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There is an explosive interest in the immediate and cost-effective analysis of field-collected biological samples, as many advanced biodetection tools are highly sensitive, yet immobile. On-site biosensors are portable and convenient sensors that provide detection results at the point of care. They are designed to secure precision in highly ionic and heterogeneous solutions with minimal hardware. Among various methods that are capable of such analysis, field-effect biosensors are promising candidates due to their unique sensitivity, manufacturing scalability, and integrability with computational circuitry. Recent developments in nanotechnological surface modification show promising results in sensing from blood, serum, and urine. This report gives a particular emphasis on the on-site efficacy of recently published field-effect biosensors, specifically, detection limits in physiological solutions, response times, and scalability. The survey of the properties and existing detection methods of four promising biotargets, exosomes, bacteria, viruses, and metabolites, aims at providing a roadmap for future field-effect and other on-site biosensors.

Current methods to detect avian influenza viruses (AIV) are time consuming and lo inw sensitivity, necessitating a faster and more sensitive sensor for on-site epidemic detection in poultry farms and urban population centers. This study reports a field effect transistor (FET) based AIV sensor that detects nucleoproteins (NP) within 30 minutes, down to an LOD of 10 EID mL from a live animal cloacal swab. Previously reported FET sensors for AIV detection have not targeted NPs, an internal protein shared across multiple strains, due to the difficulty of field-effect sensing in a highly ionic lysis buffer. The AIV sensor overcomes the sensitivity limit with an FET-based platform enhanced with a disposable well gate (DWG) that is readily replaceable after each measurement. In a single procedure, the virus-containing sample is immersed in a lysis buffer mixture to expose NPs to the DWG surface. In comparison with commercial AIV rapid kits, the AIV sensor is proved to be highly sensitive, fast, and compact, proving its potential effectiveness as a portable biosensor.

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Implantable image sensors have the potential to revolutionize neuroscience. Due to their small form factor requirements; however, conventional filters and optics cannot be implemented. These limitations obstruct high-resolution imaging of large neural densities. Recent advances in angle-sensitive image sensors and single-photon avalanche diodes have provided a path toward ultrathin lens-less fluorescence imaging, enabling plenoptic sensing by extending sensing capabilities to include photon arrival time and incident angle, thereby providing the opportunity for separability of fluorescence point sources within the context of light-field microscopy (LFM). However, the addition of spectral sensitivity to angle-sensitive LFM reduces imager resolution because each wavelength requires a separate pixel subset. Here, we present a 1024-pixel, 50  µm thick implantable shank-based neural imager with color-filter-grating-based angle-sensitive pixels. This angular-spectral sensitive front end combines a metal–insulator–metal (MIM) Fabry–Perot color filter and diffractive optics to produce the measurement of orthogonal light-field information from two distinct colors within a single photodetector. The result is the ability to add independent color sensing to LFM while doubling the effective pixel density. The implantable imager combines angular-spectral and temporal information to demix and localize multispectral fluorescent targets. In this initial prototype, this is demonstrated with 45 μm diameter fluorescently labeled beads in scattering medium. Fluorescent lifetime imaging is exploited to further aid source separation, in addition to detecting pH through lifetime changes in fluorescent dyes. While these initial fluorescent targets are considerably brighter than fluorescently labeled neurons, further improvements will allow the application of these techniques to in-vivo multifluorescent structural and functional neural imaging.