Designing citizen science tools for learning: lessons learnt from the iterative development of nQuire

This paper reports on a 4-year research and development case study about the design of citizen science tools for inquiry learning. It details the process of iterative pedagogy-led design and evaluation of the nQuire toolkit, a set of web-based and mobile tools scaffolding the creation of online citizen science investigations. The design involved an expert review of inquiry learning and citizen science, combined with user experience studies involving more than 200 users. These have informed a concept that we have termed ‘citizen inquiry’, which engages members of the public alongside scientists in setting up, running, managing or contributing to citizen science projects with a main aim of learning about the scientific method through doing science by interaction with others. A design-based research (DBR) methodology was adopted for the iterative design and evaluation of citizen science tools. DBR was focused on the refinement of a central concept, ‘citizen inquiry’, by exploring how it can be instantiated in educational technologies and interventions. The empirical evaluation and iteration of technologies involved three design experiments with end users, user interviews, and insights from pedagogy and user experience experts. Evidence from the iterative development of nQuire led to the production of a set of interaction design principles that aim to guide the development of online, learning-centred, citizen science projects. Eight design guidelines are proposed: users as producers of knowledge, topics before tools, mobile affordances, scaffolds to the process of scientific inquiry, learning by doing as key message, being part of a community as key message, every visit brings a reward, and value users and their time

A “Learning Revolution”? Investigating Pedagogic Practices around Interactive Whiteboards in British Primary Classrooms

Interactive whiteboards have been rapidly introduced into all primary schools under UK Government initiatives. These large, touch-sensitive screens, which control a computer connected to a digital projector, seem to be the first type of educational technology particularly suited for whole-class teaching and learning. Strong claims are made for their value by manufacturers and policy makers, but there has been little research on how, if at all, they influence established pedagogic practices, communicative processes and educational goals. This study has been designed to examine this issue, using observations in primary (elementary) school classrooms. It is funded by the UK Economic and Social Research Council and builds on the authors’ previous research on ICT in educational dialogues and collaborative activities

Decarbonising the critical sectors of aviation, shipping, road freight and industry to limit warming to 1.5–2°C

Limiting warming to well below 2°C requires rapid and complete decarbonisation of energy systems. We compare economy-wide modelling of 1.5°C and 2°C scenarios with sector-focused analyses of four critical sectors that are difficult to decarbonise: aviation, shipping, road freight transport, and industry. We develop and apply a novel framework to analyse and track mitigation progress in these sectors. We find that emission reductions in the 1.5°C and 2°C scenarios of the IMAGE model come from deep cuts in CO2 intensities and lower energy intensities, with minimal demand reductions in these sectors’ activity. We identify a range of additional measures and policy levers that are not explicitly captured in modelled scenarios but could contribute significant emission reductions. These are demand reduction options, and include less air travel (aviation), reduced transportation of fossil fuels (shipping), more locally produced goods combined with high load factors (road freight), and a shift to a circular economy (industry). We discuss the challenges of reducing demand both for economy-wide modelling and for policy. Based on our sectoral analysis framework, we suggest modelling improvements and policy recommendations, calling on the relevant UN agencies to start tracking mitigation progress through monitoring key elements of the framework (CO2 intensity, energy efficiency, and demand for sectoral activity, as well as the underlying drivers), as a matter of urgency

Dental microwear texture analysis of Homo sapiens sapiens: foragers, farmers, and pastoralists

Objectives. The current study seeks to determine if a sample of foragers, farmers, and pastoralists can be distinguished by their dental microwear texture signatures. Materials and Methods. The study included a sample of 719 individuals from 51 archaeological sites (450 farmers, 192 foragers, 77 pastoralists). All were over age 12 and sexes were pooled. Using a Sensofar® white-light confocal profiler we collected dental microwear texture analysis (DMTA) data from a single first or second molar from each individual. We leveled and cleaned data clouds following standard procedures and analyzed the data with Sfrax® and Toothfrax® software. The DMTA variables were complexity and anisotropy. Statistics included ANOVA with partial eta squared and Hedges's g. We also performed a follow-up K-means cluster analysis. Results. We found significant differences between foragers and farmers and pastoralists for complexity and anisotropy, with foragers having greater complexity than either the farmers or the pastoralists. The farmers and pastoralists had greater anisotropy than the foragers. The Old World foragers had significantly higher anisotropy values than New World foragers. Old and New World farmers did not differ. Among the Old World farmers, those dating from the Neolithic through the Late Bronze Age had higher complexity values than those from the Iron Age through the medieval period. The cluster analysis discerned foragers and farmers but also indicated similarity between hard food foragers and hard food farmers. Discussion. Our findings reaffirm that DMTA is capable of distinguishing human diets. We found that foragers and farmers, in particular, differ in their microwear signatures across the globe. There are some exceptions, but nothing that would be unexpected given the range of human diets and food preparation techniques. This study indicates that in general DMTA is an efficacious means of paleodietary reconstruction in humans

Drosophila KCNQ Channel Displays Evolutionarily Conserved Electrophysiology and Pharmacology with Mammalian KCNQ Channels

Of the five human KCNQ (Kv7) channels, KCNQ1 with auxiliary subunit KCNE1 mediates the native cardiac IKs current with mutations causing short and long QT cardiac arrhythmias. KCNQ4 mutations cause deafness. KCNQ2/3 channels form the native M-current controlling excitability of most neurons, with mutations causing benign neonatal febrile convulsions. Drosophila contains a single KCNQ (dKCNQ) that appears to serve alone the functions of all the duplicated mammalian neuronal and cardiac KCNQ channels sharing roughly 50–60% amino acid identity therefore offering a route to investigate these channels. Current information about the functional properties of dKCNQ is lacking therefore we have investigated these properties here. Using whole cell patch clamp electrophysiology we compare the biophysical and pharmacological properties of dKCNQ with the mammalian neuronal and cardiac KCNQ channels expressed in HEK cells. We show that Drosophila KCNQ (dKCNQ) is a slowly activating and slowly-deactivating K+ current open at sub-threshold potentials that has similar properties to neuronal KCNQ2/3 with some features of the cardiac KCNQ1/KCNE1 accompanied by conserved sensitivity to a number of clinically relevant KCNQ blockers (chromanol 293B, XE991, linopirdine) and opener (zinc pyrithione). We also investigate the molecular basis of the differential selectivity of KCNQ channels to the opener retigabine and show a single amino acid substitution (M217W) can confer sensitivity to dKCNQ. We show dKCNQ has similar electrophysiological and pharmacological properties as the mammalian KCNQ channels, allowing future study of physiological and pathological roles of KCNQ in Drosophila and whole organism screening for new modulators of KCNQ channelopathies

Stone Age Yersinia pestis genomes shed light on the early evolution, diversity, and ecology of plague

The bacterial pathogenYersinia pestisgave rise to devastating outbreaks throughouthuman history, and ancient DNA evidence has shown it afflicted human populations asfar back as the Neolithic.Y. pestisgenomes recovered from the Eurasian Late Neolithic/Early Bronze Age (LNBA) period have uncovered key evolutionary steps that led to itsemergence from aYersinia pseudotuberculosis-like progenitor; however, the number ofreconstructed LNBA genomes are too few to explore its diversity during this criticalperiod of development. Here, we present 17Y. pestisgenomes dating to 5,000 to 2,500y BP from a wide geographic expanse across Eurasia. This increased dataset enabled usto explore correlations between temporal, geographical, and genetic distance. Ourresults suggest a nonflea-adapted and potentially extinct single lineage that persistedover millennia without significant parallel diversification, accompanied by rapid dis-persal across continents throughout this period, a trend not observed in other pathogensfor which ancient genomes are available. A stepwise pattern of gene loss provides fur-ther clues on its early evolution and potential adaptation. We also discover the presenceof theflea-adapted form ofY. pestisin Bronze Age Iberia, previously only identified inin the Caucasus and the Volga regions, suggesting a much wider geographic spread ofthis form ofY. pestis. Together, these data reveal the dynamic nature of plague’s forma-tive years in terms of its early evolution and ecology

‘Fractional Recovery’ Analysis of a Presynaptic Synaptotagmin 1-Anchored Endocytic Protein Complex

BACKGROUND: The integral synaptic vesicle protein and putative calcium sensor, synaptotagmin 1 (STG), has also been implicated in synaptic vesicle (SV) recovery. However, proteins with which STG interacts during SV endocytosis remain poorly understood. We have isolated an STG-associated endocytic complex (SAE) from presynaptic nerve terminals and have used a novel fractional recovery (FR) assay based on electrostatic dissociation to identify SAE components and map the complex structure. The location of SAE in the presynaptic terminal was determined by high-resolution quantitative immunocytochemistry at the chick ciliary ganglion giant calyx-type synapse. METHODOLOGY/PRINCIPLE FINDINGS: The first step in FR analysis was to immunoprecipitate (IP) the complex with an antibody against one protein component (the IP-protein). The immobilized complex was then exposed to a high salt (1150 mM) stress-test that caused shedding of co-immunoprecipitated proteins (co-IP-proteins). A Fractional Recovery ratio (FR: recovery after high salt/recovery with control salt as assayed by Western blot) was calculated for each co-IP-protein. These FR values reflect complex structure since an easily dissociated protein, with a low FR value, cannot be intermediary between the IP-protein and a salt-resistant protein. The structure of the complex was mapped and a blueprint generated with a pair of FR analyses generated using two different IP-proteins. The blueprint of SAE contains an AP180/X/STG/stonin 2/intersectin/epsin core (X is unknown and epsin is hypothesized), and an AP2 adaptor, H-/L-clathrin coat and dynamin scission protein perimeter. Quantitative immunocytochemistry (ICA/ICQ method) at an isolated calyx-type presynaptic terminal indicates that this complex is associated with STG at the presynaptic transmitter release face but not with STG on intracellular synaptic vesicles. CONCLUSIONS/SIGNIFICANCE: We hypothesize that the SAE serves as a recognition site and also as a seed complex for clathrin-mediated synaptic vesicle recovery. The combination of FR analysis with quantitative immunocytochemistry provides a novel and effective strategy for the identification and characterization of biologically-relevant multi-molecular complexes

A Post-Synaptic Scaffold at the Origin of the Animal Kingdom

The evolution of complex sub-cellular structures such as the synapse requires the assembly of multiple proteins, each conferring added functionality to the integrated structure. Tracking the early evolution of synapses has not been possible without genomic information from the earliest branching animals. As the closest extant relatives to the Eumetazoa, Porifera (sponges) represent a pivotal group for understanding the evolution of nervous systems, because sponges lack neurons with clearly recognizable synapses, in contrast to eumetazoan animals.We show that the genome of the demosponge Amphimedon queenslandica possesses a nearly complete set of post-synaptic protein homologs whose conserved interaction motifs suggest assembly into a complex structure. In the critical synaptic scaffold gene, dlg, residues that make hydrogen bonds and van der Waals interactions with the PDZ ligand are 100% conserved between sponge and human, as is the motif organization of the scaffolds. Expression in Amphimedon of multiple post-synaptic gene homologs in larval flask cells further supports the existence of an assembled structure. Among the few post-synaptic genes absent from Amphimedon, but present in Eumetazoa, are receptor genes including the entire ionotropic glutamate receptor family.Highly conserved protein interaction motifs and co-expression in sponges of multiple proteins whose homologs interact in eumetazoan synapses indicate that a complex protein scaffold was present at the origin of animals, perhaps predating nervous systems. A relatively small number of crucial innovations to this pre-existing structure may represent the founding changes that led to a post-synaptic element

Automatic Robust Neurite Detection and Morphological Analysis of Neuronal Cell Cultures in High-content Screening

Cell-based high content screening (HCS) is becoming an important and increasingly favored approach in therapeutic drug discovery and functional genomics. In HCS, changes in cellular morphology and biomarker distributions provide an information-rich profile of cellular responses to experimental treatments such as small molecules or gene knockdown probes. One obstacle that currently exists with such cell-based assays is the availability of image processing algorithms that are capable of reliably and automatically analyzing large HCS image sets. HCS images of primary neuronal cell cultures are particularly challenging to analyze due to complex cellular morphology. Here we present a robust method for quantifying and statistically analyzing the morphology of neuronal cells in HCS images. The major advantages of our method over existing software lie in its capability to correct non-uniform illumination using the contrast-limited adaptive histogram equalization method; segment neuromeres using Gabor-wavelet texture analysis; and detect faint neurites by a novel phase-based neurite extraction algorithm that is invariant to changes in illumination and contrast and can accurately localize neurites. Our method was successfully applied to analyze a large HCS image set generated in a morphology screen for polyglutaminemediated neuronal toxicity using primary neuronal cell cultures derived from embryos of a Drosophila Huntington’s Disease (HD) model.National Institutes of Health (U.S.) (Grant