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The rapid growth and development of technology has had significant implications for healthcare, personalized medicine, and our understanding of biology. In this work, we leverage the miniaturization of electronics to realize the first demonstration of wireless detection and communication of an electronic device inside a cell. This is a significant forward step towards a vision of non-invasive, intracellular wireless platforms for single-cell analyses. We demonstrate that a 25 $$\upmu $$ μ m wireless radio frequency identification (RFID) device can not only be taken up by a mammalian cell but can also be detected and specifically identified externally while located intracellularly. The S-parameters and power delivery efficiency of the electronic communication system is quantified before and after immersion in a biological environment; the results show distinct electrical responses for different RFID tags, allowing for classification of cells by examining the electrical output noninvasively. This versatile platform can be adapted for realization of a broad modality of sensors and actuators. This work precedes and facilitates the development of long-term intracellular real-time measurement systems for personalized medicine and furthering our understanding of intrinsic biological behaviors. It helps provide an advanced technique to better assess the long-term evolution of cellular physiology as a result of drug and disease stimuli in a way that is not feasible using current methods.

The identification of non-canonical UCP1-independent thermogenic mechanisms offers new opportunities to target such pathways to improve metabolic health. Based on our recent studies on Ca(2+) futile cycling thermogenesis in beige fat, we applied the newly developed implantable wireless optogenetic system to activate Ca(2+) cycling in an adipocyte-specific manner without external stimuli, i.e., fat-specific cold mimetics. Here, we describe the detailed methodology and application to the prevention of obesity.

Current clinical brain tumour therapy practices are based on tumour resection and post-operative chemotherapy or X-ray radiation. Resection requires technically challenging open-skull surgeries that can lead to major neurological deficits and, in some cases, death. Treatments with X-ray and chemotherapy, on the other hand, cause major side-effects such as damage to surrounding normal brain tissues and other organs. Here we report the development of an integrated nanomedicine-bioelectronics brain-machine interface that enables continuous and on-demand treatment of brain tumours, without open-skull surgery and toxicological side-effects on other organs. Near-infrared surface plasmon characteristics of our gold nanostars enabled the precise treatment of deep brain tumours in freely behaving mice. Moreover, the nanostars' surface coating enabled their selective diffusion in tumour tissues after intratumoral administration, leading to the exclusive heating of tumours for treatment. This versatile remotely controlled and wireless method allows the adjustment of nanoparticles' photothermal strength, as well as power and wavelength of the therapeutic light, to target tumours in different anatomical locations within the brain.

Pathogenic INS gene mutations are causative for mutant INS-gene-induced diabetes of youth (MIDY). We characterize a novel de novo heterozygous INS gene mutation (c.289A>C, p.T97P) that presented in an autoantibody-negative 5-month-old male infant with severe diabetic ketoacidosis. In silico pathogenicity prediction tools provided contradictory interpretations, while structural modeling indicated a deleterious effect on proinsulin folding. Transfection of wildtype and INS p.T97P expression and luciferase reporter constructs demonstrated elevated intracellular mutant proinsulin levels and dramatically impaired proinsulin/insulin and luciferase secretion. Notably, proteasome inhibition partially and selectively rescued INS p.T97P-derived luciferase secretion. Additionally, expression of INS p.T97P caused increased intracellular proinsulin aggregate formation and XBP-1s protein levels, consistent with induction of endoplasmic reticulum stress. We conclude that INS p.T97P is a newly identified pathogenic A-chain variant that is causative for MIDY via disruption of proinsulin folding and processing with induction of the endoplasmic reticulum stress response.

A body area sensor network (bodyNET) is a collection of networked sensors that can be used to monitor human physiological signals. For its application in next-generation personalized healthcare systems, seamless hybridization of stretchable on-skin sensors and rigid silicon readout circuits is required. Here, we report a bodyNET composed of chip-free and battery-free stretchable on-skin sensor tags that are wirelessly linked to flexible readout circuits attached to textiles. Our design offers a conformal skin-mimicking interface by removing all direct contacts between rigid components and the human body. Therefore, this design addresses the mechanical incompatibility issue between soft on-skin devices and rigid high-performance silicon electronics. Additionally, we introduce an unconventional radiofrequency identification technology where wireless sensors are deliberately detuned to increase the tolerance of strain-induced changes in electronic properties. Finally, we show that our soft bodyNET system can be used to simultaneously and continuously analyse a person’s pulse, breath and body movement. By integrating wireless stretchable on-skin sensor tags and flexible readout circuits attached to textiles using an unconventional radiofrequency identification design, a body area sensor network can be created that can continuously analyse a person’s pulse, breathing and body movement.

We report the realization of coupling-independent, robust wireless sensing of fully passive resistive sensors. $\mathcal{P}\mathcal{T}$-symmetric operation obviates sweeping, permitting real-time, single-point sensing. Self-oscillation is achieved through a fast-settling nonlinearity whose voltage amplitude is proportional to the sensor's resistance. These advances markedly simplify the reader. A dual time-scale theoretical framework generalizes system analysis to arbitrary operating conditions and a correction strategy reduces errors due to detuning from $\mathcal{P}\mathcal{T}$-symmetric conditions by an order of magnitude.

Wireless energy harvesting devices convert received ac energy into dc voltages suitable to power the back-end functionality of the devices. The low energy available to the devices require high ac–dc conversion efficiency in order for enough power to be delivered to the load. This paper presents a model to characterize loss through charge pump cells in wireless energy harvesting devices. The proposed model includes the time-domain effects of the input radio-frequency energy wave and provides additional insight into how clock and switch parameters along with architecture considerations can be used to improve the efficiency of ac–dc conversion. Results are verified using simulation in a 0.18- $\mu$ m CMOS technology. We show the impact of threshold voltage on reverse conduction and the limitations on increasing transistor switch sizes to support high current loads. Design examples use the presented model to optimize design parameters to decrease loss in the charge pump. We compare the performance between sine-wave and square-wave clocked charge pumps to show the tradeoff between charge pump loss and clock generation power consumption. Furthermore, the benefits of easily computing architectural changes is demonstrated using the proposed model showing how the calculated equivalent resistance can be used to determine the benefits of mixed-mode clocking.