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Here you can read about everything that's happening in the ISB Group.

Invited lecture (and possibly teaser-performance) in upcoming MBM workshop

Events, News Posted on Thu, September 10, 2020 00:57:45

There are quite a few public lectures planned for this autumn, and one of the ones I am looking forward to a little bit extra is the MBM workshop, in Gothenburg, on October 15-16, 2020. MBM stands for Modelling in Biology and Medicine, and this is the second edition of the workshop. The workshop started as an initiative by a couple of enthusiastic Ph.D. students at the Math Department at Chalmers/Gothenburg University. But since it turned out so successful, they easily got both the support by the more senior leadership at the department, and enough positive feedback to decide to do a second edition. I really liked attending it last year, both since it was a Swedish workshop on systems biology, which means that it helps foster and grow the Swedish systems biology community, and since they managed to create a nice and cosy athmosphere. Partially because of this, the post-conference informal conversations last year led to me mentioning some of the bigger plans I am working on, which are going to become more public this year.

My dual life: scientist by day, pianist by night. Now they are starting to come together at last!

Those plans involve me combining my science and create careers into one, by doing joint lecture-performances, mixing piano, dancing, and digital twin-based stories. The original plan for this year’s workshop was to do some version of such a lecture-performance at the physical workshop. But since the physical edition had to be cancelled – due to the pandemic – the lecture will be held online. Nevertheless, in the presentation text of me at the home page, my CV covers – for the first time in a scientific event! – both my science and creative careers are mentioned side by side, and as two parts of the same thing. Already this feels really cool! And during the lecture, I plan to say, and probably also show, something short about those new and border-crossing plans in action. The workshop is held completely online, so you will be able to see it, also if you are not living in Sweden. And, later in the autumn, a more proper trailer for the first such lecture-performance will be released. The first proper such lecture-performance is planned be held during the autumn of 2021.

An exciting autumn awaits! And, the workshop is still open for abstract submissions!


New grant: 2 MSEK from ELLIIT “Usable digital twins in healthcare”

News Posted on Tue, September 08, 2020 00:28:07

We have gotten a new grant! The money this time comes from ELLIIT, which is a joint technology programme for Linköping, Lund, Halmstad University, and Blekinge Institute of Technology. The project we applied for is called “Usable digital twins in healthcare“, and it will focus on solving the many different practical challenges involved in bringing our digital twins into actual clinical practice: involving e.g. legal, technical, and ethical issues. A summary of the project and its main steps is given in the figure below. The funding is 2 MSEK, i.e. 200 kEUR/kUSD over a two-year period.

Upcoming lecture in new European webinar series on 3R, Sept 22-24

3R and animal experiments, Events, News Posted on Sun, September 06, 2020 22:56:51

A new international webinar series on 3R – replacement, reduction, and refinement of animal experiments – is about to start! And we are present with a lecture!

From our group, Gunnar Cedersund and Elin Nyman are members of the National Committee on 3Rs, which also serves as the steering committee for the Swedish 3R center (S3RC). Our S3RC has now joined forces with a few other corresponding national centres, and this has led to the launch of a new webinar series. The first edition of this will take place on Sept 22-24, lunch times i.e. 12.30-13.30 CET. Gunnar will present a lecture on digital twins on the last day, i.e. Sept 24.

This is a great initiative, and I hope it will be the start of more collaborations between the centres!

More info, and sign-up here.

Upcoming Ph.D. defense, Sebastian Sten, “Mathematical modelling of neurovascular coupling”

Events, News Posted on Sat, September 05, 2020 01:59:22

On Friday, this coming week, September 11, 2020, at 9AM CET, our Ph.D. student Sebastian Sten will defend his Ph.D. thesis, entitled “Mathematical modelling of neurovascular coupling”.

Sebastian has been co-supervised between Gunnar Cedersund (who leads this group), Fredrik Elinder (BKV and electrophysiological expert), and Maria Engström (who was the main supervisor, and who is an expert on fMRI). In the thesis, Sebastian presents four papers which incrementally unravels more and more mechanistic details of how the main signal in fMRI – the BOLD signal – is generated. In Paper 1, he demonstrates that the main part of the BOLD signal response can not be caused by a negative feedback, as was first believed, but by a combination of a fast positive and a slow negative feedforward arm. In Paper 2, the model from paper 1 is extended with GABA, which makes it able to describe the negative BOLD response. In Paper 3, he unravels more mechanistic details of the two arms, and finds out that there are in fact at least three arms: the fastest positive is the NO-arm from interneurons, the slightly slower positive arm is the PGE2 arm from pyramidal cells, and the slowest negative arm is caused by NPY interneurons. In the final paper 4 (still in ms), these mechanistic details for the signalling and the control of the arteriolar diameter is embedded in a larger model, which also contains the biomechanical flow to capillariies and venules, and the creation of the actual BOLD signal. The final model is – to the best of our knowledge – the most complete and comprehensive model for the BOLD signal, and it simultaneously describes data and extracts information from informative optogenetic stimulation experiments in mice, from unique BOLD and Local Field Potential (LFP) experiments in monkeys, and from advanced MRI measurements of BOLD, volumes and flows, in humans.

Front page of the thesis, illustration done by our other group member Christian Simonsson, who wanted to capture not only the brain, but that experiments, analysis, and mathematical modelling has come together.

Overview of the main processes studied in the thesis.

After the defense, Sebastian will work for two more weeks, wrapping up the final paper. Thereafter, other people in the group will continue to work on these models, e.g. by connecting them to more detailed models for metabolism, electrophysiology, and – eventually – to clinical practice, e.g. by allowing for more measurements to come together into a more comprehensive and complete analysis of fMRI data. However, Sebastian himself will thereafter start a position at AstraZeneca, in the group we have the most contact with there: their metabolic and cardiovascular preclinical modelling group.

A link to the Ph.D. thesis is found here, and a link to the youtube event where the defense is broadcasted is found here.

Sebastian about to do the final formal step before the actual defense: nailing his thesis to the “thesis tree” of the medical faculty.

Presentations at the VPH Virtual Physiological Human conference

3R and animal experiments, Events, News Posted on Sun, August 30, 2020 01:43:23

As usual, we have attended the Virtual Physiological Human conference, which this year was given as an eConference. This year, our group was represented with two oral presentations, and three poster presentations. The first oral presentation was held by Gunnar Cedersund, with the title: “Multi-organ and multi-level digital twin models enters the clinic”, and it was similar to the presentation already held at numerous earlier occasions, e.g. at Almedalen, in the Swedish Parliament, at NIH, etc.

Screen short from Peter Gennemark’s presentation at the VPH conference

The second presentation was of a new project: Belén Casas’ postdoc project on modelling of microphysiological systems. This project is financed by AstraZeneca, who are the ones who do the experiments, in collaboration with the company TissUse. This modelling has allowed us to both understand the available system better, and to create a first translation up to humans. This brings us one step closer to finding a workable replacement for animal experiments regarding research on type 2 diabetes and Nonalcoholic SteatoHepatitis (NASH) in the liver. The postdoc project has been supervised by Gunnar Cedersund and Peter Gennemark (AstraZeneca, but also adjoint associate professor in our group). Since Belen is now away on parental leave, Peter gave the presentation. The three final poster presentations were on digital twins and multi-level modelling (Tilda Herrgårdh), on modelling of fatty acid fluxes in the fat tissue (Kajsa Tunedal), and on a new model for exercise (Antonia Klingsäter). Apart from our own presentations, it was interesting to see that the new ASME V&V40 guidelines from FDA, on usage of modelling in certification, are getting more and more traction. Another interesting presentation was the keynote held by Tarique Hussain, who talked about how he has been using advanced modelling of the heart, to help guide treatment planning of complicated cases in child cardiology.

Screen short from the presentation by Tarique Hussain

New postdoc position in the new 12 MEuro X-HiDE project

Uncategorised Posted on Sun, August 30, 2020 01:17:35

There is a now a first postdoc position open in the new X-HiDE project, of which we are a central part. X-HiDE is a new major systems biology center that is about to launch in Sweden, which recently got a major grant of 12 MEuro, over an 8 year period. The topic will be systems biology of immunology. The over-arching goal is to build up a comprehensive and re-usable model, to be useful as a module in other models for a wide variety of diseases associated with dysfunctional inflammation: cardiovascular disease, auto-immune diseases, NASH, COPD, diabetes, cancer, etc. There are more than 10 experimental and clinical partners on board, which all will contribute with data and biological/medical expertise. Apart from this, a number of large and small companies are on board as co-funders, including e.g. AstraZeneca, and Wolfram MathCore. This particular postdoc is focused on modelling, and the main expertise sought after is data-driven mechanistic modelling (typically done using ODEs).

Because of the existence of the long-term substantial funding, there will be more similar modelling positions opened up later, including a soon to be announced more senior tenure-track position. These early positions will be excellent opportunities for junior researchers, who want to be a part of building up a new systems biology center.

NOTE: Deadline for this first postdoc position is midnight September 1 CEST!

/Gunnar Cedersund, leader of X-HiDE’s workpackage on modelling

Ph.D. defense of Markus Karlsson: MRI-based modelling of liver function

Events Posted on Thu, January 30, 2020 11:26:55
Markus preparing for his Ph.D. defense.

Today there is a new Ph.D. defense in ISB group: that of Markus Karlsson. Markus has been working with usage of magnetic resonance imaging techniques to characterize the liver, and the formal title of the Ph.D. thesis is: “Non-Invasive Characterization of Liver Disease – by multimodal quantitative magnetic resonance”. Various techniques have been tested, MRS-PDFF (to measure liver fat), T1 relaxation (to estimate fibrosis), R2* (to estimate iron in the liver), etc. In three of the papers (Paper 1,2 and 4), normal MRI analysis has been done in different patient cohorts, and in two of the papers (Paper 3 and 5), mathematical modelling has been done in collaboration with ISB group. More specifically:

Paper 1 established a relationship between R2* and MRS-PDFF, and saw that liver fat distorts the R2* signal with about one R2* unit per MRS-PDFF unit. This could be used to device a simpe correction method when using R2* to estimate liver iron levels.

Paper 2 looked at the relationship between T1 and liver fibrosis in a cohort of approximately 100 patients with various degrees of diffuse liver disease, ranging from no fibrosis to cirrhosis. In the literature, different degrees of connection between T1 and liver fibrosis have been reported, and this paper unfortunately supports the conclusion that there is low correlation.

Paper 3 was the main paper deviced by us:

Model-inferred mechanisms of liver function from magnetic resonance imaging data: Validation and variation across a clinically relevant cohort. Forsgren MF, Karlsson M, Dahlqvist Leinhard O, Dahlström N, Norén B, Romu T, Ignatova S, Ekstedt M, Kechagias S, Lundberg P, Cedersund G. PLoS Comput Biol. 2019 Jun 25;15(6):e1007157.

In this paper, the data consists of DCI-MRI data, i.e. dynamic MRI images which have been enhanced by the contrast agent gadoxetate, which has been injected into the arm at the beginning of the time-series. By combining this data with a previously developed compartment transport model, we could estimate reliable uptake rates into the liver for all patient groups. Furthermore, in this paper we also showed that these estimated uptake rates, only accesible using the model, serve as new useful biomarkers for estimating liver function and fibrosis. In this paper, we also demonstrated how nonlinear mixed-effects modelling could be used to simplify the currently used protocol, to save money and time in the clinic.

Paper 4 looked at the relationship between magnetic resonance cholangiopancreatography (MRCP) and liver function estimated using DCI-MRI.

Paper 5 again looks at modelling of DCI-MRI data, to characterize the transport rates in and out of hepatocytes. In this paper, we compare uptake rates in humans and rats, and in rats with different exposures to a drug which impacts liver function. This allows us to establish a translational framework, that can predict the likely effect of a drug in humans, based on these available data and new data for the effect of the drug in rats. This is useful for drug development, when one wants to estimate the likely effect of a drug in humans based on available pre-clinical and clinical evidence.

Opponent for the defense is Steven Sourbron, who has worked with similar uptake and perfusion modelling in many of the central organs for many years, and who is one of the leading authorities in the field. In the examination committee sits Sven Månsson (Malmö), Lennart Blomqvist (Stockholm) and Zoltan Szabo (Linköping), who have complementary radiological and clinical competence.

What makes a modelling work Science? Its ability to describe data!

Systems biology and science Posted on Mon, March 04, 2019 00:51:15

In my work as a scientist, one of the possible tasks I can take upon
myself is to be a reviewer. This is important, but almost completely
non-valued; there is no pay, and no funding agency cares very much whether you do it or not. However, the review process is the most important place where scientific
discussions are taking place, because currently – and unfortunately –
this is virtually the only criteria for what constitutes a scientific finding
today: has it been published in a peer-reviewed journal? I therefore do
spend some time doing this. And I fight a lot of the time with papers
and authors who want to publish mathematical modelling works without any
comparison with experimental data. I strongly believe that such works
are not science, and that they should not be published. Today, I just
submitted such a response, and since the reply is written in a
completely non-specific manner to the paper in question – it could have
been written to any paper with the same problem – I also post it here.
My principle for the the next decade of my life, which I just entered,
is “going public, going deep”, and this publishing of this here on the blog, is a
part of me following that new principle.

Here is the review reply that I wrote:

“Thank you for your comments.

I do recognize the fact that you and others have published similar
papers in the past, where models have been developed and presented with
no comparison with data. There is nothing I can do about that. However,
that fact does not transform such works into science. Modern science is,
in my very firm opinion, the truth-seeking tool that was established by
Galileo, many hundreds of years ago: it builds on i) the mathematical
formalization of mechanistic hypotheses of the system that you study,
and then ii) usage of *data* to distinguish between those hypotheses.
The hypothesis that has the best ability at describing data – in the
first round estimation data, and in the second round independent
validation data, based on predictions and *then* experiments – is the
superior hypothesis. It is this formula for truth-seeking that
distinguished the science that started with Galileo, and the
church-driven epistemology that ruled science before him (note that the
prior Aristotelian science worldview also involved mathematics, and
data, but not in the same hypothesis-testing manner). If Galileo’s
formula is not followed, it is not science. That a paper has been
published in a scientific journal does not make that work science. It
does mean, however, that that work *should not* have been published. The
only exception to that principle exists within the field of
mathematics, which has other criteria for its judgements of a paper:
e.g. that what is presented should be i) previously non-proven and ii)
should hold true for a large family of equations/examples. Another type
of paper in mathematics can be that of a new method, e.g. for
optimization, that is proven to be superior to existing methods.

Unfortunately, this conception of what science is was lost in the field
of modelling of biological systems during a large part of the 20th
century. During this time, it was called mathematical biology,
complexity theory, etc. This was, to a large extent, rectified, during
the beginning of the 21st century, with the conception of systems
biology. However, unfortunately, much old-school data-free modelling is
still done. This has to stop! It is giving, and has been giving, the
field of modelling in biology a bad reputation, with the impression that
it has nothing to do with reality or biology – and rightly so, such
modelling has nothing to do with reality! At least not in any way that
has been demonstrated by science.

Two further clarifications and responses to your reply are in order:

i) You say that your model is based on data. That is true. The model structure is based on data. Your manuscript does
therefore function as a review of existing biology. But that is
something different than publishing an original research paper, with
novel results. That is something that is fundamentally different than
the kind of comparison between simulations of the *entire model
structure* and data that I am referring to above. It is a bit like
saying that the Ptolemaic worldview (with the sun in the middle) is
based on data because it includes the sun, the planets, and the earth;
which are observed in experiments. The question is not if they are
present. The question is which way of connecting them in relationship to
each other that is the correct one. To go beyond what can be said with
biology alone – i.e. to do mathematical modelling – requires that one
puts the structure together using competing hypotheses (e.g. one with
the sun in the middle, and one with the earth in the middle), and then
sees which of the two corresponding models that produces simulations
that best agrees with data (existing data and future data). That is how
science has functioned since Galileo, and that is how it should still
function today.

ii) You say that a model component
in your model – that has not been validated in any fashion whatsoever –
produces a prediction that a specific component is important; you then
also point to some papers that claim the same thing. That could, on
the surface, seem like a comparison with data. However, with the model
structure that you have put together – with the most well-known and most
often considered main players in the beta cell ethiology – you could
identify any component in your model as the most important one, and then
find many papers that claim that that component is the most important
one. That is, unfortunately, how biology is allowed to work today, with
many co-existing hypotheses, that are allowed to continue to co-exist,
where each lab focusing on one of the components is allowed to point to
limited results as to why their particular component is the most
important one, and without forcing anyone to challenge these claims with
respect to each other; without finding out what the big picture looks
like. That is where systems biology can and should come in and make a
difference: by putting up alternative hypotheses regarding what is the
most important component(s), and then letting data, systems-level data,
judge which of the hypotheses that is the most compelling one. This is
how systems biology has worked in many/most of the papers that are cited
in the review paper that I gave you. That way requires a model that
produces simulations (time-curves, typically), that agrees with
estimation data, and with validation data.

In summary, for me to
judge this or any paper as publishable, you need to produce (at least)
these two things: i) at least one curve, e.g. a simulation of a variable
as it progresses in time, that agrees with corresponding data; ii) a
prediction that is validated by another dataset, not used for estimating
the parameters in the model. In fact, apart from that you should also
demonstrate that your model is superior to other models, i.e. that it
can describe all data that one of the currently most important and
realistic models can, and then more data apart from that.

other words, there are many papers that are published for beta-cells,
including for their ethiology. These models can describe a lot of data,
in the above manner. Why not take one of those models, find a feature or
dataset that they cannot explain (there are many), and then go ahead
and improve the model to make it able to explain those data (while still
retaining the ability to explain all old data). If you then also show
that this is not due to overfitting w.r.t. all data, i.e. if you then
show that your new model also can describe some validation data, not
used for model fitting, then you will have contributed with an
improvement that follows the tradition of science. Then, and only then, I
will judge your – or any scientist’s – paper as publishable.

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