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  • Evaluating the Quick Fix: Weight Loss Drugs and Cellular Respiration Image File: QuickFixPrimImage.tiff Sources for images: Balance: Public Domain CCO http://www.pd4pic.com/scales-justice-scale-libra-balance-weighbridge.html Mitochondria: https://thumb7.shutterstock.com/thumb_large/1503584/235472731/stock-vector-mitochondrion-235472731.jpg Pills: https://pixabay.com/static/uploads/photo/2014/07/05/15/16/pills-384846_960_720.jpg

    Evaluating the Quick Fix: Weight Loss Drugs and Cellular Respiration

    Learning Objectives
    • Students will be able to explain how the energy from sugars is transformed into ATP via cellular respiration.
    • Students will be able to predict an outcome if there is a perturbation in the cellular respiration pathway.
    • Students will be able to state and evaluate a hypothesis.
    • Students will be able to interpret data from a graph, and use that data to make inferences about the action of a drug.
  • Using phylogenetics to make inferences about historical biogeographic patterns of evolution.

    Building Trees: Introducing evolutionary concepts by exploring Crassulaceae phylogeny and biogeography

    Learning Objectives
    Students will be able to:
    • Estimate phylogenetic trees using diverse data types and phylogenetic models.
    • Correctly make inferences about evolutionary history and relatedness from the tree diagrams obtained.
    • Use selected computer programs for phylogenetic analysis.
    • Use bootstrapping to assess the statistical support for a phylogeny.
    • Use phylogenetic data to construct, compare, and evaluate the role of geologic processes in shaping the historical and current geographic distributions of a group of organisms.
  • “The outcome of the Central Dogma is not always intuitive” Variation in gene size does not necessarily correlate with variation in protein size. Here, two related genes differ in length due to a deletion mutation that removes four nucleotides. Many students do not predict that the smaller gene, after transcription and translation, would produce a larger protein.

    Predicting and classifying effects of insertion and deletion mutations on protein coding regions

    Learning Objectives
    Students will be able to:
    • accurately predict effects of frameshift mutations in protein coding regions
    • conduct statistical analysis to compare expected and observed values
    • become familiar with accessing and using DNA sequence databases and analysis tools
  • Example image of dividing cells obtained from the Allen Institute for Cell Science 3D Cell Viewer.

    A virtual laboratory on cell division using a publicly-available image database

    Learning Objectives
    • Students will name and describe the salient features and cellular tasks for each stage of cell division.
    • Students will predict the relative durations of the stages of cell division using prior knowledge and facts from assigned readings.
    • Students will describe the relationship between duration of each stage of cell division and the frequency of cells present in each stage of cell division counted in a random sample of images of pluripotent stem cells.
    • Students will identify the stages of cell division present in research-quality images of human pluripotent stem cells in various stages of cell division.
    • Students will quantify, analyze and summarize data on the prevalence of cells at different stages of cell division in randomly sampled cell populations.
    • Students will use data to reflect on and revise predictions.