Cell bystander effect induced by radiofrequency electromagnetic fields and magnetic nanoparticles

Induced effects by direct exposure to ionizing radiation (IR) are a central issue in many fields like radiation protection, clinic diagnosis and oncological therapies. Direct irradiation at certain doses induce cell death, but similar effects can also occur in cells no directly exposed to IR, a mechanism known as bystander effect. Non-IR (radiofrequency waves) can induce the death of cells loaded with MNPs in a focused oncological therapy known as magnetic hyperthermia. Indirect mechanisms are also able to induce the death of unloaded MNPs cells. Using in vitro cell models, we found that colocalization of the MNPs at the lysosomes and the non-increase of the temperature induces bystander effect under non-IR. Our results provide a landscape in which bystander effects are a more general mechanism, up to now only observed and clinically used in the field of radiotherapy.Comment: 16 pages, 4 figures, submitted to International Journal of Radiation Biolog

Directed Molecular Stacking for Engineered Fluorescent Three-Dimensional Reduced Graphene Oxide and Coronene Frameworks

[EN] Three‐dimensional fluorescent graphene frameworks with controlled porous morphologies are of significant importance for practical applications reliant on controlled structural and electronic properties, such as organic electronics and photochemistry. Here we report a synthetically accessible approach concerning directed aromatic stacking interactions to give rise to new fluorogenic 3D frameworks with tuneable porosities achieved through molecular variations. The binding interactions between the graphene‐like domains present in the in situ‐formed reduced graphene oxide (rGO) with functional porphyrin molecules lead to new hybrids via an unprecedented solvothermal reaction. Functional free‐base porphyrins featuring perfluorinated aryl groups or hexyl chains at their meso‐ and β‐positions were employed in turn to act as directing entities for the assembly of new graphene‐based and foam‐like frameworks and of their corresponding coronene‐based hybrids. Investigations in the dispersed phase and in thin‐film by XPS, SEM and FLIM shed light onto the nature of the aromatic stacking within functional rGO frameworks (denoted rGOFs) which was then modelled semi‐empirically and by DFT calculations. The pore sizes of the new emerging reduced graphene oxide hybrids are tuneable at the molecular level and mediated by the bonding forces with the functional porphyrins acting as the “molecular glue”. Single crystal X‐ray crystallography described the stacking of a perfluorinated porphyrin with coronene, which can be employed as a molecular model for understanding the local aromatic stacking order and charge transfer interactions within these rGOFs for the first time. This opens up a new route to controllable 3D framework morphologies and pore size from the Ångstrom to the micrometre scale. Theoretical modelling showed that the porosity of these materials is mainly due to the controlled inter‐planar distance between the rGO, coronene or graphene sheets. The host‐guest chemistry involves the porphyrins acting as guests held through π‐π stacking, as demonstrated by XPS. The objective of this study is also to shed light into the fundamental localised electronic and energy transfer properties in these new molecularly engineered porous and fluorogenic architectures, aiming in turn to understand how functional porphyrins may exert stacking control over the notoriously disordered local structure present in porous reduced graphene oxide fragments. By tuning the porosity and the distance between the graphene sheets using aromatic stacking with porphyrins, it is also possible to tune the electronic structure of the final nanohybrid material, as indicated by FLIM experiments on thin films. Such nanohybrids with highly controlled pores dimensions and morphologies open the way to new design and assembly of storage devices and applications incorporating π‐conjugated molecules and materials and their π‐stacks may be relevant towards selective separation membranes, water purification and biosensing applications.S.I.P. and S.W.B. thank The Royal Society and STFC for funding. B.Y.M. thanks the University of Bath for a studentship (ORS). D.G.C. thanks the Fundación General CSIC for funding (ComFuturo Program). Dr. Jose A. Ribeiro Martins, Professors Jeremy K. M. Sanders and Paul Raithby are acknowledged for training, helpful discussions and porphyrin supramolecular chemistry. The S.I.P. group thanks the EPSRC for funding to the Centre of Graphene Science (EP/K017160/1) and to the Centre for Doctoral Training in Sustainable Chemical Technologies (EP/L016354/1). The authors thank EPSRC National Service for Mass Spectrometry at Swansea and EPSRC National Service for Crystallography at Southampton for data collection. The authors also acknowledge the ERC for the Consolidator Grant O2SENSE (617107, 2014–2019)

Growth factor choice is critical for successful functionalization of nanoparticles

Nanoparticles (NPs) show new characteristics compared to the corresponding bulk material. These nanoscale properties make them interesting for various applications in biomedicine and life sciences. One field of application is the use of magnetic NPs to support regeneration in the nervous system. Drug delivery requires a functionalization of NPs with bio-functional molecules. In our study, we functionalized self-made PEI-coated iron oxide NPs with nerve growth factor (NGF) and glial cell-line derived neurotrophic factor (GDNF). Next, we tested the bio-functionality of NGF in a rat pheochromocytoma cell line (PC12) and the bio-functionality of GDNF in an organotypic spinal cord culture. Covalent binding of NGF to PEI-NPs impaired bio-functionality of NGF, but non-covalent approach differentiated PC12 cells reliably. Non-covalent binding of GDNF showed a satisfying bio-functionality of GDNF:PEI-NPs, but turned out to be unstable in conjugation to the PEI-NPs. Taken together, our study showed the importance of assessing bio-functionality and binding stability of functionalized growth factors using proper biological models. It also shows that successful functionalization of magnetic NPs with growth factors is dependent on the used binding chemistry and that it is hardly predictable. For use as therapeutics, functionalization strategies have to be reproducible and future studies are needed

Multi-Scale Modelling of Aggregation of TiO2 Nanoparticle Suspensions in Water

Titanium dioxide nanoparticles have risen concerns about their possible toxicity and the European Food Safety Authority recently banned the use of TiO2 nano-additive in food products. Following the intent of relating nanomaterials atomic structure with their toxicity without having to conduct large-scale experiments on living organisms, we investigate the aggregation of titanium dioxide nanoparticles using a multi-scale technique: starting from ab initio Density Functional Theory to get an accurate determination of the energetics and electronic structure, we switch to classical Molecular Dynamics simulations to calculate the Potential of Mean Force for the connection of two identical nanoparticles in water; the fitting of the latter by a set of mathematical equations is the key for the upscale. Lastly, we perform Brownian Dynamics simulations where each nanoparticle is a spherical bead. This coarsening strategy allows studying the aggregation of a few thousand nanoparticles. Applying this novel procedure, we find three new molecular descriptors, namely, the aggregation free energy and two numerical parameters used to correct the observed deviation from the aggregation kinetics described by the Smoluchowski theory. Ultimately, molecular descriptors can be fed into QSAR models to predict the toxicity of a material knowing its physicochemical properties, enabling safe design strategies

Soft solution fluorine-free synthesis of anatase nanoparticles with tailored morphology

TiO2 nanoparticles with tailored morphology have been synthesized under exceptionally soft conditions. The strategy is based on the use of a non-aqueous alcoholic reaction medium in which water traces, coming either from the air (atmospheric water) or from an ethanol–water azeotropic mixture (ethanol 96%), are incorporated in order to accelerate hydrolysis of the Ti–precursor. Moreover, organic surfactants have been used as capping agents so as to tailor crystal growth in certain preferential directions. Combinations of oleic acid and oleylamine, which lead to the formation of another surfactant, dioleamide, are employed instead of fluorine-based compounds, thus increasing the sustainability of the process. As a result, TiO2 nanostructured hierarchical microspheres and individual nanoparticles with exposed high-energy facets can be obtained at atmospheric pressure and temperatures as low as 78 °C

Artificial Intelligence in Orthodontics: Where Are We Now? A Scoping Review

Objective: This scoping review aims to determine the applications of Artificial Intelligence (AI) that are extensively employed in the field of Orthodontics, to evaluate its benefits, and to discuss its potential implications in this speciality. Recent decades have witnessed enormous changes in our profession. The arrival of new and more aesthetic options in orthodontic treatment, the transition to a fully digital workflow, the emergence of temporary anchorage devices and new imaging methods all provide both patients and professionals with a new focus in orthodontic care. Materials and methods: This review was performed following the Preferred Reporting Items for Systematic reviews and Meta-Analyses extension for Scoping Reviews (PRISMA-ScR) guidelines. The electronic literature search was performed through MEDLINE/PubMed, Scopus, Web of Science, Cochrane and IEEE Xplore databases with a 11-year time restriction: January 2010 till March 2021. No additional manual searches were performed. Results: The electronic literature search initially returned 311 records, and 115 after removing duplicate references. Finally, the application of the inclusion criteria resulted in 17 eligible publications in the qualitative synthesis review. Conclusion: The analysed studies demonstrated that Convolution Neural Networks can be used for the automatic detection of anatomical reference points on radiological images. In the growth and development research area, the Cervical Vertebral Maturation stage can be determined using an Artificial Neural Network model and obtain the same results as expert human observers. AI technology can also improve the diagnostic accuracy for orthodontic treatments, thereby helping the orthodontist work more accurately and efficiently