Using a Computer Simulation to Teach Science Process Skills to College Biology and Elementary Majors

The Lateblight computer simulation (Arneson and Ticknor, 1990) has been implemented in the general biology laboratory and the science methods course for elementary teachers to reinforce the processes of science and to allow the students to engage, explore, explain, elaborate and evaluate the methods of building concepts in science. The students develop testable hypotheses and then use the program to run experiments and collect data. In addition, they research relevant background information and subsequently present their results in a poster during class

Beyond the black box: Promoting mathematical collaborations for elucidating interactions in soil ecology

© 2019 The Authors. Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant-soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: Theory spanning scales and ecological hierarchies, processes, and evolution

Beyond the black box: promoting mathematical collaborations for elucidating interactions in soil ecology

This work is licensed under a Creative Commons Attribution 4.0 International License.Understanding soil systems is critical because they form the structural and nutritional foundation for plants and thus every terrestrial habitat and agricultural system. In this paper, we encourage increased use of mathematical models to drive forward understanding of interactions in soil ecological systems. We discuss several distinctive features of soil ecosystems and empirical studies of them. We explore some perceptions that have previously deterred more extensive use of models in soil ecology and some advances that have already been made using models to elucidate soil ecological interactions. We provide examples where mathematical models have been used to test the plausibility of hypothesized mechanisms, to explore systems where experimental manipulations are currently impossible, or to determine the most important variables to measure in experimental and natural systems. To aid in the development of theory in this field, we present a table describing major soil ecology topics, the theory previously used, and providing key terms for theoretical approaches that could potentially address them. We then provide examples from the table that may either contribute to important incremental developments in soil science or potentially revolutionize our understanding of plant–soil systems. We challenge scientists and mathematicians to push theoretical explorations in soil systems further and highlight three major areas for the development of mathematical models in soil ecology: theory spanning scales and ecological hierarchies, processes, and evolution

A hand hygiene intervention to decrease infections among children attending day care centers: Design of a cluster randomized controlled trial

Background: Day care center attendance has been recognized as a risk factor for acquiring gastrointestinal and respiratory infections, which can be prevented with adequate hand hygiene (HH). Based on previous studies on environmental and sociocognitive determinants of caregivers' compliance with HH guidelines in day care centers (DCCs), an intervention has been developed aiming to improve caregivers' and children's HH compliance and decrease infections among children attending DCCs. The aim of this paper is to describe the design of a cluster randomized controlled trial to evaluate the effectiveness of this intervention.Methods/design: The intervention will be evaluated in a two-arm cluster randomized controlled trial among 71 DCCs in the Netherlands. In total, 36 DCCs will receive the intervention consisting of four components: 1) HH products (dispensers and refills for paper towels, soap, alcohol-based hand sanitizer, and hand cream); 2) training to educate about the Dutch national HH guidelines; 3) two team training sessions aimed at goal setting and formulating specific HH improvement activities; and 4) reminders and cues to action (posters/stickers). Intervention DCCs will be compared to 35 control DCCs continuing usual practice. The primary outcome measure will be observed HH compliance of caregivers and children, measured at baseline and one, three, and six months after start of the intervention. The secondary outcome measure will be the incidence of gastrointestinal and respiratory infections in 600 children attending DCCs, monitored over six months by parents using a calendar to mark th

Learning a Prior on Regulatory Potential from eQTL Data

Genome-wide RNA expression data provide a detailed view of an organism's biological state; hence, a dataset measuring expression variation between genetically diverse individuals (eQTL data) may provide important insights into the genetics of complex traits. However, with data from a relatively small number of individuals, it is difficult to distinguish true causal polymorphisms from the large number of possibilities. The problem is particularly challenging in populations with significant linkage disequilibrium, where traits are often linked to large chromosomal regions containing many genes. Here, we present a novel method, Lirnet, that automatically learns a regulatory potential for each sequence polymorphism, estimating how likely it is to have a significant effect on gene expression. This regulatory potential is defined in terms of “regulatory features”—including the function of the gene and the conservation, type, and position of genetic polymorphisms—that are available for any organism. The extent to which the different features influence the regulatory potential is learned automatically, making Lirnet readily applicable to different datasets, organisms, and feature sets. We apply Lirnet both to the human HapMap eQTL dataset and to a yeast eQTL dataset and provide statistical and biological results demonstrating that Lirnet produces significantly better regulatory programs than other recent approaches. We demonstrate in the yeast data that Lirnet can correctly suggest a specific causal sequence variation within a large, linked chromosomal region. In one example, Lirnet uncovered a novel, experimentally validated connection between Puf3—a sequence-specific RNA binding protein—and P-bodies—cytoplasmic structures that regulate translation and RNA stability—as well as the particular causative polymorphism, a SNP in Mkt1, that induces the variation in the pathway

Transcriptome analyses based on genetic screens for Pax3 myogenic targets in the mouse embryo

<p>Abstract</p> <p>Background</p> <p>Pax3 is a key upstream regulator of the onset of myogenesis, controlling progenitor cell survival and behaviour as well as entry into the myogenic programme. It functions in the dermomyotome of the somite from which skeletal muscle derives and in progenitor cell populations that migrate from the somite such as those of the limbs. Few Pax3 target genes have been identified. Identifying genes that lie genetically downstream of <it>Pax3 </it>is therefore an important endeavour in elucidating the myogenic gene regulatory network.</p> <p>Results</p> <p>We have undertaken a screen in the mouse embryo which employs a <it>Pax3^GFP</it>allele that permits isolation of Pax3 expressing cells by flow cytometry and a <it>Pax3^PAX3-FKHR</it>allele that encodes PAX3-FKHR in which the DNA binding domain of Pax3 is fused to the strong transcriptional activation domain of FKHR. This constitutes a gain of function allele that rescues the <it>Pax3 </it>mutant phenotype. Microarray comparisons were carried out between <it>Pax3^GFP/+</it>and <it>Pax3^{GFP/PAX3-FKHR}</it>preparations from the hypaxial dermomyotome of somites at E9.5 and forelimb buds at E10.5. A further transcriptome comparison between Pax3-GFP positive and negative cells identified sequences specific to myogenic progenitors in the forelimb buds. Potential Pax3 targets, based on changes in transcript levels on the gain of function genetic background, were validated by analysis on loss or partial loss of function <it>Pax3 </it>mutant backgrounds. Sequences that are up- or down-regulated in the presence of PAX3-FKHR are classified as somite only, somite and limb or limb only. The latter should not contain sequences from Pax3 positive neural crest cells which do not invade the limbs. Verification by whole mount <it>in situ </it>hybridisation distinguishes myogenic markers. Presentation of potential Pax3 target genes focuses on signalling pathways and on transcriptional regulation.</p> <p>Conclusions</p> <p>Pax3 orchestrates many of the signalling pathways implicated in the activation or repression of myogenesis by regulating effectors and also, notably, inhibitors of these pathways. Important transcriptional regulators of myogenesis are candidate Pax3 targets. Myogenic determination genes, such as <it>Myf5 </it>are controlled positively, whereas the effect of <it>Pax3 </it>on genes encoding inhibitors of myogenesis provides a potential brake on differentiation. In the progenitor cell population, <it>Pax7 </it>and also <it>Hdac5 </it>which is a potential repressor of <it>Foxc2</it>, are subject to positive control by <it>Pax3</it>.</p

Global urban environmental change drives adaptation in white clover

Urbanization transforms environments in ways that alter biological evolution. We examined whether urban environmental change drives parallel evolution by sampling 110,019 white clover plants from 6169 populations in 160 cities globally. Plants were assayed for a Mendelian antiherbivore defense that also affects tolerance to abiotic stressors. Urban-rural gradients were associated with the evolution of clines in defense in 47% of cities throughout the world. Variation in the strength of clines was explained by environmental changes in drought stress and vegetation cover that varied among cities. Sequencing 2074 genomes from 26 cities revealed that the evolution of urban-rural clines was best explained by adaptive evolution, but the degree of parallel adaptation varied among cities. Our results demonstrate that urbanization leads to adaptation at a global scale

Cataract Surgery in the Medicare Merit-Based Incentive Payment System

Objective: To characterize the development and performance of a cataract surgery episode-based cost measure for the Medicare Quality Payment Program. Design: Claims-based analysis. Participants: Medicare clinicians with cataract surgery claims between June 1, 2016, and May 31, 2017. Methods: We limited the analysis to claims with procedure code 66984 (routine cataract surgery), excluding cases with relevant ocular comorbidities. We divided episodes into subgroups by surgery location (Ambulatory Surgery Center [ASC] or Hospital Outpatient Department [HOPD]) and laterality (bilateral when surgeries were within 30 days apart). For the episode-based cost measure, we calculated costs occurring between 60 days before surgery and 90 days after surgery, limited to services identified by an expert committee as related to cataract surgery and under the influence of the cataract surgeon. We attributed costs to the clinician submitting the cataract surgery claim, categorized costs into clinical themes, and calculated episode cost distribution, reliability in detecting clinician-dependent cost variation, and costs with versus without complications. We compared episode-based cost scores with hypothetical “nonselective” cost scores (total Medicare beneficiary costs between 60 days before surgery and 90 days after surgery). Main Outcome Measures: Episode costs with and without complications, clinician-dependent variation (proportion of total cost variance), and proportion of costs from cataract surgery-related clinical themes. Results: We identified 583 356 cataract surgery episodes attributed to 10 790 clinicians and 8189 with ≥ 10 episodes during the measurement period. Most surgeries were performed in an ASC (71%) and unilateral (66%). The mean episode cost was $2876. The HOPD surgeries had higher costs; geography and episodes per clinician did not substantially affect costs. The proportion of cost variation from clinician-dependent factors was higher in episode-based compared with nonselective cost measures (94$3738 vs. $2276). Conclusions: The cataract surgery episode-based cost measure performs better than a comparable nonselective measure based on cost distribution, clinician-dependent variance, association with cataract surgery-related clinical themes, and quality alignment (higher costs in episodes with complications). Cost measure maintenance and refinement will be important to maintain clinical validity and reliability. Financial Disclosure(s): Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article

Patchy field sampling biases understanding of climate change impacts across the Arctic

Effective societal responses to rapid climate change in the Arctic rely on an accurate representation of region-specific ecosystem properties and processes. However, this is limited by the scarcity and patchy distribution of field measurements. Here, we use a comprehensive, geo-referenced database of primary field measurements in 1,840 published studies across the Arctic to identify statistically significant spatial biases in field sampling and study citation across this globally important region. We find that 31% of all study citations are derived from sites located within 50 km of just two research sites: Toolik Lake in the USA and Abisko in Sweden. Furthermore, relatively colder, more rapidly warming and sparsely vegetated sites are under-sampled and under-recognized in terms of citations, particularly among microbiology-related studies. The poorly sampled and cited areas, mainly in the Canadian high-Arctic archipelago and the Arctic coastline of Russia, constitute a large fraction of the Arctic ice-free land area. Our results suggest that the current pattern of sampling and citation may bias the scientific consensuses that underpin attempts to accurately predict and effectively mitigate climate change in the region. Further work is required to increase both the quality and quantity of sampling, and incorporate existing literature from poorly cited areas to generate a more representative picture of Arctic climate change and its environmental impacts