Yes, there are more similarities between solar cells and pizza than you might think. 
I'm a solar energy researcher working towards eliminating the defects in and improving the performance of industrial solar cells. A PhD is a long journey full of untimely experiments and countless sleepless nights, so I often find myself eating while working (definitely not in the labs!) and working while eating. One day, intrigued by how delicious a cheese pizza is, I realized how alike the pizza and the cell samples I work with are.

Build your own Solar Cell

A solar cell is a device that generates electricity when the sun shines over it. A combination of these cells linked in sequence makes a solar panel that can generate significant power, and that is what you see on people's rooftops, in solar-powered streetlights, and calculators. As a good pizza starts with a perfect dough base, solar cells begin with a very pure form of silicon wafer (which is also the second most abundant element in the Earth's crust), scientifically called a 'base.' Some extra elements like boron or phosphorus are then added to this silicon base to make it more conductive. 
Then comes the toppings. Yes, both for the pizza and the cells! Pizzas are loaded with a bunch of toppings for various flavors; solar cells are also coated with some very thin layers that help enhance their performance. These layers are called 'dielectrics.' They help reduce the reflection off the surface to increase the light absorption, passivate some surface defects, and possess some hidden benefits for the base. The most common dielectric, silicon nitride, used in the industry is also responsible for the blue color you see on most solar panels (a silicon wafer is otherwise grey!). 
We all know that pizza does not taste great after sitting in the fridge for a week. A similar degradation occurs in most solar cells. Once the panels are installed and are out in the sun, their performance degrades after the first few years (anywhere between 2-10% relatively). And losing a slice or two of a pizza might not make a dent in your pocket, but this degradation is responsible for a loss of billions of dollars every year. We call it 'light-induced degradation' (or LID). 

Light-Induced degradation (Staleness)

LID is a family of defects that occur in the presence of light; however, technically speaking, the resulting charge carriers are responsible, not the light. This degradation is not a new phenomenon, and researchers have been working on understanding and solving it for years. The good news is one of the most common defects responsible for LID has now been nearly solved in most panels worldwide. Unfortunately, we now have a new variant of LID in all kinds of panels. However, it only occurs at high-temperatures under light: "light- and elevated temperature-induced degradation," or LeTID. More sunlight is essential for higher electricity generation from the solar panels, but higher temperatures are detrimental (we only need the light, not the heat, for solar electricity generation). 

Limiting Staleness

This new kind of degradation is a focus of numerous researchers globally, including me. In my research, I work on mitigating this degradation by simply playing with the dielectrics (after all, it is all about the toppings, right?). 

Firstly, we have found that reducing the thickness of the dielectrics can significantly mitigate this degradation (1). You can imagine how applying less tomato sauce can prevent the pizza from going soggy. Reducing the thickness means using less material and thus lower costs. However, there is a threshold beyond which reducing the thickness might lead to other kinds of losses. 

Secondly, we also devised that the placement of the dielectrics plays a vital role in the extent of potential degradation (2). By studying multiple industrial cells, it was observed that adding a very thin layer of a second dielectric can strongly modulate the degradation. This reduced the degradation by creating a barrier layer between the first dielectric (Silicon nitride) and the silicon base. Another solution we found is the dependence of degradation on the silicon wafer thickness (3). By thinning the wafers, severely low degradation was observed. Similar to how a thin-crust pizza can help prevent you from gaining extra calories if you are on a diet!
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These three solutions effectively alleviate the degradation in current solar cells without increasing their manufacturing cost. With solar installations progressing at record levels each year, the mitigation of these defects will accelerate the transition to a cleaner world. So, we can leave the next generations with tastier pizzas and a healthier planet! 

1. U. Varshney, M. Abbott, A. Ciesla, D. Chen, S. Liu, C. Sen, M. Kim, S. Wenham, B. Hoex, and C. Chan, "Evaluating the Impact of SiNx Thickness on Lifetime Degradation in Silicon," IEEE J. Photovoltaics, vol. 9, no. 3, pp. 601–607, 2019.

2 . U. Varshney, C. Chan, B. Hoex, B. Hallam, P. Hamer, A. Ciesla, D. Chen, S. Liu, C. Sen, A. Samadi, and M. Abbott, "Controlling Light- And Elevated-Temperature-Induced Degradation with Thin Film Barrier Layers," IEEE J. Photovoltaics, vol. 10, no. 1, pp. 19–27, 2020.
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3. U. Varshney, M. Kim, M. U. Khan, P. Hamer, C. Chan, M. Abbott, and B. Hoex, "Impact of Substrate Thickness on the Degradation in Multicrystalline Silicon," IEEE J. Photovoltaics, vol. 11, no. 1, pp. 65–72, 2020.

If I had to go back in time and give myself advice, I’d tell myself to be cautious of advice. Advice isn’t necessarily good or bad, but it’s often misguided or the wrong fit. In your scientific career, especially early on, it’s tempting to trust all the guidance tossed your way. More experienced scientists should know better than you, right? Not necessarily. 

Here’s some advice I received and learned — through experience — to disregard. 

1. Place the least amount of effort into your coursework and secondary responsibilities so that lab is your first and only priority. Why this advice is bad: As a graduate student researcher or any sort of trainee, you are a student first and a researcher second. There’s a reason why you only get a stipend and not a lab tech’s salary. Capitalize on your time as a grad student, and be sure to prioritize career development, networking, reading papers, extra-curricular activities, and more.
2. Stay in grad school until you have 4 or 5 publications. Why this advice is bad: 4 or 5 publications sounds great, but do you need that many publications to be a competitive job candidate? Likely, no. Remember that your CV is more than your publications. Many hiring managers look for qualities and skills over publication quantity.
3. Put as much content in your presentations as possible to show off how much work you’ve done. Why this advice is bad: Where do I begin? First, the purpose of a presentation is to share a story, not to brag about your work. Secondly, when communicating, quality is better than quantity. Thirdly, presentations should be digestible. A bombardment of data without context is unpleasant for your audience.
4. Work a strict 9-5 (at least) Why this advice is bad: Lab work doesn’t always fit neatly into a 9-5. Sometimes experiments run late. Other times they wrap up early. Reward yourself when you work late, like taking it easy the following day. And don’t force yourself to find busy work when you've already finished your goals for the day.
5. Pick up as many projects as time allows. Why this advice is bad: Time is not your only resource. Energy, attention, and patience are all resources that factor into your workload. You might have time to do another project, but you have time to do it well? Also, extra time in your schedule is essential for flexibility, networking, mentoring, and other responsibilities.
6. Don’t do [insert career move here]. I.e.: post-doc, PhD, go into industry….etc. Why this advice is bad: Absolute nay-sayers advise from their perspective. Advice should not be cookie-cutter but adjusted for each individual.  
7. It’s too early for you to worry about networking. Why this advice is bad: It’s never too early to start networking.

An upside to academia is the freedom to make your own choices. But with freedom comes uncertainty. Grad school and science careers are challenging to navigate. Suitable, appropriate guidance will help you through, while erroneous, biased advice can hold you back. Practice healthy skepticism, and in the end, always choose what's best for you.

Have you been given extraordinarily ill-fitting advice as a scientist? If so, tell us in the comment section below! Or, tweet at us, @BoldedScience, #BadAdvice. 

Entrepreneurship offers a unique opportunity to continue exploring and researching while learning new skills and tackling challenges that will dramatically enhance your career. However, it is paramount to recognize the stark differences between life in academia vs. life as an entrepreneur. Here are some examples of approaches that may need to change as you embark on your entrepreneurial journey. 

​Decision Making
As scientists, we like to gather as much data as possible before making a decision. Unfortunately, this isn’t possible in entrepreneurship. You will need to adapt and become comfortable making tough critical decisions with only 50% of the information. 

Presentations & Discussions
Whenever I read a paper, attend a conference lecture, or make academic presentations, the same setup is used: background, rationale, results, discussion, and finally, material/methods. In the business world, the goal is to share the most important information in a short amount of time. You are expected to concisely explain the problem you are solving, your solution, and how you will achieve results. 

Scope of Work
In research, we have our primary project, and we immerse ourselves in that topic, working days, weeks, and months with an intense singular focus. In contrast, entrepreneurs will need to maximize their limited time by conducting multiple initiatives concurrently. Learning how to effectively switch context between subjects to solve problems is a skill that will help you tremendously. One minute you may be engineering and the next you may have to close a sales deal.

While in academia, there are few things you can do to prepare yourself for this transition.

1. Contribute to lab members’ projects or collaborate with other labs.
The reason I’d advocate for this is that it forces you to work with other people/groups. Academia can often lead to working solo, which prevents you from learning the critical soft-skills needed to succeed in a team-based environment when there are multiple chefs in the kitchen. In entrepreneurship, great teamwork and effective communication can make the difference between success and failure.

2. Leverage your network and ask questions
If you’re looking to build a business in the life-sciences sector, you are in the prime spot to do some target market research. Reach into your network, speak with your colleagues, and investigate your business problem. There is no better time to do this. Scientists are far more likely to answer your questions as a graduate student than when you cold-call them as an entrepreneur.

3. Reading literature or books about building start-ups are helpful, but the best learning comes from experience. Find a start-up in the industry where you want to build your business and work there part-time. Listen, learn, and observe. Pick up on how teams self-organize, how company culture develops, and keep an eye out for solid work practices. How are meetings structured to maximize efficiency? How are large teams coordinating their work? How are company leaders communicating with each other? When it’s time to break out on your own, you’ll have a point of reference for how processes work. Stitch together practices that worked well, and learn from the mistakes you’ve made during this experience.

For those in academia who have already begun their transition into entrepreneurship, there are two important considerations you should make before diving in.

Intellectual Property (IP)
The very first thing you need to do is read through your institution’s intellectual property (IP) agreement to find a clause that details who really owns the IP.

Most institutions stipulate that the IP generated within the scope of your employment belongs to the institution. Here are some things to consider: 

• Finding strong legal support, especially if you are filing patents. 
• Sourcing facilities, equipment, resources to continue research & development. 
• Submitting an invention disclosure to your institution. While most institutions have some IP & commercialization department to assist you, it likely isn’t free. You’ll either have to give up a significant equity stake in your company or engage in a revenue share agreement to access support.  

If you’re building a service, you’re leveraging YOUR know-how, YOUR expertise, and YOUR intellectual capital. I would highly recommend that you build your business by yourself. When you’re trying to fundraise, investors want clarity around the ownership of your IP. Essentially, any revenue share or ownership will significantly reduce your ability to raise capital.

Feasibility of Entrepreneurship
Secondly, you should look to sort out the logistics of the transition. Prior to your capital raise, you'll be responsible for the business's operating costs and your own living expenses. All businesses are different, but I'd recommend preparing for 8-12 months with no income.

Transferable skills and interests 
In academia, we are passionate about our research and motivated to contribute to the scientific community. This is one of the greatest things about being a scientist. But there is more than one way to make an impact. Entrepreneurship in life-sciences provides a unique opportunity for us to solve problems that the community faces while staying close to our research roots. At BioBox, our team remains deeply connected to our academic origins and are committed to solving the challenges that we faced while in academia. The days are long, and the pressure is high, but it is a feeling that we are used to during our time grinding in the lab and spending countless hours trying to get our experiments to work. 

​One of the best things you learn in academia is the importance of self-sufficiency. In your research project, you are most likely the single champion and key driver of that project. Your years of work in a self-directed and independent environment prepares you very well for the challenges you will face when building your own business.

In many ways, academia is an excellent training ground for entrepreneurship. For those who are considering breaking out and building their own business, I can assure you that it will be one of the most rewarding experiences you’ll have in your career. 

A wave of controversy and outrage followed the recent publication of a study by AlShebi et al. from the New York University of Abu Dhabi on November 17th. In their Nature Communications paper, the authors analyzed 3 million mentor–protégé pairs to assess the impact of mentorship quality on the future scientific career of protégés. In addition, the gender of both mentors and mentees was analyzed as a potential factor affecting the quality of such mentorships. 

The study found that increasing the number of female mentors was associated with a reduction in post-mentorship impact (fewer articles published) by female mentees. Likewise, a decrease in citations of the papers published by female-female mentor pairs was reported during the mentorship period. It concluded by saying that 'opposite-gender mentorship may actually increase the impact of women who pursue a scientific career and that current diversity policies should be revisited. 

Shortly after its release, a myriad of scientists from a diverse range of backgrounds expressed their concerns and/or disagreements on social media about the interpretation of the data, claiming the paper amplified every bias experienced by female academics nowadays. Unsurprisingly, two days later, the journal indicated the paper was under investigation. Finally, a bit over a month after its publication, the paper was retracted on December 21st. The authors attributed the retraction to issues in the validation of 'key measures' identified by the reviewers. The journal itself added that this experience reinforced their commitment to equity and inclusion in research, and in support, they will be launching further initiatives to support female scientists. 

Despite being a relatively large study, most of the criticism was directed towards the methodology and criteria used in the study, with emphasis on two particular aspects: the use of co-authorships as a measure for informal mentorship and the use of scientific publications (or citations of those publications) as a metric for success. 

The other side of the equation

After its release, several articles collecting the opinion of experts and established scientists in the field have been released. But, what about the opinion of the other side of the equation: the mentees and protégés? To gain insight into junior scientists' experiences and opinions on the impact of mentorships in their careers, I conducted interviews with researchers or professionals in the early stage of their careers. 

Pina Knauff, Dr. rer.nat/ Life Sciences
Pina is a Postdoctoral researcher in the field of Molecular neurogenetics at Charité-Universitätsmedizin Berlin in Germany. She has been active in the field for nine years, during which she has had five mentors. From those, two of them were women. When asked about the differences between having a male mentor over a female mentor, she explained that her female mentors were more empathetic and invested in providing guidance in her experience. Dr. Knauff has published five articles throughout her career, two of which were published under female mentorships. 

Edna Gómez Fernández, PhD/ Economy
Edna is currently a freelance consultant. She completed her doctoral degree in social sciences at the University of Arizona, focusing on government and public policy and economics. Before leaving academia, she was active for 12 years. Throughout this time, she had only one female mentor out of seven. When choosing her mentors, gender was not a determinant factor for Edna. She believes that choosing a mentor who is an expert in the field that aims for efficient and professional communication is more important. As she did not publish under the supervision of a female mentor, Edna believes that the publishing process can benefit from having a male mentor. However, she also expressed that her last mentorships experiences - all of them with male mentors - influenced her decision to leave academia. 

Ethiraj Ravindran, PhD/ Life Sciences
Ethiraj is a postdoctoral researcher also working at Charité-Universitätsmedizin Berlin. He has been active for 12 years in the field of Clinical Neuroscience. From his experience, he noticed that female mentors take their roles more seriously and that personal growth is also considered. He has felt more encouraged by his current female mentor and confirms that this experience played a significant role when deciding to continue in academia after his Ph.D. 

Lucía Trías, MSc/ Design
Lucía is an independent design researcher. She recently completed her Master's degree at the Anhalt University in Dessau, Germany. During her 11 years of career, her first mentor - a female mentor – played a major role in Lucía's decision to further pursue a degree in academia. She thinks that in her area of research, decolonial design, having a male mentor can be detrimental as the female perspective mostly influences the field. 'In my experience, my female mentors exhibited more openness and a broader capacity to listen to critical thoughts without taking things personal,' she added. 'Accepting mistakes was also something that my male mentors were not good at, and I felt this had something to do with arrogance and feeling of superiority in their position.' 

Success in academia: what matters the most?

Conversations regarding which factors define a successful academic path have long been on the table. Traditionally, academic success is measured in the form of research performance. Yet, career success is composed of two components: objective and subjective. The objective success is determined by the system, is measurable, and therefore more public. The subjective success is personal; it reflects one's own sense of career. A recent study by Sutherland K. A. found that personal success is changing among early-career academics, who report factors such as contribution to society or influencing students' lives as better metrics of success. 

In this regard, interviewees also agree that the number of publications or citations should not be used to quantify success. Assessing the quality of mentorship based on the end product prioritizes the objective component of success. By doing this, AlShebli et al. neglected various other factors related to subjective success, including the current climate in academia that is strongly advocating for healthier working environments, where the 'publish or perish' vicious circle is not appealing for the upcoming generation of researchers. 

Furthermore, success is often defined differently by men compared to women. Evidence also indicates that male scientists cite themselves more often than women. These, coupled with the reality that women leave academia earlier than men, contribute to the discrepancies in the number of publications between genders. Finally, 'the publishing process can be sometimes shifted by the journals' interest, and this should not diminish the quality of the submitted work' says Dr. Ravindran. 

If correctly interpreted, this study could have contributed to the ongoing call for career development strategies that acknowledge the predominant patriarchal environment. Instead, it crashed and burned, demonstrating the importance of drawing proper conclusions and the immediate rejection of anything that perpetuates the systemic biases against women in STEM. ​​​​

“What made you want to be a Scientist?”

This question always takes me aback. I have been in science so long it’s hard to pinpoint that exact moment where I went from not-a-scientist to the path I’m on now. I was always good at science… but that didn’t make me want to pursue a career in it. After sitting on the question for some time, I realise there isn’t a what that made me want to pursue science, but rather, a who.

Travel back to 2014. My hair is long, my experience isn’t, I’m doing my undergraduate degree in biology, and I am lost. My studies killed my love for the subject. I had such a miserable time that I didn’t see myself staying in science at all. Monthly career fairs on the university lawn showcasing non-science-specific careers; “train for another three years to become an accountant!” - is this all my hard work and studying can give me? I felt lost, unsure as to where my degree could take me. In a bid to work out what I wanted to do, I secured a placement in a lab at University College London (UCL), researching the effects of diet on aging in fruit flies. I (in my naive mind) thought that all I needed was a taste of lab-work, and the answer to my uncertainties would magically reveal itself.

Without a shadow of a doubt, my placement at UCL changed the course of my career. However, this wasn’t because of the technical skills I gained or how good it looked on my CV. Rather, it was the guidance and mentorship I didn’t know I was missing. During my placement, I worked under a post-doc named Adam. He took the time to explain the area of science to me (on many occasions more than once). In the lab, he taught me techniques, and before long, I was proficient enough to collect data for his project. We had frequent discussions about the results and what it meant in the area of research, but most importantly, he gave me the confidence to speak freely and ask questions.

If I had to identify when my path shifted to the science-trajectory, I could pinpoint the exact moment; a conversation I had with Adam one day during my placement. Curious about our methodology, I asked, “How come we only use female flies in these experiments?” “Because the field assumes that males don’t respond in the same way,” he replied. I pondered on that for a bit, “Is there any evidence of this? Has anyone shown it?” “No, but you can be the first!” And that was the birth of  My First Project . Prior to that placement, I had hardly been entrusted with a pipette, let alone an entire project. The independence empowered me in an indescribable way.

I spent the whole summer working on my project – discerning the differences between males and females in response to changes in diet. There was no feeling greater than having a tray full of vials labeled with my name. All experimental work I had done before that had been pre-arranged university practicals. I had never had anything with my name! Here I was, being trusted with a full tray! 

The following weeks flew by and were the most enjoyable working days I had experienced. I caught the train to London every day with energy and enthusiasm. I would get to work setting up my experimental flies, doing dissections, imaging slides on expensive microscopes, and analysing my data. Adam and I would meet frequently. He would help me with my analysis and truly catapulted my love of programming and data visualisation with R (something I now use every day in my PhD). He would ask questions to challenge me, and we’d have thought-experiments over the implications of my results. After a couple of months, it looked like I had meaningful results!

But most importantly, I would often get praise and told I was doing a good job, not just from Adam but from many members of the lab. In the two years of my undergraduate up to that point, I was only told I wasn’t doing enough; this was a significantly positive experience for my confidence and mental health. Adam’s and the lab’s support also extended far beyond my project; we had many open conversations about my next steps and further education. It was Adam who not only suggested I pursue a Masters but also told me I’d be good at it.

Now, here I am, seven years later, in the final year of my PhD. I may be far away from flies, but I still experience the impact of Adam’s support. He enabled me to see my love and passion for science, to realise I actually have something to offer. At the time, I didn’t realise how much I needed a good mentor to provide inspiration, guidance, and support (both technical and mental).

As I reflect, I can identify the characteristics that I feel make a good mentor:

Patience: Those earlier in their career have less experience and need support.
Two-way Conversation: Exchanging what you both expect from the relationship and what you continually need.
Sharing Experience with openness & honesty to allow learning from one’s mistakes.
Giving Credit & Praise: We are all humans and thrive off encouragement.
Enthusiasm: It’s contagious!
Trust:  A mentor is not a babysitter.

It is important to note that while some of these points are universal (I think every mentor should be a good communicator), some are specific to me. Others may require something else from mentorship. Some trainees require motivation, reality checks, etc. This is why honest and frequent conversation of your and your mentor’s needs and expectations is vital for the relationship to flourish.

During my later scientific career, I have been fortunate enough to mentor two lab-placement students, in addition to dozens of academic students, via my job as a tutor. I have utilised everything I learnt from Adam, and other great mentors, to give the best support and guidance I can. At the time of writing, both lab placement students have decided against pursuing lab-based careers, but this makes no difference to me. A successful mentorship doesn’t result in training the next you; from a successful mentorship emerges two people who feel they have grown and developed from the experience.
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Don’t get caught thinking that it’s just lab supervisors or training directors who can take on this role. We all have the opportunity to be mentors. You may not think it – but there are those out there for whom your experience is exactly what they are missing. 

In less than one-year, scientists created not one, not two, but three vaccines with over 90% efficacy for Covid-19. Which begs the question, what gives? Why don't we have cures for all our other ailments? After spending billions of dollars on cancer research for decades, where is that cure? Regrettably, there is none. And it's not in a vault protected by the government and big pharma either. The reality is, cancer is extremely hard to treat, study, and understand.

Infectious disease vs. cancer
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Infectious diseases are easily targeted in comparison to cancer cells. Bacteria have a unique cell wall compared to animal cells. Some antibacterial medications attack their membranes and cell wall synthesis, killing bacteria and minimally harming ourselves. Bacterial enzymes differ from animal enzymes, too. Newer antibacterials inhibit bacterial proteins, leaving our enzymes unperturbed. Viruses are also easily distinguished from our cells. They produce their own distinct proteins and have unique genes. We use vaccines to train our immune system to be alerted to their "foreign" presence.

But cancer cells? They're a bit trickier than bacteria and viruses.

What is cancer?

Cancer is a mass of our cells that have uncontrolled growth, avoidance of cell death, and the annoying habit of acquiring genetic mutations that enable unwanted behavioral adaptations. Ironically, killing a cancer cell is easy; we do it in test tubes all the time. The challenge is killing the cancer cells and not our healthy cells. Unlike bacteria and viruses, cancer cells have our genes, our proteins, and our molecular machinery. So how do we kill cancer cells inside a human body?

The answer lies in the research. Through years and years of experimental research, we are learning what makes cancer cells tick. By figuring out how cancer cells behave differently, anti-cancer drugs can be designed that do not harm non-cancer cells.  

What makes a cancer cell?

It all comes down to abnormalities in the DNA. Genetic mutations can be inherited from your parents, acquired over time due to general wear and tear, or result from environmental stress (cigarette smoke, UV, etc..). 

We have an increased susceptibility to cancer when an oncogene or tumor suppressor is mutated. Oncogenes are genes that contribute to cancer if they are over-expressed or hyper-activated, i.e., epidermal growth factor receptor (EGFR). Tumor suppressors are genes that, if turned off, contribute to tumorigenesis. The most famous tumor suppressor is P53, a protein that signals cells to die. When P53 is weakened or inactivated, cells don't die when they are injured or malfunction.

Having one mutation in an oncogene or a tumor suppressor may increase the probability of getting cancer, but it won't cause cancer on its own. An estimated 2-6 cancer-related genes must be mutated for tumorigenesis, and further mutations can contribute to disease severity.

Barriers to treating cancer.

​Cancer is a heterogeneous disease. When we refer to cancer, we are not mentioning one disease, but a family of hundreds of diseases. A treatment that works well for breast cancer might not necessarily work for pancreatic. To complicate matters further, each tumor can be characterized by its unique genotype, meaning that not every patient will respond to treatment similarly.  

Cancer cells mutate and adapt. After wrapping your head around the infinite permutations of cancer types and genotypes, also consider that an individual tumor may be heterogeneous as well. Cancer cells divide so quickly in stressful environments that they often incorporate mutations during DNA replication. Mutagenesis creates subpopulations within a tumor, causing issues such as metastasis and chemotherapy resistance. 

The difference is subtle. As mentioned, the drug designed to kill cancer cells shouldn't poison the rest of our body. But if the difference between the cancer cells and our cells are only 2-6 genetic mutations, designing a specific drug is no trivial task. Currently, most chemotherapies are designed with one of the following anti-cancer strategies:

• Attack proliferation: A hallmark of cancer is rapid cell division. A key component of cell division is complete replication of the cell's genome. Therefore, many cancer drugs impair DNA replication machinery, impede DNA repair proteins needed for replication, or create DNA damage that will block DNA replication. Unfortunately, these chemotherapies also attack healthy cells that divide quickly (hair, nails, muscle, and GI tract cells), causing common side effects like hair loss, loss of appetite, and fatigue. Toxicity to neuronal, kidney, and heart tissue is often the dose limitation for these drugs.
• Target the mutated protein: Drugs can be designed to recognize the mutated protein specifically while having limited recognition of the wild-type protein. For example, inhibitors have been created for EGFR with activating mutations found in some non-small cell lung cancers. Additionally, vaccines targeting mutated KRAS proteins, commonly found in lung, colorectal, and pancreatic cancers, are undergoing clinical trials.
• Induce synthetic lethality: Synthetic lethality is a phenomenon where disruption of two genes of similar function causes the cell to die, while only disrupting one of the genes allows the cells to live. The concept is simple, identify a mutated gene in cancer, and find a second gene to inhibit pharmaceutically to kill the cancer cell. The synthetic lethal concept was recently used to develop Parp inhibitors, a chemotherapy used to treat BRCA deficient cancers. The successful creation of Parp inhibitors jumpstarted a movement in cancer research to discover other genetic synthetic lethal relationships of genes commonly mutated in cancer.

Modeling Cancer. Early cancer research takes place in test tubes. Protein function and structure are investigated in solution, while cancer cells are manipulated in dishes. When in vitro studies seem promising, experimentation moves on to mouse models. Unfortunately, what works well in a test tube often does not work well in the body. And sometimes, a drug that works marvelously in a mouse is toxic to humans. Therefore, preclinical studies are tweaked and repeated extensively to ensure that clinical studies are as safe as possible. Computational models can help bridge the gap between animal testing and human testing, but with limitations. On average, it takes 30 years from drug design to clinical trial approval. And as careful as scientists are during those 30 years, cancer clinical trials have the highest failure rate. Most trials fail due to adverse side effects (aka: when the drug also attacks our healthy cells).

So, will there ever be a cure?

To answer that question, we'd have to define the word "cure." A cure is a gold-standard treatment to eradicate or alleviate a disease completely. To date, only two diseases have been successfully eradicated from the earth, smallpox and rinderpest (both viruses that were wiped out by vaccination — yay, vaccines!).

Likely an end-all cure to cancer is not in our near future. But wait! Before you close out of this blog post, annoyed by my pessimism, I have a message of hope for you. Although "cures" are not on our immediate horizon, adequate treatment and prevention are already here — with more to come. Let's look at breast cancer as an example. In 1971 the 5-year survival rate of all breast cancers was 53%. Today, the 5-year survival rate is nearing 90%! Encouraging numbers, to say the least, these stats are representative of the advancements made in cancer research.

Cancer researchers have chosen an arduous career, often riddled with disappointment and setbacks. Although earth-shattering, groundbreaking discoveries are preferred, in science, it's often the small victories that will culminate in clinically relevant treatments. Cancer research may seem slow, but it is undoubtedly progressing.

If the Rose Family of Schitt's creek can have their estate repossessed and forced to live in a motel within a one-horse town, you can survive any misfortune your research career throws your way. Rough patches are a given in research. Grant rejections, failed experiments, and criticisms; oh my! So, how do scientists cope during the downturns of the research roller coaster? We have our ways. But if you feel hung out to dry and have difficulty seeing through the fog, it's time to channel some experts at maneuvering through tough times.

Moira: Reality shifter
"You are blind to Reality and for that I am most Proud."

Johnny Rose: No school, like the old school.
"Let me explain something about business. It's a dance. And sometimes you lead. And sometimes you follow."

Alexis: The eternal optimist
"I don't skate through life, David. I walk through life in really nice shoes."

David: Classic overthinker 
“He told me he doesn’t want my help, so I’m just going to play the supportive partner and watch him fail.”

You learn a lot about yourself in graduate school. The same is true while running a marathon. Signing up for either is a great way to realize your masochistic tendencies. Jokes aside, continually working towards two immense challenges has taught me several valuable lessons that I share here.

Lesson 2: Focus
Whether it be training for a marathon or completing your PhD, it's essential to maintain focus on the goal, despite challenges. Marathon courses tend to pass through the main roads of whichever city is hosting the race. To not get lost (or disqualified), runners should not stray from the course -- no matter how intriguing side streets or trails along the way may seem! While many runners race without issue, others find themselves lost by accident. Those in the latter category will undoubtedly take longer to finish -- unless they pick up the pace once back on track! How stressful! Now, replace the concept of "marathon course" with "PhD timeline." You get the idea.

Lesson 3: Pace yourself
In each marathon I've run, there was always some person shouting reminders, "it's a marathon, not a sprint!" In my first two marathons, I failed to heed the warning. I tried to keep pace with more advanced runners early on. As a consequence, I would tire before I was even remotely close to the finish. I have since learned to avoid this miserable fate. In my last marathon, my mile splits were negative, meaning that I started at a slower pace and progressively ran faster as the race went on. As a result, I enjoyed the race more, performed much better, and I was happier overall. 

Progressing toward a PhD requires a steady pace as well. Before my qualifying exam, I frequently had 10+ hour days in the lab, usually running at least three experiments at once. I churned out data fast. On one occasion, I was mistaken for a more senior graduate student during a data talk because I had done so much. It felt good, but the compliments were unintentionally toxic; I craved more appraisal.

Long story short: I became burnt-out. After passing my qual in September 2019, I entered a lull period for a few months. Sprinting the start of my PhD has surely helped me look productive on paper, but I became worried that I would head to the finish fatigued. 

Lesson 4: Recovery is important
Before training for marathons, I didn't realize how many physiological systems are taxed and need recovery following a race. After a hard run, your muscles, central nervous system, and psyche need time to recover. Moreover, each has a different recovery timeline. The muscles may recover in a day or two, while the CNS needs more time, and who really knows about the psyche, TBH. 

The CNS needs to recover after working hard during research too. A typical week for a graduate student can involve planning, problem-solving, project management, writing, and executing experiments. These are strenuous activities, especially when done altogether. I've learned that a whole-body recovery from both physical and mental fatigue is essential for long term success.

Lesson 5: It's better with a buddy
I used to prefer solo running, convinced that it was easier to be self-sufficient. However, it's tougher to run alone, without much-added benefit. I realized having a running-buddy is way better. In particular, running with friends makes it easier to stay motivated, especially in the early mornings, through bad weather, and during the last mile of a race. I learned the value of a buddy translates to the lab for the same reasons. My labmate is a great friend, and his presence alone helps me feel motivated and keep going when the going gets tough.

Lesson 6: Fuel up 
Consuming sufficient nutrients before, during, and after a marathon is essential. In my first marathon, I neglected to fuel myself. So, during my second marathon, I grabbed fuel (i.e., sports drink, orange slices, gels) at every mile marker where it was available, and I was less fatigued because of it.

The academic equivalent of sports fuel is probably free food at seminars. In addition to nutrients, food can also provide a mental break. I'm borrowing Michael Pollan's idea of table fellowship here: the exchanges we have with our friends around a table can be equally as filling as the meal itself. Sitting down to share a meal is mentally rejuvenating and helps prepare me mentally for the next day in the lab or a morning race.

Recent developments of mRNA vaccines to protect people from SARS-COV-2 are making headlines. The first two successful mRNA vaccines, the immunization jointly developed by Pfizer and BioNTech and a second vaccine developed by Moderna, are turning mRNA vaccines into a household topic. For many scientists, this is not only great news for public health but also a proof-of-concept that mRNA vaccines can work! Today, I'll share with you some significant scientific discoveries and principles that make mRNA vaccines possible. 

What is mRNA?
mRNA is the abbreviation of Messenger RiboNucleic Acid. As the name suggests, it is responsible for relaying messages encoded in DNA molecules to protein production in cells. 

The synthesis of mRNA, a process called transcription, is carried out by RNA polymerase. tRNA molecules help to bring in the bricks needed for protein synthesis. For mRNA vaccine production, mRNA synthesis starts with a DNA template, and the mRNA molecules are synthesized using a phage RNA polymerase. 

How do mRNA vaccines work?
COVID mRNA vaccines function by delivering the mRNA that encodes spike proteins. Spike proteins are a protein on the surface of the SARS-COV-2 virus, and it plays an essential role in facilitating viruses to enter the cell. By delivering mRNA molecules that encode this protein into human bodies, cells inside the human body will synthesize this spike protein and prime the immune system accordingly. A diagram from Bloomberg news summarizes this well. 

How is mRNA delivered?
Most of the mRNA vaccines encapsulate mRNA molecules in lipid nanoparticles. Other delivery methods in RNA therapeutics include using polymeric nanoparticles comprising of RNA and cationic polymer. For small interfering RNA (siRNA), conjugating RNA to N-acetylgalactosamine, which targets receptors on hepatocytes for uptake, is also an option. 

What are the difficulties for mRNA vaccine development?
The hurdles for developing an effective mRNA vaccine can be divided into two parts: (1) mRNA cannot enter the cell intact, and (2) it cannot be translated into protein efficiently. 

• mRNA cannot enter the cell intact. 
  • Naked mRNA molecules are not stable. mRNA is easily degraded by nucleases. Thus, protecting these mRNA molecules is a hurdle that must be overcome. 
  • Naked mRNA cannot enter cells through free diffusion. mRNA molecules are large and negatively charged, meaning they cannot passively pass through cell membranes. 
• mRNA cannot be translated efficiently.
  • Naked, single-stranded RNA triggers cells' antiviral defense. Cells generate an immune response that results in active degradation of these mRNA molecules. Consequently, no protein-of-interest can be synthesized. 
  • Non-optimal codon usage (e.g., Use of rare codons or codons with low tRNA abundance). mRNA has a specific code wherein every three bases (drawn from a pool of A, U, C, G, and other modified bases) encodes an amino-acid needed for the protein. Strangely, some codes work better than others. Non-optimal choice of codes (base combinations) may result in bottlenecks in protein yield during translation. 
  • mRNA forms improper secondary structures. mRNAs can fold upon each other, causing secondary structures. Some secondary structures of mRNA hinder the binding of polymerase or other regulatory components that result in inefficient protein synthesis. 
  • Non-optimal regulatory regions (e.g., 5'UTR, 3'UTR, ployA tail). Non-optimized regions of mRNA that do not directly code for protein production may lead to insufficient binding of regulatory protein complexes that promote the translation of mRNA. 

What are the scientific discoveries that help to overcome these problems?
Most of the work falls into two categories: (1) direct mRNA modifications and (2) optimization of delivery particles. 

• Direct mRNA modification. 
  • Chemical modification of mRNA molecules. Most of the chemical modifications focus on either minimizing cells' antiviral defense or improving mRNA's stability. Modifications include capping mRNA at 5' end, modifying the sugar backbone of mRNA (e.g., methylate 2' hydroxyl group, add Amide-3 linkage), and modifying the mRNA (e.g., methylate cytidine, modify uridine to 5-Bromo-uridine). 
  • Codon optimization. mRNA codes can be changed to exclusively use codons with high tRNA abundance, and tRNAs expressed efficiently in a specific tissue. Codons can also be optimized to minimize pesky secondary structure formation. 
  • Regulatory region optimization can lead to improved binding of regulatory components to enhance protein translation and improve mRNA stability. No gold standard for this method has been developed yet. However, development in bioinformatics tools is improving this standard practice. 
• Optimization of delivery particles
  • Lipid nanoparticle engineering. Many efforts have been made to increase mRNA stability by adding lipids with positive charges (as mRNA are negatively charged) to improve cells' uptake of mRNA particles and promote endosome escape. 
  • Addition of chemicals in lipid nanoparticles. One example is to add MPLA, a chemical that impairs antiviral defense and promotes T-cell activation. 

What are the differences between the Pfizer and Moderna vaccines?
Both vaccines use lipid nanoparticles to deliver mRNA that encodes SARS-COV-2's spike proteins. However, because specific formulations are secret, the exact differences are unknown. Yet, it is speculated the differences in the lipid components are the reason why Pfizer's vaccine needs to be preserved at an ultra-cold temperature. In contrast, Moderna's vaccine can be shipped in a regular freezer. The difference in lipid composition may also explain why the Pfizer vaccine results in fewer side effects.

What else to look for?
Moderna's mRNA vaccines against other infectious diseases, such as its Zika vaccine currently in clinical trials, are worth watching. It posted encouraging Phase I clinical trial data and may come to the market sometime in the future. 

Other applications of mRNA vaccine technology include immunizations for cancer, such as a cancer vaccine jointly developed by Moderna and Merck that targets common mutations in KRAS, an oncogene that is often mutated in cancer patients. ​

Performing science outreach has become a common alternative career for many classically trained scientists. Whether it’s running a popular YouTube channel where you perform chemistry experiments for kids or writing articles for medical magazines, there are plenty of ways in which you can work within science outreach once you’ve defended your dissertation! Just ask the fine folks at ComSciCon, who are pretty much the United Nations of science communication with their impressive diversity in subject matter.

My Journey into informal STEM education

Before starting my doctorate, I did archaeological research as an undergraduate at the University of Oregon. I realized the kids on the field trips were much more interesting than the shell midden I was analyzing. Why did everyone love being inside a museum more than a science classroom? How could we tell they were engaged? And Why? Was it because of my awesome Hamlet impression using a skull of a cave bear?

My experience at the museum led me to informal science education research, a field that’s garnering more attention. Today, kids are often learning outside of their traditional school settings, especially due to the COVID-19 pandemic, which has led to school closings and prompting students to learn elsewhere. 

While completing my doctorate in Education at the University of Illinois at Chicago, I worked in two different science museums and conducted research about informal science education. Currently, I’m the director of STEAM and Innovation for the Boy Scouts of America in Chicago. I oversee all STEAM (science, technology, engineering, arts, and math) programming, which runs the gamut of different mediums of science outreach, from videos to after-school activities! I’m fairly extroverted, so doing this work is quite a joy. 

Outreach through writing

I’m also a writer, mostly for mainstream online mediums. In most of my articles, I unpack challenging scientific findings and make them easy to understand. This kind of work is perhaps one of the most common jobs we think of when it comes to science outreach, i.e., the scientist penning a brilliant and retrospective piece for National Geographic. However, there are issues when it comes to writing, especially with presenting current research to a wide range of audiences. Sometimes the science itself is challenging to slough through (such as my Kavli Award-nominated piece on Neanderthal DNA in modern humans). Sometimes, it’s emotionally hard to work through (such as my article on the history of American eugenics). But kindling a sparkle of interest in someone’s eyes when they learn something new brings me such joy and fulfillment, and I bet it does for you too.

If you’re still interested in doing this as a career, awesome! I love my job, and I can’t recommend it enough, especially for those passionate about making science engaging and inclusive for everyone.  

Here are some tips on how to get started: 


1. Identify what medium you want to do: Are you chatty? Think about public speaking, a video series, or even serving as a scientist-in-residence at a museum (think Emily Gaskin of the Field Museum’s The Brain Scoop). But not everyone is outgoing, and some may prefer writing or drawing their science out. Heck, with all the animated modes that exist now, I’ve seen some brilliant work explaining challenging science in less than 5-7 minutes on teded.com. However, be honest with yourself: how do you like best explaining challenging subjects? On that note...  

2. Identify your audience: Who do you want to explain scientific findings to? It’s easy to say kids for most communicators. After all, children are young, they’re excited, and a little bit of foam and lightning gets them cheering. However (and I say this as both an educator and as a parent), certain subjects work better with older age groups, as well as humor. If your humor is a little of the dark and cheeky side, you may get some surly middle-schoolers engaged in physics. If you’re into bright and straightforward science that focuses on size, pre-kindergarteners may be your audience. But don’t forget their parents: adults are the largest audience for science communication and can understand more complicated concepts. With that being stated, as we’ve seen with the last four years of the Trump administration, science denial is a real thing and can be crushing to hear as a novice science communicator. Science denialism is especially relevant when it comes to what you are presenting on….  

3. Identify your subject: Some folks within science communication love to focus on one specific topic, such as neurology or wildlife ecology. However, plenty of informal educators focus on a wide range of subjects, such as myself or my fellow communicator, Sadie Witkowski at PhDrinking. Give yourself some thought: which topics make you passionate to write about, heck, to sell? There’s plenty of folks that groan at theoretical physics but squeal with joy when presented with the opportunity to give a tour of invasive plants in a prairie ecosystem. Speaking of green...

4. Look for work (if you want): If you’ve read this far and are going, “Yaaassss, Dr. Voggut Vegeta-barge! This is me, and this is the song of my people! I want to work in science communication!” Awesome, love to hear it. And don’t worry, boo, no one can pronounce my last names. Remember, there are a ton of different jobs to find, with various titles. Always look for the descriptions:

• need a teaching background (this is very common for museum/zoo positions, but years of being a TA as a graduate student will come in handy!).
• Ability to fundraise (not as scary as you think).
• Experience researching various subjects (such as museum studies).
• These are all descriptions that may lead you to a STEM education outreach job. Can’t find one?...  

5. Start your own work (if you want): A few folks have successfully trekked out on their own as guest speakers, authors, and illustrators. Self-starting and free-lancing can be challenging to do, as it requires not only grit (think rejection after rejection...but everyone reading has at least one failed NSF project under their belt, so y’all get it), but a fair amount of paperwork. It can be done, though! I’m currently getting paid for many of my articles through taking part with MassiveSci, where graduate students can gain experience, network, publish, and find out new paid opportunities for both contract and full-time work. 

This list, and my experience, is far from exhaustive. If you have any questions, please feel free to reach out to me or to many of the brilliant people running ComSciCon, which was the basis for me getting back into writing.