Flow cytometry is one of the most important technologies for high-throughput single-cell analysis. Fluorescent labeling acts as the primary approach for cellular analysis in flow cytometry. Nevertheless, the fluorescent tags are not applicable to all cases, especially to small molecules, for which labeling may significantly perturb the biological functionality. Spontaneous Raman scattering flow cytometry offers the capability to non-invasively detect chemical contents of cells but suffers from slow data acquisition. In order to achieve label-free high-throughput single-particle analysis using Raman scattering, we developed a 32-channel multiplex stimulated Raman scattering flow cytometry (SRS-FC) technique that can measure chemical contents of single particles at a speed of 5 μs per Raman spectrum. Using mixed polymer beads, we demonstrate the discrimination of different particles at a throughput of up to 11,000 particles per second. This is a four orders of magnitude improvement in throughput compared to conventional spontaneous Raman flow cytometry. As a proof of concept, we show the differentiation of 3T3-L1 cells at different states by SRS-FC according to the difference in cellular chemical content. The SRS-FC technique opens new opportunities for high-throughput and high-content chemical analysis of live cells in a label-free manner.

Muscle satellite cells are myogenic stem cells whose quiescence, activation, self-renewal, and differentiation are influenced by oxygen supply, an environmental regulator of stem cell activity. Accordingly, stem cell-specific oxygen signaling pathways precisely control the balance between muscle growth and regeneration in response to oxygen fluctuations, and hypoxia-inducible factors (HIFs) are central mediators of these cellular responses. However, the roles of HIFs in quiescent satellite cells and activated satellite cells (myoblasts) are poorly understood. Using transgenic mouse models for cell-specific HIF expression, we show here that HIF1α and HIF2α are preferentially expressed in pre- and post-differentiation myoblasts, respectively. Interestingly, double knockouts of HIF1α and HIF2α (HIF1α/2α dKO) generated with the MyoD system in embryonic myoblasts resulted in apparently normal muscle development and growth. However, HIF1α/2α dKO produced with the tamoxifen-inducible, satellite cell-specific Pax7 system in postnatal satellite cells delayed injury-induced muscle repair due to a reduced number of myoblasts during regeneration. Analysis of satellite cell dynamics on myofibers confirmed that HIF1α/2α dKO myoblasts exhibit reduced self-renewal but more pronounced differentiation under hypoxic conditions. Mechanistically, the HIF1α/2α dKO blunted hypoxia-induced activation of Notch signaling, a key determinant of satellite cell self-renewal. We conclude that HIF1α and HIF2α are dispensable for muscle stem cell function under normoxia but are required for maintaining satellite cell self-renewal in hypoxic environments. Our insights into a critical mechanism in satellite cell homeostasis during muscle regeneration could help inform research efforts to treat muscle diseases or improve muscle function.

With the rapid development of science and technology and economic society, the application of artificial intelligence(AI) is more and more common, its development has a profound impact on our work and lifestyle. In the field of e-commerce, AI technology has also been well applied and achieved good results. AI has become an important driving force for the development of e-commerce. This paper simply described the e-commerce development situation and prospects of AI technology, analyzes the present situation of the application of AI technology in the field of e-commerce, mainly study and discuss in detail from the aspect of assistant of AI, intelligent logistics, recommendation engine and the optimal pricing application through the research of e-commerce intelligent operation instance - Baidu take-away, probes into the important impact and great significance on the e-commerce development of artificial intelligence.

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