Fei Xu

DNA is an attractive molecular alternative for dense and durable information storage, which offers immense potential for long-term archival data storage. However, the unprotected DNA molecules may degrade when exposed to factors such as temperature variation, enzyme hydrolysis, and oxidative stress, which results in failure of data recovery. Here, we present a protection scheme that stabilizes DNA using chitosan and polyvinyl alcohol (PVA) nanofibers, enabling high-fidelity recovery after long-term storage. Chitosan was used to protect DNA backbone from temperature variations, and PVA nanofibers was used to encapsulate DNA to mitigate external damage such as strand breakage. Accelerated aging experiments showed that the combined chitosan/PVA protection increased the DNA half-life by nearly 30-fold relative to unprotected controls. Specifically, the protected 150-bp DNA exhibited a projected half-life of 97.8 years at 20 °C and 940.5 years at 10 °C. We further validated this approach by encoding textual data into the protected DNA. Sequencing results confirmed high-fidelity recovery of the encoded text. These results indicate that the proposed DNA protection approach provides a promising solution for long-term and reliable DNA storage.

A temperature-selective DNA nanoassembly system inspired by environmental selection, in which structural patterns defined by temperature are stably inherited through replication, offers a route toward adaptive artificial nanostructures.

Spiking neural membrane systems (SN P systems) are a class of bio-inspired models inspired by the activities and connectivity of neurons. Extensive studies have been made on SN P systems with synchronization-based communication, while further efforts are needed for the systems with rhythm-based communication. In this work, we design an asynchronous SN P system with resonant connections where all the enabled neurons in the same group connected by resonant connections should instantly produce spikes with the same rhythm. In the designed system, each of the three modules implements one type of the three operations associated with the edge detection of digital images, and they collaborate each other through the resonant connections. An algorithm called EDSNP for edge detection is proposed to simulate the working of the designed asynchronous SN P system. A quantitative analysis of EDSNP and the related methods for edge detection had been conducted to evaluate the performance of EDSNP. The performance of the EDSNP in processing the testing images is superior to the compared methods, based on the quantitative metrics of accuracy, error rate, mean square error, peak signal-to-noise ratio and true positive rate. The results indicate the potential of the temporal firing and the proper neuronal connections in the SN P system to achieve good performance in edge detection.

A temperature-responsive three-state switching DNA nanosystem that performs holding, reacting, and resetting at three different temperatures.