Time-stretch imaging has been regarded as an attractive technique for high-throughput imaging 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 for visualizing sub-cellular complexity of single cells, and (2) the ability to unravel the heterogeneity and complexity of the highly diverse population of cells - a central problem of single-cell analysis in life sciences - is required. We here demonstrate an optofluidic time-stretch imaging flow cytometer that enables these two features, in the context of high-throughput multi-class (up to 14 classes) phytoplantkton screening and classification. Based on the comprehensive feature extraction and selection procedures, we show that the intracellular texture/morphology, which is revealed by high-resolution time-stretch imaging, plays a critical role of improving the accuracy of phytoplankton classification, as high as 94.7%, based on multi-class support vector machine (SVM). We also demonstrate that high-resolution time-stretch images, which allows exploitation of various feature domains, e.g. Fourier space, enables further sub-population identification - paving the way toward deeper learning and classification based on large-scale single-cell images. Not only applicable to biomedical diagnostic, this work is anticipated to find immediate applications in marine and biofuel research.

Parallelized fluorescence imaging has been a long-standing pursuit that can address the unmet need for a comprehensive three-dimensional (3D) visualization of dynamical biological processes with minimal photodamage. However, the available approaches are limited to incomplete parallelization in only two dimensions or sparse sampling in three dimensions. We hereby develop a novel fluorescence imaging approach, called coded light-sheet array microscopy (CLAM), which allows complete parallelized 3D imaging without mechanical scanning. Harnessing the concept of an "infinity mirror", CLAM generates a light-sheet array with controllable sheet density and degree of coherence. Thus, CLAM circumvents the common complications of multiple coherent light-sheet generation in terms of dedicated wavefront engineering and mechanical dithering/scanning. Moreover, the encoding of multiplexed optical sections in CLAM allows the synchronous capture of all sectioned images within the imaged volume. We demonstrate the utility of CLAM in different imaging scenarios, including a light-scattering medium, an optically cleared tissue, and microparticles in fluidic flow. CLAM can maximize the signal-to-noise ratio and the spatial duty cycle, and also provides a further reduction in photobleaching compared to the major scanning-based 3D imaging systems. The flexible implementation of CLAM regarding both hardware and software ensures compatibility with any light-sheet imaging modality and could thus be instrumental in a multitude of areas in biological research.

BackgroundKnowledge construction is a form of communication in which people can work individually or collaboratively. Peer support services have been adopted by the public psychiatric and social welfare service as a regular form of intervention since 2015 in Hong Kong. Peer-based services can help people with bipolar disorder (BD) deal with the implications of the diagnosis, the way in which individuals with BD receive treatment, and the lifestyle changes that take place as a result of the diagnosis. Through a qualitative paradigm, this study aims to examine how individuals with BD use technical and expert-by-experience knowledge.MethodsA total of 32 clients of mental health services were recruited from hospitals, Integrated Community Centers for Mental Wellness, and non-governmental organizations. They participated in semi-structured individual interviews. All interviews were recorded, transcribed verbatim, and analyzed using thematic analysis with the aid of NVivo. The findings were verified by peer researchers.ResultsThree main themes are presented in this article, including how clients made sense of the knowledge provided by mental health professionals and peer support workers (PSWs), critical perspectives about peer support services, and the way in which the services are more than knowledge transfer alone. Participants generally indicated that knowledge sharing revolved around three experiences: mood changes, medications, and sense of hope. Nevertheless, an empathic understanding of the clients’ experience was more important than the sharing of knowledge. Some clients perceived medication as the chief means to recovery, so PSWs were not useful for them. However, PSW role models had an effect beyond mere knowledge transmission, as they could promote clients’ pursuit of functional recovery goals.ConclusionsThe present study has improved our understanding of knowledge sharing between clients with BD and health professionals or PSWs, which should take place in an empathic and hope-instilling manner. It has also emphasized the value of the presence of a role model who can speak convincingly with clients to facilitate recovery. The present findings can be used to improve the care of people with BD by generating important guidance with regard to enhancing the knowledge exchange between clients and health practitioners.

Complex and irregular cell architecture is known to statistically exhibit fractal geometry, i.e., a pattern resembles a smaller part of itself. Although fractal variations in cells are proven to be closely associated with the disease-related phenotypes that are otherwise obscured in the standard cell-based assays, fractal analysis with single-cell precision remains largely unexplored. To close this gap, here we develop an image-based approach that quantifies a multitude of single-cell biophysical fractal-related properties at subcellular resolution. Taking together with its high-throughput single-cell imaging performance (~10,000 cells/sec), this technique, termed single-cell biophysical fractometry, offers sufficient statistical power for delineating the cellular heterogeneity, in the context of classification of lung-cancer cell subtypes and tracking of cell-cycle progression. Further correlative fractal analysis shows that single-cell biophysical fractometry can enrich the standard morphological profiling depth and spearhead systematic fractal analysis of how cell morphology encodes cellular health and pathological conditions.

The performance of ultrafast time-stretch imaging at long wavelengths (beyond 1.5 μm) has suffered from low detection sensitivity due to the increasing loss of optical dispersive fibers. Here, we report an ultrafast optical imaging system with a line scan rate of ∼19  MHz at the 2.0-μm wavelength window by combining second-harmonic generation (SHG) with the highly sensitive time-stretch detection at 1.0 μm. In this imaging system, the sample is illuminated by the pulsed laser source at 2.0 μm in the spectrally encoding manner. After SHG, the encoded spectral signal at 2.0 μm is converted to 1.0 μm and then mapped to the time domain through a highly dispersive fiber at 1.0 μm, which provides a superior dispersion-to-loss ratio of ∼53  ps/nm/dB, ∼50  times larger than that of the standard fibers at 2.0 μm (typically ∼1.1  ps/nm/dB). These efforts make it possible for time-stretch technology not only being translated to longer wavelengths, where unique optical absorption contrast exists, but also benefitting from the high detection sensitivity at shorter wavelengths.