Il proteoma mitocondriale cardiaco e le sue implicazioni con i meccanismi di cardioprotezione

Le malattie cardiache rappresentano una delle maggiori cause di morbilità e mortalità dei paesi occidentali. I mitocondri sono elementi essenziali nella risposta cellulare al danno, negli eventi di morte cellulare, e nei meccanismi cardioprotettivi. Comprendere il ruolo del proteoma mitocondriale cardiaco nei meccanismi cardioprotettivi è un obiettivo chiave per i ricercatori impegnati ad individuare nuove strategie di prevenzione e cura delle malattie cardiache. Il diverso profilo delle proteine rilevate in un tessuto o cellula, o la variazione quantitativa di proteine possono essere potenziali indicatori di uno stato fisiologico e/o patologico. In questo lavoro è stato approfondito il ruolo che il proteoma mitocondriale cardiaco esercita nei meccanismi cellulari associati alla cardioprotezione, utilizzando i dati disponibili in letteratura. In particolare sono state esposte le strategie di proteomica utilizzate dai ricercatori per lo studio del proteoma mitocondriale e delle sue variazioni quantitative e modifiche post-traduzionali coinvolte nei meccanismi di cardioprotezione. Proteoma è un termine usato per descrivere l’insieme delle proteine espresse da un genoma. Le metodiche di studio del proteoma si avvalgono principalmente dell’elettroforesi, per la separazione delle proteine da un campione, e della spettrometria di massa per l’identificazione. Un approccio possibile per indagare i cambiamenti nel proteoma mitocondriale è quello di determinarne le variazioni in condizioni di cardioprotezione (utilizzando il fenomeno del precondizionamento), rispetto al proteoma che si riscontra in condizioni fisiologiche ed a quello che si riscontra in condizioni di stress ischemico. Gli eventi cardioprotettivi si associano all’attivazione di chinasi come PKCε, AKT, ERK ed all’inibizione della GSK-3β . Inoltre l’inibizione del poro di transizione di permeabilità mitocondriale (MPTP) è considerato uno dei principali bersagli dei segnali cardioprotettivi

Neuromorphic hardware for somatosensory neuroprostheses

In individuals with sensory-motor impairments, missing limb functions can be restored using neuroprosthetic devices that directly interface with the nervous system. However, restoring the natural tactile experience through electrical neural stimulation requires complex encoding strategies. Indeed, they are presently limited in effectively conveying or restoring tactile sensations by bandwidth constraints. Neuromorphic technology, which mimics the natural behavior of neurons and synapses, holds promise for replicating the encoding of natural touch, potentially informing neurostimulation design. In this perspective, we propose that incorporating neuromorphic technologies into neuroprostheses could be an effective approach for developing more natural human-machine interfaces, potentially leading to advancements in device performance, acceptability, and embeddability. We also highlight ongoing challenges and the required actions to facilitate the future integration of these advanced technologies

NEUROTECH - A European Community of Experts on Neuromorphic Technologies

Neuromorphic Computing Technology (NCT) is becoming a reality in Europe thanks to a coordinated effort to unite the EU researchers and stakeholders interested in neuroscience, artificial intelligence, and nanoscale technologies

Embodied neuromorphic intelligence

The design of robots that interact autonomously with the environment and exhibit complex behaviours is an open challenge that can benefit from understanding what makes living beings fit to act in the world. Neuromorphic engineering studies neural computational principles to develop technologies that can provide a computing substrate for building compact and low-power processing systems. We discuss why endowing robots with neuromorphic technologies – from perception to motor control – represents a promising approach for the creation of robots which can seamlessly integrate in society. We present initial attempts in this direction, highlight open challenges, and propose actions required to overcome current limitations

Feed-forward and recurrent inhibition for compressing and classifying high dynamic range biosignals in spiking neural network architectures

Neuromorphic processors that implement Spiking Neural Networks (SNNs) using mixed-signal analog/digital circuits represent a promising technology for closed-loop real-time processing of biosignals. As in biology, to minimize power consumption, the silicon neurons' circuits are configured to fire with a limited dynamic range and with maximum firing rates restricted to a few tens or hundreds of Herz. However, biosignals can have a very large dynamic range, so encoding them into spikes without saturating the neuron outputs represents an open challenge. In this work, we present a biologically-inspired strategy for compressing this high-dynamic range in SNN architectures, using three adaptation mechanisms ubiquitous in the brain: spike-frequency adaptation at the single neuron level, feed-forward inhibitory connections from neurons belonging to the input layer, and Excitatory-Inhibitory (E-I) balance via recurrent inhibition among neurons in the output layer. We apply this strategy to input biosignals encoded using both an asynchronous delta modulation method and an energy-based pulse-frequency modulation method. We validate this approach in silico, simulating a simple network applied to a gesture classification task from surface EMG recordings.Comment: 5 pages, 7 figures, to be published in IEEE BioCAS 2023 Proceeding

Pronto Soccorso Pediatrico. Osservazione Breve Intensiva: un modello assistenziale. L'esperienza grossetana.

LO studio raccoglie la casistica di 12 anni (1998-2011) sull'utilizzo dello strumento osservazione breve intensiva per la gestione nel Pronto Soccorso Pediatrico di Grosseto. Vengono riportati gli accessi annuali, le OBI, divise per periodo dell'anno, patologia con i relativi outcome (dimissioni, rivoveri, follow-up). Lo studio è stata anche lìoccasione di rivedere e revisionare i protocolli e lineeguida delle più comuni patologie osservate in PSP e gestite in OBI

Computational Investigation of the Molecular Mechanisms Regulating Nucleic Acid Processing Metalloenzymes

Polymerases and nucleases are enzymes processing DNA and RNA. They are involved in crucial processes for cell life by performing the extension and the cleavage of nucleic acid chains during genome replication and maintenance. Additionally, both enzymes are often associated to several diseases, including cancer. In order to catalyze the reaction, most of them operate via the two-metal-ion mechanism. For this, despite showing relevant differences in structure, function and catalytic properties, they share common catalytic elements, which comprise the two catalytic ions and their first-shell acidic residues. Notably, recent studies of different metalloenzymes revealed the recurrent presence of additional elements surrounding the active site, thus suggesting an extended two-metal-ion-centered architecture. However, whether these elements have a catalytic function and what is their role is still unclear. In this work, using state-of-the-art computational techniques, second- and third-shell elements are showed to act in metallonucleases favoring the substrate positioning and leaving group release. In particular, in hExo1 a transient third metal ion is recruited and positioned near the two-metal-ion site by a structurally conserved acidic residue to assist the leaving group departure. Similarly, in hFEN1 second- and third-shell Arg/Lys residues operate the phosphate steering mechanism through (i) substrate recruitment, (ii) precise cleavage localization, and (iii) leaving group release. Importantly, structural comparisons of hExo1, hFEN1 and other metallonucleases suggest that similar catalytic mechanisms may be shared by other enzymes. Overall, the results obtained provide an extended vision on parallel strategies adopted by metalloenzymes, which employ divalent metal ion or positively charged residues to ensure efficient and specific catalysis. Furthermore, these outcomes may have implications for de novo enzyme engineering and/or drug design to modulate nucleic acid processing

Computational investigations of polymerase enzymes: Structure, function, inhibition, and biotechnology

AbstractDNA and RNA polymerases (Pols) are central to life, health, and biotechnology because they allow the flow of genetic information in biological systems. Importantly, Pol function and (de)regulation are linked to human diseases, notably cancer (DNA Pols) and viral infections (RNA Pols) such as COVID‐19. In addition, Pols are used in various applications such as synthesis of artificial genetic polymers and DNA amplification in molecular biology, medicine, and forensic analysis. Because of all of this, the field of Pols is an intense research area, in which computational studies contribute to elucidating experimentally inaccessible atomistic details of Pol function. In detail, Pols catalyze the replication, transcription, and repair of nucleic acids through the addition, via a nucleotidyl transfer reaction, of a nucleotide to the 3′‐end of the growing nucleic acid strand. Here, we analyze how computational methods, including force‐field‐based molecular dynamics, quantum mechanics/molecular mechanics, and free energy simulations, have advanced our understanding of Pols. We examine the complex interaction of chemical and physical events during Pol catalysis, like metal‐aided enzymatic reactions for nucleotide addition and large conformational rearrangements for substrate selection and binding. We also discuss the role of computational approaches in understanding the origin of Pol fidelity—the ability of Pols to incorporate the correct nucleotide that forms a Watson–Crick base pair with the base of the template nucleic acid strand. Finally, we explore how computations can accelerate the discovery of Pol‐targeting drugs and engineering of artificial Pols for synthetic and biotechnological applications.This article is categorized under: Structure and Mechanism > Reaction Mechanisms and Catalysis Structure and Mechanism > Computational Biochemistry and Biophysics Software > Molecular Modelin