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Is blood flow the key to the early detection and treatment of Alzheimer’s Disease?

Project Description

This a fully funded 3.5 year PhD studentship with 6 months placement in a leading research laboratory in the USA.

This studentship represents an outstanding opportunity for an enthusiastic and highly motivated individual interested in undertaking research into how neurovascular function alters during progression of Alzheimer’s disease.
The studentship will last 3.5 years (to include a 6 month placement in the lab of Dr Alberto Vazquez, University of Pittsburgh, USA). Funding is included for tuition fees (at Home/EU level), a stipend of £15,500 per year and an allowance for research consumables, conference attendance and research training (~£15,000 per year).

Alzheimer’s Disease (AD) is a growing health concern with 850,000 people living with dementia in the UK alone, expected to rise to over 1 million by 2025. There is currently no effective treatment for AD. Most of our recent insights into the causes of AD are linked to the discovery of increased amounts of Beta-Amyloid plaques associated with significant neuronal loss. Despite the large investment in both clinical and pre-clinical research resources focussed on the Beta-Amyloid hypothesis, no effective preventative or remedial treatment has so far been found. Consequently, alternative theories regarding the onset and development of AD have been proposed. A notable rival hypothesis is the Neurovascular Degeneration Hypothesis, first proposed by Zlokovic. This suggests that a functional deficit within cells of the neurovascular unit would deprive neurons of adequate oxygen and glucose, which could either be the initial trigger of AD, or significantly add to the disease burden. If correct, this hypothesis offers potential for development of new therapeutic targets and/or early imaging biomarkers for AD.
We have previously developed a stable preclinical preparation suitable for multimodal longitudinal imaging. Emerging technologies will allow us, for the first time, to image from single cell to whole brain over the course of AD. During the PhD, you will receive training in several experimental techniques including: multiphoton microscopy (enabling cellular resolution imaging), optical imaging spectroscopy (single blood vessel resolution), BOLD fMRI (whole brain resolution imaging), electrophysiology and optogenetics. Furthermore you will undertake a 6 month placement with Dr Alberto Vazquez at the University of Pittsburgh, using GCAMP6f technology to non-invasively image neuronal activity in the same mouse model of AD. Combining these techniques, you will investigate the timecourse of, and mechanisms underlying, changes in neurovascular function in a pre-clinical mouse model of AD (using both an anaesthetized and awake preparation). These data will be used to both identify early blood-based biomarkers of AD and develop potential blood-based treatments for AD.

This PhD studentship is part of the Battelle-Jeff Wadsworth Scholarship Programme based at the University of Sheffield; funded by a generous donation to the University by the Battelle Memorial Institute based in the USA. The ambition for the scholarship programme is to provide an outstanding educational experience for early-career researchers by fostering a global community of scholarship to support the exchange of new ideas and the importance of working with others to solve problems.

Funding Notes

This project is competition funded. There is one vacancy on this project full funded for 3.5 years with 6 months placement in USA.

Requirements: We ask for a minimum of a first class or high upper second-class undergraduate honours degree in neuroscience or a related discipline or a distinction or high merit at Masters level in a suitable MSc.

All applications are made online via View Website


To find out more about the research group and supervisors, please see:

Related Subjects

How good is research at University of Sheffield in Psychology, Psychiatry and Neuroscience?

FTE Category A staff submitted: 34.45

Research output data provided by the Research Excellence Framework (REF)

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