Tag Archives: UCL

Shannon Edwards – UCL Genetics Institute

“I am grateful to have gained so much in such a short space of time.”

During my placement at UCL, I was fortunate enough to gain an insight into Computational Biology under the supervision of Jack Humphrey. Having been informed of the functions FUS and TDP-43, I soon learnt that as with many proteins, the change in expression of the genes that code for such RNA- and DNA-binding proteins, respectively, can be argued to characterise many neurodegenerative diseases. In this case, the diseases looked at were ALS and Frontotemporal Dementia. The efficiency with which the analysis of the regulation of genes took place using programming software such as R Studio was apparent from the beginning and this became the main method to manipulate sample data.

Shannon Edwards 1As a practice for writing code, I made use of a publicly available differential expression dataset that compared the gene expression between mice brains that were treated with two antisense oligonucleotides, (ASO’s). One of the ASO’s was a random sequence and the other was specific to the FUS transcript. I found the process for plotting the resultant graphs particularly complex, considering that I am a part of a generation that is said to be ‘tech-savvy’. I believe that practice through an online course teaching coding, as well as creating sample plots whilst at UCL is enough to show the depth of understanding required to make the most out of one week, let alone a PhD or career. Nevertheless, after altering the R script several times I was able to comprehend that the greater the log10 (Base Mean) value, the closer the Log2FoldChange value was to zero, indicating a smaller quantity change, although the areas of clustering can suggest similarities between sub-sections of data. The resulting plot is shown below.

Shannon Edwards 2Arguably the most complicated task was set towards the end of the week. The proposition was that mutations in the TDP-43 gene would impact the RNA-binding ability of the TDP-43 protein, and I used pre-existing data to analyse whether it would act as a knockdown. I found that the hypothesis was difficult to support based on this dataset, and as expected in science; more data would need to be analysed. Using skills within R such as vector arithmetic helped to reach this judgement as it gives rise to additional data such as log10(gene length) which was calculated from given data to produce a plot with fewer points. Also; the ‘for()’ loop function loaded the data into one plot using the same commands, but did so in such a way that each dataset was still uniquely identified with the assistance of different colours, as you can see in the picture above.

My placement allowed me to witness how science calls for patience and the ability to ask the right questions to manipulate and evaluate the data that could add another piece to the puzzle. With thanks to Jack for giving up his time, everyone at UCL for their hospitality (and smoothies) and In2scienceUK for providing me with the placement, I am grateful to have gained so much in such a short space of time.


Monique’s placement in Tissue Engineering

Monique Nahr undertook a placement in Tissue Engineering under the supervision of Azi Rezaei, in the group of Dr Gavin Jell at UCL’s Royal Free Hospital.

I gained an insight into tissue engineering, from scaffolding cells in collagen to growing and culturing cells, 3d printing and nanotechnology. I also experienced what working towards a PhD and independent research would be like, and I loved it. My favourite bit was tensile testing the shell of a breast implant to see how strong it was. I would definitely recommend in2scienceUK. Not only is it fun but it gives you an insight to the real world of science and most importantly allows you to get involved.

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Glial Cell Research by Farzana Miah

Farzana learnt about glial cell research during her two-week placement under the supervision of Angshu Angbohang, in the group of Professor Astrid Limb.

During my two weeks at the UCL Institute of Ophthalmology I’ve learnt about the human glial cell, a type of stem cell, that is able to regenerate into retinal neurons.  This is important because the retinal neurons are photoreceptors at the back of the human retina which enables you to sense light and therefore allows you to see.

Scientists have discovered that the Muller glial cells in zebrafish have the ability to regenerate the retina neurons multiple times once they are damaged. This ultimately intrigues us to find out why and how they are able to do that and if one day a human may be able to do the same.These are the steps that I have taken during my placement, they all link together therefore it was important to do each step carefully as any mistake could of had an effect onto the final result:

Farzana 1

Cell culture

Firstly I saw two Petri dishes that had cells inside of them, however one dish was confluent and the other dish had cells that were sparsely separated. We used the confluent dish which had to be vacuumed as there was solution around the cells, this gave us the cells we needed and nothing else. Furthermore, the cells were attached to the dish, due to this we had to use a solution called triple E as this helped detach the cells from the surface of the Petri dish. We then placed the dish into an incubator at 37 degrees Celsius which was followed by centrifuging the cells. Five minutes later the cells were at the bottom of the dish, we then removed the triple E by aspirating it and adding 5ml of medium (which provide nutrients to the cell). Finally we stained the cells using methyl blue.

RNA Extraction

We then extracted RNA from the cells we cultured. I removed medium first and then added the triple E solution as this helps detach the cells from the dish. We then centrifuged the cells which left a cell plate present (a white disk at the bottom). We then removed the triple E solution to give us the cells that we needed to extract the RNA.

We added lysis buffer (one micro litre) and beta-mercaptoethanol (a corrosive alcohol), we mixed them together and added 350 micro litres into control and treatment tubes. After that we used a syringe to help move the solution up and down, to help the breakdown with the lysis buffer to go faster. I centrifuged the cells again and then transfered the solution into an eppendorf tube.

Reverse Transcription

Reverse transcription is when the RNA turns into cDNA by using mRNA, primers, DTT and a reverse transcriptase enzyme (such as “Superscript”)


The polymerase chain reaction (PCR) is to help the cDNA to multiply rapidly and the forward and reverse primers bind to each strand. We needed cDNA, primer, water and Gotaq (a green solution that contained everything). We use cDNA because we know how long it lasts, however a normal DNA can affect the results.

Farzana 2The primers use to test for photoreceptor are:

1) NR2E3

2) Recoverin


4) Betactin

Farzana 3
Gel Electrophoresis

This was done because we needed space for the reverse transcription solution (mRNA, primer, DTT and superscript). To do this we need agarose gel, solution buffer and red gel (something that allows you to see the band).

Farzana 4


The treated human Muller glial stem cells photoreceptors are more expressed than the controlled ones.
The treated human Muller glial stem cells photoreceptors are more expressed than the controlled ones.

Farzana 6

The Wonders of FTCD

by Britney Afram

My supervisor (Heather Payne) works within UCL’s Institute of Cognitive Neuroscience in the Visual Communication Group, who conduct research looking at how the brain processes language in people who are born profoundly deaf. The language they use is very variable such as British Sign Language and spoken language. Looking at language processing in people born deaf gives a unique perspective because they can compare BSL and spoken language and contrast the networks shared to know what brain areas are interested in language whether it is visual or auditory.

So what is Cognitive Neuroscience?

Cognitive Neuroscience is the study of the neural basis of behavior. It aims to explain cognitive processes in terms of brain-based mechanisms- ‘what part of the brain does what’!

What are some of the methods used by the Visual Communication Group?

As they are not able to observe brain processes, VCG use a Near infrared spectroscopy to examine neural basis of signed and spoken language processing. Eye tracking allows to study how infants attend to visual language input early in life. The Visual Communication Group also use functional transcranial Doppler sonography (fTCD) and functional magnetic resonance imaging (fMRI).

Why Functional Transcranial Doppler sonography (fTCD)?

Some deaf children may even have a cochlear implant which is unsuitable for a MRI scan. Functional Transcranial Doppler sonography (fTCD) assesses relative blood flow to the left and right sides of the brain.  A benefit to this method is its portability allowing it to be used in different environments.

The set-up of the equipment requires attention to the various wires and ports. The fTCD uses two laptops: one to observe the results from the Doppler box and another to show the stimulus to the participant. Additionally there needs to be a connection between both laptops by the parallel port replicator which allows signals to be sent much quicker and several wires are connected to the laptops and Doppler box.

What do we do in a testing session with children born deaf?

During the actual procedure the ultrasound probes are attached with a conductive gel on the left and right sides of the head, just in front of the ears approximately perpendicular to the direction of blood flow. This enables it to monitor the rate of blood flow in the middle cerebral artery to each brain hemisphere whilst the participant performs a description of a 12 seconds long silent moving penguin animation. Software called QL allows us to visualize the signal simultaneously letting us know we are in the right place for the artery and showing the speed of blood.

How were the results analyzed?

The results are then put into a toolbox for Matlab (a programming language) which extracts the average Doppler signal from the left and right hemispheres over a period of interest in which the task was performed. The graph produced shows the difference in left and right activations to extract a laterality index. Positive values indicate left lateralization and  negative values indicate right lateralization. In most people language is processed predominantly by the left hemisphere of the brain.

My favorite moment of my placement was getting to try the technique out:

Britney spent a week in UCL’s Institute of Cognitive Neuroscience, in the group of Dr Mairead McSweeney, and under the supervision of Heather Payne.

Bees seem to be forgetting how to make the honey

There has been constant debate over the past decade revolving around the cause or many causes for the decline in the number of bumblebees situated in the British countryside.  Many scientists believe this decrease is caused by ubiquitous contrails which contain water vapour, carbon dioxide, oxides of sulphur and nitrogen along with metal particles such as aluminium. These nanoparticles are released from the jet’s exhaust at such a high altitude with lower vapour pressure that the water vapour condenses and may freeze (deposition) forming tiny ice crystals. This mixture of crystals and particles forms a sort of cloud. Scientists therefore assume that the nanoparticles of  aluminium found in these artificial clouds or contrails is inhaled directly via the olfactory nerves by animals in this case or insects as the particles begin to disperse and descend due to gravity and eventually absorbed by the plants.

This may be a very valid theory, however recently, there has been dispute as to whether the industrial discharge containing aluminium is also implicating the aetiology of sporadic Alzheimer’s Disease (AD) and affecting the mental functioning of bumblebees. The bumblebees fail to differentiate between normal nectar and nectar that contains aluminium.

Scientists at Keele  and Sussex University found that there was a large amount of aluminium in the pupae collected, between 13 and 200 ppm whilst a minimum of chronic exposure of 3ppm would be harmful to the human brain. At high levels in the brain, aluminium acts as a neurotoxin and thus  causing a myriad of problems due to it inhibiting or altering the chemical impulses between neurones (delivering messages to the brain and back).  Excess aluminium promotes formation and accumulation of insoluble A beta and hyperphosphorylated tau. Insoluble amyloid beta protein (A beta) leading to defective phosphorylation-dephosphorylation reactions and reduced glucose utilization, all contributing to the appearance of  neurological disorders such as AD.

Since this is the destructive effect on humans with such a little dosage, there must be some sort of correlation with animals and insects such as a bumblebee that had x70 as much aluminium in its system.

Scientists believe that this detrimental quantity of aluminium would cause cognitive decline, the theory being simultaneous to how it affects the human brain causing Alzheimer’s Disease.  The figures farming the bewildering and intriguing spectre suggest  that aluminium-induced cognitive dysfunction may be catalysing the decline in the bumblebee population. Injections of aluminium in animals produce behavioural, neuropathological and neurochemical changes that partially model AD.

Sara Belazregue spent two weeks in Professor Maria Fitzgerald’s group in UCL’s Department of Neuroscience, Physiology & Pharmacology, supervised by Dr Madeleine Verriotis.

X-Ray and Laser Imaging using iterative methods by Osman Omar

On my in2scienceUK Placement, I studied ptychography and worked with laser imaging with a PhD student, Stefanos Chalkidis. During my placement, I scanned various different things such as a piece of mica, glass, a sample from a colleague and a wing from a dead fly.

First, we set up the sample by attaching it to a glass substrate using tape and then mounted it to the sample stage which was in a blackout box along with the camera used to capture the image, a diffuser and the laser itself. Next, we received a live feed of the sample on a computer from which we then took various different types of scans, such as ROI scan, which takes images of the sample in a circular pattern within a region of interest, a flat scan which takes images of the background alone without any sample present and a dark scan which takes images with the laser turned off.

Next, we used the data from the scans and by running various different python scripts, we formed reconstructions of our scanned object which we then further analysed. The reconstructions were performed by using two algorithms in succession for which we could choose how many iterations we wanted to run. We used two different amounts, 500 of each algorithm for one reconstruction and 2000 for another, and compared the differences. We also changed the position of the diffuser to see how that would affect our results and what changes we would get.

Here is one set of our results: The insect wing; diffuser at 250mm, original position, closest to laser.


The left image shows the transmission image of the object, whilst the middle image is the phase change of the object and the right image depicts the phase change of the illumination. We also moved the diffuser to 240mm and here are our results:


Here are our set of results when analysing the mica:


I also went to the Diamond Light Source, located in Harwell, which is a synchrotron. Electrons are sped up and accelerated there in a circular pattern to near light speed, from which then X-rays and other lights are emitted. These beams are then directed off into laboratories or beamlines so they can be used for experiments and research such as new medicines or cutting-edge technology. I was given a tour of the building and met scientists who worked with my supervisor in his field of research, which is near-field ptychography.