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.

Double modulation SRS and SREF microscopy: signal contributions under pre-resonance conditions.

Pre-electronic resonance enhancement can increase the sensitivity of non-linear Raman microscopy to the single molecule detection limit. A major problem, however, is the generation of background signal due to unwanted linear and non-linear photophysical processes. In this work, we report the setup of a novel detection scheme for stimulated Raman scattering microspectroscopy based on the simultaneous modulation of pump and Stokes beam. Apart from allowing the parallel detection of stimulated Raman loss and gain (SRL and SRG), the setup gives access to the quantitative analysis of different sources of background signal. We report spectrally and temporally resolved measurements on three exemplary rhodamine dyes and derive the contributions of two-photon absorption and stimulated emission to their SRL, SRG, and stimulated Raman excited fluorescence signals. These results give guidelines for the further improvement of the sensitivity of non-linear Raman micospectroscopy under electronic pre-resonance conditions.

Synchronized subharmonic modulation in stimulated emission microscopy.

In this work, we have demonstrated a stimulated emission (SE)-based pump-probe microscopy with subharmonic fast gate synchronization, which allows over an order of magnitude improvement in signal-to-noise ratio. Critically, the alternative way of modulation is implemented with the highest possible frequency that follows the lasers' repetition rate. Its working is based on a homemade frequency divider that divides the repetition frequency (76 MHz) of the Ti:sapphire (probe) laser to half of the repetition frequency, 38 MHz, which is used to synchronously drive the pump laser and to provide the reference signal for the ensuing lock-in detection. In this way, SE can be detected with sensitivity reaching the theoretical (shot noise) limits, with a much lower time constant (0.1 ms) for faster image acquisition.

Raman image-activated cell sorting.

The advent of image-activated cell sorting and imaging-based cell picking has advanced our knowledge and exploitation of biological systems in the last decade. Unfortunately, they generally rely on fluorescent labeling for cellular phenotyping, an indirect measure of the molecular landscape in the cell, which has critical limitations. Here we demonstrate Raman image-activated cell sorting by directly probing chemically specific intracellular molecular vibrations via ultrafast multicolor stimulated Raman scattering (SRS) microscopy for cellular phenotyping. Specifically, the technology enables real-time SRS-image-based sorting of single live cells with a throughput of up to ~100 events per second without the need for fluorescent labeling. To show the broad utility of the technology, we show its applicability to diverse cell types and sizes. The technology is highly versatile and holds promise for numerous applications that are previously difficult or undesirable with fluorescence-based technologies.

Improved Exact Enumerative Algorithms for the Planted (l, d)-Motif Search Problem.

In this paper efficient exact algorithms are proposed for the planted ( l, d)-motif search problem. This problem is to find all motifs of length l that are planted in each input string with at most d mismatches. The "quorum" version of this problem is also treated in this paper to find motifs planted not in all input strings but in at least q input strings. The proposed algorithms are based on the previous algorithms called qPMSPruneI and qPMS7 that traverse a search tree starting from a l-length substring of an input string. To improve these previous algorithms, several techniques are introduced, which contribute to reducing the computation time for the traversal. In computational experiments, it will be shown that the proposed algorithms outperform the previous algorithms.