In-silico clearing enables deep optical imaging of biological samples by correcting image blur caused by scattering and aberration. This breakthrough method offers researchers unprecedented insights ...into three-dimensional biological systems, with enormous potential for advancing biology and medicine to better understand living organisms and human health.
A general strategy for controlling particle movement across streams would enable new capabilities in single‐cell analysis, solid‐phase reaction control, and biophysics research. Transferring cells ...across streams is difficult to achieve in a well‐controlled manner, since it requires precise control of fluid flow along with external force fields or precisely manufactured mechanical structures. Herein a strategy is introduced for particle transfer based on passive inertial lift forces and shifts in the distribution of these forces for channels with shifting aspect ratios. Uniquely, use of the dominant wall‐effect lift parallel to the particle rotation direction is explored and utilized to achieve controllable cross‐stream motion. In this way, particles are positioned to migrate across laminar streams and enter a new solution without significant disturbance of the interface at rates exceeding 1000 particles per second and sub‐millisecond transfer times. The capabilities of rapid inertial solution exchange (RInSE) for preparation of hematological samples and other cellular assays are demonstrated. Lastly, improvements to inline flow cytometry after RInSE of excess fluorescent dye and focusing for downstream analysis are characterized. The described approach is simply applied to manipulating cells and particles and quickly exposing them to or removing them from a reacting solution, with broader applications in control and analysis of low affinity interactions on cells or particles.
Inertial lift forces present in finite Reynolds number confined flows are capable of manipulating particles traveling at high speeds. These geometry‐dependent forces are employed to transfer cells and particles from one solution to another at high rates, enabling automated operations on cells and expanding the utility of flow cytometric assays.
Drug susceptibility (also called chemosensitivity) is an important criterion for developing a therapeutic strategy for various cancer types such as breast cancer and leukemia. Recently, functional ...assays such as high-content screening together with genomic analysis have been shown to be effective for predicting drug susceptibility, but their clinical applicability is poor since they are time-consuming (several days long), labor-intensive, and costly. Here we present a highly simple, rapid, and cost-effective liquid biopsy for
ex vivo
drug-susceptibility testing of leukemia. The method is based on an extreme-throughput (>1 million cells per second), label-free, whole-blood imaging flow cytometer with a deep convolutional autoencoder, enabling image-based identification of the drug susceptibility of every single white blood cell in whole blood within 24 hours by simply flowing a drug-treated whole blood sample as little as 500 μL into the imaging flow cytometer without labeling. Our results show that the method accurately evaluates the drug susceptibility of white blood cells from untreated patients with acute lymphoblastic leukemia. Our method holds promise for affordable precision medicine.
The drug susceptibility of leukemia cells in whole blood is evaluated by using extreme-throughput imaging flow cytometry with deep learning.
The last two decades have witnessed a dramatic growth of wearable sensor technology, mainly represented by flexible, stretchable, on‐skin electronic sensors that provide rich information of the ...wearer's health conditions and surroundings. A recent breakthrough in the field is the development of wearable chemical sensors based on surface‐enhanced Raman spectroscopy (SERS) that can detect molecular fingerprints universally, sensitively, and noninvasively. However, while their sensing properties are excellent, these sensors are not scalable for widespread use beyond small‐scale human health monitoring due to their cumbersome fabrication process and limited multifunctional sensing capabilities. Here, a highly scalable, wearable SERS sensor is demonstrated based on an easy‐to‐fabricate, low‐cost, ultrathin, flexible, stretchable, adhesive, and biointegratable gold nanomesh. It can be fabricated in any shape and worn on virtually any surface for label‐free, large‐scale, in situ sensing of diverse analytes from low to high concentrations (10–106 × 10−9 m). To show the practical utility of the wearable SERS sensor, the sensor is tested for the detection of sweat biomarkers, drugs of abuse, and microplastics. This wearable SERS sensor represents a significant step toward the generalizability and practicality of wearable sensing technology.
Highly scalable, wearable surface‐enhanced Raman spectroscopy based on an easy‐to‐fabricate, low‐cost, ultrathin, flexible, stretchable, adhesive, and biointegratable gold nanomesh is demonstrated in this study. It can be fabricated in any shape and worn on virtually any surface for label‐free, large‐scale, in situ sensing of diverse analytes from low to high concentrations.
Optofluidic time-stretch quantitative phase imaging (OTS-QPI) is a powerful tool as it enables high-throughput (>10,000 cell/s) QPI of single live cells. OTS-QPI is based on decoding temporally ...stretched spectral interferograms that carry the spatial profiles of cells flowing on a microfluidic chip. However, the utility of OTS-QPI is troubled by difficulties in phase retrieval from the high-frequency region of the temporal interferograms, such as phase-unwrapping errors, high instrumentation cost, and large data volume. To overcome these difficulties, we propose and experimentally demonstrate frequency-shifted OTS-QPI by bringing the phase information to the baseband region. Furthermore, to show its boosted utility, we use it to demonstrate image-based classification of leukemia cells with high accuracy over 96% and evaluation of drug-treated leukemia cells via deep learning.
The development of reliable, sustainable, and economical sources of alternative fuels is an important, but challenging goal for the world. As an alternative to liquid fossil fuels, algal biofuel is ...expected to play a key role in alleviating global warming since algae absorb atmospheric CO2 via photosynthesis. Among various algae for fuel production, Euglena gracilis is an attractive microalgal species as it is known to produce wax ester (good for biodiesel and aviation fuel) within lipid droplets. To date, while there exist many techniques for inducing microalgal cells to produce and accumulate lipid with high efficiency, few analytical methods are available for characterizing a population of such lipid-accumulated microalgae including E. gracilis with high throughout, high accuracy, and single-cell resolution simultaneously. Here we demonstrate high-throughput, high-accuracy, single-cell screening of E. gracilis with fluorescence-assisted optofluidic time-stretch microscopy-a method that combines the strengths of microfluidic cell focusing, optical time-stretch microscopy, and fluorescence detection used in conventional flow cytometry. Specifically, our fluorescence-assisted optofluidic time-stretch microscope consists of an optical time-stretch microscope and a fluorescence analyzer on top of a hydrodynamically focusing microfluidic device and can detect fluorescence from every E. gracilis cell in a population and simultaneously obtain its image with a high throughput of 10,000 cells/s. With the multi-dimensional information acquired by the system, we classify nitrogen-sufficient (ordinary) and nitrogen-deficient (lipid-accumulated) E. gracilis cells with a low false positive rate of 1.0%. This method holds promise for evaluating cultivation techniques and selective breeding for microalgae-based biofuel production.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
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