- After selecting file, please be patient while results are generated.
Before uploading a new calibration dataset please click the 'START AGAIN' button below to clear previously uploaded values. For full report with all calculated values please select 'DOWNLOAD RESULTS' checkbox below. - Default for Tecan Spark M10 microplate reader and 96-well, black, flat bottom microplates (cat. no. 30122298, Tecan, Austria).
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Input for ZINFE & NINFE
CALIBRATION
READOUT
Finanancial support provided through Croatian Science Foundation grant no. UIP-2017-05-9537 "Glycosylation as a factor in the iron transport mechanism of human serum transferrin" GlyMech at University of Zagreb Faculty of Pharmacy and Biochemistry.
Continuing support is provided through Croatian Science Foundation grant no. UIP 2020-02-4857 "Light-Driven Functionalization of Unreactive Sites Using Oxidative Amination" LIGHT-N-RING at University of Zagreb Faculty of Pharmacy and Biochemistry.
Additional support was provided by the European Structural and Investment Funds for the “Croatian National Centre of Research Excellence in Personalized Healthcare” (contract #KK.01.1.1.01.0010), “Centre of Competences in Molecular Diagnostics” (contract #KK.01.2.2.03.0006), and the European Regional Development Fund grant for “Strengthening of Scientific Research and Innovation Capacities of the Faculty of Pharmacy and Biochemistry at the University of Zagreb” (FarmInova, contract #KK.01.1.1.02.0021).
Introduction to ZINFE & NINFE
Friganović, Šakić, Weitner, 2020.-2022.
Corrector function to eliminate inner filter effect for fluorescence measurements in microplates using variable z-positions.
For absorbance inner filter effect corrections, go to AINFE.
For more information please consult published paper:
Weitner, T.; Friganović, T.; Šakić, D.
Inner Filter Effect Correction for Fluorescence Measurements in Microplates Using Variable Vertical Axis Focus.
Analytical Chemistry, 2022. doi:10.1021/acs.analchem.2c01031
Raw data can be found here: doi:10.5281/zenodo.5849302
Data should be formatted as:
Output data (from above calibration) is formatted as:
Example test file can be downloaded here.
For more inputs, use this link.
For details about data formatting, export and updates about the method please contact davor.sakic@pharma.unizg.hr.
Help from Mario Gabričević (discussion), Tino Šeba, Valentina Borko, and Robert Kerep (testing) is greatly appreciated.
NOTES
r2: the coefficient of determination representing the proportion of the variance of the dependent variable that is explained by an independent variable(s) in a regression model.
rmsre: root mean squared relative error.
steyx: the standard error of the estimated dependent variable y in a simple linear regression model.
LOD: limit of detection corresponding to the lowest quantity of a substance that can be differentiated from the blank sample (absence of the substance) at a given confidence level.
mErr%: the percentage error of the slope of the line of corrected fluorescence, as compared to the slope of the ideal dependence derived from Beer-Lambert law.
Calibration range: range of concentrations used for calibration (lowest-highest).
Correction range: range of concentrations applicable for correction (LOD-highest).
Parametric model (Pm): Corrected fluorescence were obtained via three parameter equation. Further details will be available pending method publication.
Black-box model (BBm) optimization: Performed by evaluation of the r2 value of a linear regression for a set of equally distributed coefficients in a chosen starting range. Distribution of coefficients within the range is defined by stepsize; larger stepsize equals rougher grid. After each cycle, the coefficient with highest r2 value was taken as a starting point for the next cycle with finer grid (smaller stepsize) and equal number of steps. Optimization was stopped if difference in r2 between two subsequent cycles is less than 10-6, or after 20 cycles.
CREDITS
Idea: Tin Weitner, 2020.-2022.
Created by: Tin Weitner, Tomislav Friganović, and Davor Šakić, 2021.
Python version: Tomislav Friganović, 2021.
Web adaptation by: Davor Šakić, 2021.-2022.
Funding: HrZZ, GlyMech, 2021.-2022., LIGHT-N-RING 2022.