The ISBGroup Blog

On Wednesday 18th of May, I had my final bachelor project presentation at ISB Group. I showed the results of my research on prediction of cardiovascular disease in type 2 diabetes patients, using Bayesian networks. Being a Dutch student, this concludes my time in Sweden, that started here: http://blog.isbgroup.eu/#post29 .

I can look back on a productive and instructive 4,5 months at ISB Group. The people in the group are awesome and I’m thankful for including me in all social events right from the start! The group proved to be a place that enables students to thrive at their own research projects and I can definitely recommend it to other international students.

– Gersom

Signaling to regulate FOXO1 may be the most important mechanism for
insulin to control transcription. In spite of this, little
is known about how insulin regulates FOXO1 and how
FOXO1 may contribute to insulin resistance in adipocytes, which is the
most critical cell type in the development of
insulin resistance. We report a detailed mechanistic analysis of insulin
control
of FOXO1 in human adipocytes obtained from
non-diabetic subjects and from patients with T2D.

Systems-wide
experimental and modeling analysis of insulin signaling through FOXO1 in human
adipocytes, normally and in type 2 diabetes.

We have been invited to give an oral presentation at the annual systems and synthetic biology conference BioSynSys, which this year is held in Bordeaux, June 27-29. The lecture of Gunnar Cedersund will be held on June 29, and will be on recent conceptual and methodological developments that help us to find more accurate and well-identified predictions and prediction uncertainties, especially in the case of unidentifiability of parameters and single-cell data. Full abstract and title is appended below, and the conference home page is found here.

TITLE AND ABSTRACT

Prediction
uncertainty in the case of unidentifiability and single-cell data – new
concepts and methods

Mathematical
modelling is an integral part of both systems and synthetic biology, because it
can more accurately deal with the complexity of biological data. However, to be
truly useful, the predictions of the model must be in the form of core
predictions, i.e. they must come with a correct uncertainty. In the last few
years, there have been important progress in this field, especially concerning
the important situations of unidentifiable parameters and single-cell data.
This presentation will give an overview of some of these developments.

In the case
of unidentifiable parameters, it has become clear that traditional approaches
based on sensitivity analyses, the Hessian of the cost function, and
sampling-based Monte Carlo approaches all give inaccurate results. In such
situations, one may instead use rediscovered and recently improved alternatives
based on the conditional profile of the likelihood function. Importantly, these
methods can now not only be used for assessing the uncertainty of parameter
values, but for the uncertainty of arbitrary model predictions.

For the
case of single-cell data, problems with unidentifiability are often more
severe: it is often not possible to generate enough data from a single cell,
and averages over many cells provide inaccurate results. In such cases, it is
instead better to use methods from nonlinear mixed-effects modelling (NLME),
which borrows information across the entire cell-population. Using simulated
data where the truth is known, and real data from individual yeast cells, I
will illustrate when, why, and how NLME is advantageous.

All in all,
these new and improved concepts and methods provide important tools for a sound
and correct model-based analysis of single-cell data.

In Linköping, we have a quite rare scientific conference: a conference that has been arranged for over 20 years exclusively by undergraduate students! This conference is called KVIT, and it is arranged by the students in the cognitive sciences programme. The overall focus of the conference is the fascinating mix that is cognitive science: neurophysiology, psychology, IT, artificial intelligence, decision-support, user-interfaces, etc. The specific theme of this year was “Quality of life”, and at this conference we had been invited to give an oral presentation. This presentation was a bit unique because it for the first time outlined some less known long-term plans of our group: to merge and extend our research on a multi-level systems-level understanding of the brain based on mathematical modelling, with fundamental research on the relationship between quantum mechanics and possibilities for free will, and with research on different states of consciousness, such as sleep, narcolepsy, and different types of meditation.

Abstract is appended below, and the entire programme and more information of the conference can be found at the conference home page.

Abstract
One of the big promises of the Information Age is that of systems medicine: that our rapidly growing biomedical datasets will be possible to analyze using
advanced mathematical models, to produce things like automated
diagnoses, personalized treatments, and an improved drug and medical
device development. In this talk, I will go through some recent
developments in this field, to show that this promise is not a
far-fetched, science fiction utopia, but a rapidly approaching reality.
Focusing essentially on my own research, I will show how such
mathematical models now can be used to e.g. replace test animals when
developing new treatments for diabetes, and be used to better unravel
the complexity of the human brain. Using such tools, we can therefore
start to obtain a new type of holistic understanding of the human
organism, into which peces of knowledge both can be examined more
correctly, and subsequently be integrated into a useful picture of the
whole. I will therefore end by a comparison of this increasingly
holistic understanding with such found in e.g. yoga traditions for
thousands of years. What are the similarities and differences, and what
will it take to one day merge such understandings?

A couple of
weeks ago, Hao held a halftime presentation of his master thesis work. His master thesis involves multi-level and
multi-scale simulations of the insulin signaling network and whole body metabolism.
The aim is to evaluate the insulin resistance in type 2 diabetes and its long term
effect on glucose dynamics in the human body.

After the
presentation, we went out for a celebratory lunch at von Dufva!

In the last week, we arranged a 2-day workshop on Biomedical engineering and decision-support. This workshop featured around 20 speakers and 30 attendees, from a wide variety of backgrounds. These backgrounds include all the steps involved in creation of decision-support systems (new biosensors, patient and personal health records, mathematical models, and the creation of usable interfaces), the testing and implementation of such systems (user-experience and user-groups, social scientists, health economy, implementation science, service design, and clinical end-users), and people from medical pedagogics, companies, and clinical decision-makers. This workshop was intended as a step towards further advancing the second-round of three already submitted VINNOVA applications (still pending), and – more generally – as a step towards the creation of a Linköping-based centre on Biomedical engineering and decision-support. This endeavor is open, so if you are interested in this process, send an email to either of the two arrangers: Elisabet or Gunnar Cedersund (elisabet.cedersund@liu.se and gunnar.cedersund@liu.se)

Some more information can be found at the workshop home page.

We have had an abstract selected for an oral
presentation at the 6th Conference
on Systems Biology of Mammalian Cells in Munich. The abstract is about our
long-term work with diabetes modeling. Gunnar will hold the presentation April
8th in the session Systems Medicine &
Systems Pharmacology chaired by Werner Mewes & Frank
Lammert. We hope to see you there!

We have published an opinion paper in Interface Focus:

Requirements
for multi-level systems pharmacology models to reach end-usage: the case of
type 2 diabetes

In the paper, we present an analysis of the current
situation where mathematical modeling steadily becomes more and more
appreciated as a tool in biomedical research and in drug development projects.
However, there are still major issues to overcome before modeling can become
one of the mainstream tools in such projects, and even more so before modeling
can be used directly in the actual treatment of patients. We review current
state-of-the-art models in diabetes research and address the most important
issues to overcome before such models can be used in drug development and in
the clinic.

We involved authors from AstraZeneca, Uppsala University,
and Eindhoven Technical University with competences reaching from disease
progression modeling, to mixed-effect PKPD modeling in the field of diabetes to
get a broad take on the subject. The paper is part of a theme issue The
Human Physiome: a necessary key to the creative destruction of medicine
organized by Stig W. Omholt and Peter Hunter from the Virtual Physiological
Human institute.