BIOMEDICAL ASSIGNMENT

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BIOMEDICAL ASSIGNMENT.

University of Strathclyde

Department of Biomedical Engineering

BE900 Tissue Mechanics Assessment #2

Unconfined Compression of biphasic and viscoelastic media

Body tissues are often modelled as being viscoelastic or biphasic. Since cellular activity depends on the mechanical environment, it is important to understand the mechanics of each type of material. You are required to submit a short report (no more than 1000 words and 8 figures) on the unconfined compression of biphasic and viscoelastic media. Using FEBio, please analyse the mechanics (stress, strain, fluid pressure etc.) of a 10 mm diameter and 3mm height cylindrical tissue in unconfined compression. You should compare two different materials:

1. Biphasic: The material should have an isotropic elastic solid phase, defined by E = 100 MPa, n=0.3, and a constant permeability of 1 x 10-15 m4/Ns. Take solid volume as 0.2.

2. Viscoelastic: The material should be based on isotropic elasticity, defined by E = 100 MPa, n=0.3. Coefficient 1 should be 0.5 and relaxation time 1 = 100. All other parameters should be left at their default values (G2-G6 = 0, t2-t6 = 1).

In class, it was shown that the relaxation modulus for a 3 parameter solid may be written as

= ‘ + ) + ,-.

This may be expressed as:

= ‘ 1 + ) ‘ +

, -. = 1 + 1+

, ,)

where ‘ = , 0. 01 = 1 and ) = 1. The value of 1 and 1 have been chosen to approximately make

the time history of the axial stress similar to that of the biphasic tissue. Please note they will not match perfectly.

Each cylinder of material should be subjected to axial unconfined compression to -0.1 strain at -0.01 s-1 by an impermeable, rigid platen. You are required to analyse, compare and contrast the mechanics of each material in the ramp phase and until equilibrium.

 

 

 

Your report should contain the following sections:

Introduction (5%): Provide a very brief introduction. The introduction should finish with precise aims and objectives of the activity.

Methods (20%): The methods section should fully describe your model. Include information regarding the mesh, materials, boundary and loading conditions along with anything else you think relevant.

Results (40%): Use appropriate figures to help you describe the mechanics of each material in unconfined compression. Every figure must be cited and described in the text, highlighting the important aspects of the figure.

Discussion (30%): Compare and contrast the materials and discuss the implications of this difference when describing the cellular stress environment.

Conclusion (5%): A short conclusion will suffice.

Hand in deadline: Noon, Monday 17 April

I will activate an online submission through the class page on MyPlace.

You should submit your report and two .feb files: one for the viscoelastic material and one for the poroelastic medium.

PLEASE NOTE:

• There is not one perfect model. Many models will achieve the aim, but some will be better than others.

• The more nodes and elements you have, the longer the solution time. The smaller the element size, the more accurate the solution. However, too many and you may be waiting hours/days for a solution. Think about how to use symmetry to reduce the problem’s geometry.

• You can use a bias in your mesh, if you wish, to concentrate nodes and elements in regions of steep gradients of fluid pressure.

Marks will be deducted if:

• Your report is late (see Penalties in the handbook) • Your report is < 750 words, or > 1250 words (0.1% per word) • You include more than 8 figures (5% per figure). Note, using a numbering system such as Figure

3a and Figure 3b will not enable to have more figures. This will still be counted as two figures. • You do not communicate in clear English. Technical clarity is of utmost importance.

You will receive a mark of zero if there is evidence of collusion or plagiarism for ALL those involved. I advise you NOT to share your electronic files with anyone. When you leave a computer, ensure you log out. You may chat and discuss the coursework, but the creation of the .feb files, along with the written report must be uniquely your own work.

BIOMEDICAL ASSIGNMENT

 
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BCHS3201: Microarray Paper

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BCHS3201: Microarray Paper. BCHS3201: Microarray Paper

Background

You will be working with data generated using Affymetrix Arabidopsis thaliana (ATH1) full genome chips. Please watch the microarray lecture posted in Blackboard for information on how the chips are constructed and how they are used. Step-by-step instructions are provided here for managing the data. While I have provided details here, keep in mind that in a real research lab, you would have to decide for yourself how to organize the data and make sense of it.

Arabidopsis thaliana

Arabidopsis thaliana is a small, flowering plant found all over the world. It is commonly considered a weed in the United States and can be found in the Midwest (Texas is too hot; the plant likes temperatures around 68°F). Arabidopsis serves as a model plant because it has a number of characteristics that make it amenable to study. The plant is small, reaching only 30 cm in height when full grown. It grows well grows well in both soil and nutrient media making it easier to develop carefully controlled studies (Meyerowitz, 1989). It is easily grown indoors in a laboratory. Crop plants require much larger facilities and land to study. The life cycle of Arabidoposis is only 6 weeks from seed to seed-producing. This allows a much faster pace for experiments than most crop plants where only one generation of plants can be grown in a calendar year (unless your university is fortunate enough to have land on two hemispheres so you can get two growing seasons in). Arabidopsis plants produce thousands of seeds per plant and these seeds are tiny making them easy to store in microcentrifuge tubes in the freezer (Meyerowitz, 1989).

Arabidopsis has a haploid genome of 5 chromosomes consisting of approximately 125 megabases (The Arabidopsis Genome Initiative, 2000). This is a very small genome compared to that of crop species. Maize, for example, is around 2,500 megabases in size (Adam, 2000). Most genes in Arabidopsis exist at a single locus in the genome. Crop plant genomes are large in part because their genomes contain large sections that are duplicated. This makes creating complete knock-outs of a particular gene difficult. Arabidopsis is amenable to genetic manipulations either through traditional cross-breeding techniques or more modern genetic modification techniques (mutation through T-DNA inserts, chemical agents, or CRISPR-CAS9). Studies conducted in Arabidopsis are often directly transferable to crop species as many of the genes have homologues in crop plants. Studying them first in Arabidopsis is easier, cheaper, and faster.

Sugar and Phytohormone Signaling Pathways

Sugars have a role in basic plant metabolism as a carbon source and also play a role as signaling molecules, contributing to the regulation of a number of pathways in plants. The expression of genes involved in mobilization of starch and lipid reserves is usually repressed by the presence of high sugar levels in the plant while genes involved in storage of carbohydrates are upregulated (Jang & Sheen, 1997; Yu, 1999). Soluble sugar levels in plants also play a role in a number of developmental processes including time to flowering (Bernier et al., 1993), shoot to root ratios (Wilson, 1988), and senescence (cells stop dividing and normal biological processes begin to deteriorate) (Dai et al., 1999). The DNA chip data you will be analyzing for class is part of a larger study to elucidate the full impact of sugar signaling in Arabidopsis and to identify potential components of signaling pathways for future study.

Phytohormones are involved in a wide array of plant responses. The plant phytohormones ethylene and abscisic acid are also intertwined with the sugar response signaling pathways.

Ethylene plays a role in a plant’s development as well as its response to environmental conditions. Ethylene has a role in shoot and root elongation, sex determination, petal senescence, and fruit ripening. It also is involved in the plant’s response to flooding and pathogens.

Abscisic acid is involved in preventing pre-mature germination of seeds, root elongation, and stomatal closure. Stomata are pores in the leaf epidermis which control the rate of gas exchange. The pore is surrounded by two bean-shaped guard cells that regulate the size of the pore opening. Abscisic acid plays a critical role in the closure of the guard cells. Plants with mutations in the abscisic acid biosynthesis pathway have a “wilty” phenotype because they are unable to close their stomata during the day when loss of water to evaporative processes is high. The mutant, aba2, has been found to allelic to the glucose insensitive 1 (gin1) mutant (meaning the mutation for both aba2 and gin1 lie in the same gene).

Signaling pathways often work together to fine-tune plant development and responses. Seed germination, for example is finely controlled by antagonist interactions between sugar and abscisic acid which inhibit germination and gibberellin and ethylene which promote germination (figure 1).

Figure 1. Seed germination is controlled by a combination of signals from sugar levels, abscisic acid, gibberellin, and ethylene.

The sugar-insensitive 6 (sis6) mutant is slightly resistant to the inhibitory effects of abscisic acid on germination (Pattison, 2004). When seeds are grown in a petri plate with nutrient medium supplemented with abscisic acid, germination is delayed in wild-type plants. The sugar-insensitive 3 (sis3) mutant is slightly resistant to the effect of abscisic acid in comparison to wild-type (Columbia ecotype) seeds. The abscisic acid insensitive 4-1 (abi4-1) mutant displays precocious seed germination in the presence of abscisic acid, germinating despite the presence of exogenous ABA which should significantly delay germination (figure 2).

 

 

Figure 2. The sis6 mutant is insensitive to the inhibitory effects of ABA on germination. Seeds were sown on the indicated media and grown in continuous white fluorescent light. Germination was scored every 12 hours for four days and then every 24 hours thereafter. Error bar represent the mean ± standard deviation (n=3). This experiment was conducted three times with similar results. From Pattison, 2004.

 

How the Data was Collected for this set of Experiments

In order to conduct a chip experiment, RNA must be collected from the samples. In our experiments, Arabidopsis seeds were surface sterilized, cold treated at 4° C in the dark for three days and then plated on Nytex mesh screens placed in petri dishes containing minimal nutrient media. After 20 hour under continuous light at 21° the nytex meshes were transferred to plates containing either minimal media, or minimal media supplemented with 100 mM sorbitol, 100 mM glucose, 10 µM abscisic acid or 50 µM ACC (ethylene pre-cursor). Seeds were grown on the new media for 12.5 hours and then frozen in liquid nitrogen. RNA was extracted using a phenol/chloroform extraction (Verwoerd et al., 1989). RNA samples were sent to the Molecular Genomics Core Facility at the University of Texas Medical Branch in Galveston for processing.

Part 1. Selecting your experimental conditions

To begin your work on the microarray project, you need to select your topic of study. You need to decide what you would like to examine and then select the appropriate control condition. Your options are in Table 1 below.

Options Topic Control Experimental Developmental Stage
1 Osmotic stress WT minimum WT sorbitol Germinating seeds
2 Osmotic stress WT sorbitol sis 6 sorbitol Germinating seeds
3 Glucose signaling WT sorbitol WT glucose Germinating seeds
4 Glucose signaling WT glucose ein2-1 glucose Germinating seeds
5 Abscisic acid signaling WT minimum WT on ABA Germinating seeds
6 Abscisic acid signaling WT glucose sis4-1 (aba2) glucose Germinating seeds
7 Abscisic acid signaling WT glucose sis5 (abi4) glucose Germinating seeds
8 Ethylene signaling WT minimal media WT ACC (ethylene) Germinating seeds

Table 1. Select your topic of study for the microarray project. Choose one option. Each row represents one possible option. Because the control must be appropriately matched to the experimental condition, you may not mix and match between rows.

Part 2. Identifying differences in gene regulation between control and experimental conditions.

1. Download the spreadsheet corresponding to your selected control and experimental conditions to your computer.

2. Take a few minutes to familiarize yourself with the spreadsheet layout.

Column A: AGI#. AGI stands for Arabidopsis Genome Initiative. Every gene in the Arabidopsis

was assigned a unique identifier during the genome sequencing project. The Affymetrix DNA

chip contains over 22,000 genes representing nearly every known gene in the genome of Arabidopsis.

Column B: Affy Probe Index #. The Affymetrix probe index # refers to the probe array that corresponds to each gene. Each probe array contains 11 pairs of probe to the same gene. One probe in each pair is a perfect match to the gene and the other contains a mismatch in the center of the probe. The software uses the data from the perfect match sets and the mismatch sets to subtract out signal that may have arisen from near (but not quite perfect) matches. The names of the probe sets are based on what was known about the gene sequence at the time the chip was created.

Names ending in means

_at all probes match one known transcript

_a all probes match alternate transcripts from the same gene

_s all probes match transcripts from different genes

_x some probes match transcripts from different genes

 

Notice that rows 2 through 65 do not have AGI#’s and the Probe Index #’s all begin with AFFX. These are the quality control probe arrays for the chip. They are included so that researchers know that there were not technical issues with the chip or samples. A mix of probes that will result in positive and absent calls are included.

 

Signal Columns: Each experiment in this data set was conducted between 3 and 6 times. The

columns that contain the word “Signal” in the header represent the value for the signal reads.

 

Detection Columns: The column to the right of each signal column is the Detection Column.

P= present

A=absent

M=marginal

 

Present means the gene was expressed in the sample, resulting in a measurable signal above a

minimal detection threshold. Absent means the gene was not expressed under the experimental conditions. Marginal means the expression was very near the detection threshold. Marginal calls require further investigation and experimentation to confirm.

 

Converted Detection Columns: The column to the right of each Detection Column is the Converted Detection Column. The PMA calls are converted to a numeric value which allows the researcher to average the detection calls and decide whether or not to include a particular gene in the data set.

P=2

A=0

M=1

 

Descriptions: what was known about the gene at the gene identity or function at the time the Chip was created.

 

3. Open a new Excel file and name it as follows: Lastname_firstname_microarray.

 

 

4. Change the name of Sheet 1 to “control” by right clicking on the tab and selecting “rename” from the pop up menu. Copy and paste all the data from your control sheet into the “control tab”.

 

5. Click the “+” sign to add another tab at the bottom of the Excel sheet. Rename the new sheet “experimental”. Copy and paste all the data from your experimental sheet into the “experimental tab”.

 

6. For both experimental and control conditions, delete the rows containing the controls. These will be the rows at the top (that lack an AGI#).

 

7. Scroll to the right. Skip a column after the “Descriptions” column. Label the next column to the right “AVG control PMA” or “AVG experimental PMA”. Calculate the average PMA call for each gene using the converted detection column values for each condition. For example, if converted PMA detection calls are located in cells E2, I2, M2, an Q2, the formula you enter into the cell would be “=(E2+I2+M2+Q2)/4”. Do this for both your control and experimental sheets. Enter the formula and copy/paste it down the column. The row numbers will change automatically.

 

 

8. Click the “+” sign to add another tab to the bottom of the Excel sheet. Rename the new sheet “combined”.

 

9. Copy the following columns into the “combined” data sheet. You will need to paste “values” for any columns containing formulas. It’s under paste options.

a. AGI#

b. Signal columns for the control

c. Leave a blank column

c. Signal columns for the experimental

d. Leave a blank column

d. AVG control PMA column

e. AVG experimental PMA column

 

10. In the combined data sheet, add another column to the right of your AVG control PMA and AVG Experimental PMA columns.. Label this one “final PMA call”. Type in the formula “=MAX(XX2:XY2) where XX is the column labeled “AVG control PMA” and XY is the column labeled “AVG exp PMA” (substitute your actual column letters for XX and XY). This formula will transfer the maximum value for the two columns to the new “final PMA call column”. The point of doing this is to preserve genes in the data set where there was signal in one of the two conditions. For example, you would not want to delete a gene from the data set because it had an absent call in the control but was upregulated 15 fold in the experimental conditions. By looking at the results using the final column, we can eliminate genes where the signal was not detected in BOTH conditions.

 

11. In the combined spreadsheet, highlight your entire data set. Make sure you pick up all the cells with data. Click “Sort & Filter” in the toolbar. Click custom sort. Check the box on the right in pop-up box that says “My data has headers”. Sort by the “final PMA call” column from smallest to largest. Delete all rows that have a value of zero for final PMA call. This will eliminate all genes that were not expressed in either the control or experimental condition from the data set.

 

12. Add a column to the right of the “Final PMA call” column labeled “AVG control signal” in your combined spreadsheet. Average the values for the signal columns in your control data set. Use the formula =AVERAGE(X2:Y2) where X is the first column with the control signal data and Y is the last column of control signal data. Copy and paste the formula from row 2 all the way down the column. The row numbers will automatically change in the formula.

 

 

 

13. Add a column to the right of the “AVG control signal” column labeled “AVG experimental signal” in your combined spreadsheet. Average the values for the signal columns in your experimental data set. Use the formula =AVERAGE(X2:Y2) where X is the first column with the control signal data and Y is the last column of control signal data. Copy and paste the formula from row 2 all the way down the column. The row numbers will automatically change in the formula.

 

14. Add a column to the right labeled of the “AVG experimental signal” column labeled “AVG control/AVG experimental”. You will divide the average control signal value by the average experimental value using the formula “=XX2/XY2” [where XX is your AVG control signal column (row 2) and XY is your AVG experimental signal column (row2)]. Copy the formula down the column.

 

15. Add a column to the right of the “AVG control/AVG experimental” column labeled T-test. You will calculate whether there is a statistically significant difference between the two conditions. The syntax for this formula is T.Test(array1,array2, tails, type). Array 1 will be the cells containing the signal values for the control. Array 2 will be the cells containing the signal values for the experimental samples. These are NOT the averaged signals but the original values on the left-hand side of your spreadsheet. We will use a 2-tailed T-test. The type will be a two-sample equal variance test which Excel designates as “2”. For example, if the control signal columns were B, C, D and the experimental signal columns were E, F, and G, then the formula to set up in row 2 for the T-Test would be “=TTEST(B2:D2, E2:G2,2,2). Copy the formula down the row to calculate the p-values for the T-Test for each gene.

 

16. Click the “+” sign to add another tab to the bottom of the Excel sheet. Rename the new sheet “final”. Copy all the data from the “combined” spreadsheet into your “final” spreadsheet using the copy and paste value option. This will allow you to go back to the combined sheet to relax the stringency of your data selection if you find you end up with no genes at all in your data set when you complete the following steps.

 

17. Highlight your entire spreadsheet. Click “Sort & Filter” in the toolbox. Click custom sort. Click the “my data has headers” box on the right of the pop-up box. Sort by T-test value from largest to smallest. Delete all genes that have a p-value greater than 0.05. The expression of these genes is not significantly different between the control and experimental conditions and can be eliminated from the data set.

 

18. Highlight your entire spreadsheet again. Click “Sort & Filter” in the toolbox. Click custom sort. Click the “my data has headers” box on the right in the pop-up box. Sort by AVG control/AVG experimental from smallest to largest. Delete all genes that have a fold change between 1.99999 and 0.499999. What you are looking for are genes where the change in expression is two-fold above or below the level for the control condition. You want to keep genes in the data set where the AVG control/AVG experimental value is below 0.5 or lower. These are genes that are UPREGULATED in the experimental compared to the control. The larger number is in your denominator so the numbers are less than 1. You also want to keep genes in the data set where the AVG control/AVG experimental value is 2 or higher. In this case, the genes are DOWNREGULATED in the experimental condition compared to the control condition. Since the larger number is in the numerator, the value is greater than 1. If you do not have any genes with at least a two-fold difference in expression, between control and experimental, relax your conditions and select genes with fold changes between 1.5 and 0.66.

 

19. Change the font color for all of the down-regulated genes to red [AVG control/AVG experimental values above 2 (or 1.5 if you relaxed the conditions)].

 

20. Change the font color for all of the up-regulated genes to green [AVG control/AVG experimental values below 0.5 (or 0.66 if you relaxed the conditions)].

 

21. Determine how many genes were up-regulated and how many were down-regulated.

 

Part 3. Gene Ontology (GO) Biological Process

1. Copy the first column with the AGI#’s into a new Excel sheet. Do not copy the column header. Save the file as a comma delimited file (CSV).

2. Go to https://www.arabidopsis.org/ . Click Search and select Gene Ontology annotations from the drop down menu.

 

3. Click Choose file. Select your CSV file. Click Functional Categorization.

 

4. Click Draw next to “Annotation Pie Chart”. This will generate 3 pie charts: GO Cellular Component, GO Biological Process, and GO Molecular Function. You will include the GO Biological Process chart in your paper. Copy and paste that into your Word file for your paper. When you write your paper, you should discuss anything that stands out to you as particularly interesting given your chosen topic. You do not need to discuss every single category of information appearing in these charts. You may include the other two charts in your paper if there is something in particular that you wish to highlight or tie into your discussion section of the paper but you are not required to do so.

 

Part 4.

Selecting a gene of interest for detailed study.

Information is continuously being added to our knowledge base. Many genes have been identified since the data in this particular data set was first collected. If you want to see if more information is available for a particular gene that has a particularly striking fold change, you can check TAIR, the Arabidopisis Information Resource at https://www.arabidopsis.org/.

Click Search:

 

Click Microarray Element from the dropdown box. Enter your locus identifier in the box (example: At5g01810). Make sure Affymetrix ATH1 is selected (this is the type of chip our data set is from) and click “Get Microarray Elements”.

 

To get detailed information on a gene of interest.

In this example, information about the gene can be found under the annotation.

 

 

You will want to select a gene that from your dataset that is strongly up or down-regulated (a fold change of 3 is preferred but you may go as low as 1.5-fold if necessary for the purpose of this assignment). You need to select a gene that has been studied in the past. Skip ones that are listed as unknown function in both our data set and when you look it up in the search above.

Next, click the search box in the top left corner again and this time select “Genes”. Enter your locus ID (example At5g01810) in the “starts with” box under the Search by Name or Phenotype section. Scroll to the bottom of the page and hit “Submit Query”. Select your locus from the list by clicking on the blue locus identifier.

 

. 

If the gene has been previously studied, a wealth of information will be available on the next page. Information to include in your paper:

1. Gene locus

2. Other names for the gene:

3. Biological Processes in which the gene plays a role (GO Biological Process)

4. The cellular component in which the protein product is expressed (GO Cellular Component)

5. Growth and developmental stages when the gene is expressed

6. The plant structures where the protein product of the gene is expressed

Take a look at the BAR eFP (The Bio-Analytic Resource for Plant Biology electronic fluorescent pictograph) data. This is a browser engine that “paints” data from genomic data sets, such as microarrays, ont pictographs that repsent the experimental samples used to generat the data set. The purpose of the tool is to help researchers develop testable hypothesis based on the enormous amount of data generated by genomics projects. If you click the Data source you have options you can select that will provide you with information on experimental work others have conducted to study this gene. The informationwill be in a nicely illustrated summary form. The original reference will be included on the page as well.

Another example for the same gene:

 

This is a great place to look for information on your gene to use in your narrative. You should cite the original papers if you use the information in this section. You may need to go back to the original paper for details or clarity.

 

 

 

 

Under the Protein Data section, you will find the following information to include in your paper:

1. Protein Length

2. Molecular weight

3. Isoelectric point

4. List of InterPro domains: Create a table of the domains and their function (if the function is known). Click on the links. This will take you out to the InterPro site where you will find info on the domain. The information in the description might provide some useful information to include in your manuscript. In the table, you should indicate a very BRIEF description of whatever you think is most relevant about this particular domain (think about what your microarray experiment was to help you decide what might be the most useful information to include in the table) and the biological process, molecular function or cellular component that is applicable to the domain (see under GO terms). If no information is available, record “none” in your table. Example:

 

 

Domain Brief Description Biological Process Molecular Function Cellular Component
NAF/FISL_domain: IPR018451 Serine-threonine protein kinase that itneracts with calcineurin B-like calsium sensor proteins Signal transduction None none

 

Table 1. Domain ontology from http://www.ebi.ac.uk/interpro/entry/InterPro/IPR018451/.

 

 

All the way at the bottom of the TAIR page, you will find a list of publications related to the gene. Use these publications as references for your paper.

 

Part 4. Write your microarray paper.

Your microarray paper should contain the following components:

1. Title: The title should contain the species name of the organism (Arabadosis thaliana), your topic of experimentation, and a statement about what you were looking for or what data you were generating.

2. Introduction: Be sure to state the purpose of the study, why the experiment was conducted, review previous works of others in the field (integrated seamlessly, not one reference after another). How a microarray works is not needed here. Assume your reader is familiar with this now long-standing, common-place technique. Focus on your topic (osmotic signaling, sugar signaling, phytohormone signaling, or the interplay between sugar and phytohormone signaling).

3. Results:

a. Report the # of genes upregulated and downregulated by 2-fold or higher.

b. Include a table of top ten most highly genes up-regulated and the top ten most highly down-

regulated genes in your experimental condition compared to to control (use your combined

spreadsheet). Also include any genes that you want to discuss in your discussion section. You

may highlight genes in the discussion that show a change in regulation in your experiment

but didn’t make the top 10. Example:

 

Example:

 

AGI # Affymetrix Probe # Fold change p-value in Student’s T-Test Description
At1g20340 255886_at -4.11044 3.33E-03 Plastocyanin, putative
At1g79040 264092_at -4.02826 6.66E-04 Photosystem II polypeptide, putative
At1g32900 261191_at +3.324657 1.19E-05 Starch synthase, putative

 

 

c. Gene ontology data

 

d. All data collected from Part B about your selected gene for deeper study.

 

e. All figures should be labeled and be accompanied by figure legends. The figure should be

referenced in the text (see figure 1).

 

f. Text (in addition to the figure legends) should be present to inform the reader what you did

and to summarize the results collected. No interpretation of the data is included here. Save

that for the discussion.

 

4. Discussion:

a. Recap you results. Take a look at the descriptions for the genes that are up or down regulated. Now look at the review of literature you selected for homework. Are there genes on the list that you would expect to see based on the literature? Looking at the descriptions, are there genes that make sense to see? If you are looking at sugar, are there genes that are obviously part of sugar metabolic pathways or involved in photosynthesis? If you are looking at phytohormones, do the receptors to your chosen phytohormone appear on the list? You might want to pull up journal articles on some of the genes appearing on the list to explain why they might be appearing on your list. Include a few suggestions for future experiments that could be conducted to expand our understanding of your topic based on your results.

5. References: You should no fewer than 6 journal articles (literature review or primary literature) cited.

6. Appendix: You will upload your Excel spreadsheet separately to the Google Drive. Be sure to drop it in the folder for your TA.

General Information:

· Your paper should be in Times Roman or Calibri font, size 12. Paper margin should be 1 inch. Please double-space the paper. The paper should not contain figures or images from any published work. In order to include previously published images, not only must you cite the source, you must also seek permission from both the original authors and the publisher. Unless you are prepared to submit the documentation for these permissions, do not include figures or images that you did not generate using the TAIR page or create yourself.

· The grading rubric is in Blackboard.

 

References:

Adam, D. (2000). Now for the hard ones. Nature 408, 792-793.

The Arabidopsis Genome Initiative (2000). Analysis of the genome sequence of the flowering plant Arabidopsis thaliana. Nature 408, 796-815.

Bernier, G., Havelange, A., Houssa, c., Petitjean, A., and Lejeune. P. (1993). Physiological signals that induce flowering. Plant Cell. 5, 1147-1155.

Dai, N., Schaffer, A., Petreikov, M., Shahak, Y., Giller, Y., Ratner, K, Levine, A., and Granot, D. (1999). Overexpression of Arabidopsis hexokinase in tomato plants inhibits growth, reduces photo synthesis, and induces rapid senescence. Palnt Cell 11, 1253-1266.

Jang, J.-C., and Sheen, J. (1997). Sugar sensing in higher plants. Trends Plant Sci. 2, 208-214.

Meyerowitz, E.M. (1989). Arabidopsis, a useful weed. Cell 56, 263-269.

Pattison, D. (2004) Characterization of sugar-insensitive mutants and analysis of sugar-regulated gene expression in Arabidopsis thaliana. [Doctoral dissertation, Rice University]. Rice University Graduate Electronic Theses and Dissertations.https://scholarship.rice.edu/handle/1911/18679

Verwoerd, T.C., Dekker, B.M. M., and Hoekema, A. (1989). A small-scale procedure for the rapid isolation of plant RNAs. Nucleic Acids Res. 17, 2362.

Wilson, J. B. (1988). A Review of evidence on the control of shoot: root ration, in relation to models. Annals of Botany. 61 (4) 433-449.

Yu, S.-M. (1999). Cellular and genetic responses of plants to sugar starvation. Plant Physiol. 121, 687-693.

BCHS3201: Microarray Paper

 
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The Aging Brain: Through Many Lives

PBS

At age 95, the poet Stanley Kunitz was named U.S. poet laureate and was still writing new poems and reading to live audiences-an inspiring example of the brain’s vitality in the final years of life. This program presents recent discoveries in neuroscience that tell us how the brain ages, and how that aging process and intact mental functions aren’t mutually exclusive. The film demonstrates that older brains continue producing new neurons and possess unique characteristics that form the basis for wisdom. Alzheimer’s disease is also an important topic. Distributed by PBS Distribution. Part of the series The Secret Life of the Brain. (56 minutes)

The Aging Brain: Through Many Lives

Video Title

The Adult Brain: To Think by Feeling

Video Title

 

The Baby’s Brain: Wider Than the Sky Full Video (54:21)

Segments Transcript

FULL PROGRAM

The Baby’s Brain: Wider Than the Sky

SEGMENTS

  1. Human Brain: Ultimate Machine03:05
  2. Premature Infant Brain02:02
  3. Genetic Code Script01:27
  4. The Primitive Beginning of Thoughts and Feelings01:56
  5. Neuron Pathways02:20
  6. Neuron Migration01:50
  7. Genetic Blueprint03:25
  8. Coping Before the Brain is Ready01:52
  9. Learning Disabilities in Preemies01:33
  10. Shaping the Brain in Unintended Ways02:05
  11. Emulating the Womb03:21
  12. Nature vs. Nurture04:11
  13. Preemie Brain Development02:51
  14. Physical Change in Development of Brain Parameters02:59
  15. Negotiating a Complicated World01:57
  16. Critical Stimulation01:16
  17. Critical Images02:20
  18. Fighting for Cortical Connections03:12
  19. Maturing Without Visual Experience01:45
  20. Removing Cataracts in Time01:43
  21. Plastic Human Brain02:17

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DESCRIPTION 

Only four weeks into human gestation, the brain’s first cells, the neurons, are already forming at an astonishing rate—250,000 every minute. This program illustrates that process and the more complex brain development that occurs during an infant’s life, both before and following birth. Viewers learn how vision and the visual cortex come into play; what happens when a baby is born with visual impairment, such as infant cataracts; and many more facts and insights regarding the early brain’s ability to shape itself in response to the demands of the world. Distributed by PBS Distribution. Part of the series The Secret Life of the Brain. (56 minutes)

Distributed by PBS Distribution.DETAILS Producer: PBSSeries: The Secret Life of the BrainDate Added: 12/12/2009Copyright Date: © 2001Item #: 41054Type: Documentary FilmRun Time: 54:21TAGSAnatomy Biological neural network Biology Brain Human brain Mind NeuropsychologyNeuroscience Neuroscience and intelligence

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The Teenage Brain: A World of Their Own

Video Title

The Child’s Brain: Syllable from Sound

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The Aging Brain: Through Many Lives

Video Title

The Adult Brain: To Think by Feeling

Video Title

 

He Baby’s Brain: Wider Than The Sky Full

 
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Gogo. If Only I Had a System …This will be your opportunity to be the teacher. Click on “View Full Description and attachments” below for the directions and questions. Be sure to open the file that says “MATH110 Read This First” before you jump in!View Full Description and Attachment(s)Start with the attached files. First read the one entitled “READ THIS FIRST” and then open the file called “Systems of Equations Problems with Answers”. It is difficult to learn how to do story problems because there are so many different types. If you want to do well on this week’s test, FOLLOW THESE INSTRUCTIONS! 1) Go through ALL the story problems provided and try to solve them. Pretend it’s a Practice Test. Check your answers with the key provided. 2) Pick ONE of the problems that you got right (that has not already been solved by a classmate), and demonstrate its solution for the rest of us. 3) Study how your classmates solved the problems that you missed. Remember that these may be on the test!

To demonstrate your problem, select Start a New Conversation and make BOTH the problem number and topic (#10 Jarod and the Bunnies) the subject of your post.

Begin your post with a statement of the problem so that we can understand what you are doing.
The answers are at the end of the file, so don’t just give an answer—we can already see what the answers are. Don’t post an explanation unless your answer matches the correct one!

Your goal should be to explain this problem so well that a classmate who “just doesn’t get it” will be able to understand it completely!
This is a moderated forum. Your posting will say PENDING and will not be visible to the rest of the class until I approve it. Occasionally, more than one person will tackle a problem before they can see the work of others. In that case, credit will be given to all posters. Once the solution to a problem has become visible, that problem is off limits and you will need to choose a different problem in order to get credit.
I will indicate in the grading comments if corrections need to be made. If you haven’t received credit, first double-check for my comments in the gradebook. If everything looks OK, then message me asking me to check on it.
You must make the necessary corrections and have your work posted in order to receive credit.
For this particular Forum, no responses are required – your initial post is worth the full 10 points. Should you choose to respond to a classmate, a request for clarification on the procedure used, a suggestion for an alternate method of solving the problem or a general comment about the technique would all be appropriate. I’m sure that a “thank you” for an exceptionally clear explanation would also be welcome!

Please sign ALL your Forum posts with the name that you like to be called – it makes it so much easier for the rest of us to address you by your preferred name when we respond.

Initial Post Due: Tuesday, by 11:55 p.m., ET

Systems+of+Equations+with+Answers.pdfMATH110 Read This First.pdf

Systems of Equations

1) A vendor sells hot dogs and bags of potato chips. A customer buys 4 hot dogs and 5 bags of potato chips for $12.00. Another customer buys 3 hot dogs and 4 bags of potato chips for $9.25. Find the cost of each item.

1)

2) University Theater sold 556 tickets for a play. Tickets cost $22 per adult and $12 per senior citizen. If total receipts were $8492, how many senior citizen tickets were sold?

2)

3) A tour group split into two groups when waiting in line for food at a fast food counter. The first group bought 8 slices of pizza and 4 soft drinks for $36.12. The second group bought 6 slices of pizza and 6 soft drinks for $31.74. How much does one slice of pizza cost?

3)

4) Tina Thompson scored 34 points in a recent basketball game without making any 3-point shots. She scored 23 times, making several free

throws worth 1 point each and several field goals worth two points each. How many free throws did she make? How many 2-point field goals did

she make?

4)

5) Julio has found that his new car gets 36 miles per gallon on the highway and 31 miles per gallon in the city. He recently drove 397 miles on 12 gallons of gasoline. How many miles did he drive on the highway? How many miles did he drive in the city?

5)

6) A textile company has specific dyeing and drying times for its different cloths. A roll of Cloth A requires 65 minutes of dyeing time and 50 minutes of drying time. A roll of Cloth B requires 55 minutes of dyeing time and 30 minutes of drying time. The production division allocates 2440 minutes of dyeing time and 1680 minutes of drying time for the week. How many rolls of each cloth can be dyed and dried?

6)

7) A bank teller has 54 $5 and $20 bills in her cash drawer. The value of the bills is $780. How many $5 bills are there?

7)

8) Jamil always throws loose change into a pencil holder on his desk and takes it out every two weeks. This time it is all nickels and dimes. There are 2 times as many dimes as nickels, and the value of the dimes is $1.65 more than the value of the nickels. How many nickels and dimes does Jamil have?

8)

9) A flat rectangular piece of aluminum has a perimeter of 60 inches. The length is 14 inches longer than the width. Find the width.

9)

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10) Jarod is having a problem with rabbits getting into his vegetable garden, so he decides to fence it in. The length of the garden is 8 feet more than 3 times the width. He needs 64 feet of fencing to do the job. Find the length and width of the garden.

10)

11) Two angles are supplementary if the sum of their measures is 180°. The measure of the first angle is 18° less than two times the second angle. Find the measure of each angle.

11)

12) The three angles in a triangle always add up to 180°. If one angle in a triangle is 72° and the second is 2 times the third, what are the three angles?

12)

13) An isosceles triangle is one in which two of the sides are congruent. The perimeter of an isosceles triangle is 21 mm. If the length of the congruent sides is 3 times the length of the third side, find the dimensions of the triangle.

13)

14) A chemist needs 130 milliliters of a 57% solution but has only 33% and 85% solutions available. Find how many milliliters of each that should be mixed to get the desired solution.

14)

15) Two lines that are not parallel are shown. Suppose that the measure of angle 1 is (3x + 2y)°, the measure of angle 2 is 9y°, and the measure of

angle 3 is (x + y)°. Find x and y.

15)

16) The manager of a bulk foods establishment sells a trail mix for $8 per pound and premium cashews for $15 per pound. The manager wishes to make a 35-pound trail mix-cashew mixture that will sell for $14 per

pound. How many pounds of each should be used?

16)

17) A college student earned $7300 during summer vacation working as a waiter in a popular restaurant. The student invested part of the money at 7% and the rest at 6%. If the student received a total of $458 in interest at the end of the year, how much was invested at 7%?

17)

2

 

 

18) A retired couple has $160,000 to invest to obtain annual income. They want some of it invested in safe Certificates of Deposit yielding 6%. The rest they want to invest in AA bonds yielding 11% per year. How much should they invest in each to realize exactly $15,600 per year?

18)

19) A certain aircraft can fly 1330 miles with the wind in 5 hours and travel the same distance against the wind in 7 hours. What is the speed of the wind?

19)

20) Julie and Eric row their boat (at a constant speed) 40 miles downstream for 4 hours, helped by the current. Rowing at the same rate, the trip back against the current takes 10 hours. Find the rate of the current.

20)

21) Khang and Hector live 88 miles apart in southeastern Missouri. They decide to bicycle towards each other and meet somewhere in between. Hector’s rate of speed is 60% of Khang’s. They start out at the same time and meet 5 hours later. Find Hector’s rate of speed.

21)

22) Devon purchased tickets to an air show for 9 adults and 2 children. The total cost was $252. The cost of a child’s ticket was $6 less than the cost of an adult’s ticket. Find the price of an adult’s ticket and a child’s ticket.

22)

23) On a buying trip in Los Angeles, Rosaria Perez ordered 120 pieces of jewelry: a number of bracelets at $8 each and a number of necklaces at $11 each. She wrote a check for $1140 to pay for the order. How many bracelets and how many necklaces did Rosaria purchase?

23)

24) Natasha rides her bike (at a constant speed) for 4 hours, helped by a wind of 3 miles per hour. Pedaling at the same rate, the trip back against the wind takes 10 hours. Find find the total round trip distance she traveled.

24)

25) A barge takes 4 hours to move (at a constant rate) downstream for 40 miles, helped by a current of 3 miles per hour. If the barge’s engines are set at the same pace, find the time of its return trip against the current.

25)

26) Doreen and Irena plan to leave their houses at the same time, roller blade towards each other, and meet for lunch after 2 hours on the road. Doreen can maintain a speed of 2 miles per hour, which is 40% of Irena’s speed. If they meet exactly as planned, what is the distance between their houses?

26)

3

 

 

27) Dmitri needs 7 liters of a 36% solution of sulfuric acid for a research project in molecular biology. He has two supplies of sulfuric acid solution: one is an unlimited supply of the 56% solution and the other an unlimited supply of the 21% solution. How many liters of each solution should Dmitri use?

27)

28) Chandra has 2 liters of a 30% solution of sodium hydroxide in a container. What is the amount and concentration of sodium hydroxide solution she must add to this in order to end up with 6 liters of 46% solution?

28)

29) Jimmy is a partner in an Internet-based coffee supplier. The company

offers gourmet coffee beans for $12 per pound and regular coffee beans for $6 per pound. Jimmy is creating a medium-price product that will

sell for $8 per pound. The first thing to go into the mixing bin was 10 pounds of the gourmet beans. How many pounds of the less expensive regular beans should be added?

29)

30) During the 1998-1999 Little League season, the Tigers played 57 games.

They lost 21 more games than they won. How many games did they win that season?

30)

31) The perimeter of a rectangle is 48 m. If the width were doubled and the length were increased by 24 m, the perimeter would be 112 m. What are the length and width of the rectangle?

31)

32) The perimeter of a triangle is 46 cm. The triangle is isosceles now, but if its base were lengthened by 4 cm and each leg were shortened by 7 cm, it would be equilateral. Find the length of the base of the original triangle.

32)

33) The side of an equilateral triangle is 8 inches shorter than the side of a square. The perimeter of the square is 46 inches more than the perimeter of the triangle. Find the length of a side of the square.

33)

34) The side of an equilateral triangle is 2 inches shorter than the side of a square. The perimeter of the square is 30 inches more than the perimeter of the triangle. Find the length of a side of the triangle.

34)

4

 

 

Answer Key Testname: SYSTEMS_OF_EQUATIONS

1) $1.75 for a hot dog; $1.00 for a bag of potato chips 2) 374 senior citizen tickets 3) $3.74 per slice of pizza 4) 12 free throws, 11 field goals 5) 180 miles on the highway, 217 miles in the city 6) 24 rolls of Cloth A, 16 rolls of Cloth B 7) 20 $5 bills 8) 11 nickels and 22 dimes 9) 8 inches

10) length: 26 feet; width: 6 feet 11) first angle = 114°

second angle = 66°

12) 72°, 72°, 36° 13) 3 mm, 9 mm, 9 mm 14) 70 mL of 33%; 60 mL of 85%

15) x = 288 7

, y = 36 7

16) 5 pounds of trail mix 30 pounds of cashews

17) $2000 18) $120,000 at 11% and $40,000 at 6% 19) 38 mph 20) 3 mph 21) 6.6 mph 22) adult’s ticket: $24; child’s ticket: $18 23) 60 bracelets and 60 necklaces 24) 80 mi 25) 10 hr 26) 14 mi 27) 56% solution: 3 L; 21% solution: 4 L 28) 4 L of 54% solution 29) 20 lb 30) 18 games 31) Length: 16 m; width: 8 m 32) 8 cm 33) 22 inches 34) 22 inches

5

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