The recent biotechnological progress has allowed life scientists and physicians to access an unprecedented, massive amount of data at all levels (molecular, supramolecular, cellular and so on) of biological complexity. So far, mostly classical computational efforts have been dedicated to the simulation, prediction or de novo design of biomolecules, in order to improve the understanding of their function or to develop novel therapeutics. At a higher level of complexity, the progress of omics disciplines (genomics, transcriptomics, proteomics and metabolomics) has prompted researchers to develop informatics means to describe and annotate new biomolecules identified with a resolution down to the single cell, but also with a high-throughput speed. Machine learning approaches have been implemented to both the modelling studies and the handling of biomedical data. Quantum computing (QC) approaches hold the promise to resolve, speed up or refine the analysis of a wide range of these computational problems. Here, we review and comment on recently developed QC algorithms for biocomputing, with a particular focus on multi-scale modelling and genomic analyses. Indeed, differently from other computational approaches such as protein structure prediction, these problems have been shown to be adequately mapped onto quantum architectures, the main limit for their immediate use being the number of qubits and decoherence effects in the available quantum machines. Possible advantages over the classical counterparts are highlighted, along with a description of some hybrid classical/quantum approaches, which could be the closest to be realistically applied in biocomputation.

Significance: Neurotrophins (NTs) are homodimeric growth factors displaying fundamental roles in the nervous system. Their activity stems from binding and activation of 3 different receptor types in nervous cell membranes. The p75 NT receptor (p75 ^NTR ) was the first to be discovered in 1986; nevertheless, for the numerous structural and functional facets so far reported, its activation mechanisms have remained elusive. Here, we demonstrate that its pleiotropic functions are regulated by different redistributions of the receptors, which crucially depend on the available NT and on the involved subcellular compartment but are unrelated to its oligomerization state. Single-particle studies proved receptors to be monomers with a fast-diffusive behavior in the membrane with, at most, transient self-interactions on the millisecond time scale.

The close contact between dogs and humans creates the best bridge for interspecies transmission of antimicrobial-resistant bacteria. The surveillance of its resistance including the detection of extended-spectrum beta-lactamases (ESBLs) in Escherichia coli as indicator bacteria is an important tool to control the use of antimicrobials. The aim of this research was to evaluate the E. coli resistance in strains by phenotypic methods, isolated from pet and stray dogs of La Plata city, Argentina. Faecal samples were collected using rectal swabs from 50 dogs with owners (home dogs=HD) and 50 homeless dogs (stray dogs=SD). They were cultured in 3 MacConkey agar plates, with and without antibiotics (ciprofloxacin and cefotaxime). 197 strains were isolated, of which only 95 strains were biochemically identified as E. coli, 46 strains were from HD, and 49 were from SD. Antimicrobial susceptibility was evaluated by the KirbyBauer disk diffusion method. The most prevalent resistance was for tetracycline, streptomycin, and ampicillin. In both groups, the level of resistance to 3rd generation cephalosporins was high, and there were multiresistant strains. There was a higher level of antimicrobial resistance in strains from SD compared to HD. There were 8 of strains suspected of being ESBLs among samples of HD and 36 of SD. One (2) of the strains isolated from HD and 11 (22) from SD were phenotypically confirmed as ESBL. Pets and stray dogs are a potential source of E. coli antibiotic resistance in Argentina; therefore, its surveillance must be guaranteed.

Mechanical force is crucial in guiding axon outgrowth before and after synapse formation. This process is referred to as "stretch growth." However, how neurons transduce mechanical input into signaling pathways remains poorly understood. Another open question is how stretch growth is coupled in time with the intercalated addition of new mass along the entire axon. Here, we demonstrate that active mechanical force generated by magnetic nano-pulling induces remodeling of the axonal cytoskeleton. Specifically, the increase in the axonal density of microtubules induced by nano-pulling leads to an accumulation of organelles and signaling vesicles, which, in turn, promotes local translation by increasing the probability of assembly of the "translation factories." Modulation of axonal transport and local translation sustains enhanced axon outgrowth and synapse maturation.

Emerging nanotechnologies offer numerous opportunities in the field of regenerative medicine and have been widely explored to design novel scaffolds for the regeneration and stimulation of nerve tissue. In this review, we focus on peripheral nerve regeneration. First, we introduce the biomedical problem and the present status of nerve conduits that can be used to guide, fasten and enhance regeneration. Then, we thoroughly discuss graphene as an emerging candidate in nerve tissue engineering, in light of its chemical, tribological and electrical properties. We introduce the graphene forms commonly used as neural interfaces, briefly review their applications, and discuss their potential toxicity. We then focus on the adoption of graphene in peripheral nervous system applications, a research field that has gained in the last years ever-increasing attention. We discuss the potential integration of graphene in guidance conduits, and critically review graphene interaction not only with peripheral neurons, but also with non-neural cells involved in nerve regeneration; indeed, the latter have recently emerged as central players in modulating the immune and inflammatory response and accelerating the growth of new tissue.

Neuroactive steroids are potent modulators of microglial functions and are capable of counteracting their excessive reactivity. This action has mainly been ascribed to neuroactive steroids released from other sources, as microglia have been defined unable to produce neurosteroids de novo. Unexpectedly, immortalized murine microglia recently exhibited this de novo biosynthesis; herein, de novo neurosteroidogenesis was characterized in immortalized human microglia. The results demonstrated that C20 and HMC3 microglial cells constitutively express members of the neurosteroidogenesis multiprotein machinery—in particular, the transduceosome members StAR and TSPO, and the enzyme CYP11A1. Moreover, both cell lines produce pregnenolone and transcriptionally express the enzymes involved in neurosteroidogenesis. The high TSPO expression levels observed in microglia prompted us to assess its role in de novo neurosteroidogenesis. TSPO siRNA and TSPO synthetic ligand treatments were used to reduce and prompt TSPO function, respectively. The TSPO expression downregulation compromised the de novo neurosteroidogenesis and led to an increase in StAR expression, probably as a compensatory mechanism. The pharmacological TSPO stimulation the de novo neurosteroidogenesis improved in turn the neurosteroid-mediated release of Brain-Derived Neurotrophic Factor. In conclusion, these results demonstrated that de novo neurosteroidogenesis occurs in human microglia, unravelling a new mechanism potentially useful for future therapeutic purposes.