Upconverting nanorockers for intracellular viscosity measurements during chemotherapy

Funding: Ministerio de Economía y Competitividad de España (MAT2016-75362-C3-1-R and MAT2017-83111R); Instituto de Salud Carlos III (PI16/ 00812); Comunidad Autónoma de Madrid (B2017/BMD-3867RENIMCM), and co-financed by the European Structural funds and also by COST action CM1403; Comunidad de Madrid predoctorate contracts and from the Spanish national project FIS2017-86007-C3-1-P (R.D-B and R.P.P).Chemicals capable of producing structural and chemical changes on cells are used to treat diseases (e.g., cancer). Further development and optimization of chemotherapies require thorough knowledge of the effect of the chemical on the cellular structure and dynamics. This involves studying, in a noninvasive way, the properties of individual cells after drug administration. Intracellular viscosity is affected by chemical treatments and it can be reliably used to monitor chemotherapies at the cellular level. Here, cancer cell monitoring during chemotherapeutic treatments is demonstrated using intracellular allocated upconverting nanorockers. A simple analysis of the polarized visible emission of a single particle provides a real-time readout of its rocking dynamics that are directly correlated to the cytoplasmic viscosity. Numerical simulations and immunodetection are used to correlate the measured intracellular viscosity alterations to the changes produced in the cytoskeleton of cancer cells by anticancer drugs (colchicine and Taxol). This study evidences the possibility of monitoring cellular properties under an external chemical stimulus for the study and development of new treatments. Moreover, it provides the biomedical community with new tools to study intracellular dynamics and cell functioning.PostprintPeer reviewe

Predicting the size and morphology of nanoparticle clusters driven by biomolecular recognition

Nanoparticle aggregation is a driving principle of innovative materials and biosensing methodologies, improving transduction capabilities displayed by optical, electrical or magnetic measurements. This aggregation can be driven by the biomolecular recognition between target biomolecules (analytes) and receptors bound onto nanoparticle surface. Despite theoretical advances on modelling the entropic interaction in similar systems, predictions of the fractal morphologies of the nanoclusters of bioconjugated nanoparticles are lacking. The morphology of resulting nanoclusters is sensitive to the location, size, flexibility, average number of receptors per particle f̄, and the analyte-particle concentration ratio. Here we considered bioconjugated iron oxide nanoparticles (IONPs) where bonds are mediated by a divalent protein that binds two receptors attached onto different IONPs. We developed a protocol combining analytical expressions for receptors and linker distributions, and Brownian dynamics simulations for bond formation, and validated it against experiments. As more bonds become available (e.g., by adding analytes), the aggregation deviates from the ideal Bethe's lattice scenario due to multivalence, loop formation, and steric hindrance. Generalizing Bethe's lattice theory with a (not-integer) effective functionality feff leads to analytical expressions for the cluster size distributions in excellent agreement with simulations. At high analyte concentration steric impediment imposes an accessible limit value facc to feff, which is bounded by facc < feff < f̄. A transition to gel phase, is correctly captured by the derived theory. Our findings offer new insights into quantifying analyte amounts by assessing nanocluster size, and predicting nanoassembly morphologies accurately is a first step towards understanding variations of physical properties in clusters formed after biomolecular recognitionThis work has been partially funded by the Spanish Research Agencies (PID2020-117080RB-C51, PDC2021-121441-C21, PCI2019- 103600,CEX2020-001039-S, PID2019-111649RB-I00 PID2020- 117080RB-C53, MDM-2017-0720, RED2018-102626-T) and Comunidad de Madrid (NANOMAGCOST, S2018/NMT-4321). European COST Actions CA17115 (MyWave), and CA17140 (Nano2Clinic) are also acknowledged. ESD thanks Comunidad de Madrid for financial support (PEJ-2017-AI/BMD-7517). Authors thank Dr Patricia Pedraz for carefull acquisition of AFM image

Controlled assembly and reduction of graphene oxide networks for conductive composites

Work presented at the 2019 ACS Spring National Meeting, March 28-April 4, 2019 · Orlando, FL.Graphene has attracted enormous interest in the scientific community as the first 2D material with exceptional mechanical, electronic and thermal properties. Pristine Graphene is notoriously difficult to process for macroscale applications, to overcome this many people use graphene oxide (GO) instead. GO is water soluble and easily functionalised and so can be simply processed into various systems. GO lacks the exceptional electronic properties of graphene due to structural disorder, therefore an important area of research is on the reduction of GO, which partly restores the structure and properties of graphene. Various techniques have been developed to perform the reduction step. We report a simple approach for preparing conductive Polymer Latex-rGO composites by using a latex-assembly method. After a treatment in the oven at low T, we can reduce the GO in situ. We make use of the inherent GO properties to optimise the aqueous composite fabrication, which is scalable and adaptable, and then restore conductivity with a simple, low temperature, heating step; opening up pathways to tunable electronic composite materials on a large scale.Peer reviewe

OpenMM 8: Molecular Dynamics Simulation with Machine Learning Potentials

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUDA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features on simulations of cyclin-dependent kinase 8 (CDK8) and the green fluorescent protein (GFP) chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations at only a modest increase in cost.Comment: 16 pages, 5 figure

OpenMM 8:Molecular Dynamics Simulation with Machine Learning Potentials

Machine learning plays an important and growing role in molecular simulation. The newest version of the OpenMM molecular dynamics toolkit introduces new features to support the use of machine learning potentials. Arbitrary PyTorch models can be added to a simulation and used to compute forces and energy. A higher-level interface allows users to easily model their molecules of interest with general purpose, pretrained potential functions. A collection of optimized CUDA kernels and custom PyTorch operations greatly improves the speed of simulations. We demonstrate these features in simulations of cyclin-dependent kinase 8 (CDK8) and the green fluorescent protein chromophore in water. Taken together, these features make it practical to use machine learning to improve the accuracy of simulations with only a modest increase in cost.</p

Hermenéutica, estética y (bio) política: reflexiones de problemáticas actuales

Artículos que abordan temas diversos como la necesidad de humanidad en la familia en tiempos de ciencia y tecnología; el trabajo digno; el ciclo menstrual femenino en relación con los derechos laborales; el problema de la identidad contemporánea o el enfoque de la responsabilidad social empresarial y su incidencia en la sociedad actual; son parte de esta compilación. A estos se añaden otros temas: un acercamiento al arte colombiano o la propuesta educativa de educar para la disponibilidad así como el compromiso del sujeto en la propuesta del cuidado. La sociedad actual necesita construir paradigmas desde el servicio y desde la responsabilidad. Ese, el hilo conductor de estos artículos

Handbook of Active Ageing and Quality of Life: From Concepts to Applications

La edición de este libro estuvo a cargo de Fermina Rojo-Pérez y Gloria Fernández-Mayoralas.El documento adjunto contiene la cubierta, portada e índice del libro.This handbook presents an overview of studies on the relationship of active ageing and quality of life. It addresses the new challenges of ageing from the paradigm of positive ageing (active, healthy and successful) for a better quality of life. It provides theoretical perspectives and empirical studies, including scientific knowledge as well as practical experiences about the good ageing and the quality of later life around the world, in order to respond to the challenges of an aged population. The handbook is structured in 4 sections covering theoretical and conceptual perspectives, social policy issues and research agenda, methods, measurement instrument-scales and evaluations, and lastly application studies including domains and geographical contexts.Peer reviewe

Laser fabrication of porous silicon-based platforms for cell culturing

In this study, we explore the selective culturing of human mesenchymal stem cells (hMSCs) on Si-based diffractive platforms. We demonstrate a single-step and flexible method for producing platforms on nanostructured porous silicon (nanoPS) based on the use of single pulses of an excimer laser to expose phase masks. The resulting patterns are typically 1D patterns formed by fringes or 2D patterns formed by circles. They are formed by alternate regions of almost unmodified nanoPS and regions where the nanoPS surface has melted and transformed into Si nanoparticles. The patterns are produced in relatively large areas (a few square millimeters) and can have a wide range of periodicities and aspect ratios. Direct binding, that is, with no previous functionalization of the pattern, alignment, and active polarization of hMSCs are explored. The results show the preferential direct binding of the hMSCs along the transformed regions whenever their width compares with the dimensions of the cells and they escape from patterns for smaller widths suggesting that the selectivity can be tailored through the pattern period