Distances are Distressingly Difficult: The Key is Variability

Welcome to the world of Observational Astronomy at Gettysburg College, population: 3, Dr Milingo, Autumn Tripet, and Braden Wolf. Autumn is a rising senior Physics major, and Braden is a rising sophomore Physics and Theatre double major. Throughout out summer here on campus, we have been working on a project determining distances to RR Lyrae stars. We are part of a larger international group established and administered by Dr Michael Fitzgerald at edit Cowan University in Australia. RR Lyrae stars are variable stars that oscillate in brightness over a period of less than 1 day. By observing their period of variability, we can ultimately determine their distance through the Period-Luminosity relationship. Autumn started this project last summer through the pandemic, working remotely from her home with weekly zoom calls with Dr Milingo. We’re continuing that work this summer, now with Braden as a team member.

Figure 1: The lab group- From left to right, Braden, Dr Milingo, and Autumn

Why do we care about these stars? Because distances to astronomical objects are really hard to figure out. A given star could be really luminous and far away and hence appear faint, or not very luminous but relatively close and appear bright. In order to find the distance to an object in the night sky, there are a few methods astronomers use. For objects close to earth, we can take what’s called a parallax measurement, which is taking a pair of images of the object ~6 months apart, measuring the apparent shift in position with respect to more distant background stars, and then using trigonometry to find the distance. However, the parallax method only works for relatively nearby objects. As the distance between the observer and star grows, the apparent shift gets smaller and the uncertainty in the measurement gets bigger. Another method to determine distance involves knowing both the apparent magnitude and the absolute magnitude of the object. Apparent magnitude is how much light reaches the earth from a given object, while absolute magnitude is how much light the object is actually putting out. Using these two quantities, we can calculate how far away an object is, because there is a relationship between the absolute magnitude, the apparent magnitude, and the distance.

We started our project by picking RR Lyrae stars that have known distances through the parallax method. We then used the Los Cumbres Observatory (LCO), a global network of telescopes, to get images of our target stars. All of these images were acquired last summer, or in the Fall of 2019. We acquired images of these stars in 4 filters: B, V, i, and z. These filters allow us to see the brightness of the star indifferent wavelength bands. The i & z filters are what we are most interested in because not a lot of research has been published for RR Lyrae stars in these filters.

Figure 2: Starfield showing HI Draconis (HI Dra), one of the stars Autumn is working on. The star is the one in the centre of the image, surrounded by the purple lines. This image is taken from the Aladin Sky Atlas software, using a different survey in the visible spectrum
Figure 3: The “Fitz” file, showing an image taken of SW Aquarii (SW Aqr), the star Braden is working on during the summer. This is the type of image we get from the telescope network, in a way that is understandable to the human eye. We will go through these to make sure that the image has clear sky, and to check details of the image exposure.

After getting these images from LCO, we went through them to dispose of any cloudy frames (e.g. any frames where the star is not visible due to weather or so dim that the brightness measurement is highly uncertain). We received files that contain the photometry for these stars, which include measurements of the brightness of our target and calibration stars in the field. Then we used a set of python scripts written by Dr. Fitzgerald to produce light curves and determine variability periods for each of the filters. A light curve is a plot of brightness vs. time. The following graphs show typical light curves produced from the scripts.

Figure 4: This is the light curve before calibration for HI Dra in the i filter, as computed by Autumn
Figure 5: This is the calibrated light curve for the z filter for SW Aqr, created by Braden

Along with the light curves, we also receive output files from the python scripts that give us calibrated apparent magnitudes. It is with these that we find the apparent magnitude of our target star, which is obtained by finding the middle magnitude value from the light curve (imagine a horizontal line slicing through the centre of the light curve above). The absolute magnitude is found from the period of the light curves (the absolute magnitude does not change, this is related to the intrinsic luminosity of the star no matter how far away it is) using the Period-Luminosity relationship for RR Lyrae stars. We’re using published period-luminosity functions from Catelan et al 2004 and Cáceres & Catelan 2008. We can find the distance using the distance modulus, written

Where ‘m’ is the apparent magnitude, ‘M’ is the absolute magnitude, and ‘d’ is the distance.

Finally, we compared the photometric distances we found to the published distances in the Gaia Data Release catalogues (ESA 2020). The Gaia satellite uses the parallax method for obtaining distances, so our work contributes to the data used to inform RR Lyrae period-luminosity functions in different observational filters. Comparing our photometric distances to Gaia’s parallax distances gives us two independent measurements of the same distance.

Figure 6: This plot compares the GAIA distance estimations to the photometric distance estimations for SW Aqr in each filter, with error bars. The actual values are in there table above the plot. Also shown is the average of the photometric distance estimations, in the right-most column.
Figure 7: Distance estimations to HI Dra in each filter, also shown with the GAIA distance estimations.


Cáceres, C., & Catelan, M. (2008). The period-luminosity relation of RR Lyrae stars in the SDSS photometric system. The Astrophysical Journal Supplement Series, 179(1), 242.

Catelan, M., Pritzl, B. J., & Smith, H. A. (2004). The RR Lyrae period-luminosity relation. I. Theoretical calibration. The Astrophysical Journal Supplement Series, 154(2), 633.

European Space Agency. (2020). Gaia Early Data Release 3 (Gaia EDR3). Cosmos. https://www.cosmos.esa.int/web/gaia/earlydr3.

Shake it ‘till you make it

Hello from the Caldwell lab! The Caldwell lab is an animal behavior lab focused on vibrational communication. We know that many animals, like frogs, birds, and crickets, produce calls to communicate, but we often only think of one component to these calls – the sounds they make. However, the act of calling also creates vibrations which can leave the signalling animal’s body and travel through branches or the ground on which that animal is perched. In this way, a call can function through two, parallel, information channels, one through the air and one through solid surfaces. For example, previous work from the Caldwell lab has found that calling red eyed treefrogs transmit vibrations throughout the vegetation they call from, and that other frogs respond to both the sound and vibrations produced by these calls. This sort of bimodal acoustic signaling brings a new and exciting perspective to our understanding of animal communication. How might animals use the information provided by call vibrations in ways we’ve never investigated? 

While summer research in years past have been centered around field research in the tropical forests of Panama, this has been the lab’s first summer here in Gettysburg, allowing us to focus on establishing projects that can be continued here throughout the year. This summer we are conducting two studies that investigate the function of bimodal acoustic calls.

Caldwell lab, from left to right: Julianna (’23), Professor Caldwell, and Aidan (’21)

Propagation of signals along a plant:

One of the projects being worked on is studying the propagation of signals along a plant. Imagine a frog calling at some position along a branch. Both sound and vibration from these calls will travel along the branch to reach other frogs, but as they travel they will be altered by the environment. Their amplitude, temporal properties, and frequency content will all change. In order to better understand how animals use bimodal acoustic signals, we are measuring how their sound and vibration components change as they propagate. This is due to the sounds and vibrations being filtered by the environment in different ways. For example, sound tends to get quieter the further you get from the source, but that’s not always true for vibrations in a plant. We will also consider the role of leaves in the propagation of bimodal acoustic signals, as they may allow a pathway for energy to travel into and out of the plant.
   Our general method is to play a series of synthetic and natural sound and vibration stimuli and to re-record these at regular 10 cm intervals along the branch. We use an electrodynamic shaker to produce vibrations and accelerometers to measure the vibrations as they travel along the branch. Similarly we use a speaker and probe microphone to measure the propagation of sound. We then remove leaves from the branch and repeat the process. This study will give insight into how sound and vibration interact during communication and will reveal some of the selective pressures that shape the evolution of bimodal acoustic calls.

Stimulus being played on and near plant that is recorded with accelerometers and probe microphone

Bimodal acoustic calls in purple martins:

Another project just started this summer investigates vibrations generated by calling birds here on campus. Near Quarry Pond, a colony of purple martins – North America’s largest swallow – provides an ideal locale for the investigation of bimodal acoustic calls. We are most interested in signals traveling along natural substrates, and so we have affixed branches from local foliage to the birds’ housing structures. We are then able to use a laser Doppler vibrometer and microphone to record sound and vibrations produced by purple martins as they call.  This summer’s work has focused on developing a methodology of recording bimodal bird calls and on building a library of call sound and vibrations. Ultimately, the end goal of this project is to conduct playback experiments to test whether call vibrations serve a communication role for these birds.

There is still work to be done once summer is over; so we plan to continue our investigation on the significance of vibrations in animal calls. Throughout the year, the Caldwell lab is committed to continuing to pursue projects begun here this summer and further our work even more. With luck, by this time next year, we may have the opportunity to conduct vibrational propagation and callback experiments on treefrogs in the tropics of Panama and take what has been learned here this summer and apply it in the field. Finally, we’d like to thank the X-SIG program for making all this work possible, all those we’ve gotten the chance to work alongside with here this summer, and you for taking the time to read this. From the three Californians, keep on vibing 🙂

Sengupta’s Lab: Where Murphy’s Law Rules

Hello from the Sengupta lab! From left to right we have Dr. Sengupta, Nathan, Keylly, and Meem. Keylly and Nathan are rising seniors and are working on the first project about the formation of clathrate hydrates. Meem is a rising sophomore and is working on the second project about the memory effect of clathrate hydrates.

Project 1: Suv’s Law, Theft, and Clathrate Hydrates

The Sengupta lab is focused on clathrate hydrates. Don’t know what those are? Don’t worry, we didn’t either, but fortunately for you all we spent a week reading through the literature and can explain the basics. To put it simply, clathrates are cages of ice that form around guest molecules under low temperature and high pressure environments. Clathrates form naturally in permafrost and oceanic sediments, and can also form in gas pipelines which could cause blockages. Our goal is to eventually be able to form and study clathrates in an apparatus we build, though the journey there is long and tiresome.

Above: The familiar structure of hexagonal ice (Ih) is what most people think of when they think of ice. The red spheres are the oxygen atoms, and the white “bonds” actually represent a pair of bonds – the hydrogen atoms (not shown) are covalently bonded to one oxygen and hydrogen bonded to another oxygen.

Below: The various cages found in clathrate hydrates – from left to right, we have the 512, 51262, and 51264 cages. This notation is exactly what it looks like: the number of pentagonal and hexagonal faces in the cage. Various cages are assembled together to form a larger crystal structure – the cubic structure II hydrate which is found in propane hydrates and THF hydrates is shown below. It consists of the 512 and 51264 cages.

The apparatus has mostly been assembled at this point, and it is truly a feat of engineering. The diagram shows what other setups have looked like in the literature, and we followed with a similar layout. Naturally, only the finest materials were gathered for this project, such as the Coleman cooler (probably from Walmart) used for the temperature controlled bath. One may also notice the custom-made lid for said cooler, born of the most premium Styrofoam in the innovation center. We’ve also spent plenty of time trying to find the leaks in the system (the bane of this project). This battle will likely never end, so we must have our wrenches and Teflon tape ready at a moment’s notice.

One may wonder what tools we have at our disposal to assemble our apparatus. We have wrenches, pipe cutting tools, a mallet, calipers, screwdrivers, measure tapes, and more. In fact, we have enough items to have part one, two, and three to our tool drawer! We also can’t forget the cauliflower and dandelion looking zip ties that we love and use so much. It was unexpected that we would have to learn how to use so many tools when we first joined Dr. Sengupta’s lab, but apparently this is a normal part of research. (Though maybe more so for us than for the synthetic chemists because we’re a physical chemistry lab.)

While constructing our apparatus we had to replace some fluids in the chiller and vacuum pump. The chiller needed its water replaced with a 50/50 water/ethylene glycol coolant mixture, and that ended up being kind of nasty. The water had some unknown gelatinous brown substance in the bottom of it, but with the power of lab paper towels it was defeated. The vacuum pump oil replacement was easy enough, though we had to make one of our few adventures into the physical chemistry lab to find the waste oil container. That lab has officially made us the worst thieves in the building. In order to pressurize the system for testing, we stole a nitrogen tank; this involved rolling the gas cylinder onto a cylinder hand truck. Think of the loudest shopping cart you’ve had at a store, now imagine that even louder and that was the sound of us dragging it down the hallway. Clearly not masters of stealth, we decided to take a second shot at theft. The thermocouples that tell us the temperature in the cell needed to be calibrated, and for this multiple data points were necessary. We used ice water, room temperature water, and then decided upon heated water as the third point. We ventured into the physical chemistry lab where they had a temperature-controlled hot water bath, and promptly nabbed it. As we exited the door having completed our heist, we were immediately met by Dr. Frey and at least five other people who asked what we were taking. Quite unfortunate timing, as had we left ten seconds later they would have been in front of us and likely not seen the water bath in our hands. Caught red handed, our thieving ways came to an end… or did it?

Our next venture into the world of clathrates was figuring out how to make ice particles. Since we have chosen to make our clathrates from ice (instead of liquid water) our “reaction” takes place at the surface of ice. Thus, increasing the surface area of ice increases the reaction rate. One way to increase the surface area for the reaction to occur on is to use fine ice particles – the finer the particles the higher is the surface area-to-volume ratio. So a suitable method to efficiently make fine ice particles was required. Dr. Sengupta wanted to find a new fabrication method because the one he had been using was … something else. The old method involved freezing relatively large water drops in liquid nitrogen, taking the ice pellets formed and running them through a coffee grinder (doesn’t pack quite the same kick as coffee beans), and then sieving them to obtain the desired size. This method is not ideal for a few reasons, mainly being that the ice particles created this way have random structures since they’re being ground into pieces. Having regular sized ice particles can be beneficial in analyzing the data later on. The method we developed after some research was surprisingly effective. We took a pressurized sprayer and sprayed a rough mist directly into liquid nitrogen, and the water droplets weren’t super small because we used fume hood air to pressurize it (~25 psi). We then sieved the sprayed contents, and after some microscope adjustments, we saw spheres! Not lame random shapes, but spheres! The pictures below show the ice particles from the coffee grinder method (left column) and spraying method (right column). It’s obvious in the first four pictures taken with our phones that our method creates much finer ice particles.

Coffee grinder particles (left) and spraying method particles (right ) at 40x magnification.

As mentioned previously, clathrates form with a guest molecule trapped in a cage of ice. The guest we have chosen to use is obscure, known only to those living in Texas or by dads who wear socks and sandals to grill. Can you guess what it is? Perhaps the picture of Hank Hill gave it away, but that’s right, it’s propane! Our venture into using propane so far has brought back our old nemesis: leaks! We had planned to start taking a blank one day and then try forming clathrates the next, but naturally every bit of piping or tubing we added, leaked. Similar to Murphy’s Law, we’ve coined “Suv’s Law” which states: “If it can leak, it will.” We fixed most of the leaks only to find the professionally-done welded pipe under the fume hood was also leaking, and we couldn’t do anything about that. We then tried switching to flexible hosing temporarily, but once the pressure went too high it popped like a balloon! We eventually got new, stronger tubing and it leaked too (because of course it did), in an extremely infuriatingly slow rate – a tiny leak which we could not even find despite a whole summer’s worth of expertise in finding and fixing leaks! Downtrodden and defeated, we simply decided to let it leak, since it wasn’t part our main experimental apparatus, while we moved on and started taking blanks. The blanks will be used to compare the pressure change in an empty vessel to one filled with ice particles where hydrates should hopefully form.

Below are the blanks we have taken so far at 30 psi. The needle valve that sets the flow rate of the gas has completely arbitrary values ranging from 0-125, yet for some reason only 3-7 seem to actually change anything. There also seems to be no linear relation from one value to the next, because why would things be easy? From 4 to 5 it appears to be around 10x faster, but from 5 to 6 it seems around 4x faster. We’ve chosen to use 5 for now, because Papa Bear’s flow rate was too high and Mama Bear’s flow rate was too low, but Baby Bear’s flow rate was just right! This is all we’re going to be able to post on this blog, because we’ve been deprived of liquid nitrogen, the thing we need to make ice particles. The suppliers took the 5th of July off and then never showed up the rest of the week, so we are unable to even attempt to make clathrates 😦 . Our last week of lab will hopefully consist of attempting to form clathrates, but that’s only if liquid nitrogen gets delivered. If not, we’ll be pretty dang bored, or worse, forced to read more literature.

Good news! We got liquid nitrogen delivered (finally) and were able to run some experiments. The graphs below are our first proper attempt at making clathrates with ice particles. We had the gauge pressure set to 15 psi (roughly 29-30 absolute psi) and our needle valve set to 5 at a temperature of -5 °C. The software was set to record for 10 hours, but it turns out more time was needed and the pressure eventually returned to ~28.5 psi after the drop. Speaking of the drop, that’s the sign we’ve been looking for! The drop in pressure indicates that the ice particles are taking in gas and forming clathrates faster than the gas is being supplied. The drop is relatively small in this experiment compared to literature examples, so we believe lowering the temperature could help.

Another great way to learn if propane clathrates have formed is by trying to light them on fire. Have you ever seen ice on fire? You have now! We’re hoping our next experiment at lower temperature (around -16 to -17°C) will yield more clathrates. We’re also going to try lighting it on fire in the fume hood so it doesn’t get blown out by the wind, but don’t tell anyone else. We’ll likely not get much else done this week except a few more experiments, but since things seem to work this is where we can really take off. During the semester we’ll both be doing research, so we’ll be able to change variables such as temperature, flow rate, and even test inhibitors that stop the clathrates from forming. At some point we’ll also look at the kinetics of the drop in pressure much closer than has been studied before.

Project 2: Non-living Chemicals Have Memory?

Hi from the crazy girl you see running around in Science Center, CUB and Huber Hall everyday. You ask me how my research is going, and my answer for that has been constant throughout this summer- “I have been successfully finding things I did not want to find, but haven’t been able to find what I wanted to find”.

Yes, you got that right- this is Meem here. I am a rising sophomore majoring in Chemistry and minoring in Writing. Allow me to give you a short introduction to my work in Dr. Sengupta’s lab. Thanks to Keylly and Nathan for doing the difficult job of explaining what clathrate hydrates are and how they form. In Dr. Sengupta’s lab, I look at the memory effect of clathrate hydrates, trying to find whether clathrate hydrates can remember their identity. Sounds weird huh? Here comes my big boring explanation.

Let me try to explain what memory effect is. When we make clathrate hydrates from fresh samples of water and guest molecules, they have been seen to have a lower rate of formation than when we make them from samples made by melting previously made hydrates. This tells us that clathrate hydrates have some sort of memory and even when we melt them, they can still remember who they were. So when we try to form hydrates from melted samples, they have higher rate of formation. But wait, aren’t they non-living, funky smelling chemical substances? Since when do they have memories?

There are three different hypotheses to explain the existence of memory effects. My personal favorite (because it’s more intuitive, I can barely explain the other two perfectly) is the residual cage structure hypothesis. It says that when you melt clathrate hydrates, there are still portions of cages that remain in the solution which later act as a point of nucleation while forming hydrate crystals.

So what do I do in lab? I pose with the bottle of my tetrahydrofuran (THF) and try to look like a real scientist. Most of the time, when I’m not trying to just look like a real scientist but actually trying to be one, I prepare a solution of THF and water in the ratio of 1:17 which is supposed to form clathrate hydrate at appropriate temperature and pressure.

Take a look at the clathrate hydrate I synthesized! They look just like ice, but trust me, they are very different – for one thing, this picture was taken in the cold room where the temperature is maintained at 4 oC – what happens to ice at 4 oC?

To study memory effect, I look at the samples under microscope at different temperatures to figure out the memory effect of clathrate hydrates. I put fresh sample under the microscope at 4 degree Celsius first because THF clathrate hydrate are supposed to form below 4 oC. Generally, I don’t get any clathrate hydrate until I undercool it by reducing the temperature to approximately -8 oC. I wait for samples to freeze at -8 oC, (often they don’t freeze! Ahhh thermodynamics! Why are you so cruel?! Why would you not freeze at -8 oC when you melt at +4 oC?) Next, I raise the temperature back to around 2-4 oC to see whether the frozen samples melt because at -8 oC, there could be ice, but at 2-4 oC, there should not be any ice. So if the samples don’t melt at 2-4 oC, I formed hydrates, yay! Sometimes, my experiment just loves messing around with me and everything melts. Sometimes, nothing melts, and again sometimes, they melt but refreeze to clear crystals. (These are the times when you see me sitting hopelessly in the chemistry lounge because I have no idea of what’s going on.)

One thing to highlight in all of this is that nucleation processes (that’s fancy science talk for freezing) in general and the the memory effect itself are random events. Thus, you have to make a large number of observations to get any meaningful statistics regarding these events. In order to observe a large number of these events, we have a number of small 1 inch diameter discs made from different metals and plastics including white and black teflon, PEEK, PVC, aluminum, copper, and PETG. Earlier this summer, I made these discs using the CNC machine at the Innovation Center (shout out to Joshua Wagner who helped us with it). Each of these discs have 92 wells and each well can hold 4 microliters of sample. This is what I use for my experiment. We have made discs from different materials to see if that has an impact on the memory effect. Here’s a picture of some of my discs. Look at that copper disc! Took me three days and breaking 5 bits of the CNC machine to make it. And guess what? Professor Sengupta almost ruined my three days and 5 broken bits worth of work by trying to make a side hole through which our thermocouple could go inside the solution and read the temperature inside. See how an edge is almost broken? Ughhh! It hurts right in my heart!

So far, clathrate hydrates have not been cooperating with me. I have a big pile of data from the same experiment repeated multiple times. These data show a wide variation in the time taken to form hydrates despite not changing anything in the procedure, we end up with different results every time we run the experiment. A lot of data to analyze I guess!

But you know why this project is cool? Because clathrate hydrates love to play around with me and sometimes they decide to form pretty little sunflowers while forming crystals. Here’s a picture of formation of clathrate hydrate in one hole of our 1 inch diameter disc, with 40X zoom under the microscope.

You see what I’m seeing? Yes, that is why I say, science is beautiful. It’ not always cooperative, but definitely beautiful! Right now, clathrate hydrates are not cooperating with me but that’s fine. I have another week and the whole Fall semester to figure things out.

But I learned more than I expected from my project. What is the biggest lesson I learned you ask? I learned that clathrate hydrate formation is more complicated then expected. But we will figure it out. Till then, you’ll probably keep seeing me running around in frustration of not finding what I expected, or excitement of finding something I didn’t expect.

Hamiltonian (feat. Einstein)

Dr. Sato, Henry Namiot (’23), Danielle Sicotte (’22), Albert Einstein (’00)

In Dr. Sato’s lab, we are using computer technology to map out the electronic landscape of the photosystem II reaction center (PSII RC). This RC is located in the middle of what looks like a bunch of spaghetti which makes up the PSII, a photosynthetic protein. The RC itself is made up of 6 pigments arranged in the D1 and D2 branches which are in charge of asymmetrically transferring electrons to an Mn cluster so that water can be oxidized. In our research, we’re paying special attention to the energy between the 6 pigments that make up the RC to hopefully pinpoint the cause of the asymmetrical charge transfer that happens in the RC after excitation via photon. This asymmetry has been somewhat of a mystery as the RC itself has a perfectly symmetrical structure which would imply that it also functions symmetrically… but this is not the case. If we manage to figure out the energetic landscape of this RC, we get one step closer to being able to develop organic solar cells which use photosynthetic processes. This would be awesome because photosynthesis is almost 100% efficient while the best solar cells are currently only about 20% efficient.

Plant spaghetti

Bacteria spaghetti

Danielle’s work:

Basically I work with a bunch of computers, the ORCA program, and code to get data about the energetic landscape of the photosystem II reaction center (PSII RC). Because the RC is so tiny with the charge transfers happening on a femtosecond scale, we have to use super high tech awesome cluster in Masters hall to model what is actually going on in there. We started this project last summer where we found an electronic pathway by which the charge transfer was asymmetrical and this year we are adding a time dependence to the simulations to hopefully get more accurate results (TDDFT). So far this summer, I have been using a new quantum chemical program, ORCA, to take in my .pdb files of the RC , run simulations on the cluster (they take up to a week to finish!) and finally spit out a bunch of data (500 KB each!) about the energy of the system. I harvest information mostly about the HOMO, LUMO, ground state, and SCF energy of the system. This first phase of research is complete and now I have started the analyzing phase of our research. The first step here is to check if my data is any good at all and test the orthogonality of the molecular orbitals. If the MO’s are orthogonal, which I assess through some nifty python code, we are ready to go and move onto the next step… which I am still developing in python. In the future, I will also use the results of Henry’s work to get data about the RC within the actual protein.

Einstein with the cluster
PSII reaction center
Data from ORCA

Henry’s work:

I am working with molecular dynamics, or MD, simulation programs to simulate the PSII reaction center. I started the summer using GROMACS. After learning the program, I spent the majority of my time trying to parameterize the unique ligands of the system so GROMACS could process the molecules and run the simulation. In the end, this proved very difficult for GROMACS, so we made the decision to switch to NAMD to see if it is any easier. So far, I have found that NAMD is a more straightforward program to use which might make the process easier. The end goal of this work is to simulate the protein complex where you would find it in a cell, in the lipid bilayer. Once this is done, I will hand off the results to Danielle so she can perform the quantum mechanical calculations to better see how the reaction center works.

Einstein the intern:

When he is not solving relativity, Einstein is our research groups photographer. Some pieces from his portfolio are pictured below.

“This isn’t relativity”
“Hello cluster, my old friend”

Welcome to Area 208 ☢

Greetings. C.elegans reporting here. For centuries, we have been under attack by many other aliens like the PA14, PQ, and Cold-Stressers. We have been working with the Powell Lab to figure out what molecular mechanisms occur in our innate immune system to defend us against these foreign invaders. So far they have found three weapons that can aid us in our quest to defeat these invaders; including the upregulation of infection response genes, the upregulation of reactive oxygen species, and simply avoiding our enemies at all costs. 

Within the Powell lab, our beloved scientists have been working to solve the question: “How does the immune system differentiate between good and bad bacteria (our nemesis), and initiate an immune response?” As listed above, they have already discovered three immune response mechanisms within the C. elegans immune system. First, when an infection is detected, infection response genes are expressed and upregulated. These infection response genes, or IRG’s, make antimicrobial proteins which then attack our enemies. Another defense mechanism we have is the making of reactive oxygen species (AKA: ROS). Although the ROS will attack our enemies, they also have a tendency to turn against us. They are highly reactive, and highly toxic (and not the smartest on the block – haha, a human saying), so we need to also upregulate an oxidative stress response to detoxify the ROS. Lastly, we use our past experiences of the bacteria or other pathogens we’ve encountered to simply avoid them in the future. We don’t mean to brag, but C. elegans have a great sense of smell. This allows us to remember the way our enemies smell; so if we smell them coming, we can hit the road, Jack. (Do you know who this Jack is?) 

In response to the above mentioned question, scientists all over the globe have theorized that the immune system is not directly looking for an infection, but rather indirect evidence of an infection (i.e. cellular damage). Our Powell scientists believe that one type of damage that contributes to this mode of indirect detection is something called oxidative damage (or oxidative stress).

Here’s a picture of our amazing scientists by the way:

Our lovely scientists, from left to right: Isabella, San, Professor Powell, Alisa, Keira

Two newbies in the lab, Alisa Liu and Isabella Jensen, have just begun their quest in researching this possibility of oxidative stress inducing an immune response. Their quest is taking place in two parts, as follows:

Mission #1: Is oxidative stress necessary to induce an immune response?

To test this, Alisa and Isabella will subject worms (that’s us!) to infection without oxidative stress. If they see worms that are exposed to PA14 (a pathogenic bacteria) with GSH (an antioxidant to combat the oxidative stress response the worms have towards the PA14) have a lower expression of infection response genes than worms with only PA14 exposed to them, then they will know that oxidative stress is necessary. 

Mission #2: Is oxidative stress sufficient on its own to induce an immune response?

To test this, Alisa and Isabella will do an avoidance assay and perform qPCR to see if the immune response was activated. They will expose the worms to PQ (a chemical that will cause the worm to have an oxidative stress response) with OP50 (worm food AKA E. coli). They expect the worms to associate the oxidative stress, caused by PQ, with OP50, leading them to avoid the OP50. If they see the worms avoid the OP50 and express infection response genes, then they will know that oxidative stress is sufficient to induce an immune response. 

Another condition they will include in this project is using fshr-1(-) worms (mutant), which are missing the infection response gene (FSHR-1). The mutant worms will be exposed to PQ with OP50 and if they see them not activating their infection response genes or avoid the OP50 then they know fshr-1 plays a role in detecting oxidative stress.

Isabella working in the biosafety cabinet:

Alisa checking a plate of worms at a microscope:

Another, more seasoned scientist in the lab, Keira Tuberty, is exploring cold shock and osmotic shock. Here’s a bit about what she’s been working on in her own words:

Mission #3: How does one type of stress response influence another type of stress response? 

Previously in the lab, I have studied the effects of a cold shock on worm viability. To perform a cold shock assay, worms are exposed to 2 ℃ for 4 hours. The resulting phenotypes include loss of pigmentation, immobility, and death. Some worms die during or immediately after a cold shock while others lose their pigmentation and become clear, only to die about 48 hours later. Intestinal fats provide pigmentation and nutrients for the worm. When these fats are reallocated from the intestine to the germline (where eggs are being produced), the worm turns clear. The Powell Lab has hypothesized that this clearing phenomenon is an example of terminal investment because the adult worm devotes its resources to its offspring, which kills the parent, but provides the offspring with a survival advantage against cold stress. 

This summer, I have combined cold stress assays with osmotic stress assays to see how one stress response influences another stress response. Exposing the worms to high salt concentrations causes osmotic stress and similar phenotypes to cold stress. To perform an osmotic shock assay, I prepare agar plates with various salt concentrations: 51 mM NaCl NGM (normal), 100 mM NaCl NGM, 200 mM NaCl NGM, 350 mM NaCl NGM, and 500 mM NaCl NGM, and put the worms onto these plates for a specified duration. Higher salt concentrations and longer durations cause more severe phenotypes and death. To find out how osmotically stress worms are affected by cold stress, I perform three types of assays. In one, I expose the worms to the various salt concentrations for 4 hours, recover the worms to normal 51 mM NaCl NGM for 20 hours, and then expose the worms to a 4 hour cold shock and score phenotypes and survival over the next 96 hours. In another similar assay, I perform a simultaneous 4 hour cold shock and osmotic shock and then recover worms to 51 mM NaCl NGM and score phenotypes and survival over the next 96 hours. In the third type of assay, I raise the worms on either 100, 200, or 350 mM NaCl NGM from embryos to young adults and then perform a 4 hour cold shock and score over the next 96 hours. We hypothesized that osmotic stress would make the worms resistant to cold stress. Preliminary data suggests that the double stress event has a synergistic effect at concentrations of 200 mM, 350 mM, and 500 mM, where the worms are more sensitive to cold shock after being osmotically stressed. However, worms that have been subjected to 100 mM NaCl NGM appear to be more resistant to cold stress than worms that have never been osmotically stressed. 

Here’s Keira and her awesome shirt at a microscope:

We’ll leave you with some more pictures taken by our beloved scientists, as well as some funny C. elegans related images our scientists found on the popular search engine, Google. C. elegans out.

Alisa, Isabella, and Carl (THE C. Elegans) out for ice cream:

A chunked plate with a heart:

A memoriam for our fallen comrades:

An oxidative stress reporter worm under a microscope:

C. elegans memes courtesy of Google Images (search: “c elegans memes”):

You don’t need to choose happy! and more…

Learn more about Dr. Berenson’s personality lab! Brett, Leah, and Ellie work with Dr. Berenson on a variety of different projects that we introduce below. First, get to know a little bit about Brett, Leah, and Ellie:

What do you like to do outside of the lab?

Ellie: Outside of the lab, I enjoy trying new vegetarian recipes, hiking, and spending time outdoors! This summer I have enjoyed getting to explore Gettysburg by doing things like going to the farmers market and trying out new restaurants.

Brett: Outside of the lab I enjoy spending time with my dog and cat. I enjoy going to the beach and spending time in the water and fishing. I spend lots of my free time outside in nature.

Leah: I love to create memories! I love to spend time with my friends, try new places to eat, explore different towns/cities, hike, and play with animals, either at the humane society or at home! I also watch a LOT of Star Wars and have been bingeing The Clone Wars this summer.

What does a typical day look like for you in the psychology lab?

Ellie: Each day looks different! I usually work on any existing tasks that I hadn’t finished the day before, whether that is working on syntax, searching for helpful literature, or helping edit and review papers that are currently in the works. When I am not working on those different projects, I am focusing on the next part of my study. This started with brainstorming and literature searches, then evolved into creating my study, and right now I am in the process of collecting data.

Brett: For days I am remote, a typical work schedule involves coordinating Zoom meetings and preparing my ideas for when I come into the lab. When I am in the lab, I typically spend my time setting up my research project, organizing, and analyzing data.

Leah: A typical day for me involves a lot of screen time. All the work I do is on some sort of screen, whether I’m reading and analyzing papers on my iPad, writing commands/codes for data files on SPSS, or gathering sources for something I’m researching. There are sometimes sighs of frustration or “loudly talking” at the computer when a command won’t run properly due to an error. Most of the time I am reading research papers and writing myself notes in the margins. Currently, I am helping Ellie collect data for her experiment. 

What have you learned about yourself during your summer?

Ellie: This summer has helped me learn a lot about myself as a student but it has also helped shape what I want to do after I leave Gettysburg. While I may not be focusing on research after my undergraduate years, I have a better sense of how I function in an environment that isn’t necessarily focused around going from class to class. 

Brett: This summer, I had expectations that I would be able to do things much faster than is realistically possible. I learned to pace myself and how to set realistic and attainable goals. I also learned how persistent I can be when I had to put a significant amount of effort into gathering participants.

Leah: I think the most important thing I learned about myself was that I definitely love research and want to make a career out of research. The grad school panel really helped me realize that I want to go straight into my PhD after Gettysburg. Overall, I furthered my understanding of how I function in a professional setting. 

What is something that you learned this summer that will help you in your future studies in psychology or beyond?

Ellie: I am much more comfortable working with SPSS after this summer. I feel like I have a deeper understanding of what happens after data collection and what working on data management looks like. I have learned multiple different analyses that will benefit me in my advanced labs during my senior year. 

Brett: I learned much about conducting research, including designing an experiment, troubleshooting the experiment, recruiting participants, and gathering/analyzing data. I feel as if I gained a great deal of expertise in data analysis and management.

Leah: Learning syntax commands has been really beneficial and I think I will carry that with me throughout the rest of my career at Gettysburg and maybe through my grad school career. I definitely am more comfortable with using SPSS as a whole, and I understand how data goes from collection to analysis. Also a very important lesson was how to dodge paywalls when I cannot get access to a paper directly through the library. 

Ellie’s Projects

One paper that I helped work on early in the summer focused on social support strategies for those with borderline personality features. Previous researchers in the personality lab examined how individuals with borderline personality features responses to positive reframing, a social support strategy that involves reframing negative experiences as opportunities for growth, differs from their responses to validation efforts, a social support strategy that validates their struggles as “normal”. The results of this study determined that those with borderline personality features favored negative validation. However, a sex difference in social support strategy preference was found. Females were more likely to prefer negative validation whereas males had a higher preference for positive reframing. I searched for pre-existing literature that provides reasoning behind why this sex difference was found and discovered that females typically utilize emotion-focusing coping while males use problem-focusing coping. Females are more likely to engage in emotional support seeking, and negative validation appeals to this preference. This is a significant contribution to literature on borderline personality and social support, as the majority of studies have consisted of solely female participants. 

While I have helped with a variety of different tasks that were a part of previously conducted studies, I have also created my own study. I am interested in social beliefs and personality- but since my study is currently being conducted, that is pretty much all I can say without giving out information that could impact my results! I have spent a good portion of my summer conducting library searches to find literature that is applicable to my project as well as creating the study itself and working on an application to the Institutional Review Board (IRB) to get it approved. I have gained in-depth experience of how psychology studies are created from the very first step.

Brett’s Projects

Since I still plan on collecting participants and conducting further research for my project, I cannot go into much detail about my study. However, one thing I learned that I can talk about is how difficult it can be to recruit valid participants. To start, I posted my study within various Facebook groups and called local townships to see if any of the employees would take my survey. It started out slow, but in one day, the numbers exploded! I was so excited to have a great turnout. However, when I met with Dr. Berenson, we quickly learned that most of those responses were from bots rather than actual people. This trend continued throughout the data collection process. At one point we had over 1000 responses, and it turned out that only about 100 were real. It was also a struggle to find serious participants, since many people were just responding randomly. I spent days filtering responses to get real, valid responses. I was able to appreciate how so little of the experimentation process involves the actual experiment, and so much involves the numerous overlooked aspects.

Leah’s Projects

One focus of my work this summer has been reading about peer mentoring in STEM. So far, there has been information on faculty-student mentorship programs but not much research has been done on peer mentoring programs. From what I’ve read, it seems as though while students gain a lot from a faculty mentor, they aren’t able to relate to them as well as they would be able to relate to a peer. Peer mentoring allows for information to be shared that might be uncomfortable or perceived as too “unprofessional” to share with professors.There are many different models of peer mentoring that I wasn’t aware of before looking at this further. A lot of my research also focused on different ways to promote inclusion. The research that I have done will be put to use in the Fall.

Toxic Positivity Study

We have all been working on data management and analyses for a study on ‘Toxic Positivity’. Social media is flooded with “memes” that emphasize the importance of happiness or being positive, but no one has considered how this may affect different types of people. These positivity memes could be potentially harmful. For example, people who have depression might view these memes as harmful because they aren’t experiencing the happiness that is being promoted and could view themselves as a burden. In this study, Psych 101 students were asked to answer a series of questions about mood and then presented with either positivity memes or snapple facts. Each image had similar colorful backgrounds to control for any extraneous variables. 

Above are examples of positivity stimuli


Above are examples of neutral stimuli

General Data Management and Analysis Work

The data from this study is put into an SPSS .sav file (which looks like an Excel sheet) and then it needs commands to be cleaned, analyzed, and interpreted. This is where the syntax comes in. We use syntax files to keep track of our data management and analysis. 

This is an example of a syntax file. We write syntax commands to assign labels to variables, assign labels to values of the variables, calculate scales, and calculate the reliability of those scales. Personality and psychopathology variables are on a continuum, so variables need to be calculated on a scale rather than in categories.

Most of what is done in terms of data management is assigning labels to variables and then assigning labels to each level of the variable. From here, we might reverse code some variables. Variables may need to be reverse coded if they are worded differently than the rest of the items in that grouping. For example, if there was a scale that was supposed to be about positive attitudes but one of the variables was asked about a negative aspect, that variable would be reverse coded. After all the variables are in the same direction (positive or negative), a scale can be calculated to find the mean, standard deviation, and other descriptive statistics. The reliability of the scale is then calculated, meaning that the scale is measuring what we were intending it to. After all the variables have syntax commands, analyses can be run. We use regression to examine main effects and statistical interactions. 

Professor Puckett’s Particle “Fish”ics Lab

Hello from Professor James Puckett’s Lab. The overarching theme is complex many body systems far from equilibrium.  This summer we are working on two distinctive projects: statistical physics of granular materials and collective animal behavior. Han G. and Carlos S. are working on the granular materials, while Justin C. is working on the collective animal behavior. 

The project on granular materials examines a fundamental assumption of using a statistical mechanics approach to granular materials – equiprobability.  This is the assumption that all microstates are equally probable.  This is true for an equilibrium thermodynamic system, but granular materials are weird.  They are inelastic and athermal, so some assumptions of statistical mechanics will need to be revised.  In terms of work, Carlos S. and Han G. have devoted a lot of time to construction of the apparatus, electronics, time in the machine-shop, and working on code.  Code to automate the apparatus, image analysis, and a lot of computation geometry. 

Justin C. works on the collective animal behavior project.   How do individuals in a group make decisions?  For humans, these decisions can be quite complex.  For our fish, we can define decisions in terms of how ordered the system is.  A helpful analogy is a magnet.  Iron can be non-magnetized (disordered) or magnetized (the spins are ordered).  For the fish, we call a disordered state a swarm and a highly polarized state a flock.  The fish can also order into another state which has rotational symmetry which we call a mill.  In this project, Justin C uses light gradients to non-invasively nudge the fish from one state to the next.  Essentially, Justin uses light to ‘magnetize’ and ‘demagnetize’ a school of fish to examine how fish interact with each other.

Statistical Mechanics of Granular material

Hi, My name is Carlos Sanchez and I am a rising senior in Physics. This is my second summer working in Professor Puckett’s Lab, where I worked on the same experiment as now. This year working along with Han G., we have now completed the apparatus, taken initial data and started to analyze our data. We have a fair share of hiccups in the building process as well as the coding process. So I was always focusing on the apparatus, fixing, modifying, tuning the experiment up to standard. I was definitely not alone with Han G. doing many things in regards to the camera set up and the piston set up. 

Figure 1: This is a picture of the apparatus set up.

Here we want to examine the density of states of a simple granular system.  To do this, we need to generate a lot of configurations of particles.  We use a pneumatic piston to excite the system into a new configuration.  We record configurations with a camera.  Everything is automated from the computer.  So there’s a lot of code to run things and more code to extract data from the images.

Figure 1 is the overview of the apparatus without the camera in view. For a breakdown of the parts look at Figure 2. There are seven main components of this apparatus: the bottom piece/structure, the box of particles, the background/LED screen, the air compressor, the piston, the valve, and the camera. Figure 2 gives a not-to-scale version of the setup with a mini-explanation of the parts, and how they work within the system of the apparatus.

Figure 2: This is a not to scale Power-Point drawn of the full apparatus.

Going from left to right the first part is the valve which is the start of everything which is controlled by code which Han will explain.

Figure 3: This is a picture of the valve.

The valve is powered by an air compressor which then is connected to the piston to make it possible to automate the piston from code. The way it is connected through the code is the circuit in figure 3.

Figure 4: This a picture of the circuit

The piston uses a dual 9V power supply which is triggered by the GPIO of a raspberry pi which interfaces with the PC that controls the rest of the apparatus. The piston is forced upwards by the compressed air from the valve to launch the particles into the air and hit the top of the particles box which can be seen in figure 4. This scatters the particles and the system will come to rest in a new configuration.

Figure 5: This is a not to scale Power-Point drawn of the particle box as well as how it is mounted

Now the particles are made of acrylic plastic which is made using a hole cutter. There are currently two sets of particles so that the system is bidisperse- two different radii -and their ratio of difference is 1.4; each set has two diameters. The first one has 1 ¾ (or 7/4) and 1 ¼ (or 5/4), the other set has 1 5/16 (or 21/16) and 15/16. After the particles settle in the box, the camera takes a picture of the particles as shown in figure 5.

This diagram shows the piston and the box of particles set up. This is not to scale either, but the explanations in the boxes are good to go off, needing no more explanation of how these work or what happens. We work in the machine shop in Masters Hall, where we have spent a lot of time cutting, drilling, filing, and sanding. We worked hard and kept having to come up with new ideas to make everything work.

Figure 7: This is a picture of Han Sanding the Upside-down T particles launcher

We had to make sure a lot of the pieces were going to work with each other, by cutting or drilling holes for screws to fit. The one piece that we worked on a lot is the upside-down T which can be seen in figure 7. Han is sanding down the piece so that it can smoothly and accurately move in the box. 

Figure 8: This is a picture of Carlos cutting a T-slot using a bandsaw

A lot of time is spent making sure everything is square and plumb. In figure 8, I am cutting a T-slot so that the bottom structure could be extended further. This will reduce parallax error of the setup from the point of view of the camera.  

After building the apparatus, our next task is image processing and data analysis.  Recall our experimental setup, we painted both of our edges red to help with our image processing. 

 The general pipeline of the image processing is the following:

1. Undistort the images due to the lens distortion.

2. Line detection for the floor and the sides.

3. Circle detection.

Distortion by the lens exists in most of the cameras. To have the best image for the computer to analyze, we need to undistort the images. To do so, we need to generate sets of calibration data. We take images of a checkerboard on a flat piece of acrylic. It is quite a repetitive process. We divide the frame up in 9 sections and take 45 images in total. Afterwards, we use the OpenCV library to generate the calibration data we need to undistort the images. 

With the collaboration with Dr. Puckett, we are able to separate our red edges from the images and remove the small blobs that came from the poor spray paint technique. 

So, we feed this image into our Hough line detection algorithm within the OpenCV library. We can get two pairs of coordinates that tell us the lines the computer has found. The blue lines on both edges are the results from the Hough line detection. To make the circle detection algorithm more efficient, we masked the region outside of both edges with Gettysburg Orange. 

After both edges are done, we move on to the horizontal floor detection. We separated the black channel of the image. As you can see, we have some problems. The particles are black as well. The line detection detected more lines within the particles. We decided not to paint the floor piece. Since the floor piece will be moving up and down within the box. We do not want to have paint rubbing within our walls. We can filter out these lines and look for the horizontal line we need. We achieve this by checking the slope, location, and the length of the lines. Our line we need should have a relatively low to zero slope, and it should be located in the lower portion of the image, and it should be the longest line. 

This is the result of our line detection. Next step is the final circle detection.

Here is our result for our circle detection. We use the Hough circle detection within SKImage library for the higher adaptability compared to OpenCV. 

Afterwards, we are able to output these data:

Where horizontal_lines_info is the array where it holds the line detection results for the floor.

left_lines_info and right_line_info stores all the line detection results for both edges.

Circles_info stores the center and radius information for all the circle detection. 

Filename_info stores the filename information for debugging and easy identification. 

The speed for all these processes takes roughly 20 seconds for each image. 

After this, we will move on to the data analysis part. We have just started the process. The general pipeline for this process is the following:

1. Align all images to a single coordinate frame.

2. Analyze the location of each particle across all the images and compare with all the images. Which includes the contacts with the particles and the walls. Find the similar states and categorize each similar state. 

Collective animal behavior

Hello, I’m Justin.  I am a rising senior physics major.  This summer, I have been working with Professor Puckett on observing symmetry breaking in collective animal behavior.  To accomplish this, we observe the different schooling formations that fish form when placed in a tank.  At the beginning of this summer, I designed a new tank with three goals in mind.  First, it must restrict the fish to a two-dimensional school.  I accomplished this by restricting the water level to about 4 cm.  This allows us to record the fish using a singular camera, since the fish will not be able to swim above or below one another.  Second, the tank must be heated uniformly.  Putting heaters in the tank would create heating gradients and introduce unintentional environmental factors that would affect the school of fish.  Instead, I placed this tank inside another tank with flowing, heated water, which has a uniform temperature.  This method will avoid creating temperature gradients.  Third, the tank cannot have currents.  This was avoided by isolating the fish from the outer, heated tank, by using acrylic walls.  This tank inside of a tank allows us to place the fish in a uniform environment without any unintentional factors to affect their movement.

Figure 1: Here I am doing some tank maintenance with the fish in the experimental tank. Since we’re using image detection software, it’s important to keep the white base as clean as possible, so every few days, I would have to siphon some debris out of the tank.

To observe the structures that schooling fish form, we use an infrared camera to record videos of the fish.  This allows us to observe the fish easily, since the IR light cannot pass through the fish, they will appear like black blots on a white background.  Then, using a visible light projector, we project different light gradients onto the tank which coax the fish into forming certain schools.  The first data sets that we collected were focused on proving that we could control the fish using this projector.  The shape that we projected onto the tank looked like a rotating propeller with a white background and black rectangles.  We observed the fish in 4 different scenarios: a black screen, a static propellor, a clockwise propellor, and a counterclockwise projector.  For the black and static propellor, we observed the fish switching between a swarm (there is no distinct organization to the fish, most fish are swimming in different directions) and a magnetized state (the fish are swimming in a circular pattern) that oscillated between clockwise and counterclockwise.  For clockwise and counterclockwise, we observed the fish following the direction of the propeller.  This shows that the fish will follow a changing light gradient, and allows us to use a similar method to observe how they switch directions.  To observe this, we programmed the projection to switch directions every three minutes.  What we have observed through a few tests is that once the projection switches direction, the fish oscillate between a swarm and a magnetized state in the old direction.  Then, after a few minutes, a group of fish will take a wide arc around the school and drag along others until the entire group is swimming in the new direction.

Chemistry is Like Cooking…Just Don’t Lick the Spoon!

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Hello and welcome to the Jameson group blogpost for Summer ’21!  This summer Erin McGrath (’23) has joined veteran Emma Armstrong (’21) in our mission to prepare and study new complexes of 1,2-dioxime ligands. 

Left to Right: Emma Armstrong, Dr. Jameson, Erin McGrath

These ligands are well known as building blocks of a class of coordination complexes known as cobaloximes.  These complexes, very well studies as model complexes of the co-enzyme vitamin B12 , have been recently rediscovered by chemists as components in catalysts that use sunlight to convert water to hydrogen and catalysts that make carbon-carbons bonds.

Note that, despite the complex overall structure of vitamin B12, the structure around the cobalt atom in both molecules is very similar.

Everyone will remember the oxime functional group from the second semester of organic chemistry ;).  If you put two oximes next to each other on a carbon chain (1,2), they can act as a “bidentate” ligand – in other words they “bite” onto a metal two times.  1,2-dioximes are very old molecules (they were discovered in the 1880s) and they have been used to bond to metal ions since 1905.

The C=N double bond is incapable of free rotation (as you’ll remember from both CH107 and CH203) and this gives rise to the possibility of isomers.  With a symmetric dioxime (by far the most common type), there are three isomer possibilities.  With an unsymmetric dioxime, a fourth isomer is possible.  By far the most common isomer found bonded to metals is the a-isomer, which bonds to metal ions through both nitrogens, to form a five-membered chelate ring.  The g-isomer is capable of forming six-membered chelate rings by bonding through one N and one O.  This type of coordination complex is exceedingly rare. 

In fact, you might expect that when preparing 1,2-dioximes from 1,2-diketones (by reacting with hydroxylamine) a statistical mixture (a:g:b = 1:2:1) would be obtained.  In fact, the a isomer is often obtained in 70-95% yield (as opposed to the expected 25% maximum yield).  This may be why so many so isomers of the g-isomer have been prepared.  The synthesis of 1,2-dioximes typically takes place in mild acid.  Raising the pH of the reaction can lead to different ratios of isomers.

Despite the thoroughly mined vein of 1,2-dioxime coordination chemistry (there are almost 5500 references to metal complexes of the a-isomer of 1,2-dioximes), we feel there a few nuggets left to uncover.  Our hope is that these we make some new complexes that might find use in the more recent catalytic applications of cobaloximes.

Cobaloxime complexes can be varied in the dioxime ligand, the neutral axial ligand or the anionic axial ligand.

Emma is working on preparing cobaloxime complexes of camphorquinone dioxime, a chiral dioxime ligand.  Chiral complexes of cobaloxime have not been made before.  The ligand itself is an interesting story.  It exists as four C=N double bond isomers, since the ligand is unsymmetric.  All four isomers were prepared, separated and the structures correctly assigned (taking into account that the regiochemistry of the Beckmann rearrangement was originally misinterpreted) by Forster just after 1900.  This achievement was remarkable considering the most sophisticated instruments available at the time gave no clues about structure.  We are interested in the b-isomer, which will give N,N-bonded complexes such as those found in cobaloximes.  It strikes us as odd that, despite the flurry of metal complexes reported for the a-, b-, and d-isomers, no cobaloxime complexes of the b-isomer were ever reported.

Cobaloxime complexes of b-camphorquinone dioxime provide their own challenges of isomers.  The ligand can orient itself in the complex is three different ways: two different ways with the dimethylcarbon bridge (circled) syn (in the same direction) and one with the dimethylcarbon bridge anti (in the opposite direction).  Luckily, these three isomers may be distinguished by NMR.  Emma has isolated all three isomers for one such combination of L and X.  This was a painstaking task requiring some very careful column chromatography.

Erin is working on cobaloximes with new variations in the anionic ligand X.  While the Co-C bond of cobaloximes has been very thoroughly studied, there is only passing mention of cobaloximes of alkynes.  This is despite the fact that metal-alkyne bonds are generally the most stable between metals and hydrocarbons.  Erin’s initial attempts gave some clues about why cobaloxime-alkyne complexes have not been thoroughly studied.  Among many failed reactions, she was able to prepare a cobaloxime-alkyne complex in about 10% yield!!!  Not great, but enough to characterize and even grow some high-quality crystals (see 2019 blog post).  Erin’s still got a few weeks left and a few more tricks up her sleeve.  We can definitely get that yield up to 20%!!!

The pandemic forced us out of the lab for an extended period of time.  What do you do if you are a synthetic chemist with a Jones for mixing and pouring and heating?  For adding a little of this and a little of that and see what you get?  You turn to the kitchen!  Because cooking is a lot like chemistry – except you CAN lick the spoon!

A custom in the Jameson household is to watch the European tennis championships (French Open and Wimbledon) on Sundays along with a breakfast of French toast and strawberries.  This can be not much fun for the cook, since French toast, for a hungry crew, needs to be cooked in several shifts.  In the lab, the Jameson group is partial to simple reactions, that make surprisingly interesting molecules, at a large scale.  Baked French toast is just such a “reaction”, that frees the cook up to watch tennis. 


The egg custard is a mixture of egg and milk in a ratio of 10 eggs/1.5 cup milk.  (This is a more egg-rich custard than normally used for French toast.)  The best bread is a denser and crustier, rather than soft.  Dense, crusty bread will take longer to soak up the custard, so the custard-bread mix should be prepared the night before.  Grease a 13 x 9 inch baking dish with butter. Slice the bread generously (~1 inch), soak each slice in the custard and “tile” the slices in the baking dish.  Tiling will allow for more slices and a larger yield!!  Pour the remaining custard over the bread and allow the bread to absorb the custard overnight in the fridge.  The “puddles” of custard will be absorbed by the bread overnight.  The next morning, sprinkle the top of the French toast with brown sugar and chopped pecans.  Bake at 350 F for 1 hour to give a crisp French toast with nicely caramelized sugar (mmmmm…).  Accompanying the French toast with fresh strawberries (folded with a bit of brown sugar to make a syrup) will ensure that this synthesis passes muster with the referees.

In Emma’s house (both during a pandemic and during normal times), Friday night pizza and ice cream is a staple.  You won’t see any take-out pizza boxes in sight, though. Her pizza is made from scratch!  During the summer of 2020, Emma’s backyard garden had an abundance of zucchini and cherry tomatoes.  Using the fresh summer produce in addition to other pantry staples, Emma’s created her new favorite pizza recipe.  The cooking of this pizza really highlights Maillard Reactions which result in caramelized sugars and proteins.


For this recipe, Emma starts by doing all of the prep-work like cleaning, cutting, and sauteing vegetables.  Zucchinis are cut into thin (less than a ¼ inch) rounds. Baby portabella mushrooms can be diced or sliced into smaller pieces. Onions are cut into ¼ inch ribbons and placed in a generously oiled sauté pan on medium low heat.  The onions are stirred occasionally and left to soften and caramelize.  The onion caramelization process usually takes about 20-30 minutes (try not to be tempted to crank the heat up because that will burn your onions before they fully reduce and get sweet). Generally speaking, Maillard Reactions are organic chemical reactions that result in “cooked” food, or food that has be caramelized, reduced, or browned.  The resulting products of Maillard Reactions are chemicals that change of enhance the flavor of the food.  Cherry tomatoes, as many as you would like, are cut in halves.  Parmesan cheese can be finely grated, sharp provolone cheese can be thinly sliced, and mozzarella can be coarsely shredded.  Lastly, preheat the oven to 450°F. Prep work is complete! This is a lot like measuring reagents used in lab for a chemical synthesis.  Cooking and chemistry both go more smoothly when you have everything you need ready for use.

On a lightly greased pizza stone or baking pan, press out a hefty ball of pizza dough (Emma loves buying Aldi’s pizza dough from the refrigerated section near the cheeses) gently with your fingertips to your desired size and shape. Once the dough is spread evenly, the sauteed onion mixture can be applied.  Next, generously sprinkle dried oregano, parsley, and red chili flake to your taste.  The thin zucchini rounds go over the onions in an even layer followed by pieces of provolone cheese and tomatoes.  To top your pizza off, mozzarella and parmesan cheese can be applied as minimally or as liberally as preferred. The pizza is cooked for 20-25 minutes, or until the crust is golden brown and the cheese is bubbling. 

On some of the mental health days or snowy mornings some of the best things to make was a warm breakfast. After finding a heart shaped waffle maker before moving into my apartment I knew that there would be many mornings of apartment brunches. I began bribing my roommates with Nespresso drinks and chocolate chips to try the gluten free waffles that I whipped up. The first time was impulsive and called for improvising for half of the ingredients but by the end of the semester there was no need for any more bribing. 


Before getting out any of the ingredients it’s best to start preheating your waffle iron if you are as impatient as I am. Start by adding 2 cups of any all-purpose Gluten-free flour, I usually use Krusteeze in one large bowl along with about one tablespoon of granulated sugar and one teaspoon of baking powder. In a separate bowl add 2 large eggs, about 1 teaspoon of vanilla, 1 and ¾ cup of milk or almond milk, and half a cup of vegetable oil. Mix the bowl of wets together then add that to the dry ingredients. Chocolate chips are always a great idea to add to the batter or mini m&ms for a more colorful look. Then you can spray your waffle iron with non-stick spray and then add your waffle mix to the iron. It should be about 5-10 minutes before they can be flipped and then taken off the waffle iron. minutes to be rWhen they finish they may be a little flatter than non-gluten free ones but don’t worry they will taste just as good if not better. They are best paired with clementine quarters or home fries and coffee.

Bladder Cancer Research with Craig and Company

Featuring: Everett Gillis, Lucy Bourdeau, and Dr. Jenna Craig

Get to Know Us!

Craig & Company (from left to right): Everett Gillis, Dr. Jenna Craig, and Lucy Bourdeau

Dr. Jenna Craig, PhD

A little bit about Dr. Craig: Dr. Craig is a rising professor (i.e. a visiting assistant professor). This will be her second year of full-time teaching at GC. She loves epigenetics and even when she tries to take her projects in the lab in other directions, epigenetics usually comes back around at some point! In her “spare time”, she is a mom to Maddie and Beau, learning sign language, baking, working out, and trying new recipes. She loves mentoring students especially in a laboratory setting such as X-SIG.

We talked more with Dr. Craig about her experiences, and to gain some of her wisdom about the Biology field. Let’s see what she has to say…

– Do you have a favorite lab procedure, and if so, what is it?

Oh gosh. I have to pick? I would go with maintenance cell culture where I grow cells for different assays. It’s almost therapeutic. Headphones, lots of flasks of cells, and that is a fun afternoon!

– How has your research experience changed the way you solve problems?

It’s actually changed a lot. Research has influenced how I troubleshoot things. When I have a problem in the lab, I research it and am usually able to solve it myself or at the very least, have a few things to try to fix the problem. This could be science related or a maintenance issue in my house. Using the knowledge that you already have coupled with what you can find in a book or online and apply it fix a problem is a process I learned and got better at the more research I did.

I am an excellent multitasker. It wasn’t always this way. But as I got better at each technique individually, I could start multiple things in the lab within an hour and be busy all morning or all day. I can do cell culture, western blots, and RNA isolation all at the same time. There’s so much to do when you’re in grad school or post-doc so being able to do this is almost a must. Because its a must, you get better and better at it everyday.  I am also an excellent manager of time because there’s so much to do in a given day. Yes, there are slow days but those are spent reading or writing which always made me wish there were experiments to do!

– What three practices helped you survive grad school?

Perseverance, hard work, and balance. Perseverance because research rarely goes right especially on the first try (or the second, or the third – you get the idea!). If you get defeated and you give up, you never finish. Perseverance is probably the most important trait students need if they’re going into a research based grad program. Hard work is also important. Hard work can mean coming in early and staying late, applying for grants, mentoring while in grad school, etc. The balance part means having friends, relationships, and having different interests. I think it was always hard for people to understand that I liked basketball when I was in grad school. Often scientists have interests outside of their field. For me, I love sports.

– Could you describe a time when you felt emotionally attached to your cell cultures?

Yeah! All the time. When I made those KO (knockout) cell lines, I was in it to win it. Every time I checked one and it wasn’t a KO, my heart broke. Definitely in grad school you were more emotionally attached because you needed successful experiments  to graduate.

– How do you relax?

I work out and make myself watch tv for 30 minutes before I go to bed. Usually the show has to be pretty mindless. If I have to pay attention to the intricacies of a story, I can’t watch it. By 10 o’clock, my brain is shut down for the night. I work two full time jobs: here as a professor and at home as a mom. At the end of the day, when I have nothing left in the tank I need to relax.

– What did your daily life look like during your post-doc research in the lab? 

I usually got into lab around 8 a.m. after dropping my kids off at daycare. Everyone else in the lab got in around 10 or 11 to start their day so I really loved having the lab all to myself for a few hours. I would first make a to-do list. This is something I wish I would have started much earlier in my academic career. My first thing to do every day was check my cells in cell culture. Knowing how much cell culture I had to do allowed me to plan the rest of my day. Usually I was doing western blots, qRT-PCR, protein and/or RNA isolation, DNA methylation assays, and/or setting up cells for an assay (drug treatment, CRISPR, etc.). I had to intertwine the “desk” work among my experiments. Oftentimes I was eating lunch in the hallway with my laptop working on a grant or a summary of my data on my projects. I was also always trying to plan two or three experiments ahead. Being much more efficient as a post-doc than as a graduate student meant I was out the door by 4 or 4:30 and picking my kids up from daycare on my way home. 

– What suggestion(s)/advice would you give to current and/or future X-sig students

Figure out what inspires you, what you’re passionate about. It doesn’t have to be what you did for X-SIG or any other internship. There is so much to do in the world of science so much so that you will be continually learning your whole life no matter what your field. With advances in technology and improvement in research techniques, there will always be more to learn. When you’re happy and interested is when I think you find genuine purpose in your life and career.

– What has been your favorite part/aspect of X-SIG this summer?

Getting to know Everett and Lucy. I love getting to know people especially when they are from different places or backgrounds. Hearing or learning about how they see their world as students at GC and young people in general is really important to me. It influences how I teach and my approach in mentoring. I love to talk about careers and the next phase (i.e. post-GC). This is so important and really the ultimate reason students are at GC. A fulfilling education and research experience can really propel students to do great things after graduation. I can’t wait to hear all about what Everett and Lucy continue to achieve here at GC and beyond. We will always be connected (I hope!).

– What is the ultimate goal/plan that you have for this specific research topic?

I want to identify a molecular mechanism that drives epigenetic differences between luminal and basal bladder cancer. Unfortunately, what we know about bladder cancer is severely lacking. To get some perspective, we are about 30 years behind breast cancer in terms of understanding the disease and its pathogenesis.  When over 80,000 people are expected to die in the year 2021 alone from bladder cancer, it is clearly important for us to learn as much as we possibly can so we can identify new therapeutic approaches. 

– What keeps you motivated when your research is not going well for certain periods of time?

Well, there are lots of things or people that motivate me to keep working hard. Some are probably more obvious than others (i.e. my kids!). I find what I do research wise really interesting and that is really motivating all by itself. I have questions and I want to know the answers. I think it is one of the coolest things to have the tools, resources, and the opportunity to apply in a research setting to try to answer those questions. 

Everett Gillis ’24:

A little bit about Everett: A rising sophomore, Everett is a BMB major often found outside or in a cell culture hood. His hobbies include gardening, coding, and biking. He has a strong interest in the medical field.

Have you ever wondered what life in lab is like for Everett? If the answer is “yes,” read the below interview where Lucy asks Everett about the ups and downs of life in lab!

– What does your daily life in the lab look like

The first thing I do in the morning is check cells. I look for confluency and contamination, then judge whether or not flasks need to be split. Much of my daily work involves cell maintenance, except for those days where I do assays. Those days are generally faster-paced and more interesting.

– What has been the greatest challenge you have experienced this summer?

Stomaching the loss of cells to contamination was very difficult.

– What are you most hopeful about for your research?

I hope to leave X-SIG having generated quality, useful data, knowing that I did the best I could in the lab.

– What has been your favorite part of your research thus far

Collecting data and sharing my project with others at brown bag lunches were both excellent parts of research.

– What are you most proud of this summer (whether in research or not)?

I am proud to have learned so much about lab techniques and bladder cancer and to have applied my knowledge to produce meaningful data.

Lucy Bourdeau ’24:

A little bit about Lucy: Lucy is a rising sophomore majoring in Biology. When she’s not in lab, you will find her hanging out with friends, taking a nap, ordering food, or buying more Hawaiian Shirts.

Want to get to know Lucy? We have you covered. Read the below interview where Everett asks Lucy about life, herself, and lab!

– How would you describe yourself?

Chaotic, messy, talkative, silly. I don’t know if those are good things to put in a science blog though. Hmmm… let me think of some good things. I’ve always considered myself a pretty empathetic person, and I make a conscious effort to live by that. 

– What is one interesting thing you do in your free time?

Ooo I don’t really know. I mostly just grew up golfing and cross-country skiing, and that’s pretty much how I spend my summers and winters when I’m not working or busy with school. When I was in second grade I was obsessed with the presidents and could name them all in order and knew a bunch of facts, but I wouldn’t say that I do that in my free time now. Maybe, I just had more interesting hobbies in second grade, I don’t know. 

– What does an average day in the lab look like for you?

Well, it used to be a lot of cell culture, but once I had harvested enough of UMUC1 WT and UMUC1 RB1 KO to lyse for protein and use in my experiments, my focus shifted from cell culture to my western blots and Bradford assays and such. When I was doing mostly cell culture, it was checking cells under the microscope, splitting cells, changing media, harvesting them, etc. Now it’s just gels, gels, gels. Protein gels, specifically. I like the gels though, whether it’s making them or running them. It’s pretty straight forward, therapeutic in a sense. Anyway, I’ve just been running gels for the past week and that’s about it. Eat, sleep, run gels, repeat. Either way, I would say there isn’t really a “typical” day in the lab for us, stuff is changing everyday, and something different needs done everyday. 

– Where do you feel most at home?

My grandparents’ house because I like them so much, and they have always been there for me. I definitely think I lucked out with my grandparents, I’ve never met such loving, generous and supportive people. Like, I bought my grandfather a Gettysburg T-shirt, and now he says it’s his favorite shirt. How adorable is that? Love Patty and Ronnie.

– What are you looking forward to next semester?

I’m excited to have the school routine again. Even though it’s almost always stressful, it’s still a routine that I’m comfortable with and I know what to expect from it. I get a lot of purpose and motivation from my academics too, even for things that have nothing to do with school.

Let’s Talk about Bladder Cancer

Above: UMUC1 RB1 KO F P21 BC cells under a light microscope.

Background information:

Our research aims to better characterize bladder cancer (BC) cells and to test the efficacy of CDK 4/6 inhibitors on BC cell proliferation and death. Bladder cancer is a very heterogeneous disease, meaning that it consists of many cells with varying molecular subtypes within a singular tumor. The American Cancer Society has estimated about 80,000 people have died with a diagnosis of bladder cancer every year for approximately the past five years. Genetic predisposition, diet, smoking, excessive alcohol consumption, and diabetes are just some of the contributing factors to the initiation and establishment of bladder cancer. Bladder cancer cells are often classified according to their gene expression profiles; their assortments of genes expressed to varying degrees; and to their morphologies, which are physical structures observable with microscopy. These characteristics give rise to three broad categories of BC cell lines: luminal, basal, and non-type, which are referred to as molecular subtypes.

Luminal bladder cancer is typically a less aggressive and invasive form of bladder cancer, whereas basal bladder cancer has been found to be more aggressive and invasive, often with poorer patient outcomes. Oftentimes, luminal and basal bladder cancer cells have opposing gene expression profiles: genes expressed in luminal cells are not expressed in basal cells and vice versa. The behavior of non-type cells is characterized as neither luminal nor basal. 

What exactly is the driving force behind differences in gene expression between the molecular subtypes? Multiple theories have been proposed, but DNA methylation has been a mechanism of particular importance to our lab. DNA methylation is the process that reduces gene expression by binding methyl groups to DNA. One gene that is strongly associated with the severity of bladder cancer and its varying molecular subtypes is Forkhead box A1 (FOXA1). It has been determined that in luminal bladder cancer cells, FOXA1 is over-expressed, while in basal cells, FOXA1 is not expressed at all. In non-type cells, FOXA1 may be either over- or under-expressed. DNA methylation has been shown to regulate FOXA1 expression. There are, however, regulatory proteins involved in controlling DNA methylation. One such protein is retinoblastoma protein 1, expressed by the gene RB1. At the protein level, RB1 works in a protein complex that binds to DNA in order to prevent DNA methylation. If RB1 is lost, not expressed, or mutated, DNA methylation can occur at a rapid rate, thereby altering gene expression and possibly causing cells to present as the more serious and dangerous basal subtype.

Figure 1. Characteristics of BC molecular subtypes.

Project #1 (Lucy):

In our lab, we are working with two cell lines: UMUC1 WT and UMUC1 RB1 KO. While UMUC1 WT is a confirmed luminal cell type that expresses both RB1 and FOXA1, UMUC1 RB1 KO does not express RB1 and interestingly, doesn’t express FOXA1 as well. In addition, UMUC1 RB1 KO has not yet been subtyped. The first objective of my research is to confirm Dr. Craig’s previous findings: that RB1 and FOXA1 are expressed in UMUC1 WT and not expressed in UMUC1 RB1 KO, of which we have several independently established clones, including clones: A, B, C, D, I, and F. To achieve this, my goal is to grow both UMUC1 WT and UMUC1 RB1 KO cell lines in order to harvest protein from these cells. Next, I will use western blotting techniques to determine whether RB1 and FOXA1 are present at the protein level in both UMUC1 WT and UMUC1 RB1 KO clones.  

Figure 2. Western blot output (completed by Dr. Craig during her post-doc research) indicating that RB1 KO in UMUC1 Luminal Bladder Cancer Cells results in loss of FOXA1 at the protein level. 

Thus far, I have isolated protein from our UMUC1 WT cell line and our UMUC1 RB1 KO Clone F cell line. After isolating protein, I used the Bradford assay to quantify the protein concentration for each sample and prepared the samples to have the same protein concentration with loading dye. Finally, after gel electrophoresis and transferring proteins to a membrane, I used antibodies to probe for RB1 in both UMUC1 WT and UMUC1 RB1 KO Clone A, B C, I, and F. The next goal is to probe for FOXA1 in these same samples. 

The second goal of my project is to further research the UMUC1 RB1 KO cell line(s)and to determine what molecular subtype category, based on gene expression, best suits this cell line. To better categorize UMUC1 RB1 KO, I will look at candidate genes, also known as biomarkers, that are known to be associated with changes in DNA methylation and molecular subtypes of bladder cancer. Such candidate genes that we may observe include GATA3, KRT5, KRT20, and others. The molecular subtype categorization of UMUC1 RB1 KO can also be reached, similarly to the first half of my project, through techniques such as western blots (observing what genes are expressed at the protein level), and qRT-PCR (RNA level expression).

Project #2 (Everett):

I aim to test the efficacy of CDK 4/6 inhibitors on RB1 (retinoblastoma protein 1) wild type (WT) and knockout (KO) human BC cell lines. The loss of RB1, a transcriptional repressor involved in phase G1 of the cell cycle, has been associated with the loss of Forkhead Box A1 (FOXA1) and the onset of more aggressive, difficult to treat forms of BC. Using WST-1 assays to quantify cell proliferation and death, I may observe the effects of therapeutics on UMUC1 cell lines in vitro.

Cells of the luminal and basal molecular subtypes are the focus of my work. As noted in Figure 1, these cell types are associated with different patient outcomes and are characterized by unique gene expression profiles. I hope to improve patient outcomes by regulating controls upstream of DNA transcription and by influencing gene expression via CDK 4/6 inhibitors in bladder cancer cells.

FOXA1, a potential influencer of BC cell behavior for its local and global effects on the human genome, is one gene I am interested in controlling as we believe the loss of this luminal marker drives the clonal evolution of basal cells in bladder tumors. The loss of FOXA1 by harmful mutations or deletions, seen in some luminal mutants and all basal BCs, may be involved in a transition of less aggressive BC into more aggressive BC. The methylation of CpG island 99, a regulator of FOXA1 expression, has been shown to “turn off” FOXA1. This control mechanism presents the opportunity to prevent the loss of FOXA1 and to reduce the severity of BC.

We hypothesize that RB1 inhibits DNA methyltransferases (DNMTs) which methylate DNA as has been observed in liver cancer cells. In WT luminal BC cells, we believe RB1 effectively prevents the methylation of CpG island 99 and allows FOXA1 to be expressed. In mutant cells with homozygous RB1 loss, classified as genomically-unstable subtype, loss of RB1 results in CpG island 99 in hypermethylation and thus FOXA1 is not expressed. RB1 KO cells — luminal cells with gene expression profiles partially characteristic of basal cells — may suggest the path taken by luminal cells in becoming more malignant and basal-like.

RB1 also plays a role in cell cycle regulation as a transcriptional repressor. In non-cancerous human cells, the underphosphorylated form of RB1 represses cell cycle (E2F) and apoptotic (E2F1) genes, preventing lysis and the progression of G1 to S-phase. When phosphorylated, the release of the repressor RB1 allows for the transcription of E2Fs and the appropriate proceeding of the cell cycle into S-phase. In cancerous RB1 KO BC cell lines, the lack of RB1 readily permits the transcription of E2Fs, unnecessarily advancing cells into S-phase. At the same time, apoptosis is inhibited by survival pathways.

In non-malignant cells, cyclin-dependent kinases (CDKs) 4 and 6 form a complex with cyclin D. Together, they promote the phosphorylation of RB1 and the transcription of E2Fs. By introducing a CDK 4/6 inhibitor to reduce the function of the CDK/cyclin D complex, the transcription of S-phase genes should decrease. I intend to observe whether a CDK 4/6 inhibitor such as palbociclib is more effective in RB1-positive or negative BC cell lines.

Palbociclib isethionate is a CDK 4/6 inhibitor approved by the FDA for use in the treatment of breast cancer. Its apoptotic effects on BC cells have been recorded in in vitro studies; thus, this therapeutic holds the potential to reduce BC proliferation. Using WST-1 assays, I observed the effect of the drug on the proliferation of UMUC1 WT and RB1 KO BC cells. Our preliminary data suggest that the RB1 KO cells do not respond to our drug in the same way as WT cells. However, we need to perform follow up experiments with drug concentrations more focused around the IC50 value (1.5μM) of palbociclib (Figures 3, 4). Otherwise, we cannot definitively say that RB1 status dictates palbociclib efficacy.

Figure 3. Measurement of proliferation of UMUC1 RB1 KO F cells in response to palbociclib isethionate.
Figure 4. Measurement of proliferation of UMUC1 WT cell in response to palbociclib isethionate.


Worms Caught in 4K- Klabonski Lab

Hello everyone! My name is Sarah Adams and I am a rising senior. I am majoring in Biochemistry & Molecular Biology and minoring in Spanish. That is me, next to the microscope where I snapshot my worm friends in HD. 

This summer, I have been working with a model organism known as Caenorhabditis elegans. C.elegans are microscopic worms which are 1 mm in length and are the perfect model organism because we can begin understanding human proteins and diseases by studying similar proteins in C.elegans. I am studying a C. elegans growth factor protein known as TGF-B/DAF-7, which is trafficked down the dendrites of neurons and released to promote growth, development, and lots of other important processes in worms. We are specifically interested in this TGF-B/DAF-7 because there is a similar protein in humans, known as GDF-11. GDF-11 has shown to be important to neurogenesis and synaptogenesis, which may be helpful for treating neurodegenerative diseases like Alzhemiers and Parkinsons.


I am trying to find out what machinery in the neurons of worms transports TGF-B/DAF-7 to the ends of dendrites. I have been conducting RNA interference (RNAi) experiments to “turn down” genes involved in extracellular vesicle trafficking to see if these genes are involved in transporting TGF-B/DAF-7. Over the summer I will be using RNAi on 7 different genes: che-3, klp-6, daf-10, unc-101, rab-2, rab-7, and rab 11.2. 

The layout of the RNAi experiment that I have been conducting this summer consisted of culturing the genes on (Tuesday/ Wednesday), seeding them on RNAi plates (Wednesday/ Thursday), picking adult worms for them to lay embryos (Friday) then picking second generation of embryos (Monday) and finally taking images of L2s (Tuesday) on our imaging microscope. 

Negative Control
Positive Control (GFP “knock-down”)

To analyze the images, I have been using a software program called ImageJ to quantify fluorescence of a TGF-B/DAF-7 signaling reporter in my worms. Bright fluorescence (like the negative control above) means everything is fine; TGF-B/DAF-7 is getting where it needs to go. Decreased fluorescence (like the positive control above) means signaling is gone; TGF-B/DAF-7 is not getting where it needs to go. 

For the rest of the summer, I am going to continue doing RNAi experiments and putting together the data for the first set of genes. Additionally I will be doing a second trial with the rab-7 and rab 11.2 genes to analyze the fluorescence as well as understand the unique characteristics that these C.elegans express when these genes are knocked down.  

This summer research has been very rewarding in learning various techniques, more about C.elegans, as well as the effect this research can have on human neurodegenerative diseases. I believe coming into research one thing that I expected is that the results I got would always be perfect and easy to analyze, but that is obviously not always the case. However, from this experience, I believed I gained an understanding on how to better project methods, data analysis and interpretation as well as the importance of patience as well as support from lab members. Overall, I have had fun these past 6 weeks of researching in Dr. Klabonski’s lab on TGF-B/DAF-7 and the C.elegans, while gaining valuable skills and experience this summer. 

Hi! My name is Nora Stenson and I am a rising senior. I am majoring in Biology and minoring in Studio Art. Below is me with the ChemiDoc, which I use to take pictures of my gels almost every day! We have a love-hate relationship.

This summer, I am working to create a plasmid that contains a human growth factor within the family TGF-B called GDF-11. We are trying to insert GDF-11 into a plasmid because it is the ortholog to the C. elegans TGF-B called DAF-7, both of which have been shown to have important effects on neurogenesis, synaptogenesis and aging. If I am able to successfully create this plasmid and have it expressed in C. elegans, this new strain of worms can be used in experiments to further the validity of results–such as Sarah’s–in direct relationship to humans! 

How am I making this plasmid? Through a series of copying, cutting and pasting! I want to include three main components in my plasmid: GDF-11, a DAF-7 promoter, and green fluorescent protein (GFP). GDF-11 is the human growth factor that we are trying to introduce in this new strain of worms; the DAF-7 promoter will direct GDF-11 to the correct cells in the worm; GFP is green fluorescent protein, which allows us to visualize our protein within the worms under a microscope.

To “copy” the pieces, I used polymerase chain reaction (PCR) to amplify them from various existing plasmids. Then, I can use restriction enzymes to “cut” the PCR product and the recipient plasmid and “paste” them together using DNA ligation. I am also able to do all of this virtually in advance using a software program called SerialCloner, where I can do hypothetical PCRs, restriction digests and ligations. 

For example, this screenshot of SerialCloner below shows the plasmid I wanted to amplify GDF-11 from originally in purple, with SacI and NsiI acting as restriction sites. The picture below the plasmid shows the number of base pairs this part of DNA should be as a product of PCR in the top left corner, which I can use to identify on a gel.

So far, I have successfully isolated the model plasmid I want to build into and GFP. GDF-11 has proven difficult to amplify by PCR and has required many changes in primers, templates, timing and temperatures. As I troubleshoot my way through amplifying and isolating GDF-11, I have also been using RNAi as Sarah has to collect data on the effects of PDI-1 and PDI-2 in first generation Cul5 6.1; rrf-3 C. elegans. Many of my trials have shown that fluorescence is impacted by the knocking down of PDI-1, indicating its possible significance in the trafficking of DAF-7.

Overall, I have found participating in research this summer to be eye-opening. It has taught me how frustrating science can be, but also how rewarding small successes are in the grand scheme of my project. At the beginning of the summer, I had a plan that I believed would be carried out smoothly, when in reality I have been troubleshooting for 6 weeks. However, I have enjoyed each step of the way and have become much more resourceful and goal oriented through this experience.