Label-free screening of brain tissue myelin content using phase imaging with computational specificity (PICS)

Inadequate myelination in the central nervous system is associated with neurodevelopmental complications. Thus, quantitative, high spatial resolution measurements of myelin levels are highly desirable. We used spatial light interference microcopy (SLIM), a highly sensitive quantitative phase imaging (QPI) technique, to correlate the dry mass content of myelin in piglet brain tissue with dietary changes and gestational size. We combined SLIM micrographs with an AI classifying model that allows us to discern subtle disparities in myelin distributions with high accuracy. This concept of combining QPI label-free data with AI for the purpose of extracting molecular specificity has recently been introduced by our laboratory as phase imaging with computational specificity (PICS). Training on nine thousand SLIM images of piglet brain tissue with the 71-layer transfer learning model Xception, we created a two-parameter classification to differentiate gestational size and diet type with an accuracy of 82% and 80%, respectively. To our knowledge, this type of evaluation is impossible to perform by an expert pathologist or other techniques.

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Monitoring Reactivation of Latent HIV by Label-Free Gradient Light Interference Microscopy

10.1101/2020.12.16.423158 ◽

2020 ◽

Author(s):

Neha Goswami ◽

Yiyang Lu ◽

Mikhail E. Kandel ◽

Michael J. Fanous ◽

Kathrin Bohn-Wippert ◽

...

Keyword(s):

Mass Density ◽

Single Cells ◽

Dry Mass ◽

Interference Microscopy ◽

Label Free ◽

Light Interference ◽

Mean Diameter ◽

Latently Infected ◽

Infected Cells ◽

Latent Hiv

SummaryLatent human immunodeficiency virus (HIV) reservoirs in infected individuals present the largest barrier to a cure. The first step towards overcoming this challenge is to understand the science behind latency-reactivation interplay. Fluorescence imaging of GFP-tagged HIV has been the main method for studying reactivation of latent HIV in individually infected cells. In this paper, we report insights provided by label-free, gradient light interference microscopy (GLIM) about the changes in measures including dry mass, diameter, and dry mass density associated with infected cells that occur upon reactivation. We discovered that mean cell dry mass and mean diameter of latently infected cells treated with reactivating drug, TNF-α, are higher for cells with reactivated HIV as compared to those with latent disease. Results also indicate that cells with mean dry mass and diameter less than 10pg and 8µm, respectively, remain exclusively in the latent state. Also, cells with mean dry mass greater than 23pg and mean diameter greater than 11µm have a higher probability of reactivating. This study is significant as it presents a new label-free approach to quantify latent reactivation of a virus in single cells based on changes in cell morphology.

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Topography and refractometry of sperm cells using SLIM

10.1101/222000 ◽

2017 ◽

Author(s):

Lina Liu ◽

Mikhail E. Kandel ◽

Marcello Rubessa ◽

Sierra Schreiber ◽

Mathew Wheeler ◽

...

Keyword(s):

Refractive Index ◽

Interference Microscopy ◽

Phase Imaging ◽

Label Free ◽

Quantitative Phase Imaging ◽

Ensemble Averaging ◽

Thickness Profile ◽

Light Interference ◽

Phase Sensitive

AbstractCharacterization of spermatozoon viability is a common test in treating infertility. Recently, it has been shown that label-free, phase-sensitive imaging can provide a valuable alternative for this type of assay. Here, we employ spatial light interference microscopy (SLIM) to decouple the thickness and refractive index information of individual cells. This procedure was enabled by quantitative phase imaging cells on media of two different refractive indices and using a numerical tool to remove the curvature from the cell tails. This way, we achieved ensemble averaging of topography and refractometry of 100 cells in each of the two groups. The results show that the thickness profile of the cell tail goes down to 150 nm and the refractive index can reach values of 1.6 close to the head.

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Measuring three-dimensional dynamics of platelet activation using 3-D quantitative phase imaging

10.1101/827436 ◽

2019 ◽

Cited By ~ 2

Author(s):

SangYun Lee ◽

Seongsoo Jang ◽

YongKeun Park

Keyword(s):

Platelet Activation ◽

Three Dimensional ◽

Dry Mass ◽

Phase Imaging ◽

Label Free ◽

Quantitative Phase Imaging ◽

Biochemical Alterations ◽

Quantitative Phase ◽

Before And After ◽

Quantitative Manner

AbstractPlatelets, or thrombocytes, are anucleated tiny blood cells with an indispensable contribution to the hemostatic properties of whole blood, detecting injured sites at the surface of blood vessels and forming blood clots. Here, we quantitatively and non-invasively investigated the morphological and biochemical alterations of individual platelets during activation in the absence of exogenous agents by employing 3-D quantitative phase imaging (QPI). By reconstructing 3-D refractive index (RI) tomograms of individual platelets, we investigated alterations in platelet activation before and after the administration of various platelet agonists. Our results showed that while the integrity of collagen-stimulated platelets was preserved despite the existence of a few degranulated platelets with developed pseudopods, platelets stimulated by thrombin or thrombin receptor-activating peptide (TRAP) exhibited significantly lower cellular concentration and dry mass than did resting platelets. Our work provides a means to systematically investigate drug-respondents of individual platelets in a label-free and quantitative manner, and open a new avenue to the study of the activation of platelets.Abstract Figure

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Label-free screening of brain tissue myelin content using phase imaging with computational specificity (PICS)

APL Photonics ◽

10.1063/5.0050889 ◽

2021 ◽

Vol 6 (7) ◽

pp. 076103

Author(s):

Michael Fanous ◽

Chuqiao Shi ◽

Megan P. Caputo ◽

Laurie A. Rund ◽

Rodney W. Johnson ◽

...

Keyword(s):

Brain Tissue ◽

Phase Imaging ◽

Label Free

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Epi-illumination gradient light interference microscopy for imaging opaque structures

Nature Communications ◽

10.1038/s41467-019-12634-3 ◽

2019 ◽

Vol 10 (1) ◽

Cited By ~ 11

Author(s):

Mikhail E. Kandel ◽

Chenfei Hu ◽

Ghazal Naseri Kouzehgarani ◽

Eunjung Min ◽

Kathryn Michele Sullivan ◽

...

Keyword(s):

Multiple Scattering ◽

Imaging Modality ◽

Single Cells ◽

Scattering Problem ◽

Biological Tissues ◽

Interference Microscopy ◽

Model Organisms ◽

Phase Imaging ◽

Label Free ◽

Light Interference

Abstract Multiple scattering and absorption limit the depth at which biological tissues can be imaged with light. In thick unlabeled specimens, multiple scattering randomizes the phase of the field and absorption attenuates light that travels long optical paths. These obstacles limit the performance of transmission imaging. To mitigate these challenges, we developed an epi-illumination gradient light interference microscope (epi-GLIM) as a label-free phase imaging modality applicable to bulk or opaque samples. Epi-GLIM enables studying turbid structures that are hundreds of microns thick and otherwise opaque to transmitted light. We demonstrate this approach with a variety of man-made and biological samples that are incompatible with imaging in a transmission geometry: semiconductors wafers, specimens on opaque and birefringent substrates, cells in microplates, and bulk tissues. We demonstrate that the epi-GLIM data can be used to solve the inverse scattering problem and reconstruct the tomography of single cells and model organisms.

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Reproductive outcomes predicted by phase imaging with computational specificity of spermatozoon ultrastructure

Proceedings of the National Academy of Sciences ◽

10.1073/pnas.2001754117 ◽

2020 ◽

Vol 117 (31) ◽

pp. 18302-18309 ◽

Cited By ~ 2

Author(s):

Mikhail E. Kandel ◽

Marcello Rubessa ◽

Yuchen R. He ◽

Sierra Schreiber ◽

Sasha Meyers ◽

...

Keyword(s):

Cell Viability ◽

Contrast Agents ◽

Assisted Reproductive Technologies ◽

Reproductive Technologies ◽

Dry Mass ◽

Sperm Cells ◽

Phase Imaging ◽

Label Free ◽

Mass Content

The ability to evaluate sperm at the microscopic level, at high-throughput, would be useful for assisted reproductive technologies (ARTs), as it can allow specific selection of sperm cells for in vitro fertilization (IVF). The tradeoff between intrinsic imaging and external contrast agents is particularly acute in reproductive medicine. The use of fluorescence labels has enabled new cell-sorting strategies and given new insights into developmental biology. Nevertheless, using extrinsic contrast agents is often too invasive for routine clinical operation. Raising questions about cell viability, especially for single-cell selection, clinicians prefer intrinsic contrast in the form of phase-contrast, differential-interference contrast, or Hoffman modulation contrast. While such instruments are nondestructive, the resulting image suffers from a lack of specificity. In this work, we provide a template to circumvent the tradeoff between cell viability and specificity by combining high-sensitivity phase imaging with deep learning. In order to introduce specificity to label-free images, we trained a deep-convolutional neural network to perform semantic segmentation on quantitative phase maps. This approach, a form of phase imaging with computational specificity (PICS), allowed us to efficiently analyze thousands of sperm cells and identify correlations between dry-mass content and artificial-reproduction outcomes. Specifically, we found that the dry-mass content ratios between the head, midpiece, and tail of the cells can predict the percentages of success for zygote cleavage and embryo blastocyst formation.

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Label-free screening of myelin distribution in brain tissue using phase imaging with computational specificity (PICS)

Quantitative Phase Imaging VII ◽

10.1117/12.2584463 ◽

2021 ◽

Author(s):

Michael J. Fanous ◽

Gabriel Popescu ◽

Chuqiao Shi ◽

Megan Caputo ◽

Laurie Rund ◽

...

Keyword(s):

Brain Tissue ◽

Phase Imaging ◽

Label Free

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Phase imaging with computational specificity (PICS) for measuring dry mass changes in sub-cellular compartments

Nature Communications ◽

10.1038/s41467-020-20062-x ◽

2020 ◽

Vol 11 (1) ◽

Author(s):

Mikhail E. Kandel ◽

Yuchen R. He ◽

Young Jae Lee ◽

Taylor Hsuan-Yu Chen ◽

Kathryn Michele Sullivan ◽

...

Keyword(s):

Cell Biology ◽

Imaging System ◽

High Specificity ◽

Dry Mass ◽

Live Cells ◽

Phase Imaging ◽

Label Free ◽

Quantitative Phase Imaging ◽

Cell Nuclei ◽

Quantitative Phase

AbstractDue to its specificity, fluorescence microscopy has become a quintessential imaging tool in cell biology. However, photobleaching, phototoxicity, and related artifacts continue to limit fluorescence microscopy’s utility. Recently, it has been shown that artificial intelligence (AI) can transform one form of contrast into another. We present phase imaging with computational specificity (PICS), a combination of quantitative phase imaging and AI, which provides information about unlabeled live cells with high specificity. Our imaging system allows for automatic training, while inference is built into the acquisition software and runs in real-time. Applying the computed fluorescence maps back to the quantitative phase imaging (QPI) data, we measured the growth of both nuclei and cytoplasm independently, over many days, without loss of viability. Using a QPI method that suppresses multiple scattering, we measured the dry mass content of individual cell nuclei within spheroids. In its current implementation, PICS offers a versatile quantitative technique for continuous simultaneous monitoring of individual cellular components in biological applications where long-term label-free imaging is desirable.

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Optical Monitoring of the Production Quality of Si-Nanoribbon Chips Intended for the Detection of ASD-Associated Oligonucleotides

Micromachines ◽

10.3390/mi12020147 ◽

2021 ◽

Vol 12 (2) ◽

pp. 147

Author(s):

Kristina A. Malsagova ◽

Tatyana O. Pleshakova ◽

Vladimir P. Popov ◽

Igor N. Kupriyanov ◽

Rafael A. Galiullin ◽

...

Keyword(s):

Production Quality ◽

Autism Spectrum ◽

Covalent Immobilization ◽

Biological Macromolecules ◽

Label Free ◽

Raman Scattering Spectroscopy ◽

Dna Oligonucleotides ◽

Highly Sensitive ◽

Highly Sensitive Detection

Gas-phase etching and optical lithography were employed for the fabrication of a silicon nanoribbon chip (Si-NR chip). The quality of the so-fabricated silicon nanoribbons (Si-NRs) was monitored by optical Raman scattering spectroscopy. It was demonstrated that the structures of the Si-NRs were virtually defect-free, meaning they could be used for highly sensitive detection of biological macromolecules. The Si-NR chips were then used for the highly sensitive nanoelectronics detection of DNA oligonucleotides (oDNAs), which represent synthetic analogs of 106a-5p microRNA (miR-106a-5p), associated with the development of autism spectrum disorders in children. The specificity of the analysis was attained by the sensitization of the Si-NR chip sur-face by covalent immobilization of oDNA probes, whose nucleotide sequence was complementary to the known sequence of miR-106a-5p. The use of the Si-NR chip was demonstrated to al-low for the rapid label-free real-time detection of oDNA at ultra-low (~10−17 M) concentrations.

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