Writing in Biology

The last time I took a Statistics course in college was back in freshman year during my second semester of college. I vaguely remember many different concepts that were discussed in class but I would not be able to solve a bunch of different statistics problems. However there have been concepts that have come up again and again in classes that I have taken since my freshman year. An example of this would be chi square problems which seem to be very popular in biology. Chi square problems are done in order to be able to reject or not reject a hypothesis. Observed values are give and expected values are found. The way the problems work is that observed is minus expected and the value that is found is then squared and divided by the expected value. This is done for every single observed value and all of these are added together. The number at the end is then compared to the number found under the degrees of freedom and comparing the two numbers tells you whether or not we accept or reject the hypothesis. Another common thing in physics is standard deviation which is also common in biology. This just tells you the amount of variation that there is in a group as a whole. A low standard deviation tells you that the numbers are pretty close to the average while a high standard deviation tells you that the numbers are spread apart. I also remember doing something involving p values as well as doing combinations. These combinations could be solved by nCr. These are just some of the things I remember from statistics.

After performing agarose gel electrophoresis on DNA samples, the samples treated with RNase were easily distinguishable. Samples treated with RNase displayed a single band of DNA, while untreated samples displayed the same band along with a smear where the much smaller RNA strands were deposited. From this I concluded that the RNase successfully eliminated the RNA contained within the extraction samples.

For the sample treated with RNase, the ratio of the absorbance at 260 nm to the absorbance at 280 nm was 1.26, which is significantly lower than the 1.8 ratio that indicates pure DNA.  From this I concluded that the DNA extraction product was contaminated. The untreated sample had a higher ratio of 2.08, indicating that the DNA was contaminated with RNA, which has a larger ratio than pure DNA.

Additionally, the concentration of the RNase treated DNA was 0.2590 µg/µL. Because the final volume of the extraction was 50 µL, I calculated that 12.95 µg of DNA extracted. The concentration of the untreated DNA was 200.7 ng/µL, which was unexpectedly low since we would expect the nucleic acid concentration to be higher before RNA is eliminated.

The epithelial to mesenchymal transition (EMT) allows cancer cells to begin the process of metastasis by unadhering to one tissue and migrating to another location. A major characteristic of this process is the loss of e-cadherin, which can result from the expression of multiple transcription factors including SNAIL, ZEB, and KLF8. EMT can also be induced by certain growth factor pathways as well as TGF beta and hypoxia. The researchers aim to target these transcription factors and signaling pathways as well as the hypoxic tumor microenvironment in order to prevent metastasis from occurring. If cancerous cells are unable to carry out EMT, the effects of metastasis should lessen. Subsequently, apoptosis-inducing therapy can be delivered to these now stationary cells. A region of interest for the researchers is aptamer-regulated exosomal therapy, where aptamers can serve as binding partners for these transcription factors and elements in these signaling pathways. This binding can inhibit the downstream effects, such as the induction of EMT. A cell suicide gene or cytokine such as TRAIL may also be incorporated into the interior of the exosome for targeted delivery.  

The last time I took Statistics was freshmen year of college which seems like it was a really long time ago. There are a lot of things I vaguely remember from the class but most of the things I remember are due to the fact that they still play a major role in classes that I have taken that are science related. Such as in classes involving genetics chi square problems can be super popular in order to help identify whether or not a hypothesis can be rejected. For chi square problems I know we get an observed value that is given to us and an expected value is one that we must find on our own. We do observed minus expected and square that value and divide it by the expected in order to come to a value. We do this for every observed value and add up all of these values we compare the number that we get to the number given to us by the degrees of freedom and that tells us whether or not we can accept a hypothesis. In physics classes that I have taken in college we have discussed standard deviation which is something that comes up in statistics. I also vaguely remember t-tests and the graph that has to do with confidence and p-values. Also I remember having to figure out the probability of something happening a different number of times with different combinations.

Our gut feeling told us that switching would bring better chances of winning the Hershey kiss, but if we switched and then got it wrong (while our original answer was correct) we would have felt frustrated, since probability says there are better chances of winning because of the switch. If we had stayed and gotten our original choice wrong, I think we would have felt better than switching and getting it wrong. Although staying would decrease the odds of winning, sometimes you want to trust your gut and original pick. Even though switching would bring better odds of winning, if you think you chose correctly the first time it might be hard to switch to the other one.We selected a cup, then were shown a cup which didn’t contain the candy, and we switched our guess to the other cup. 7 times out of 10 the cup we switched to contained the candy. We won the game 7 times. Our winning probability is .7 or 70%. We are not surprised by these results since the probability of winning when a switch is made is higher than the probability of winning when choosing to stay with the original choice. It makes sense that the mean of winning is higher when switching.

If calcium affects the actions of contractile proteins and intracellular signaling proteins involved in phagocytosis, which allows cillia to contract faster, then adding higher concentrations of calcium should lead to increased numbers of vacuoles in the Tetrahymena cells. Figure 3 and Figure 4 from the “Pseudopterosin A inhibits phagocytosis and alters intracellular calcium turnover in a pertussis toxin sensitive site in Tetrahymena thermophila” paper on Moodle. Figure 3 shows that the higher the calcium concentration, the higher the incidence of phagocytosis. In Figure 4, we see that the control group has a lower level of phagocytosis than does the group given the calcium. Both these figures suggest that our hypothesis is correct since in our hypothesis, we state that the calcium should lead to more phagocytosis and vacuoles. If our hypothesis is correct an increase in the number of vacuoles will occur with the higher concentration of calcium. Record the number of vacuoles in ten different cells with different calcium concentrations. We will compare the amount of vacuoles in the cells with different calcium concentrations to the control by looking at the standard deviation and mean.

We chose up and right to be the positive direction. The intial position of the ball is 0.3m. The inital velocity is 0 because it is not in motion yet so it does not have a velocity. The initial force of the ball is 0.1568 N because the force is mass times acceleration. The initial acceleration of the ball is -9.8 m/s2 because that is the force of gravity. It is negative because we chose down to be negative and the ball is moving down. The force and acceleration stay the same because they are constants. Force is 0.1568N and acceleration is -9.8 m/s2..The velocity at 0.01 seconds is -0.098 because final velocity is initial velocity plus acceleration times the change in seconds.     The position of the ball after 0.01 seconds is 0.3 because final position is initial position plus velocity times the change in time. The condition for the ball hitting the table is the acceleration and force change because gravity is no longer causing a change in either. The ball hits the table at 0.25 and 0.26 seconds. When time equals 0 then force equals 0 since there is no force acting on it in the horizontal direction.

The class methatheria is made up of marsupials these marsupials have the placenta get their nourishment from yolk. Their young is altricial meaning that they are incapable of moving around on their own soon after bring born. They have a short gestation and a long lacatopn period for their young. A good way to differentiate them from eutherians is by looking at their premolars and molars. Metatherians have three premolars and 4 molars. Eutherians were found as early as the cretaceous for their fossils they have a chorioallantoic placenta. As for their prmolars and molars they have 4 premolars and three molars. Eutherians have more morphological diversity compared to the metatherians. They have a greater range in body size, more complex social behavior, and precocial young. This means their young is pretty well developed to survive outside the womb. They also have higher taxanomic diversity, relatively bigger brains, and higher metabollic rates. They also have a higher investment in gestation instead of lactation. Which means there is faster postnatal growth.

The omentum is a sheet of adipose tissue that surrounds the digestive organs.  It is a common site of ovarian cancer metastasis. There are two ways in which ovarian cancer is known to metastasize.  The first is passive dissemination.  In this model, cancer cells detach from the tumor and are transported by the peritoneal fluid and ascites to their metastatic site.  Ascite formation occurs due to VEGF signaling and blocking of lymphatic vessels.  Cancer cells adhere to their metastatic site using matrix metalloproteinase (MMP), which is upregulated in cancer cells.  MMP, along with other proteins, is also responsible for enhanced cell motility.  The tumor cells then release cytokines such as interleukins to cause angiogenesis and a preferential microenvironment.  The second model is hematogenous metastasis.  Cancer cells undergo intravasation at the primary tumor site and extravasation at a distance metastatic site.  The cancer cells target their metastatic site using cancer associated fibroblasts (CAFs).  CAFs at the primary tumor site secrete proteins that upregulate pathways that promote cell motility in ovarian cancer cells.  At the metastatic site, adipocytes and macrophages form a favorable tumor microenvironment.

Yeung TL, Leung CS, Yip KP, Au Yeung CL, Wong ST, Mok SC. Cellular and molecular processes in ovarian cancer metastasis. A Review in the Theme: Cell and Molecular Processes in Cancer Metastasis. Am J Physiol Cell Physiol. 2015;309(7):C444-56.