TSP conference: papers and posters

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. 

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.

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

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 UNSW 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 from literature review. It is a technique that can be potentially used in therapeutic medicine to treat patients who are incurable or suffer from severe side effects of current treatments. Cellular reprogramming can be divided into two categories: classic cellular reprogramming and transdifferentiation. Classic cellular reprogramming has already been demonstrated to generate functional red blood cells from human induced pluripotent stem cells. On the other hand, functional neural stem or progenitor cells can be produced from human fibroblasts bypassing the induced pluripotent stem cell state through the process of transdifferentiation. These two approaches have been the focus of my poster with the hope that a solution will be found in the immediate future for those currently incurable.

Student: Marko Beaocanin
Supervisor:  Professor Rajib Rahman

I had the opportunity to work with Professor Rajib Rahman on two primary aims: to develop an introductory understanding on the literature and theory of electron transfer in silicon spin-based quantum dots; and to perform numerical simulations on the Gadi supercomputer using the nemo3d simulator to verify this existing theory. My simulation process involved incrementally changing the vertically-applied magnetic and electric field parameters in the nemo3d simulator, and running 19 complete simulations in total. I produced results analogous to the Zeeman and Stark effects, which describe how the quantised energy levels of a quantum dot split apart in the presence of externally-applied magnetic and electric fields.  

Student: Catherine Cheng 
Supervisor:  Dr Kim-Vy Tran 

Cosmological simulations like the IllustrisTNG simulations have revolutionised the way we study galaxies, opening up many possibilities not previously available through observational data. This project focusses on exploring whether the IllustrisTNG simulations are able to corroborate findings from observational surveys - in particular whether or not we are able to detect galaxies with unusually extended gas regions such as Magpi179104. From our results it was determined that no objects within our stellar mass range had unusually large regions of gas between the stellar half mass radius and twice the stellar half mass radius for their given stellar size or the baryonic mass within their stellar disk. This indicates that we have not been able to yet detect the observed objects via simulation.

Student: Jenny Wang,
Research Group: UNSW NEWTS Lab 
Supervisor: Dr. Ben Montet 

TESS (Transiting Exoplanet Survey Satellite) has discovered over 2000 planetary candidates since its launch in 2018. However, since TESS only observes each sector of the sky for 27 days, most planetary candidates discovered so far have very short periods (less than 14 days). I have developed a pipeline that searches for single transit events among the existing TESS Objects of Interest (TOIs) in order to find longer-period companions to existing planetary candidates. I am currently running this pipeline on all known TOIs. 

Student: Michelle Ding 
Supervisor: Associate Professor Dennis Stello 

Astroseismology, the composite of studying oscillations and stars. Given the opportunity to use python to program a system that will differentiate between “good” and “bad” data, the task was an interesting challenge to take upon. Provided with data from the Kepler Telescope, the idea of the program is to eliminate “red” noise from the data and then determine whether peaks on the generated graph aligns with previous data. If the alignment is correct, then the data is “claimed” to be “reliable”. Researchers can therefore use the reliable data to determine stellar features such as structure and evolution.

Student: Pavitraa Hathi 
Supervisor: Assistant Professor Sarah Martell  

Globular clusters are collections of stars held together tightly by gravity. Studies have shown that all globular clusters (GCs) demonstrate anticorrelations in certain pairs of elemental abundances, however why these anticorrelations occur is still unknown. In my project I looked previous papers that have studied GCs in the Large Magellanic Cloud (LMC) that are approximately 2-8 Gyr (much younger than the heavily studied >10 Gyr GCs in the Milky Way). I compared the LMC data with data for GCs in the Milky Way to find the same anticorrelations in both sets of GCs. This means that the mechanism which causes anticorrelations in GCs operated more recently than previously thought, which could open up a new avenue for research into the formation of GCs.

Student: Nikki Huang 
Research Group: Gatt Resilience Group, NeuRA 
Supervisor: Dr. Justine Gatt  

The absence of mental illness is not equivalent to mental health or wellbeing. It is therefore important to develop valid and reliable measures of wellbeing which can identify individuals at risk of poor coping and inform strategies to improve resilience. The COMPAS-W is a 26-item self-report measure of wellbeing developed by the Gatt Resilience Group with six constituent subcomponents: Composure, Own-worth, Mastery, Positivity, Achievement and Satisfaction. As the scale was developed using data from a cohort of 1669 healthy adult twins (18-61 years), researchers were also able to evaluate the relative contributions of genetic and environmental factors to wellbeing. It was found that genes play a moderate role in determining wellbeing (heritability h² = 48%), although the Composure and Achievement subcomponents showed relatively higher sensitivity to unique environmental influences. COMPAS-W is a validated measure of wellbeing which can be used to quantify mental health and inform future strategies in health promotion and clinical treatment. 

Name: Felix Lempriere 
Supervisor: Dr Laura McKemmish

Computational Quantum Chemistry provides a bridge between experiment and theory in Chemistry allowing predictions and corroboration of properties for molecules and reactions of interest. The accuracy and usefulness of such models is limited by the method and choice of “basis set” used, which is in necessitated by the available computational time. In this project we benchmarked several commonly used moderate sized basis-sets against a large chemical database to determine which were the most cost-effective and accurate, to help guide computational chemists designing their calculations. 

Name: Rosanna Xu
Supervisor:

On the 14th of August 2019, researchers detected one of the most mysterious gravitational waves in history (called the ‘GW190814 event’). The gravitational wave corresponded to the collision between two astronomical bodies of 23 and 2.6 solar masses. The larger is easily classified as a black hole, but the smaller body falls into the ‘mass gap’ between neutron stars and black holes, meaning that it is either the heaviest neutron ever found, lightest black hole ever found, or an entirely new astronomical body altogether. In my research, I have used the knowledge that colliding black holes radiate more gravitational energy than neutron stars. I have calculated the constant of proportion between radiated energy and original kinetic energy for the collision between (a) black hole – black hole, (b) neutron star – neutron star collisions, and then used this information to calculate that constant for (c) black hole – neutron star collisions. Finally, I compared these constants with the GW190814 event and concluded that the GW190814 event is a collision between two black holes.