Investigating Zinc Homeostasis as a Potential Mediator of PDAC Metastasis
Pancreatic cancer is one of the deadliest variations of cancer, mostly due to it high metastatic potential and poor early screening rates. My aim is to investigate a possible mechanism by which PDAC cells metastasize.
Recent Comments
One of the experiments that I've been running to assess the migratory potential of cells has been quite challenging to set up. Based on literature I had read prior, I was expecting a certain concentration of Zn not to be cytotoxic to the cells, however, I kept getting results where the cells would all be dead by the end of the experimental period. I've had to remedy this by doing toxicity assays and reducing the overall concentration of Zn. That is to say, even in science where there is an expectation of reproducible results, sometimes data will contradict the published information and then is it is your job to assess what the best course of action is from there.
I have found my peers in the lab to be the most useful resource for my project. While reading experimental procedures is good so you know what you're doing generally, having someone who can give you the practical tricks and reasoning behind the procedures has been really helpful for understanding and gaining proficiency in a number of techniques. Just recently, I learned a new technique that I'm planning to use in another project that I'm undertaking, and I was able to gain a strong understanding of it through peer mentorship. I've always found that that type of learning has been really conducive to my ability to absorb information, so it has been very good to maintain that environment while doing research this summer.
My current hypothesis is that the nutrient deprived environment that you need to examine migratory behavior results in increased Zn sensitivity, and that is why the concentration is more cytotoxic to the cells. I'm planning to rerun the experiment at in a slightly higher nutrient environment and then just normalize the data with a proliferation experiment
The prevalence of genetic variants classified as “Variants of Unknown Significance” (VUS) among patients in the Morgan Stanley Children’s Hospital Program for Cardiomyopathy, Heart Failure, and Transplantation is remarkable. While it is expected that children are born with genetic variants due to the inherent nature of physiology, it is astonishing that, despite the advanced technology available today, our understanding of these genetic mutations and their impacts remains limited. Genetic testing on children presenting with various subcategories of cardiovascular diseases often cannot determine whether the genetic variant they possess is the cause of the disease. This uncertainty complicates treatment, as it is more challenging compared to treating children whose genetic variants are identified as either pathogenic or benign. When a genetic variant is classified as pathogenic or benign, physicians can more accurately determine whether the child's symptoms are due to their genetic sequence or an underlying condition, thereby facilitating more targeted and effective treatment strategies. My work has underscored the significant prevalence of "Variants of Unknown Significance" still present in clinical practice, emphasizing the critical need to enhance genetic research and expand our knowledge base. Such advancements are essential for improving diagnostic accuracy, developing targeted therapies, and ultimately enhancing patient care.
As I delve deeper into the fields of genomics and pediatric cardiology through my work, I have increasingly relied on resources such as Google Scholar and PubMed. These platforms have proven invaluable in providing extensive information, allowing me to understand the complexities of these disciplines without needing to consult my mentor too frequently. The wealth of research articles, case studies, and reviews available on these databases has significantly enhanced my knowledge of more subtle aspects of the fields. This continuous learning process not only enriches my experience but also empowers me to contribute more effectively, particularly as I prepare to begin publishing my own research.
I totally agree with your second point. There is such a wealth of data sets and information that are freely available online that can provide such meaningful insight into any topics, but they are often not taken advantage of as much as they maybe should be. My lab also holds journal club where we read a paper that is not necessarily connected to our individual projects, and I've found that experience in trying to critique and understand literature that isn't inherently in your field of expertise to be a great exercise.
One of the experiments that I've been running to assess the migratory potential of cells has been quite challenging to set up. Based on literature I had read prior, I was expecting a certain concentration of Zn not to be cytotoxic to the cells, however, I kept getting results where the cells would all be dead by the end of the experimental period. I've had to remedy this by doing toxicity assays and reducing the overall concentration of Zn. That is to say, even in science where there is an expectation of reproducible results, sometimes data will contradict the published information and then is it is your job to assess what the best course of action is from there.
I have found my peers in the lab to be the most useful resource for my project. While reading experimental procedures is good so you know what you're doing generally, having someone who can give you the practical tricks and reasoning behind the procedures has been really helpful for understanding and gaining proficiency in a number of techniques. Just recently, I learned a new technique that I'm planning to use in another project that I'm undertaking, and I was able to gain a strong understanding of it through peer mentorship. I've always found that that type of learning has been really conducive to my ability to absorb information, so it has been very good to maintain that environment while doing research this summer.
Some immediate expectations I have for my research project is to begin data collection. We have completed setting up the experiment, and are now ready to recruit participants and begin collecting data. Our research is a part of a larger scientific study on human cognition, specifically in areas of perception, attention, visual mental imagery, and imagination. I do plan on working on the research project throughout the year, with the expectation of finishing data collection by the end of August, and then data analysis and concluding the project by November. I plan to stay in the Living Lab for all of next year, and will either join a different project for the next summer, or conduct my own independent project.
The overarching question for our research project is "can we know what you know?" Essentially, are we able to understand the subjective experiences of a person? This research question aims to answer many fruitful questions, whether on a smaller scale or on a larger scale. In terms of a smaller scale, we will determine if the iSDT (introspective signal detection theory) model holds validity, and if it can surpass the current SDT (signal detection theory) model. Validating the iSDT model can help bridge the gap across studies of consciousness, metacognition, and visual mental imagery. On a larger scale, understanding subjective experiences can be immensely helpful for the scientific community, as well as in various settings, such as the for physical or mental health care -- where, for example, a doctor is able to better understand the subjective experience of pain that the patient self-reports. In other words, it may be able to provide a measure of verifying introspective subjective measures.
It seems like you are moving in a promising direction on the experimental set-up, and I look forward to seeing how your work progresses. The future directions also seem quite interesting.
Looking at expectations for STEM projects is always a bit difficult because regardless of your expectations, if the data is not interesting, the is not interesting. While this could mean more experiments with better parameters need to be completed, but sometimes projects just run their course. On the flip side, if the data is great, then that opens up a whole host of different opportunities. Currently, I am working on my project with a PhD student, but the approach is mostly at my discretion. I have some promising initial findings that suggest that my protein of interest may help to increase cellular migration, but I will need to continue into some more technically advanced experiments that involve creating a knockout cell line to see if those initial findings are supportable. If it turns out that they are, then there is a possibility that I could publish a paper on the topic.
Since pancreatic cancer is often not found until it migrates to other organ sites, it is often a very challenging disease to treat. Due to this understanding, possible mechanisms that allow cells to migrate more effectively is important for understanding the overall scope of the disease as well as creating methods for earlier detection.
Given that my project deals mostly with (ethically sourced) urine samples and chemicals, I think the biggest ethical issue that I deal with on a daily basis in in the collection of data. As we run the same test on many samples, we routinely encounter outliers that do not fit our expected results. It is then up to us as researchers to decide whether those outliers are a result of human error or a measurement that truly limits our findings. While it is easy to chalk it up to human error, it can create potentially disastrous outcomes in the long run. As such, my research group has taken care to run adequate further testing on any outliers that arise to ensure that we feel fully confident in the data that we collect.
In a "basic science" project, it is hard to consider alternative viewpoints. In fact, ideally, a researcher would probably not have a viewpoint at all and allow the data to speak for itself. However, I have often heard experienced scientists refer to their projects as stories as they piece together the parts that create a full narrative of whatever they investigate. Much like writers with a literary narrative, it can be for scientists to "kill their babies," or discard pieces that they have spent time and energy fitting into the story. Yet over the course of the past couple weeks. I have come to realize that that is a necessary part of truly objective science; it is the only way to ensure that the story being presented comes from an objective viewpoint, rather than the scientist's own.
I think your point about story crafting in science is quite interesting because often times scientists have to balance presenting their objective results but also making those results seem interesting so that the information becomes more widely spread through publications or conferences. Obviously, if a breakthrough is made the data will speak for itself, but it largely is the titles or headlines that will circulate in the wider public. This makes the story telling aspect becomes even more important so that the actual results are what is understood and presented, not confusion or misinformation surrounding the story telling.
At my current stage there aren't really many ethical concerns since I'm only working with cultured cell lines and bacteria, but as I continue into the more advanced stages of my research, I will eventually begin to use mice animal models to examine my hypothesis about zinc homeostasis in vivo. This obviously has some ethical concerns due to working with living creatures as test subjects. However, this process is heavily controlled to ensure the human treatment of the animal at all times. Looking more broadly and into the future for next summer since I'm hoping to interact with patients, understanding how the past has affected their relationships with the healthcare system will be important.
Science is in a lot of ways very collaborative, not only on the smaller scale within the individual lab environment but also on a larger scale. When I began my project, I read a lot of existing literature on zinc homeostasis and metastatic characteristics of pancreatic cancer cells to try to understand how others had approached similar problems. However, I've found that the main source of alternative inputs has come from other people in the lab where they can provide alternate directions from which to tackle the problem.
Through interactions within the Laidlaw community, I have recognized that my major in Urban Studies, Environment & Sustainability inherently intersects with other fields like public health, economics, sociology, engineering, linguistics, and so on! These disciplines, although distinct, must work in tandem with other subjects by introducing innovative methods, concepts, and ways of thinking. Conversations with peers from different disciplines have broadened my perspective, encouraging me to think more holistically about urban planning.
For example, my project's focus on GIS, maps, history, and the cultural influences of people pushes me to think about how environmental scientists play a role, how an anthropologist might approach certain things, and how an engineer would go about building an element of my work. All of these social dynamics of urban space are integrated with something else. Hence, I am eager to embrace these interdisciplinary approaches not only to enrich my research but also to enhance its practical applicability.
I totally agree that urban studies is an incredibly interdisciplinary field that really encapsulates how the intersection of fields can create better results and how the incongruity of those fields can cause unforeseen problems in the future that can't be solved by just one discipline. I'm looking forward to hearing about your approach to the project!