Gene/Protein
Disease
Symptom
Drug
Enzyme
Compound
Pivot Concepts:
Gene/Protein
Disease
Symptom
Drug
Enzyme
Compound
Target Concepts:
Gene/Protein
Disease
Symptom
Drug
Enzyme
Compound
Query: EC:2.4.1.14 (
SPS
)
813
document(s) hit in 31,850,051 MEDLINE articles (0.00 seconds)
Inductively coupled plasma mass spectrometry (ICP-MS) is a suitable tool for multi-element analysis at low concentration levels. Rare earth element (REE) determinations in standard reference materials and small volumes of molten ice core samples from Antarctica have been performed with an ICP-time of flight-MS (ICP-TOF-MS) system. Recovery rates for REE in e.g.
SPS
-SW1 amounted to approximately 103%, and the relative standard deviations were 3.4% for replicate analysis at REE concentrations in the lower ngL(-1) range. Analyses of REE concentrations in Antarctic ice core samples showed that the ICP-
TOF
-MS technique meets the demands of restricted sample mass. The data obtained are in good agreement with ICP-Quadrupole-MS (ICP-Q-MS) and ICP-Sector Field-MS (ICP-SF-MS) results. The ICP-
TOF
-MS system determines accurately and precisely REE concentrations exceeding 5ngL(-1) while between 0.5 and 5ngL(-1) accuracy and precision are element dependent.
...
PMID:Rare earth elements determined in Antarctic ice by inductively coupled plasma--time of flight, quadrupole and sector field-mass spectrometry: An inter-comparison study. 1857 77
Mathematical modeling of Quantitative Structure - Property Relationships met great interest in fields of in silico drug design and more recently, pharmaceutical analysis. In our approach we proposed automated method of creation Quantitative Structure-Retention Relationship (QSRR) for analysis of triptans, selective serotonin 5-HT
1
receptor agonists used for the treatment of acute headache. The method was created using hybrid machine learning approach, namely Genetic algorithm (GA) coupled with artificial neutral networks (ANN). Performance of proposed hybrid GA-ANN model was evaluated with predicting relative retention times of naratriptan hydrochloride impurities. Several ANN types were coupled with GA and tested: single-layer ANN (SL-ANN), double-layer ANN (D-ANN) and higher order architectures: pi-sigma ANN (PS-ANN) and sigma-pi-sigma ANN (SPS-ANN). Partial Least Squares (PLS) method was used as a reference. The separation of naratriptan hydrochloride and its related products (impurities and degradation products) was obtained by developing a gradient high-performance liquid chromatography method with diode-array detector (HPLC-DAD). Degradation products during acid-basic hydrolysis were identified with an electrospray ionization tandem mass spectrometry (Q-
TOF
-MS/MS) detector. Independent data for outer validation of QSRR model was obtained from the determination of related products of sumatriptan succinate via an HPLC-DAD method. Accuracy of QSRR was measured by inner-validation on naratriptan data and outer validation on sumatriptan succinate samples. The best performing model were PS-ANN and
SPS
-ANN with mean errors of 8% (Q
2
=0.87) and 15% (Q
2
=0.77) on an inner-validation data set, respectively. Validation on similar samples from an outer validation data set of sumatriptan succinate impurities gave mean errors of 18% (R
2
pred
=0.64) and 17% (R
2
pred
=0.63) for the PS-ANN and
SPS
-ANN models, respectively.
...
PMID:Quantitative structure-retention relationship model for the determination of naratriptan hydrochloride and its impurities based on artificial neural networks coupled with genetic algorithm. 2810 13
