High-aspect ratio nanostructures such as nanowires and nanotubes are a powerful new tool for accessing the cell interior for delivery and sensing. Controlling and optimizing cellular access is a critical challenge for this new technology, yet even the most basic aspect of this process, whether these structures directly penetrate the cell membrane, is still unknown. Here we report the first quantification of hollow nanowires—nanostraws—that directly penetrate the membrane by observing dynamic ion delivery from each 100-nm diameter nanostraw. We discover that penetration is a rare event: 7.1 ± 2.7% of the nanostraws penetrate the cell to provide cytosolic access for an extended period for an average of 10.7 ± 5.8 penetrations per cell. Using time-resolved delivery, the kinetics of the first penetration event are shown to be adhesion dependent and coincident with recruitment of focal adhesion-associated proteins. These measurements provide a quantitative basis for understanding nanowire–cell interactions, and a means for rapidly assessing membrane penetration.

Nanodiagnostics as a field makes use of fundamental advances in nanobiotechnology to diagnose, characterize and manage disease at the molecular scale. As these strategies move closer to routine clinical use, a proper understanding of different imaging modalities, relevant biological systems and physical properties governing nanoscale interactions is necessary to rationally engineer next-generation bionanomaterials. In this Review, we analyse the background physics of several clinically relevant imaging modalities and their associated sensitivity and specificity, provide an overview of the materials currently used for in vivo nanodiagnostics, and assess the progress made towards clinical translation. This work provides a framework for understanding both the impressive progress made thus far in the nanodiagnostics field as well as presenting challenges that must be overcome to obtain widespread clinical adoption.

Endogenous biomarkers remain at the forefront of early disease detection efforts, but many lack the sensitivities and specificities necessary to influence disease management. Inspired by emerging adoptive cell transfer immunotherapies and the natural migration of immune cells to pathology, here we describe a new class of cell-based in vivo sensors for ultrasensitive disease detection. In our proof of concept, we perform adoptive transfer of syngeneic macrophages which were engineered to produce a synthetic biomarker upon adopting a 'tumor-associated' metabolic profile. Notably, the macrophage sensor detected tumors as small as 25-50 mm 3 , effectively tracked the immunological response in two models of acute inflammation, and was more sensitive than both protein and nucleic acid cancer biomarkers. This technology establishes a clinically translatable approach to early cancer detection and provides a conceptual framework for the use of engineered immune cells for the monitoring of many disease states in addition to cancer.

Nanowire (NW) arrays offer opportunities for parallel, nondestructive intracellular access for biomolecule delivery, intracellular recording, and sensing. Spontaneous cell membrane penetration by vertical nanowires is essential for these applications, yet the time- and geometry-dependent penetration process is still poorly understood. In this work, the dynamic NW-cell interface during cell spreading was examined through experimental cell penetration measurements combined with two mechanical models based on substrate adhesion force or cell traction forces. Penetration was determined by comparing the induced tension at a series of given membrane configurations to the critical membrane failure tension. The adhesion model predicts that penetration occurs within a finite window shortly after initial cell contact and adhesion, while the traction model predicts increasing penetration over a longer period. NW penetration rates determined from a cobalt ion delivery assay are compared to the predicted results from the two models. In addition, the effects of NW geometry and cell properties are systematically evaluated to identify the key factors for penetration.

Technologies for the longitudinal monitoring of a person's health are poorly integrated with clinical workflows, and have rarely produced actionable biometric data for healthcare providers. Here, we describe easily deployable hardware and software for the long-term analysis of a user's excreta through data collection and models of human health. The 'smart' toilet, which is selfcontained and operates autonomously by leveraging pressure and motion sensors, analyses the user's urine using a standard-of-care colorimetric assay that traces red-green-blue values from images of urinalysis strips, calculates the flow rate and volume of urine using computer vision as a uroflowmeter, and classifies stool according to the Bristol stool form scale using deep learning, with performance that is comparable to the performance of trained medical personnel. Each user of the toilet is identified through their fingerprint and the distinctive features of their anoderm, and the data are securely stored and analysed in an encrypted cloud server. The toilet may find uses in the screening, diagnosis and longitudinal monitoring of specific patient populations.