MR Relaxation Studies of Hemoglobin Aggregation Process in Sickle Cell Disease: Application for Diagnostics and Therapeutics

Guevara, Manuel Arsenio Lores; Naranjo, Juan Carlos García; Mirabal, Carlos Alberto Cabal

doi:10.1007/s00723-018-1104-0

Cited by 6 publications

(5 citation statements)

References 26 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The S-peak is the water molecules at the intermediate hydration layer, and the T-peak are water molecules, which came into direct contact with the surface of macromolecular protein. Dortch et al and McDonald et al, proposed the idea of exchange peaks 33 and surface relaxation 34 , respectively, but the observation in this work is in consistent with the three peaks model proposed by Lores et al and Thompson et al 35,36 .…”

Section: Resultssupporting

confidence: 88%

Machine learning assistive rapid, label-free molecular phenotyping of blood with two-dimensional NMR correlational spectroscopy

Peng

Loh

2020

Commun Biol

View full text Add to dashboard Cite

Translation of the findings in basic science and clinical research into routine practice is hampered by large variations in human phenotype. Developments in genotyping and phenotyping, such as proteomics and lipidomics, are beginning to address these limitations. In this work, we developed a new methodology for rapid, label-free molecular phenotyping of biological fluids (e.g., blood) by exploiting the recent advances in fast and highly efficient multidimensional inverse Laplace decomposition technique. We demonstrated that using two-dimensional T1-T2 correlational spectroscopy on a single drop of blood (<5 μL), a highly time- and patient-specific ‘molecular fingerprint’ can be obtained in minutes. Machine learning techniques were introduced to transform the NMR correlational map into user-friendly information for point-of-care disease diagnostic and monitoring. The clinical utilities of this technique were demonstrated through the direct analysis of human whole blood in various physiological (e.g., oxygenated/deoxygenated states) and pathological (e.g., blood oxidation, hemoglobinopathies) conditions.

show abstract

Section: Resultssupporting

confidence: 88%

Machine learning assistive rapid, label-free molecular phenotyping of blood with two-dimensional NMR correlational spectroscopy

Peng

Loh

2020

Commun Biol

View full text Add to dashboard Cite

show abstract

“…Dortch RD et al and McDonald PJ et al , proposed the idea of exchange peaks 30 and surface relaxation 31 , respectively, but the observation in this work is in consistent with the three peaks model proposed by Thompson B.C. et al and Lores G. et al 32,33 .…”

Section: Resultssupporting

confidence: 85%

Machine learning assistive rapid, label-free molecular phenotyping of blood with two-dimensional NMR correlational spectroscopy

Peng

Loh

2020

Preprint

View full text Add to dashboard Cite

10Translation of the findings in basic science and clinical research into routine practice is hampered 11 by large variations in human phenotype. Developments in genotyping and phenotyping, such as 12 proteomics and lipidomics, are beginning to address these limitations. In this work, we developed 13 a new methodology for rapid, label-free molecular phenotyping of biological fluids (e.g., blood) 14 by exploiting the recent advances in fast and highly efficient multidimensional inverse Laplace 15 decomposition technique. We demonstrated that using two-dimensional T1-T2 correlational 16 spectroscopy on a single drop of blood (<5 μL), highly time-and patient-specific ´molecular 17 fingerprint´ can be obtained in minutes. Machine learning techniques were introduced to 18 transform the NMR correlational map into user-friendly information for point-of-care disease 19 diagnostic. The clinical utilities of this technique were demonstrated through the direct analysis 20 of human whole blood in various physiological (e.g., oxygenated/deoxygenated states) and 21 pathological (e.g., blood oxidation, hemoglobinopathies) conditions. (145 words) 22 23 Keywords: rapid phenotyping of blood, 2D NMR correlational spectroscopy, machine learning, 24 disease diagnostic and monitoring. Introduction 1High-resolution nuclear magnetic resonance (NMR) spectroscopy is a powerful and attractive 2 technique in biochemistry (e.g., for structural protein analysis 1 , characterizing metabolomics 3 responses in biological samples 2-4 ) and inorganic chemistry 5 . However, high-resolution NMR 4 systems are large, expensive and incompatible with in-situ or portable applications. There is an 5 increasing demand for low field portable NMR system for use in food sciences 6 , oil-gas 6 exploration 7 , and point of care clinical testing [8][9][10] . In high field NMR, biochemical information is 7 typically detected and encoded in the frequency domain ("chemical shift"), in which the spectral 8 resolution scale with respect to the external magnetic field. This reduces its portability and limit 9 its downstream application in a large scale manner. 10However, biochemical and biophysical information (e.g., molecular rotational, diffusional 11 motion) can also be encoded in the relaxation times frame, namely the longitudinal (T1) and 12 transverse (T2) using a portable low field NMR system. In addition, molecular information in the 13 time-domain can be inversely decoded with the availability of fast and reliable Laplace inversion 14 algorithm 7,11 . This can provide parallel information that is not available in the traditional NMR 15 frequency domain based spectra. 16In recent years, significant advances in NMR system miniaturization 8,12-14 (e.g., electronic 17 console 12,13,15,16 , radio-frequency probe 9,10,17-19 , microfluidic-based chip 20,21 ) utilizing small foot-18 print permanent magnetic (<1 Tesla) for one-dimensional NMR relaxometry on water-proton 19 (e.g., spin-spin relaxation (T2-relaxation)) have been widely applied for point-of-care medi...

show abstract

“…( 2 . Proton magnetic relaxation in protein solutions is determined by the dominant contribution of the water protons [3,[11][12][13]. The other protons, belonging to the macromolecular structure, have magnetic relaxation times very short; much shorter than the magnetic relaxation times of the water protons at the protein solution and than the dead times of the majority of the equipments utilized to measure relaxation, then its contribution can be neglected [12].…”

Section: Resultsmentioning

confidence: 99%

“…The developed method to determine S, based on PMR, is very useful because it decreases, in one order of magnitude, the volume of sample needed to perform the experiment; avoids the washing of the viscometer between measurements; is fast (around 5 min per measurement, 30 min per patient); is not affected by the turbidity of the sample and the skills of the technician performing the measurement and allows reporting directly the value of S. Despite these advantages, the PMR is an expensive experimental method with respect to the traditional methods to measure S, nevertheless, this disadvantage can be minimized when we added other potential medical applications [13,18].…”

Section: Parametermentioning

confidence: 99%

“…Magnetic Resonance has been employed to determine  in protein solutions [3][4][5][6][7][8]; which reduces in one order of magnitude the minimal sample volume to be employed with respect to the classical viscometers, avoids the viscometer washing between determinations and supply directly the value of  without additional experimental evaluations. Nevertheless; experiments based on the nitroxide radicals Electronic Paramagnetic Resonance (EPR) spectra, the longitudinal magnetic relaxation of 13 C in molecules of Glicine and Glutathione belonging to the red blood cells (RBC), the water self-diffusion coefficient and the proton dispersion profiles underestimate the values of  in protein solutions [5,6]. On the other hand, other methods based on nuclear magnetic relaxation [7,8] modify the sample using superparamagnetic particles [7] or employ calibration curves obtained using samples with a very different nature with respect to the protein solutions [8].…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Dynamic viscosity of blood serum determined using proton magnetic relaxation

Torres,

Guevara,

Milán

et al. 2023

Preprint

Self Cite

View full text Add to dashboard Cite

An experimental procedure, based on proton magnetic relaxation, is presented to determine the absolute dynamic viscosity in blood serum (hS). The blood serum samples were obtained voluntary from whole blood of healthy individuals and patients, and processed by classical methods (centrifugation and decanting). The Carr-Purcell-Meiboon-Gill pulse sequence was employed to determine the transverse proton magnetic relaxation time (T2) in a Tecmag Magnetic Resonance console coupled to a magnet of 0. 095 T and the temperature of measurement was 293 K. A theoretical linear behavior of the transverse proton magnetic relaxation rate (1/T2) as a function of hS was obtained after the consideration of blood serum as an extremely diluted solution of albumin and globulins, and assuming a fast exchange of water molecules between the bound phase and the solvent. A value of hS= 1.29±0.07 mPa s was obtained in samples belonging to 20 voluntary healthy individuals, which statistically match with the value obtained using the Ostwald viscometer for the same samples (hS= 1.32±0.04 mPa s, P=0.104319>0.05, a=0.05). The potential medical utility of the presented proton magnetic resonance procedure was demonstrated in patients with Multiple Myeloma (24) and Sickle Cell Disease (34), in which hS resulted increased with values of 1.40±0.18 mPa s (P=0.0137509<0.05, a=0.05) and 1.36±0.10 mPa s (P=0.00809615<0.05, a=0.05) respectivelly.

show abstract

MR Relaxation Studies of Hemoglobin Aggregation Process in Sickle Cell Disease: Application for Diagnostics and Therapeutics

Cited by 6 publications

References 26 publications

Machine learning assistive rapid, label-free molecular phenotyping of blood with two-dimensional NMR correlational spectroscopy

Machine learning assistive rapid, label-free molecular phenotyping of blood with two-dimensional NMR correlational spectroscopy

Machine learning assistive rapid, label-free molecular phenotyping of blood with two-dimensional NMR correlational spectroscopy

Dynamic viscosity of blood serum determined using proton magnetic relaxation

Contact Info

Product

Resources

About