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 self-contained 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.

Nanofluidics represents a promising solution to problems in fields ranging from biomolecular analysis to optical property tuning. Recently a number of simple nanofluidic fabrication techniques have been introduced that exploit the deformability of elastomeric materials like polydimethylsiloxane (PDMS). These techniques are limited by the complexity of the devices that can be fabricated, which can only create straight or irregular channels normal to the direction of an applied strain. Here, we report a technique for nanofluidic fabrication based on the controlled collapse of microchannel structures. As is demonstrated, this method converts the easy to control vertical dimension of a PDMS mold to the lateral dimension of a nanochannel. We demonstrate here the creation of complex nanochannel structures as small as 60 nm and provide simple design rules for determining the conditions under which nanochannel formation will occur. The applicability of the technique to biomolecular analysis is demonstrated by showing DNA elongation in a nanochannel and a technique for optofluidic surface enhanced Raman detection of nucleic acids.

Pref-1 is an EGF-repeat-containing protein that inhibits adipocyte differentiation. To better understand the origin and development of white adipose tissue (WAT), we generated transgenic mouse models for transient or permanent fluorescent labeling of cells using the Pref-1 promoter, facilitating inducible ablation. We show that Pref-1-marked cells retain proliferative capacity and are very early adipose precursors, prior to expression of Zfp423 or PPARγ. In addition, the Pref-1-marked cells establish that adipose precursors are mesenchymal, but not endothelial or pericytal, in origin. During embryogenesis, Pref-1-marked cells first appear in the dorsal mesenteric region as early as embryonic day 10.5 (E10.5). These cells become lipid-laden adipocytes at E17.5 in the subcutaneous region, whereas visceral WAT develops after birth. Finally, ablation of Pref-1-marked cells prevents not only embryonic WAT development but also later adult adipose expansion upon high-fat feeding, demonstrating the requirement of Pref-1 cells for adipogenesis.