New single-cell technologies continue to fuel the explosive growth in scale of heterogeneous data. However, existing computational methods are inadequately scalable large datasets and therefore cannot uncover complex cellular heterogeneity.

ABSTRACT Cellular biophysical properties are the effective label‐free phenotypes indicative of differences in cell types, states, and functions. However, current phenotyping methods largely lack throughput specificity required majority cell‐based assays that involve large‐scale single‐cell characterization for inquiring inherently complex heterogeneity many biological systems. Further confounded by reported robust reproducibility quality control, widespread adoption mainstream cytometry...

Time-stretch imaging has been regarded as an attractive technique for high-throughput flow cytometry primarily owing to its real-time, continuous ultrafast operation. Nevertheless, two key challenges remain: (1) sufficiently high time-stretch image resolution and contrast is needed visualizing sub-cellular complexity of single cells, (2) the ability unravel heterogeneity highly diverse population cells - a central problem single-cell analysis in life sciences required. We here demonstrate...

The association of the intrinsic optical and biophysical properties cells to homeostasis pathogenesis has long been acknowledged. Defining these label-free cellular features obviates need for costly time-consuming labelling protocols that perturb living cells. However, wide-ranging applicability such cell-based assays requires sufficient throughput, statistical power sensitivity are unattainable with current technologies. To close this gap, we present a large-scale, integrative imaging flow...

Abstract Complex and irregular cell architecture is known to statistically exhibit fractal geometry, i.e., a pattern resembles smaller part of itself. Although variations in cells are proven be closely associated with the disease-related phenotypes that otherwise obscured standard cell-based assays, analysis single-cell precision remains largely unexplored. To close this gap, here we develop an image-based approach quantifies multitude biophysical fractal-related properties at subcellular...

A growing body of evidence has substantiated the significance quantitative phase imaging (QPI) in enabling cost-effective and label-free cellular assays, which provides useful insights into understanding biophysical properties cells their roles functions. However, available QPI modalities are limited by loss resolution at high throughput thus run short sufficient statistical power single-cell precision to define cell identities a large heterogeneous population cells-hindering utility...

We developed dispersion-free inertial focusing to overcome the inherent (size-)dispersion of which imposes challenges on applications requiring uniform positioning polydisperse particles, e.g. , microfiltration and flow cytometry.

Real-time <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">in situ</i> image analytics impose stringent latency requirements on intelligent neural network inference operations. While conventional software-based implementations the graphic processing unit (GPU)-accelerated platforms are flexible and have achieved very high throughput, they not suitable for latency-sensitive applications where real-time feedback is needed. Here, we demonstrate...

Free-space angular-chirp-enhanced delay (FACED) is an ultrafast laser-scanning technique that allows for high imaging speed at the scale orders of magnitude greater than current technologies. However, this advantage has only been restricted to bright-field and fluorescence imaging—limiting variety image contents hindering its applicability in image-based bioassay, which increasingly demands rich phenotypic readout a large scale. Here, we present new high-speed quantitative phase (QPI) based...

Abstract Image‐based cytometry faces challenges due to technical variations arising from different experimental batches and conditions, such as differences in instrument configurations or image acquisition protocols, impeding genuine biological interpretation of cell morphology. Existing solutions, often necessitating extensive pre‐existing data knowledge control samples across batches, have proved limited, especially with complex data. To overcome this, “Cyto‐Morphology Adversarial...

Scaling the number of measurable parameters, which allows for multidimensional data analysis and thus higher-confidence statistical results, has been main trend in advanced development flow cytometry. Notably, adding high-resolution imaging capabilities complex morphological cellular/sub-cellular structures. This is not possible with standard cytometers. However, it valuable advancing our knowledge cellular functions can benefit life science research, clinical diagnostics, environmental...

Abstract Motivation New single-cell technologies continue to fuel the explosive growth in scale of heterogeneous data. However, existing computational methods are inadequately scalable large datasets and therefore cannot uncover complex cellular heterogeneity. Results We introduce a highly graph-based clustering algorithm PARC - phenotyping by accelerated refined community-partitioning – for ultralarge-scale, high-dimensional data (&gt; 1 million cells). Using single cell mass cytometry,...

Biophysical properties of cells could complement and correlate biochemical markers to characterize a multitude cellular states. Changes in cell size, dry mass subcellular morphology, for instance, are relevant cell-cycle progression which is prevalently evaluated by DNA-targeted fluorescence measurements. Quantitative-phase microscopy (QPM) among the effective biophysical phenotyping tools that can quantify sizes sub-cellular density distribution single at high spatial resolution. However,...

Abstract Inertial focusing excels at the precise spatial ordering and separation of microparticles by size within fluid flows. However, this advantage, brought its inherent size-dependent dispersion, could turn into a drawback that challenges applications requiring consistent uniform positioning polydisperse particles, such as microfiltration flow cytometry. To overcome fundamental challenge, we introduce Dispersion-Free Focusing (DIF). This new method minimizes particle dispersion while...

Abstract Complex and irregular cell architecture is known to statistically exhibit fractal geometry, i.e., a pattern resembles smaller part of itself. Although variations in cells are proven be closely associated with the disease-related phenotypes that otherwise obscured standard cell-based assays, analysis single-cell precision remains largely unexplored. To close this gap, here we develop an image-based approach quantifies multitude biophysical fractal-related properties at subcellular...

We report a robust method based on generative deep learning to reconstruct quantitative phase image (QPI). By employing multiplexed asymmetric-detection time-stretch optical microscopy (multi-ATOM), we simultaneously captured multiple intensity contrasts of the same cell in microfluidic flow, revealing different phase-gradient orientations at high throughput (10,000 cells/sec). Using conditional adversarial networks (cGAN), performed systematic analysis how and their combinations influence...

Abstract Image-based cytometry faces constant challenges due to technical variations arising from different experimental batches and conditions, such as differences in instrument configurations or image acquisition protocols, impeding genuine biological interpretation of cell morphology. Existing solutions, often necessitating extensive pre-existing data knowledge control samples across batches, have proved limited, especially with complex data. To overcome this, we introduce Cyto-Morphology...

Scaling the number of measurable parameters, which allows for multidimensional data analysis and thus higher-confidence statistical results, has been main trend in advanced development flow cytometry. Notably, adding high-resolution imaging capabilities complex morphological cellular/sub-cellular structures. This is not possible with standard cytometers. However, it valuable advancing our knowledge cellular functions can benefit life science research, clinical diagnostics, environmental...

Phytoplankton is highly diversified in species, differing size, geometries, morphology and biochemical composition. Such diversity plays a critical role the atmospheric carbon cycle marine ecosystem. Large-scale quantitation classification of phytoplankton with taxonomic information thus significance environmental monitoring even biofuel production. To this end, we report high-throughput, label-free imaging flow cytometer (>10,000 cells/sec) based on quantitative phase time stretch...

Continuing development of image-based bioassay is mainly hampered by the lack throughput to systematically screen a large cell/tissue population under extensive experimental conditions; and overwhelming reliance on biochemical markers, which are not always effective, especially when there poor prior knowledge markers. Here we demonstrate ultralarge-scale, high-resolution "on-the-fly" quantitative phase imaging (QPI) single-cells whole-tissue-slide spinning-disk assay platform at an rate...

Abstract A growing body of evidence has substantiated the significance quantitative phase imaging (QPI) in enabling cost-effective and label-free cellular assay, which provides useful insights into understanding biophysical properties cells their roles functions. However, available QPI modalities are limited by loss resolution at high throughput thus run short sufficient statistical power single cell precision to define identities a large heterogeneous population – hindering utility...

Phytoplankton, highly diversified in species, plays a critical role the atmospheric carbon cycle and marine ecosystem [1]. Capable of doing large-scale analysis phytoplankton is thus significance environmental monitoring biofuel production. However, current techniques lack throughput to efficiently screen heterogeneous population at single-cell precision for accurate taxonomic classification and/or overwhelmingly rely upon biochemical assays, which are typically non-invasive destructive,...