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Electroactive smart materials play an important role for tissue regenerative applications. Poly(vinylidene fluoride) (PVDF) is a specific subtype of piezoelectric electroactive material that generates electrical potential upon mechanical stimulation. This work focuses on the application of piezoelectric PVDF films for neural differentiation. Human neural precursor cells (hNPCs) are cultured on piezoelectric poled and non‐poled β‐PVDF films with or without a pre‐coating step of poly‐d‐lysine and laminin (PDL/L). Subsequently, hNPCs differentiation into the neuronal lineage is assessed (MAP2+ and DCX+) under static or dynamic (piezoelectric stimulation) culture conditions. The results demonstrate that poled and coated β‐PVDF films induce neuronal differentiation under static culture conditions which is further enhanced with mechanical stimulation. In silico calculations of the electrostatic potential of different domains of laminin, highlight the high polarity of those domains, which shows a clear preference to interact with the varying surface electric field of the piezoelectric material under mechanical stimulation. These interactions might explain the higher neuronal differentiation induced by poled β‐PVDF films pre‐coated with PDL/L under dynamic conditions. Our results suggest that electromechanical stimuli, such as the ones induced by piezoelectric β‐PVDF films, are suitable to promote neuronal differentiation and hold great promise for the development of neuroregenerative therapies. [ABSTRACT FROM AUTHOR]

Diclofenac is a worldwide consumed drug included in the watch list of substances to be monitored according to the European Union Water Framework Directive (Directive 2013/39/EU). Aerobic granular sludge sequencing batch reactors (AGS-SBR) are increasingly used for wastewater treatment but there is scant information on the fate and effect of micropollutants to nutrient removal processes. An AGS-SBR fed with synthetic wastewater containing diclofenac was bioaugmented with a diclofenac degrading bacterial strain and performance and microbial community dynamics was analysed. Chemical oxygen demand, phosphate and ammonia removal were not affected by the micropollutant at 0.03 mM (9.54 mg L–1). The AGS was able to retain the degrading strain, which was detected in the sludge throughout after augmentation. Nevertheless, besides some adsorption to the biomass, diclofenac was not degraded by the augmented sludge given the short operating cycles and even if batch degradation assays confirmed that the bioaugmented AGS was able to biodegrade the compound. The exposure to the pharmaceutical affected the microbial community of the sludge, separating the two first phases of reactor operation (acclimatization and granulation) from subsequent phases. The AGS was able to keep the bioaugmented strain and to maintain the main functions of nutrient removal even through the long exposure to the pharmaceutical, but combined strategies are needed to reduce the spread of micropollutants in the environment. [ABSTRACT FROM AUTHOR]

BBB dysfunction during aging is characterized by an increase in its permeability and phenotypic alterations of brain endothelial cells (BECs) including dysregulation of tight junction's expression. Here we have investigated the role of BEC senescence in the dysfunction of the BBB. Our results suggest that the transition from young to aged BBB is mediated, at least in part by BEC senescence. [ABSTRACT FROM AUTHOR]

The increase in the available G protein-coupled receptor (GPCR) structures has been pivotal in helping to understand their activation process. However, the role of protonation-conformation coupling in GPCR activation still needs to be clarified. We studied the protonation behavior of the highly conserved Asp 2.50 residue in five different class A GPCRs (active and inactive conformations) using a linear response approximation (LRA) p K a calculation protocol. We observed consistent differences (1.3 p K units) for the macroscopic p K a values between the inactive and active states of the A2AR and B2AR receptors, indicating the protonation of Asp 2.50 during GPCR activation. This process seems to be specific and not conserved, as no differences were observed in the p K a values of the remaining receptors (CB1R, NT1R, and GHSR).

G protein-coupled receptors (GPCRs) mediate several signaling pathways through a general mechanism that involves their activation, upholding a chain of events that lead to the release of molecules responsible for cytoplasmic action and further regulation. These physiological functions can be severely altered by mutations in GPCR genes. GPCRs subfamily A17 (dopamine, serotonin, adrenergic and trace amine receptors) are directly related with neurodegenerative diseases, and as such it is crucial to explore known mutations on these systems and their impact in structure and function. A comprehensive and detailed computational framework - MUG (Mutations Understanding GPCRs) - was constructed, illustrating key reported mutations and their effect on receptors of the subfamily A17 of GPCRs. We explored the type of mutations occurring overall and in the different families of subfamily A17, as well their localization within the receptor and potential effects on receptor functionality. The mutated residues were further analyzed considering their pathogenicity. The results reveal a high diversity of mutations in the GPCR subfamily A17 structures, drawing attention to the considerable number of mutations in conserved residues and domains. Mutated residues were typically hydrophobic residues enriched at the ligand binding pocket and known activating microdomains, which may lead to disruption of receptor function. MUG as an interactive web application is available for the management and visualization of this dataset. We expect that this interactive database helps the exploration of GPCR mutations, their influence, and their familywise and receptor-specific effects, constituting the first step in elucidating their structures and molecules at the atomic level., Competing Interests: The authors have no conflicts of interest to declare., (© 2022 The Author(s).)

Neurodegenerative diseases affect over 30 million people worldwide with an ascending trend. Most individuals suffering from these irreversible brain damages belong to the elderly population, with onset between 50 and 60 years. Although the pathophysiology of such diseases is partially known, it remains unclear upon which point a disease turns degenerative. Moreover, current therapeutics can treat some of the symptoms but often have severe side effects and become less effective in long-term treatment. For many neurodegenerative diseases, the involvement of G proteincoupled receptors (GPCRs), which are key players of neuronal transmission and plasticity, has become clearer and holds great promise in elucidating their biological mechanism. With this review, we introduce and summarize class A and class C GPCRs, known to form heterodimers or oligomers to increase their signalling repertoire. Additionally, the examples discussed here were shown to display relevant alterations in brain signalling and had already been associated with the pathophysiology of certain neurodegenerative diseases. Lastly, we classified the heterodimers into two categories of crosstalk, positive or negative, for which there is known evidence., (Copyright© Bentham Science Publishers; For any queries, please email at epub@benthamscience.net.)

Viruses are a diverse biological group capable of infecting several hosts such as bacteria, plants, and animals, including humans. Viral infections constitute a threat to the human population as they may cause high mortality rates, decrease food production, and generate large economical losses. Viruses co-evolve with their hosts and this constant evolution must be clarified to better predict possible viral outbreaks, and to develop improved diagnostic methods and therapeutical approaches. In this review, we summarize several viral databases that store key information retrieved from a variety of omics approaches. Furthermore, we explore the use of such databases to predict Virus-Host interactions through artificial intelligence algorithms, focusing on the latest methodologies to characterize biological networks., (Copyright © 2022 Elsevier Inc. All rights reserved.)