Stochastic electrotransport selectively enhances the transport of highly electromobile molecules

Nondestructive chemical processing of porous samples such as fixed biological tissues typically relies on molecular diffusion. Diffusion into a porous structure is a slow process that significantly delays completion of chemical processing. Here, we present a novel electrokinetic method termed stochastic electrotransport for rapid nondestructive processing of porous samples. This method uses a rotational electric field to selectively disperse highly electromobile molecules throughout a porous sample without displacing the low-electromobility molecules that constitute the sample. Using computational models, we show that stochastic electrotransport can rapidly disperse electromobile molecules in a porous medium. We apply this method to completely clear mouse organs within 1–3 days and to stain them with nuclear dyes, proteins, and antibodies within 1 day. Our results demonstrate the potential of stochastic electrotransport to process large and dense tissue samples that were previously infeasible in time when relying on diffusion.Simons Foundation. Postdoctoral FellowshipLife Sciences Research FoundationBurroughs Wellcome Fund (Career Awards at the Scientific Interface)Searle Scholars ProgramMichael J. Fox Foundation for Parkinson's ResearchUnited States. Defense Advanced Research Projects AgencyJPB FoundationNational Institutes of Health (U.S.)National Institutes of Health (U.S.) (Grant 1-U01-NS090473-01

Implantable Nanosensors for Human Steroid Hormone Sensing In Vivo Using a Self‐Templating Corona Phase Molecular Recognition

Dynamic measurements of steroid hormones in vivo are critical, but steroid sensing is currently limited by the availability of specific molecular recognition elements due to the chemical similarity of these hormones. In this work, a new, self-templating synthetic approach is applied using corona phase molecular recognition (CoPhMoRe) targeting the steroid family of molecules to produce near infrared fluorescent, implantable sensors. A key limitation of CoPhMoRe has been its reliance on library generation for sensor screening. This problem is addressed with a self-templating strategy of polymer design, using the examples of progesterone and cortisol sensing based on a styrene and acrylic acid copolymer library augmented with an acrylated steroid. The pendant steroid attached to the corona backbone is shown to self-template the phase, providing a unique CoPhMoRE design strategy with high efficacy. The resulting sensors exhibit excellent stability and reversibility upon repeated analyte cycling. It is shown that molecular recognition using such constructs is viable even in vivo after sensor implantation into a murine model by employing a poly (ethylene glycol) diacrylate (PEGDA) hydrogel and porous cellulose interface to limit nonspecific absorption. The results demonstrate that CoPhMoRe templating is sufficiently robust to enable a new class of continuous, in vivo biosensors

Implanted Nanosensors in Marine Organisms for Physiological Biologging: Design, Feasibility, and Species Variability

© 2018 American Chemical Society. In recent decades, biologists have sought to tag animals with various sensors to study aspects of their behavior otherwise inaccessible from controlled laboratory experiments. Despite this, chemical information, both environmental and physiological, remains challenging to collect despite its tremendous potential to elucidate a wide range of animal behaviors. In this work, we explore the design, feasibility, and data collection constraints of implantable, near-infrared fluorescent nanosensors based on DNA-wrapped single-wall carbon nanotubes (SWNT) embedded within a biocompatible poly(ethylene glycol) diacrylate (PEGDA) hydrogel. These sensors are enabled by Corona Phase Molecular Recognition (CoPhMoRe) to provide selective chemical detection for marine organism biologging. Riboflavin, a key nutrient in oxidative phosphorylation, is utilized as a model analyte in in vitro and ex vivo tissue measurements. Nine species of bony fish, sharks, eels, and turtles were utilized on site at Oceanogràfic in Valencia, Spain to investigate sensor design parameters, including implantation depth, sensor imaging and detection limits, fluence, and stability, as well as acute and long-term biocompatibility. Hydrogels were implanted subcutaneously and imaged using a customized, field-portable Raspberry Pi camera system. Hydrogels could be detected up to depths of 7 mm in the skin and muscle tissue of deceased teleost fish (Sparus aurata and Stenotomus chrysops) and a deceased catshark (Galeus melastomus). The effects of tissue heterogeneity on hydrogel delivery and fluorescence visibility were explored, with darker tissues masking hydrogel fluorescence. Hydrogels were implanted into a living eastern river cooter (Pseudemys concinna), a European eel (Anguilla anguilla), and a second species of catshark (Scyliorhinus stellaris). The animals displayed no observable changes in movement and feeding patterns. Imaging by high-resolution ultrasound indicated no changes in tissue structure in the eel and catshark. In the turtle, some tissue reaction was detected upon dissection and histopathology. Analysis of movement patterns in sarasa comet goldfish (Carassius auratus) indicated that the hydrogel implants did not affect swimming patterns. Taken together, these results indicate that this implantable form factor is a promising technique for biologging using aquatic vertebrates with further development. Future work will tune the sensor detection range to the physiological range of riboflavin, develop strategies to normalize sensor signal to account for the optical heterogeneity of animal tissues, and design a flexible, wearable device incorporating optoelectronic components that will enable sensor measurements in moving animals. This work advances the application of nanosensors to organisms beyond the commonly used rodent and zebrafish models and is an important step toward the physiological biologging of aquatic organisms