Dataset Information

Direct Determination of Ni²⁺-Capacity of IMAC Materials Using Near-Infrared Spectroscopy.

ABSTRACT: The present paper reports a new method for the quantification of the Ni²⁺-capacity of an immobilized metal affinity chromatography (IMAC) material using near-infrared spectroscopy (NIRS). Conventional analyses using UV absorption spectroscopy or atomic absorption spectrometry (AAS) need to dissolve the silica-based metal chelate sorbent as sample pretreatment. In the first step, those methods were validated on the basis of an ideal homogenous NiSO?-solution and unveiled that UV with an intermediate precision of 2.6% relative standard deviation (RSD) had an advantage over AAS with an intermediate precision of 6.5% RSD. Therefore, UV analysis was chosen as reference method for the newly established NIRS model which has the advantage of being able to measure the material directly in diffuse reflection mode. Partial least squares regression (PLSR) analysis was used as multivariate data analysis tool for quantification. The best PLSR result obtained was: coefficient of determination (R²) = 0.88, factor = 2, root mean square error of prediction (RMSEP) = 22 µmol/g (test-set validation) or 7.5% RSD_PLSR. Validation of the Ni²⁺-capacity using UV absorption spectroscopy resulted in an intermediate precision of ±18 µmol/g or 5.0% RSD. Therefore, NIRS provides a fast alternative analysis method without the need of sample preparation.

SUBMITTER: Kirchler CG

PROVIDER: S-EPMC6321272 | biostudies-literature | 2018 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Direct Determination of Ni<sup>2+</sup>-Capacity of IMAC Materials Using Near-Infrared Spectroscopy.

Kirchler Christian G CG Henn Raphael R Modl Julia J Münzker Felix F Baumgartner Tanja H TH Meischl Florian F Kehle Alexander A Bonn Günther K GK Huck Christian W CW

Molecules (Basel, Switzerland) 20181124 12

The present paper reports a new method for the quantification of the Ni<sup>2+</sup>-capacity of an immobilized metal affinity chromatography (IMAC) material using near-infrared spectroscopy (NIRS). Conventional analyses using UV absorption spectroscopy or atomic absorption spectrometry (AAS) need to dissolve the silica-based metal chelate sorbent as sample pretreatment. In the first step, those methods were validated on the basis of an ideal homogenous NiSO₄-solution and unveiled that UV with a ...[more]

PMID: 30477229

Similar Datasets

Project description:BackgroundCerebral blood flow (CBF) is maintained over a range of blood pressures through cerebral autoregulation (CA). Blood pressure outside the range of CA, or impaired autoregulation, is associated with adverse patient outcomes. Regional oxygen saturation (rSO2) derived from near-infrared spectroscopy (NIRS) can be used as a surrogate CBF for determining CA, but existing methods require a long period of time to calculate CA metrics. We have developed a novel method to determine CA using cotrending of mean arterial pressure (MAP) with rSO2that aims to provide an indication of CA state within 1 minute. We sought to determine the performance of the cotrending method by comparing its CA metrics to data derived from transcranial Doppler (TCD) methods.MethodsRetrospective data collected from 69 patients undergoing cardiac surgery with cardiopulmonary bypass were used to develop a reference lower limit of CA. TCD-MAP data were plotted to determine the reference lower limit of CA. The investigated method to evaluate CA state is based on the assessment of the instantaneous cotrending relationship between MAP and rSO2 signals. The lower limit of autoregulation (LLA) from the cotrending method was compared to the manual reference derived from TCD. Reliability of the cotrending method was assessed as uptime (defined as the percentage of time that the state of autoregulation could be measured) and time to first post.ResultsThe proposed method demonstrated minimal mean bias (0.22 mmHg) when compared to the TCD reference. The corresponding limits of agreement were found to be 10.79 mmHg (95% confidence interval [CI], 10.09-11.49) and -10.35 mmHg (95% CI, -9.65 to -11.05). Mean uptime was 99.40% (95% CI, 99.34-99.46) and the mean time to first post was 63 seconds (95% CI, 58-71).ConclusionsThe reported cotrending method rapidly provides metrics associated with CA state for patients undergoing cardiac surgery. A major strength of the proposed method is its near real-time feedback on patient CA state, thus allowing for prompt corrective action to be taken by the clinician.

Project description:The activities of enzymes are the basis of evaluating the quality of honey. Beekeepers usually use concentrators to process natural honey into concentrated honey by concentrating it under high temperatures. Active enzymes are very sensitive to high temperatures and will lose their activity when they exceed a certain temperature. The objective of this work is to study the kinetic mechanism of the temperature effect on diastase activity and to develop a nondestructive approach for quick determination of the diastase activity of honey through a heating process based on visible and near-infrared (Vis/NIR) spectroscopy. A total of 110 samples, including three species of botanical origin, were used for this study. To explore the kinetic mechanism of diastase activity under high temperatures, the honey of three kinds of botanical origins were processed with thermal treatment to obtain a variety of diastase activity. Diastase activity represented with diastase number (DN) was measured according to the national standard method. The results showed that the diastase activity decreased with the increase of temperature and heating time, and the sensitivity of acacia and longan to temperature was higher than linen. The optimum temperature for production and processing is 60 °C. Unsupervised clustering analysis was adopted to detect spectral characteristics of these honeys, indicating that different botanical origins of honeys can be distinguished in principal component spaces. Partial least squares (PLS) and least squares-support vector machine (LS-SVM) algorithms were applied to develop quantitative relationships between Vis/NIR spectroscopy and diastase activity. The best result was obtained through Gaussian filter smoothing-standard normal variate (GF-SNV) pretreatment and the LS-SVM model, known as GF-SNV-LS-SVM, with a determination coefficient (R²) of prediction of 0.8872, and root mean square error (RMSE) of prediction of 0.2129. The overall results of this paper showed that the diastase activity of honey can be determined quickly and non-destructively with Vis/NIR spectral methods, which can be used to detect DN in the process of honey production and processing, and to maximize the nutrient content of honey.

Dataset Information

Direct Determination of Ni2+-Capacity of IMAC Materials Using Near-Infrared Spectroscopy.

Publications

Direct Determination of Ni<sup>2+</sup>-Capacity of IMAC Materials Using Near-Infrared Spectroscopy.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Direct Determination of Ni²⁺-Capacity of IMAC Materials Using Near-Infrared Spectroscopy.