Whole slide imaging (WSI) has recently been cleared for primary diagnosis in the U.S. A critical challenge of WSI is to perform accurate focusing in high speed. Traditional systems create a focus map prior to scanning. For each focus point on the map, a sample needs to be static in the x-y plane, and axial scanning is needed to maximize the contrast. Here we report a novel focus map surveying method for WSI. In this method, we illuminate the sample with two LEDs and recover the focus points based on 1D autocorrelation analysis. The reported method requires no axial scanning, no additional camera and lens, works for stained and transparent samples, and allows continuous sample motion in the surveying process. By using a 20× objective lens, we demonstrate a mean focusing error of ∼0.08  μm in the static mode and ∼0.17  μm in the continuous motion mode. The reported method may provide a turnkey solution for most existing WSI systems due to its simplicity, robustness, accuracy, and high speed. It may also standardize the imaging performance of WSI systems for digital pathology and find other applications in high-content microscopy, such as time-lapse live-cell imaging.

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In the presence of unpredictable disturbances and uncertainties, cells intelligently achieve their goals by sharing information via cell-cell communication and making collective decisions, which are more reliable compared to individual decisions. Inspired by adaptive sensor network algorithms studied in communication engineering, we propose that a multi-cellular adaptive network can convert unreliable decisions by individual cells into a more reliable cell-population decision. It is demonstrated using the effector T helper (a type of immune cell) population, which plays a critical role in initiating immune reactions in response to invading foreign agents (e.g., viruses, bacteria, etc.). While each individual cell follows a simple adaptation rule, it is the combined coordination among multiple cells that leads to the manifestation of "self-organizing" decision making via cell-cell communication.

Generating robust, predictable perturbations in cellular protein levels will advance our understanding of protein function and enable control of physiological outcomes in biotechnology applications. Previous studies have shown that controlling RNA transcription achieves perturbations in protein levels over a timescale of several hours. Here, we demonstrate the potential for harnessing the protein degradation machinery to achieve robust, rapid control of a specific protein level in the yeast Saccharomyces cerevisiae. Using a light-driven protein degradation machinery and red fluorescent proteins as reporters, we show that under constant transcriptional induction, repeated triangular fluctuations in protein levels can be generated by controlling the protein degradation rate. Consistent with previous results using transcriptional control, we observed a continuous decrease in the magnitude of fluctuations as the modulation frequency increased, indicating low-pass filtering of input perturbation. However, compared to hour-scale fluctuations observed using transcriptional control, modulating the protein degradation rate enabled five to ten minute-scale fluctuations. Our study demonstrates the potential for repeated control of protein levels by controlling protein degradation rate, at timescales much shorter than that achieved by transcriptional control.