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Precision Medicine DTP - Blood flow and solute transport in human placental vascular networks: an in-silico approach to characterising pregnancy pathologies


Project Description

Background

The human placenta performs diverse functions later taken on by several different organs. In particular, it mediates the exchange of vital solutes, including respiratory gases and nutrients, between the mother and the developing fetus. The complex heterogeneous structure of the placenta is adapted to perform these various functions. However, despite its availability for ex-vivo perfusion experiments just after birth and the importance of placental dysfunction in conditions such as fetal growth restriction, the link between placental structure and function in health and disease remains poorly understood [1].

Recent advances in three-dimensional (3D) imaging have revealed aspects of placental structure in intricate detail [1, 2]. Fetal blood flows from the umbilical cord through a complex network of vessels that are confined within multiple villous trees; the trees sit in chambers that are perfused with maternal blood. Much of the solute exchange between maternal and fetal blood takes place across the thin-walled peripheral branches of the trees (terminal villi) which contain the smallest feto-placental capillaries. Quantitative measurements have demonstrated structural differences between healthy and pathological placentas [3], but physical explanations for the observed symptoms of diseases such as pre-eclampsia and diabetes have so far been confined mainly to studies on two-dimensional histological data [2]. Little is known about how the elaborate and irregular 3D organisation of capillaries within terminal villi, the primary functional exchange units of the feto-placental circulation, contributes to solute exchange in health and disease.

The research will employ a state-of-the-art 3D imaging catalogue of placental microstructure to derive theoretical models of solute transport. The output of 3D confocal microscopy and X-ray micro-computed tomography covers a wide range of spatial scales, from 1 μm to 1 cm, which will aid in the design of computational models. The structural datasets will be complemented by the linked anonymised clinical characteristics from the National Pregnancy Biobank (St Mary’s Hospital, Manchester).

Aims

In this study, we will combine image analysis and computer simulations of blood flow as a suspension of deformable particles [4] to examine the dependence of solute transport on the geometrical arrangement of capillaries within terminal villi of the placenta. The properties of these functional exchange units will be quantified and encapsulated in a general theory of feto-placental transport that links the complex 3D structure of fetal microvascular networks to their solute exchange capacity. Particular emphasis will be placed in understanding how these mechanisms are compromised in pathological placentas taking advantage of recorded clinical endpoints. Future studies will investigate how this theory can complement current imaging modalities used for the risk-assessment and diagnosis of pregnancy complications in vivo.

Training Outcomes

The student will receive state-of-the-art training in the core disciplines of image analysis, computational modelling, and physiology while gaining expert knowledge in the context of placental research. This highly interdisciplinary approach is well aligned with the “T-shaped researcher” training requirements identified as key in the DTP in Precision Medicine. The student will develop the essential soft and domain-specific skills necessary to design and implement novel quantitative and computational methods that could solve challenging problems across the entire spectrum of cardiovascular medicine both in academic and industrial settings.

This MRC programme is joint between the Universities of Edinburgh and Glasgow. You will be registered at the host institution of the primary supervisor detailed in your project selection.

All applications should be made via the University of Edinburgh, irrespective of project location. For those applying to a University of Glasgow project, your application along with any supporting documents will be shared with University of Glasgow.

http://www.ed.ac.uk/studying/postgraduate/degrees/index.php?r=site/view&id=919

Please note, you must apply to one of the projects and you must contact the primary supervisor prior to making your application. Additional information on the application process is available from the link above.

For more information about Precision Medicine visit:
http://www.ed.ac.uk/usher/precision-medicine

Funding Notes

Start: September 2020

Qualifications criteria: Applicants applying for a MRC DTP in Precision Medicine studentship must have obtained, or will soon obtain, a first or upper-second class UK honours degree or equivalent non-UK qualification, in an appropriate science/technology area.
Residence criteria: The MRC DTP in Precision Medicine grant provides tuition fees and stipend of at least £15,009 (RCUK rate 2019/20) for UK and EU nationals that meet all required eligibility criteria.

Full eligibility details are available: View Website

Enquiries regarding programme:

References

[1] Erlich A, et al. (2019) Physical and geometric determinants of transport in fetoplacental microvascular networks. Sci Adv 5:eaav6326.

[2] Jensen OE & Chernyavsky IL (2019) Blood flow and transport in the human placenta. Ann Rev Fluid Mech 51:25.

[3] Junaid TO, et al. (2017) Whole organ vascular casting and micro-CT examination of the human placental vascular tree reveals novel alterations associated with pregnancy disease. Sci Rep 7:4144.

[4] Bernabeu MO, et al. (2019) Abnormal morphology biases haematocrit distribution in tumour vasculature and contributes to heterogeneity in tissue oxygenation. preprint: https://www.biorxiv.org/content/10.1101/640060v1

How good is research at University of Edinburgh in General Engineering?
(joint submission with Heriot-Watt University)

FTE Category A staff submitted: 91.80

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

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