Hemoglobin quantification in red blood cells via dry mass mapping based on UV absorption

Kaza, Nischita; Ojaghi, Ashkan; Robles, Francisco E.

doi:10.1117/1.jbo.26.8.086501

Cited by 23 publications

(20 citation statements)

References 38 publications

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“…RBCs function as an important biosignature in medical diagnosis with its characteristic morphological and molecular properties [43, 44]. In recent years, the label‐free QPI methods attains significant interest in the diagnosis of RBCs due to its potential ability to estimate the dry mass of hemoglobin by exploiting the linear relation exist between refractive index and mass concentration [45, 46]. The dry mass (DM) associated with the RBC is related to the measured phase by the expression [46],

italicDM goodbreak= \sum_{r} \frac{λ}{2 italicπβ} normalΔ φ ((), r) \cdot S_{p}

where

λ

the wavelength of the light source,

bold-italicr

is the position vector with

((), x, y)

coordinates in the reconstructed image,

S_{p}

is the entire cell area, and

β

represents the refractive index increment at a specific wavelength.…”

Section: Resultsmentioning

confidence: 99%

“…In recent years, the label‐free QPI methods attains significant interest in the diagnosis of RBCs due to its potential ability to estimate the dry mass of hemoglobin by exploiting the linear relation exist between refractive index and mass concentration [45, 46]. The dry mass (DM) associated with the RBC is related to the measured phase by the expression [46],

italicDM goodbreak= \sum_{r} \frac{λ}{2 italicπβ} normalΔ φ ((), r) \cdot S_{p}

where

λ

the wavelength of the light source,

bold-italicr

is the position vector with

((), x, y)

coordinates in the reconstructed image,

S_{p}

is the entire cell area, and

β

represents the refractive index increment at a specific wavelength. We prepared the RBC specimens by diluting a factor of home‐made Dulbecco's phosphate buffered saline, whole preparation process was carried out under an inverted microscope, until the blood cells in the field of vision become sparse.…”

Section: Resultsmentioning

confidence: 99%

“…RBCs function as an important biosignature in medical diagnosis with its characteristic morphological and molecular properties [43,44]. In recent years, the label-free QPI methods attains significant interest in the diagnosis of RBCs due to its potential ability to estimate the dry mass of hemoglobin by exploiting the linear relation exist between refractive index and mass concentration [45,46]. The dry mass (DM) associated with the RBC is related to the measured phase by the expression [46],…”

Section: Qpi For Red Blood Cellsmentioning

confidence: 99%

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Label‐free single‐shot imaging with on‐axis phase‐shifting holographic reflectance quantitative phase microscopy

Liu

et al. 2022

Journal of Biophotonics

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Quantitative phase microscopy (QPM) has been emerged as an indispensable diagnostic and characterization tool in biomedical imaging with its characteristic nature of label‐free, noninvasive, and real time imaging modality. The integration of holography to the conventional microscopy opens new advancements in QPM featuring high‐resolution and quantitative three‐dimensional image reconstruction. However, the holography schemes suffer in space‐bandwidth and time‐bandwidth issues in the off‐axis and phase‐shifting configuration, respectively. Here, we introduce an on‐axis phase‐shifting holography based QPM system with single‐shot imaging capability. The technique utilizes the Fizeau interferometry scheme in combination with polarization phase‐shifting and space‐division multiplexing to achieve the single‐shot recording of the multiple phase‐shifted holograms. Moreover, the high‐speed imaging capability with instantaneous recording of spatially phase shifted holograms offers the flexible utilization of the approach in dynamic quantitative phase imaging with robust phase stability. We experimentally demonstrated the validity of the approach by quantitative phase imaging and depth‐resolved imaging of paramecium cells. Furthermore, the technique is applied to the phase imaging and quantitative parameter estimation of red blood cells. This integration of a Fizeau‐based phase‐shifting scheme to the optical microscopy enables a simple and robust tool for the investigations of engineered and biological specimen with real‐time quantitative analysis.

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italicDM goodbreak= \sum_{r} \frac{λ}{2 italicπβ} normalΔ φ ((), r) \cdot S_{p}

where

λ

the wavelength of the light source,

bold-italicr

is the position vector with

((), x, y)

coordinates in the reconstructed image,

S_{p}

is the entire cell area, and

β

represents the refractive index increment at a specific wavelength.…”

Section: Resultsmentioning

confidence: 99%

italicDM goodbreak= \sum_{r} \frac{λ}{2 italicπβ} normalΔ φ ((), r) \cdot S_{p}

where

λ

the wavelength of the light source,

bold-italicr

is the position vector with

((), x, y)

coordinates in the reconstructed image,

S_{p}

is the entire cell area, and

β

Section: Resultsmentioning

confidence: 99%

Section: Qpi For Red Blood Cellsmentioning

confidence: 99%

See 1 more Smart Citation

Label‐free single‐shot imaging with on‐axis phase‐shifting holographic reflectance quantitative phase microscopy

Liu

et al. 2022

Journal of Biophotonics

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show abstract

“…But it may be noted that biological material can contain more than trace amounts of iron. Dried human red blood cells, for example, are composed of 95-98% haemoglobin (Kaza et al, 2021), corresponding to an iron content of 0.33%. Moreover, loss of volatile products during thermal decomposition will increase the percentage of iron in the residues.…”

Section: Discussionmentioning

confidence: 99%

Heat-induced changes in molecular biosignatures and the influence of Mars-relevant minerals

Haezeleer

Fox

Strasdeit

2023

International Journal of Astrobiology

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The search for signs of life is a major objective in the exploration of Mars. Of particular interest are chemical biosignatures such as biomolecules. However, molecular biosignatures are susceptible to extreme environmental conditions such as heat, ionising radiation and strong oxidants. Therefore, a knowledge of the stability of possible biosignature molecules under present and past conditions on Mars is important, as well as the nature of possible alteration products. In the light of the long volcanically active history of Mars, we have studied the thermal behaviour of selected biological compounds, namely, haemin (an iron porphyrin closely related to the haem prosthetic group), cytochrome c (a small protein) and lecithin (a mixture of phospholipids). Samples were exposed to temperatures up to 900°C under an inert atmosphere of nitrogen, either in neat form or in mineral matrices. The matrix materials used were sodium chloride, gypsum (CaSO4 ⋅ 2H2O), Ca-montmorillonite (STx-1b), the Martian regolith simulant JSC Mars-1A and some mixtures thereof. Key results are: (1) The onset of significant decomposition for haemin, cytochrome c and lecithin occurs around 240°C. At slightly higher temperatures the disappearance of all characteristic infrared spectral bands indicates complete decomposition and loss of the primary biosignatures. (2) Haemin stoichiometrically releases CO2 and HCl during the initial thermal decomposition phase, at the end of which the iron porphyrin core is still intact. High-temperature products of haemin include graphite, α-iron and cementite (Fe3C). (3) Neat lecithin forms long-chain polyphosphates at 500°C, whereas lecithin‒NaCl mixtures form diphosphate (pyrophosphate). As these anions are absent and rare, respectively, in minerals, they may potentially serve as secondary biosignatures. (4) Heating a mixture of NaCl and JSC Mars-1A at 800°C in the presence of lecithin produces the aluminosilicate mineral sodalite (Na8[AlSiO4]6Cl2), which however appears to be of limited use as a secondary biosignature.

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“…Deep-ultraviolet microscopy (UV) is a label-free imaging technique that leverages the distinctive spectral properties of endogenous biomolecules in this region of the spectrum (200-400 nm) to yield quantitative molecular and structural information from biological samples [17][18][19][20][21][22]. Owing to the shorter wavelength of UV light, deep-UV microscopy offers higher spatial resolution than conventional methods.…”

Section: Introductionmentioning

confidence: 99%

Virtual Staining, Segmentation, and Classification of Blood Smears for Label-Free Hematology Analysis

2022

Self Cite

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Objective and Impact Statement. We present a fully automated hematological analysis framework based on single-channel (single-wavelength), label-free deep-ultraviolet (UV) microscopy that serves as a fast, cost-effective alternative to conventional hematology analyzers. Introduction. Hematological analysis is essential for the diagnosis and monitoring of several diseases but requires complex systems operated by trained personnel, costly chemical reagents, and lengthy protocols. Label-free techniques eliminate the need for staining or additional preprocessing and can lead to faster analysis and a simpler workflow. In this work, we leverage the unique capabilities of deep-UV microscopy as a label-free, molecular imaging technique to develop a deep learning-based pipeline that enables virtual staining, segmentation, classification, and counting of white blood cells (WBCs) in single-channel images of peripheral blood smears. Methods. We train independent deep networks to virtually stain and segment grayscale images of smears. The segmented images are then used to train a classifier to yield a quantitative five-part WBC differential. Results. Our virtual staining scheme accurately recapitulates the appearance of cells under conventional Giemsa staining, the gold standard in hematology. The trained cellular and nuclear segmentation networks achieve high accuracy, and the classifier can achieve a quantitative five-part differential on unseen test data. Conclusion. This proposed automated hematology analysis framework could greatly simplify and improve current complete blood count and blood smear analysis and lead to the development of a simple, fast, and low-cost, point-of-care hematology analyzer.

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Hemoglobin quantification in red blood cells via dry mass mapping based on UV absorption

Cited by 23 publications

References 38 publications

Label‐free single‐shot imaging with on‐axis phase‐shifting holographic reflectance quantitative phase microscopy

Label‐free single‐shot imaging with on‐axis phase‐shifting holographic reflectance quantitative phase microscopy

Heat-induced changes in molecular biosignatures and the influence of Mars-relevant minerals

Virtual Staining, Segmentation, and Classification of Blood Smears for Label-Free Hematology Analysis

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