Hemoglobin consumption by P. falciparum in individual erythrocytes imaged via quantitative phase spectroscopy

Rinehart, Matthew T.; Park, Han Sang; Walzer, Katelyn A.; Chi, Jen‐Tsan; Wax, Adam

doi:10.1038/srep24461

Cited by 39 publications

(34 citation statements)

References 30 publications

(55 reference statements)

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“…A diffraction phase microscope with a fluorescent arm capable of acquiring multiple fluorescent bands, as well as FRET signals, was constructed . The new QPI instrument employed a spectrally selected illumination of 670 nm with a bandwidth of 1.2 nm using a coherent white light source . Instead of using a typical off‐axis style interferometer arrangement, a diffraction phase interferometer was implemented.…”

Section: Methodsmentioning

confidence: 99%

Molecular and biophysical analysis of apoptosis using a combined quantitative phase imaging and fluorescence resonance energy transfer microscope

Eldridge

Hoballah

Wax

2018

Journal of Biophotonics

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Apoptotic mechanisms are often dysregulated in cancerous phenotypes. Additionally, many anticancer treatments induce apoptosis and necrosis, and the monitoring of this apoptotic activity can allow researchers to identify therapeutic efficiency. Here, we introduce a microscope which combines quantitative phase imaging (QPI) with the ability to detect molecular events via fluorescence (or Förster) resonance energy transfer (FRET). The system was applied to study cells undergoing apoptosis to correlate the onset of apoptotic enzyme activity as observed using a FRET-based apoptosis sensor with whole cell morphological changes analyzed via QPI. The QPI data showed changes in cell disorder strength during the initiation of apoptotic enzymatic activity.

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Section: Methodsmentioning

confidence: 99%

Molecular and biophysical analysis of apoptosis using a combined quantitative phase imaging and fluorescence resonance energy transfer microscope

Eldridge

Hoballah

Wax

2018

Journal of Biophotonics

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“…A detailed discussion about this correction is presented in Ref. . In this equation, the RI of the interstitial space of the natural tissue ( n 0 ( t = 0)) represents the RI of water according to our model.…”

Section: Methodsmentioning

confidence: 99%

Skeletal muscle dispersion (400‐1000 nm) and kinetics at optical clearing

Oliveira

Carvalho

Nogueira

et al. 2017

Journal of Biophotonics

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Skeletal muscle dispersion and optical clearing (OC) kinetics were studied experimentally to prove the existence of the refractive index (RI) matching mechanism of OC. Sample thickness and collimated transmittance spectra were measured during treatments with glucose (40%) and ethylene glycol (EG; 99%) solutions and used to obtain the time dependence of the RI of tissue fluids based on the proposed theoretical model. Calculated results demonstrated an increase of RI of tissue fluids and consequently proved the occurrence of the RI matching mechanism. The RI increase was observed for the wavelength range between 400 and 1000 nm and for the 2 probing molecules explored. We found that for 30 min treatment with 40% glucose and 99% EG, RI of sarcoplasm plus interstitial fluid was increased at 800 nm from 1.328 to 1.348 and from 1.328 to 1.369, respectively.

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“…The practical issue is whether there are detectable differences in values of α between RBCs from healthy controls and ones from diabetic patients. Related to this issue, it has been recently reported that the dramatic alterations in protein compositions and growing parasites at the late stage of malarial infection result in a significant discordance between the cytoplasmic oxy-Hb content and the phase-originated cellular drymass 68 .…”

Section: Common-path Diffraction Optical Tomography (Cdot) For Simulmentioning

confidence: 99%

Refractive Index Tomograms and Dynamic Membrane Fluctuations of Red Blood Cells from Patients with Diabetes Mellitus

Lee

Park

Jang

et al. 2016

Blood

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Background: Diabetic effects on blood rheology are important topics and have been extensively investigated. In particular, it has been known that diabetic RBCs exhibit significantly deteriorated deformability compared to healthy RBCs. Despite the importance of previously measured mechanical properties of diabetic RBCs, several problems remain to be elucidated. First, conventional techniques have difficulties in measuring intrinsic properties of individual cells. Detailed quantification of diabetic alteration in RBCs at the individual cell level is also hard to achieve. Accordingly, previous approaches do not allow the systematical correlative analyses to be performed on simultaneously measured various cell parameters. As a consequence, there are still no general agreements on the integrated effects of diabetic complications or hyperglycemia on individual human RBCs. Methods: To effectively settle the arisen problems, we quantitatively and non-invasively measured the individual RBCs from diabetic and healthy blood donors to figure out the characteristics of diabetic RBCs by employing the quantitative phase imaging (QPI) technique. From the reconstructed three-dimensional (3-D) refractive index (RI) tomogram and the time-series of 2-D phase map of individual RBCs, the morphological (volume, surface area, and sphericity), biochemical (Hb concentration and Hb content), and mechanical (membrane fluctuation) parameters were retrieved. Systematic correlative analyses among measured six RBC parameters and independently determined HbA1c level, defined as the ratio of HbA1c to total Hb, were also performed. In measuring red cells, only gently sedimented RBCs of discocytes were selected. After excluding erroneously measured RBCs, 40, 40, 40, 38, 39, 40 control RBCs of six healthy donors and 40, 40, 40, 40, 40, 40 diabetic RBCs of six diabetic patients were finally analyzed respectively for the study of diabetic effects on characteristics of individual human RBCs. Results: HbA1c level is defined as a percentage of HbA1c, the majority of glycated Hbs in RBC, to total Hb contents in blood. Because HbA1c is formed through 120-days long, non-enzymatic glycation process of Hb, HbA1c level has been perceived as an effective mean to estimate mean glucose concentration of individuals for the last three months. In other words, HbA1c reflects the degree of hyperglycemia. The most noticeable alterations in diabetic RBCs can be found when mean RBC membrane fluctuations of individuals are rearranged in the increasing order of the measured HbA1c levels. The mean values of membrane fluctuations for RBCs are 59.7 ¡¾ 6.2, 58.3 ¡¾ 4.9, 55.0 ¡¾ 5.4, 57.1 ¡¾ 7.4, 51.0 ¡¾ 6.8, and 49.6 ¡¾ 4.6 nm for healthy volunteers, and 45.1 ¡¾ 4.0, 46.9 ¡¾ 3.4, 48.8 ¡¾ 4.0, 47.6 ¡¾ 4.2, 43.0 ¡¾ 4.1, and 48.0 ¡¾ 5.0 nm for diabetic patients, in order of increasing HbA1c. As shown in Fig. 4, mean membrane fluctuation of non-diabetic RBCs tends to decrease as the HbA1c level increases (Pearson correlation coefficient of -0.87 with a p-value of 0.02). Beyond this level of HbA1c, RBCs from diabetic patients exhibit significantly decreased and settled membrane fluctuation. This observed negative correlation between RBC membrane fluctuation and HbA1 is also conceptually in accordance with the report of the previous study. Conclusions: We quantitatively and non-invasively characterize the morphological, biochemical, and mechanical alterations of individual RBCs by diabetes mellitus. HbA1c levels of subjects, which reflect one's mean blood glucose concentration of last three months, were also determined using hematology analyzers. Accordingly, correlative analyses among the retrieved individual RBC parameters and HbA1c level were performed to search unique features which cannot be addressed by conventional techniques with incapability of simultaneous measurement of those parameters. Figure Box plot of membrane fluctuation for measured RBCs from six healthy controls and diabetic patients in increasing order of HbA1c. Boxes, median values with upper and lower quartiles. Short horizontal lines and error bars in each box plot denote the mean values and standard deviations, respectively. Figure. Box plot of membrane fluctuation for measured RBCs from six healthy controls and diabetic patients in increasing order of HbA1c. Boxes, median values with upper and lower quartiles. Short horizontal lines and error bars in each box plot denote the mean values and standard deviations, respectively. Disclosures No relevant conflicts of interest to declare.

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Hemoglobin consumption by P. falciparum in individual erythrocytes imaged via quantitative phase spectroscopy

Cited by 39 publications

References 30 publications

Molecular and biophysical analysis of apoptosis using a combined quantitative phase imaging and fluorescence resonance energy transfer microscope

Molecular and biophysical analysis of apoptosis using a combined quantitative phase imaging and fluorescence resonance energy transfer microscope

Skeletal muscle dispersion (400‐1000 nm) and kinetics at optical clearing

Refractive Index Tomograms and Dynamic Membrane Fluctuations of Red Blood Cells from Patients with Diabetes Mellitus

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