Research concepts
Reading concentration–response curves
Concentration-response curves: Does the decisive part of the curve contain observations?
Source editorial review:
Before interpreting the result
Does the decisive part of the curve contain observations?
- Read the units, linear or logarithmic scale and concentrations actually tested.
- Distinguish measured points, scatter and the line calculated by the model.
- Check whether the ends and middle region were observed or extrapolated.
Concentration-response curves
A curve contains observations and a mathematical representation; read them separately. Points show where measurements occurred, while the line summarizes a chosen model. Changing an axis scale changes visual impression without adding data. Endpoints, scatter and concentration coverage affect confidence in fitted parameters, especially where part of the response was extrapolated.
A reading case: what to check
Before copying a value from a figure, identify units, measured points and the number of independent preparations. If the graph never reaches a plateau, inspect how the fit defined its maximum. A calculated value may still be reportable, but must retain that limitation. Comparing curves also requires checking that both vertical axes describe the same response.
What to preserve in the record
A visually smooth curve does not fill gaps in the data. If the fit depends on unobserved endpoints, retain that limitation beside the parameter and examine possible assay interference.
Questions and answers
Does the decisive part of the curve contain observations?
A curve contains observations and a mathematical representation; read them separately. Points show where measurements occurred, while the line summarizes a chosen model. Changing an axis scale changes visual impression without adding data. Endpoints, scatter and concentration coverage affect confidence in fitted parameters, especially where part of the response was extrapolated.
What should the review record preserve?
A visually smooth curve does not fill gaps in the data. If the fit depends on unobserved endpoints, retain that limitation beside the parameter and examine possible assay interference.
Sources
- Quantitative high-throughput screening: a titration-based approach that efficiently identifies biological activities in large chemical libraries.
- A single-parameter logistic equation for fitting concentration-response curves from standard acute ecotoxicity assays.
- A specific mechanism for nonspecific activation in reporter-gene assays.