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Name: Thomas Nguyen
Supervisor: Sarah Brough

Name: Hannah Wah Day
Supervisors:��Martina Lessio and Fabio Colasuonno

Name:��Kerri Belinda Wainstein
Supervisor:��Marc Wilkins

Name:��Yashwanth Madan
Supervisor:��Sarah Martell

Lithium is a rare element, constituting 1% of the universe, and is known for its susceptibility to destruction through nuclear fusion in stars. Subsequently, astronomers expect that the lithium content within a star will gradually diminish over time due to the fusion and convection that occur throughout its lifespan. An intriguing puzzle emerges as several thousand red giant stars have been observed to be rich in lithium content. This defies our expectations as the red giant phase is late in a star's life cycle, by which time most of the initial lithium abundance should have been destroyed. Studies of the other properties of lithium-rich red giants aim to pinpoint what is special about them, and what unusual processes they may have undergone. This project investigates the recent observation that ~55% of lithium rich stars also exhibit strong absorption in the helium absorption line at 10830 Å, using optical and near-infrared spectroscopy for a set of 49 red giants obtained with the Very Large Telescope in Chile. Within this data set we do not find any correlation between high lithium abundance and high helium absorption, with 2 stars having high helium absorption and none of those stars having high lithium abundance. Future work in this project will include simulating evolution of lithium abundance in a population of red giants to understand which processes are effective at creating lithium richness.

Name: Joseph Evans
Supervisor:��Michael Janitz

Circular RNAs (circRNAs) are small noncoding molecules that are increasingly believed to play an important role in gene expression. They consist of a single strand of RNA, covalently looped to itself to form a circular molecule. As a relatively new focus in the literature, there are limited tools and softwares available for analysing circRNAs. In particular, the presence of microRNA recognition elements (MREs) and RNA-binding protein (RBP) sites, as well as the visualisation of the molecule, are the key features that could be considered using bioinformatics. Here, we investigated two bioinformatics softwares for circRNA analysis: CircView and CRAFT. We found that CircView was capable of basic visualisation of circRNAs, but was unable to provide any deeper MRE or RBP site analysis. CRAFT provided a much more promising bioinformatics platform for functional predictions involving MREs and RBP sites. 

Name:��Auguste McNally
Supervisor:��Martina Stenzel

Lithium metal anodes are ideal for lithium-ion battery use due to their high energy density. The use of zero excess lithium in batteries (i.e. anode-free batteries) offers the remarkable energy density of the lithium metal anode while minimising the risk and reducing cost by forming the anode in situ on the current collector. However, these anode free batteries suffer from poor cyclability due to formation of unreactive lithium from the plating and stripping process. This project investigated the use of lab made aluminium-lithium alloy as a cathode collector for anode free batteries to increase their cyclability and capacity. Current results show that the lithium, at low current rates, can be sufficiently stripped from the alloy and thus potentially act as an extra lithium source for anode free batteries.��

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Names:��Willow Heller and Alyssa Lim
Supervisor:��Gavan McNally

Fibroplast growth factor (FGF21) is a liver-derived hormone with pharmaceutical applications in diabetes treatment. Further, recent research has nominated a potential circuit-specific function in suppressing alcohol consumption in both humans and rodents. Prior research has not examined the effect of this compound when animals are given a choice between alcohol and an alternative. Furthermore, the effect of this drug following escalated alcohol consumption has yet to be observed. The present study examined the effect of different dosages of an FGF21 analogue PF-05231023 on home-cage intermittent ethanol consumption in mice exhibiting pre-existing escalated alcohol consumption, freely choosing between water and ethanol. We observed that a 3% dosage of PF-05231023 but not a 1% or 10% dosage significantly reduced ethanol preference and consumption in the first day following injections. We conclude that PF-05231023 has some effect in reducing alcohol consumption in this model of alcohol use disorder, however its effects are less clear over extended periods.

Name:��Xiangjun Tan
Supervisor:��Susan Coppersmith

It is well known that quantum algorithms can simulate the many-body problem. Our work specifically focuses on simulating collective oscillations, which can contribute non-linearly to the evolution of flavours. We simulate the time evolution of a model with three neutrino flavours for one neutrino and collective neutrino oscillations using U ∈ SU(4) representation on a noisy quantum processor. We explore a generalization of the Trotter-Suzuki approximation for time-dependent Hamiltonian dynamics. Additionally, we suppress errors using strategies like the Trotter and Cartan decomposition to reduce the gate cost. A noise model for the corresponding quantum processor is also created to perform Zero-Noise Extrapolation (ZNE) and Probabilistic Error Cancellation (PEC) error mitigation on NISQ devices.

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Name: Angela Lin
Supervisor:��Maitreyee Roy

Epiretinal membrane (ERM), a prevalent eye condition primarily affecting the elderly, is characterised by fibrocellular tissue on the retina's inner surface. While Optical Coherence Tomography (OCT) has long served as the conventional method for ERM detection, the assessment process remains a formidable and time-consuming challenge for ophthalmologists. Recent advancements in the medical field have witnessed a transformative integration of deep learning-based artificial intelligence (AI) in the diagnosis of ERM. This innovative approach facilitates detecting and staging common ocular disorders, such as ERM, which possess distinctive features. This study delves into the research papers that have explored the capabilities of various AI models in ERM determination and conducted comparative analyses of their performance. The findings across these studies are remarkable, underscoring the AI models' superior performance metrics, including accuracy, specificity, and sensitivity in ERM diagnosis when compared to traditional ophthalmological assessments. In essence, the research unequivocally demonstrates that AI models exhibit a significantly enhanced capability to detect and diagnose ERM, thus presenting an advancement in the field of ophthalmology.

Name: Peta Gilbert
Supervisor: Grace Lindner and��Dr Michael Janitz

Name: Karina Guo
Supervisors: Jason Bragg and Will Cornwell

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Name:��Carmen Ossimitz
Supervisors:��Jai Tree, Thomas Zammit and Brandon Sy

Name: Vanessa Prajitno��
Supervisor: Dr. Blake Cochran & Dr. Kerry-Anne Rye

Type 1 Diabetes (T1D) is a metabolic autoimmune disease caused by pancreatic β-cell dysfunction as a result of immune system disorders. Viral infections such as SARS-CoV-2 may induce activation of inflammatory chemokines which precipitates to chronic inflammation that may aggravate β-cell dysfunction as the patient’s immune system starts to produce auto-antibodies against virally infected β-cells. Reduced β-cell functions cause lower expression of insulin, resulting in persistent hyperglycaemia. However, studies have found that β-cell dysfunction can be mitigated by HDL apolipoprotein mimetic peptides such as D6PV. We demonstrated this by using NOD mice to analyse D6PV treatment efficacy, measuring blood glucose concentration and characterizing the severity of insulinitis in pancreatic islet cells. Our results found a significant reduction of blood glucose levels and less inflammatory infiltrates present in pancreatic islets of D6PV-treated mice, thus indicating that there is great potential in the usage of D6PV to treat patients with T1D.

Name: Hugo Sebesta��
Supervisor: Prof. Rajib Rahman and Dr Edyta Osika

When a particle is constrained in a number of degrees of freedom, it becomes best described by quantum physics. Within this theory, a sufficiently small particle is best described by a wave function, the evolution of which is determined with Schrodinger’s equation. The quantum dot is a 1D approximation of an electron constrained in all three dimensions, such as at a phosphorus impurity in a silicon lattice. Such a quantum system can be described as “two-level”, making it relevant in the quantum computing scene. I have performed several typical calculations relating to this system, showcasing some important quantum effects and ideas including Hamiltonians, anticrossing and detuning, time evolution with a changing electric field (loosely simulating some interaction) and resonance-driven quantum state transitions between the computational base states.

Name: Yingze (Rita) Lyu��
Supervisor: Dr. Benjamin Montet��

Star spots are areas of the reduced surface caused by magnetic fields inhibiting the process of convection or the transfer of heat due to the movement of plasma within a star. They appear as dark patches on the photosphere of stars, so it reduces the star’s overall brightness. Therefore, star spot activities may lead to erroneous planetary properties for transiting exoplanets. This may provoke false planet detections and reduce the precision of astrometry. In my research project, I have developed a python function that calculates the astrometric shift of the photometric centre of light caused by their star spots and used real-life sunspot data to test and validate the function.

Name: Felix Lempriere��
Supervisor: Scott Kable

Prior experimental investigations of the roaming photodissociation of formaldehyde (H₂CO -> CO + H₂) through Velocity Map Imaging (VMI) of the dissociating CO fragment revealed anisotropic behaviour in the velocity distributions. This anisotropic behaviour is linked to the correlations between the v, J and μ vectors which in turn describe the mechanism behind the molecular reaction. An energy-dependent change in these correlations indicates potential energy-dependent switching between reaction mechanisms. In this project we aimed to determine the energy-dependent anisotropy of previous experimental CO data, to look for patterns in isotropy to guide further experimental investigation of these vector correlations, and better understand the dissociation mechanisms behind formaldehyde roaming.

Name: Claudia Tran ��
Supervisor: Dr Maitreyee Roy ��

Keratoconus is an eye disease of children & young adults, where vision is gradually distorted through changes to the front surface of the eye. There is limited success detecting keratoconus in less equipped clinics, so the aim of the project is to develop a necessary screening test. I have been involved in the conceptual development of SPARK, and I hope to present the work so far at the conference. SPARK involves the use of a smartphone and contact lens to detect keratoconus, using MATLAB to simulate the surface of the eye. ��

I was fortunate to work with Dr Maitreyee Roy and Jack Gordon, fostering an introductory understanding of keratoconus and machine learning through literature reviews. These involved concepts such as the emissions spectra of LEDs & Köhler illumination, the application of decision trees, the Cylite Hyperparallel OCT, as well the role of the Basement Membrane in keratoconus detection.

Name: Emily Huynh��
Supervisor:

Strokes are the cause of death for many people each year and by observing blood supply to the brain, therapies for stroke prevention and treatment can be developed. In particular, the brain’s response to losing oxygen and being reoxygenated is an interesting area for further research. In this presentation, I consider the significance of a paper published earlier this year that proposed a new model to monitor the brain. Instead of rodent models, which requires complex machinery and techniques, a group of Japanese scientists experimented with Zebrafish. This species has transparent larvae and has many advantages in terms of management, monitoring and data collection.

Name: Jessica Whetters
Supervisor: Richard Vickery & Ingvars Birznieks

Electrical stimulation is a core tenant of research in sensory neurophysiology, as it allows the measurement of neural responses and the testing of specific variables on the sensation of touch. One form of electrical stimulation is Transcutaneous Electrical Stimulation (TENS) – a method which uses electrodes (often silver chloride) placed on the skin to deliver repetitive electrical pulses. Previous research demonstrates that nerve impulses tend to ‘fuse’ and plateau in response to TENS frequencies of 80-100Hz, demonstrating the inability of TENS to consistently recruit afferents at high frequency. To determine if this is the result of stimulus issues or physiology of nerve afferents, I will do a literature review of the current research – particularly focusing on how repetitive stimulation of frequencies 100Hz and upwards affects nerve recordings as SNAP recordings. I will also explain the relevance of this question to the research being conducted in Richard and Ingvars’ lab.

Name: Kaya Dahlke��
Supervisor: Dr Michael Janitz

mRNA transmits information so cells can make proteins from the information contained in DNA. Mature mRNA has a chain of Adenine bases at its end for protection called a poly A tail. I used data collected using nanopore sequencing to compare the poly A tail length distribution between healthy uterus tissue and endometrial cancer. I did this for the full distribution, as well as for only the mitochondrial mRNA. I also compared the poly A tail length at different points along the chromosome between healthy and cancerous tissue. The aim of this was to cross check that the sequenced data was correct and follows known patterns.

Name: Konstantina Harellis��
Supervisor: Dr Dominic Glover

As part of the iGEM 2021 ���������¼� PROTECC Coral team, we investigated two systems that could be used to improve the thermotolerance of the algal species Symbiodinium goreaui. Elevated ocean temperatures due to global warming result in the production of reactive oxygen species (ROS) in the algal species which get released and disrupt the coral-algae symbiotic relationship. The ROS result in the expulsion of the algae from the coral host, leading to the starvation of the host and subsequent coral bleaching. Our proposed glutathione system aims to neutralise ROS and hence prevent the expulsion of the algae. Additionally, the introduction of small heat shock proteins in the algae prevents protein aggregation and denaturation that might occur in higher temperatures. Therefore, introducing these two systems could hypothetically increase thermotolerance and prevent coral bleaching. This is what our research tested and what I will present in the TSP conference.

Name: Bethany Yee
Supervisor: Lawrence Lee

Nature has been able to optimise biochemical reactions by bringing together, or colocalising, natural catalysts called enzymes. These structures are called multi-enzyme complexes (MECs). While there has been research into designing synthetic MECs that could be tailored for specific reactions there has been little work in using base-pairing complementarity between RNA as a scaffold and RNA-binding proteins. This would allow the structures to be modular, highly controlled and be able to self-assemble in vivo. Through Molecular Dynamic Simulation, Pymol and kinetic modelling we assessed the validity of RNA scaffolds and fine-tuned a MEC design based of the biochemical pathway of the cofactor f420. Further research will involve expressing the MEC in both in vitro and in vivo experiments in order to construct and characterise the function and synthesis of the multi-enzyme complex.

Student: Konstantina Harellis

As part of the TSP Student Conference, I decided to create and present a poster about cellular reprogramming