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The ISBGroup Blog

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

Precise4Q meeting in Linköping

Events, News Posted on Tue, November 12, 2019 16:02:17

During 7th and 8th of the November, we have had meeting with our partners in the PRECISE4Q project here in Linköping. In PRECISE4Q, we are working wit developing hybrid models for a decision support for Stroke treatment together with scientists within health informatics, computer science, machine learning, medicine, etc.

During the meetings, we discussed our upcoming EU review (we are financed by EUs Horizon 2020 project), how we should move forward in general, and met with local scientists here in Linköping that are working with similar things.



Master thesis presentation

Uncategorised Posted on Fri, October 04, 2019 18:18:09

Today, Therese Alenvret presented here master thesis on how health information from the clinic and/or different mobile devices can be retrieved and modeled to be used by our digital twin. So now we now more about the posibilities and challanges with accessing personal data to the digital twin. Good job Therese!



Autumn update – two new PhDs and a Post-doc

Uncategorised Posted on Fri, October 04, 2019 15:19:28

With the summer long gone, and a new term in full swing, it is time for a very late and past-due update post! The autumn of 2019 was hectic, exciting and rewarding! The year started off with the addition of three new group members, two PhDs and a post-doc (more about this further down). We also started our to date most collaborative effort, which was to connect (almost) all of our existing models. The first phase of this project culminated in a fully packed event at the Almedalen week in the beginning of the summer, but more about this in a later blog post.

The group has grown. We have had several new (but old) additions. Both me (Christian Simonsson) and Nicolas Sundqvist, both previous master-thesis students in systems biology, started PhD-positions in the group. Here’s a short update from us. I’m finishing up my projects concerning the metabolic syndrome and I have just started new projects concerning disease progression in the liver (ASH/NASH).  Adding to this, I will spend half of my PhD working at the Division of Radiological Sciences (RAD) in the group of Peter Lundberg, doing clinical research. Right now, I am analyzing MRE data for patients with suspected liver fibrosis. Nicolas is continuing his work with metabolic flux modelling, but he has also branched out, and is now doing modelling of fMRI data and brain metabolism in the group of Maria Engstrom. Also, Belen Casas is doing her post-doc in our group. Her post-doc project concerns mechanistic modeling of MPS-systems.

Three talented internship-students have just ended their one year stay with us. Kajsa Tunedal has worked with several projects, including modelling of NEFA circulation and uptake in the liver, and modelling of cortisol levels in relation to stress. Henrik Podéus has worked with connecting several models describing the different aspects of the neurovascular coupling in collaboration with Sebastian Sten (PhD in Maria Engstroms group). Anton Tornerefelt has with collaborators from Örebro’s University created a model of Macrophages activation. You all have done great work and we wish you the best of luck in all your future endeavors!

Here is two of our latest group photos! The latter is from our latest group retreat, which took place at the beautiful Omberg eco-park.



Update from MTD

Uncategorised Posted on Fri, October 04, 2019 15:01:41

Two exciting days of biomedical engineering just ended after our division hosted the annual MTD conference. The purpose of MTD is to be the most important meeting place for medical technology in Sweden. Where all key stakeholders; researchers, company representatives and medical experts can meet and discuss important questions. Our presence was at the digitalization of healthcare track where our PI, Gunnar, held the opening talk. He presented our group vision of personalized medicine: digital twins – physiologically based, personalized, simulation models to be used in healthcare. Also, Elin and Tilda each had poster presentations representing modelling research. All in all, two good days where we could showcase our research vision to the Swedish biomedical community.



New internship student – Antonia

Uncategorised Posted on Fri, October 04, 2019 14:30:17

Hello, my name is Antonia and I’m the new intern in the ISB group. My research project is about the dietary effects on acute and chronic inflammation in the human liver, and also how exercise and muscle growth is affected by switching diets. The state of the liver is strongly associated with both physical activity and your dietary habits, therefore it’s quite relevant to look at these two factors and how they could affect the liver. My focus will be on the switching from an omnivore to a strict plant-based diet. Since I’m vegan myself, I thought it would be interesting to do a project that is connected to my lifestyle. I’m planning on working on this project throughout the whole year and I’m excited to see how it goes!



Medicinteknikdagarna

Uncategorised Posted on Tue, October 01, 2019 16:39:42

This week we are going to Medicinteknikdagarna – a conference for medical engineering here in Linköping (at Konsert & kongress). We have a presentation on Wednesday 13:30 and we have two posters. We will also be present in the LiU monter. The poster session and LiU monter is open for the public. Hope to see you there!

Info about the conference: https://www.mtf.nu/event/medicinteknikdagarna-2019/



Precise4Q meeting in Dublin

Uncategorised Posted on Tue, October 01, 2019 16:36:52

This May, I (Tilda) was in Dublin for meetings with the Precise4q consortium. Check out the project here: https://precise4q.eu/. We presented our progress and discussed the coming EU review in Luxembourg this December. Next meeting will be here in Linköping this November. Stay tuned!



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.

In
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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