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The breakpoint can be important in decision making [1] The figures illustrate some of the results and regression types obtainable. A segmented regression analysis is based on the presence of a set of ( y, x ) data, in which y is the dependent variable and x the independent variable .
The minimum inhibitory concentration, which is the lowest concentration of the antibiotic that stops the growth of bacteria, can be estimated from the size of the zone of inhibition. Antibiotic susceptibility testing has been needed since the discovery of the beta-lactam antibiotic penicillin. Initial methods were phenotypic, and involved ...
Interpretation is more complicated in mixed susceptibility populations. These are plotted as linear dimensions or squares of distances as a function of the natural logarithm of antibiotic concentration in the disks. The MIC is determined from the zero intercept of a linear regression fit through the data. [12]
Nowadays, the MIC is used in antimicrobial susceptibility testing. The MIC is reported by providing the susceptibility interpretation next to each antibiotic. The different susceptibility interpretations are: "S" (susceptible or responding to a standard dosing regimen), "I" (intermediate or requiring increased exposure), and "R" (resistant).
Alternative online IC50 calculator (www.ic50.org) based on Python, NumPy, SciPy and Matplotlib; ELISA IC50/EC50 Online Tool (link seems broken) IC50 to pIC50 calculator; Online tool for analysis of in vitro resistance to antimalarial drugs; IC50-to-Ki converter of an inhibitor and enzyme that obey classic Michaelis-Menten kinetics
Sabrina Carpenter has an NSFW New Year's resolution.. On Jan. 2, the "Espresso" singer shared her goal for 2025 on Instagram — and it looks like she already broke it. "new year’s resolution no ...
This is the scenario Americans could face in Trump’s second term. Under Trump, Christian nationalists will have unprecedented access to the power of the federal government. Trump’s GOP has ...
SciPy (pronounced / ˈ s aɪ p aɪ / "sigh pie" [2]) is a free and open-source Python library used for scientific computing and technical computing. [3]SciPy contains modules for optimization, linear algebra, integration, interpolation, special functions, FFT, signal and image processing, ODE solvers and other tasks common in science and engineering.