Fit Parameters
Fit Parameters - Related Videos
01:58
Studying the Permeation of FITC and FITC-Ferritin through an In Vitro Blood-Brain Barrier Model
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2025
This video demonstrates a method to study permeation through an in vitro blood-brain barrier (BBB) model using astrocytes and endothelial cells on a membrane insert, with free FITC and FITC-loaded ferritin. FITC-ferritin bound to receptors on endothelial cells and crossed the membrane barrier to the lower chamber while free FITC showed restricted permeation and remained in the upper chamber.
02:56
FITC-Dextran Feeding: A Method to Quantify Intestinal Permeability in C. elegans
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2023
This video introduces a method of to visualize and measure the integrity of the C. elegans intestine lumen by feeding worms FITC-labeled dextran. The example protocol shows the assay done with 3,3’-diindolylmethane (DIM)-treated and pathogen-fed worms.
11:13
In Vitro Permeation of FITC-loaded Ferritins Across a Rat Blood-brain Barrier: a Model to Study the Delivery of Nanoformulated Molecules
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Cited by 15 •
2016
A method to establish an in vitro model of blood-brain barrier based on a co-culture of rat brain microvascular endothelial cells and astrocytes is described and validated. This system proved to be a valid tool to study the effect of nanoformulation on the trans-barrier permeation of fluorescent molecules.
04:50
Imaging FITC-dextran as a Reporter for Regulated Exocytosis
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Cited by 10 •
2018
Here we detail a method for live cell imaging of regulated exocytosis. This method utilizes FITC-dextran, which accumulates in lysosome-related organelles, as a reporter. This simple method also allows distinguishing between different modes of regulated exocytosis in cells that are difficult to manipulate genetically.
01:10
Wave Parameters
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2023
The simplest mechanical waves are associated with simple harmonic motion and repeat themselves for several cycles. These simple harmonic waves can be modeled using a combination of sine and cosine functions. Consider a simplified surface water wave that moves across the water's surface. Unlike complex ocean waves, in surface water waves, water moves vertically, oscillating up and down, whereas the disturbance of the wave moves horizontally through the medium. If a seagull is floating on the...
FAQs
Least-squares optimization adjusts fit parameters to reduce the differences between measured and calculated values, giving greater importance to discrepancies according to the chosen treatment of measurement uncertainty. The optimum is therefore the parameter set that best reproduces the available observations under the model. In chemistry, this can extract quantitative constants from kinetic, equilibrium, spectral, or thermodynamic measurements.
Measurement uncertainty indicates how reliable each observation is and should influence the fit rather than being treated as irrelevant background. Data with different uncertainties can lead to different estimated values, because the optimization balances discrepancies according to their expected precision. Reporting this treatment helps readers judge whether fitted chemical constants are supported by the measurements.
Parameter correlations show whether changes in two fitted quantities can compensate for one another while preserving similar calculated behavior. Strong correlation means the data may not independently determine those quantities, even when the overall fit appears good. Examining correlations therefore helps distinguish robust chemical interpretation from parameter combinations that are mathematically acceptable but poorly resolved.
Constraints restrict the allowed values or combinations of fit parameters during optimization. They can prevent the model from selecting results that conflict with established conditions or the intended chemical interpretation. Because constraints influence the solution, researchers should evaluate whether they are justified and recognize that the resulting parameters reflect both the measurements and the imposed limitations.
A practical workflow begins by selecting a model and identifying the measured quantities it must reproduce. Researchers then specify how measurement uncertainty and any constraints will be handled, perform the optimization, and examine parameter uncertainty and correlations. Finally, they evaluate goodness of fit and physical meaning before using the results to compare systems or interpret chemical behavior.
Goodness of fit compares the model's calculated behavior with the experimental observations and helps reveal whether the chosen parameters adequately describe the data. It should be considered alongside parameter uncertainty and correlations, because a close reproduction alone does not establish a unique or physically meaningful interpretation. Together, these checks support more careful chemical conclusions.
The relevant parameter depends on the experiment and model: kinetic analyses may estimate reaction-rate constants, equilibrium studies may determine equilibrium constants, and spectroscopy may fit peak positions or intensities. Thermodynamic data can yield thermodynamic coefficients. These results help researchers interpret mechanisms, compare chemical systems, and predict conditions that were not directly measured.