Selective Optical Imaging for Detection of Bacterial Biofilms in Tissues.

SIGNIFICANCE: The development of an imaging technique to accurately identify biofilm regions on tissues and in wounds is crucial for the implementation of precise surface-based treatments, leading to better patient outcomes and reduced chances of infection. AIM: The goal of this study was to develop an imaging technique that relies on selective trypan blue (TB) staining of dead cells, necrotic tissues, and bacterial biofilms, to identify biofilm regions on tissues and wounds. APPROACH: The study explored combinations of ambient multi-colored LED lights to obtain maximum differentiation between stained biofilm regions and the underlying chicken tissue or glass substrate during image acquisition. The TB imaging results were then visually and statistically compared to fluorescence images using a shape similarity measure. RESULTS: The comparisons between the proposed TB staining method and the fluorescence standard used to detect biofilms on tissues and glass substrates showed up to 97 percent similarity, suggesting that the TB staining method is a promising technique for identifying biofilm regions. CONCLUSIONS: The TB staining method demonstrates significant potential as an effective imaging technique for the identification of fluorescing and non-fluorescing biofilms on tissues and in wounds. This approach could lead to improved precision in surface-based treatments and better patient outcomes.

Pulse Shape and Timing Dependence on the Spike-Timing Dependent Plasticity Response of Ion-Conducting Memristors as Synapses.

Ion-conducting memristors comprised of the layered materials Ge2Se3/SnSe/Ag are promising candidates for neuromorphic computing applications. Here, the spike-timing dependent plasticity (STDP) application is demonstrated for the first time with a single memristor type operating as a synapse over a timescale of 10 orders of magnitude, from nanoseconds through seconds. This large dynamic range allows the memristors to be useful in applications that require slow biological times, as well as fast times such as needed in neuromorphic computing, thus allowing multiple functions in one design for one memristor type-a "one size fits all" approach. This work also investigated the effects of varying the spike pulse shapes on the STDP response of the memristors. These results showed that small changes in the pre- and postsynaptic pulse shape can have a significant impact on the STDP. These results may provide circuit designers with insights into how pulse shape affects the actual memristor STDP response and aid them in the design of neuromorphic circuits and systems that can take advantage of certain features in the memristor STDP response that are programmable via the pre- and postsynaptic pulse shapes. In addition, the energy requirement per memristor is approximated based on the pulse shape and timing responses. The energy requirement estimated per memristor operating on slower biological timescales (milliseconds to seconds) is larger (nanojoules range), as expected, than the faster (nanoseconds) operating times (~0.1 pJ in some cases). Lastly, the memristors responded in a similar manner under normal STDP conditions (pre- and post-spikes applied to opposite memristor terminals) as they did to the case where a waveform corresponding to the difference between pre- and post-spikes was applied to only one electrode, with the other electrode held at ground potential. By applying the difference signal to only one terminal, testing of the memristor in various applications can be achieved with a simplified test set-up, and thus be easier to accomplish in most laboratories.