Drafts

- you can present your data in a photograph, draing, diagram or graph (most common)
- line graphs are the most common types of graphs used in science
- don't make it too compact and don't leave too much white space either
- 3-4 curves should be the max, especially if the curves cross each other
- when lines do cross, it would be best to distinguish each line by thickness or different patterns
- bar graphs are different lengths to display comparative values
- use vertical rather than horizontal bars
- use bar graphs instead of line graphs for discrete data or when findings can be divided and compared in different ways
- scatter plots are similar to line graphs except the dots are not connected by lines
- instead a best-fit line is drawn to show how the two variables are related to each other, can be curved or linear
- data points can overlap which is fine because you are mostly looking for the relationship/correlation between the 2 variables
- place the independent variable on the x-axis and the dependent variable on the y-axis
- if you are req'd to write a title for your paper, the best thing to do is describe what is graphed in terms of y axis versus x axis
- the figure legend should be a description of the figure content
- the legend should contain: title, description of contents and explanations of symbols and abbreviations( (pg. 70)
- figures w/ only figure titles don't usually appear in scientific writing except for on posters and slides

            Last year, the Zika virus was struck fear into soon-to-be parents. This virus affected those who were pregnant, however the main problems arose with the babies that the mothers gave birth to. The newborns would have major birth defects including partially collapsed skull, damage to eye, limited joint movement, brain damage and most importantly, decrease in brain size. However, researches have further developed a study in which this virus can actually be used to suppress or even treat deadly brain cancers. In a study, scientists infected human and mice cells with the Zika virus. In both cells, the virus killed stem cells as thought, however the ones that were killed were ones that would go on to become an aggressive type of brain tumor, the highlight was that it left the healthy cells unharmed. The virus did not infect normal brain tissue, with this, they conducted more research, infecting mice with cancer and observing. Half of the mice infected with cancer were treated with the virus and the other left untreated. The mice who were treated with the virus had tumors that either shrank or grew at a slower rate, therefore living longer, half of them living over six weeks, compared to those untreated who died within two weeks. Further development of this research could bring viable and effective treatment plans to those who are infected with certain brain cancers, however more research is definitely needed to find the effects of this potential treatment option.  

In addition to teaching and directing programs, Dr. Peterson has also published papers during her career. One paper that is particularly interesting is called Novel progesterone receptors: neural localization and possible functions. In this paper, she described research her lab conducted on rat forebrains. Their main purpose was to discover which receptors were most prominent in the brain, in an effort to decide which receptor she should focus to paper on. In order to do this, they used in-situ hybridization to map genes encoding receptors and their binding partners inside the rat’s forebrain. The findings are displayed with images of the x-ray film autoradiograms. Their information indicated that mPR (membrane progestin receptor) was not expressed significantly in the neuroendocrine area of the brain. On the other hand, PGRMC1, PGRMC2 and SERBP1 were expressed much more, and they were found in the hippocampus, cortical, and cerebral regions where functions controlled by progesterone happen. PGRMC stands for progesterone receptor membrane component, and SERBP is plasminogen activator inhibitor 1 RNA-binding protein. Ultimately, it was discovered that PGRMC1 was the most abundantly expressed gene in the results, so that is what they focused on in the review.

- decide how you want to present your data, in the text or in an illustration
- if your data is listed in words then its best to present it in a couple of sentences in your results section
- present data in graphs when you want to reveal some kind of trend or correlation
- if you want to give precise numbers then its important to prepare tables rather than graphs
- look for patterns in order to create the most useful table
- usually independent values go on the right and depend values go on the left
- it is best to use a graph when you want to stress the importance of standard error or deviation
- tables present data more precisely than a graph but don't usually clearly show trends within your data
- tables are a good way to present facts
- for a graph, it is trend that is more important than exact numbers
- design figures and tables by keeping the reader in mind in order to have a strong impact
- figures and tables must be able to stand on their own
- not all data needs to be described in the text, just emphasize your key findings and use tables and figures to back up conclusions you've made
- figures and legends need to be independent of the text, meaning the reader must be able to understand what is being portrayed by reading the title and the legend without searching the text for an explanation
- place info where you would want/expect the reader to find it
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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. 

The United States’ healthcare system was first implemented by several powerful industries that likely saw the american public as a source of profit rather than a populace that deserved affordable, high quality care. This conglomerate, composed of the various insurance and pharmaceutical companies, have continually opposed the transition to a national health care system as they have profited tremendously from the sale of high-cost pharmaceuticals as well as the annual rise of both premiums and deductibles. Furthermore, while not a direct oppositional force, the Government would likely not provide universal health care without some form of tax reform to compensate as the increasing rate of diseases such as obesity and diabetes will likely lead to increasing cost.  Similarly, physicians and employers may also appear apprehensive as health care providers have been concerned with loss of autonomy and some nations, such a Germany, require employers to pay a percentage of the taxes that ultimately fund their national health care system. The implantation of a single payer system would likely benefit the average american citizen, particularly those of lower average income, minorities and children, however, a single-payer plan continues to be misrepresented as a socialist movement and is therefore seen as a direct threat to a capitalist nation.The various parties involved have different perspectives, opinions and concerns regarding to the healthcare system used and these feelings are not all exclusively to ensure efficacy and affordability.  

Throughout the course of the United State’s history the foundation of human rights has continually shifted and expanded. At first, the focus was on human rights for those of certain races or gender and over time the focus of these progressive movements has shifted to more specific issues, such as health care. the concepts of affordable universal health care as a human right as well as a single-payer healthcare system have risen in popularity amidst the rises expenses and conversely deteriorating levels of care. In its present state, health care in the United States is covered by both public insurance programs, such as Medicare or Medicaid, as well as private insurance companies that are typically granted through one’s employer or directly purchased. Following the mounting pressure from the american public as well as several democratic government employees, the affordable care act (ACA) was passed in 2014 which attempted to decrease the amount of uninsured or underinsured citizens. This was the United State’s first step towards a system that began to resemble a single-payer system or national health insurance system where a centralized government system provides universal healthcare that is then performed by private practices.  Galae’s article describes the current socio-economic implications of this change, particularly in regards to a single-payer system. Galea provides an assessment of the political landscape by identifying the opposing parties and their concerns before countering these claims using the concept of a single-payer system and the nations that have already implemented this system.

I took Statistics 240 during Fall 2016 in my sophomore year of college at University of Massachusetts, Amherst. I remember only a minimal amount of material from the course since I took it almost three semesters ago. I do remember the main topics such as standard deviation, standard error, variance, probability, and a few other her topics. As a biology major, I have encounters chi squared which is often used with experiments that have observed values and expected values. In Statistic 240, I learned about standard deviation and how if you square the value then you get variance. I also learned about probability and how probabilities can be added or multiplied in certain scenarios. Although there are things I remember, I would need to refer back to my old notes to remember fully how to use the equations and figure out certain problems.

Along with discovering new genes, the experiment also identified Shh affecting transcription of other already known genes. These genes were divided into categories of positively regulated and negatively regulated. Multiple genes in each category were grouped together based off of common effects on development. One group of genes found to be positively regulated by Shh was follistatin and follistatin-like2. These genes are known to work on the Bone Morphogenic Protein (BMP) pathway. The fact that increased levels of Shh also increase the levels of these two proteins provides a link between Shh and BMP. It had been previously shown that BMP signalling had an effect on Hh signalling, but this experiment is the first evidence of Shh regulating follistatin. Other groups of genes were found which suggest Hh plays a role in development of different neural areas in the brain, modify expression in specific locations, and interact with other signalling pathways such as the iroquois (irx) genes.