New tools are needed to match cancer patients with effective treatments. Patient-derived organoids offer a high-throughput platform to personalize treatments and discover novel therapies. Currently, methods to evaluate drug response in organoids are limited because they overlook cellular heterogeneity. In this study, non-invasive optical metabolic imaging (OMI) of cellular heterogeneity was characterized in breast cancer (BC) and pancreatic cancer (PC) patient-derived organoids. Baseline heterogeneity was analyzed for each patient, demonstrating that single-cell techniques, such as OMI, are required to capture the complete picture of heterogeneity present in a sample. Treatment-induced changes in heterogeneity were also analyzed, further demonstrating that these measurements greatly complement current techniques that only gauge average cellular response. Finally, OMI of cellular heterogeneity in organoids was evaluated as a predictor of clinical treatment response for the first time. Organoids were treated with the same drugs as the patient's prescribed regimen, and OMI measurements of heterogeneity were compared to patient outcome. OMI distinguished subpopulations of cells with divergent and dynamic responses to treatment in living organoids without the use of labels or dyes. OMI of organoids agreed with long-term therapeutic response in patients. With these capabilities, OMI could serve as a sensitive high-throughput tool to identify optimal therapies for individual patients, and to develop new effective therapies that address cellular heterogeneity in cancer.

We report an all-printed thin-film transistor (TFT) on a polyimide substrate with linear transconductance response. The TFT is based on our purified single-walled carbon nanotube (SWCNT) solution that is primarily consists of semiconducting carbon nanotubes (CNTs) with low metal impurities. The all-printed TFT exhibits a high ON/OFF ratio of around 103and bias-independent transconductance over a certain gate bias range. Such bias-independent transconductance property is different from that of conventional metal-oxide-semiconductor field-effect transistors (MOSFETs) due to the special band structure and the one-dimensional (1D) quantum confined density of state (DOS) of CNTs. The bias-independent transconductance promises modulation linearity for analog electronics.

Fluorescence lifetime imaging microscopy (FLIM) is a powerful technique, capable of label-free assessment of the metabolic state and function within single cells. The FLIM measurements of autofluorescence were recently shown to be sensitive to the functional state and subtype of T cells. Therefore, autofluorescence FLIM could improve cell manufacturing technologies for adoptive immunotherapy, which currently require a time-intensive process of cell labeling with fluorescent antibodies. However, current autofluorescence FLIM implementations are typically too slow, bulky, and prohibitively expensive for use in cell manufacturing pipelines. Here we report a single photon-excited confocal whole-cell autofluorescence system that uses fast field-programmable gate array-based time tagging electronics to achieve time-correlated single photon counting (TCSPC) of single-cell autofluorescence. The system includes simultaneous near-infrared bright-field imaging and is sensitive to variations in the fluorescence decay profile of the metabolic coenzyme NAD(P)H in human T cells due to the activation state. The classification of activated and quiescent T cells achieved high accuracy and precision (area under the receiver operating characteristic curve, AUC = 0.92). The lower-cost, higher acquisition speed, and resistance to pile-up effects at high photon flux compared to traditional multiphoton-excited FLIM and TCSPC implementations with similar SNR make this system attractive for integration into flow cytometry, sorting, and quality control in cell manufacturing.