Issue 10: Fact & Fiction 2 June 2026 This issue traverses the boundaries of truth, certainty and fabrication. Join us to illuminate the myriad grey space that lies in between. Editorial Shining Light on the Grey by Ingrid Sefton, Kara Miwa-Dale and Anabelle Dewi Saraswati A word from the Editors-in-Chief and some enlightening insights from this Issue's Cover Illustrator Biological evolution That Protein is AI, Dude by KJ Srivastava Move over nature, is artificial intelligence the new apex predator of protein evolution? Determinism and indeterminism Contingent Realities - the (Ph)ailure of a (Ph)act by Edmond Sim From Plato to quantum mechanics, Edmond muses whether objective facts truly exist — or if reality depends on who's observing it. Climate change To Prevent Climate Catastrophe, Keep Reading by Madeleine Kelly Madeleine argues its time to rewrite the landscape of climate fiction from one of impending doom into one of hope and action. Paleontological reconstructions Terrible Lizards and their Terrible Reconstructions by Kaya Czerwinska A flying Stegosaurus, upside-down Hallucigenias: Kaya revisits palaeontology's most delightfully bizarre mistakes. Traditional Chinese medicine The Human Body: A Portrait Painted by a Thousand Minds by Isaac Tian Isaac examines how different cultures have attempted to answer the same timeless question: how does the human body truly work? Neuroscience When Fiction Feels Real: How the Brain Builds Reality by Terra Gi Where does reality exist: in the world, or in our mind? Terra probes how the brain blurs the boundaries of perception and experience. Genetic engineering The Predictions of Genomics: Fictions Once Called Fact by Scarlett Yang Beyond mere educated guesses, precision in scientific prediction is paving the way forward in genomic innovation. Little scientists Young Scientists in the Making by Kacy Toombs Cultivating curiosity in children is not only considerate, but fundamentally scientific, Kacy posits. Biobanks How Population Biobanks Shed Light on Disease by Jason Chien Jason unlocks how biobanks are helping researchers probe new insights into human health and disease. Sex differences Unpacking Myths: Distortions of Sex Differences in Popular Culture by Vicenta Wheatley From dating podcasts to TikTok algorithms: how science on sex differences is simplified, sensationalised, and sold. Time travel Reimagining Time: From Relativity to Wormholes by Zahra Halela If time is relative, bending the bounds of physics and reality, Zahra considers how far-fetched the notion of time-travel really is. Truth under AI Are Truths Possible Under AI? by Vanessa Cheng As AI blurs the line between truth and deception, Vanessa considers how it is changing the way we see the world. Opposites attract Dating Isn’t Physics – Opposites Don’t Attract by Elva Assisan Elva repels the theory that our magnetic pull towards the trope of "opposites attract" is founded in science. Misinformation Fiction Disguised as Fact: The Cost of Scientific Misinformation by Kara Miwa-Dale Vaccines save lives — but as Kara explores, misinformation can undermine them just as powerfully.

< Back to Issue 10 The Predictions of Genomics: Fictions Once Called Fact by Scarlett Yang 2 June 2026 Illustrated by Anabelle Dewi Saraswati Edited by Aimee Fogarty-Bennett What is a prediction in science? We often think a prediction is just a guess about the outcome of an event – something we throw out into the blue and then try to test. I, for one, have definitely thrown out random guesses when I didn't do any pre-reading for my university practicals. However, predictions are more than random guesses. They require a set of precise beliefs about how the world works. In making a prediction, we essentially pull from a past set of beliefs, particularly scientific knowledge, to say we believe this will happen in the future. Scientific predictions must be precise so that they can be proven wrong. We like making statements that are likely to be true under all circumstances (after all, it does feel great to be right!). However, it's important to know that the point of a prediction is its provability. When our prediction is wrong, we are able to begin questioning the perceived ‘facts’ of science and revise them to more accurately predict the future. It is precisely this falsifiability, and what happens when our predictions are proven wrong or incomplete, that is sometimes more important than a correct prediction. Essentially, we can say that scientific predictions are 1) based on past knowledge, and 2) specific. Think of it this way: we are trying to run a printer, and we know that there is a red cartridge and a blue cartridge inside. A guess would be to say, "We will print colour”. This is not specific enough to be proven wrong, and not based on our past knowledge. Instead, a prediction would be that, based on colour theory, "if I have red and blue , I should get purple text." If we print and get green ink, I know there is something wrong with my past knowledge. What we thought was fact becomes fiction we had postulated. Each new fact we collect reshapes the prediction that follows, nudging our proposed knowledge closer to the truth. After all, what makes science ‘science’ is the fact that it is rarely certain, but rather a process of increasingly more accurate predictions. One of the most extraordinary fields for watching this process is genomics. Understanding our genome The birth of genome analysis arguably came with the Human Genome Project. The idea was, in itself, quite simple. If we could sequence all three billion base pairs of human DNA, every genetic instruction our body follows, we could surely understand all diseases. It would enable us to predict, and ultimately prevent, the things that kill us. It took thirteen years and roughly three billion dollars. It was completed in 2003 (1). It was an incredible achievement. Unfortunately, it did not solve all problems. However, it was incredible all the same because it revealed the scale of what we did not yet know about human function. The genome is not a simple instruction manual. It is a dense, layered system in which the same sequence can mean different things depending on context, timing, the presence of other genes, and environmental signals we are still cataloguing. Say, if our red cartridge and blue cartridge are the genetic code, whether or not we get purple ink depends on the instructions the computer sends, whether the printer is working, and the relative amounts of red and blue ink, including the possibility of no blue at all. A green page means something is releasing yellow somewhere we didn't expect. A red page means something is blocking the blue cartridge entirely. It's easy to know we have blue and red cartridges inside. Understanding how the cartridges are actually used by the printer has occupied genomics ever since. These letters have allowed us to do something genuinely strange and exciting: simulate a living organism from its own genetic data. NeuroMechFly is one such project, a digital fruit fly with sensors that receive signals and six legs that respond to virtual terrain (2). The aim of the project is to find where our predictions, shown by the simulation, about real flies fail, and what that tells us about the nervous system and how it controls movement. If the model holds up to real behaviour, our understanding is roughly correct. If not, there is more to know. So far, researchers are still working on it. But what simulations like this can do is expand our understanding of humans, since more than 60% of fruit fly genes have human counterparts, and roughly 75% of the genes known to cause human genetic diseases are also found in flies (3). Indeed, fruit flies have helped us understand human biology in the past, including giving us the first tumour suppressor gene (4). But even so, isn't it interesting to consider the effects of using flies as a model of disease for humans? And whether our predictions about being "similar enough" actually hold? It is important to keep in mind that we cannot always extend our understanding directly across species. If we do, we can meet a paradox . Paradoxes We know that as we get older, we get significantly higher cancer rates. The science behind this is simple. As our cells replicate more, there are higher chances of mutations building up, thus leading to higher chances of cancer. Similarly, larger humans have higher rates of cancer, simply because there are more cells, more divisions, and as a result, a higher chance of mutation. Essentially, printing a thousand pages should produce more errors than printing ten. If we extend this knowledge to a bowhead whale, which weighs over 80,000 kg and lives more than 200 years compared to humans – averaging around 70 kg and 80 years ourselves – we would predict whales must be riddled with cancer. This prediction was reasonable, evidence-based, and most importantly, wrong. Across mammals, there is no correlation between body size, lifespan, and cancer incidence. A mouse weighs around 20 grams. A blue whale weighs up to 150,000 kilograms. The cancer-rate difference between them is incredibly small. The observation that large, long-lived animals do not carry proportionally enormous cancer burdens was first formally noted by the statistician Richard Peto in 1977. It became known as Peto's Paradox, and it has been generating arguments ever since (5). I have two predictions about why it fails. First, cancer rates in large animals are simply difficult to measure. Our data is incomplete, our sample sizes are skewed, and our conclusions are premature. Second, for a whale-sized organism to exist at all, it must have evolved mechanisms of cancer suppression far beyond our own. Either or both could be true. Neither might be. So far in science, we have found extraordinary mechanisms that potentially explain parts of this paradox. TP53 is a tumour suppressor gene which codes for a protein that detects DNA damage and triggers cell death before a damaged cell can divide. Elephants have 20 copies of this gene compared to the single copy humans carry (6). When their cells are exposed to DNA damage, they undergo apoptosis more effectively, meaning problematic cells die before they can replicate. Bowhead whales express a gene called CIRBP at around 100 times the level of other mammals, which dramatically improves the repair of double-stranded DNA breaks (7). Rather than killing damaged cells, the whale's cells repair the DNA so that mutations rarely accumulate. When researchers applied these mechanisms by introducing higher CIRBP expression into fruit flies, the flies lived longer and became more resistant to radiation-induced DNA damage. In human cells, DNA repair efficiency roughly doubled (7). We are starting to take what evolution spent millions of years building and turn our predictions into intention. We are starting to explore the possibility of applying these mechanisms to humans through the exciting field of genetic engineering. Genetic Engineering If we understand genetic information from genomics well enough, can we rewrite it? As with all things in science, the answer is: only if we narrow the scope of the question, and provide specificity. If a genetic condition is caused by a single gene, the answer increasingly is yes. One such case is a baby called KJ Muldoon, who was born with a faulty gene for the protein that breaks down nitrogen. Without it, ammonia builds up in the blood, which is highly toxic. Using a CRISPR base editing therapy designed specifically for KJ's mutation, the wrong DNA letter was converted to the correct one (8). Instead of living in and out of hospital, KJ has been able to live a normal life. Genetic engineering is a field of extraordinarily rapid development. We have already moved from the early approach of extracting cells, editing them outside the body and returning them, to delivering the editing machinery directly into living tissue. Maybe one day we can answer the broader question of addressing diseases that are caused by far more complex factors than a single gene. But for now, being able to help KJ live a normal life despite being born with a condition that had no cure is an inspiring example of how predictions can be turned into intentions, fiction into fact, and how genomics is changing the world of biology. References National Human Genome Research Institute. International consortium completes Human Genome Project. National Institutes of Health. April 14, 2003. https://www.genome.gov/11006929/2003-release-international-consortium-completes-hgp Lobato-Rios V, Ramalingasetty ST, Özdil PG, Arreguit J, Ijspeert AJ, Ramdya P. NeuroMechFly, a neuromechanical model of adult Drosophila melanogaster . Nat Methods . 2022;19(5):620-627. doi:10.1038/s41592-022-01466-7 Reiter LT, Potocki L, Chien S, Gribskov M, Bier E. A systematic analysis of human disease-associated gene sequences in Drosophila melanogaster . Genome Res . 2001;11(6):1114-1125. doi:10.1101/gr.169101 Gateff E. Malignant neoplasms of genetic origin in Drosophila melanogaster . Science . 1978;200(4349):1448-1459. doi:10.1126/science.96525 Callier V. Core Concept: Solving Peto's Paradox to better understand cancer. Proc Natl Acad Sci U S A . 2019;116(6):1825-1828. doi:10.1073/pnas.1821517116 Sulak M, Fong R, Mika K, et al. TP53 copy number expansion is associated with the evolution of increased body size and an enhanced DNA damage response in elephants. eLife . 2016;5:e11994. doi:10.7554/eLife.11994 Firsanov D, Zacher M, Tian X, et al. Evidence for improved DNA repair in the long-lived bowhead whale. Nature . 2025;648(8094):717-725. doi:10.1038/s41586-025-09694-5 Children's Hospital of Philadelphia. World's first patient treated with personalized CRISPR gene editing therapy at Children's Hospital of Philadelphia. CHOP News. May 15, 2025. https://www.chop.edu/news/worlds-first-patient-treated-personalized-crispr-gene-editing-therapy-childrens-hospital Previous article back to Fact & Fiction Next article

< Back to Issue 10 Fiction Disguised as Fact: The Cost of Scientific Misinformation by Kara Miwa-Dale 2 June 2026 Edited by Nushi Singh In 1998, Andrew Wakefield published a paper in The Lancet claiming that the MMR vaccine was linked to autism. For such a serious claim, the evidence was astonishingly weak (1). The study included only 12 hand-picked participants, had no control group, and was riddled with inconsistencies. To make matters worse, Wakefield failed to disclose that he had received funding from a lawyer representing parents taking legal action against vaccine manufacturers. He further concealed that he had filed a patent for a rival vaccine that stood to benefit if confidence in the MMR vaccine fell. Despite these glaring flaws, the paper gained enormous influence. Media outlets across the world amplified its alarming claims, often with little scientific scrutiny (2). The Wakefield study became one of the clearest examples of fiction disguising itself as fact: a false narrative cloaked in the appearance of scientific credibility. Once released into the public sphere, emotionally charged claims quickly began to overshadow scientific evidence. Wakefield’s paper sparked widespread concern about the MMR vaccine. Few members of the public were likely to read the original study themselves, let alone critically evaluate its methods. Instead, many depended on journalists and news reports to interpret the findings. In doing so, they relied on a broader trust in scientific institutions and science communication, often assuming that published research had already been thoroughly vetted (3). This misplaced trust had far-reaching consequences. Before the paper was published, MMR vaccination rates in the UK sat at around 91-92%. Within five years, by 2003, this had fallen to approximately 80% (4). Although it is impossible to prove that Wakefield’s paper alone caused this drop, there is little doubt that it ignited widespread anxiety. By the time subsequent research had comprehensively refuted the claims (5, 6, 7), public trust had already been badly damaged. The media played an important role in amplifying parental fear. News coverage often prioritised emotional headlines and personal anecdotes over scientific evidence. Although evidence supporting vaccine safety was reported during this time, it accounted for only 37% of media stories during the controversy (2). Parents who were unsure about vaccinating their children were strongly influenced by mass media coverage (8). In one Welsh study, parents who chose not to vaccinate their children were 4.5 times more likely to rely on newspapers for information about the MMR vaccine (9). Twelve years later, Wakefield’s paper was finally retracted (10). By then, however, the damage had already been done. Despite overwhelming evidence disproving the claims, many people continued to believe them. Psychologists describe this as the ‘continued influence effect’, where misinformation can continue shaping attitudes and behaviour even after it has been debunked (11). Misinformation is not only persuasive — in some cases, it can also be deadly. It would be comforting to believe that society has become better at recognising misinformation. Unfortunately, the problem remains deeply entrenched. In some cases, misinformation does not originate from fraudulent researchers, but from governments themselves. This is perhaps even more insidious, because institutional authority can give misinformation an appearance of legitimacy that is extraordinarily difficult to undo. A striking example emerged in Japan in 2013, following the introduction of a national HPV vaccination program for teenage girls. The vaccine was supported by strong scientific evidence demonstrating its effectiveness in preventing cervical cancer (12). Yet only two months after launching the program, the Japanese government suspended its active recommendation of the vaccine due to growing public concern about safety (13). These concerns were largely driven by media reports of alleged side effects following vaccination. Television programs and newspaper stories featured emotional stories from young women reporting chronic pain and neurological symptoms, triggering widespread panic across the country (14). Crucially, many media outlets failed to emphasise that no scientific evidence had established a causal link between the vaccine and these symptoms. Although the government described the suspension as temporary while investigations continued, political caution and public pressure transformed it into a prolonged policy pause. Vaccination rates plummeted from 70% to barely 1% within a single year (15). The suspension ultimately lasted more than eight years, creating what researchers have described as a ‘lost generation’ of women who missed the opportunity to be protected against HPV (14). While the program has since been reinstated, public trust has not fully recovered. As of 2025, vaccination rates remain around 30% — a far reach from the World Health Organisation target of 90% (16). The long-term consequences may not become apparent for decades, as cervical cancer rates rise in under-vaccinated populations. This case highlights the powerful role of the media in shaping public perceptions of risk, and in turn, influencing policy decisions with enduring public health consequences. Addressing misinformation is not solely the responsibility of scientists or governments. Journalists and media organisations also play a critical role in shaping public understanding. The persistence of misinformation highlights an important reality: scientific evidence alone is not enough. Even the most robust research can be undermined if it is not communicated in a way that is accessible, transparent and trustworthy. This is where science communication becomes essential — helping to bridge the gap between evidence and public understanding so that scientific knowledge can inform real-world decisions. In the space between fact and fiction, communication determines which voice is heard. In an age where information moves faster than ever, the ability to communicate science clearly, honestly, and effectively may be just as important as the science itself. References 1. Flaherty DK. The Vaccine-Autism Connection: A Public Health Crisis Caused by Unethical Medical Practices and Fraudulent Science. Annals of Pharmacotherapy . 2011;45 (10):1302-1304. doi: 10.1345/aph.1Q318 2. Lewis J, Speers, T. Misleading media reporting? The MMR story. Nature Reviews Immunology . 2003; 3 (11):913-918. doi:10.1038/nri1228 3. Howell EL, Wirz CD, Scheufele DA, Brossard D, Xenos MA. Deference and decision-making in science and society: How deference to scientific authority goes beyond confidence in science and scientists to become authoritarianism. Public Understanding of Science . 2020; 29 (8):800-818. doi:10.1177/0963662520962741 4. Pearce A, Law C, Elliman D, Cole TJ, Bedford H. Factors associated with uptake of measles, mumps, and rubella vaccine (MMR) and use of single antigen vaccines in a contemporary UK cohort: prospective cohort study. BMJ . 2008; 336 (7647):754-757. doi:10.1136/bmj.39489.590671.25 5. Peltola H, Patja A, Leinikki P, Valle M, Davidkin I, Paunio M. No evidence for measles, mumps, and rubella vaccine-associated inflammatory bowel disease or autism in a 14-year prospective study. The Lancet . 1998; 351 (9112):1327-1328. 6. Madsen KM, Hviid A, Vestergaard M, et al. A population-based study of measles, mumps, and rubella vaccination and autism. New England Journal of Medicine . 2002; 347 (19):1477-1482. doi:10.1056/NEJMoa021134 7. Taylor B, Miller E, Farrington C, et al. Autism and measles, mumps, and rubella vaccine: no epidemiological evidence for a causal association. The Lancet . 1999; 353 (9169):2026-2029. doi:10.1016/S0140-6736(99)01239-8 8. Evans M, Stoddart H, Condon L, Freeman E, Grizzell M, Mullen R. Parents' perspectives on the MMR immunisation: a focus group study. Br J Gen Pract . 2001; 51 (472):904-910. https://pmc.ncbi.nlm.nih.gov/articles/PMC1314147/ 9. Walsh S, Thomas DR, Mason BW, Evans MR. The impact of the media on the decision of parents in South Wales to accept measles-mumps-rubella (MMR) immunization. Epidemiol Infect . 2015; 43 (3):550-560. doi:10.1017/s0950268814000752 10. Rao TS, Andrade C. The MMR vaccine and autism: Sensation, refutation, retraction, and fraud. Indian J Psychiatry . 2011; 53 (2):95-96. doi:0.4103/0019-5545.82529 11. Johnson HM, Seifert CM. Sources of the continued influence effect: When misinformation in memory affects later inferences. Journal of Experimental Psychology: Learning, Memory, and Cognition . 1994; 20 (6):1420. doi:10.1037/0278-7393.20.6.1420 12. Paavonen L, Naud P, Salmerón J, et al. Efficacy of human papillomavirus (HPV)-16/18 AS04-adjuvanted vaccine against cervical infection and precancer caused by oncogenic HPV types (PATRICIA): final analysis of a double-blind, randomised study in young women. The Lancet . 2009; 374 (9686):301-314. doi:10.1016/S0140-6736(09)61248-4 13. Iked S, Ueda Y, Yagi A, et al. HPV vaccination in Japan: what is happening in Japan? Expert Review of Vaccines . 2019; 18 (4):323-325. doi:10.1080/14760584.2019.1584040 14. Takahashi T, Ichimiya M, Tomono M, et al. Overcoming HPV Vaccine Hesitancy in Japan: A Narrative Review of Safety Evidence, Risk Communication, and Policy Approaches. Vaccines . 2015; 13 (6):590. https://www.mdpi.com/2076-393X/13/6/590 15. Yagi A, Ueda Y, Oka E, Nakagawa S, Kimura T. Human papillomavirus vaccination by birth fiscal year in Japan. JAMA network open . 2024; 7 (7):e2422513. https://doi.org/10.1001/jamanetworkopen.2024.22513 16. Sazawa M, Ishiguro C, Mimura W, Maeda M, Murata F, Fukuda H. Impact of the resumption of proactive recommendation of HPV vaccination on HPV vaccination rates in Japan: an interrupted time series analysis based on the VENUS study. BMJ Public Health . 2025; 3 (2):e000982. doi:10.1136/bmjph-2024-000982 Previous article back to Fact & Fiction Next article

< Back to Issue 10 Shining Light on the Grey by Ingrid Sefton, Kara Miwa-Dale and Anabelle Dewi Saraswati 2 June 2026 Illustrated by Anabelle Dewi Saraswati Edited by the Editor-in-Chiefs Truth: from that with a little t, to the just out of reach capital T “Truth”. We seek it, we declare it, we believe in it. An innate drive towards answers, embedded in the human process of scientific exploration. Our notions of fact and fiction often feel like black and white binaries with clear boundaries; easily distinguishable, one or the other. Consider an alternative. That science, as in life, is a chiaroscuro of fact and fiction. Shades of light and shadow, which contrast truths and contradictions in order to point us to a clearer, but never fully transparent view of reality. Our scientific methods help us whittle away outright lies, and approach a closer approximation to that of fact than one of fiction. Yet, undeniably, there remains frustratingly little we can say with utmost certainty. History is littered with reminders of how fragile “truth” can be. There was a time when illness was understood as a delicate imbalance of blood, phlegm, black bile and yellow bile. At one point, continents were assumed to be fixed and unmoving, until tectonic plates revealed a restless Earth in constant motion. It is precisely by interrogating these once-settled “facts” that science advanced — not in straight lines, but through disruption, revision, and occasional collapse. And still, there are questions we orbit but have not yet landed on. What exactly is dark matter, which seems to hold galaxies together while refusing to reveal itself? How does consciousness emerge from the quiet electrical choreography of neurons? In these spaces, science is not a catalogue of answers, but a map of known unknowns. A lack of absolutes does not negate the power of science – far from it. Indeed, this is a large part of what drives us to become ever more inquisitive, innovative and critically questioning of the scientific landscape. Ideas once accepted as unquestionable truths can be later overturned through science, just as concepts once dismissed as fantasy may eventually become reality. May this issue urge you to pause, to consider the myriad of grey space that exists in between as you traverse the boundaries of truth, certainty and fabrication. Where does one end, and another begin? A word from the Cover Illustrator Anabelle For this issue’s cover illustration, I was inspired by the history and strange patterns of crop circles. These vast, intricate formations pressed into fields that sit somewhere between scientific curiosity, mass hysteria, art, and folklore; the perfect visual encapsulation for this issue’s theme, Fact and Fiction. Cropping up throughout the late 70s to 80s, they became a cultural phenomenon tied to UFO sightings, conspiracy theories, extraterrestrial speculation, and pseudoscientific fascination. Conceptually, crop circles simultaneously exist as a hoax, artwork, scientific anomaly, and collective myth, depending on the observer. I approached the illustration through a lens of nostalgia, imagining it as the cover of a forgotten children’s mystery book you could stumble upon in an op-shop dating all the way back to the 80s or 90s; sun-faded, slightly eerie, but playful in its wonder. The Midwest-inspired rural scene allowed me to lean into that atmosphere of a quiet blue hour mystery that surrounded alien encounters and paranormal media in the late twentieth century, when crop circles occupied such a strange and persistent place in the pop culture zeitgeist. The beauty in crop formations lies in their underlying precision. Many are built off fractal geometry and repeating mathematical systems, and naturally occurring patterns found throughout science and nature. Even as objects associated with fiction and conspiracy, they are deeply rooted in structure, mathematics, and design. Crop circles are carefully designed spectacles intended to provoke interpretation. Whether read as evidence, artwork, prank, or myth, they reveal how deeply humans want to believe in stories larger than themselves. The cover became less about proving whether something is real or fabricated, and more about exploring the fragile, fascinating space in between. Previous article back to Fact & Fiction Next article

< Back to Issue 10 The Human Body: A Portrait Painted by a Thousand Minds by Isaac Tian 2 June 2026 Illustrated by Chris Cao Edited by Adrija Dutta The only nourishment humans hunger for more than food is truth. For millennia, we have been propelled by this inarticulable appetite for discovery, yet our understanding of the human body has remained limited–and at times, conflicting. Our fascination with ourselves began long before the modern day. Prior to the interconnectedness of the contemporary global platform, research into the human body was undertaken independently in various cultures. As a result of geographical separation, cultures have arrived at different interpretations of our bodies, diseases, and treatments (1). The Chinese developed Traditional Chinese Medicine; from the Indian subcontinent arose Ayurveda; the Greek laid the basis for Unani. More recently, the Europeans gave us naturopathy, homeopathy, and of course–Western medicine. The modern Australian medical system is predominantly founded on conventional Western medicine. Nevertheless, traces of foreign medical practices have embedded themselves into the system (2). In a world now riddled with cultural intersections, the frontiers of knowledge and established practices collide, leaving us – as patients – with a critical question: who is right, and who is wrong? More interestingly, could both sides of the argument be right? The vast backdrop of conventional Western medicine has certainly served us well. Western scientists have – for the most part – established a reliable theoretical basis upon which our understanding of bodily functions, diseases and treatments are founded (3). Through various experiments, they have visualised the microscopic and characterised the medically novel, revealing previously undiscovered cellular and molecular mechanisms, ultimately birthing the biomedical foundations of Western medicine (3). Discoveries such as William Harvey’s elaboration of the circulatory system in 1628, Edward Jenner’s founding principles of vaccination in the 1700s, and Louis Pasteur’s discovery of microbial origins in the 1800s are episodes in a lengthy collection that forms the foundation for Western medicine (3). Whilst there are still gaps in the Western understanding of bodies, studies such as these largely suggest that the foundations for Western medicine are tangibly sound - rendering them reliable to an extent. The strength of Western medicine lies in the tangibility of the proposed cellular mechanisms. Alternative approaches such as Traditional Chinese Medicine and Ayurveda places greater emphasis on spirituality in body systems, undertaking the belief that intangible forces are at play to influence the human condition (3). Due to their immaterial nature, scientific inquiry is largely unable to support or refute these spiritual ideas. Although, interestingly – treatments based on these foundations aren’t completely unfounded. For example, the concept of Qi (pronounced chee ) is central to Traditional Chinese Medicine. Qi is thought to be a fundamental life force that circulates around the body, and it is believed that acupuncture can stimulate this circulation to relieve pain (1, 4). Sounds insane right? How can we manipulate an immaterial force to alleviate physical symptoms? It turns out that it may not be the immaterial Qi the acupuncture needle targets – but rather the fascia of musculoskeletal systems that cause the nerve stimulation experienced in acupuncture (5). Remarkably, acupuncture has been shown to reduce multiple types of pain in patients (4). The fascination here lies neither in the tangibility of Western mechanisms nor the grandeur of Chinese spirituality alone, but in how the two systems converge. The treatment stems from ancient China, but its mechanisms are more clearly elucidated by Western medicine. This harmonious combination of varying cultural understanding is fascinating. Better yet, it achieves the ultimate goal of treatments – to deliver a beneficial outcome to the patient. The interplay of medical systems extends beyond just China and the West. For instance, yoga – widely prevalent in Ayurveda – is traditionally grounded in the Ayurvedic ideas of the three energies (called doshas) and the five elements in the human body, a foundation that may seem outdated. However, the practice of Yoga remains highly effective and complements many Western medical treatments (1). Additionally, it has been shown to improve outcomes of chronic conditions and pain (6). These positive outcomes for patients bode well with the Western understanding of pain sensation pathways (7). The human body seems endlessly complex and rightly so. Medicine has been and will likely always be a developing field of intersecting understanding. By virtue of their persistence throughout centuries and even millennia, the medical systems from various cultures merit exploration and investigation. Whilst it is imprudent to single out a medical system as the best, it is prudent to cherish how differing approaches can complement each other to deliver benefits to patients. Validity and truth should not be overly emphasised when the goal of medicine is to do the greatest good for the greatest number of people. Through cooperation and unity, each system contributes to a more complete understanding of health. References Baars EW, Hamre HJ. Whole Medical Systems versus the System of Conventional Biomedicine: A Critical, Narrative Review of Similarities, Differences, and Factors That Promote the Integration Process. Evid Based Complement Alternat Med. 2017;2017:4904930. doi: 10.1155/2017/4904930 PubMed PMID: 28785290; PubMed Central PMCID: PMC5530407. Australian Health Practitioner Regulation Agency. AHPRA Annual Report 2023-24 [Internet]. Australian Health Practitioner Regulation Agency; [cited 2026 May 10]. Available from: https://www.ahpra.gov.au/Publications/Annual-reports/Annual-report-2024/Highlights.aspx Silvano G. A brief history of Western medicine. Journal of Traditional Chinese Medical Sciences. 2021 Nov 1;8:S10–6. doi: 10.1016/j.jtcms.2020.06.002 Vickers AJ, Linde K. Acupuncture for chronic pain. JAMA. 2014 Mar 5;311(9):955–6. doi: 10.1001/jama.2013.285478 PubMed PMID: 24595780; PubMed Central PMCID: PMC4036643. Finando S, Finando D. Qi, acupuncture, and the fascia: a reconsideration of the fundamental principles of acupuncture. J Altern Complement Med. 2012 Sep;18(9):880–6. doi: 10.1089/acm.2011.0599 PubMed PMID: 22874011. Holtzman S, Beggs RT. Yoga for chronic low back pain: A meta-analysis of randomized controlled trials. Pain Res Manag. 2013;18(5):267–72. doi: 10.1155/2013/105919 PubMed PMID: 23894731; PubMed Central PMCID: PMC3805350. Gupta S, Gautam S, Kumar U, Arora T, Dada R. Potential Role of Yoga Intervention in the Management of Chronic Non-malignant Pain. Evid Based Complement Alternat Med. 2022 May 28;2022:5448671. doi: 10.1155/2022/5448671 PubMed PMID: 35668780; PubMed Central PMCID: PMC9167073. Previous article back to Fact & Fiction Next article

< Back to Issue 10 Contingent Realities - the (Ph)ailure of a (Ph)act by Edmond Sim 2 June 2026 Illustrated by Eric Wang Edited by Rita Fortune "What is true for you is true for you, and what is true for me is true for me" – Protagoras sneered (1). “I cannot but agree” – Plato replied, terse and tight-lipped. They were bitter ideological enemies. Whilst Protagoras sold a world built entirely on human perception, Plato demanded absolute, unchanging facts: forms and realities that existed independently of human viewing (2). For millennia, the discipline of physics sided vehemently with him. The entire enterprise of the physical sciences was a crusade to banish the ‘will’ of anthropomorphic gods and heroes, to uncover the definitive and rational "facts" behind the universe. The pursuit of logos, rather than mythos. Eight years following Plato’s death, a student of his, Zeno of Citium, established the Stoic school, spreading the belief that the universe operated due to reason (logos), was monistic (i.e. one interconnected physical system governed by consistent laws), and operated on cause and effect (3). This belief in determinism (the idea that events in the future had been determined by a chain of past occurrences) reached its zenith in the Scientific Revolution of the 17/18th centuries. Fact: repeatable, reversible and reliable We will start with an easy question: what is a fact? I would argue that a statement is a fact if it: (i) stems from a pre-existing state of affairs in the world; and (ii) is singular, i.e. is restricted to reality, of which there is one. This is described in perhaps the most incomprehensible quotation of mankind by Aristotle (4). “To say that that which is, is not, and that which is not, is, is a falsehood; therefore, to say that which is, is, and that which is not, is not, is true” (4). ‘Pre-existing’ requires a past. For something to already be there, waiting for us to see it, it can't have just spawned from the void. Every 'is' requires a 'why'. This relentless search for the chain of cause and effect reached its extreme in the 18th century with the French polymath, Pierre-Simon Laplace. His proposal of a hypothetical entity, now famously known as Laplace’s Demon, served as the ultimate thought experiment for the deterministic worldview that dominated the Scientific Revolution. Imagine a massive, omnipresent intellect – a demon. If this intelligence knew the exact location and force of each single atom in the universe right now, it would know everything. Uncertainty would vanish. The past and the future would be simultaneously now (5). A rock does not "choose" to roll; rather it rolls because gravity acts upon its mass. Similarly, in a deterministic universe, you do not "choose" to act. Your current physical state was caused by the state of the universe one second ago. That state was caused by the state one year ago, which was caused by the state of the universe before you were born, stretching all the way back to the initial conditions of the Big Bang. We conclude: there only exists one unique solution that maps space to time. Two different pasts never merge into the exact same future. Two identical presents never split into different futures. ‘c’ is a constant (crisis): Classical mechanics, in all its beautiful and symmetrical mathematics, provides us this shocking revelation that reality may be deterministic, and that free will is an illusion, a fiction within the slow march of time (7). Occam’s razor (that is, that the simplest explanation is usually the correct one) is seemingly disproven through two fundamental flaws within the classical framework. Firstly, the speed of light (denoted as c) is unique because it stays the same regardless of how fast you are moving. James Clerk Maxwell discovered that electric and magnetic fields are perfectly synced; a ripple in an electric field creates a magnetic one, and that magnetic ripple in turn regenerates the electric field. This continuous loop creates an electromagnetic wave, which we see as light. The speed of this wave is determined by two fundamental properties of empty space: how easily it allows electric and magnetic fields to form and spread. As these properties of the vacuum itself never change, light always travels at the exact same speed, whether you are racing toward the light source or standing perfectly still. The immediate consequences of forcing light to travel at a constant value are rather disturbing. Consider the unfortunate events of a German salary worker in the early 20th century: It was another miserable, grey day in Germany. Albert was staring out the window of a Deutsche Bahn train that was currently four hours late, thinking that his day couldn’t get any worse. CRACK. Lightning strikes the metal frame of the train car, right at the front. Albert jumps, spilling his lukewarm coffee. But before he can even dry off his trousers, a second lightning bolt strikes the very back of the train. He spills his coffee over his shirt. Albert has to get off the train at the next stop, Bern, to get to his job working at the Swiss Patent office. As he dries off his clothes on the platform, he observes an express train that runs straight through the station. Lightning, particularly vicious today, strikes both the front and end of the train carriage at the exact same time. When he was sitting inside the moving carriage, the light from the front strike had reached his eyes first because he was moving toward it. Remember, the speed of light remains constant even in his moving carriage. But now, standing completely still on the damp Bern platform, the light from both strikes on this new express train reached him exactly simultaneously (9). The man on the platform and the passengers on the train would fundamentally argue on the chronological order of events in the universe. Yet the frightening fact was neither of them was wrong (10). (This assumes that the Deutsche-Bahn moves at speeds close to the speed of light, however due to strikes from the train worker union, it would be a challenge for the train to move at a non-zero speed at all.) Recall our first condition for the definition of fact – the existence of a pre-existing past. Yet, if two observers cannot even agree on "when” an event took place, this condition fails. Fact, it seems, depends entirely on how fast you go. Bohr-ing reality is fundamentally uncertain. The second deviation from naive Laplace was the discovery of the hollow atom. Rutherford used the analogy of planets (the electrons) orbiting a star (the nucleus) seemingly never straying from their tidy, well-defined and circular orbits. Electromagnetism prevented this model from being taken seriously. Any particle that possesses charge must release energy when accelerated. Now, imagine a satellite that constantly releases energy each orbit around Earth. Naturally, the satellite will fall into the Earth. The same would occur to the electron. It would spiral into the nucleus in less than a fraction of a picosecond. Every atom in the universe would instantly implode. Two independent theories then arose almost simultaneously following this discovery. In 1925-26, the landmark papers of Heisenberg’s matrix mechanics (which uses matrices to calculate important quantum properties) and Schrödinger’s wave mechanics (an equation that relates a quantum state to its energy) attempted to provide reasons as to why energy did not disappear from the electron’s orbit (11). Breaking with the tradition of presenting the quantum ‘ghost’ of randomness, quantum mechanics actually provides a more deterministic theory than one may realise. Akin to Laplace’s demon, Schrödinger’s equation describes the time evolution of a quantum system: given an initial quantum state, we can make a definite and certain prediction of what that quantum state will be at any later time (12). This is a very intangible concept and would likely be poorly understood, so let me demonstrate this by way of an example of a coin toss. Imagine a coin spinning rapidly on a table. If you try and guess whether it’s showing heads or tails at that specific microsecond, you probably can’t. It’d be too blurry. However, the blur itself is not random. The way the coin spins, its momentum, its wobble, the friction against the table is governed by strict, unbreakable rules. If you know exactly how the coin was flicked (the initial quantum state), Schrödinger’s formula can predict with 100% certainty exactly what that "blur" will look like five seconds from now, ten days from now, or one hundred years from now. The deterministic nature of quantum mechanics is that the blur itself evolves predictably. The infamous and rather misrepresented "quantum randomness" only applies at the very end, when you finally get fed up and slap your hand down on the coin, forcing it to be either heads or tails (the measurement) (13). The issue, therefore, with this notion of fact under a quantum lens is the lack of a singular outcome. Time evolution is a well-defined function, yet outcome can only be predicted probabilistically. Therefore, we fail yet again the second condition of fact. Fact is – the friends we made along the way? An ongoing unresolved issue in quantum theory is how to explain the two conflicting ways in which systems evolve. Unobserved states evolve smoothly, yet exhibit discontinuous jumps into an outcome when measured. The infamous “Wigner’s Friend” paradox provides an example (14). Suppose your friend is inside a sealed lab watching a spinning coin. In their perspective, when they stop the coin and read its face, its state collapses into a singular outcome. In the shivering cold, you curse that you had to be the one to stand outside. According to the rules of quantum mechanics, because you haven’t seen the coin face, the smooth, unbroken evolution is still happening. You get sick of suffering in the name of science, so you rush into the laboratory and ask your friend what the coin landed on. At that moment, the superposition abruptly collapses for you. Facts no longer appear grounded in an objective, observer-independent past. Instead, they become relational, contingent upon who is observing the system. Worse still, facts seem capable of multiplying: different observers may legitimately describe different realities. This forms the basis for Rovelli’s Relational Quantum Mechanics (15). In RQM, an object (like an electron, a coin, or a cat) does not inherently "possess" properties like position or momentum in isolation. Instead, those properties only exist when two physical systems interact. Asking "Where is the particle right now?" when nothing is looking at it is a grammatically incorrect question, equivalent to asking “What is the sound of one hand clapping?" The property of "position" only truly comes into meaning if there exists a detector for which the electron interacts with (16). Any interaction is essentially an exchange of information between two systems. Rovelli formalises this by proposing two foundational postulates. First, there is a finite limit to the relevant information one system can extract from another. Second, it is always possible to extract new information (17). At first glance, these seem at odds: how can you continually extract new data if the total capacity is capped? The consequence of this tension is what we traditionally call "collapse", but RQM reframes it simply as an update of relative information. If you have maxed out the information capacity of a system — for instance, by pinning down the spinning coin’s exact momentum — then asking a new question about its position forces the system to "forget" old information to make room for the new. This directly yields Heisenberg’s uncertainty principle. If we wish to keep using the word "fact" in our theory of modern physics, we must redefine it. Facts are no longer global, pre-existing truths built into a singular reality. Instead, they are by nature local, inherently plural, and entirely dependent on the relationship between the watcher and the watched. Protagoras peers down, then looks up at Plato with a bright-eyed grin. "As I was saying,” References Plato. Theaetetus. Waterfield R, translator. London: Penguin Classics; 1987. Plato. The Republic. Lee D, translator. 2nd ed. London: Penguin Books; 2003. Sellars J. Stoicism. Berkeley: University of California Press; 2006. Aristotle. Metaphysics. Ross WD, translator. Oxford: Clarendon Press; 1924. Laplace PS. A Philosophical Essay on Probabilities. Truscott FW, Emory FL, translators. New York: John Wiley & Sons; 1902. University of Oxford. The Eddington Number. Oxford: University of Oxford. 2020. https://www.maths.ox.ac.uk/about-us/life-oxford-mathematics/oxford-mathematics-alphabet/e-eddington-number Mastin L. Determinism. The Basics of Philosophy. 2008. https://www.philosophybasics.com/branch_determinism.html Einstein A. Relativity: The Special and the General Theory. Lawson RW, translator. New York: Henry Holt and Company; 1920. Norton JD. The Relativity of Simultaneity. Pittsburgh: University of Pittsburgh. 2022. https://www.pitt.edu/~jdnorton/teaching/HPS_0410/chapters/Special_relativity_rel_sim/ Norton JD. Einstein for Everyone. Pittsburgh: University of Pittsburgh. 2022. https://www.pitt.edu/~jdnorton/teaching/HPS_0410/chapters/Special_relativity_clocks_rods/ Heisenberg W. Über quantentheoretische Umdeutung kinematischer und mechanischer Beziehungen. Z Phys. 1925;33(1):879-93. Nave R. Schrödinger Equation [Internet]. Atlanta: Georgia State University. 2017. http://hyperphysics.phy-astr.gsu.edu/hbase/quantum/schr.html Ismael J. Quantum Mechanics. Stanford: Stanford Encyclopedia of Philosophy. 2021. https://plato.stanford.edu/entries/qm/ Wigner EP. Remarks on the mind-body question. In: Good IJ, editor. The Scientist Speculates. London: Heinemann; 1961. p. 284-302. Rovelli C. Relational quantum mechanics. Int J Theor Phys. 1996;35(8):1637-78. Laudisa F, Rovelli C. Relational Quantum Mechanics. Stanford: Stanford Encyclopedia of Philosophy. 2021. https://plato.stanford.edu/entries/qm-relational/ Rovelli C. Helgoland. Segre E, Carnell S, translators. New York: Riverhead Books; 2021. Previous article back to Fact & Fiction Next article

< Back to Issue 10 Dating Isn’t Physics – Opposites Don’t Attract by Elva Assisan 2 June 2026 Illustrated by Jessica Walton Edited by Cady Jacobson The opposites attract trope has a history of being very popular in our media, appearing quite literally everywhere from Pride and Prejudice by Jane Austen to 10 Things I Hate About You by Gil Junger. Its popularity is undoubtedly a result of the conflict and passion that this dynamic brings to a narrative. Popular culture portrays high contrast couples as those with more exciting, balanced and emotionally fulfilling lives. However, while it often looks like “you bring me out of my shell” when an introvert and extrovert meet in the beginning, it often ends in arguments about going out and staying in. Despite how popular the trope is, science suggests that opposites, in fact, do not attract. The ‘Similarity Attraction Affect’ theory proposes that individuals feel more attracted to those who are similar in attitudes (1). When people encounter those with similar attitudes, they feel affective attractions. They find that their interactions are smoother and therefore more enjoyable. Even in daily life, individuals find that they have more satisfying interactions with those that they have similarities with. When another person shares similar opinions or behaviours, it creates feelings of acceptance and emotional security. This validation strengthens self-esteem and encourages emotional closeness (1), as successful long-term relationships are usually built on compatibility and mutual understanding, rather than dramatic contrast. In addition to similarity increasing feelings of acceptance due to shared values, similarity has also been found to make communication easier. Couples who share values and lifestyles generally experience fewer misunderstandings and conflicts, as they approach situations in much the same way. If two people agree on major life decisions, such as family expectations, finances, and future goals, decision making becomes less stressful (2). On the other hand, relationships with more extreme differences become more exhausting over time as more major issues have to be resolved. Montoya, Horton and Kirchner conducted a meta-analysis examining attraction and found that both actual and perceived similarity significantly increased interpersonal attraction (3). Essentially, people are more likely to enjoy spending time with those who remind them of themselves by having shared humour, hobbies, and values. Building on this, it is not just about having similarities with another person, but having a dynamic where you are invited to act on your core traits and behaviours. For example, dominant people prefer to interact with partners who invite them to be dominant, and submissive people prefer to interact with partners who invite them to be submissive. When people have different qualities which work in conversation, that same mutual understanding is found. Another example of this is having an organised partner who remembers appointments, while the spontaneous partner ensures life contains fun, instead of colour-coded spreadsheets. Individuals are also naturally drawn to environments and relationships that reinforce their self-concept and worldview (4). Indeed, the idea that opposites attract may actually originate from this notion of complementarity. Importantly, the claim that similarity matters does not mean couples have to be the exact same. Healthy relationships still require individuality, compromise, and respect for differences. Minor differences can improve relationships by encouraging personal development and preventing boredom (2). While the idea that “opposites attract” sounds romantic and makes great material for movies, psychological research suggests that similarity is usually what keeps relationships alive, particularly once the excitement wears off. Ultimately, successful relationships are less about finding your complete opposite and more about finding someone whose weirdness matches your own closely enough that neither of you end up arguing about how to load the dishwasher every night. References Byrne D. An Overview (and Underview) of Research and Theory within the Attraction Paradigm. Journal of Social and Personal Relationships . 1997; 14 (3):417–431. doi:10.1177/0265407597143008 Luo S, Klohnen EC. Assortative Mating and Marital Quality in Newlyweds: A Couple-Centered Approach. Journal of Personality and Social Psychology . 2005; 88 (2):304–326. doi:10.1037/0022-3514.88.2.304 Montoya RM, Horton RS, Kirchner J. Is actual similarity necessary for attraction? A meta-analysis of actual and perceived similarity. Journal of Social and Personal Relationships . 2008; 25 (6):889–922. doi:10.1177/0265407508096700 Dryer DC, Horowitz LM. When do opposites attract? Interpersonal complementarity versus similarity. Journal of Personality and Social Psychology . 1997; 72 (3):592–603. doi:10.1037/0022-3514.72.3.592 Previous article back to Fact & Fiction Next article

< Back to Issue 10 Reimagining Time: From Relativity to Wormholes by Zahra Halela 2 June 2026 Illustrated by Saraf Ishmam Edited by Thanishka Rajmohan Time is a social construct. It interweaves itself into the very fabric of humanity as a rigid structure that does not allow for tardiness. It creates and constrains, and at its essence, it controls. When viewed through a scientific lens, time is a fundamental physical dimension. It exists independently, within a fourth dimension invisible to the eye. It is not universal either – it passes at different rates according to speed and gravity. Is it truly too far-fetched to stretch and warp the limits of time itself, to imagine time that exists beyond the present, and into the past or future? One such consideration comes from the mathematical equation that describes how things change over time. Here, time is a quantity, often referred to as coordinate time. Coordinates are often thought to have direct and measurable quantities, as in, for every input of x there is an output of y . Special relativity, however, reaches beyond the limitations that direct coordinates constrain us to, and instead posits that these measurements’ results are dependent on the motion of an observer. Essentially, they conclude that absolute space and time are, in fact, products of fiction (1). Special relativity, then, can be harnessed in the understanding of time travel into the future. Another possibility is one presented by a well-known film, Christopher Nolan’s Interstellar . In Interstellar , a different type of relativity is explored, namely general relativity, which contemplates the confounding query of how time travel into the past can be feasible. General relativity is a theory proposed by Einstein which interweaves time, gravity and space (2). While special relativity does acknowledge the connectedness of space and time, general relativity is able to tie in the fundamental ‘force’ of gravity as something that is not a force, but in fact a warping of spacetime. Essentially, general relativity propounds that massive objects are able to distort the relationship between space and time, which is a key concept in the film (3). Nevertheless, general relativity has its limitations, in that it fails to incorporate quantum physics and Mach’s principles (4). Thus, if general relativity still requires further modifications to be irrefutable and robust, then other possibilities must be considered for time travel to come to fruition in the future. One potential mechanism is the existence of wormholes. Wormholes are tunnels within spacetime that connect parts of the universe through a certain type of warping, its theoretical background aligning heavily with general relativity (5). This then begs the question – can wormholes provide a satisfactory solution for time travel? The answer is slightly more complicated than merely a yes or a no. If one were to consider travel between two distances, a wormhole seems to be the perfect answer, theoretically. Not only do they facilitate time travel between galaxies, but also allow for interterrestrial communication within parallel universes (6). On a more practical note, however, wormholes still have a marginally long way to go before a substantial discovery is made to turn a complex theory into fact. References Bertschinger E. Coordinates and proper time. Accessed April 6, 2026. https://ocw.mit.edu/courses/8-224-exploring-black-holes-general-relativity-astrophysics-spring-2003/3982882af388dae3407906357a419cba_coordsproptime.pdf Buzzo D. Time Travel: Time Dilation. Electronic Visualisation and the Arts. 2014 . doi: 10.14236/EWIC/EVA2014.21 . Dutfield S, Bartels M, Tillman NT. What is the theory of general relativity? Understanding Einstein’s space-time revolution | Space. Accessed May 13, 2026. https://www.space.com/17661-theory-general-relativity.html Palomo MU. Einstein’s theoretical failures of General Relativity. Independent physics. December 2, 2023. Accessed May 13, 2026. https://independentphysics.com/einsteins-failures-of-general-relativity-gravitational-potential-energy-and-machs-principle/ Aichelburg PC. Wormholes and time travel. In: Vol 504. AIP. 2000;504(1):1111-1112. doi: 10.1063/1.1290914 . Morris MS, Thorne KS, Yurtsever U. Wormholes, time machines, and the weak energy condition. Phys Rev Lett . 1988;61(13):1446-1449. doi: 10.1103/PhysRevLett.61.1446 . Previous article back to Fact & Fiction Next article

< Back to Issue 10 That Protein is AI, Dude by KJ Srivastava 2 June 2026 Illustrated by Ciara Dahl Edited by Aimee Fogarty-Bennett For decades, scientists used a glowing jellyfish protein called Green Fluorescent Protein (GFP) to light up living cells. This protein emits a bright green light when exposed to UV light, and is used to visibly ‘tag’ cells for all sorts of experiments. Then, researchers used AI to generate a protein that serves the same function. And… it worked? The resulting protein, esmGFP, is so different from known natural fluorescent proteins that researchers compare the gap between them to roughly half a billion years of evolution. This protein is widely marketed as ‘AI simulating evolution’; but how much evolution is actually happening here, how does this work, and why is this being AI generated a big deal? Before this, evolution was the only protein designer we had. A jellyfish glows because evolution happened to stumble onto a protein called GFP that can absorb and emit light (1). Over millions of years, random mutations, that is, changes in DNA, slightly altered proteins. Natural selection, however, kept the versions that still worked. In the same sense, biology uses trial and error to build things, and nature keeps what works. This means every protein on earth is part of a gigantic, evolutionary family tree. Scientists can compare proteins by looking at sequence identity (2) – the percentage of amino acids that match between two proteins. Usually, closely related proteins have similar sequences and similar functions. The farther apart two proteins are evolutionarily, the more likely the chemistry fails and the protein stops functioning entirely. If you try to mutate or engineer a protein to match the function of a very different, distantly related protein, the chemistry is highly likely to fail. Because their sequences and structures have drifted too far apart, you can't easily swap parts or force them to interact without losing the necessary biochemical function! Why? Proteins are unbelievably sensitive to shape. They are made up of units called amino acids, and only work if they fold into an extremely precise and stable 3D structure. A few bad mutations can completely ruin the fold. Some examples of this in humans are cystic fibrosis, Alzheimer's, Sickle Cell Anaemia, and Huntington’s (3). The model researchers used to generate this protein is called ESM3 (4). It was trained on enormous databases of natural proteins, like a large language mode (LLM), but for biology. ChatGPT predicts plausible next words. ESM3 predicts plausible amino acids, structures and functions. Give it part of a protein sequence and it can iteratively fill in the gaps, adjusting the molecule until the chemistry and structure begin to make sense together. One of these generated proteins is esmGFP! Now this is when stuff starts getting really weird: esmGFP shares around 58% sequence identity with the closest natural fluorescent protein. In evolutionary terms, that is an enormous gap. For context, you share 60% of your DNA with a banana (5). No, I’m not lying to you. This is an astonishing number, and researchers estimate the difference could correspond to roughly half a billion years of evolution. After reading the frankly ridiculous 58% number, I immediately thought that's weird. It is, in fact, comical to assume that a machine that only has 58% of the parts of another would behave in the same way. It's the same in biology. Normally proteins that are this different are not expected to behave in the same way. Proteins are incredibly dependent on structure, and structure depends on sequence! Change too much and the entire fold usually destabilises – the protein misfolds, clumps together or just stops working. The fact that esmGFP can glow is even weirder. Forgive the ‘nerd talk’ that will take over the rest of the paragraph, but glowing for a protein is not an easy feat. GFP glows because part of the protein folds inward and creates a tiny chemical structure called a chromophore (6). Inside this pocket, three amino acids – serine, tyrosine, and glycine – react together to form a ring-like structure capable of absorbing and emitting light. In other words, the amino acids all need to be at the right angles, surrounding proteins need to stabilise the structure, the fold has to protect the chromatophore from the outside environment, and more. A model, without simulating any atoms like a physics engine, iteratively predicted something that works out. This is fascinating because the AI model appears to have internalised some of the deeper rules that connect protein sequence to behaviour – rules that even biologists still don’t fully understand. Moreover, scientists can explain how esmGFP functions chemically. They can map the fold. They can identify the chromophore. They can experimentally confirm that the protein fluoresces. But they can’t explain how artificial intelligence made it to this protein. Inside models like ESM3, there's still a major interpretability problem for scientists and biologists. The model learned from huge amounts of biological data and somehow developed an internal representation of what ‘working proteins’ look like; however, that representation is mostly hidden from us. The logic the model used to navigate this protein space and propose sequences that evolution may never have encountered at all is a black box (7). Maybe biology has a hidden schema where functional proteins follow deeper statistical or geometric rules. A schema which AI models can learn before we can clearly articulate it ourselves. Nature is an incredible engineer, but it's also deeply conservative. Evolution does not search for the best possible molecule, only whatever is good enough to survive right now. If a protein helps an organism reproduce, it stays. If not, it disappears. As a result, biology is full of accidents and compromises. Proteins can be inefficient, unstable, or bizarrely complex simply because evolution had no reason, or no viable path, to improve them further. AI hence creates a different approach to biological design. Instead of searching nature for useful molecules, researchers can generate proteins tailored to human needs: enzymes that break down plastic, proteins that capture carbon more efficiently, medicines aimed at specific targets, or even synthetic underwater adhesives inspired by mussels and barnacles (8) (find the link to this incredibly cool project here !). The deepest implication of this discovery is philosophical; life on earth is a sample size of one. This means everything we call “biology” comes from the same evolutionary tree, shaped by chance, constraint, and what was “good enough” to survive. esmGFP works, even with a sequence drifted far from known fluorescence proteins. Unsettlingly enough, maybe life isn’t defined by specific molecules at all, but by the rules that make those molecules work. Thank you for reading and I hope I could convince you that esmGFP matters beyond “AI made a glowing thing.” Check it out and play with esm yourself here ! References University of Queensland. How the jellyfish revolutionised brain science. 2020. https://qbi.uq.edu.au/brain/nature-discovery/how-jellyfish-revolutionised-brain-science RCSB Protein Data Bank. Data P. Sequence Similarity Search. 2017. https://www.rcsb.org/docs/search-and-browse/advanced-search/sequence-similarity-search Valastyan JS, Lindquist S. Mechanisms of protein-folding diseases at a glance. Disease Models & Mechanisms. 2014;7(1):9–14. doi: 10.1242/dmm.013474 EvolutionaryScale. Evolutionaryscale.ai . 2024. https://www.evolutionaryscale.ai/ Pfizer. How Genetically Related Are We to Bananas? Pfizer. 2022. https://www.pfizer.com/news/articles/how_genetically_related_are_we_to_bananas Craggs TD. Green fluorescent protein: structure, folding and chromophore maturation. Chemical Society Reviews. 2009;38(10):2865. doi: 10.1039/b903641p Kosinski M. What is black box artificial intelligence (AI)? IBM. 2024. https://www.ibm.com/think/topics/black-box-ai Liao H, Hu S, Yang H, Wang L, Tanaka S, Takigawa I, et al. Data-driven de novo design of super-adhesive hydrogels. Nature. 2025;644(8075):89–95. doi: 10.1039/b903641p Previous article back to Fact & Fiction Next article

< Back to Issue 10 Young Scientists in the Making by Kacy Toombs 2 June 2026 Illustrated by Saraf Ishmam Edited by Ingrid Sefton When you look at a baby, a multitude of thoughts might cross your mind, ranging from “aww cute” to “ ew, I’m never having kids” . You might see a baby babbling, screaming, drooling, or giving you that heedless, unwavering stare, and think about how silly that baby is. How socially inept! There’s not a thought behind those eyes! But what if I told you that every single baby is actually a young scientist? That everyday, babies are conducting social and scientific experiments; testing the limits of their understanding and noting down the mechanics of our world? Together, let’s explore how everyday babies are deploying the scientific method to learn about the world around them, and how they use these techniques to navigate life. If you’re at all familiar with this magazine, you’ll most likely know exactly what the scientific method entails. For those of you who haven’t touched a science kit since your Year 9 biology class, I’ll briefly explain. The scientific method (also known as the analytical method) is the use of a series of experiments to test a hypothesis. These experiments are often circular in their function, with the hypothesis modified and further retested until consistent results are achieved (1). It is standard practice within the many fields of science, and can range from wildly entertaining social experiments, to closely controlled quantitative observations. In the most basic terms, the scientific method is the art of asking a question, then seeking an answer. Picture a baby in a highchair. They’re happily wobbling their arms and swinging their plump little legs. Maybe they are even dribbling out the remnants of their mushy lunches. They pick up their spoon, and instead of using the spoon for its intended purpose, they drop it onto the floor. There are a number of things happening in this given scenario. A baby isn’t simply dropping the spoon to be annoying or to make itself laugh; though many babies have in the past, and will in the future, think that this act is very, very funny. The baby is asking a question – creating a hypothesis – and testing a number of variables. What happens when I let go of this spoon? When they drop the spoon, they are observing science in action. Gravity – the spoon falls down. Physics – the spoon spins in the air and bounces on the floor. The energy of sound waves – the clattering of the spoon on tile is loud, versus the soft boff of it bouncing on carpet. There are also the social aspects to consider. How will the people around them react? Will they come pick up the spoon? Is this a good way to get somebody’s attention? Like all great scientists, a baby will need to run multiple tests to come to conclusive results, so they will drop a lot of spoons. Now, am I advocating for us to let children throw their spoons around? Of course not. Part of this experience is for children to also learn that throwing spoons at the dinner table isn’t classified as decent behaviour in our society. But I do believe that it is important to acknowledge what a child is doing here. This action stems from curiosity, and it is important to cultivate that curiosity rather than quash it. Curiosity is a common trait we associate with ourselves as a species, and more often than not, is an intrinsic characteristic of children. Ironically enough, science has a hard time pinpointing the ‘why’ behind our curiosity (2), though many theories on the cognitive development of humans link our need to observe the environment and animal behaviour to survival (3). The power of curiosity is a baby’s best tool in their metaphorical toolkit. As a newly conscious being, there’s a lot about the world that they simply don’t understand. There’s a reason why the phrase, “ a baby’s brain is like a sponge” , is so well known. They absorb everything, and are constantly using any newly acquired knowledge to test the limits of their own understanding. The art of observing the world and the willingness to learn from it can be broken down into four main categories: questioning (the act of verbalising curiosity), physical exploration (bodily curiosity as a sensory experience), philosophising (the act of verbalising wonder) and embodied fascination (bodily wonder that does not seek a cognitive answer) (4). Of course, a baby won’t start verbalising their curiosity until they can speak (at which point you might be forced into the repetitive hell of a child’s never-ending echolalia of “ but why?” ), but instinctually the questions are present. These four categories are not mutually exclusive; often wonder can lead to curiosity and curiosity can lead to wonder. When people are given the room to explore their curiosity in any learning institution, they naturally grasp the concepts taught to them with a better understanding (5). Unfortunately, many modern day schools prioritise academic performance over a child’s own understanding of any given topic. I’m sure we can all relate to being talked at by a lecturer in the classroom rather than being invited to participate in the conversation. It’s a pretty fast way to get your brain to switch off and dull any curious inclination you might have had. It is no secret that some children learn differently from others, and this method of simply giving instruction in class can work for some. But using the broadest methods of engaging in wonder and curiosity will help all students, alongside their relationship with learning as a whole (6). Have you ever wondered why children enjoy field trips so much? It isn’t just the novelty of breaking a set routine and ‘skipping’ a school day; it’s also much simpler than that. Field trips give students a safe space to have fun with their learning and actively immerses them in all four categories of wonder and curiosity. Let’s take the example of students going to a planetarium. A child has the opportunity to physically explore a space; by interacting with planet mobiles or using their hands to feel textures on touchable exhibits, children are engaging in their bodily curiosity. Questions are naturally prompted by these physical explorations – “Is this Mars?”, “Which planet is Earth?” – which can lead to further discussions with their teachers and peers. Through these discussions, children can start philosophising certain ideas based on their newly acquired knowledge: “ These space rocks look like rocks on Earth. I wonder if they are made of the same thing?” . And in the quieter moments, children can idly sit with their own embodied fascination, taking in the atmosphere of the universe from inside the cool dome of the planetarium. There are no examinations or grading on field trips. A child has the freedom to simply be. This cultivation of curiosity at such a young age actively helps aid in the development of more complex and abstract thoughts (7) and leads to children in learning institutions taking more intellectual risks when approaching topics unknown to them. There’s a magic in being curious, in this need to fill in the blanks of their own knowledge. When children are comfortable in their own lack of understanding, they are not only more receptive to learning, but are shown to be more flexible in their beliefs when presented with new ideas (8). They engage more in classrooms, they speak up when they don’t understand, and they embrace the discomfort of not knowing. It all starts with the little, nappy-wearing scientist, sitting in their highchair. These babies are setting up their own cognitive learning systems from the moment they open their eyes. They let their curiosity guide their experimentation, which shapes how they come to understand the world. So what if they’re not making any groundbreaking revelations? They don’t need to be. Give in to your own curiosity next time you encounter a baby in the wild. See if you can observe the little scientist in action as they interact with the world for the first time. And hell, maybe let them drop a few spoons. References Gregersen E. Scientific method. Britannica. 24 April 2026. https://www.britannica.com/topic/empirical-evidence Kobayashi K, Ravaioli S, Baranès A, et al . Diverse motives for human curiosity. Nature Human Behaviour. 2019;3:587-595. doi: 10.1038/s41562-019-0589-3 Del Claro K. It All Began Out of Necessity and Curiosity. Behavioral Ecology . 2026;1-10. doi: 10.1007/978-3-032-13988-7_1 Heggen MP, Lynngård AM. Wonder and curiosity beyond the obvious—a dynamic model of bodily and verbal understandings of these phenomena. Humanities and Social Sciences Communications. 2026;13:167. doi: 10.1057/s41599-025-06467-3 Kidd C, Hayden B. The Psychology and Neuroscience of Curiosity.” Neuron. 2015;88(3):449-460. doi: 10.1016/j.neuron.2015.09.010 Peterson EM. Supporting curiosity in schools and classrooms. Behavioral Sciences. 2020;35:7-13. doi: 10.1016/j.cobeha.2020.05.006 Hall S. The Young Child as Scientist. A Learning Moments Collection. Videatives. 2015. https://videatives.com/node/2117 Jirout JJ, Vitiello VE, Zumbrunn SK. Curiosity In Schools. The New Science of Curiosity . Edited by Gordon G., 243-266. Nova, 2018. Previous article back to Fact & Fiction Next article

< Back to Issue 10 Terrible Lizards and their Terrible Reconstructions by Kaya Czerwinska 2 June 2026 Illustrated by Esme MacGillivray Edited by Vicenta Wheatley This comes as a surprise to nobody, but it isn't the easiest task in the world to figure out an extinct creature’s appearance, habitat and behaviour from a few bones. Our understanding of animals is constantly evolving with new discoveries and technology, much like the species themselves. Yet, no matter how cunning we are to glean all kinds of fascinating history about those who lived so long before us, we humans can't always get it right. Let’s take a walk down memory lane to look at some of history’s more eccentric paleontological reconstructions! Stegosaurus Figure 1 W.H. Ballou’s Vision of a Flying Stegosaurus. Note. Image reproduced from (3). Stegosaurus is one of the more well-known dinosaurs and can be easily spotted among a child’s plastic figurine set. When presented with something Stegosaurus -shaped, one is left with very little doubt in their mind that it is, indeed, a Stegosaurus . There’s no modern animal quite like it. However, this distinctness is exactly what gave scientists trouble when they first discovered it. More specifically, why did it have plates on its body, and where were they supposed to go? Othniel Charles Marsh, the paleontologist who discovered it, initially believed that the plates sat flat over its back like armour or roof tiles (1). This is where its name, which translates to ‘roofed lizard’, came from. The confusion did not end after realising the plates were supposed to stand upright, though. Imaginations ran wild as their function remained unclear. One 1912 edition of the Cincinnati Enquirer claimed that they were used for defence against predators, calling Stegosaurus the ‘most grotesque animal’ and ‘a freak of nature’ (2). Another article, written by William Hosea Ballou, was published in the Ogden Standard-Examiner in 1920, suggesting that it used its plates like wings for gliding or flight (3). This was considered absurd even for the time, but was certainly charming to picture. To this day, what our spiky friends used their plates for is up for debate. Some of the more recent hypotheses are that they assisted with regulating temperature or colourful displays, which have been supported by the discovery of channels inside the plates that might have held blood vessels (4). However, even once we conclusively figure out what their true function was, flying Stegosaurus will remain a whimsical and creative interpretation. Elasmosaurus Figure 2 Cope’s Initial Reconstruction of Elasmosaurus with its Head on the Wrong End. Note. Image reproduced from (5). Sometimes, one can get so distracted by workplace drama that they can’t make head nor tail of the work they’re supposed to be doing - literally. This was the case for Edward Drinker Cope, a rival of Othniel Charles Marsh (who described Stegosaurus ). Both paleontologists competed to discover more new species, often criticising and even sabotaging each other’s work. In 1869, Cope attempted to describe a new marine creature called Elasmosaurus , which had four flippers and a long neck, almost like the Loch Ness monster (5). Unfortunately, he made one crucial error. In his reconstruction, he had mistakenly attached the head to the tail end instead of the neck. While it was quickly pointed out and fixed, Cope’s blunder was much to the amusement of Marsh, who frequently mentioned it in order to call Cope a ‘careless’ scientist who rushed his work (6). People tend to use this moment as an example of the many insults and arguments Marsh and Cope threw at each other during their lifelong feud. However, an animal like Elasmosaurus had not been seen before, and it’s very common for lizards to have long tails. Deciding that the longer end must be the tail wouldn’t have been a completely unreasonable guess at the time. At the end of the day, it’s important to remember that paleontologists during their time were working from much less information than we have today. Hallucigenia Figure 3. Initial Reconstruction of Hallucigenia Walking Using Spines. Note. Image reproduced from (7). Hallucigenia ’s name means ‘hallucination’ or ‘dream producer’, which is a good indicator of the experience scientists had while attempting to figure this creature out. It lived around 505 million years ago during the Cambrian era, a time when evolution was being particularly experimental (7). All kinds of strange, worm-like creatures were wandering the ocean floor, and many of them were very small. This certainly doesn’t help scientists trying to interpret the vague and cryptic shapes these animals can create when they become fossils. The first proposed idea about Hallucigenia was that it moved on a set of stiff, straight legs, with tentacles coming out of its back (8). If that wasn’t confusing enough, there was also a mysterious stain near one end of the initial fossil’s body, prompting debate about which side was the head. The mystery was finally solved when a second specimen was discovered, sitting in the rock at a different angle that allowed its legs to be seen more clearly. The ‘legs’ were actually spines on its back, and its real legs were the ‘tentacles’ (9). Scientists had been looking at it upside-down the whole time. While we finally know roughly what it looked like, Hallucigenia continues to be somewhat of an enigma to this day, with many things left to figure out about its place in the tree of life and its relatedness to other species. Oviraptor Figure 4. Oviraptor Embryo from Flaming Cliffs. Note. Image reproduced from (12). As a fossilised animal’s behaviour can’t be observed in action, scientists often rely on context clues from the environment that the fossil was found in. This was the case for a dinosaur discovered on top of a nest of fossilised eggs in 1924. The new species was named Oviraptor , meaning ‘egg thief’, in reference to the belief that it preyed on the eggs of another dinosaur called Protoceratops (10). However, some later analyses revealed that Oviraptor didn’t have teeth well-suited for eating eggs, and probably didn’t include them in its diet (11). It was later discovered that the eggs from the original specimen contained not Protoceratops , but baby Oviraptor embryos - Oviraptor had been framed for eating its own children (12). While the mistake has been rectified for several decades by now, it is still food for thought that humanity’s first instinct was to assume this dinosaur was hunting the eggs and not incubating them. There has, first through our knowledge gaps and later through pop culture portrayals, persisted an idea of dinosaurs as nothing more than scaly, destructive beasts. Dinosaurs are unintelligent and run purely on impulse. Dinosaurs kill on sight. Dinosaurs would never take care of their children. Yet, they did. Humans are not the only animals capable of caring or compassionate acts, and Oviraptor is a reminder to be careful of anthropocentrism. Woolly Rhinoceros Figure 5. Reconstruction of the ‘Unicorn’ by Gottfried Wilhelm Leibniz. Note. Image reproduced from (13). Almost the holy grail of paleontological blunders is the Magdeburg Unicorn. Not knowing how to put together a Woolly Rhinoceros skeleton is understandable, but this specific reconstruction of one has many notable issues, including a lack of back legs and a completely missing torso. The glaring inaccuracies can be attributed to the fact that the fossil was discovered and reconstructed in the 1600s, long before any other examples in this article (13). Paleontology as a discipline was still in its infancy, and beliefs in creatures such as unicorns were still common. Thus, when a number of woolly rhinoceros and woolly mammoth bones were discovered in a cave, inexperience and superstition combined to manifest them into a brand new creature. The origin of the horn is somewhat dubious but was most likely a narwhal tusk (14). As paleontology advanced, the unicorn’s status as a plausible reconstruction gradually slipped away. However, on a bad day, it’s still helpful to picture a living Magdeburg Unicorn frolicking through fields in all its bizarre glory. Perhaps if this article had been written a few years from now, there would be a few new entries about animals that we think we understand well today. The only constant truth in science is that it never stops moving forward. With every step, we leave behind a piece of what we thought the truth was, and it’s only fair to show some appreciation for those who laid the path. However, two things can be true at once. We can respect the hard work of each scientist in history who has made attempts to improve humanity’s understanding of the world around us. And we can also laugh at the fact that in hindsight, many of those attempts turned out to be spectacularly strange. References Marsh OC. A new order of extinct Reptilia (Stegosauria) from the Jurassic of the Rocky Mountains. Zenodo [Internet]. 1877 Dec 1; Available from: https://zenodo.org/record/1450038#.YoPJRIjMLrc The Ogden standard-examiner. (Ogden, UT), Aug. 15 1920. https://www.loc.gov/item/sn85058393/1920-08-15/ed-1/ . "Was Most Grotesque Animal" Newspapers.com . The Cincinnati Enquirer, 22 June 1912. https://www.newspapers.com/article/the-cincinnati-enquirer-was-most-grotesq/113116207/ . Farlow JO, Hayashi S, Tattersall GJ. Internal vascularity of the dermal plates of Stegosaurus (Ornithischia, Thyreophora). Swiss Journal of Geosciences. 2010 Aug 24;103(2):173–85. Cope ED. The Fossil Reptiles of New Jersey (Continued). The American Naturalist. 1869 Apr 1;3(2):84–91. Davidson JP. Bonehead mistakes: The background in scientific literature and illustrations for Edward Drinker Cope’s first restoration of Elasmosaurus platyurus. Proceedings of the Academy of Natural Sciences of Philadelphia. 2002 Oct;152(1):215–40. Conway Morris S. A new metazoan from the Cambrian Burgess Shale of British Columbia. Palaeontology. 1977;20(3):623–40. Stephen Jay Gould. Wonderful life : the Burgess Shale and the nature of history. New York: W.W. Norton & Company; 1989. Ramsköld L, Xianguang H. New early Cambrian animal and onychophoran affinities of enigmatic metazoans. Nature. 1991 May;351(6323):225–8. Henry Fairfield Osborn. Three new Theropoda, Protoceratops zone, central Mongolia. American Museum Novitates. 1924 Jan 1;144:1–12. Barsbold, R. "Khishchnye dinosavry mela Mongoliy" [Carnivorous Dinosaur of the Cretaceous of Mongolia]. Transactions of the Joint Soviet-Mongolian Paleontological Expedition . 1983 19: 5–119. Norell MA, Clark JM, Demberelyin D, Rhinchen B, Chiappe LM, Davidson AR, et al. A Theropod Dinosaur Embryo and the Affinities of the Flaming Cliffs Dinosaur Eggs. Science. 1994 Nov 4;266(5186):779–82. Gottfried Wilhelm Leibniz. Protogaea. University of Chicago Press; 2008. Kolfschoten, Thijs. THE WOOLLY RHINOCEROS FROM SEWECKENBERGE NEAR QUEDLINBURG (GERMANY). 157. 39-48. doi:10.11588/propylaeum.868.c11306. Previous article back to Fact & Fiction Next article

< Back to Issue 10 How Population Biobanks Shed Light on Disease by Jason Chien 2 June 2026 Illustrated by Chris Cao Edited by Cady Jacobson Imagine yourself as a researcher. Perhaps your work requires biological samples from a rare disease, but finding and collecting these samples from patients is difficult. Or maybe your research depends on comparing a person’s current cell or tissue data to what it was ten years ago, but you cannot afford to wait a decade. Thankfully, there are biobanks: specialised facilities that store biological samples and other relevant medical information from donors, while also distributing samples to researchers regardless of where they are based. Biobanks also act as data custodians, de-identifying and anonymising patient information. In addition, they work with Institutional Review Boards (essentially, university or agency ethics boards) to review the merits of each access request before deciding whether to deliver samples to applicants (1). For some biobanks and sample types, samples can even be returned after being used for research (2). There are biobanks storing non-human data, such as the Svalbard Global Seed Vault or Australia’s Victorian Conservation Seedbank, which store viable seeds of many plant species and their various strains (3). Even within biomedical biobanks, they vary in the types of samples stored and by extension, their intended and fulfilled functions, as well as why they were built (4).There are disease-specific biobanks storing samples relevant to specific diseases; for example, a cardiovascular biobank that specialises in storing tissue immediately following a patient’s death, such that it can be used for physiological studies (2). However, this article will focus specifically on population biobanks, a subset of biomedical biobanks, in the context of disease investigation. Ethical issues surrounding biobanking will not be a major focus, including matters such as how sample donors provide consent for the use of their samples during research (4). Population biobanks store tissue samples, plus health and personal information of donors. Large sites have sample counts ranging from hundreds of thousands to millions (1). Population biobanks aim to have enough samples to represent the huge variation among a region or country’s population, and store many parameters of each sample donor, such as lifestyle data (e.g. cardiovascular disease or smoking status) and omics data (5). Biomedical scientists study many aspects of what goes on in human cells and tissues, down to the molecular level, due to their relevance for our understanding of disease. These factors include our genetic makeup, regulation and expression of genes, as well as the effects of environmental factors and metabolism (6). In such omics approaches, our existing knowledge of the complete set of genes in species such as humans allows information from an individual’s own genome to be generated and then compared or combined with data from other individuals. This gives rise to approaches such as genomics (concerning genes), proteomics (concerning proteins) and metabolomics (concerning molecules involved in metabolism). Large subsets of this data from individuals, as well as population-level variations associated with specific diseases, can be used for research. For example, the number of genes involved in cancer alone can easily exceed thousands (7). Large sample quantities allow researchers doing many different investigations to identify factors correlated with disease resistance and susceptibility to many diseases (1). This complements methods of investigating disease mechanisms involving specific genes and molecules by helping researchers identify candidate genes and molecules for further investigation. As a consequence, many samples in population biobanks are actually from healthy donors rather than hospital patients (5). Beyond providing samples, some of these large biobanks are also direct providers of omics data. While biobanks are not necessary for generating omics data from one or a few individuals, they enable the collection of data from enough samples to represent the diversity of the population and capture variants as rare as those in 0.1% of the population (6). Because of rigorous sample processing and quality control procedures standardised across biobanks, the omics data generated from samples collected by different biobanks can also be more easily combined by researchers to yield insights (1). Furthermore, as new higher-resolution biotechnology develops, they can be used to investigate samples collected in the past (1). For example, the UK biobank enrolled 500,000 participants for its first cohort in 2006, collecting blood, urine, and saliva samples, in addition to substantial lifestyle data and physical measurements for each participant (5). Though there is no flashy silver-bullet discovery like penicillin directly resulting from the biobank, it has greatly increased our knowledge of which genes and proteins to target when designing new drugs, along with which genetic variants increase our predisposition to a range of diseases, such as cancer and cardiovascular diseases (8). Population biobanks are huge, long-term investments. For example, funding from the UK government and various non-profits for the UK biobank have exceeded £90 million British Pounds from its inception to 2014 (1). Reasons for their construction include understanding the mechanisms of disease, translating research into interventions, improving health outcomes, and promoting biotechnology (1). Population biobanks that are able to effectively engage sample donors can generate population data to support research into diseases that most heavily affect a country (1). The majority of the world’s biobank datasets are still composed primarily of individuals with white Northern European ancestry (9), and using data from one population can be significantly less effective for identifying risk factors in another population. This limitation serves as a driver for developing countries to build their own population biobanks (9). Part of the reason most biobanks are built is to serve as a national public good, with data made accessible to both academic researchers at affordable rates and to industry researchers (1, 10). Large population biobanks are usually run as a public entity or as public-private partnerships with a large proportion of public funding (10). In fact, even with cost recovery measures that charge users for accessing biobank samples — often with higher rates for industry researchers — revenues still fall below operating costs (1). That said, biobanks create benefits beyond their own countries, and multinational collaborations have expanded their scale and reach (1), allowing researchers to access omics data and request samples from biobanks overseas. With biobanking infrastructures in place, multinational collaborations have emerged that facilitate data sharing between research institutions across different countries through consortia – formal collaborations between participating institutions that establish common research goals and reduce competition over the use of specialised facilities (11). In other words, they seek to minimise situations in which multiple research groups inadvertently work on the exact same project, leading to an inefficient allocation of resources. One example is the International Cancer Genome Consortium (ICGC). This agreement creates a collaboration framework for data exchange in around 200 large-scale cancer research projects, with participating biobanks from Europe, China, Australia, USA, and other countries. Participating biobanks include large population biobanks, but also other types such as disease-specific biobanks (12). To finalise, biobanks are not simply a place where biological samples are stored. They are dynamic entities that can be scaled up and down, places where samples are sent in and out, and they face financial pressures as national research priorities change. They are places where innovation occurs in a wide range of areas, from cryostorage to management of digital information. The power of population biobanks and their research potential lies in their cohort sizes. Hopefully, biobanks will continue to generate valuable new discoveries as newly established cohorts around the world begin to mature. References Chalmers D, Nicol D, Kaye J. et al. Has the biobank bubble burst? Withstanding the challenges for sustainable biobanking in the digital era. BMC Med Ethics. 2016;17(1):39. doi:10.1186/s12910-016-0124-2. PMID: 27405974; PMCID: PMC4941036. Yamada, K.A., Patel, A.Y., Ewald, G.A. et al . How to Build an Integrated Biobank: The Washington University Translational Cardiovascular Biobank & Repository Experience. Clinical And Translational Science . 2013;6(3):226-231. doi: https://doi.org/10.1111/cts.12032 Seed deposit at Doomsday Vault ensures Australia’s plant future. ABC News. 2018 Mar 1. https://www.abc.net.au/news/2018-03-01/australia-makes-deposit-in-to-doomsday-vault-to-ensure-survival/9496308 De Souza, Yvonne G.; Greenspan, John S. Biobanking past, present and future: responsibilities and benefits. AIDS. 2013 ; 27(3):303-312. doi: 10.1097/QAD.0b013e32835c1244 Busby H, Martin P. Biobanks, national identity and imagined communities: The case of UK biobank. Science as Culture. 2006 Sep;15(3):237–51. doi:10.1080/09505430600890693 Murtagh, M.J., Demir, I., Harris, J.R. et al. Realizing the promise of population biobanks: a new model for translation. Hum Genet . 2011;130:333–345. doi: https://doi.org/10.1007/s00439-011-1036-3 Ferolito BR, Dashti H, Giambartolomei C, Peloso GM, Golden DJ, Gravel-Pucillo K, et al. Leveraging large-scale biobanks for therapeutic target discovery. Human Genetics and Genomics Advances. 2026 Jan;7(1):100556. doi:10.1016/j.xhgg.2025.100556 Szustakowski JD, Balasubramanian S, Kvikstad E, Khalid S, Bronson PG, Sasson A, et al. Advancing human genetics research and drug discovery through exome sequencing of the UK Biobank. Nat Genet. 2021 Jul;53(7):942–8. doi:10.1038/s41588-021-00885-0 Rudan I, Marušić A, Campbell H. Developing biobanks in developing countries. J Glob Health. 2011 Jun;1(1):2–4. PubMed PMID: 23198094; PubMed Central PMCID: PMC3484738. Caulfield T, Burningham S, Joly Y, Master Z, Shabani M, Borry P, et al. A review of the key issues associated with the commercialization of biobanks. Journal of Law and the Biosciences. 2014 Mar 1;1(1):94–110. doi:10.1093/jlb/lst004 Nature Index. 2021. How to be part of a research consortium. Available from: https://www.nature.com/nature-index/news/how-to-be-part-of-a-research-consortium Hudson (Chairperson) TJ, Anderson W, Aretz A, Barker AD, Bell C, Bernabé RR, et al. International network of cancer genome projects. Nature. 2010 Apr;464(7291):993–8. doi:10.1038/nature08987 Previous article back to Fact & Fiction Next article