Don’t deny it: your password is terrible

by Viet Hoang

We have all been down this road: you are making a new account and you need to choose a password. You decide to use the same, easy-to-remember password that you have already used for every other account. You feel a little guilty because you know if someone gets ahold of one of your accounts, every other account will be compromised. Unfortunately, this has probably already happened. Avast, an antivirus company, has released a tool that will check a database of 30 million leaked passwords and search for yours: https://www.avast.com/hackcheck/. Over the years, many large companies have had large security breaches, such as Linkedin and Dropbox with over 117 million and 68 million passwords being leaked respectively (1,2).

Fortunately, all the passwords that were leaked were heavily encrypted. Before passwords are stored, they are processed using a hash function, which is a mapping between the input (password) and the output (hash) (3). 

A hash is a string of seemingly random characters that is unique to every password. The hashed password is stored in place of the real one. When a user is trying to log in, their input is hashed, and if the resulting hash matches with the hash stored in the database, then we know they have given the correct password without actually needing to know the password.

Despite the apparent strength of storing hashed passwords, hackers can also compute the hash of any string and compare it with leaked passwords. With access to modern computing power, they are able to compare millions of possible passwords per second (3). More powerful hash functions can slow down this process, but it is of no use if the password is easy to guess. 

What are bad passwords?

Any password under eight characters long is unacceptable, as it can easily be brute-force attacked (4). Suppose you have an eight-character password composed of only lowercase letters and numbers. There are 26+10=36 characters to choose from and you have to choose eight. Therefore there are 368 possible combinations, which may seem like a lot, but if the hacker is making millions of comparisons per second, then after a few days at most, your password is likely cracked. 

There is still no guarantee of safety for passwords greater than eight characters. Ideally, people would use random characters as their passwords. Unfortunately, humans are lazy and predictable and use simpler passwords that are easy to remember. They use common words, such as “password”, or names. Some are more diligent and will substitute some letters with numbers like exchanging “E” for “3” or “S” for “5”. Most modern password cracking techniques take advantage of this and use dictionary attacks, which use a list of commonly used words, names, and substitutions to crack passwords. 

How to construct an uncrackable password

A good password should be easy to remember and immune to both brute-force and dictionary attacks. Dr. Mike Pound from the University of Nottingham recommends that a password should be composed of four uncommonly used words (4). Any password of this structure should easily exceed eight characters, making traditional brute-force impossible. Furthermore, since there are approximately 170000 English words, the number of possible passwords is 1700004 which is far too large to use dictionary attacks. For even further complexity, words from different languages, misspelled words, and random symbol insertions can all be used as well. Putting everything together, below is an example password that is almost uncrackable:

terracot_taportfolliomagn1ifiqueabstract

The four words used are terracotta, portfolio, magnificent (in french) and abstract. Note that this specific password should never be used as it is now on a public website!

 

1. https://blog.linkedin.com/2016/05/18/protecting-our-members
2. https://www.theguardian.com/technology/2016/aug/31/dropbox-hack-passwords-68m-data-breach
3. https://www.geeksforgeeks.org/store-password-database/
4. https://www.youtube.com/watch?v=3NjQ9b3pgIg

 

Let’s Get Ethical

by Sofia Reynoso

Recently, I watched a documentary series called Unnatural Selection on Netflix. The show details how an emerging field of genetic engineering has caused a stir not only in the scientific community but among the general public as well. Concepts like “gene drive” and “biohacking” irked me for days after binge-watching the show, so I dove into the McGill eCalendar to find a class on bioethics, but to no avail. If this show had shaken me, finding not many options for my newfound interest shocked me even more. How was it that the future scientists of the world were not required to have an understanding of the ethical implications of their work?

Just this past December, the scientist responsible for editing the genome of twins using CRISPR for a study on HIV was sentenced to three years in prison. (1) The embryos of these twin girls were genetically modified to prevent HIV from being passed on from the HIV+ father. When he presented his work in 2018, he was met with outrage from scientists around the world. (2) Jennifer Doudna, a co-inventor of the CRISPR-Cas9 technology, cited the implications of a non peer-reviewed report by the scientist in question. (3) She also stated, “It’s very disturbing. It’s inappropriate. It goes against all of the guidelines that were established by the National Academy of Science’s report from 2017, and I think there’s just no way to defend it.” (4)

In addition, the infamous Tuskegee syphilis experiment is a classic example of how bias contributed to an obviously unethical study when African American subjects were misinformed regarding their treatment for syphilis, leading to a lack of consent. The study was conducted over 40 years. Following public outrage, the subjects and their families reached a $10 million settlement in 1974. (5)

Biology is not the only field subject to such scandals. In high school history classes, often students engage in debates surrounding the events that transpired in Hiroshima and Nagasaki during World War II. This is not just a debate of history. The development of the atomic bomb would not have been possible without advancements in physics and chemistry. Had the Manhattan Project not existed, the world would be drastically different. So was it ethical for scientists to develop the atomic bomb or other weapons of mass destruction?

While it may seem that McGill is somewhat detached from debates like these, in 2016, Dr. Alain Brunet, an associate professor in the Department of Psychology, developed a treatment plan for those who experienced heartbreak using a pill originally intended for those suffering from PTSD. (6) The groundbreaking work showed tremendous success but also begs the question: how far is too far?

Last semester, my friends in engineering mentioned a course they’re required to take called FACC 100 (Intro to Engineering Profession). When asked to explain the course description, one of my friends said, “I don’t know, ethics and stuff.” One assignment for the class posed an ethical question for the students and required them to write how they would grapple with the proposed situation. And while some may complain about the course, I longed for something similar in my Biology program. 

Although some ethics-related classes are available to science students, I still struggle to grasp why engineering students are required to discuss the ethical qualms of their future work, while science students are not. 

One of MSURJ’s goals is to encourage undergraduate students to engage in research on campus. Part of being a researcher is comprehending the impact of one’s work. McGill should encourage students to participate in ethical scientific research. If McGill wishes to raise the world’s best scientists, science students should be required to take an ethics course.

Even though the Faculty of Science does not require students to complete an ethics course, you can still search for one that may interest you. Here is a list with some options for science ethics courses:

Courses with a focus on ethics:

• NSCI 300
• PHIL 343
• PHIL 341
• ENVR 203
• ENVR 400

Courses with portion of class dedicated to ethics:

• PHGY 488 
• EXSU 500 
• BMDE 505
• PHAR 508
• BASC 201
• HGEN 400
• BIEN 200
• BIEN 330
• PHGY 351

*Note: Some courses listed may be restricted to you; make sure to check out the McGill eCalendar to confirm. In addition, some classes are in faculties other than science.

If you are a science student, be aware of this gap in our learning. McGill affords us an incredible education and opportunity to learn; in this case, we just have to seek it out. 

 

References:

1. https://www.cnn.com/2019/12/30/china/gene-scientist-china-intl-hnk/index.html
2. https://www.sciencemag.org/news/2018/11/crispr-bombshell-chinese-researcher-claims-have-created-gene-edited-twins
3. https://news.berkeley.edu/2018/11/26/doudna-responds-to-claim-of-first-crispr-edited-babies/
4. https://www.cnn.com/videos/tv/2018/11/28/news-stream-stout-doudna-crispr-chinese-scientist-babies.cnn
5. https://www.cdc.gov/tuskegee/timeline.htm
6. https://montrealgazette.com/news/local-news/montreal-research-broken-heart-there-might-be-a-pill-for-you

Scientific Research – a long term investment cut short by underfunding

by Alina He

Funding in scientific research has suffered a decade long decline in Canada. A recent reinvestment attempts to recover from this major setback.   

Most research is funded by government grants. In Canada, the Canadian Institutes of Health Research (CIHR), National Sciences and Engineering Research Council (NSERC), and Social Sciences and Humanities Research Council (SSHRC) are the major providers of federal research funding (1). The state of basic research in Canada was evaluated in the Naylor Report conducted in 2017 by the Advisory Panel on Federal Support for Fundamental Science (3). The report concluded that research funding had been on a decade long decline in Canada (3). In 2018, the government made its largest contribution to research funding with an investment of $1.7 billion over five years (5). However, this funding will mainly go towards attempting to recover from the underinvestment during the previous decade.

Canada was ranked 15th worldwide in funding for university research and development as a share of GDP in 2017 (2). This ranking alone does not necessarily give pause. However, if we look at the change in funding from 2011 to 2017, Canada is ranked 34th worldwide (2). This reveals the decline in government funding placed Canada in a less competitive position on the global level.

Underfunding resulted in research labs cutting down on lab members, equipment, and even closing down (3). A survey revealed 51% to 63% of mid-career and senior investigators will decrease their number of trainees, and 30% to 40% are considering moving from Canada or stopping their research altogether (3). The short term consequences of underfunding are severe. However, the long term consequences are far worse. There is an immense loss of research that could potentially have significant implications.

This issue does not only affect researchers, but also society as a whole. There is a general lack of public awareness about how critical research is to the progression of society. Basic research is the foundation for the healthcare and technology we have today, and it is the pathway for future innovation. As Professor Robert Dijkgraaf puts it, research is a long term investment, like saving for retirement (4). The federal funding put towards many projects has been directly linked to their success (4). Meaning, our return is based on our initial investment. The underfunding in previous years demonstrated a prioritization of short term over long term goals. This short-sighted view has held research progress back, and societal progress is paying the cost.

For those of us just getting into research, a lack of funding is especially troubling as it directly affects our job opportunities in the future. However, this is an issue that ultimately affects everyone. There is hope that the funding situation will improve. The recent budget increase was a step in the right direction, but continuous federal investment is necessary in order for research to move forward in a strong and sustainable manner.

 

Links 

1. https://www.mcgill.ca/research/research/funding/federal
2. https://itif.org/publications/2019/10/21/us-funding-university-research-continues-slide
3. https://www.macleans.ca/opinion/innovative-science-research-in-canada-is-dying-a-silent-death/)
4. https://futurism.com/expert-todays-lack-of-funding-for-basic-research-could-prove-devastating-in-the-future
5. https://www.universityaffairs.ca/news/news-article/budget-2018-gives-major-boost-fundamental-research-canada/

The hidden treasure that is CHEM396

by Elias Andraos

As a U2 chemistry student that completed a CHEM 396 project this past summer, I am surprised by how often other students that I mention the course to have not heard of it. I had a really great experience with it, so I thought I’d write up this little FAQ to let people know about the opportunities a CHEM 396 course can offer. 

Most of this applies to any 396 course, but I thought I’d make a pitch for CHEM 396 in particular.

What is a 396 course?

A 396 course is an independent research project that a student completes under the supervision of an instructor. It counts as an elective course and is designed to provide an introduction to undergraduate research. 396 courses are offered under all departments in the faculty of science.

I’m not a Chemistry student, can I still do a CHEM 396?

Yes! Any Bachelor of Science student can take a 396 course in any department at McGill. 

Why should I do a CHEM 396?

Even if you find chemistry absolutely boring (and I’m sorry if you do) it is a very useful tool in many different fields such as environmental science, biochemistry, biology, and many others. Many of the research groups in the department of chemistry at McGill are working on problems relevant to diverse topics such as cancer research, antibiotic resistance, and materials science. Doing a CHEM 396 project can help you see how chemistry can be used to further research in any field you may be studying. Additionally, the chemistry department at McGill has one of the highest research group to student ratios, meaning that there are many professors who have spots for undergraduates in their labs.

How do I approach a professor to ask for a project?

Find a professor whose research you find interesting by reading the short descriptions of their research here: https://www.mcgill.ca/chemistry/researchthemes. Many professors also link to the website of their research group. Read about their current research to be able to express informed interest in one of their research areas. Whether you want to write an email or try to talk to the professor in person (ideally in a situation where they will have time such as office hours) is up to you, but in either case, have a CV and a transcript ready. Be brave and remember; you’ve got nothing to lose.

Read more at…

https://www.mcgill.ca/science/research/undergraduate-research/science-research-courses

https://www.mcgill.ca/science/research/undergraduate-research/finding-opportunities#units

Think Outside of the Box When it Comes to Getting into Research

by Janet Wilson

The benefits of doing undergraduate research are extensive. It can teach you how to deal with failure, build key transferable skills and help you form an academic network. Understandably, undergraduate research positions are coveted by many. But truth be told, it is tough to know where and how to begin as a student-researcher and it can be intimidating to seek out a research position for the first time. But fear not, MSURJ is here! You may think that the only way to get involved as an undergrad is in a lab at your university, but that is far from true. There are many other research opportunities that you may not be aware of that can serve as an excellent way to begin as a student-researcher.

First off, I began as a student researcher in a hospital, administering surveys to patients, collecting and analyzing data. I was able to learn from diverse mentors at the top of their field of research, acquired valuable clinical and research skills, and was able to actively participate in all aspects of my project. Although it was very different from a traditional student research position in a university lab, I don’t think I missed out in the slightest.

Sometimes it can be challenging to obtain a paid research position in a hospital right away, especially if you don’t have connections. Therefore, it may be necessary to start by volunteering, in order to network and show your supervisors that you are a good fit for their position. If you are highly motivated to make money, there are many funding opportunities to seek out such as the Canada Summer Jobs program which your employer can use to subsidize your pay. When contacting professors/employers that you are interested in researching with, tell them about such funding sources. Often taking on an undergraduate student can be extra work for the lab, therefore it can be beneficial to let them know of funding sources.

Apart from a position in a hospital, another non-traditional research opportunity is in the private sector. Many companies look for student interns, particularly in the fields of mathematics, computer science and the physical sciences. Opportunities in the private sector are not only great for building your resume, but they also teach you key industry-specific skills, many of which cannot be taught in the lecture hall. They will also help you when you begin the inevitable post-university job search!

If you are passionate about a specific research topic, don’t be shy to expand your search outside of only the labs of McGill professors. Other universities in Montreal such as UdeM and Concordia are great resources. Also, research institutes such as the Computer Research Institute of Montreal (CRIM), the Research Institute of the McGill University Health Centre (RI-MUHC) and the Montreal Clinical Research Institute (IRCM) are all great institutions within our hometown to look into.

Finally, some faculty-specific research awards can serve to kick start your research career. These include the Summer Undergraduate Research in Engineering award (SURE), which provides a 16-week, full-time paid internship position in an engineering lab at McGill. The Science Undergraduate Research Award (SURA) and NSERC Undergraduate Research Student Awards (USRA) also provide funding for aspiring researchers in the Faculty of Science.

In summary, don’t be shy to pursue non-traditional research opportunities and good luck with your search!

Research-backed tips to help you work smarter, not harder this finals season

By Katharine Kocik

The last finals season of the decade is approaching, and whether it’s your first set of finals or last, it can be a stressful time. Here are some tips backed by recent research to help you survive the next few weeks.

Sleep – you’ve likely heard it before, and for good reason. Research consistently links better sleep quality, duration, and consistency with better academic performance. One recent nature paper found that factors related to sleep accounted for approximately 25% of variation in academic scores (1)! Although it’s easy to sacrifice sleep for more study time, knowing it can affect performance to this degree may encourage you to give it greater priority during finals. Anxiety is a serious challenge for many students while studying for finals, and research indicates that getting enough sleep can help to keep anxiety levels down. One study showed that even small increases in sleep duration lowered anxiety during the day, making it worth your time to sleep a little more for your well-being during a stressful time at school (2).

If you’re not getting enough sleep at night, research indicates that taking a nap can improve memory recall. A 2019 nature study looked at how different sleep patterns impacted chronically sleep-deprived high school students (3). Interestingly, students that “split” their sleep into a period of 5 hours at night and a 90 minute nap at 2:00pm performed better at memory tests than students that slept the same amount of time, 6.5 hours, all in the same period at night.

Don’t be afraid to shift your schedule to what naturally works best for you. A study of Seattle high school students in 2018 revealed that delaying school start times by an hour reduced sleepiness and improved academic performance (4). Fortunately, you can make your own schedule, so if you work better by waking up later and going to bed later, it may be better to lean into it rather than forcing yourself to wake up earlier than what is natural. McLennan Library is open 24 hours during finals, as well as Burnside for Science/Arts & Science students, and the Tim Hortons on Sherbrooke and University is always open (and also so much less busy at non-peak hours) for your coffee and snack needs. Just make sure to account for the time of your final!

In terms of mindset while studying, a study looked at students’ strategies for persevering through a task and identified a few mindsets correlated with success in completing challenges (5). Although it may be intuitive, it’s helpful to know what is shown to be effective for other students. The first of three strategies is “Emotional Regulation”, or maintaining a positive mood while working. This involved mentally reminding oneself to stay positive, if not taking other steps to stay in a good mood, like taking a break or studying with friends. Two other mindsets are thinking about completion being near, and thinking about the positive consequences of completing the task. For the former strategy, an example is reminding oneself that only finals remain after a semester of hard work, and for the latter, thinking about improving grades. A final strategy is keeping track of one’s progress towards a goal, by breaking a challenge into multiple steps and tracking completion of each part one-by-one.

Although research is a powerful tool in predicting if a lifestyle shift or new strategy might be effective, it’s also important to consider what is tried and true for yourself–you know yourself better than anyone else. If something isn’t working, though, it may be time to try something new, and research can help point towards what could make a difference

Best of luck this finals season!

 

1. Okano, K., Kaczmarzyk, J.R., Dave, N. et al. Sleep quality, duration, and consistency are associated with better academic performance in college students. npj Sci. Learn. 4, 16 (2019) doi:10.1038/s41539-019-0055-z
2. Cousins, J.N., Rijn, E., Ong, J.L. et al. Does splitting sleep improve long-term memory in chronically sleep deprived adolescents?. npj Sci. Learn. 4, 8 (2019) doi:10.1038/s41539-019-0047-z
3. Ben Simon, E., Rossi, A., Harvey, A.G. et al. Overanxious and underslept. Nat Hum Behav (2019) doi:10.1038/s41562-019-0754-8
4. Dunster, G.P., De La Iglesia, L, Ben-Hamo, M., et al. Sleepmore in Seattle: Later school start times are associated with more sleep and better performance in high school students. Science Advances. 4, 12 (2018) doi:10.1126/sciadv.aau6200
5. Hennecke, M., Czikmantori, T., and Brandstätter, V. ( 2019) Doing Despite Disliking: Self‐regulatory Strategies in Everyday Aversive Activities. J. Pers., 33: 104– 128. https://doi.org/10.1002/per.2182.

 

On the Horizon in Machine Learning: Identifying Natural Selection At Work in the Human Genome

Written by: Janet Wilson

Machine Learning (ML) is a rapidly evolving branch of artificial intelligence in which a program is developed that can evolve on its own and improve by learning from data and experience. It can be used to make predictions, classify items, estimate probabilities and more. For example, ML is used in Apple’s face recognition method, Google’s search result algorithms and fraud detection methods used by credit card companies.

In most recent news, ML is being trained and has been successfully identifying evolutionary pressures that the human genome is under and how natural selection is shaping it over time.

Due to the fact that the human genome is comprised of more than 20,000 genes and more than 3 million base pairs, ML has the potential to outperform humans by a large margin. The error-prone, tedious data analysis and DNA sequence searching/comparing methods that would have to be employed by humans would take ages and wouldn’t be nearly as accurate as computer-based methods have the potential to be.

Usually ML involves teaching a program how to perform a task using a method called supervised learning. The programmer will provide the machine with the expected output of the program and from this the machine will determine how it should generate the output. This is called the training phase. This challenging in the case of genome analysis, because the expected result of the computation we want the program to perform simply isn’t known.

Currently researchers are trying to train ML systems to identify evolution based on simulated examples of natural selection, allowing the machine to create and internalize a definition of what natural selection looks like from its own statistical, computerized point of view.

The second phase of ML involves testing the program on data other than that which it has encountered in its training phase. ML algorithms have been tested on genome data and have successfully identified the evolution of the lactase gene in caucasian populations. This is a clear, known example of evolution in the human genome which has allowed individuals with the lactase gene to digest cows milk.

Based on massive human genome sequencing, over 20,000 mutations have been identified that researchers want to understand further through ML. Now the task of researchers is to continue to train and perfect their programs to be able to identify and visualize the evolution of this massive number of mutations, that continues to increase.

Hopefully soon, these machines will be able to trace the evolutionary roots and propagation of all mutations found in the human population. Their refined skills will allow us to understand our evolutionary history and perhaps even predict the future evolutionary patterns of the human race. Although it is unfortunate that this is yet another example of computers outperforming humans, the potential applications of ML are vast and exciting. On top of genetic analysis and evolution-modelling, ML methods are being employed in many other fields and have the potential to drastically improve medicine, technology, marketing and much, much more. So we will have to sit back and see where ML leads!

Observing Molecular Machines using Cryo-EM

In 2017, the Nobel Prize in Chemistry was awarded to Jacques Dubochet, Joachim Frank, and Richard Henderson for their development of cryo-electron microscopy (cryo-EM). In 1986, Ernst Ruska, and Gerd Binning and Heinrich Rohrer won the Nobel Prize in Physics for designing the first electron microscope and for designing the scanning tunneling microscope respectively. In 1982, Aaron Klug won the Nobel Prize in Chemistry for developing crystallographic electron microscopy. With so many Nobel Prizes having been awarded for electron microscopy, what makes this recent development different from the other two?

The keywords for cryo-EM are proteins and resolution. Binning and Rohrer’s scanning tunneling microscope, designed way back in 1981, had a maximal lateral resolution of 0.1 nm and a maximal depth resolution of 0.01 nm—a resolution high enough to resolve individual atoms. They do this by slowly hovering a needle only one atom wide at the tip over an extremely flat surface of a solid that is made of a uniform lattice of atoms and reading the disturbances in the voltage difference between the surface and the microscope tip.

However, proteins (and other macromolecules but we are less excited about them—“another DNA structure, woooooo,” said nobody ever after the double-helix structure was determined in 1953) are these wild things that require atomic-level resolution to determine how the individual amino acids are oriented, but are also absolutely gigantic molecules where the 3-dimensional configurations of said amino acids matter just as much, if not more as their identities. Therefore it is no surprise that just slowly hovering a really thin needle over a uniform layer of proteins doesn’t really get you to this 3D structure. Not to mention that proteins are really delicate flowers and will precipitate and become some amorphous aggregate if you so much as look at them funny (okay I exaggerate, but only slightly). A good resolution of a protein for structural biologists averages at around 2.5 angstroms (Å, 1 Å = 0.1 nm), though there are many that have a higher resolution. For reference, a covalently bonded carbon atom has a diameter of 1.5 Å.

The current gold standard for protein structural determination is with x-ray crystallography, where an x-ray beam is fired into a protein crystal and due to the crystalline nature of the proteins, the single beam diffracts into many different directions which is caught on a screen. The beam’s diffraction angles and intensities can then be measured to produce a 3D electron-density map of the individual atoms can be reconstituted to eventually yield a complete 3D protein structure. However, protein crystallization often requires the use of poisonous salts and precipitants, and extreme pHs that would never be found in living organisms and very large proteins and membrane proteins are often impossible to crystallize. (Also the actual crystallization process is very luck-based and even for regular sized proteins may or may not happen. Trying to grow protein crystals is very good for building character.) This is where cryo-EM, our star, finally comes into the scene.

Electron microscopy usually uses some form of electron interactions between a source and the object to be imaged. In order to not disturb these delicate interactions, the imaging has to take place in an absolute vacuum, which falls under the “will aggregate protein” condition category. Instead, a pure sample of a protein of interest is frozen down and an electron beam is fired onto the frozen protein to produce an image—a “trace”—on a detector. Other than the freezing instead of vacuum, this sounds like pretty standard electron microscopy, no? The key advancements were figuring out how to flash freeze water-soluble proteins (because normal freezing could also fall in the “will aggregate protein” category, and may produce ice crystals which are NOT protein) and how to get the detectors good enough to achieve the really high resolution but also really large width required to image proteins.

The protein in the frozen sample is found in various orientations and from taking an image of hundreds of different orientations of the same protein using the new, high-tech detector that was recently developed, a computer can be used to generate a complex electron density map comparable to those obtained through x-ray crystallography, which can then be used to generate the true structure of the protein in high resolution and accuracy.

An example of cryo-EM images of a protein that together can be used to generate a 3D structure. Image: Maofu Liao, Harvard Medical School.

The beauty of cryo-EM is that it can do everything that x-ray crystallography cannot: image proteins in a non-poisonous environment and image very large proteins. It also doesn’t require painstakingly screening every possible combination of precipitant, salt, and pH possible and hoping and praying that out of one of those potentially thousands of combinations a crystal will grow within your tenure in that lab.

But you may be wondering, “who cares about protein structures anyways?”. Protein structures are very important in drug development, and are also important in understanding the molecular mechanisms of both healthy and disease states. Viruses are also basically protein assemblies, and determining their structures are very important in understanding their pathology and behaviour on a molecular scale. Also, they look cool! (Protein aesthetics is usually how people get suckered into structural biology). Appreciate this nice picture of the Zika virus obtained through cryo-EM. 

Cryo-EM structure of the Zika Virus. PDB: 5IRE Sirohi et al. (2016) The 3.8 angstrom resolution cryo-EM structure of Zika virus. Science. 352, 467-470

Happy lurking the cryo-EMs!

MSURJ Launch 2017

The 12th annual launch of the McGill Science Undergraduate Research Journal took place in the Bellini Atrium, where students from science, engineering, and other faculties joined to celebrate the achievements of undergraduate researchers at McGill. The authors, editors, and peer reviewers were also in attendance. Attendees grabbed some food and drinks, and then gathered to listen to the guest speakers. Three McGill leaders in scientific research generously shared their experiences in research and academia with the next generation of scientists.

First to speak was Dr. Tomoko Ohyama, the newest faculty member in the Biology Department. She talked about her research experiences in Japan, the United States, and Canada. Her research focuses on studying Drosophila larvae and their nervous system. She specifically studies the process of decision making in these larvae. When faced with a decision to make, “you think you are deciding, but I don’t think you are,” she hypothesizes. She hopes to be able to further elucidate the decision making process in humans by studying this process in Drosophila larvae.

Dr. Durcan, an assistant professor researching at the Montreal Neurological Institute, gave a short presentation on his experience in research over his lifetime. Currently, Dr. Durcan uses mouse models and stem cells to study the molecular basis behind neurodegenerative diseases such as Alzheimer’s Disease. He obtains stem cells from blood, which can become pluripotent, or stem cell like. He can then develop the cells into dopaminergic neurons. Before this technique was developed, it was exceedingly difficult for researchers to study neurons. In Dr. Durcan’s lab, he hopes to understand the cellular biology causes behind Alzheimer’s. Since the population of Canada is aging, he described neurodegenerative disorders as epidemics that are sweeping the nation. These disorders have become one of the leading causes of death, particularly for the older generation. Dr. Durcan said that without further research, these diseases will begin to overwhelm the healthcare system. His lab hopes to develop therapies for Alzheimer’s that will repudiate this dire future.

The final professor to speak was Dr. Kenneth Ragan. He is one of the faces that most new science and engineering students at McGill will become well acquainted with. He has been teaching first year physics classes for over 10 years and runs an astrophysics lab that specializes in studying the wave behaviour of particles at very high energies. After the casual mingling, he gave an equally casual speech on more than just what he researched, but rather on how he got to where he was. He talked about the fun and the spontaneity of life. He talked about how a scientist’s dream is to have their research appear on the Big Bang Theory. He talked about how it is okay not to know what one wants to do immediately, because in the end, everything will turn out fine. For a man of few words, he is one of many memorable speeches.

After the professors spoke, the author of the paper featured on the cover of this year’s edition of MSURJ gave a brief talk. She highlighted the importance of interdisciplinary research, as well as creating interdisciplinary teams for policy making. She emphasized that problems can be tackled from many different angles, and that we are more likely to create better solutions by combining the varied skills of different professionals.

This year’s event highlighted some of the exceptional research being done at McGill University by students and professors alike.

McGill Biochemistry Research Awareness Day (RAD) 2016

Research Awareness Day (RAD) is an annual event run by the Biochemistry Undergraduate Society (BUGS), which seeks to inform and inspire students about research being done by some of the foremost professors in McGill’s Biochemistry department.

Professors at this event first gave short presentations about the research being conducted in their labs, and then spent lunchtime answering questions from students. Students attending RAD were then given the chance to meet with three different professors in small groups, affording students the opportunity to ask professors more questions about their research and career path. After lunch, Dr. Young gave a presentation detailing ways for students to get involved in research as an undergraduate. The event ended by transitioning into an intimate cocktail hour, during which there were poster presentations by graduate students in these professors’ labs.

Overall, RAD was a well-structured, successful event that gave insight into the groundbreaking research being done by professors in the Biochemistry department. It provided students the opportunity to learn more about a career in research, and how to get involved as an undergraduate.

Listed below are some of the professors at this event, along with a brief overview of the research that they discussed.

 

Professor Albert Berghuis:

With the rapid development of antibiotic resistance, the need for new antibiotics has become increasingly urgent. This is the focus of Dr. Albert Berghuis’ research. The Berghuis lab uses structural biological approaches to examine various biochemical interactions. The goal is to use techniques such as X-ray crystallography, electron microscopy, and NMR spectroscopy to examine the enzymes with which bacteria destroy antibiotic molecules, and use that knowledge to create next generation antibiotics that can bypass the enzymes but remain biologically active. With pharmaceutical companies stopping antibiotic development due to a decreased profitability, it’s up to independent laboratories such as that of Dr. Berghuis to continue the research in this field. His lab also studies the development of anticancer drugs.

Dr. Kalle Gehring:

The prime focus of Dr. Gehring’s lab is to decipher the structure of various proteins, particularly those involved in neurodegenerative diseases and the ubiquitin system, protein folding in the endoplasmic reticulum, and bacterial virulence factors. A typical project at the Gehring lab consists of growing bacteria to extract and purify a certain protein, crystallizing the protein, and the analyzing its structure using X-ray crystallography and NMR spectroscopy. Recently, the lab is pursuing the study of parkin, a protein involved in a link between mitochondria and neurodegenerative diseases such as Parkinson’s disease.

Dr. Sidong Huang:

Dr. Huang’s research is focused on using a functional genomics approach to study cancer-related mechanism, and to create new treatment strategies for cancer using this information. The current approach to cancer treatment primarily involves chemotherapy and drugs that target cancer cell mutations. Current cancer drugs are not very effective as resistant cancer develops in almost all patients. While the main solution to this problem is through the development of new drugs, Dr. Huang uses another approach. Using functional genomic tools such as shRNA, cDNA and CRISPR libraries, Dr. Huang and his students systematically screen each gene and create custom drug combinations that target those that modulate drug resistance. They also hope to uncover genetic dependencies of cancer pathways which then can be exploited therapeutically. This novel approach hopes to overcome drug resistance in cancer patients and to provide a more effective treatment strategy.

Dr. William J. Muller:

The Muller lab creates and uses murine models of human breast cancer to understand the effects of oncogene activation in normal cells, discover the cooperation between oncogenes and tumour suppressors, and eventually develop preclinical models.

Dr. Bhushan Nagar:

The Nagar lab uses structural techniques to analyse macromolecules, with specific focus on determining innate immunity mechanisms and nucleotide-specific interactions in mRNA silencing.

Dr. Nahum Sonenberg (represented by Argel Valles and Nathaniel Robichaud):

The Sonenberg lab conducts diverse research on two major topics: mRNA translation and translational control of cancer. Through researching how different pathways are affected and alter mRNA translation, the Sonenberg lab hopes to better understand Autism spectrum disorders and psychiatric disorders. Research in translational control of cancer aims to understand how non-cancer cells can promote tumour survival, as well as develop methods of tumour selective killing of cancer cells.

Dr. Jose Teodoro:

The Teodoro lab aims to determine the role that transcription factor p53 plays in tumour angiogenesis. Angiogenesis is a natural process in human development and wound healing, but in tumours, angiogenesis allows the cancer cells to have access to nutrients that otherwise would be inaccessible. The Teodoro lab also hopes to use virus target specificity in cancer treatment.

Dr. Ian Watson:

The Watson lab aims to translate the genome of melanoma, the deadliest form skin cancer, in hopes of developing new therapeutic strategies.

Dr. Jason Young:

The Young lab focuses on the function of chaperones in protein folding, with emphasis on the roles of misfolded proteins in neurodegenerative diseases such as Parkinson’s disease. The function of the Hsp70 chaperone system and its role in disease states are of particular interest.