Tag: #LoveResearch

What Can VHI Women’s Mini Marathon Do For You?

I have never been a runner. In my head, the word ‘marathon’ was linked to professional athletes and the Olympics or Athletics competitions. I could not imagine anyone doing a race as long as one gets guts. However, once I found the courage and motivation to explore my body’s limits. It was probably our team fundraising ‘Hell&Back’ challenge in 2019 that ignited that courage. We did many! Virtual VHI MiniMarathon, the Dublin Mountain Way in a Day, Cyclothone, to name a few.

Eventually, I decided to do it on my own in 2024. I booked the VHI Mini Marathon 2024 entry and started my training. Having many fitness apps at my disposal let me pick the right training plan. 10K sounded manageable. The fitness watch kept all my training records, so I got a very good understanding of my body potential and limits to do 10K.

On that sunny day, hundreds and hundreds of women were getting to the starting line. Each set their own ambition and target. I had three: 1) jogging from start to finish, 2) finishing within 1hr and 20 min, and 3) supporting the Conor Foley Neuroblastoma Cancer Research Foundation.

So, June 2nd was fast approaching, and I injured my calf during the Wicklow hike. However, giving up was not an option, but healing was required. So, I decided to stop running for a week and gradually get back on track.

The atmosphere was cheering and empowering, and the sun was bright and hot. The green ‘wave’ began their race at about 12:45. Running in a big company was easy. It is less doubtful if you are in a group of allies. Distance and time flew. I was sinking into the diversity and variety of running women and supporters along the road, enjoying every minute. Some took over me, and I took over some. I stuck to my training pace to ensure my power and energy were not draining quickly under the sun. My fitness watch counted the distance, heart bit and steps, showing that I was slightly slower on average than during my training. I decided not to break the limits and kept running, listening to my body. Somewhere at the back of my head, I hoped to speed up at the end, if any. Unfortunately for me, the final 1-2 km were up the hill, so the slop ate my efforts.

Being a researcher puts every experience in perspective. We tend to analyse the flow of any information, sometimes unconsciously, by asking questions and reflecting. One of the running advantages is that you see an accomplishment right now at the finish line. Your fitness watch provides all the data to plan and complete a given challenge with very good accuracy. It is not about luck. It is about your trust in your body and mind. You are in the driving seat! Delighted with my accomplishment!

So, what is next on my to-do list? Definitely another race, very likely Run in the Dark.

Written by Olga Piskareva

Class 2024: Congratulations to Ciara, Ellen and Rabia!

Massive congratulations on the official moulding of PhD and MSc by Research to our promising young scientists: Rabia Saleem, Dr Ciara Gallagher and Dr Ellen King! Great accomplishments!

Three different journeys, with two through the COVID-19 pandemic. The full range of ups and downs. Who said that the PhD is a straight line? It has never been. It is more like the Irish weather: some days are sunny and bright, and some have scattered showers, gale winds and stormy snow, with sunshine developing elsewhere. The journey was spiced up with publications, conferences, travels, days out and fundraising events with the team.

It is a proud moment for me as well. 🙂 Three PhD and one MSc by Research students graduated within the last 12 months.

Of note, Ellen was behind our Twitter activities in the past, making our team visible!

Wish you all the best of luck on your new adventure!

Olga Piskareva

How things work in science: Gene editing technology

Few advancements in biomedical sciences hold as much promise for revolutionising cancer research as CRISPR-Cas9. This ground-breaking gene-editing tool has sparked a wave of innovation, offering precision and efficiency in manipulating the human genome in the fight against cancer.

Now, what is it? CRISPR is basically an acronym for a very long name Clustered Regularly Interspaced Short Palindromic Repeats Associated Protein 9 or CRISPR-Cas9 for short. It was found in simple organisms such as archaea and bacteria. Interestingly, this is a component of bacterial immune systems that can cut DNA. So, this feature was proposed for use as a gene editing tool, a kind of precise pair of molecular scissors that can cut a target DNA sequence. So, the CRISPR-Cas9 scissors allow us to precisely edit the DNA sequence of living organisms by adding in (knock-in) or removing (knockout) a gene of interest.

For cancer research, for example, the CRISPR-Cas9 scissors can be used to introduce therapeutic genes or correct mutations associated with cancer predisposition syndromes. Meanwhile, those scissors can also disrupt genes involved in treatment resistance, sensitising cancer cells to existing therapies.

Jennifer Doudna and Emmanuelle Charpentier have won the 2020 Nobel Prize in Chemistry “for the development of a method for genome editing.”. A nice accompanying piece was published in The Conversation, highlighting the history of these scissors and the politics behind it.

Jennifer Doudna explains this revolutionary genetic engineering tool in a TED lecture. However, she warns:

“All of us have a huge responsibility to consider carefully both the unintended consequences as well as the intended impacts of a scientific breakthrough.”

I hope you enjoyed it!

Witten by Rabia Saleem

Congratulations to a new Dr in the house: Dr Ellen King

Huge congrats to a newly minted Dr Ellen King!  She passed her PhD viva on April 9. This is a testimony to your dedication, strong will and hard work. May this PhD be the beginning of many more successful endeavours, Ellen!

We thank examiners Prof Sally-Ann Cryan (RCSI) and Prof Joanne Lysaght (TCD) for the time and expertise they provided.

We also thank the RCSI PhD Programme for their generous support!

From left to right: Prof Joanne Lysaght, Dr Ellen King, Dr Olga Piskareva & Prof Sally-Ann Cryan

How things work in science: targeting cell components.

How do researchers study cells? How do we get the nitty gritty?

We use many methods to tag and chase various cell components. One of my favourites is fluorescent microscopy. It allows the use of nearly all spectrum of colours from blue to purple in one go. However, we prefer to narrow it down to 2-3 colours and avoid their overlap.

How does it work? First, we use DAPI or Hoescht, which are blue fluorescent dyes used to stain DNA. This way, we tag the nucleus of the cell. Then, we tag a protein of interest. In our case, it was MYCN, a protein that acts as a transcription factor. MYCN amplification is associated with poor prognosis in neuroblastoma. As a transcription factor, it binds to genomic DNA and is located in the nucleus. We used a specific antibody that was labelled with a green fluorescent dye. Look at the image below. The green colour pattern overlaps with the blue colour. Then, we tagged the cytoskeleton, a complex of various proteins that hold the cell architecture and dynamics. We used phalloidin with red fluorescence. It is a highly selective bicyclic peptide and a popular choice for staining actin filaments.

Neuroblastoma organoids stained with DAPI, Phalloidin and anti-MYCN antibody. This work was done during the Fulbright journey to Ewald’s Lab at Johns Hopkins

Now, we can enjoy visualising cells and test different research questions. For example, how do cells respond to a drug? Or how do neuroblastoma cells spread?

Written by Olga Piskareva

How things work in science: Scaffolding

At the Cancer Bioengineering Group, we use different types of scaffolds to mimic the 3D structure of tumours outside the body. We use these scaffolds to test new therapeutics and understand the tumour microenvironment. But I bet you didn’t think we had this in common with spiders?

Spiders make their webs by producing silk from specialized glands in their abdomen. They release the silk through spinnerets located at the back of their abdomen, then use their legs to manipulate the silk strands into intricate patterns, depending on the species and purpose of the web.

The process of web building begins with a scaffold. The specialized glands that spiders use are called spinnerets, and they produce liquid silk proteins that solidify into a thread when they come into contact with air. Using their many legs, spiders can manipulate the threads by changing the speed and tension they enforce on the silk, thus controlling thickness, stickiness and strength. They first lay a framework of non-sticky threads, known as scaffolding. And layer by layer, different species of spiders will add their own artistic sticky silk design to the scaffold depending on their aim. Take the deadly redback spider for example, these guys have a utilitarian approach to web building relying on their webs mainly for shelter and capturing prey. As such, they don’t put much effort into producing irregular and messy homes. In comparison, the orb-weaving spider produces “Mona Lisa”-like designs, with complex geometric patterns and intricate designs. The differences in effort seem to come from the environments in which the webs are located, with the redbacks choosing more sheltered environments and thus not needing much strength to their webs. Whereas orb-weaving spiders are more adapted to a range of environments, from forests to grasslands to urban gardens. So, while the redback gets a lot of attention for their neurotoxic venom, they need to step up their artistic skills to match that of their orb-weaving colleagues.

The redback spider and its webs are reminiscent of an aggressive tumour, which is erratic, dangerous, and unpredictable. We want to find the “anti-venom” for such tumours so we can wipe them out for good.

Watch this amazing web-building timelapse by BBC Earth.

Written by Ellen King

How things work in Science: Tìr na nÒg

In humans, NANOG, SOX2, and OCT4 are transcription factors that maintain the undifferentiated state of embryonic stem cells (ESCs). NANOG was first discovered in 2003 by Chambers et al. and Mitsui et al. as a transcription factor in ESCs responsible for cellular self-renewal. More importantly, it enables continuous self-renewal of cancer stem cells, leading to metastasis when the regulatory genes involved do not function normally. These have been identified as cancer stem cells, with NANOG being a marker of “stemness”. In multiple cancer types, NANOG has various effects, including cellular expression of mesenchymal phenotype, cellular invasion/migration, repressed apoptosis, drug resistance, and increased angiogenesis. In pathways, NANOG either promotes or represses the expression of other genes that lead to cancer-favoured cellular behaviour. Overall, a higher expression level of NANOG is usually indicated in cases of poor prognosis.

NANOG is even more interesting due to its eponym, which comes from TĂŹr na nÒg. A Celtic myth of the Land of Youth, where the Tuath DĂ© resided in a supernatural land of paradise. This land offered beauty, health, joy, and everlasting youth to the inhabitants. As the myth goes, the Tuath DĂ© were gods of the land, and the god that ruled, ManannĂĄn mac Lir, was the first ancestor of humans. In various Celtic legends, humans are invited by the gods to visit TĂŹr na nÒg on great adventures.

However, time passes much slower in Tìr na nÒg, making it precarious for humans to return to their own world. As is the fateful tale of Oisín, who fell in love with the Tìr na nÒg goddess, Niamh. He travelled with her to Tìr na nÒg, where they lived happily in paradise. Upon a visit back to Ireland, Oisín realized that all his family had died over the years. When Oisín found a group of men who were struggling to move a giant rock, he stopped to lend them a hand while on his horse. However, the weight of the rock caused his saddle strap to snap. He fell from his horse, and when he touched the ground, he suddenly aged 300 years all at once.

Written by Alysia Scott

Sources:

Gawlik-Rzemieniewska, Natalia, and Ilona Bednarek. “The role of NANOG transcriptional factor in the development of malignant phenotype of cancer cells.” Cancer biology & therapy vol. 17,1 (2016): 1-10.

“The Story of Tír Na NÓg.” Celtic Titles, 10 Feb. 2022

Congratulations to Dr Ciara Gallagher!


Huge congrats to a newly minted Dr Ciara Gallagher!  She defended her PhD on March 8 – International Women’s Day. Your enthusiasm and perseverance are truly fascinating! May this be the stepping stone towards a brighter future, Ciara!

We thank examiners Dr Marie McIlroy (RCSI) and Prof Jan Ć koda (Masaryk Uni) for the time and expertise they provided.

We also thank the Irish Research Council for their generous support!

Dr Ciara Murphy (Chair), Dr Olga Piskareva (Supervisor), Dr Ciara Gallagher, Prof Jan Skoda (examiner), Dr Marie McIlroy (Examiner)

Ever wonder how scientists figure out a specific protein’s role in cancer?

Researchers use various methods, but I employ gene knockdown in my experiments. Basically, I use small RNA molecules that specifically target and degrade the mRNA of my gene of interest. This leads to a decrease in the corresponding protein levels, enabling me to observe the effects on neuroblastoma cell behaviour.

I feel a bit like Sherlock Holmes, you know? I’m selectively putting my suspect protein – the one I’m eyeing – under the spotlight to see how it’s pulling the strings on the cell’s behaviour. It’s like I’m in a cellular mystery, complete with a gene knockout magnifying glass đŸ”đŸ§ŹđŸ•”

So, what I’ve been up to these past months is knocking down my protein and trying to find answers to the following questions:

Can neuroblastoma cells survive? And if not, how do they meet their demise? Do they go on a growth spree and start proliferating? Are they capable of migration? And here’s the twist – when my protein of interest takes a dip, do other proteins decide to change their expression levels?

The picture below can probably help you get an idea of what I’ve done so far. Do you see those brighter spots in Pictures A and B? Those are dead cells. Their number indicates the proportion of dead cells after a treatment. Picture A has just a few; the majority are healthy and well-spread cells. This is our negative control, a condition when we show neuroblastoma cells that have been transfected, but no gene knockdown happened. Transfection is the term for introducing small RNA molecules. Now, in Picture B, when we knocked down the protein, it caused the death of the cells, and you can clearly see that from all those many little bright spots.

We have found answers to many of the previous questions, but new questions have arisen, and we can’t wait to answer them!

Written by Federica Cottone

How things work in Science: Classifiers

For our next little series introducing a different thing in science and how it works every week, I decided to focus on classifiers. With artificial intelligence becoming more and more prominent in our daily lives as of late, I thought this would be a good lead into the explicitly science-focused topics to come. So, what is a classifier? How does it work? And why does it matter?

At their core, classifiers are algorithms designed to categorize input data into predefined classes or categories. They learn patterns and relationships from labelled training data to make predictions on new, unseen data.

Once features are extracted, identified and quantified from labelled or annotated input data, mathematical models are employed for pattern recognition and predictions.

These models can range from simple decision trees to complex neural networks, each with its own strengths and weaknesses.

Training these models is an iterative process. That means to produce one good classifier, lots of classifiers were created in the process: Every time the pattern recognition is run, the annotated data is categorised by the classifier and compared to the annotation class. Prediction errors are corrected, and performance is optimised. This whole process is one iteration. How many iterations are required for a well-trained classifier varies widely and is largely dependent on the input data and application. For my tissue classifiers, it took up to 20,000 iterations.

Classifiers use these models to categorise unseen data into categories the user-defined at the start. In the figure, you can see my annotated histological slides from which the classifier extracted patterns to then classify the rest of the slide and entirely unseen slides into tumour (red), stroma (green) and background (blue) classes.

From identifying fraudulent transactions, filtering out junk mail, targeted advertising, and facial recognition to unlock your phone or diagnosing diseases, classifiers play a vital role in automating decision-making processes and driving advancements across a wide range of industries. Keep your eyes peeled, and you can find more classifiers in action all around you.

Written by Ronja Struck