A minimal model for spontaneous cell polarization and edge activity in oscillating, rotating and migrating cells

How the cells break symmetry and organize their edge activity to move directionally is a fun- damental question in cell biology. Physical models of cell motility commonly rely on gradients of regulatory factors and/or feedback from the motion itself to describe polarization of edge activity. Theses approaches, however, fail to explain cell behavior prior to the onset of polarization. Our analysis using the model system of polarizing and moving fish epidermal keratocytes suggests a novel and simple principle of self-organization of cell activity in which local cell-edge dynamics depends on the distance from the cell center, but not on the orientation with respect to the front-back axis. We validate this principle with a stochastic model that faithfully reproduces a range of cell-migration behaviors. Our findings indicate that spontaneous polarization, persistent motion, and cell shape are emergent properties of the local cell-edge dynamics controlled by the distance from the cell center.Comment: 8 pages, 5 figure

Dynamic measurement of the height and volume of migrating cells by a novel fluorescence microscopy technique

We propose a new technique to measure the volume of adherent migrating cells. The method is based on a negative staining where a fluorescent, non cell-permeant dye is added to the extracellular medium. The specimen is observed with a conventional fluorescence microscope in a chamber of uniform height. Given that the fluorescence signal depends on the thickness of the emitting layer, the objects excluding the fluorescent dye (i.e., cells) appear dark, and the decrease of the fluorescent signal with respect to the background is expected to give information about the height and the volume of the object. Using a glass microfabricated pattern with steps of defined heights, we show that the drop in fluorescence intensity is indeed proportional to the height of the step and obtain calibration curves relating fluorescence intensity to height. The technique, termed fluorescence displacement method, is further validated by comparing our measurements with the ones obtained by atomic force microscopy (AFM). We apply our method to measure the real-time volume dynamics of migrating fish epidermal keratocytes subjected to osmotic stress. The fluorescence displacement technique allows fast and precise monitoring of cell height and volume, thus providing a valuable tool for characterizing the three-dimensional behaviour of migrating cells

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino de tector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower-or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Event reconstruction for KM3NeT/ORCA using convolutional neural networks

The KM3NeT research infrastructure is currently under construction at two locations in the Mediterranean Sea. The KM3NeT/ORCA water-Cherenkov neutrino detector off the French coast will instrument several megatons of seawater with photosensors. Its main objective is the determination of the neutrino mass ordering. This work aims at demonstrating the general applicability of deep convolutional neural networks to neutrino telescopes, using simulated datasets for the KM3NeT/ORCA detector as an example. To this end, the networks are employed to achieve reconstruction and classification tasks that constitute an alternative to the analysis pipeline presented for KM3NeT/ORCA in the KM3NeT Letter of Intent. They are used to infer event reconstruction estimates for the energy, the direction, and the interaction point of incident neutrinos. The spatial distribution of Cherenkov light generated by charged particles induced in neutrino interactions is classified as shower- or track-like, and the main background processes associated with the detection of atmospheric neutrinos are recognized. Performance comparisons to machine-learning classification and maximum-likelihood reconstruction algorithms previously developed for KM3NeT/ORCA are provided. It is shown that this application of deep convolutional neural networks to simulated datasets for a large-volume neutrino telescope yields competitive reconstruction results and performance improvements with respect to classical approaches

Discutindo a educação ambiental no cotidiano escolar: desenvolvimento de projetos na escola formação inicial e continuada de professores

A presente pesquisa buscou discutir como a Educação Ambiental (EA) vem sendo trabalhada, no Ensino Fundamental e como os docentes desta escola compreendem e vem inserindo a EA no cotidiano escolar., em uma escola estadual do município de Tangará da Serra/MT, Brasil. Para tanto, realizou-se entrevistas com os professores que fazem parte de um projeto interdisciplinar de EA na escola pesquisada. Verificou-se que o projeto da escola não vem conseguindo alcançar os objetivos propostos por: desconhecimento do mesmo, pelos professores; formação deficiente dos professores, não entendimento da EA como processo de ensino-aprendizagem, falta de recursos didáticos, planejamento inadequado das atividades. A partir dessa constatação, procurou-se debater a impossibilidade de tratar do tema fora do trabalho interdisciplinar, bem como, e principalmente, a importância de um estudo mais aprofundado de EA, vinculando teoria e prática, tanto na formação docente, como em projetos escolares, a fim de fugir do tradicional vínculo “EA e ecologia, lixo e horta”.Facultad de Humanidades y Ciencias de la Educació

Interplay between cytoskeletal forces, membrane tension and shape in rapidly migrating cells

Cell migration is a fundamental process in all animal cells. The ability of cell to migrate is crucial for many pathological and physiological conditions such as morphogenesis, the immune response to inflammatory or vascular diseases and cancer metastasis. Actin polymerization pressure and membrane tension are two major forces defining the dynamics of cell leading edge during migration: actin polymerization pushes the membrane forward to drive the motion, while membrane tension is believed to counteract and control protrusion. Recent studies implicated membrane tension in control of cell spreading, limiting lateral extension of the cell, confining protrusion to a single leading edge, and crushing actin network during retraction at the cell rear; however, direct experimental evidence is conflicting. Moreover, actin polymerization and membrane tension are not directly opposing each other, since membrane tension is oriented along the membrane surface, while actin polymerization is directed generally parallel to the substrate. Thus the shape of the leading edge may have important, albeit as yet unknown effect on the force balance. To understand how these forces are orchestrated at the cell’s leading edge, we employed the model system of fish epithelial keratocytes which are spontaneously highly motile and are characterized by a remarkably stable shape and constant protrusion rate, making any changes due to experimental treatments traceable and accessible for quantitative analysis. We set out to measure actin protrusion rate, membrane tension, and three dimensional shape of these cells subjected to manipulation of osmotic pressure, cytoskeletal contractility and drastic shape perturbations (cell wounding). To accomplish this goal, we first developed a simple and reliable technique to measure cell height and volume. This method is based on exclusion of fluorescent dye from the volume of the cell: the decrease of the fluorescent signal with respect to the background is proportional to the height and the volume of the object. We calibrated the technique using a glass microfabricated pattern with steps of defined heights and validated it by comparing our measurements with the ones obtained by atomic force microscopy (AFM). The method is fast and allows precise monitoring of height and volume of rapidly migrating cells, and do not require any modification to the standard epifluorescence setup. We applied our method to measure the real-time volume dynamics of migrating fish epidermal keratocytes subjected to osmotic stress and cytoskeletal perturbations. We then analyzed the relationship between shape of the cell, protrusion rate and membrane tension. We find that protrusion rate does not correlate with membrane tension, but, instead, is strongly correlated with cell roundness. We rationalized the relationship between cell roundness and protrusion velocity using the framework developed for wetting phenomena. The contact angle that the cell forms with the substrate defines the contribution of membrane tension to the force balance at the leading edge: the higher the contact angle, the less load is applied from the membrane to the actin network and therefore the faster is actin protrusion. We validated this concept by manufacturing topographically modified surfaces and showing that the leading edge of the cell exhibits pinning on substrate ridges - a phenomenon characteristic of spreading of liquid drops. These results demonstrate the role of contact angle at the leading edge in control of protrusion, which has important implications for cell shape dynamics and cell migration in 3D. We have also analyzed protrusion velocity in the case of high planar curvature of the advancing edge which was accomplished by making small circular wounds in keratocyte’s lamellipodia. The fact that these wounds presenting negative planar curvature close faster than the protrusion rate at the edge of the cell, is consistent with the important role of membrane curvature in the control of protrusion velocity. Our study underscores the fundamental importance of membrane configuration for cellular force balance and edge dynamics. It provides a novel framework for understanding the relationship between global cell shape and its local dynamics, of the balance between lamellipodia protrusion and blebbing, and for modulation of cell shape and motion by substrate topology

Funding knowledgebases: Towards a sustainable funding model for the UniProt use case [version 1; referees: 2 approved]

Millions of life scientists across the world rely on bioinformatics data resources for their research projects. Data resources can be very expensive, especially those with a high added value as the expert-curated knowledgebases. Despite the increasing need for such highly accurate and reliable sources of scientific information, most of them do not have secured funding over the near future and often depend on short-term grants that are much shorter than their planning horizon. Additionally, they are often evaluated as research projects rather than as research infrastructure components. In this work, twelve funding models for data resources are described and applied on the case study of the Universal Protein Resource (UniProt), a key resource for protein sequences and functional information knowledge. We show that most of the models present inconsistencies with open access or equity policies, and that while some models do not allow to cover the total costs, they could potentially be used as a complementary income source. We propose the Infrastructure Model as a sustainable and equitable model for all core data resources in the life sciences. With this model, funding agencies would set aside a fixed percentage of their research grant volumes, which would subsequently be redistributed to core data resources according to well-defined selection criteria. This model, compatible with the principles of open science, is in agreement with several international initiatives such as the Human Frontiers Science Program Organisation (HFSPO) and the OECD Global Science Forum (GSF) project. Here, we have estimated that less than 1% of the total amount dedicated to research grants in the life sciences would be sufficient to cover the costs of the core data resources worldwide, including both knowledgebases and deposition databases

Funding knowledgebases: Towards a sustainable funding model for the UniProt use case [version 2; referees: 3 approved]

Millions of life scientists across the world rely on bioinformatics data resources for their research projects. Data resources can be very expensive, especially those with a high added value as the expert-curated knowledgebases. Despite the increasing need for such highly accurate and reliable sources of scientific information, most of them do not have secured funding over the near future and often depend on short-term grants that are much shorter than their planning horizon. Additionally, they are often evaluated as research projects rather than as research infrastructure components. In this work, twelve funding models for data resources are described and applied on the case study of the Universal Protein Resource (UniProt), a key resource for protein sequences and functional information knowledge. We show that most of the models present inconsistencies with open access or equity policies, and that while some models do not allow to cover the total costs, they could potentially be used as a complementary income source. We propose the Infrastructure Model as a sustainable and equitable model for all core data resources in the life sciences. With this model, funding agencies would set aside a fixed percentage of their research grant volumes, which would subsequently be redistributed to core data resources according to well-defined selection criteria. This model, compatible with the principles of open science, is in agreement with several international initiatives such as the Human Frontiers Science Program Organisation (HFSPO) and the OECD Global Science Forum (GSF) project. Here, we have estimated that less than 1% of the total amount dedicated to research grants in the life sciences would be sufficient to cover the costs of the core data resources worldwide, including both knowledgebases and deposition databases