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Visual informations obtained from
standard curve
Just looking at a normal standard curve can give some very useful information on assay performance since different assay conditions give rise to different types of deviation from the normal standard curve.
different types of deviation from the normal standard curve are as cited below:
a) A normal standard curve
b) Highly irregular standard curve
c) Distorted standard curve
d) Steep standard curve
e) Broad standard curve
f) Shallow standard curve
g) High standard curve
Trouble shooting in normal standard
curve and possible remedy
There are different types of trouble shootings in normal standard curve and we have possible remedy as below:
a) A normal standard curve: We hope that all our assays will look like this.
b) Highly irregular standard curve: Indicating faulty experimental technique.
c) Distorted standard curve (Particularly at low dose): Indicates incomplete saturation of the antibody. Check the preparation of the working dilution of the antibody.
d) Steep standard curve (at low dose): Indicates that the amount of labeled analyte is too low for the range of standards used. Check the preparation of labelled analyte and /or the standards.
Diagrammatic view of different types
of standard curve
A normal standard curve
a) We hope that all our assays will look like this.
Diagrammatic view of different types
of standard curve Cont’d
Highly irregular standard curve
b) Indicating faulty experimental technique.
Diagrammatic view of different types
of standard curve Cont’d
Steep standard curve
d) Indicates that the amount of labeled analyte is too low for the range of standards used. Check the preparation of labelled analyte and /or the standards.
Diagrammatic view of different types
of standard curve Cont’d
Broad standard curve
e) Indicates that the amount of labelled analyte is too high for the range of standards used ( or may also be due to incomplete saturation of the antibody). Check the preparation of the labelled analyte and/or the standards (and/or the antibody).
Diagrammatic view of different types
of standard curve Cont’d
High standard curve
f) Indicates inadequate separation of bound from free analyte. Check the separation procedure.
Non-statistical concepts in RIA
Counting rate (c): It is the number of counts per minute (ct/min) recorded by the counter. Example: A total activity tube (that is, a counting tube containing the full amount of tracer which was added to each tube at the beginning of the assay) yields 75000 counts in a counting period of 3 minutes. Its counting rate is c= 75000ct/3 min= 25000 ct/min. Example: An assay tube (either a standard or an unknown) yields a 15076 counts in a 3 minutes. Its counting rate is c= 15076ct/3min= 5025ct/min. Normalised counting rate (p): It is counting rate as a proportion of the mean counting rate measured on the total activity tube (s). It is expressed numerically as 100 times the ratio (sample counting rate) / ( total activity counting rate). Example: The above assay tube yields a normalise dcounting rate of p= 5025ct/min / 25000 ct/min*100= 20.
Statistical concepts in RIA
Mean: The mean (or average) of a set of replicate
results is equal to the sum of all the results
divided by the number of results.
Example: If duplicate tubes yield P= 20.1 and
20.7, respectively, the mean P is given by
P= 20.1+ 20.7/2= 20.
Example: If the derived analyte concentration x in
the above 2 tubes was 10.5ng/ml and 9.7ng/ml,
respectively, the mean x is given by
x= 10.5+9.7/2= 10.1ng/ml
Statistical concepts in RIA
Standard Deviation (SD): It is the measure of
amount of scatter among replicates.
Number of degree of freedom (F): It is a statistical
concept relating to the number of independent
quantities in a calculation.
Example: In the above calculation of SD, the
number of degree of freedom (F), is equal to r-
1; therefore are r independent replicate results,
but one degree of freedom is lost.
Statistical concepts in RIA Cont’d
Coefficient of variation of the mean (CVM): The
CVM is the standard deviation of the mean
expressed as a percentage of the mean:
Example: For the same two replicate tubes,
CVM of p = 0.30/20.4*100%= 1.5%
Counting statistics error (S): It is related to the
number of counts collected
Example: S= 100/√n%
Statistical concepts in RIA Cont’d
Non-counting statistics error (R): Errors other than counting statistics error (R) is called as Non-counting statistics error.
Overall CV^2 = R^2 + S^2
The errors R and S, which are independent of each other, are thus said to add in quadrature- there squared values add togathere. We can alternatively write: R^2 = Overall CV^2 - S^2
Example: The observed CV in the example is 2.1% , for a replicate pair of the tubes having a counting statistics CV for each tube of 0.8% is: R^2 = 2.1^2 – 0.8^2 = 3.
Weighted R^2 (H): F * R^2 (where F: Degree of freedom)
