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Mini Case Response

Detail the variances encountered or anticipated between doctoral and undergraduate experiences, categorizing each distinction as positive, negative, or neutral.

Graduate-level courses differ from undergrad courses; the latter often benefiting from established teaching methods. In contrast, graduate courses may be infrequent and centered on emerging topics, leaving professors unfamiliar with optimal teaching approaches. Students become quasi-test subjects, aiding in refining future teaching methods. This is seen neutrally, aligning with the trial/error aspect of research but may be negative if topics are uninteresting or if professors shift excessive teaching responsibility to students.

Undergraduate work involves solved problems, while graduate work centers on unsolved issues, necessitating self-guided research. This neutrality is positive, fostering self-taught and disciplined graduates, but may be negative if the research lacks personal interest, hindering solution finding.

In STEM graduate courses, the lack of resemblance among peers is inconsequential, with mutual respect prevailing in the shared pursuit of education and cutting-edge research.

Privileges in STEM exist, notably favoring domestic students over international counterparts, leading to potential exploitation of the latter's time and work/life balance.

Mentorship's potential in overcoming racial biases is discussed, with personal experiences negating any racially influenced challenges.

Reflecting on unique contributions, the individual highlights involvement in grant proposals, co-authored papers, research presentation assistance, and mentoring. Additionally, the publication of articles has positively impacted the lab's reputation.

Email Etiquette Example

When Seeking Research Progress Assistance

Dear Dr. Sampath,

I have finished a preliminary version of my machine learning algorithm for feature extraction of biosignals to predict glucose levels. However, I am not clear on how to analyze the results. As per your request, I've included a link to my Google Colab document outlining the implementation of this algorithm and annotated the code blocks with notes from outputs I have obtained. I am referring to literature to help me diagnose the problem and have included a primary paper that I used. I look forward to hearing back from you at your earliest availability.

Sincerely,

Brian Hanson, Jr.

Dream Scientific Job

Apple Machine Learning Engineer

Contribute to solving forefront challenges, participate in advancing foundational research and technology, and explore the positive impact of open-source software development on a global scale. Acquire practical training and collaborate with industry leaders in computer vision, medical computing, scientific computing, data and analytics, and software processes.

Ideal candidates should:

  • Possess a bachelor’s, master’s, or Ph.D. degree in Computer Science or a related field

  • Demonstrate experience in object-oriented programming, preferably using C++

  • Exhibit software development proficiency, such as an active GitHub account, successful school or co-op projects, or participation in programming competitions

  • Have documented contributions to open source software (preferred)

Required Skills:

  • Object-oriented Programming, Software Engineering (design, data structures, version control, etc.)

Current Skills:

  • Object-oriented Programming with C++

  • Programming with C++, C, Java, and Python

  • Parallel Programming with CPUs (openMP, MPI, PREMA) and GPUs (CUDA)

  • Software Engineering

Skills to Develop:

  • Enhance C++ programming knowledge (API and latest features)

  • Improve understanding of data structure (space/time) complexity

Methods for Skill Acquisition:

  • Read tutorials for new skills and concepts

  • Practice coding examples

  • Implement the latest C++ features into research project code

  • Read the documentation about data structures and incorporate them into research project code

Dream Scientific Job - Cover Letter

Apple  Summer Internship Program One Apple Parkway Cupertino, CA

Dear Apple Summer Internship Committee,

I am writing to express my sincere interest in the Apple Machine Learning Engineer position, as advertised on Apple's website. As a highly motivated PhD candidate in Computer Science at Old Dominion University (ODU), I am confident that my academic background, research experience, and collaborative skills align well with the opportunities Apple offers.

Under the guidance of Dr. Sampath Jayarthna at the Neurological Information Retrieval and Data Science (NIRDS) Lab, I have engaged in projects that would prepare me for this position. Through my involvement in various projects at NIRDS, I have honed my expertise in developing and designing algorithms for big data analysis.

My Ph.D. dissertation focuses on the development of machine learning algorithms for the feature selection of viable bio-signals for predicting glucose levels of diabetic patients.

One of my key strengths is my adaptability in utilizing diverse machine-learning techniques. I am well-versed in supervised and unsupervised learning methods and have experience with model deployment in production environments. My commitment to staying abreast of the latest advancements in machine learning ensures that I can contribute fresh perspectives and creative solutions to Apple's dynamic and innovative environment.

What excites me most about the prospect of working at Apple is the company's relentless pursuit of excellence and its commitment to pushing the boundaries of technology. I am particularly drawn to Apple's focus on integrating machine learning into its products to enhance user experiences.

I am confident that my technical expertise, collaborative mindset, and passion for leveraging machine learning for real-world impact align well with Apple's vision. I am eager to bring my skills to your esteemed team and contribute to the next wave of groundbreaking innovations.

Thank you for considering my application. I am eager to discuss how my unique skills and experiences align with Apple's goals. I look forward to the possibility of contributing to your innovative teams.

Sincerely,

Brian Hanson

Dream Scientific Job - Interview Questions

  1. What attracted you to this position, and what contributions can you make to our organization? Response: I am drawn to the Machine Learning Engineer position at Apple because of the company's commitment to innovation and its influence on shaping the future of technology. Apple's focus on integrating machine learning into its products aligns perfectly with my passion for leveraging artificial intelligence to create impactful solutions. My academic background, combined with hands-on experience in implementing machine learning models, positions me to contribute creative and effective solutions to enhance user experiences and further Apple's technological advancements.

  2. What are your professional goals? Response: My professional goals revolve around becoming a leading expert in machine learning and contributing to transformative technologies. I aim to continuously develop my skills, staying at the forefront of advancements in the field. I aspire to make meaningful contributions to innovative projects at Apple, working collaboratively with a dynamic team to push the boundaries of what machine learning can achieve.

  3. What experiences or skills will help you manage projects in our company? Response: My experience in managing projects during my academic pursuits, coupled with my technical skills in machine learning and project management tools, positions me well for success in project management at Apple. I am adept at translating complex technical requirements into actionable project plans, ensuring timely and high-quality deliverables. My ability to collaborate effectively with cross-functional teams and communicate technical concepts to non-technical stakeholders will contribute to the seamless execution of projects.

  4. What is the biggest conflict you have ever been involved in during graduate school? How did you handle the situation? What did you learn? Response: During my graduate school, a significant conflict arose within our research team regarding the direction of a project. I facilitated open communication, actively listened to all perspectives, and encouraged a collaborative problem-solving approach. Through transparent discussions, we reached a consensus that aligned with our collective goals. This experience taught me the importance of effective communication, conflict resolution, and the value of fostering a collaborative and inclusive team environment.

  5. Describe a situation in which you did all the right things and were still unsuccessful. What did you learn from the experience? Response: In a machine learning project, despite meticulous planning and execution, the model's performance fell short of expectations. I learned the importance of acknowledging failures, conducting thorough post-mortem analyses, and iteratively refining strategies. This experience reinforced my commitment to continuous improvement, adaptability, and resilience in the face of challenges.

  6. Please tell us about your research interests and how they fit the organization’s mission/direction. Response: My research interests center around scalable machine learning solutions and their real-world applications. This aligns seamlessly with Apple's mission to integrate cutting-edge technologies into user-centric products. I am particularly interested in contributing to projects related to 3D Slicer-based applications, computational modeling, and end-to-end simulation workflows, areas where I believe my expertise can significantly contribute to Apple's forward-looking initiatives.

  7. What do you look for in your profession and work colleagues? Response: In my profession, I seek opportunities for continuous learning, innovation, and the chance to make a meaningful impact. Regarding work colleagues, I value collaboration, diversity of thought, and a shared commitment to excellence. I believe a supportive and inclusive team environment is crucial for fostering creativity and achieving collective goals.

  8. What are three leadership competencies you possess? Please provide an example of when you have used these to provide effective leadership during a difficult time. Response: I possess effective communication, strategic thinking, and adaptability as key leadership competencies. During a challenging project, I demonstrated effective communication by fostering transparent dialogue, strategic thinking by re-evaluating our approach, and adaptability by swiftly adjusting the project plan. This leadership approach ensured the successful completion of the project and strengthened team cohesion.

  9. Have you ever experienced a situation where you had difficulties getting people to accept your ideas? What was your approach to handling these situations? Response: Yes, in a collaborative research setting, there were instances where my ideas faced resistance. I addressed this by actively seeking feedback, tailoring my communication to resonate with diverse perspectives, and highlighting the benefits of my proposed ideas. Through persistence and collaboration, I successfully gained acceptance for my ideas, emphasizing the collective success of the team.

  10. What types of resources would you require to successfully continue your research agenda? Response: To continue my research agenda successfully, I would require access to cutting-edge hardware, software, and datasets relevant to machine learning. Additionally, collaboration with interdisciplinary experts and participation in conferences to stay updated on the latest advancements would be invaluable. Apple's commitment to innovation and providing state-of-the-art resources makes it an ideal environment for advancing my research agenda.

  11. How would you involve others (students, technicians, etc.) in your research? Response: I believe in fostering a collaborative research environment by involving others through mentorship, knowledge sharing, and teamwork. I would actively engage students, technicians, and colleagues by providing learning opportunities, encouraging diverse perspectives, and ensuring that each team member's strengths contribute to the collective success of the research project.

  12. Please identify your most significant work and why you picked it. Response: My most significant work involves the development of a scalable mesh adaptation software for high-performance computing architectures. I selected this project due to its transformative potential in addressing complex challenges. It required a multidisciplinary approach, incorporating advanced algorithms, data structures, and collaborative efforts. This work showcases my ability to tackle intricate problems and contribute to advancements in scalable computing.

  13. Tell us about your teaching methods, philosophy, and goals. Response: My teaching philosophy centers around creating an inclusive and engaging learning environment. I emphasize practical application, critical thinking, and hands-on projects to enhance comprehension. My goal is to instill a passion for continuous learning, providing students with the skills and knowledge necessary for success in the rapidly evolving field of machine learning.

  14. What methods have proven effective, and what have you learned from the experience? Response: Effective teaching methods include interactive discussions, real-world case studies, and project-based learning. These approaches cater to diverse learning styles and promote a deeper understanding of the material. I have learned that fostering an interactive and collaborative classroom atmosphere enhances student engagement and facilitates a more comprehensive grasp of complex concepts.

  15. Describe strategies you have used to create an inclusive learning environment for your students. Response: I promote inclusivity by encouraging open dialogue, respecting diverse perspectives, and incorporating a variety of teaching materials to cater to different learning styles. I actively seek feedback from students, adapt my teaching methods based on their needs, and create an atmosphere where every student feels valued and included in the learning process.

Biomed Seminar & G-Club Summaries

September 14, 2023 - Dr. Krishnanand Kaipa Presentation

Biologically Inspired Robotics: From Animals and Insects in Nature to Autonomous Robots

Summary

Dr. Krishnanand Kaipa's presentation delved into the realm of biologically inspired robotics, exploring the adaptation of animals and insects in nature for the development of autonomous robots. These robots are crucial for real-world applications, ranging from supply movement across uneven terrain to aiding in disaster scenarios. The study encompasses the entire animal kingdom, focusing on morphology, actuation, and control as key traits. Morphology involves analyzing the body plan of natural creatures, considering aspects such as kinematic structure, limb specialization, and body segment geometry. Examples include amphibious robots inspired by freshwater turtles and self-righting robots inspired by horseshoe crabs. The presentation highlighted developmental robots influenced by infant learning, employing machine learning and simulations. While the research showcased promising applications in medical and emergency contexts, some aspects lacked clear motivation, such as amphibious robots and those inspired by elephant movement. Despite this, the overall presentation demonstrated the potential of biologically inspired robotics in addressing complex tasks.

 

September 21, 2023 - Dr. Balasubramanian Ramjee

Resorcinarene Cavitands as Nanoscale Building Blocks and Nanoparticle Stabilizers

 

Summary

Dr. Balasubramanian Ramjee's presentation centered on the fabrication of nanomaterials using resorcinarene cavitands, particularly focusing on their application as building blocks and nanoparticle stabilizers. The discussion delved into the creation of nanocapsules with distinct morphologies, emphasizing their importance in various fields such as drug delivery, imaging, catalysis, and sensing. The presenter highlighted the challenges associated with creating complementary biochemical sensors and the development of resorcinarene cavitand-based surfactants to stabilize metal nanoparticles. While the content was challenging for a Computer Science student with limited chemistry background, the presenter's enthusiasm and engagement were commendable. However, the use of excessive jargon hindered the accessibility of the presentation for an interdisciplinary audience.

 

September 28, 2023 - Dr. Howard G. Adams

 

Mentoring Up

Dr. Howard G. Adams delivered an excellent presentation on the concept of "Mentoring Up," providing practical advice on finding mentors who can guide not only in academic matters but also in career and life decisions. He emphasized the significance of identifying mentors who hold positions one aspires to attain, highlighting the mutual benefits of the mentor-student relationship. Dr. Adams shared insights into the value of approaching mentors with a willingness to learn, respect for their time, and a commitment to applying their advice. The presentation conveyed the importance of students taking the initiative in establishing mentorship connections and showcased a real-life example of successful mentorship.

 

October 5, 2023 - Dr. Amay J. Bandodkar

New Classes of Wearable and Implantable Sensors and Energy Devices for Broad Healthcare Applications

Summary

Dr. Amay J. Bandodkar's presentation focused on the development of wearable and implantable sensors and energy devices for diverse healthcare applications. The discussion covered various systems, including flexible devices, tissue-like devices, neurochemical sensors, and sweat-activated batteries. Dr. Bandodkar emphasized the challenges in developing biocompatible sensors and presented innovative solutions, such as biofuel cell-based sensors and wireless, battery-free monitoring devices. The presenter effectively communicated complex topics to an interdisciplinary audience, providing practical examples to illustrate the potential applications of the research. Questions were raised about the transition to human trials, integration into healthcare, and performance under diverse conditions, posing challenges for future research.

 

October 12, 2023 - Dr. Kevin Muchiri

Navigating the PhD Odyssey: A Personal Journey in Engineering Management and Systems Engineering

Summary

Dr. Kevin Muchiri shared valuable insights and practical advice based on his personal journey in pursuing a PhD in Engineering Management and Systems Engineering. He discussed the importance of discipline, routine, and mentorship in navigating the challenges of a PhD program. Dr. Muchiri emphasized the significance of networking, asking thoughtful questions, and taking deliberate steps to approach potential mentors. His presentation underscored the value of time management and proactive decision-making in academic and professional pursuits. Dr. Muchiri's personal anecdotes and advice on addressing workplace conflicts resonated with the audience, offering practical guidance for those on their own PhD odyssey.

November 2, 2023

Dr. David Gauthier Fish antics: Understanding dynamics of complex wildlife systems

 

Dr. Gauthier completed his PhD and post-doctoral studies studying bacterium infecting striped bass (or rockfish). Striped bass have high ecological and economic importance in the Chesapeake bay. The bacteria in particular are mycobacterium spp, which are slow-growing, aerobic, non-spore-forming, non-motile rods. A new species of this bacteria was discovered in the early 2000s called M. shottsii (implicated in striped bass skin lesions and visceral disease). This species is the worst laboratory bacterium in the world due to the time required to grow and culture them. It was discovered that this bacteria equally infects both genders of fish up to age 7 but seems to infect males (that are older than 7 years) more frequently than old females. Force-of-infection models for bovine tuberculosis were applied to apparent prevalence data for CB striped bass. This essentially involved fitting a model to the data and seeing if including a mortality variable would improve the model fit. The result supported the existence of disease-associated mortality. To better understand the infection of this bacteria, tag-and-release studies were conducted in Rappahannock river during the years 2005-2012. Diagnosis of infections were made on the basis of skin lesions. Photographic documentation was taken at release and return, with the conclusion of this study being that chronic disease progression is in the order of 1-2 years in these fish.

 

An essential question was posed: why are striped bass in particular getting infected by this bacteria? Factors that would enable this phenomena must include: the environment, pathogen, and host. One theory was that mycobacteriosis is a stress disease. As these fish undergo stressful circumstances, they are more prone to infection. Another theory was the temperature-oxygen "squeeze" hypothesis. Bass prefer temperatures less than 25 degrees Celsius. In the winter, this is not a problem. In the summer, they will take refuge in deep channels. Plankton, which produce oxygen, bloom at water surface. They sink to the bottom at death and decompose; therefore, there is less oxygen in deep channels. This is possibly fertile ground for mycobacteriosis to infect rockfish. A temperature effects study was also conducted. Fish were infected with m. shottsii or m. pseudoshottsii; and after 4 weeks, water temperature was increased. The results did not support exacerbation of disease with elevated temperature. In fact, as temperature increased, the density of bacterium either remained the same or decreased. Results indicated that life near the thermal maximum of the host may limit effects by the pathogen. Dr. Gauthier also now conducts research as part of a tick research team for disease ecology. They have collected over 250,000 ticks across Hampton Roads with the goal of exploring dynamics of three amblyomma/rickettsia host/pathogen systems. Ticks with these pathogens have been in VA for the past 30 years, causing typhus and other diseases in humans when bitten. After a long period of study, the following was understood for Ixodes Affinis ticks: they reside in clear geographically separated clades, their populations expand via short distance dispersal on mammals in all life stages (especially deer as adults), and their high gene flow is facilitated by abundant, connected forest habitats. The following was understood for Amblyomma Maculatum ticks: they have low gene flow among sites but widely distributed haplotypes, long-distance dispersal of immature ticks via birds or adults on large mammals may found new populations, their populations are maintained in the short term by mammals in successional habitats, and ephemeral successional habitats prevent short-distance dispersal events that would connect geographically close populations.

 

I thought that this was a very interesting presentation, although I wish that Dr. Gauthier did a better job at explaining to what degree striped bass impacts our society and how much of an impact these bacteria cause. Such great efforts have gone into understanding the infection but why? What knowledge are we hoping to gain and what are we trying to improve/prevent? Although he mentioned that rockfish play an important role both ecologically and economically, the motivation behind this specific work was not clear. The tick research however, was clear in that we need to understand how these populations are spreading so that we can prevent an outbreak of the diseases that these ticks cause. Of course, my thoughts immediately go to creating cures for the diseases or establishing immunity, but it is much wiser to handle the source of the problem. The only suggestion that comes to mind is the research that one of Dr. Gauthier's PhD students is currently conducting - understanding the migration patterns of the tick hosts, and correlating that to the tick populations. I would be very interested to see what all this research has helped us conclude years from now. 

November 9, 2023 - Dr. Christian Reidys Towards an information theoretic framework for data analysis

Dr. Reidys's research mission is to bring math closer to biology. His lab's approach considers the fact that real world problems generate structured data. This structure drives mathematical theory. This theory leads to algorithmic approaches to real world problems and when applied, more structured data is generated. His work introduces a new perspective regarding the analysis of Multiple Sequence Alignments (MSA), representing aligned data defined over a finite alphabet of symbols. The framework is designed to produce a data-driven semantics manifesting in a block decomposition of an MSA, where each block is comprised of sequences exhibiting a certain site-coherence. The key component of this framework is an information theoretical potential defined on pairs of sites (links) within the MSA. This potential quantifies the expected drop in variation of information between the two constituent sites, where the expectation is taken with respect to all possible sub-alignments, obtained by removing a finite, fixed collection of rows. Genomic alignments are observed from a dual perspective using hamming DI-stance (number of distinct sites between a pair of genome sequences) and Hamming TRI-stance (number of distinct sites among a triple of sequences). Genetic alignments are considered to be topo-arithmetical objects. This dual structure can be used to forecast watershed moments in viral evolution, such as COVID-19. The way the structure of an object varies in time reflects the strain dynamics in a viral population. This can be tested by building an alert system for VOC emergence and validate it on historical COVID-19 data. The information in an object can be understood through homological and co-homological algebra. Weighted homology can be computed efficiently. This anomaly detection in an MSA is composed of inverse fold solutions of a fixed tRNA secondary structure, where the anomalies are represented by inverse fold solutions of a different RNA structure. In conclusion, homological algebra, topology, and information theory can come together and shed light on evolving alignments. The methodologies and theory developed are setting agnostic being widely available to any kind of data array. An understanding akin to quantum mechanics - but for the information theory of data arrays is currently in development.

 

While Dr. Reidys has a good presentation style, I unfortunately did not understand most of this presentation (from a Computer Scientist perspective), as it was biologically and mathematically heavy. I cannot shed any insight on its impact or what can be done in future efforts regarding this research, aside from a suggestion to utilize this methodology in studying the evolution of other viruses as well.

G-Club Presentations November 9, 2023

Quentin Richards - Exploring Dielectric Elastomer Actuators as Artificial Muscles for Powered Prosthetic Limbs

There are nearly 2 million people living with limb loss. A study from 2019 shows that people discontinue prosthetic use after 6 months. Different powered prosthetics can be expensive and are constrained by the fact that they're usually created for very specific purposes. If the motors of a powered prosthetic are replaced, then the best alternative is an actuator that models the human body. Actuators should have low cost, fast response time, and high load-bearing capabilities. One of the challenges of conventional actuators is the fact that multiple components are needed for standard rigid actuators (a motor, gearbox, encoder, etc.). Quentin's work focuses on using dielectric elastomer actuators as artificial muscles. He developed a transtibial prostethic design in CAD. His next steps are to cut DEAs into circular shapes using a laser cutter and to construct a high voltage driving circuit for DEAs. Quentin did a great job presenting, showing clear progress in his work and its importance/impact in achieving the end goal of his PhD.

 

Marcus Easterling - Early Detection of Non-small cell lung cancer

NSCLC accounts for 80-85% of all lung cancers. SCLC is easier to diagnose but harder to treat. They both cause over 130,000 deaths per year. The current state-of-the-art uses low dose computed tomography which is expensive. Marcus's approach to early detection uses carbon SPE which consists of composite electrodeposition, an ssDNA aptamer, targeting miRNAs, and an analysis called DPV for current change. He presented a differential pulse voltammogram that shows that this work has good sensitivity for miRNA-21 and has confirmed viability of a Pd*Au nanocomposite for electrochemical biosensing applications, achieving an attomolar detection limit for the chosen target. Opportunities for improvement include lower sample volumes which will allow shorter analysis times, minimum cross contamination, and enhanced sensitivity/control. Marcus did well overall presenting, showing clear progress in his work and its importance/impact in achieving the end goal of his PhD. I would however suggest that he take more time to explain some concepts since not everyone in the audience has a heavy biology/chemistry background, and there are some aspects of his work that are not easily understandable from the way he presented.

November 16, 2023 - Dr. Rishi Drolia From Listeria Invasion of Host Barriers to Next-Generation Bioengineered Probiotics to Prevent Infectious and Inflammatory Diseases

 

Dr. Drolia has a vigorous research background with the anatomy of the gut barrier. He specifically has studied the impact of listeria monocytogenes, which is a zoonotic pathogen found in ruminants. This pathogen was discovered in food-borne outbreaks during the late 70s and early 80s. High risk foods included sausage, lunch meats, hotdogs, ice cream, and more. When consuming contaminated foods, the pathogen goes through the intestine barrier, causes diarrhea, and reaches both the brain and fetus of pregnant women (leading to abortion and neonatal listeriosis). About 1600 people are infected each year with approximately a 30% fatality rate. Listeria monocytogenes is highly invasive and can cross three host barriers. A Listeria adhesion protein (LAP)-medicated translocation technique was developed to combat this pathogen. It manipulates innate epithelial defenses and induces intestinal barrier dysfunction to promote bacterial translocation. It was tested with gerbils since they are the most human-relevant compared to other mice. Gauging host-pathogen interactions led to engineering next generation bio-engineered probiotics that exclude pathogens through competitive exclusion, maintaining intestinal epithelial barrier functions, and contact-dependent immunomodulation. Probiotics benefit gut health, aid in lactose metabolism, and offer many more benefits. Dr. Drolia's lab specifically studied lactobacillus casei and developed a bio-engineered version called BLP. Studies showed that BLP successfully protects mice from listeriosis (as opposed to regular probiotics), succeeding in 92% of cases. Future projects include: (1) a study on host-pathogen interaction at the blood-brain and blood-placental barriers (2) inflammatory bowel disease (IBD) (of which ulcerative colitis and Crohn's disease are two forms). This disease is hallmarked by severe inflammation, diarrhea, and weight loss. Hsp60 was found to increase inflammation and cause barrier dysfunction in IBD. (3) prevention strategies for other pathogens. Dry biofilms are a health hazard. They survive in low-moisture, high-temperature conditions in dry food processing facilities. Studies found that dual species allow biofilms to survive in these conditions. Current sanitization (using isopropyl alcohol) is not efficient. New sanitization strategies must be developed. I liked Dr. Drolia's speaking ability and tone throughout the presentation. I was able to follow and understand some things but there were technical aspects where a lot of biological jargon was used, and these parts were difficult for me to follow. The motivation for his projects and their impact are clear. Since it was tested with mice, I would be interested to know if studies are conducted to prevent the listeriosis pathogen from contaminating food - if anything can be added to food in their production facilities or what measures could be taken to prevent their contamination so that the pathogen fails to survive on the food.

G-Club Presentations - November 16, 2023

Taylor Patrick - Electrical Cell on Substrate Impedance Sensing (ECIS) for characterization of Fibroblasts treated with DOX and PAN Anticancer Drugs

 

Taylor's primary research goal is to monitor and characterize the effect of cytotoxins on wound healing. Part of this motivation includes cancer, which causes 1 in every 6 deaths worldwide. Doxorubicin (DOX) is an anthracycline that is an effective and commonly used anti-cancer chemotherapeutic. A problem is that exposure to DOX can induce senescence and cause permanent cell division arrest. There exists a need for drug discovery and delivery that effectively treats cancer and limits negative short term and long term side effects. Fibroblasts offer a possible solution, as they have been utilized for drug discovery and cytotoxic effects during anticancer treatments. P-anisic acid (PAN) may offer the anticancer effect with less toxicity (senescence) on non-cancerous cells. Senescent cells exhibit morphological changes that can be measured and characterized by Electrical Cell on Substrate Impedance Sensing (ECIS). Future work includes: Synergistic Therapy (co-delivery of multiple known effective drugs may offer notable therapy benefits), data analysis (evaluation of electrical characteristics across multiple trials), and 3D Bioprinting with integrated bioink conductive sensing electrodes. Taylor did well overall presenting but did move a bit fast in some sections so I was not always able to follow the technical aspects of her work. There is a clear goal and progress was shown towards her end goal, with future directions of her research established.

 

Shania Sanderson - Expanding LYMESIM: Simulating Population Dynamics and Tick-borne Diseases in Dermacentor Variablis and Amblyomma Americanum

 

Sandy's research focuses on studying/modeling ticks. Occurrences of tick-borne diseases averages around 52,000 cases per year. Incidences are expected to increase due to the impact of climate change. Shania's research objective is to have continuous active surveillance of tick populations in Hampton roads and to assess the prevalence of ticks carrying pathogens. This involves understanding host interactions. Ticks feed on most vertebrates and have a different host per life stage. There are four different tick species found in the southeastern U.S. The blacklegged tick carries limes disease. A modeling method called lymesim 2.0 is used to predict behavioral trends of this tick in different areas. In a recent study, it predicted similar trends to tick behavior in MN and VA but not NY. The addition of rat behavior modeling improved the NY tick model however. The American Dog tick causes rocky mountain fever. Modeling software ADTSIM 2.0 focuses on modeling interactions between ticks and host types. Shania's research involves making this model more accurate by also integrating predator/prey behavior. Future work includes another tick, haemaphsalis. This tick was recently discovered and is known to reproduce asexually. The diseases it causes are currently unknown. This was a good presentation, as I was able to follow Shania for the most part; however, she also spoke and moved through her slides a bit too quickly. Her research objectives were clearly established along with current/future work. Progress is being made in her research.

Erem Ujah - Ultrasensitive tapered optical fiber biosensor for early detection of prostate cancer

 

Ujah had a compelling talk about his research leading with a fact that 1 in 8 men die from prostate cancer. Digital rectum examination is the traditional method for detecting prostate cancer. Ujah's current work focuses on using fiber optics to provide a less invasive method for detecting prostate cancer. Fiber optics is lightspeed transmission, usually used for telecommunications, that can now be used in bio-sensing. Ujah uses a flame to create a tapered region of fiber optic which allows sensing. microRNA can be examined through urine to provide sensing. He developed a method called the Prometheus fiber fabrication, which uses an air tank and a propane tank to control the flame level. Light moves through the fiber. Some escapes at the tapered region and then merges with light inside the fiber at a certain point. Future work includes increasing sensitivity measurement by placing gold nanoparticles on fiber optics. There were technical difficulties in presenting his work using the projector, so Ujah spoke from memory and used the white board. He did a fantastic job at breaking down problems, and explaining them in simpler terms or using metaphors to help everyone understand his work. His presentation skills are among the best in G-RISE and he established clear objectives with clear progress in his research.

November 30, 2023 - Dr. Leopold Green Design Workflow for Engineering Bacterial Therapeutics to Control Host Immunity Chronic disease is impacting our quality of life globally. It's important to study the global and regional prevalence of multimorbidity in the adult population in community settings. These diseases must be connected to something. Host-microbiome interactions and timmune response is critical in a septic environment. The aberrant and imbalanced signaling dynamics primarily cause a dysfunctional innate immune response, exacerbating pathogen invasion of injured tissue and further stalling the healing process. Dr. Green's lab aims to design smart, microbial theranostics derived from host commensal dwellers. Acute inflammatory response is dynamic and complex. To design biological controllers that regulate the critical divergence of the immune response during septicemia, the intricate differences in immune cell dynamics and coordinated molecular signals of healthy and sepsis injury must be understood. Dr. Green's lab deployed an ordinary differential equation (ODE)-based model to capture the hyper and abundance of monocytes, M1, and M2 macrophage phenotypes, resulting in immune paralysis. The model was fit to in vivo experimental data obtained from a mouse peritonitis inflammation model. Local sensitivity analysis on IL-6 production rate in Neutrophils illustrates a clear divergence of health vs. septic immune response. Using a model-based analysis framework, they designed a biological controller that successfully regulates macrophage dysregulation observed in septic wounds. The model describes a systems biology approach to predict and explore critical parameters as potential therapeutic targets to transition septic wound inflammation toward a healthy, wound-healing state. The lab is also focused on gut, vaginal, and skin applications. Modular components of biosensors allow for fast genetic assembly. The lab engineers living therapeutics capable of sensing localized inflammation and secreting anti-inflammatory effectors. They optimized the two-component sensor for inflammation-associated metabolite, allowing for the logical detection of inflammation triggered IL-22 Secretion. They also use DNA as a material to design a structure to perform any function and incorporate it into organisms, encoding DNA nanostructures into genomes so that they are incorporated into organisms' nanostructures. DNA nanospores are inserted into neuron membranes as artificial passive ion channels, providing instant quasi-intracellular recording through pre-inserted nanopores and repetitive quasi-intracellular recording through DNA nanopores in delicate ex vivo neurons. This also allows for functionalizing nanocages for particle encapsulation (e.g. QDs, AuNPs, cytokines, and other biomolecules). I understood almost nothing from this presentation. While the presenter gave great practical advice for the PhD life and the pros/cons in entering industry positions vs. starting one's own business, he needs to practice presenting to multidisciplinary audiences.

 

G-Club Presentations - November 30, 2023

Christopher Animashaun - Development of biosensors for minimally invasive lactate detection

Lactate is vital to cellular function. It is an indicator of physical endurance, and is used for food preservation (for the prevention of bacteria). Current detection methods are limited in sensitivity to lactate and take a long time to detect lactate (gather results, send to lab, very invasive). There is a need to non-invasively and quickly detect lactate. Christopher proposes to do this with biosensors. A biosensor converts biological/chemical reactions into readable detection signals from substrates in the reaction. Drawbacks of biosensors in literature include: poor electron mobility, expensive material, and the fact that they are based in intravenous blood extraction. Chris' method uses bioreceptors for lactate based on lactate dehydrogenase (LDH) and lactate Oxidase (LOx). His proposed biosensors are more cost-effective and include bacterial nancellulose (BNC) and sweat detection (noninvasive). Clear progress and understanding of the literature are apparent; however, as a Computer Scientist it was difficult for me to follow and understand his method.

 

Alex Hunt - Detection of microRNA-21 for Prostate Cancer Diagnostics

Prostate cancer is the second most diagnosed cancer in the U.S. Annual deaths are about 30,000 between the years 1999-2020. Symptoms for prostate cancer are minimal. Screening is invasive. PSAs have seen limited use for the detection of prostate cancer. A PSA test measures the amount of PSA molecules in a patient's blood. However, PSAs are unreliable, producing false positives and false negatives. There's a need for a reliable and noninvasive test. Alex is exploring urinary RNAs. Advantages include: it's produced by prostatic tumor, collected non-invasively, and are available in large quantities. Alex is looking at miR-21. In his detection method, Alex applied wax to the electrode substrate and found ways to preserve ink for his trials. Future work includes fixing the ink gaps on the electrodes. Clear progress and understanding of the literature are apparent; however, as a Computer Scientist it was difficult for me to follow and understand his method.

 

Zuri Jules-Culver - Next-Generation Bioengineered Probiotics for IBD

Probiotics are found in various foods. They are used for different treatments and are very important for gut health (helps to modulate the immune system). Zuri is focusing on Inflammatory Bowel Disease (IBD). There is a high prevalence of IBD in older adults, leading to cardiovascular disease and respiratory diseases. Zuri proposes a treatment for IBD. She is currently setting up her lab equipment. Future work includes plasmid transformation into bacteria and staining it to confirm that it indeed transformed. Zuri needs to spend more time explaining her proposed method and why she thinks it will work. I don't recall her presenting any work that has been done to address IBD in literature.

 

Layla Rashad - Ant Zombie Fungus

Layla focused on the fungal species ophiocordyceps. It is found in tropical and temperate environments. Spores infect carpenter ants and spread throughout the ants' bodies. The fungus spores attach to the ant's body and takes over neurological function, forcing the ant to move to an area of ideal conditions so that it may mature while the fungus devours the ant. Bulbs grow from the stems of the fungus, eventually bursting and infecting more ants. Other species of this fungus infect spiders, dragonflies, caterpillars, and moths. To prevent the spread of fungus in the human setting, contaminated items can be sterilized. Layla explained that this is not her primary research and was just a topic that she researched out of interest while she was transitioning to a new lab.

G-Club Presentations - December 7, 2023

Brent Lake discussed the urgent need to address schistosomiasis, a global health crisis impacting over 230 million people. The disease originates from snails laying eggs in tissues, leading to inflammatory immune responses and severe conditions like hepatomegaly and liver fibrosis. Current vaccination strategies focusing on Tc1/Tch1 responses prove ineffective for chronic infections due to Th2 skew. Brent outlined project goals: understanding metabolic changes in APC from schistosomiasis infection, exploring phenotypic/functional APC changes, and employing transcriptomics for adjuvant discovery. Progress has been made in understanding APC changes, although the presentation posed challenges for those with limited biological knowledge.

 

Reagan Aviha presented research on developing a Zinc Oxide Nanowire on Carbon Nanotube Bio-anode for a Glucose Biofuel Cell. Highlighting the importance of bioelectric solutions for neurological disorders, Reagan discussed the limitations of current biofuel cells, emphasizing the need for enhanced stability and electrical conductivity. Experimental processes involved ZnO-NS hydrothermal synthesis, morphological and spectral analysis, and enzyme immobilization. Initial experiments showed a drop in current with increasing glucose concentration. Reagan successfully fabricated nanostructures on bucky paper and identified areas for improvement in structure density. Understanding the presentation required some biological background.

 

Amit Sarode focused on addressing environmental damage caused by energy production through the development of an MXene/Thylakoid-based biofuel cell. Stressing the eco-friendly imperative, Amit discussed the low power density of current biofuels. The biofuel cell mechanism involved light absorption by thylakoid to oxidize water, generating dioxygen, which was then reduced at the cathode. The biofuel cell demonstrated an open-circuit voltage of 0.458 V, a photocurrent density of 32 uA/cm^2, and a power density of approximately 3.2 uW/cm^2 when paired with a Pt GDE cathode. While the impact of the work was clear, the technical details were challenging to follow without a robust background in biology.

December 14, 2023 - Rebecca Richardson

Unraveling the Protein Puzzle: Exploring Human Protein Interactions through a LexA-E. coli Two Hybrid Approach

Rebecca Richardson's main focus is on deciphering complex diseases by investigating the human-protein interactome, the intricate network of protein interactions in the human body. With approximately 20,000 unique proteins in the human genome, current protein analysis methods involve mass spectrometry and yeast hybrid techniques. Rebecca opts for the LexA-E. Coli Two Hybrid approach due to its cost-effectiveness and user-friendly nature.

This innovative method diverges from the traditional focus on virus and bacteria protein-protein interactions and emphasizes direct protein-protein interactions. One notable protein in her study is Prostate Apoptosis Response-4 (par-4), known to be implicated in cancer and neurodegenerative diseases, showing a strong association with diseased individuals.

Rebecca employs various methods and strategies to unravel unknown protein functions, including protein structure prediction, sequence homology, and the use of single-cell and whole organism models for gene expression manipulation. Her investigation extends to glucose regulated protein 78 (GRP78), known to interact with par-4. Through Sanger sequencing, she successfully cloned a fusion protein between LexA-DBD and cl-Par-4, demonstrating its non-toxic nature. This represents the first attempt to quantify the binding strength of active cl-Par-4 homomer using the LexA system.

The project also delves into targeting peptides of Cleaved-Apoptosis Response-4, with a focus on therapeutic applications. Insulin, as the first therapeutic peptide with a small molecular weight, sets the stage for using peptides in disease detection and drug delivery. Rebecca cloned human brain cDNA fragments into LexA reporter vectors and conducted a combinatorial peptide screening with LexA-E2H. This groundbreaking screening identifies cl-Par-4 therapeutic targeting peptides, opening avenues for future work.

Rebecca's presentation style, aided by excellent visual aids, including a real-time video of protein-protein interactions, facilitated a high-level understanding. However, due to limited biology background, the detailed aspects were challenging to follow. Despite this, the presentation successfully highlighted the feasibility of investigating human protein-protein interactions with the LexA system, paving the way for future studies, including a cytotoxicity study on LexA DBD::GRP78, an assay on GRP78 and cl-Par-4 LexA-E. coli Two Hybrid, and quantifying the binding strength of cl-Par-4 and GRP78 using B-Gal assay. Additionally, future work involves directionally cloning peptides into a reporter vector, conducting a B-Gal assay to measure binding strength, and validating screening results using Poly-His pull-down assays.

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