Week 3 - Ben Grodner

Another week gone by, and summer is really starting to come into full swing. As the temperatures rise, it's been important to get outside early and avoid the muggy afternoon heat. Work has also started to heat up as things start to fall into rhythm. This week I had my first experience in the operating room! I got to scrub in for the first time and shadowed Dr. Rodeo through three arthroscopic joint surgeries. The first surgery was a set of meniscus sutures to decrease the mobility of a torn section of the cartilage. The second brought a torn rotator cuff back into place against the joint. The third surgery was an anterior cruciate ligament (ACL) replacement by transplant with a hamstring tendon.

One of the first things I noticed about surgery was how coordinated the actions of each person were. It was like a finely choreographed dance where each person has an essential role as supporting member to the lead (Dr. Rodeo). It was impressive to see how finely tuned everything was. Largely, the preparation including incisions, and setup of arthroscopy was not done by Dr. Rodeo, but rather by other staff, the PA, or the resident. Dr. Rodeo would sweep into the room at exactly the moment when the dangerous or difficult step was to be taken. Again, as in the clinic, Dr. Rodeo's exhaustive knowledge and experience showed through everything as he calmly dealt with small missteps or unexpected events all while educating the resident thoroughly and giving over key actions for their learning benefit. I was also impressed by the general atmosphere of calm combined and alternated with intense focus.

The precision of the suturing techniques was impressive especially in the meniscus tear. Six stitches were placed in a precise pattern at short intervals in the torn section and secured to an anchor in the bone. The precision was especially impressive because of the confusing logistics involved. Every step had to be performed in a precise order with the right tool, or none of it would have worked. This was largely due to the use of arthroscopy where only three generally small incisions were made. In the rotator cuff surgery, I was struck by how much the techniques resembled carpentry and sewing. There were four anchors bored into the humerus using a hammer and awl and the suturing was performed in a clever pattern to pull evenly on the torn tendon and suck it back to its correct position on the bone. The most exciting surgery was the ACL replacement, which had the most steps and was therefore logistically challenging. The removal of a hamstring tendon happened so quickly, I almost missed it. The tendon was prepared by folding over several times and wrapping it with suture material. There were sutures attached to each end of the now ligament. A hole was drilled through the femur again with surprising quickness, and measurements were made on the depth of the hole. Then a button was attached to the end of the constructed  ligament at the correct length and the whole system was slid through the hole until the button just passed the end of the hole. Then the button was rotated to secure the built ligament. A second hole had been bored through the humerus and the tendon was secured at the correct tension using a plug in the hole and an anchor in the bone. All in all, an incredible procedure to witness. Again, it was all performed in such a state of calm, I hardly realized when something dramatic was happening (like removing a hamstring or boring a hole in the femur).

Watching the "dance" in the OR I realized that if I were to design any system for OR use, I would have to take into account the logistical nightmares I witnessed. Research has moved forward this week as I got trained on the local fluorescent microscope and have begun to stain samples and prepare slides for my bacterial assay. I am looking to start building a list of possible taxa in joint infections to build a generalized probe set for FISH.

Week 3 - Leigh Slyker

One of the most interesting cases this week, interestingly enough, was not a plastic surgery. We had a light day in the OR, and had the opportunity to shadow an abdominal aortic aneurysm repair surgery. Prior to a rushed Google search, I had no idea what this surgery consisted of, but seeing that it would be performed under X-Ray, and simply due to its novelty, I was quite excited to see what the procedure entailed. However, due simply to the complexity of the operation, it was difficult to see exactly what was going on. That is, until the device representative walked in...

Bringing with him 30 or so years of experience with vascular grafts, the representative was more enthusiastic in explaining the procedure than any surgeon we had yet encountered. This was possibly due to the fact that he was, unlike the surgeons, merely providing feedback from the sidelines. Still, he was able to explain every part of the surgical process, from how they used reconstructed 3D renderings from CAT scans to figure out the best sizing and placement for the graft, to how the surgeons were able to deploy, adjust and double check the graft.

Perhaps the funniest moment of the whole operation was that after hearing that we were biomedical engineering students, the representative excitedly said something like "oh well then you can ask me all about pore size and wall diameter!"

.. and ask I did, although perhaps not as much as I would have liked.

Unfortunately, I got called up to lab during the middle of the procedure, so I missed the most exciting part of the surgery. When I came back to the OR, the graft was already securely in place, and they were just double checking and closing.

Still, the time spent in lab yielded some albeit incomplete mechanical testing data, which I will have to take as a consolation prize.  

Week 3 - Alex

Week 3

Being at the end of the program, I feel comfortable saying the last two weeks may turn out to be one of the more consequential experiences of my Ph.D. Not because of what I learned, but because of my exposure to modern cardiac EP modeling tools. The first two days focused on machine learning and data mining. These lectures were less informative for me, as I took a machine learning course last year. I was still far from understanding all of the math in the data mining lecture. However, I was aware of most of the tools, and knew where I could look to learn more about them.

Wednesday through Friday focused on applying FEniCS to solve multi-cell cardiac EP problems, then applying those tools to a summer project. This was the portion of the course that I think will have the biggest impact on my future research. I am working with two students to develop and probe a multi-cell microtissue and whole heart EP model for arrhythmic behavior after drug application. 

This project requires the use of FEniCS, Docker, and a cell model repository called CellML. Both FEniCS and CellML are new tools to me. FEniCS, as I mentioned in my week 2 post, is a fast C++-based PDE solver with an intuitive Python wrapper. Additionally, FEniCS solves single-cell ODEs in a fraction of the time of my current implementation. It allows for easy implementation of new single cell models into a micro-tissue, and hopefully a whole heart model. While scaling up from the single cell model wasn’t on my radar before this program, it may become one of the Specific Aims for my thesis after this project. 

The CellML repository includes hundreds of cardiomyocyte ODE systems, implemented in a format called CellML. A research scientist at Simula shared a module with me that can convert any CellML cell model to a FEniCS-readable Python file. This tool will enable me to make comparisons between multiple models, and run fitting algorithms to compare the conductance differences between different cell models. For example, this may be important as many people are interested in understanding the differences between iPSC-derived CM models and mature human CM models. 

Finally, Docker is a tool that is used to ensure complex programs with many software dependencies can be run on any computer. It works by running a virtual environment with all dependencies for a program. This is particularly helpful for FEniCS, as it’s a large and difficult-to-install software package. Also, it is possible to create a Docker environment that can run, and plot all of the figures for a given simulation. This can be used to address the issue of reproducibility. For example, I could create a Docker environment (called an Image) that anyone could download and run on their own computer – the image would run any simulations and plot all of the figures from a published paper.

I expect that my experience working on a summer project with FEniCS, CellML, and Docker will set me up to write a strong thesis proposal by next Spring.

Week 2 - Alex

I got to Oslo on Friday, and spent the weekend touring the city with my brother. Before jumping into the science, it’s worth mentioning something about Oslo:

Oslo is beautiful. The skies are usually blue, and you can see clear water and distant hills from most of the city. The sun is out from 3am to 11pm, so you never really get sleepy. There’s plenty of outdoor seating at restaurants, cafés, and bars around the Oslo harbor. My use of the word “plenty” is deliberate, as every alcohol-friendly outdoor space in New York is shoulder-to-shoulder by 2pm. With all this praise, it’s worth mentioning Oslo is also prohibitively expensive — usually between 130-200% more expensive than New York. It makes Brooklyn feel like a college campus. 

Now for the science:

The keynote talk on Monday was from Michael Regnier. He is a University of Washington professor who researches mechanistic and translational elements of myosin activator 2-deoxy-ATP. I don’t have a strong background in myosin mechanics, but found the translational impacts of his research inspiring.

Following the keynote, we discussed introductory biophysics concepts (Gibbs, mass action, cooperativity), which I learned in a biophysics course this past semester. It was good to review, as it set a foundation for the week. The next day built upon the first, by diving into the biophysics of ion channels, and using these equations to derive systems of ODE equations to construct an action potential. In the end, the first three days built up to implementing an ODE solver in Python to construct a multi-channel action potential.

The next two days focused on heart mechanics and finite element modeling using a PDE solver called FEniCs, developed by Simula. Wednesday was taught by Andrew McCulloch and Kim McCabe, from UC San Diego and Simula, respectively. This is where I started struggling with the material. I had never seen finite elements before, and assumed I could understand the majority of the material. Not the case. I was (sort of) able to grasp the whole heart mechanics bit. I had seen a lot of pressure-volume curves in undergrad, and knew what healthy and heart failure curves looked like. Once we jumped to modeling the heart with continuum mechanics, I was… dumbfounded. My focus and facial guise turned from understanding to existing, committing the important vocabulary to my brain, and hoping no one asked me at lunch, “How do you construct the displacement gradient tensor, again?” At the very least, when the day comes that I need to model something with continuum mechanics, I’ll know some of examples of how it’s used, and what to look up.

The next day was spent on FEniCS, a finite element solver developed by Simula. My introduction to FEniCS and all of its uses may end up being the most consequential thing I learn at Simula. The tool, while difficult to understand initially, enables me to run single-cell simulations in a fraction of the time, and to scale up my research from the single cell to micro tissue, and possibly, whole heart. The day was taxing on the entire group. The programming was new for a few people, and the math was new for almost everyone. While we previously appreciated the opportunity to work on problems during the lecture time, on Friday, we struggled to even attempt the problems. 

I’m excited for Monday. We’ll implement FEniCS to solve tissue electrophysiology problems. I’m hoping that my understanding of single-cell EP problems will flatten the learning curve for FEniCS. 

Week 3- Mariela

What an exciting week!

I kicked off this week with clinic shadowing, along with meetings regarding the clinical trials Dr. Nanus and his collaborators are working with. I was able to meet the team that's the liaison between the doctors and the drug producers and oversee the progress of the many (in the high seventies!) trials the team conducts. They were kind enough to offer to talk more about it with me in the future. Perhaps I will be able to dip in to how drug clinical trials work soon.

Later that week, I was able to observe a robotic cystectomy with a neobladder reconstruction under Dr. Douglas Scherr, a surgical urologist. The surgery consists of removing the bladder using the da Vinci Surgical System, then manually intervening to create a new bladder out of part of the intestine that is then reconnected to the urethra. Before Immersion, I didn't even think that removing the bladder is an option, let alone using robots and making a new one out of part of the intestine.

I was accompanied by a medical intern, who answered my silly questions and walked me through the procedure. The nurse anesthetist also very kindly answered my questions, and we bonded over the fact that he used to be a chemical engineer. It was fascinating seeing from the screen how the robot scissors and cauterizer snipped around the bladder, the camera zooming in and out. The precise motions made it look easy. The whole set up was surreal, almost like a video game. After the surgery was done, I asked Dr. Scherr if the joy sticks had any haptic feedback when he tugged and pulled. He answered that while newer machines did have some feedback, he was very used to the movements and didn't need the feedback. That just blew me away, knowing that all those precise motions he had done with the robot arms were all just well-practiced motions.

At the lab, I streamlined the platelet purification protocol and practice would we would pick cells with the CellCelector. The CellCelector is a machine that does just that: select and pick individual cells for further RNA extraction, in our case. Platelets are much smaller and "stickier" than CTCs, so picking them precisely is a bit of a challenge.

 

Figure 1: Assessing the presence of platelets by immunofluorescence using Alexafluor 647 conjugated Mouse anti Human CD61 antibody, as observed with the CellCelector. Left: Brightfield 20x; Right: Cy5 20x.

Fun in NYC: I was able to snag tickets for The Late Show with Stephen Colbert! I went along with David, who was the actual expert of the show. It was very exciting to see how the show is produced and participating in a live audience. Very worth staying up late.