The unsupervised non-negative matrix factorization disentangles the molecular components in the human skin in vivo from the Raman microspectroscopy data.

Blood cell analysis is one of the standard clinical tests. Despite the widespread use of exogenous markers for blood cell quantification, label-free optical methods are still of high demand due to their possibility for in vivo application and signal specific to the biochemical state of the cell provided by native fluorophores. Here we report the results of blood cell characterization using label-free fluorescence imaging techniques and flow-cytometry. Autofluorescence parameters of different cell types -white blood cells, red blood cells, erythrophagocytic cells -are assessed and analyzed in terms of molecular heterogeneity and possibilities of differentiation between different cell types in vitro and in vivo.

Molecular, morphological, and physiological heterogeneity is the inherent property of cells which governs differences in their response to external influence. Tumor cell metabolic heterogeneity is of a special interest due to its clinical relevance to tumor progression and therapeutic outcomes. Rapid, sensitive, and noninvasive assessment of metabolic heterogeneity of cells is a great demand for biomedical sciences. Fluorescence lifetime imaging (FLIM), which is an all-optical technique, is an emerging tool for sensing and quantifying cellular metabolism by measuring fluorescence decay parameters of endogenous fluorophores, such as NAD(P)H. To achieve accurate discrimination between metabolically diverse cellular subpopulations, appropriate approaches to FLIM data collection and analysis are needed. In this paper, the unique capability of FLIM to attain the overarching goal of discriminating metabolic heterogeneity is demonstrated. This has been achieved using an approach to data analysis based on the nonparametric analysis, which revealed a much better sensitivity to the presence of metabolically distinct subpopulations compared to more traditional approaches of FLIM measurements and analysis. The approach was further validated for imaging cultured cancer cells treated with chemotherapy. These results pave the way for accurate detection and quantification of cellular metabolic heterogeneity using FLIM, which will be valuable for assessing therapeutic vulnerabilities and predicting clinical outcomes.

Systematic autofluorescence characterization of all coded amino acids was performed Lysine, a non-aromatic amino acid, exhibited the highest fluorescent signal Revirsible transition between cysteine crystals determines on-off autofluorescence Ultrafast lifetime decay shown experimentally, confirming governing role in emission

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