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2 results on '"Stigenberg, Mathilda"'

1. Predicting tumour growth-driving interactions from transcriptomic data using machine learning

Author

Stigenberg, Mathilda and Stigenberg, Mathilda

Abstract

The mortality rate is high for cancer patients and treatments are only efficient in a fraction of patients. To be able to cure more patients, new treatments need to be invented. Immunotherapy activates the immune system to fight against cancer and one treatment targets immune checkpoints. If more targets are found, more patients can be treated successfully. In this project, interactions between immune and cancer cells that drive tumour growth were investigated in an attempt to find new potential targets. This was achieved by creating a machine learning model that finds genes expressed in cells involved in tumour-driving interactions. Single-cell RNA sequencing and spatial transcriptomic data from breast cancer patients were utilised as well as single-cell RNA sequencing data from healthy patients. The tumour rate was based on the cumulative expression of G2/M genes. The G2/M related genes were excluded from the analysis since these were assumed to be cell cycle genes. The machine learning model was based on a supervised variational autoencoder architecture. By using this kind of architecture, it was possible to compress the input into a low dimensional space of genes, called a latent space, which was able to explain the tumour rate. Optuna hyperparameter optimizer framework was utilised to find the best combination of hyperparameters for the model. The model had a R2 score of 0.93, which indicated that the latent space was able to explain the growth rate 93% accurately. The latent space consisted of 20 variables. To find out which genes that were in this latent space, the correlation between each latent variable and each gene was calculated. The genes that were positively correlated or negatively correlated were assumed to be in the latent space and therefore involved in explaining tumour growth. Furthermore, the correlation between each latent variable and the growth rate was calculated. The up- and downregulated genes in each latent variable were kept and used for

Published
2023

2. To monitor the microbial biodiversity in soil within Uppsala

Author

Godow Bratt, Tora, Stigenberg, Mathilda, Elenborg, Andreas, Ågren, Sarah, and Medhage, Andreas

Subjects
Isothermal amplification, microorganism, Mikrobiologi, Environmental Biotechnology, citizen science, recombinase polymerase amplification, Miljöbioteknik, microbes, Microbiology, RPA, soil
Abstract

This is an exploration of the potential for a citizen science project, with the goal to get the general public involved in microbial soil biodiversity around Uppsala, Sweden. Biodiversity serves an important role in how an ecosystem performs and functions. A large part of Earth's biodiversity exists below ground in soil, where microorganisms interact with plants. It would be beneficial to analyse the abundance and spread of some microorganisms in order to gain a better understanding of soil biodiversity. We suggest that one species family to study could be Phytophthora. Phytophthora is a genus of oomycetes that often are pathogenic, causing disease in various trees and other plants. It is unknown exactly how widespread the genus is today, making it extra interesting for the proposed study. For the general public to be able to do this a device needs to be developed that is easy to use and preferably could be used directly in the field. An isothermal amplification method is suitable for identifying the microorganism under these conditions. Many isothermal amplification methods are expensive, perhaps too expensive for a citizen science study, but have great potential for easy field testing. We propose a device utilizing RPA and lateral flow strips. RPA - Recombinase Polymerase Amplification is a method for amplification that might be suitable since it is simple, sensitive, and has a short run time. It is however expensive, which is an issue, but isothermal amplifications are expensive across the board. Lateral flow strips can be used to visualize the results. They utilize antibodies to detect the previously amplified amplicons, and give a positive or negative test answer that would be understandable to even untrained study participants. One of the biggest obstacles identified in this project concerns amplifying DNA from a soil sample, because an extraction step is necessary. The methods we have identified for extraction are not performable in the field, since they require centrifugation. In the proposition for a device a possible work-around for this is proposed, but since it has yet to be tested it is not yet known whether it will work or not.

Published
2021

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