A deep learning-enabled portable imaging flow cytometer for cost-effective, highthroughput, and label-free analysis of natural water samples

We report a deep learning-enabled field-portable and cost-effective imaging flow cytometer that automatically captures phase-contrast color images of the contents of a continuously flowing water sample at a throughput of 100 mL/h.The device is based on partially coherent lens-free holographic microscopy and acquires the diffraction patterns of flowing micro-objects inside a microfluidic channel.These holographic diffraction patterns are reconstructed in real time using a deep learning-based phase-recovery and image-reconstruction method to produce a color image of each micro-object without the use of external labeling.Motion blur is eliminated by simultaneously illuminating the sample with red,green,and blue light-emitting diodes that are pulsed.Operated by a laptop computer,this portable device measures 15.5 cm×15 cm×12.5 cm,weighs 1 kg,and compared to standard imaging flow cytometers,it provides extreme reductions of cost,size and weight while also providing a high volumetric throughput over a large object size range.We demonstrated the capabilities of this device by measuring ocean samples at the Los Angeles coastline and obtaining images of its micro-and nanoplankton composition.Furthermore,we measured the concentration of a potentially toxic alga(Pseudo-nitzschia)in six public beaches in Los Angeles and achieved good agreement with measurements conducted by the California Department of Public Health.The cost-effectiveness,compactness,and simplicity of this computational platform might lead to the creation of a network of imaging flow cytometers for largescale and continuous monitoring of the ocean microbiome,including its plankton composition.

Miniscope3D:optimized single-shot miniature 3D fluorescence microscopy

Miniature fluorescence microscopes are a standard tool in systems biology.However,widefield miniature microscopes capture only 2D information,and modifications that enable 3D capabilities increase the size and weight and have poor resolution outside a narrow depth range.Here,we achieve the 3D capability by replacing the tube lens of a conventional 2D Miniscope with an optimized multifocal phase mask at the objective’s aperture stop.Placing the phase mask at the aperture stop significantly reduces the size of the device,and varying the focal lengths enables a uniform resolution across a wide depth range.The phase mask encodes the 3D fluorescence intensity into a single 2D measurement,and the 3D volume is recovered by solving a sparsity-constrained inverse problem.We provide methods for designing and fabricating the phase mask and an efficient forward model that accounts for the fieldvarying aberrations in miniature objectives.We demonstrate a prototype that is 17mm tall and weighs 2.5 grams,achieving 2.76μm lateral,and 15μm axial resolution across most of the 900×700×390μm^(3) volume at 40 volumes per second.The performance is validated experimentally on resolution targets,dynamic biological samples,and mouse brain tissue.Compared with existing miniature single-shot volume-capture implementations,our system is smaller and lighter and achieves a more than 2×better lateral and axial resolution throughout a 10×larger usable depth range.Our microscope design provides single-shot 3D imaging for applications where a compact platform matters,such as volumetric neural imaging in freely moving animals and 3D motion studies of dynamic samples in incubators and lab-on-a-chip devices.