Intelligent Image-Activated Cell Sorting.

A fundamental challenge of biology is to understand the vast heterogeneity of cells, particularly how cellular composition, structure, and morphology are linked to cellular physiology. Unfortunately, conventional technologies are limited in uncovering these relations. We present a machine-intelligence technology based on a radically different architecture that realizes real-time image-based intelligent cell sorting at an unprecedented rate. This technology, which we refer to as intelligent image-activated cell sorting, integrates high-throughput cell microscopy, focusing, and sorting on a hybrid software-hardware data-management infrastructure, enabling real-time automated operation for data acquisition, data processing, decision-making, and actuation. We use it to demonstrate real-time sorting of microalgal and blood cells based on intracellular protein localization and cell-cell interaction from large heterogeneous populations for studying photosynthesis and atherothrombosis, respectively. The technology is highly versatile and expected to enable machine-based scientific discovery in biological, pharmaceutical, and medical sciences.

Microfluidic Separation and Enrichment of Escherichia coli by Size Using Viscoelastic Flows.

Here, we achieve the separation and enrichment of Escherichia coli clusters from its singlets in a viscoelastic microfluidic device. E. coli, an important prokaryotic model organism and a widely used microbial factory, can aggregate in clusters, leading to biofilm development that can be detrimental to human health and industrial processes. The ability to obtain high-purity populations of E. coli clusters is of significance for biological, biomedical, and industrial applications. In this study, polystyrene particles of two different sizes, 1 and 4.8 µm, are used to mimic E. coli singlets and clusters, respectively. Experimental results show that particles migrate toward the channel center in a size-dependent manner, due to the combined effects of inertial and elastic forces; 4.8 and 1 µm particles are found to have lateral equilibrium positions closer to the channel centerline and sidewalls, respectively. The size-dependent separation performance of the microdevice is demonstrated to be affected by three main factors: channel length, the ratio of sheath to sample flow rate, and poly(ethylene oxide) (PEO) concentration. Further, the separation of E. coli singlets and clusters is achieved at the outlets, and the separation efficiency is evaluated in terms of purity and enrichment factor.

Inertial Separation of Particles Assisted by Symmetrical Sheath Flows in a Straight Microchannel.

Over the past two decades, inertial microfluidics, which works at an intermediate range of Reynolds number (∼1 < Re < ∼100), has been widely used for particle separation due to its high-throughput and label-free features. This work proposes a novel method for continuous separation of particles by size using inertial microfluidics, with the assistance of symmetrical sheath flows in a straight microchannel. Here, larger particles (>3 µm) are arranged close to the channel sidewalls, while smaller particles (<2 µm) remain flowing along the channel centerline. This conclusion is supported by experimental data with particles of different sizes ranging from 0.79 to 10.5 µm. Symmetrical Newtonian sheath flows are injected on both sides of particle mixtures into a straight rectangular microchannel with an aspect ratio (AR = height/width) of 2.5. Results show that the separation performance of the developed microfluidic device is affected by three main factors: channel length, total flow rate, and flow rate ratio of sheath to sample. Besides, separation of platelets from whole blood is demonstrated. The developed microfluidic platform owns the advantages of low fabrication cost, simple experiment setup, versatile selections of particle candidates, and stable operations. This systematic study provides a new perspective for particle separation, which is expected to find applications across various fields spanning physics, biology, biomedicine, and industry.

Microenvironmental Analysis and Control for Local Cells under Confluent Conditions via a Capillary-Based Microfluidic Device.

Sophisticated functions of biological tissues are supported by small biological units of cells that are localized within a region of 100 µm scale. The cells in these units secrete molecules to form their microenvironment to play a vital role in biological functions. Various microfluidic devices have been developed to analyze the microenvironment but were not designed for cells in a culture dish in a confluent condition, a typical setup for cell and tissue cultivation. This study presents a novel glass capillary-based microfluidic device for studying confluent cells in a culture dish. The multiple capillaries allow the device to confine the local flow in 100 µm or smaller scale to form two adjacent regions with different chemical properties; it can simultaneously perform local cell stimulation and collect secreted molecules from the stimulated cells. Cell removal was achieved upon trypsin stimulation from a limited area (3.8 × 10-3 ± 1.0 × 10-3 mm2), which corresponded to 7.6 ± 2.0 cells, using the mouse skeletal myoblast cell line (C2C12 cells) in a confluent condition. Microenvironmental analysis was demonstrated by measuring the secreted tumor necrosis factor alpha (TNF-α) collected from the microenvironment of the stimulated and unstimulated mouse leukemic monocyte cell line (RAW264 cells) to track temporal changes in the TNF-α production. The TNF-α secreted from stimulated cells was approximately four-fold higher than that from unstimulated cells in 90 min. This device enables local cell stimulation and the collection of secreted molecules for cells under confluent conditions, which contributes to the analysis of the cellular microenvironment.

Label-free chemical imaging flow cytometry by high-speed multicolor stimulated Raman scattering.

Combining the strength of flow cytometry with fluorescence imaging and digital image analysis, imaging flow cytometry is a powerful tool in diverse fields including cancer biology, immunology, drug discovery, microbiology, and metabolic engineering. It enables measurements and statistical analyses of chemical, structural, and morphological phenotypes of numerous living cells to provide systematic insights into biological processes. However, its utility is constrained by its requirement of fluorescent labeling for phenotyping. Here we present label-free chemical imaging flow cytometry to overcome the issue. It builds on a pulse pair-resolved wavelength-switchable Stokes laser for the fastest-to-date multicolor stimulated Raman scattering (SRS) microscopy of fast-flowing cells on a 3D acoustic focusing microfluidic chip, enabling an unprecedented throughput of up to ∼140 cells/s. To show its broad utility, we use the SRS imaging flow cytometry with the aid of deep learning to study the metabolic heterogeneity of microalgal cells and perform marker-free cancer detection in blood.

Identification of Single Yeast Budding Using Impedance Cytometry with a Narrow Electrode Span.

Impedance cytometry is wildly used in single-cell detection, and its sensitivity is essential for determining the status of single cells. In this work, we focus on the effect of electrode gap on detection sensitivity. Through comparing the electrode span of 1 µm and 5 µm, our work shows that narrowing the electrode span could greatly improve detection sensitivity. The mechanism underlying the sensitivity improvement was analyzed via numerical simulation. The small electrode gap (1 µm) allows the electric field to concentrate near the detection area, resulting in a high sensitivity for tiny particles. This finding is also verified with the mixture suspension of 1 µm and 3 µm polystyrene beads. As a result, the electrodes with 1 µm gap can detect more 1 µm beads in the suspension than electrodes with 5 µm gap. Additionally, for single yeast cells analysis, it is found that impedance cytometry with 1 µm electrodes gap can easily distinguish budding yeast cells, which cannot be realized by the impedance cytometry with 5 µm electrodes gap. All experimental results support that narrowing the electrode gap is necessary for tiny particle detection, which is an important step in the development of submicron and nanoscale impedance cytometry.

Sheathless Inertial Focusing Chip Combining a Spiral Channel with Periodic Expansion Structures for Efficient and Stable Particle Sorting.

Efficient and reliable manipulation of biological particles is crucial in medical diagnosis and chemical synthesis. Inertial microfluidic devices utilizing passive hydrodynamic forces in the secondary flow have drawn considerable attention for their high throughputs, low costs, and harmless particle manipulation. However, as the dominant mechanism, the inertial lift force is difficult to quantitatively analyze because of the uncertainties of its magnitude and direction. The equilibrium position of particles varies along the migration process, thus inducing the instabilities of particle separation. Herein, we present a designable inertial microfluidic chip combining a spiral channel with periodic expansion structures for the sheathless separation of particles with different sizes. The stable vortex-induced lift force arising from the periodic expansion and the Dean drag force significantly enhanced the focusing process and determined the final equilibrium position. The experimental results showed that over 99% of target particles could be isolated with the high target sample purity of 86.12%. In the biological experiment, 93.5% of the MCF-7, 89.5% of the Hela, and 88.6% of the A549 cells were steadily recovered with excellent viabilities to verify the potential of the device in dealing with biological particles over a broad range of throughputs. The device presented in this study can further serve as a lab-on-chip platform for liquid biopsy and diagnostic analysis.

Effects of Flow-Induced Microfluidic Chip Wall Deformation on Imaging Flow Cytometry.

Imaging flow cytometry is a powerful tool by virtue of its capability for high-throughput cell analysis. The advent of high-speed optical imaging methods on a microfluidic platform has significantly improved cell throughput and brought many degrees of freedom to instrumentation and applications over the last decade, but it also poses a predicament on microfluidic chips. Specifically, as the throughput increases, the flow speed also increases (currently reaching 10 m/s): consequently, the increased hydrodynamic pressure on the microfluidic chip deforms the wall of the microchannel and produces detrimental effects lead to defocused and blur image. Here, we present a comprehensive study of the effects of flow-induced microfluidic chip wall deformation on imaging flow cytometry. We fabricated three types of microfluidic chips with the same geometry and different degrees of stiffness made of polydimethylsiloxane (PDMS) and glass to investigate material influence on image quality. First, we found the maximum deformation of a PDMS microchannel was >60 µm at a pressure of 0.6 MPa, while no appreciable deformation was identified in a glass microchannel at the same pressure. Second, we found the deviation of lag time that indicating velocity difference of migrating microbeads due to the deformation of the microchannel was 29.3 ms in a PDMS microchannel and 14.9 ms in a glass microchannel. Third, the glass microchannel focused cells into a slightly narrower stream in the X-Y plane and a significantly narrower stream in the Z-axis direction (focusing percentages were increased 30%, 32%, and 5.7% in the glass channel at flow velocities of 0.5, 1.5, and 3 m/s, respectively), and the glass microchannel showed stabler equilibrium positions of focused cells regardless of flow velocity. Finally, we achieved the world's fastest imaging flow cytometry by combining a glass microfluidic device with an optofluidic time-stretch microscopy imaging technique at a flow velocity of 25 m/s. © 2019 International Society for Advancement of Cytometry.

Isolating Single Euglena gracilis Cells by Glass Microfluidics for Raman Analysis of Paramylon Biogenesis.

Time-course analysis of single cells is important to characterize heterogeneous activities of individual cells such as the metabolic response to their environment. Single-cell isolation is an essential step prior to time-course analysis of individual cells by collecting, culturing, and identifying multiple single-cell targets. Although single-cell isolation has been performed by various methods previously, a glass microfluidic device with semiclosed microchannels dramatically improved this process with its simple operation and easy transfer for time-course analysis of identified single cells. This study demonstrates isolating single cells of the highly motile microalgae, Euglena gracilis, by semiclosed microchannels with liquid flow only. The isolated single cells were identified in isolating channels and continuously cultured to track, by Raman microscopy, for the formation of subcellular granules composed of polysaccharide paramylon, a unique metabolite of E. gracilis, generated through photosynthesis. Through low-temperature glass bonding, a thin glass interface was incorporated to the microfluidic device. Thus, the device could perform the direct measurements of cultured single cells at high magnification by Raman microscopy with low background noise. In this study, the first demonstration of sequential monitoring of paramylon biogenesis in a single identified E. gracilis cell is shown.

Optofluidic time-stretch quantitative phase microscopy.

Innovations in optical microscopy have opened new windows onto scientific research, industrial quality control, and medical practice over the last few decades. One of such innovations is optofluidic time-stretch quantitative phase microscopy - an emerging method for high-throughput quantitative phase imaging that builds on the interference between temporally stretched signal and reference pulses by using dispersive properties of light in both spatial and temporal domains in an interferometric configuration on a microfluidic platform. It achieves the continuous acquisition of both intensity and phase images with a high throughput of more than 10,000 particles or cells per second by overcoming speed limitations that exist in conventional quantitative phase imaging methods. Applications enabled by such capabilities are versatile and include characterization of cancer cells and microalgal cultures. In this paper, we review the principles and applications of optofluidic time-stretch quantitative phase microscopy and discuss its future perspective.

Ultrasensitive detection of nucleic acids based on dually enhanced fluorescence polarization.

Highly sensitive detection of nucleic acids is crucial for genomics, transcriptomics, and heterogeneity studies. Conventional fluorescence polarization and intensity-based assays for DNA/RNA measurements often suffer from a poor limit of detection and a long test period. A versatile nanoscale probe based on a competitive displacement assay and fluorescence polarization was proposed for the simple, fast and sensitive detection of nucleic acids. For the probe, a partially complementary double-stranded DNA (dsDNA) was used as a connector of gold nanoparticles (AuNPs) and Alexa fluor 488 dyes (Alexa488), leading to the nanometal surface energy transfer (NSET) between Alexa488 and AuNPs. Meanwhile, suppression of the fluorescence intensity caused a decrease in the effective concentration of the Alexa488, and an increase in the volume or mass prolonged the rotational relaxation time of the Alexa488, both of which increased polarization of the Alexa488 in an aqueous solution. After competitive displacement between the probe and the target strand, the decrease in the volume or mass of the Alexa488 and fluorescence recovery resulted in the decline of the fluorescence polarization of the Alexa488, which could be used to sensitively detect the target concentration. After optimization, the fluorescence polarization-based method achieved a pM level detection of single-stranded nucleic acids within 30 minutes.

Time Sequential Single-Cell Patterning with High Efficiency and High Density.

Single-cell capture plays an important role in single-cell manipulation and analysis. This paper presents a microfluidic device for deterministic single-cell trapping based on the hydrodynamic trapping mechanism. The device is composed of an S-shaped loop channel and thousands of aligned trap units. This arrayed structure enables each row of the device to be treated equally and independently, as it has row periodicity. A theoretical model was established and a simulation was conducted to optimize the key geometric parameters, and the performance was evaluated by conducting experiments on MCF-7 and Jurkat cells. The results showed improvements in single-cell trapping ability, including loading efficiency, capture speed, and the density of the patterned cells. The optimized device can achieve a capture efficiency of up to 100% and single-cell capture efficiency of up to 95%. This device offers 200 trap units in an area of 1 mm², which enables 100 single cells to be observed simultaneously using a microscope with a 20× objective lens. One thousand cells can be trapped sequentially within 2 min; this is faster than the values obtained with previously reported devices. Furthermore, the cells can also be recovered by reversely infusing solutions. The structure can be easily extended to a large scale, and a patterned array with 32,000 trap sites was accomplished on a single chip. This device can be a powerful tool for high-throughput single-cell analysis, cell heterogeneity investigation, and drug screening.

High-throughput, label-free, single-cell, microalgal lipid screening by machine-learning-equipped optofluidic time-stretch quantitative phase microscopy.

The development of reliable, sustainable, and economical sources of alternative fuels to petroleum is required to tackle the global energy crisis. One such alternative is microalgal biofuel, which is expected to play a key role in reducing the detrimental effects of global warming as microalgae absorb atmospheric CO2 via photosynthesis. Unfortunately, conventional analytical methods only provide population-averaged lipid amounts and fail to characterize a diverse population of microalgal cells with single-cell resolution in a non-invasive and interference-free manner. Here high-throughput label-free single-cell screening of lipid-producing microalgal cells with optofluidic time-stretch quantitative phase microscopy was demonstrated. In particular, Euglena gracilis, an attractive microalgal species that produces wax esters (suitable for biodiesel and aviation fuel after refinement), within lipid droplets was investigated. The optofluidic time-stretch quantitative phase microscope is based on an integration of a hydrodynamic-focusing microfluidic chip, an optical time-stretch quantitative phase microscope, and a digital image processor equipped with machine learning. As a result, it provides both the opacity and phase maps of every single cell at a high throughput of 10,000 cells/s, enabling accurate cell classification without the need for fluorescent staining. Specifically, the dataset was used to characterize heterogeneous populations of E. gracilis cells under two different culture conditions (nitrogen-sufficient and nitrogen-deficient) and achieve the cell classification with an error rate of only 2.15%. The method holds promise as an effective analytical tool for microalgae-based biofuel production. © 2017 International Society for Advancement of Cytometry.

Chronoamperometric interrogation of an electrochemical aptamer-based sensor with tetrahedral DNA nanostructure pendulums for continuous biomarker measurements.

Tetrahedral DNA nanostructure (TDN) is highly promising in developing electrochemical aptamer-based (E-AB) sensors for biomolecular detection, owing to its inherit programmability, spatial orientation and structural robustness. However, current interrogation strategies applied for TDN-based E-AB sensors, including enzyme-based amperometry, voltammetry, and electrochemical impedance spectroscopy, either require complicated probe design or suffer from limited applicability or selectivity. In this study, a TDN pendulum-empowered E-AB sensor interrogated by chronoamperometry for reagent-free and continuous monitoring of a blood clotting enzyme, thrombin, was developed. TDN pendulums with extended aptamer sequences at three vertices were immobilized on a gold electrode via a thiolated double-stranded DNA (dsDNA) at the fourth vertex, and their motion is modulated by the bonding of target thrombin to aptamers. We observed a significantly amplified signalling output on our sensor based on the TDN pendulum compared to E-AB sensors modified with linear pendulums. Moreover, our sensor achieved highly selective and rapidly responsive measurement of thrombin in both PBS and artificial urine, with a wide dynamic range from 1 pM to 10 nM. This study shows chronoamperometry-enabled continuous biomarker monitoring on a sub-second timescale with a drift-free baseline, demonstrating a novel approach to accurately detect molecular dynamics in real time.

Enhanced CRISPR/Cas12a-based quantitative detection of nucleic acids using double emulsion droplets.

Pairing droplet microfluidics and CRISPR/Cas12a techniques creates a powerful solution for the detection and quantification of nucleic acids at the single-molecule level, due to its specificity, sensitivity, and simplicity. However, traditional water-in-oil (W/O) single emulsion (SE) droplets often present stability issues, affecting the accuracy and reproducibility of assay results. As an alternative, water-in-oil-in-water (W/O/W) double emulsion (DE) droplets offer superior stability and uniformity for droplet digital assays. Moreover, unlike SE droplets, DE droplets are compatible with commercially available flow cytometry instruments for high-throughput analysis. Despite these advantages, no study has demonstrated the use of DE droplets for CRISPR-based nucleic acid detection. In our study, we conducted a comparative analysis to assess the performance of SE and DE droplets in quantitative detection of human papillomavirus type 18 (HPV18) DNA based on CRISPR/Cas12a. We evaluated the stability of SEs and DEs by examining size variation, merging extent, and content interaction before and after incubation at different temperatures and time points. By integrating DE droplets with flow cytometry, we achieved high-throughput and high-accuracy CRISPR/Cas12a-based quantification of target HPV18 DNA. The DE platform, when paired with CRISPR/Cas12a and flow cytometry techniques, emerges as a reliable tool for absolute quantification of nucleic acid biomarkers.

Passive microfluidic devices for cell separation.

The separation of specific cell populations is instrumental in gaining insights into cellular processes, elucidating disease mechanisms, and advancing applications in tissue engineering, regenerative medicine, diagnostics, and cell therapies. Microfluidic methods for cell separation have propelled the field forward, benefitting from miniaturization, advanced fabrication technologies, a profound understanding of fluid dynamics governing particle separation mechanisms, and a surge in interdisciplinary investigations focused on diverse applications. Cell separation methodologies can be categorized according to their underlying separation mechanisms. Passive microfluidic separation systems rely on channel structures and fluidic rheology, obviating the necessity for external force fields to facilitate label-free cell separation. These passive approaches offer a compelling combination of cost-effectiveness and scalability when compared to active methods that depend on external fields to manipulate cells. This review delves into the extensive utilization of passive microfluidic techniques for cell separation, encompassing various strategies such as filtration, sedimentation, adhesion-based techniques, pinched flow fractionation (PFF), deterministic lateral displacement (DLD), inertial microfluidics, hydrophoresis, viscoelastic microfluidics, and hybrid microfluidics. Besides, the review provides an in-depth discussion concerning cell types, separation markers, and the commercialization of these technologies. Subsequently, it outlines the current challenges faced in the field and presents a forward-looking perspective on potential future developments. This work hopes to aid in facilitating the dissemination of knowledge in cell separation, guiding future research, and informing practical applications across diverse scientific disciplines.

MSGM: An Advanced Deep Multi-Size Guiding Matching Network for Whole Slide Histopathology Images Addressing Staining Variation and Low Visibility Challenges.

Matching whole slide histopathology images to provide comprehensive information on homologous tissues is beneficial for cancer diagnosis. However, the challenge arises with the Giga-pixel whole slide images (WSIs) when aiming for high-accuracy matching. Learning-based methods are difficult to generalize well with large-size WSIs, necessitating the integration of traditional matching methods to enhance accuracy as the size increases. In this paper, we propose a multi-size guiding matching method applicable high-accuracy requirements. Specifically, we design learning multiscale texture to train deep descriptors, called TDescNet, that trains 64 ×64×256 and 256 ×256×128 size convolution layer as C64 and C256 descriptors to overcome staining variation and low visibility challenges. Furthermore, we develop the 3D-ring descriptor using sparse keypoints to support the description of large-size WSIs. Finally, we employ C64, C256, and 3D-ring descriptors to progressively guide refined local matching, utilizing geometric consistency to identify correct matching results. Experiments show that when matching WSIs of size 4096×4096 pixels, our average matching error is 123.48 [Formula: see text] and the success rate is 93.02 % in 43 cases. Notably, our method achieves an average improvement of 65.52 [Formula: see text] in matching accuracy compared to recent state-of-the-art methods, with enhancements ranging from 36.27 [Formula: see text] to 131.66 [Formula: see text]. Therefore, we achieve high-fidelity whole-slice image matching, and overcome staining variation and low visibility challenges, enabling assistance in comprehensive cancer diagnosis through matched WSIs.

Machine learning implementation strategy in imaging and impedance flow cytometry.

Imaging and impedance flow cytometry is a label-free technique that has shown promise as a potential replacement for standard flow cytometry. This is due to its ability to provide rich information and archive high-throughput analysis. Recently, significant efforts have been made to leverage machine learning for processing the abundant data generated by those techniques, enabling rapid and accurate analysis. Harnessing the power of machine learning, imaging and impedance flow cytometry has demonstrated its capability to address various complex phenotyping scenarios. Herein, we present a comprehensive overview of the detailed strategies for implementing machine learning in imaging and impedance flow cytometry. We initiate the discussion by outlining the commonly employed setup to acquire the data (i.e., image or signal) from the cell. Subsequently, we delve into the necessary processes for extracting features from the acquired image or signal data. Finally, we discuss how these features can be utilized for cell phenotyping through the application of machine learning algorithms. Furthermore, we discuss the existing challenges and provide insights for future perspectives of intelligent imaging and impedance flow cytometry.

Microsecond cell triple-sorting enabled by multiple pulse irradiation of femtosecond laser.

Femtosecond-laser-assisted cell manipulation, as one of the high throughput cell sorting techniques, is tailored for single-step multiple sorting based on controllable impulsive force. In this paper, femtosecond laser pulses are focused within a pocket structure and they induce an impulse force acting on the flowing objects. The impulsive force is shown to be controllable by a new method to adjust the femtosecond pulse properties. This allows precise streamline manipulation of objects having various physical qualities (e.g., weight and volume). The pulse energy, pulse number, and pulse interval of the femtosecond laser are altered to determine the impulsive force strength. The method is validated in single cell or bead triple-sorting experiments and its capability to perform streamline manipulation in as little as 10 µs is shown. The shift profiles of the beads acting under the impulsive force are studied in order to better understand the sorting mechanism. Additionally, beads and cells with different fluorescence intensities are successfully detected and directed into different microchannels, with maximum success rates of 90% and 64.5%, respectively. To sum up, all results suggest that this method has the potential to sort arbitrary subpopulations by altering the number of femtosecond pulses and that it takes the first step toward developing a single-step multi-selective system.

10 µm thick ultrathin glass sheet to realize a highly sensitive cantilever for precise cell stiffness measurement.

The micro-cantilever-based sensor platform has become a promising technique in the sensing area for physical, chemical and biological detection due to its portability, small size, label-free characteristics and good compatibility with "lab-on-a-chip" devices. However, traditional micro-cantilever methods are limited by their complicated fabrication, manipulation and detection, and low sensitivity. In this research, we proposed a 10 µm thick ultrathin, highly sensitive, and flexible glass cantilever integrated with a strain gauge sensor and presented its application for the measurement of single-cell mechanical properties. Compared to conventional methods, the proposed ultrathin glass sheet (UTGS)-based cantilever is easier to fabricate, has better physical and chemical properties, and shows a high linear relationship between resistance change and applied small force or displacement. The sensitivity of the cantilever is 15 µN µm-1 and the minimum detectable displacement at the current development stage is 500 nm, which is sufficient for cell stiffness measurement. The cantilever also possesses excellent optical transparency that supports real-time observation during measurement. We first calibrated the cantilever by measuring the Young's modulus of PDMS with known specific stiffness, and then we demonstrated the measurement of Xenopus oocytes and fertilized eggs in different statuses. By further optimizing the UTGS-based cantilever, we can extend its applicability to various measurements of different cells.