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Identity and purity were assessed. Analyzation methods of the products obtained included Gas Chromatography and IR spectroscopy. When obtaining the IR analysis, it illustrated the bonds contained in the product obtained. There is a singlet peak present in the IR analysis at around 1450 cm^-1. This indicates the double bond between two carbons. The significant peak signified at the 3000 cm^-1 may indicate an impurity which may be due to the presence of water. In addition, there is a quadruplet present at around 1600 cm ^-1. The gas chromatography illustrated that 100% of the area fell under one peak indicating that the product was made up of only cyclohexene and had a retention rate of 0.058. It also indicates in the gas chromatography that the total area is 9596.

During this experiment, cyclohexanol reacted with phosphoric acid under high temperature to perform the acid catalyst dehydration reaction and produced the target product of cyclohexene which was obtained in a 18.87% yield. The percent yield of 18.87% indicates 81.13% of the original amount was lost. A gas chromatography and infrared analysis readings were taken which illustrated data regarding retentions and peaks. In addition, two chemical tests were performed in a 3% solution of bromine in dichloromethane and 1% potassium permanganate and 10% sulfuric acid. These were known as the bromine in dichloromethane and potassium permanganate chemical tests. When performing the bromine in dichloromethane test for alkenes, the cyclohexene solution started out as clear and colorless and remained clear after the addition of bromine while cyclohexane started out as clear and colorless and turned to a color known as reddish-orange instantly when swirled. For the 1% potassium permanganate and 10% sulfuric acid test for alkenes, cyclohexane started out as a clear color and then turned into a brown precipitate. The cyclohexane started out as clear and converted into purple after the addition of KMnO₄. 

The data presented to us was from Karakuri. This data illustrates individuals gender, GPA, Hours studied, and Hours slept per week. To find the correlation between two things like gender vs GPA it could be depicted in a bar graph. Another type of correlation would be between hours studied versus GPA's. After analyzing a portion of the data presented it could be seen that males or females who studied more had a higher GPA, however, there were outliers present. In addition, these individuals also had a lower number of hours slept. 

There was also the discussion of using a silibinin which inhibits non-small cell lung cancer metastasis by targeting a pathway known as the EGFR/LOX pathway. When LOX is inhibited it could lead to a collagen cross-linking deficiency, however, when upregulated can promote metastasis of existing tumors.  It permits for cancer cells to move and inhabit a new environment. This means we could draw out attention to LOX and its role in lung adenocarcinoma patients. The drug silibinin and EGFR inhibitor was able to inhibit NSLC cell migration and decrease tumor metastasis through a EGFR/LOX dependent manner. From the journal article, “Silibinin Inhibits NSCLC Metastasis by Targeting the EGFR/LOX Pathway,” LOX is controlled by HIF-1α under a state of deprived oxygen and is prompted by TGF-β in cancer cells

Essentially, this is performed via the TRIF and RIP1 dependent mechanisms. This involves the recruitment DD containing adaptor protein FADD through the interaction of DD. FADD through DED (death effector domain) is able to interact with procaspase-8. When activated is then believed to initiate cell death. The activation of TLR3 in lung epithelial cells is involved in promoting neutrophil recruitment in the pre-metastatic lung. Neutrophils in the tumor-bearing host can change their polarization resulting in the alteration of rather than suppressing they will be promoting tumor metastasis. 

Although we have not yet looked at a direct target or method of treatment to prevent the cancer cells from migrating to other parts there are useful articles that have served as templates. In the article titled, “Tumor Exosomal RNAs Promote Lung Pre-Metastatic Niche Formation by Activating Alveolar Epithelial TLR3 to Recruit Neutrophils,” it discusses how lung epithelial cells are key for starting neutrophil recruitment and lung metastatic niche formation. This is done so by sensing tumor exosomal RNA through TLR3. TLR3 stands for toll like receptor 3. TLR3 is a nucleotide-sensing TLR and it is activated by double-stranded RNA, this means there is a viral infection. It plays a role in adaptive immunity and pathogen recognition. The TLR3 pathway is activated when there is exposure to cigarettes, viruses, or other pathogens. After performing some research on the TLR pathways it has also been known to be involved in apoptosis. 

From project one we learned that lung adenocarcinoma is a type of cancer that could lead to be metastatic. This occurs when lung cancer cells break away from a tumor and travel to other parts of the body through the blood or lymph system. The central idea is that the cancer cells are now thriving in a new place and multiplying. It is affecting other organs that are near the site of where the cancer was first found and formed. Some of the sites known to be affected by lung cancer is the liver, bone, brain, and other organs. Our route and plan of treatment has not yet been established however, we have been doing research on sime areas to explore and look into. So far out team has found a variety of sites that give us insights in what way to take our project. 

 I took Statistics 240 course with Joanna Jeneralczuk during the fall 2017 semester. Throughout this course I learned about the basics of probability, binomial and normal distributions, Central Limit Theorem, simple linear regression, sampling distribution of the population mean and proportion, how to use the Z and T table, and etc. At the end of this course the core objective was to learn how to analyze data and draw inferences. In addition, to know how to present data graphically and interpret them. As well as recognize whether reported results correlate with the study and analysis conducted. From this course, a key component that was helpful in my other courses was probability since it also became useful in my genetics course. It is a key idea because probability is a component that comes up a lot throughout the biology courses I have taken. It is a topic that is also relevant in our lives. For genetics we had to determine the probability that out of three children one will come out with blue eyes given the parents genotype. 

During the fall 2017 semester I took Statistics 240 course with Joanna Jeneralczuk. Throughout this course I learned about the basics of probability, binomial and normal distributions, Central Limit Theorem, simple linear regression, sampling distribution of the population mean and proportion, how to use the Z and T table, and etc. At the end of this course the core objective was to learn how to analyze data and draw inferences. In addition, to know how to present data graphically and interpret as well as recognize whether reported results correlate with the study and analysis conducted. From this course, a key component that was helpful in my other courses was probability since it also became useful in my genetics course. At the end of the course we had to form groups and perform studies and use our statistical analysis skills to carry out correlations between variables. 

Our primary focus was to study and survey students attending a four-year college or university. Our sample was random, and we compared majors as well. We asked what kind of major they take, how many credits are required to graduate, and a minimum cost of money that goes into one semester only. The date we collected was illustrated in a histogram give a visual representation of our results and what they mean. A scatterplot was also created to demonstrate whether there is a relationship between the two variables and how they affect one another. It helped us interpret and visually see if college expenses increase as an individual enrolls in more credits in one semester.