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Fast, nondestructive three-dimensional (3D) imaging of live suspension cells remains challenging without substrate treatment or fixation, precluding scalable single-cell morphometry with minimal alterations. While optical sectioning techniques achieve 3D live cell imaging, lateral versus depth resolution differences further complicate analysis. We present a scalable microfluidic method capable of 3D fluorescent isotropic imaging of live, nonadherent cells suspended inside picoliter droplets with high-speed single-cell volumetric readout (800 to 1,200 slices in 5 to 8 s) and near-diffraction limit resolution (~216 nm). The platform features a droplet trap array that leverages flow-induced droplet interfacial shear to generate intradroplet microvortices, which rotate single cells on their axis to enable optical projection tomography (OPT)-based imaging. This allows gentle (~1 mPa shear stress) observation of cells encapsulated inside nontoxic isotonic buffer droplets, facilitating scalable OPT acquisition by simultaneous spinning of hundreds of cells. We demonstrate 3D imaging of live myeloid and lymphoid cells in suspension, including K562 cells, as well as naive and activated T cells—small cells prone to movement in their suspended phenotype. Our fully suspended, orientation-independent cell morphometry, driven by isotropic imaging and spherical harmonic analysis, enabled the study of primary T cells across various immunological activation states. This approach unveiled six distinct nuclear content distributions, contrasting with conventional 2D images that typically portray spheroid and bean-like nuclear shapes associated with lymphocytes. Our arrayed-droplet OPT technology is capable of isotropic, single live-cell 3D imaging, with the potential to perform large-scale morphometry of immune cell effector function states while providing compatibility with microfluidic droplet operations. 

Shared logs offer linearizable total order across storage shards. However, they enforce this order eagerly upon ingestion, leading to high latencies. We observe that in many modern shared-log applications, while linearizable ordering is necessary, it is not required eagerly when ingesting data but only later when data is consumed. Further, readers are naturally decoupled in time from writers in these applications. Based on this insight, we propose LazyLog, a novel shared log abstraction. LazyLog lazily binds records (across shards) to linearizable global positions and enforces this before a log position can be read. Such lazy ordering enables low ingestion latencies. Given the time decoupling, LazyLog can establish the order well before reads arrive, minimizing overhead upon reads. We build two LazyLog systems that provide linearizable total order across shards. Our experiments show that LazyLog systems deliver significantly lower latencies than conventional, eager-ordering shared logs. 

Quorum systems (e.g., replicated state machines) are critical distributed systems. Building correct, high-performance quorum systems is known to be hard. A major reason is that the protocols in quorum systems lead to non-deterministic state changes and complex branching conditions based on different events (e.g., timeouts). Traditionally, these systems are built with an asynchronous coding style with event-driven callbacks, but often lead to “callback hell” that makes code hard to follow and maintain. Converting to synchronous coding styles (e.g., using coroutines) is challenging because of the complex branching conditions. In this paper, we present Dependably Fast (DepFast), an effective, expressive framework for developing quorum systems. DepFast provides a unique QuorumEvent abstraction to enable building quorum systems in a synchronous style. It also supports composition of multiple events, e.g., timeouts, different quorums. To evaluate DepFast, we use it to implement two quorum systems, Raft and Copilot. We show that complex quorum systems implemented by DepFast are easy to write and have high performance. Specifically, it takes 25%–35% fewer lines of code to implement Raft and Copilot using DepFast, and the DepFast-based implementations have comparable performance with the state-of-the-art systems. 

Quorum systems (e.g., replicated state machines) are critical distributed systems. Building correct, high-performance quorum systems is known to be hard. A major reason is that the protocols in quorum systems lead to non-deterministic state changes and complex branching conditions based on different events (e.g., timeouts). Traditionally, these systems are built with an asynchronous coding style with event-driven callbacks, but often lead to “callback hell” that makes code hard to follow and maintain. Converting to synchronous coding styles (e.g., using coroutines) is challenging because of the complex branching conditions. In this paper, we present Dependably Fast (DepFast), an effective, expressive framework for developing quorum systems. DepFast provides a unique QuorumEvent abstraction to enable building quorum systems in a synchronous style. It also supports composition of multiple events, e.g., timeouts, different quorums. To evaluate DepFast, we use it to implement two quorum systems, Raft and Copilot. We show that complex quorum systems implemented by DepFast are easy to write and have high performance. Specifically, it takes 25%–35% fewer lines of code to implement Raft and Copilot using DepFast, and the DepFast-based implementations have comparable performance with the state-of-the-art systems. 

Many cellular analytical technologies measure only the average response from a cell population with an assumption that a clonal population is homogenous. The ensemble measurement often masks the difference among individual cells that can lead to misinterpretation. The advent of microfluidic technology has revolutionized single-cell analysis through precise manipulation of liquid and compartmentalizing single cells in small volumes (pico- to nano-liter). Due to its advantages from miniaturization, microfluidic systems offer an array of capabilities to study genomics, transcriptomics, and proteomics of a large number of individual cells. In this regard, microfluidic systems have emerged as a powerful technology to uncover cellular heterogeneity and expand the depth and breadth of single-cell analysis. This review will focus on recent developments of three microfluidic compartmentalization platforms (microvalve, microwell, and microdroplets) that target single-cell analysis spanning from proteomics to genomics. We also compare and contrast these three microfluidic platforms and discuss their respective advantages and disadvantages in single-cell analysis.