scholarly journals Estimation of the initial velocity of enzyme-catalysed reactions by non-linear regression analysis of progress curves

1985 ◽  
Vol 228 (1) ◽  
pp. 55-60 ◽  
Author(s):  
R G Duggleby
Keyword(s):  
Linear Regression ◽  
Initial Velocity ◽  
Linear Regression Analysis ◽  
Kinetic Properties ◽  
Progress Curve ◽  
Wide Range ◽  
Non Linear ◽  
Subjective Element ◽  
Zero Time

Most methods for studying the kinetic properties of an enzyme involve the determination of initial velocities. When the reaction progress curve shows significant curvature due to depletion of the substrate, accumulation of inhibitory products or instability of the enzyme, estimation of the initial velocity is a subjective and inexact process. Two methods have been suggested [Cornish-Bowden (1975) Biochem. J. 144, 305-312; Boeker (1982) Biochem J. 203, 117-123] that attempt to eliminate this subjective element. The present study offers a third alternative, which is based on fitting a reparameterized form of the integrated Michaelis-Menten equation to the progress curves by non-linear regression. This method yields estimates and standard errors of the initial velocity and of the time to reach 50% reaction. No prior knowledge of the apparent product concentration at zero time or infinite time is required, since both of these quantities are also estimated from the data. It is shown that this method yields reliable estimates of the initial velocity under a wide range of circumstances, including those where the two previously published methods perform poorly.

Evaluation and comparison of a radiative energy attenuation method for determining cholesterol in serum.

1985 ◽  
Vol 31 (4) ◽  
pp. 605-608 ◽  
Author(s):  
P L Cary ◽  
C A Johnson ◽  
P D Whitter ◽  
J W Parker
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
High Performance ◽  
Linear Regression Analysis ◽  
Radiative Energy ◽  
Comparison Methods ◽  
Analytical Recovery ◽  
Wide Range

Abstract Determination of cholesterol by a radiative energy attenuation (REA) technique was evaluated and compared with results obtained by the Boehringer Mannheim High Performance Cholesterol Assay and the Du Pont aca. Within-assay and between-assay CVs for the REA method, for two sets of controls, were both less than 5%. We observed no interference with lipemic samples. Analytical recovery averaged 102.8%. We used all three methods for parallel determinations of 217 patients' samples containing a wide range of cholesterol concentrations. Linear regression analysis of the REA results vs those of the comparison methods were as follows: REA = 1.03 Boehringer - 0.072 (r = 0.993) and REA = 1.02 aca - 0.048 (r = 0.995). We also discuss bilirubin interference with the REA method for cholesterol.

scholarly journals Analysis of kinetic data for irreversible enzyme inhibition

1989 ◽  
Vol 257 (2) ◽  
pp. 419-424 ◽  
Author(s):  
P J Gray ◽  
R G Duggleby
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Enzyme Inhibition ◽  
Kinetic Data ◽  
Organophosphorus Compounds ◽  
Linear Regression Analysis ◽  
Irreversible Inhibitors ◽  
Progress Curve ◽  
Inhibition Kinetic

Many organophosphorus compounds are irreversible inhibitors of acetylcholinesterase. The methods used in the literature to determine the inhibition kinetic constants usually involve either manual determination of the slope at various points along the inhibition progress curve or fitting polynomials to the curve. The present study investigates the use of non-linear-regression analysis to determine the various parameters. A method is suggested that yields accurate values for the inhibition constants under a range of circumstances.

scholarly journals Non-Destructive Micromagnetic Determination of Hardness and Case Hardening Depth Using Linear Regression Analysis and Artificial Neural Networks

Metals ◽  
2020 ◽  
Vol 11 (1) ◽  
pp. 18
Author(s):  
Rahel Jedamski ◽  
Jérémy Epp
Keyword(s):  
Neural Network ◽  
Neural Networks ◽  
Regression Analysis ◽  
Artificial Neural Networks ◽  
Linear Regression ◽  
Linear Regression Analysis ◽  
Case Hardening ◽  
Artificial Neural ◽  
Non Destructive

Non-destructive determination of workpiece properties after heat treatment is of great interest in the context of quality control in production but also for prevention of damage in subsequent grinding process. Micromagnetic methods offer good possibilities, but must first be calibrated with reference analyses on known states. This work compares the accuracy and reliability of different calibration methods for non-destructive evaluation of carburizing depth and surface hardness of carburized steel. Linear regression analysis is used in comparison with new methods based on artificial neural networks. The comparison shows a slight advantage of neural network method and potential for further optimization of both approaches. The quality of the results can be influenced, among others, by the number of teaching steps for the neural network, whereas more teaching steps does not always lead to an improvement of accuracy for conditions not included in the initial calibration.

Residue Analysis of Organophosphorus and Organochlorine Pesticides in Fatty Matrices by Gas Chromatography Coupled with Electron-Capture Detection

2006 ◽  
Vol 61 (5-6) ◽  
pp. 341-346 ◽  
Author(s):  
Jae-Woo Park ◽  
A. M. Abd El-Aty ◽  
Myoung-Heon Lee ◽  
Sung-Ok Song ◽  
Jae-Han Shim
Keyword(s):  
Gas Chromatography ◽  
Electron Capture ◽  
Simple Procedure ◽  
Linear Regression Analysis ◽  
Residue Analysis ◽  
Electron Capture Detection ◽  
Relative Standard ◽  
Wide Range ◽  
Repeatability And Reproducibility

A multiresidue method for the simultaneous determination of 22 organochlorine (OCs) and organophosphorus (Ops) pesticides (including isomers and metabolites), representing a wide range of physicochemical properties, was developed in fatty matrices extracted from meat. Pesticides were extracted from samples with acetonitrile/n-hexane (v :v, 1:1). The analytical screening was performed by gas chromatography coupled with electron-capture detection (ECD). The identification of compounds was based on their retention time and on comparison of the primary and secondary ions. The optimized method was validated by determining accuracy (recovery percentages), precision (repeatability and reproducibility), and sensitivity (detection and quantitation limits) from analyses of samples fortified at 38 to 300 ng/g levels. Correlation coefficients for the 22 extracted pesticide standard curves (linear regression analysis, n = 3) ranged from 0.998 to 1.000. Recovery studies from 2 g samples fortified at 3 levels demonstrated that the GC-ECD method provides 64.4-96.0% recovery for all pesticides except 2,4′-DDE (44.6-50.4%), 4,4′-DDE (51.1-57.5%) and 2,4′-DDT (50.0-51.2%). Both repeatability and reproducibility relative standard deviation values were < 20% for all residues. Detection limits ranged from 0.31 to 1.27 ng/g and quantification limits were between 1.04 and 4.25 ng/g. The proposed analytical method may be used as a simple procedure in routine determinations of OCs and Ops in meat. It can also be applied to the determination of pesticide multi-residues in other animal products such as butter and milk.

scholarly journals CURVAS DE SECAGEM E AVALIAÇÃO DA ATIVIDADE DE ÁGUA DA BANANA PASSA

2004 ◽  
Vol 22 (1) ◽  
Author(s):  
MILTON CANO-CHAUCA ◽  
AFONSO M. RAMOS ◽  
PAULO C. STRINGHETA ◽  
JOSÉ ANTONIO MARQUES ◽  
POLLYANNA IBRAHIM SILVA
Keyword(s):  
Experimental Data ◽  
Linear Regression ◽  
Moisture Content ◽  
Water Activity ◽  
Linear Regression Analysis ◽  
Sorption Isotherms ◽  
Exponential Model ◽  
Drying Time ◽  
Non Linear ◽  
Drying Curves

Curvas de secagem de banana passa foram determinadas, utilizando-se três temperaturas do ar de secagem. Os resultados indicaram que para reduzir o teor de umidade do produto até 23,5% foram necessários tempos de secagem de 51, 36 e 30 horas paras as temperaturas de 50, 60 e 70ºC, respectivamente. O modelo exponencial U/Uo = exp(-kt) foi ajustado para os dados experimentais mediante análise de regressão não-linear, encontrandose alto coeficiente de regressão linear. Determinou-se a atividade de água do produto ao longo do processo de secagem para as três temperaturas testadas. Estudou-se a correlação entre a atividade de água e o teor de umidade do produto, determinando-se as isotermas de dessorção da banana passa a 25ºC. Observou-se que a atividade de água diminuiu em função do tempo de secagem e do teor de umidade para as três temperaturas de secagem. Os dados experimentais foram ajustados mediante regressão não-linear ao modelo polinomial e a seguinte equação foi obtida: U = -1844,93 + 7293,53Aa – 9515,52Aa2 + 4157,196Aa3. O ajuste mostrou-se satisfatório (R2 > 0,90). DRYING CURVES AND WATER ACTIVITY EVALUATION OF THE BANANA-PASSES Abstract Banana drying curves were determined by utilizing three drying air temperatures. The results indicated that to reduce the moisture content of the product until 23.5% it were necessary drying times of 51, 36 and 30 hours for temperatures of 50, 60 and 70ºC, respectively. The exponential model U/Uo = exp(-kt) was adjusted for the experimental data by means of non linear regression analysis, and a high coefficient of linear regression was found. The water activity of the product was determined throughout the drying process for the three tested temperatures. The correlation between the water activity and moisture content of the product was studied, and the sorption isotherms were determined at 25º C. It was observed that the water activity decreased in function to the drying time and moisture content for the three drying temperatures. The experimental data were adjusted by means of non linear regression to the polynomial model and the following equation was obtained: U = - 1844.93 + 7293.53A a – 9515.52 Aa 2 + 4157.196A a 3. The final adjust was satisfactory (R2 > 0.90).

scholarly journals Reliability of Nitrogen Content (%N) and Carbon:Nitrogen Atomic Ratios (C:N) as Indicators of Collagen Preservation Suitable for Radiocarbon Dating

Radiocarbon ◽  
2012 ◽  
Vol 54 (3-4) ◽  
pp. 879-886 ◽  
Author(s):  
Fiona Brock ◽  
Rachel Wood ◽  
Thomas F G Higham ◽  
Peter Ditchfield ◽  
Alex Bayliss ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Linear Regression ◽  
Radiocarbon Dating ◽  
Linear Regression Analysis ◽  
Atomic Weight ◽  
Animal Bones ◽  
Bone Powder ◽  
Wide Range ◽  
Pass Through ◽  
Percent Nitrogen

A recent study into prescreening techniques to identify bones suitable for radiocarbon dating from sites known for poor or variable preservation (Brock et al. 2007, 2010a) found that the percent nitrogen (%N) content of whole bone powder was the most reliable indicator of collagen preservation. Measurement of %N is rapid, requires little preparation or material, and is relatively cheap. The technique reduces the risk of needlessly sampling valuable archaeological objects, as well as saving time and money on their unsuccessful pretreatment prior to dating. This method of prescreening is now regularly used at the Oxford Radiocarbon Accelerator Unit (ORAU). In the original study, linear regression analysis of data from 100 bones from 12 Holocene sites across southern England showed that when 0.76% N was chosen as a threshold, 84% of bones were successfully identified as containing sufficient (i.e. >1%) or insufficient (i.e. <1%) collagen for dating. However, it has been observed that for older, Pleistocene bones the failure rate may be higher, possibly due to the presence of more degraded, short-chain proteins that pass through the ultrafilters used in pretreatment, resulting in lower yields. Here, we present linear regression analysis of data from nearly 600 human and animal bones, antlers, and teeth, from a wide range of contexts and ages, to determine whether the 0.76% threshold identified in the previous study is still applicable. The potential of carbon:nitrogen atomic weight ratios (C:N) of whole bone to predict collagen preservation is also discussed.

scholarly journals EXPLORATION OF INTERCALATED KAOLINITE CLAY FOR THE UPTAKE OF BASIC DYE BY ADSORPTION − EQUILIBRIUM, KINETICS AND THERMODYNAMIC STUDIES

2021 ◽  
Vol 46 (1) ◽  
Author(s):  
C. E. Chigbundu ◽  
K. O. Adebowale
Keyword(s):  
Experimental Data ◽  
Linear Regression ◽  
Goodness Of Fit ◽  
Linear Regression Analysis ◽  
Dye Adsorption ◽  
Batch Adsorption ◽  
Sem Images ◽  
Kaolinite Clay ◽  
Non Linear ◽  
The Impact

Dyes are complex and sensitive organic chemicals which exposes microbial populations, aquatic lives and other living organisms to its toxic effects if their presence in water bodies or industrial effluents are not properly handled. This work therefore, comparatively studied the adsorption efficiencies of natural raw kaolinite (NRK) clay adsorbent and dimethyl sulphoxide (DMSO) faciley intercalated kaolinite clay (DIK) adsorbent for batch adsorption of Basis Red 2 (BR2) dye. The impact of varying the contact time, temperature and other operating variables on adsorption was also considered. The two adsorbents were characterized using SEM images, FTIR and XRD patterns. Linear and non-linear regression analysis of different isotherm and kinetic models were used to describe the appropriate fits to the experimental data. Error analysis equations were also used to measure the goodness-of-fit. Langmuir isotherm model best described the adsorption as being monolayer on homogenous surfaces while Kinetic studies showed that Elovich model provides the best fit to experimental data. The adsorption capacities of NRK and DIK adsorbents for the uptake of BR2 were 16.30 mg/g and 32.81 mg/g, respectively (linear regression) and 19.30 mg/g and 30.81 mg/g, respectively (non-linear regression). The thermodynamic parameter, ∆G showed that BR2 dye adsorption onto the adsorbents were spontaneous. DIK adsorbent was twice efficient compared with NRK for the uptake of BR2 dye.

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