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What is Variation?01:14

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Apart from the measures of central tendency, distribution, outliers, and the changing characteristics of data with time, an important characteristic of any data set is its variation or spread. In some data sets, the data values are concentrated closely near the mean; in others, the data values are more widely spread out from the mean.
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In the field of psychology, there are several ways to organize measurements of a trait, feature, or characteristic (i.e., variables). Qualitative data, such as ethnicity, can be tabulated into a frequency count to provide information about the proportion, as well as the variety of groups in a sample or population. On the other hand, researchers can perform a wider set of calculations on quantitative data. The mean, mode, and median, for instance, are central tendency measures to identify a...
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Genotypic Identification of Cystoisospora in Immunocompromised Patients Using Tm-Variation Analysis.

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Area of Science:

  • Medical Parasitology
  • Molecular Diagnostics
  • Infectious Diseases

Background:

  • Cystoisospora causes significant illness in immunocompromised individuals.
  • Conventional PCR aids diagnosis but requires refinement for differential molecular identification of cystoisosporiasis.
  • Melting curve analysis (MCA) presents a potential advancement for molecular diagnosis.

Purpose of the Study:

  • To evaluate the efficacy of real-time PCR coupled with melting curve analysis (qPCR-MCA) for diagnosing and genotyping Cystoisospora.
  • To compare qPCR-MCA with conventional PCR and microscopy for Cystoisospora detection.
  • To investigate the genetic diversity and prevalence of Cystoisospora genotypes in immunocompromised patients in Egypt.

Main Methods:

  • Collected 293 diarrheic stool samples from oncology patients.
  • Performed microscopy, nested PCR (nPCR), and qPCR targeting the ITS2 rRNA gene.
  • Utilized melting temperature (Tm) analysis post-qPCR for genotyping and compared results with PCR-RFLP.

Main Results:

  • qPCR detected Cystoisospora in 10.9% of samples, higher than microscopy (3.1%) and nPCR (5.8%).
  • qPCR-MCA identified two distinct Cystoisospora genotypes with specific melting peaks (85.8°C and 88.6°C), indicating genetic variation.
  • Genotype II was more prevalent (65.6%), found in various cancer patients, while Genotype I was more common in lymphomas and mammary tumors.

Conclusions:

  • qPCR-MCA provides a direct, reliable method for identifying and differentiating Cystoisospora species and genotypes.
  • This technique is valuable for rapid screening of Cystoisospora genotypes, particularly in high-risk immunocompromised populations.
  • The study highlights the potential role of specific genotypes in the development of cystoisosporiasis in immunocompromised patients.