PERSE PERIODICAL
Created by students, for students
With special thanks to our editors and designers:
Leanne Suo-Sanders, Aamarah
Khurram, Brijes
Harish, Atida Kusotera, Hercules Voultsos and Sophie Ji.
Welcome to Perse Periodical!
Editors' notes:
Welcome to the Michaelmas issue of Perse Periodical, the student-led science magazine of the Perse Upper. I am delighted to introduce our latest publication to you. We aim to cultivate a deeper appreciation for scientific research and exploration beyond the confines of classroom learning. Within the pages of the Perse Periodical, you will find a diverse array of content, including articles, book reviews and games.
In this issue, we explore cutting-edge research and science that promise to transform how we see our world. From advancements in our understanding of the human body, to breakthroughs in reverse ageing.
Additionally, I am very grateful to the editors and design team for their unwavering commitment to maintaining such a high standard of quality in this magazine. Their dedication and collaborative spirit have been indispensable in completing this magazine.
With kind regards, Luke West
Acknowledgements:
Thank you to everybody who has contributed to making this magazine this term - Ciaran Morgan, Alison Siu, Neelkantha Mukherjee, Millie Ely, James Bell, Liu Chenning and to Dr Miller especially.
What does the amino acid Tryptophan do, and did it come from space?
Type 2 Diabetes: New Insights in Pancreatic Cell Function
Reverse Ageing in mice: Is Now the Time?
Geoengineering the Arctic: Is mitigation possible, ethical and sustainable? What is ‘Personalised Medicine’ and what challenges are left to overcome in its development?
What does the amino acid
Tryptophan do, and did it come from space?
By Ciaran Morgan
Amino acids are molecules used by all living things to make proteins. These proteins are essential to maintain healthy bodily functions, including muscle growth, tissue repair, and nutrient absorption.
Tryptophan, C11H12N2O2 is one of the 20 amino acids
This is because it is concentrated in the hypothalamus and midbrain and the fluctuations in its concentration lead to disorders of mood. Antidepressants work against this by inhibiting the body’s inactivation of serotonin, which elevates the concentration of serotonin and therefore elevates mood.
The chemical structure of niacin, which is a precursor molecule to NAD, a primary component in aerobic respiration.
considered whether
building such water have Work acids expected more
The spectral lines of tryptophan, which was used to identify it in space.
Type 2 Diabetes: New Insights in Pancreatic
β-Cell Function
By Neelkantha Mukherjee
Type 2 diabetes is one of the most common ailments affecting more than 530 million people worldwide. Tissues become resistant to insulin in regulating blood sugar which leads to hyperglycaemia or increased blood sugar. The β-cells in pancreatic islets of Langerhans continue to produce more insulin to regulate hyperglycaemia and this vicious cycle ultimately leads to β-cell failure. The majority of these pathologies tend to cause irreversible damage to the system making diabetes and associated disorders a challenging problem to treat clinically. The following are three new findings related to insulin production.
Prevalence of diabetes in the world and its projected increase over the next 20 years.
1. A helper for Insulin Secretion:
One of the therapeutic strategies for managing diabetes is to activate insulin production from the pancreas. To that end, genetic screening was performed across 310 individuals to search for new endocrine regulators of pancreas function (Viesi et al, 2024). Specifically, global gene expression from 18 different tissues was analysed to identify potential endocrine regulators of insulin secretion.
This analysis identified liver-specific haptoglobinrelated protein (HPR) as genetically enriched with islet insulin responses.
How the human body regulates insulin production
To test whether HPR might be useful in alleviating diabetes by activating β-cells, researchers treated mice with either HPR protein or saline as control. These mice were then fed a high fat diet to mimic obesity-induced insulin resistance which developed in salinetreated mice as expected. The mice treated with HPR treatment were protected from developing insulin resistance. This research highlights a novel liver-produced protein that improves β-cell function, HPR.
2. A New Signalling Pathway that Causes β-cell Dysfunction:
The action pathway of incretins
Insulin production involves folding of the peptide hormone within the endoplasmic reticulum (ER). Conditions that produce cellular stress, including ER stress, are linked to β-cell dysfunction. Mechanisms that lead to ER stress and how that affects insulin production are therefore important research areas. One of the mechanisms that leads to insulin secretion from β-cells is the action of incretins. Briefly, incretin hormones are gut-produced peptides that are secreted after eating and stimulate insulin secretion by the activation of signalling cascades involving cAMP production. A common cause for β-cell dysfunction is impairment of the β-cell response to incretins such as glucagon-like peptide 1 (GLP-1). Current research has identified ATF4, a transcription factor, to be key player activated by ER stress (Lee, 2024). When ATF4 is produced it leads to the transcription and production of PDE4D, a phosphodiesterase, which acts to reduce cAMP within the cell. cAMP-dependent signalling pathways downstream of incretin hormones are therefore negatively affected by ATF4 production, consequently leading to β-cell dysfunction. This pathway could, therefore, be a therapeutic target for protecting β-cell function during the progression of Type 2 diabetes.
3. How inflammation affects insulin production:
In response to glucose in food, pancreatic β-cells rapidly secrete preproduced insulin and then continue to produce insulin to reach glycaemic control. The first phase insulin release (FPIR) is among the earliest detectable parameters of β-cell dysfunction. Stress, among other conditions, leads to inflammation. This causes the production of secreted proteins called cytokines such as interleukin 6 (IL6), interferon g (IFN g) and tumour necrosis factor a (TNFa) from macrophages within the islets. New research shows that of these cytokines, only TNFa causes the internalisation of incretin receptors from the membrane to the inside of the β-cell (Hussain et al, 2024).
In response to glucose in food, pancreatic β-cells rapidly secrete preproduced insulin and then continue to produce insulin to reach glycaemic control. The first phase insulin release (FPIR) is among the earliest detectable parameters of β-cell dysfunction. Stress, among other conditions, leads to inflammation. This causes the production of secreted proteins called cytokines such as interleukin 6 (IL6), interferon g (IFN g) and tumour necrosis factor a (TNFa) from macrophages within the islets. New research shows that of these cytokines, only TNFa causes the internalisation of incretin receptors from the membrane to the inside of the β-cell (Hussain et al, 2024).
The action of Pancreatic Islet cells, and their functions
As a result, this renders the β-cells resistant to incretin action and leads to β-cell dysfunction. Progressing forward, researchers have identified that activation of retinoic acid receptor 7 protects β-cells from TNF α-induced β-cell dysfunction.
Summary
Liver produces haptoglobin-related protein (HPR) that augments insulin production from βcells. Gut-produced incretin GLP1, when engaged with its receptor GLPR on β-cells, induces cAMP that
ultimately leads to insulin secretion. ER stress induces the production of ATF4 which transcribes PDE4D, a phosphodiesterase, that reduces β-cell cAMP, consequently reducing insulin production. Pancreas-resident macrophages produce, among other cytokines, TNFa that leads to the internalisation of GLPR thus reducing incretin signalling and reducing insulin production. Red arrows: lead to β-cell dysfunction; Green arrows: promote β-cell function of insulin production.
Reverse Ageing in mice: Is Now the Time?
By Alison Siu
How does ageing work?
According to Steven Horvath, we can estimate the age of our cells by finding out the changes in our DNA methylation patterns. For an embryonic stem cell to become specialised, the cell goes through a process called de-novo-methylation (differentiation). This process is catalysed by a group of enzymes called DNA methyltransferases (DNMT), which adds methyl groups to the C bases at the CpG sites (where C and G bases are found together) located in different regions in a gene. This causes certain genes to be expressed, and other genes to be silenced. This also allows the stem cell to become a specialised cell, adapted to perform for a particular function. However, as we age, not all the genes that should be read are expressed, causing a cell to lose their function.
Research from the Harvard Medical School has demonstrated that it is possible that we can turn back the biological clock in our cells and become young once again.
A major discovery
To find out more about the effects of the epigenome (the DNA wrapped around histones) on ageing, scientists used two mice which are twins (They have the same genes), then disrupted the epigenome on one of the mice. After 10 months, the same mouse had twice the age as its twin. Instead of accelerating ageing, an experiment was also conducted on slowing down ageing: they found out that NMN, a sirtuin activating molecule (Sirtuin is a family of signalling proteins involved in metabolic regulation) can make the cardiovascular system of an old mice younger, thus allowing the mice with NMN to have younger cells and run faster, compared to the other mice of the same age which cannot.
The birth of a new treatment
Another ground-breaking discovery was made by the Sinclair lab at the Havard University, in which scientists were able to restore the vision of a blind mouse. As we age, some of our cells start to lose their abilities to regenerate, with the Central Nervous System being the first. Part of the Central Nervous System is the Retinal Ganglion Cells (RGC), which has already lost their ability to regenerate by a few days after birth. At the Sinclair lab, scientists produced a “OSK in an optic nerve crush injury model” to experiment on whether it is possible to allow adult RGC cells to regenerate again.
Using the Tet-Off adeno-associated virus as a vector, OSK is injected to two groups of mice via an intravitreal injection (an injection into the clear gel in the eyeball). However, after 2 weeks, the optical nerve was damaged by the procedure “optical nerve crush” for one of the groups. What was surprising was that after 12-16 weeks with the OSK turned on, the RGC axon fibres regenerated and reached the chiasm, where the optic nerve connects to the brain. It was also found out that the neurons regenerated was half the age as the original neurons before the experiment.
Human central nervous system
By this discovery, the scientists decided to continue their research further to see if RGCs can be regenerated in patients that have glaucoma, a disease that causes blindness due to old age. By expressing the OSK genes, once again, they have reversed the age of the RGCs and restored vision in old mice with glaucoma. To test whether the mouse can actually see, they used four computer screens to surround it, with each of the screens displaying moving lines. The mouse with glaucoma would stand still, with its head not moving, whilst the mouse treated with OSK expression moved its head, trying to follow the movement of the lines.
This has proved to be another step in biotechnology towards reverse ageing, suggesting that in the near future, we may even be able to successfully reverse the age of human cells, treating organ failure and diseases that were once thought to be untreatable, such as Parkinson’s and Alzheimer’s disease.
Reverse ageing in mice; two siblings, one who has been genetically altered to be older, used to see if researchers could reverse ageing.
Geoengineering the Arctic: Is Mitigation Possible, Ethical and Sustainable?
By Millie Ely
Global warming across the globe compared to pre-industrial conditions
The Arctic, whilst sparsely populated, has been more affected by anthropogenic climate change than any other place. Arctic Amplification boosts the warming and its consequences through feedback loops, particularly the Albedo Effect.
This phenomenon threatens the Arctic’s unique ecosystem and global climate stability. Geoengineering is a controversial yet innovative and potentially transformative approach in response to the crisis. How feasible are these approaches? If they could be effective, is it ethical for humans to push involvement and mitigation in the Far North?
Arctic Amplification is driven by feedback mechanisms. The loss of reflective sea ice and the release of greenhouse gases from thawing permafrost produce a positive feedback loop driven by warming and melting. Reduced albedo causes the absorption of excess insolation, promoting the melting of sea ice, which further lowers the albedo.
Marine Cloud Brightening has the potential to work on a regional scale, and if implemented over vulnerable areas of sea ice, could reduce the impacts of Arctic Amplification. So far it is still in the beginnings of research, and the fact that it has not had large-scale success over the past 12 years suggests it may be ineffective in the long run. This technique may be more likely to have success in tropical areas such as coral reefs, where stopping the absorption of heat could cause bleaching to decrease and protect the ecosystem from its base.
The slowing of Arctic sea ice melt has been attempted through other preventative than cloud brightening such as ice thickening. Researchers are exploring methods to enhance ice thickness and resilience to heat. This includes deploying reflective materials on the surface of the ice to increase its albedo and internal geoengineering structures to promote ice formation. The success of this technique is still unclear, and it has not been evaluated over a scale much larger than a lab.
The strengthening of sea ice could help to stabilise regional climate patterns and protect marine ecosystems that are reliant on ice habitats. However, due to the natural fluctuations in sea ice that have always been observed, it does not seem ethical to influence the ice. Implementing engineering within a fragile ecosystem could cause more damage than benefits. Perhaps over a brief time scale such as seasonally, it could help Arctic sea ice to refreeze during the winter and promote the regrowth of the Arctic yearly.
Marine cloud brightening above a coral reef
The scale that ice thickening could be successful on is so small that it is not a feasible strategy to reduce the impact of Arctic Amplification.
Techniques such as biochar application – converting biomass into a stable carbon form that can be buried in soil, and afforestation efforts specifically tailored to Arctic conditions, could sequester carbon dioxide from the Arctic, improving the capability of the Arctic to maintain and absorb carbon. These techniques are on a small scale, again, and are likely to have negligible impact on the carbon cycle in the Arctic. The practicality of geoengineering relies on technological advancements. Marine cloud brightening and ice thickening offer potential benefits for cooling or preventing warming in the Arctic, however they also pose challenges such as unpredictable regional climate changes and costs. The resilience of ecosystems to these techniques is not clear yet due to the novelty of the research.
There is some potential for geoengineering to mitigate Arctic Amplification, but there are significant ethical and practical issues. The scale of the techniques examined here is small and relatively short-term, so these techniques seem unsustainable.
Icethickeningthroughaddingextrawaterontopoftheice
What is ‘Personalised Medicine’ and what challenges are left to overcome in its development?
By James Bell
Personalised medicine has been a concept at the forefront of bioscience research ever since the entire human genome was mapped successfully in 2003, in fact, it was likely an idea that existed even before the project completion. To quote a useful analogy when it comes to explaining what is meant by ‘personalised medicine’: a teenage boy would not buy the same clothes as his grandmother, yet when they get sick, they are likely to be treated in almost the exact same way.
This is because of the “one-size-fits-all” approach to medicine. The current system is, referring back to the analogy, that grandma’s clothes do the job for everyone and that’s that. But what if there was a way to transform this universalist way of thinking to personalised healthcare, epitomised by the delivery of "the right drug to the right patient at the right time”? What if everyone got the clothes that look and feel best on them?
Despite this, the respective emphasis on medical universalism versus specificity has fluctuated over the course of history. Some argue that medicine is already ‘personalised’, as doses and drugs administered can differ completely depending on how a disease presents itself symptom-wise, the physical and mental condition of the patient, and so on. Australia’s National Health and Medical Council rather broadly defines personalised medicine as ‘the capacity to predict disease development and influence decisions about lifestyle choices or tailor medical practice to an individual’. This covers its wide range of interpretations well.
The context in which ‘personalised medicine’ is often incorporated is in reference to customised healthcare founded on individualised genomic risk information. This information comes in the form of observable ‘biomarkers’ used to predict how a particular disease or illness may affect a specific person, allowing for tailor made treatment based on a patient’s DNA.
Despite the promising research into personalised medicine, it is still yet to be used in public treatment. To put it simply, the investment needed would me immense, likely making the task greater than it’s worth. Furthermore, it’s important to realise the paradigm shift required for the generalised use of personalised medicine would have vast implications. Almost all forms of medical professionals would need advanced training, not only into understanding the subject itself, but also how to use the massively expensive technology needed for reading the human genome. Ethical issues are also a large factor, as ensuring privacy and the confidentiality of genomic results is of colossal importance, after all, the thought of your entire genomic sequence being leaked in a data breach isn’t exactly a pleasant one.
Even with the possibility of the use of AI to personalise therapy, and this being more cost-effective for stretched healthcare systems, as well as genomic sequencing getting cheaper, there are other costs. Screening for a disease involves accumulating the genomes of many healthy individuals to benefit a small minority. This is still hugely expensive.
There are clearly issues with the implementation of personalised medicine with the technology and understanding we have today. However, Francis Collins (then-director of National Human Genome Research Institute) stated that by the year 2020: “gene-based designer drugs are likely to be available… for example, cancer treatment will precisely target the molecular fingerprints of particular tumours, and genetic information will be used routinely… ” . While scientists aren’t quite there yet with ‘gene-based designer drugs’, ongoing research seems promising. The development of personalised medicine is constantly ongoing and it’s seeming more and more likely that Francis Collins’ prediction could well come true in the near future.
How do Quantum computers differ to classical computers?
By Liu Chenning
What Are Quantum Computers?
Quantum computers represent a revolutionary leap in computing technology. Unlike classical computers, which process information in binary (bits of 0s and 1s), quantum computers harness quantum-mechanical phenomena, such as superposition and entanglement, to perform complex calculations at unprecedented speeds.
For instance, while a classical computer might need to sequentially search a database by checking each entry, a quantum computer can evaluate all possibilities simultaneously, significantly reducing the time required for certain computational tasks.
What Is Superposition?
Superposition is a quantum property where a quantum object exists in multiple states simultaneously. For quantum computing, this means that a quantum bit (qubit) can represent both 0 and 1 at the same time, unlike classical bits that can only represent one state at a time. This property dramatically increases the computational power of quantum systems.
Representation of superposition
What Is Entanglement?
Entanglement describes a phenomenon where two or more qubits become interconnected in such a way that the state of one qubit directly affects the state of the other, even when separated by vast distances. When one qubit's state changes, the entangled qubit's state updates instantaneously, enabling highly coordinated computations across a network of qubits.
Why Do We Need Quantum Computers, and Who Is Experimenting with This Technology?
Modern computing is approaching a critical limit. Classical transistors, the building blocks of traditional computers, are nearing atomic scales, leading to issues like quantum tunneling**, where electrons bypass the transistor barriers, rendering them ineffective. Quantum computers, by leveraging quantum effects, overcome these limitations, paving the way for breakthroughs in areas such as cryptography, optimization, and scientific simulation.
Google’s new quantum computer, Google Quantum AI.
Currently, major organizations and companies are heavily investing in quantum research. Notable players include:
IBM: Offers the IBM Quantum Experience, enabling public experimentation with quantum processors.
Google: Achieved "quantum supremacy" in 2019 with a calculation performed in seconds that would take classical supercomputers thousands of years.
Microsoft: Focused on topological qubits to improve stability and reduce error rates.
D-Wave Systems: Commercialized quantum annealers for optimization problems.
How
1. Processing Units:
Quantum computers use qubits capable of representing multiple states simultaneously, whereas classical computers use transistors that can only represent one state at a time.
Temperature Requirements
Quantum computers rely on superconducting materials, which must be kept near absolute zero (-273°C) to function effectively, making their operation resource-intensive. Classical computers, on the other hand, operate at room temperature.
3. Error Rates:
Quantum systems are highly sensitive to environmental disturbances, leading to higher error rates. While classical computers achieve stability through established technologies, quantum error correction remains an area of active research.
4. Energy Efficiency:
While quantum computations require minimal energy at low temperatures, maintaining the cooling systems consumes significant power.
Advantages of Quantum Computers and Their Future
Potential
Quantum computers offer transformative advantages:
1. Power and Speed:
Quantum systems can process massive datasets and solve complex problems exponentially faster than classical supercomputers. For example, Google's Sycamore quantum processor solved a calculation in 200 seconds that would take a classical supercomputer an estimated 10,000 years.
2. Applications Across Industries:
Healthcare: Accelerating drug discovery and personalized medicine.
Finance: Optimizing portfolios and predicting market trends.
Weather Prediction: Enhancing climate modeling and disaster forecasting.
Artificial Intelligence (AI): Improving machine learning models and autonomous systems.
3. Climate Change Mitigation:
Quantum computers can analyze vast datasets related to carbon emissions, deforestation, and weather patterns, providing actionable insights to combat global warming.
4. Cybersecurity:
Quantum encryption methods, such as **quantum key distribution (QKD)**, offer unparalleled data protection. However, they also pose risks, as malicious actors could exploit quantum decryption to bypass classical encryption.
A diagram of quantum key distribution
Disadvantages of Quantum Computers
1. Operational Costs:
The energy consumption of a quantum vs classical computer in a Monte Carlo simulation –quicker tasks are better with a quantum computer.
The energy and infrastructure required to maintain quantum systems make them inaccessible to general consumers.
2. Environmental Sensitivity:
Quantum bits are prone to decoherence (loss of quantum state) when exposed to external interference, such as temperature fluctuations or electromagnetic signals.
3. Limited Use Cases:
Quantum computers excel at specific tasks, like optimization and cryptography, but are not well-suited for general-purpose computing, such as web browsing or gaming.
4. Security Risks:
The ability of quantum systems to break classical encryption schemes poses significant risks, especially if quantum technology falls into the wrong hands.
My Opinion on Quantum Computers
Quantum computing represents an extraordinary leap forward in technology, with the potential to transform industries. However, current quantum systems are still in their infancy, plagued by stability and scalability challenges. Until these obstacles are overcome, quantum computers will likely remain tools for specialized applications in research and industry. For everyday consumers, classical computers are sufficient for most tasks.
In the future, as quantum technology matures and costs decline, we may see wider adoption. However, this shift will require breakthroughs in quantum error correction, hardware design, and energy efficiency.
Conclusion
Quantum computers offer unparalleled potential but remain in a nascent stage of development. While their advantages over classical systems are significant, the technology's limitationshigh costs, error rates, and specialized use cases -mean that quantum computing has yet to realize its full potential. Continued research and development will determine whether quantum computers can transition from experimental devices to indispensable tools across all sectors.
Strands
Inspired by the NYC strands game and the classic wordsearch, you must find all the words as well as the “spangram” which is the theme of the game using the clue below. Enjoy!
Connections
Inspired by the NYC connections game, you must find the links between words and place them in four categories (consisting of four different words). These connections can range from being auditory to contextual. We hope you enjoy the scientific connections that we have created!
You can write the four categories in the boxes below
The answers to the strands and connections will be released in the next issue…
Answers to previous issue…
Units of temperature: Celsius, Kelvin, Fahrenheit and Rankine
Computer scientists: Babbage, McCarthy, Neuman and Berners-Lee
Radiation: Curie, Sievert, Becquerel and Röntgen
Awards: Nobel, Fields, Turing and Copley