Thermodynamic model for voltammetric responses in conducting redox polymers.

Electroactive polymer materials are known to play important roles in a vast spectrum of modern applications such as in supercapacitors, fuel cells, batteries, medicine, and smart materials, etc. They are usually divided into two main groups: first, conducting π-conjugated organic polymers, which conduct electricity by cation-radicals delocalized over a polymer chain; second, redox polymers, which conduct electricity via an electron-hopping mechanism. Polymer materials belonging to these two main groups have been thoroughly studied and their thermodynamic and kinetic models have been built. However, in recent decades a lot of mixed-type materials have been discovered and investigated. To the best of our knowledge, a thermodynamic-based description of conducting redox polymers (CRPs) has not been provided yet. In this work, we present a thermodynamic model for voltammetric responses of conducting redox polymers. The derived model allows one to extract thermodynamic parameters of a CRP including the polaron delocalization degree and redox active groups interaction constant. The model was verified with voltammetric experiments on three recently synthesized CRPs and showed a satisfactory predictive ability. The simulated data are in good agreement with the experiment. We believe that developing theoretical descriptions for CRPs and other types of electroactive materials with the ability to simulate their electrochemical responses may help in future realization of new systems with superior characteristics for electrochemical energy storage, chemical sensors, pharmacological applications, etc.

Towards the development of a DNA automaton: modular RNA-cleaving deoxyribozyme logic gates regulated by miRNAs.

Advancements in DNA computation have unlocked molecular-scale information processing possibilities, utilizing the intrinsic properties of DNA for complex logical operations with transformative applications in biomedicine. DNA computation shows promise in molecular diagnostics, enabling precise and sensitive detection of genetic mutations and disease biomarkers. Moreover, it holds potential for targeted gene regulation, facilitating personalized therapeutic interventions with enhanced efficacy and reduced side effects. Herein, we have developed six DNAzyme-based logic gates able to process YES, AND, and NOT Boolean logic. The novelty of this work lies in their additional functionalization with a common DNA scaffold for increased cooperativity in input recognition. Moreover, we explored hierarchical input binding to multi-input logic gates, which helped gate optimization. Additionally, we developed a new design of an allosteric hairpin switch used to implement NOT logic. All DNA logic gates achieved the desired true-to-false output signal when detecting a panel of miRNAs, known for their important role in malignancy regulation. This is the first example of DNAzyme-based logic gates having all input-recognizing elements integrated in a single DNA nanostructure, which provides new opportunities for building DNA automatons for diagnosis and therapy of human diseases.

Cationic Magnetite Nanoparticles for Increasing siRNA Hybridization Rates.

An investigation of the interaction principles of nucleic acids and nanoparticles is a priority for the development of theoretical and methodological approaches to creating bionanocomposite structures, which determines the area and boundaries of biomedical use of developed nanoscale devices. «Nucleic acid-magnetic nanoparticle¼ type constructs are being developed to carry out the highly efficient detection of pathogens, create express systems for genotyping and sequencing, and detect siRNA. However, the data available on the impact of nanoparticles on the behavior of siRNA are insufficient. In this work, using nanoparticles of two classical oxides of inorganic chemistry (magnetite (Fe3O4) and silica (SiO2) nanoparticles), and widely used gold nanoparticles, we show their effect on the rate of siRNA hybridization. It has been determined that magnetite nanoparticles with a positive charge on the surface increase the rate of siRNA hybridization, while negatively charged magnetite and silica nanoparticles, or positively charged gold nanoparticles, do not affect hybridization rates (HR).