Technology

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UP-CATRIN offers a technological solution for the design and synthesis of densely and selectively functionalized conductive graphenes, for seamless integration in the biosensing devices. This is achieved through the chemistry of fluorographene, enabling the synthesis of tailored graphene derivatives. The functionalization with out-of-plane groups serves for conjugation with biorecognition units, and the in-plane dopants in vacancies boost the electrochemical activity. A prominent advantage of these graphene derivatives lies in their uniform functional group distribution and high degree of functionalization. This uniformity fosters specific binding interactions while effectively reducing interference from sample contaminants, thereby markedly improving the devices’ signal-to-noise ratio, selectivity, and sensitivity. The conjugation handles are grafted directly to the graphene backbone. This design eliminates the need for lengthy linkers and optimizes electron transfer.

The immobilization technique in conjunction with aptamers’ size, solution ionic strength, thermodynamic effects and the DNA structure affect the MNPs’ coverage and aptamers’ arrangement. Well established cross-linking methodologies to immobilize DNA sequences on MNPs will be examined and evaluated. The selected aptamers will also be tested in the presence of other similar proteins and more complex solutions with known concentrations of the selected biomarkers. Moreover, we should also determine the low detection limit (LOD), the lowest concentration of the selected biomarkers that our aptamers can detect. Possible redesign and optimization might be needed after the first testing. Immobilization on MNPs might change the binding capacity and specificity of the aptamers. Thus, it is essential to use our results as input for optimization of the final product before the involvement of graphene. Towards achieving our goal of high sensitivity and specificity.

Schematic representation of aptamer structure

Magnetite (Fe3O4) MNPs will be synthesized while electrochemical sensing is required, electrical conductivity will be achieved by transforming, at a second synthetic stage, magnetite MNPs to hybrid systems (Janus MNPs) composed of a gold contact on one side and a magnetic part on the other. These hybrid MNPs will be conjugated with the aptamers following established protocols and finally purified to be used within the platform. MNPs will facilitate sample purification and avoid non-specific signals, as well as to act as flow control at different stages of the bioassay e.g., incubation of bioreceptors with the sample, purification, recognition, and signal acquisition.

Firstly, by adequate selection and moving of external magnetic field the MNP/aptamer conjugates will be regionally retained while secondly, the magnetic field is directed towards the electrodes where the recognition process occurs. Finally, MNPs not binding to the electrode are eliminated towards an absorbent pad. At each specific stage, magnetic field parameters (field amplitude, duration, field sign) will be independently optimized to maximize the signal acquisition.

Illustration of the optimum scenario, in which each MNP has only one aptamer immobilized and targets a specific biomarker. The four stages are depicted: a). before, b) during, and c), d) after the detection of its target biomarker.

The use of AI will aim for two goals: a regression to forecast the suitability of aptamers to build biosensors, and the use of Generative AI as a source of both optimal molecules for graphene functionalization and new aptamer structures for the biosensors.
In order to achieve these targets, we will explore the possibilities brought by training our ANNs (Artificial Neural Networks) with real 1D and 2D structures and their associated features, provided by partners from the project. We intend to research different complexities for our ANN structures, such as GNNs (Graph Neural Networks) both for tasks of regression and Adversarial or Variational Generation.

This image belongs to the publication with DOI 10.3934/mbe.2023102

It is coming soon

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