument for visualizing the performance of various processes over time, enabling the identification of trends and patterns crucial for quality improvement. These charts map out a series of data points chronologically, offering insights into the stability and efficiency of a process. A run chart's creation involves plotting data points on a graph, with the time intervals on the horizontal axis and the specific measurements on the vertical axis. For example,...
Interpreting R Charts01:22

Interpreting R Charts

R chart, or range chart, is a fundamental tool in statistical process control used to monitor the variability within a process. It complements the X-bar (x̄) chart by focusing on the range of the data, rather than individual values, providing a clear picture of the process dispersion over time.
An R chart plots the range of subsets of measurements collected from a process. Each point on the chart represents the range—defined as the difference between the maximum and minimum values—of a sample...
The R Chart01:02

The R Chart

In statistical process control, control charts, particularly R charts, are instrumental in monitoring process variations and identifying non-random patterns that run charts might miss. R charts track the variability within process subgroups, which is crucial when standard deviation use is impractical or unknown process variations exist.
R charts are pivotal for pinpointing shifts in process variability. Stability is indicated when all data points remain within the defined upper and lower...

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Related Experiment Video

Updated: May 23, 2026

Analysis of Raw and Processed Cyperi Rhizoma Samples Using Liquid Chromatography-Tandem Mass Spectrometry in Rats with Primary Dysmenorrhea
07:36

Analysis of Raw and Processed Cyperi Rhizoma Samples Using Liquid Chromatography-Tandem Mass Spectrometry in Rats with Primary Dysmenorrhea

Published on: December 23, 2022

[KRAS analysis management: Process and delays].

Nadège Lapeyrere1, Simone Mathoulin-Pélissier, Jean-Philippe Merlio

  • 1Réseau de cancérologie d'Aquitaine, Bordeaux, France.

Annales De Pathologie
|April 24, 2012
PubMed
Summary
This summary is machine-generated.

Delays in molecular cancer analysis, particularly for KRAS gene mutations, can disadvantage patients. Streamlining pre-analytical steps and implementing electronic procedures are crucial for faster results.

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Fully Processed Recombinant KRAS4b: Isolating and Characterizing the Farnesylated and Methylated Protein

Published on: January 16, 2020

Related Experiment Videos

Last Updated: May 23, 2026

Analysis of Raw and Processed Cyperi Rhizoma Samples Using Liquid Chromatography-Tandem Mass Spectrometry in Rats with Primary Dysmenorrhea
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Analysis of Raw and Processed Cyperi Rhizoma Samples Using Liquid Chromatography-Tandem Mass Spectrometry in Rats with Primary Dysmenorrhea

Published on: December 23, 2022

Fully Processed Recombinant KRAS4b: Isolating and Characterizing the Farnesylated and Methylated Protein
07:08

Fully Processed Recombinant KRAS4b: Isolating and Characterizing the Farnesylated and Methylated Protein

Published on: January 16, 2020

Area of Science:

  • Oncology
  • Molecular Genetics
  • Clinical Pathology

Background:

  • Anti-cancer therapies increasingly rely on detecting specific genetic alterations for personalized treatment.
  • Early determination of these genetic markers is essential to avoid patient disadvantage.
  • The Aquitaine platform of molecular tumour genetics (PGMC) initiated a program to assess and enhance molecular analysis organization in 2009.

Purpose of the Study:

  • To describe the molecular cancer analysis process, including KRAS gene analysis.
  • To evaluate the organization of pathology laboratories involved in these analyses.
  • To identify and quantify delays within the different phases of the molecular analysis workflow.

Main Methods:

  • A working group was formed to map the steps from analysis prescription to report generation.
  • A retrospective study of the first quarter of 2009 was conducted to measure management delays.
  • A questionnaire assessed pathology laboratory organization to pinpoint factors causing delays.

Main Results:

  • The median turnaround time from analysis prescription to result was 15 days (range: 7-78 days).
  • Identified delays originated from pathology labs (e.g., delayed sample submission, standard mail) and the PGMC (e.g., re-testing, new extractions).
  • Specific pre-analytical practices significantly contributed to extended turnaround times.

Conclusions:

  • There is a critical need to accelerate pre-analytical phases in molecular diagnostics.
  • Implementing electronic procedures can improve efficiency and reduce reporting times.
  • Establishing regional facilities may enhance the speed and accessibility of molecular analysis results for clinicians.