Biotechnological applications of purine and pyrimidine deaminases.

Deaminases, ubiquitous enzymes found in all living organisms from bacteria to humans, serve diverse and crucial functions. Notably, purine and pyrimidine deaminases, while biologically essential for regulating nucleotide pools, exhibit exceptional versatility in biotechnology. This review systematically consolidates current knowledge on deaminases, showcasing their potential uses and relevance in the field of biotechnology.

Unraveling Brain Synchronisation Dynamics by Explainable Neural Networks using EEG Signals: Application to Dyslexia Diagnosis.

The electrical activity of the neural processes involved in cognitive functions is captured in EEG signals, allowing the exploration of the integration and coordination of neuronal oscillations across multiple spatiotemporal scales. We have proposed a novel approach that combines the transformation of EEG signal into image sequences, considering cross-frequency phase synchronisation (CFS) dynamics involved in low-level auditory processing, with the development of a two-stage deep learning model for the detection of developmental dyslexia (DD). This deep learning model exploits spatial and temporal information preserved in the image sequences to find discriminative patterns of phase synchronisation over time achieving a balanced accuracy of up to 83%.

Bridging Imaging and Clinical Scores in Parkinson's Progression via Multimodal Self-Supervised Deep Learning.

Neurodegenerative diseases pose a formidable challenge to medical research, demanding a nuanced understanding of their progressive nature. In this regard, latent generative models can effectively be used in a data-driven modeling of different dimensions of neurodegeneration, framed within the context of the manifold hypothesis. This paper proposes a joint framework for a multi-modal, common latent generative model to address the need for a more comprehensive understanding of the neurodegenerative landscape in the context of Parkinson's disease (PD).

Reconstruction of the Maërl habitat to better understand its ecological integrity.

Maërl habitats are composed of coralline red algae species that can live freely rolling on the seabed and forming nodules, the so-called rhodoliths, or incrusted forming coralligenous habitats. Maërl habitats are generally distributed in the Mediterranean at a depth of between 30 m and 70 m and are considered one of the most emblematic Mediterranean seabeds. In the present study, the complex structure of maërl habitats was investigated to i) characterise the relief features and classify the different sediments, ii) to estimate the abundance of the coralline red algae (both rhodoliths and encrusting ones) and iii) to analyse the biodiversity of the species inhabiting the habitat.