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A Novel Microgravity Simulator Applicable for Three-Dimensional Cell Culturing

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Random Positioning Machines (RPM) were introduced decades ago to simulate microgravity. Since then numerous experiments have been carried out to study its influence on biological samples. The machine is valued by the scientific community involved in space relevant topics as an excellent experimental tool to conduct pre-studies, for example, before sending samples into space. We have developed a novel version of the traditional RPM to broaden its operative range. This novel version has now become interesting to researchers who are working in the field of tissue engineering, particularly those interested in alternative methods for three-dimensional (3D) cell culturing. The main modifications concern the cell culture condition and the algorithm that controls the movement of the frames for the nullification of gravity. An incubator was integrated into the inner frame of the RPM allowing precise control over the cell culture environment. Furthermore, several feed-throughs now allow a permanent supply of gas like CO 2. All these modifications substantially improve conditions to culture cells; furthermore, the rewritten software responsible for controlling the movement of the frames enhances the quality of the generated microgravity. Cell culture experiments were carried out with human lymphocytes on the novel RPM model to compare the obtained response to the results gathered on an older well-established RPM as well as to data from space flights. The overall outcome of the tests validates this novel RPM for cell cultivation under simulated microgravity conditions.
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Microgravity Sci. Technol.
DOI 10.1007/s12217-014-9364-2
ORIGINAL ARTICLE
A Novel Microgravity Simulator Applicable
for Three-Dimensional Cell Culturing
Simon L. Wuest ·St´
ephane Richard ·
Isabelle Walther ·Reinhard Furrer ·
Roland Anderegg ·J¨
org Sekler ·Marcel Egli
Received: 8 July 2013 / Accepted: 26 March 2014
© Springer Science+Business Media Dordrecht 2014
Abstract Random Positioning Machines (RPM) were
introduced decades ago to simulate microgravity. Since then
numerous experiments have been carried out to study its
influence on biological samples. The machine is valued by
the scientific community involved in space relevant topics
as an excellent experimental tool to conduct pre-studies,
for example, before sending samples into space. We have
developed a novel version of the traditional RPM to broaden
its operative range. This novel version has now become
interesting to researchers who are working in the field of
tissue engineering, particularly those interested in alterna-
tive methods for three-dimensional (3D) cell culturing. The
main modifications concern the cell culture condition and
the algorithm that controls the movement of the frames for
the nullification of gravity. An incubator was integrated into
the inner frame of the RPM allowing precise control over
the cell culture environment. Furthermore, several feed-
throughs now allow a permanent supply of gas like CO2.
All these modifications substantially improve conditions to
culture cells; furthermore, the rewritten software responsi-
ble for controlling the movement of the frames enhances
the quality of the generated microgravity. Cell culture
S. L. Wuest ·R. Anderegg ·J. Sekler
Institute for Automation, University of Applied Science
Northwestern Switzerland, Windisch, Switzerland
S. L. Wuest ·S. Richard ·I. Walther ·M. Egli ()
CC Aerospace Biomedical Science and Technology, Lucerne
School of Engineering and Architecture,
Seestrasse 41, 6052 Hergiswil, Switzerland
e-mail: marcel.egli@hslu.ch
R. Furrer
Institute of Mathematics, University of Zurich,
urich, Switzerland
experiments were carried out with human lymphocytes on
the novel RPM model to compare the obtained response to
the results gathered on an older well-established RPM as
well as to data from space flights. The overall outcome of
the tests validates this novel RPM for cell cultivation under
simulated microgravity conditions.
Keywords Random Positioning Machine ·Microgravity ·
Tissue engineering ·3D cell cuturing ·Kinematic
acceleration
Nomenclature
tTime [s]
IInner frame
OOuter frame
GGlobal frame
gI(t) Earth gravitation vector in the inner frame, at
the time point t[g]
gGEarth gravitation vector in the global frame
[g]
α(t) Rotation angle of the outer frame to the
global frame, at the time point t[rad]
α0Rotation angle of the outer frame to the
global frame, at the time point t=0 [rad]
β(t) Rotation angle of the inner frame to the outer
frame, at the time point t[rad]
β0Rotation angle of the inner frame to the outer
frame, at the time point t=0 [rad]
Gmean Mean gravity [g]
GX,mean ;GY,mean;GZ,mean Mean gravity in X-, Y-and
Z-direction (inner frame) [g]
gX,I,i ,g
Y,I,i ,g
Z,I,i Samples indicating the direction of
the earth gravity vector transposed to the
Microgravity Sci. Technol.
inner frame, in the local X-, Y-andZ-
directions, respectively [g]
pglobal (t)Arbitrary point in the global frame, at time
point t[m]
rlocal Arbitrary point in the local inner frame [m]
rX,loca l ,r
Y,local;rZ,local Coordinates in the X,Yand Z-
directions of an arbitrary point rlocal in the
local inner frame [m]
rDistance from the center of rotation [m]
ωαRotation velocity of the outer frame [rad/s]
ωβRotation velocity of the inner frame [rad/s]
ωRotation velocity if both frames rotate with
the same velocity ωα=ωβ=ω[rad/s]
Aglobal (t)Acceleration considered in the global frame,
at time point t[m/s2]
AX,global(t ),A
Y,global (t ), AZ,global(t ) Acceleration con-
sidered in the global frame in X,Y,andZ-
direction, respectively, at time point t[m/s2]
Amean,global Mean acceleration, considered in the global
frame [m/s2]
˘
Amean,global Minimum expected mean acceleration
[m/s2]
ˆ
Amean,global Maximum expected mean acceleration
[m/s2]
Alocal (t)Acceleration in the local inner frame, at time
point t[m/s2]
Amean,local Mean acceleration, considered in the local
frame [m/s2]
Introduction
Regular 2-dimensional (2D) cell culture techniques repre-
sent a convenient method to study biological processes.
The use of this method has substantially improved our
understanding of cellular mechanisms over the last decades.
Tissue cells are cultured in plastic dishes, where they
anchor to the inner flat surface via the extracellular
matrix. Obviously, this conventional 2D approach does not
account for the third dimension. Cells naturally belong to a
3-dimensional (3D) organization forming cell clusters or
tissues in which mechanical, structural and chemical inter-
actions between cells and/or the extracellular matrix (ECM)
take place in all three dimensions.
Indeed, recent evidence reveals striking discrepancies in
the behavior of cells cultured in 2D or 3D (Anders et al.
2003;Weaveretal.1997;Wolfetal.2003). In fact, 3D cell
cultures reflect the in vivo situation more accurately than
2D cell cultures, and 3D culture allows reducing the gap
between the artificial cell culture in vitro and the physio-
logical situation. Therefore, researchers have been looking
for 3D cell culture strategies that enable more accurate
mimicking of tissue or organ structures and functions. To
do so, culture techniques have been constantly developed.
Single and co-culture techniques have been developed such
as cellular spheroids (Lin and Chang 2008) or polarized
epithelial cell culture (Shaw et al. 2004). Spheroidal cell
structures for example were introduced in tumor research
a long time ago (Santini and Rainaldi 1999;Ivascuand
Kubbies 2006; Friedrich et al. 2009).
In that context, spheroids have been shown to better
represent characteristics of in vivo tumors. Furthermore,
they have also been developed to study angiogenesis
(Wenger et al. 2005; Wenger et al. 2004). Of all the strate-
gies to simulate 3D in vivo tissue growth, hydrogels have
emerged as an attractive option that provides an artifi-
cial environment for optimal 3D cell culture. Such gels
consist of collagen (Butcher and Nerem 2004), dextran
(Cadee et al. 2000; Cascone et al. 2001), Matrigel™
(Hughes et al. 2010) as well as other materials (Burdick
and Prestwich 2011; Eyrich et al. 2007;Hoetal.2010;
Masters et al. 2005). Those gels can be supplemented with
particular enzymes and growth factors (Kleinman et al.
1986; Kleinman et al. 1982). In addition to hydrogels, 3D
platforms have been developed such as the BioLevitator™
from Hamilton. There, cells loaded with magnetic beads are
cultured in 3D while exposed to a magnetic field.
In this paper, an alternative approach to 3D cell cultur-
ing by using the RPM is presented. The RPM (van Loon
2007; Borst and Van Loon 2009) is a 3-axis clinostat in
which the two axes are essentially rotated at constant speed.
Its working concept evolved from simple clinostats, which
were developed first in 1879 by Julius von Sachs, a botanist
who wanted to investigate gravitropism in plants (van Loon
2007). Through the particular movement generated by the
RPM, the weight vector is continually reoriented as in
traditional clinorotation, but with directional randomization.
The purpose of the original idea was to simulate weight-
lessness more accurately, but the concept can be applied to
generate 3D culture as well. Indeed, randomization of the
Earth gravity vector allows redistributing the gravity forces
constantly so that cells grow in a similar environment as
in organs/tissues (Kraft et al. 2000). Cells cultured under
those conditions will no longer sediment, therefore allow-
ing for omnidirectional cell growth. Supporting this idea,
a similar approach has already been successfully applied
using a rotating wall vessel bioreactor (Barrila et al. 2010).
Moreover, it has been recently shown that proliferating
endothelial cells cultured on the RPM start to grow as
multicellular spheroids. Later on, tubular structures were
formed by the spheroidal growing cell structure and a clear
increase of extracellular matrix proteins was measured as
well (Pietsch et al. 2011).
The evolution of the RPM reported here lies mainly
in the full integration of a CO2incubator directly on
the internal frame of the RPM. Such an upgrade allows
Microgravity Sci. Technol.
close control of the temperature without the need of a
completely air-conditioned room. In addition, CO2can con-
stantly be supplied to the cells. CO2regulation allows
maintaining a constant pH matching physiological condi-
tions (7.2–7.5) and makes additional buffering strategies
unnecessary.
Material and Methods
Random Positioning Machine (RPM)
The RPM has a solid lightweight construction that sup-
ports two gimbal-mounted frames (Fig. 1). A commercially
available CO2incubator, slightly modified to fit the needs,
is attached to the inner frame, which provides a 14 liter
cell culture chamber. The chamber offers optimal culture
conditions, such as maintaining defined levels of CO2and
temperature. In addition, the chamber is equipped with
various sensors for monitoring crucial culturing parame-
ters. The movement of the rotating frames is driven by two
independently operated and controlled engines via timing
belts to avoid slippage. Complicated belt routing is avoided
by mounting one engine directly onto the outer frame. This
design ensures independent control of the frames move-
ment. The incubator motion is monitored through encoders
attached to the motors directly. 3D accelerometers fixed
to the inner frame are used for quality control of the
movement.
This version of the RPM is equipped with a rotational
feed-through for gas and liquids allowing, for example,
constant CO2supply to the incubator. Power supply for the
various devices on the inner and outer frame, as well as
time critical communication, are transmitted via slip ring
capsules. As an alternative route, non-time critical infor-
mation can also be transmitted via a WLAN. The WLAN
system offers the advantage of being able to monitor cru-
cial RPM data from a nearby office by using a standard web
browser. Having the incubator placed in the RPM instead of
placing a small (desktop) RPM inside an incubator brings
the advantage of a relatively large test chamber. At the same
time the confinement of the incubator chamber insures that
all samples are in a reasonable distance to the center of
rotation in order to avoid centrifugal forces. In addition
the incubator does not get contaminated through the RPM
machinery such as oil vapor or debris of wear.
The software designed to control the RPM functions is
run on a built-in industrial PC and is a LabVIEW based
application. Numerous functions have been implemented
into the operating software like an automatic start-stop func-
tion executable at predefined time/date or the option to
monitor all the crucial incubator parameters like tempera-
ture, gas composition and motion.
Biological Experiment
All chemicals and drugs used for conducting the mentioned
biological experiments were purchased from Sigma (Buchs,
Switzerland) unless otherwise stated.
Lymphocytes Culture
Peripheral blood (450 ml) was collected from healthy
donors and further processed for lymphocyte isolation as
previously described (Cogoli-Greuter et al. 1996; Cogoli-
Greuter et al. 1994; Gmunder et al. 1990; Pippia et al.
1996). In brief: a lymphocyte-enriched suspension was
prepared by gradient centrifugation using Lymphocyte
Separation Medium (PAA, LMS-1077, J15-004). A T lym-
phocyte enriched suspension was later obtained using a
Human T Cell Enrichment kit (RnD research, HTCC-25).
The cells were re-suspended in RPMI-1640 supplemented
with 40 mM HEPES, 5 mM sodium bicarbonate, gen-
tamycin (50 μl/ml), 4 mM L-Glutamine and 10 % fetal calf
serum (PAA A15-101). The cells were then transferred into
LYCIS containers (1 ml at a density of 1.5 million cells/ml)
(Chang et al. 2012) and mounted either at the rotating cen-
ter of the RPM or in a stationary laboratory incubator(equal
incubator as on the RPM). In the experiments described
here, the samples that were placed at the rotating center of
the RPM (within a radius of 10 cm) experienced a rota-
tion with an angular velocity of 40 deg/s and an ambient
temperature of 37 C. Cells on the RPM were exposed
to the RPM simulated microgravity for one hour prior to
lymphocyte activation by injection of concanavalin A /CD
28 mixture (10 μg/ml and 4 μg/ml final concentrations,
respectively; performed by a quick interruption of the
rotation, <1 min.). After activation, the cells remained
under their respective conditions (simulated microgravity or
stationary) for 22 h.
FACS Analysis
For the FACS analysis, T lymphocytes were stained at 4 C
using a CD-25 antibody (MACS, 130-091-024) and fixed
with 2 % paraformaldehyde according to the manufacture’s
instructions. Thereafter, the T lymphocyte populations were
investigated by a FACS analyzer (BD FACS Calibur,
Becton Dickinson). The CD-25 positive T lymphocytes
were considered as activated.
Statistical Analysis
Statistical variations were tested by applying the Wilcoxon
rank-sum Test (p values 0.05 were regarded as statis-
tically different). Data are reported as means ±standard
deviation (n =3).
Microgravity Sci. Technol.
Results and Discussion
Equalizing Gravitation Through Random Positioning
The basic idea followed, to generate simulated micrograv-
ity, is to distribute the Earth’s gravity vector in space evenly
over time by constantly reorienting the sample chamber
to random positions (van Loon 2007). Therefore the RPM
can be treated as a quasi-static machine (if the time frames
are chosen small enough). Kinematic effects greatly depend
on the position of the sample and the rotation velocity.
Since the rotation velocity is small, kinematic effect such as
centrifugal forces are negligible. In this section the con-
cept of quasi-static random positioning is discussed in more
details.
Gravity Vector Transposition to the Inner Frame
For the examination, it is important to distinguish between
the static global and the rotating local frame (coordinate
system) of the inner frame (Figs. 1and 2). The moving
frames of the RPM are mounted in the global frame, which
is fixed, and gravity acts always normal to the ground
(representing the global XY-plane). The local inner frame
represents the frame (coordinate system) of the sample and
is constantly reoriented with respect to the global frame. The
gravity vector of the global frame is transposed into the local
inner frame. This decomposition of the gravity vector to the
inner coordinate system (where the samples are mounted)
is computed, by employing two rotational matrixes. For this
operation the position of the outer and inner frames needs to
be known:
gI(t)=I
OR(t)·O
GR(t)·
gG
gI(t)=
cos β(t)0sinβ(t)
010
sin β(t)0cosβ(t)
gI(t)=
cos α(t)·sin β(t)
sin α(t)
cos α(t)·cos β(t)
·
10 0
0cosα(t)sin α(t)
0sinα(t)cos α(t)
·
0
0
1
Random Walk
To equalize gravity we employ a Random Walk algorithm
by which both frames of the RPM rotate at a constant
velocity, but the rotation direction is inverted at randomly
chosen time points. The velocity transition from forward
to backward rotation takes place at a constant rotational
acceleration.
Plotting the local gravity vector of the inner frames over
the course of time, it becomes clear that the vector tip travels
on a sphere with a radius of 1 g. However the distribu-
tion is not entirely even and concentrates at the two poles
lying at the rotational axis of the inner frame (local Y-axis;
Fig. 3). They become predominant after a short time. This
phenomenon can be explained by the rotation of the outer
frame. Every time the outer frame is in a vertical position,
with the rotation axis of the inner frame parallel to the grav-
ity, the local gravity vector is unavoidably pulled towards
one of the two poles. In general, the resulting picture is sym-
metrical. Figure 4illustrates the time course of how many
times the Earth’s gravity vector is pointing to an arbitrary
position after a given period of time (1, 6, 15, 30, 60 min
and 5 h).
Mean Gravity
As a quality measure for the distribution of orientation, we
use the mean gravity over time, defined as:
Gmean =GX,mea n2+GY,mean2+GZ,mean2
where the mean gravity values in the three directions are
defined as follows:
GX,mean =n
i=1gX,I,i
n
GY,mean =n
i=1gY,I,i
n
GZ,mean =n
i=1gZ,I,i
n
The mean gravity is easy to compute and memory efficient,
since only the sum of all samples in X,Yand Z, as well as
the total number of samples, has to be stored. In Fig. 5the
mean gravity is plotted over time. The mean gravity falls
quickly below 0.1 g and stabilizes below 0.03 g within 2 h
of operation. With this concept two points lying opposite
each other (sign change) are compensated. Therefore the
two poles seen in Fig. 4also cancel themselves out. In Fig. 5
Microgravity Sci. Technol.
Fig. 1 Picture of the RPM construction. A CO2incubator is mounted
in the center of the gimbal framework. The frames are driven by two
independent precision motors
a temporal increase between approximately 0.5 and 1.5 h is
visible. This appears because the Random Walk algorithm
is based on random numbers and because the mean grav-
ity is computed through averaging. At the beginning of an
experiment little data contribute to the average, making it
sensitive to any deviations. With the elapsing experiment
time, the mean gravity becomes increasingly robust. This
temporal increase of the mean gravity thus depends on the
combination of the random numbers.
Numerical Illustration
Since the Random Walk algorithm depends on random
numbers, the outcome of two successive runs, are not iden-
tical. To demonstrate the reliability of the algorithm several
hundred runs of numerical simulations were performed.
Each of these simulations represents an experiment of sev-
eral hours. The resulting mean gravity at a defined time
were finally recorded and plotted as a histogram. As shown
in Fig. 6, all values stay below 0.03 g. The mean value of
these 500 samples is 0.0086 g ±0.0039 g (SD) for a rota-
tional velocity of 60 deg/sec and 0.0105 g ±0.0044 g (SD)
for 40 deg/sec. The histograms in Fig. 6are illustrating that
the Random Walk is reliably producing simulated micro-
gravity at both velocities. For particular angular velocities
and assuming piecewise constant accelerations, it is possi-
ble to show that the expected mean squared gravity vanishes
over time. The approach, based on a central limit theorem,
is mathematically quite involved and is outside the scope of
this article.
Kinematics
For slow rotations the quasi-static approach is sufficiently
valid and applies for all samples close enough to the cen-
ter of rotation. The acceleration caused by kinematics is,
however, much more difficult to deal with and depends
greatly on the sample position relative to the center of
rotation (Fig. 7).
The experienced acceleration of an arbitrary point can
be computed as follows: Any point
plocal in the inner
frame can be described with a vector
rlocal from the
center of rotation. The path of
plocal in the global frame, as
both frames rotate, is computed by employing two rotational
matrixes:
pglobal =G
OR·O
IR·
rlocal
pglobal (t ) =10 0
0cosα·t+α0)sin α·t+α0)
0sin α·t+α0)cos α·t+α0)
·
cos ωβ·t+β00sin ωβ·t+β0
01 0
sin ωβ·t+β00cos
ωβ·t+β0
·rX,loca l
rY,local
rZ,local
By differentiating the position twice with respect to
time we get the accelerations AX,global (t),AY,global(t) and
AZ,global (t), acting in the direction of the global coordi-
nate systems axis X,Yand Z, respectively. From these three
accelerations the absolute acceleration magnitude Aglobal
can be computed.
Aglobal (t ) =AX,global (t )2+AY,global (t )2+AZ,gl obal (t)2
To simplify, we assume that both frames rotate with an
identical velocity, ωα=ωβ=ω.Thetermsα0and β0can
Fig. 2 Schematic of the RPMs
gimbal framework. The samples
(on the inner frame) are rotated
around two perpendicular axes
Microgravity Sci. Technol.
Fig. 3 Distribution of the local gravity vector over the course of time.
The blue line indicates the path of the gravity vector, as it would be
experienced by a sample at the center of rotation. The local gravity
vector frequently passes through two poles lying on the Y-axis (rota-
tion axis of inner frame). This becomes clearly visible already after
6min(top left). (Random Walk, Velocity: 60 deg/sec)
be set to zero (α0=β0=0), since they have no influence
on the mean and peak acceleration. This results in:
Aglobal (t)=ω2·r2
X,loca l 4.5+cos (2·ω·t)
2
+r2
Y,local +r2
Z,local 4.5cos (2·ω·t)
2
rX,loca l ·rY,local ·4·cos (ω·t)rX,local ·rZ,local
·sin (2·ω·t)+rY,local ·rZ,local ·4·sin (ω·t)
From this formula we can approximate the mean accelera-
tion:
Amean,global ω24.5·r2
X,loca l +r2
Y,local +4.5·r2
Z,local
To illustrate the formula above, path and total acceleration
for three different points are shown in Fig. 7. All points
have the same radius length but acceleration is by far not the
same.
r1=0.1[m]
3
1
1
1
r2=0.1[m]
2
1
0
1
r3=0.1[m]
0
1
0
Even though the kinematic acceleration depends on the
location, it is limited to a range given by the rotation velocity
and the distance from the center of rotation:
˘
Amean,global ω2·r
ˆ
Amean,global 3
2·ω2·r
Microgravity Sci. Technol.
Fig. 4 Histograms of the orientation mapped as color code on an
imaginary sphere. The color of a particular spot on the sphere indi-
cates how often the gravity vector pointed at that direction. According
to the simulation, the orientation distribution is uneven, but symmetri-
cal and two poles become dominant after a short time (Random Walk,
Velocity: 60 deg/sec, fs=50 Hz)
Local Acceleration
The acceleration computed in the global frame (for a
specific time point) is not the acceleration experienced by
a point in the local frame. To be more precise, the absolute
value of the local and global acceleration is the same, but
not the direction:
Aglobal (t)=
Alocal (t)
Aglobal (t)=
Alocal (t)
Microgravity Sci. Technol.
Fig. 5 The mean gravity (upper track) as well as the mean gravity
of the components in the X-, Y-andZ- directions (lower track) plot-
ted over time. The temporal increase between 0.5 and 1.5 h appear
because the Random Walk algorithm is based on random numbers
and because the mean gravity is computed through averaging. With
the elapsing experiment time, the mean gravity becomes increasingly
robust to temporal deviations
To compute the local acceleration the global acceleration
has to be transformed by again employing the above rotation
matrixes:
Alocal (t)=0
IRT·G
0RT·
Aglobal (t )
Alocal (t)=
cos ωβ·t+β00sin
ωβ·t+β0
010
sin ωβ·t+β00cos
ωβ·t+β0
·
10 0
0cos
(ωα·t+α0)sin (ωα·t+α0)
0sin
(ωα·t+α0)cos (ωα·t+α0)
·
Aglobal (t )
Again we can set the terms α0and β0to zero (α0=β0=0).
The rotation velocity shall be the same for both frames,
ωα=ωβ=ω. After substituting and simplifying we finally
get:
Alocal (t )
=ω2
rX,local ·cos(2·ω·t)3
2rZ,local ·sin(2·ω·t)
2
rX,local ·2·cos ·t) rY,local rZ,local ·2·sin ·t)
rX,local ·sin(2·ω·t)
2rZ,local ·cos(2·ω·t)+3
2
By computing the mean gravity, we first compute the mean
gravity for all three components in X,Yand Zand then we
Fig. 6 Histograms of 500
numerical simulations. Each
sample represents the mean
gravity at the center of rotation
after 5 h in operation. Left:
Random Walk, velocity:
60 deg/sec. Right: Random
Walk, velocity 40 deg/sec. The
histograms are illustrating that
the Random Walk is reliably
producing simulated
microgravity at both velocities
Microgravity Sci. Technol.
Fig. 7 Path and acceleration for three points with the same distance
from the center of rotation. Both (outer and inner) frames rotate at a
constant velocity with 60 deg/sec. The top row shows the path in blue.
The vector in magenta indicates the position of the specific point at
time t=0. On the bottom row, the global acceleration as a function
of time (in blue) and the corresponding mean (green)aswellasthe
minimum and maximum (red) is plotted. The resulting accelerations
depend greatly on the position, even though the distance to the center
of rotation is the same
Fig. 8 The mean global acceleration (Amean,gl obal) and peak global acceleration ( ˆ
Aglobal ) depending on the location (r=10 cm; ω=60 deg/sec)
Microgravity Sci. Technol.
compute the total mean gravity by using the vector addition.
If we do the same for the local acceleration we get:
Amean,local =ω2
1.5·rX,loca l
rY,local
1.5·rZ,local
Amean,local =
Amean,local
=ω22.25 ·r2
X,loca l +r2
Y,local +2.25 ·r2
Z,local
Acceleration Depending on the Position
As we have already seen above, the experienced accelera-
tion of a point depends strongly on the location. By iterating
through multiple points on a sphere and computing the mean
global acceleration (Amean,global )and the peak acceleration
(ˆ
Aglobal ), we get the results illustrated in Fig. 8. The radius
length ris constant and set to 10 cm. By visualizing the peak
acceleration, it becomes clear that the highest peak accel-
erations do not appear at the same locations as the highest
mean accelerations (Fig. 8). The points on the XZ-plane
(being perpendicular to the rotation axis of the inner frame)
experience the highest mean acceleration. The highest peak
accelerations appear on two planes parallel to the XZ-plane
and are approximately 0.38·raway from the XZ-plane. The
smallest accelerations appear on the two points lying on the
rotation axis of the inner frame (Y-axis).
Experimental Validation
T Lymphocytes purified from human peripheral blood
can be activated by Con A in vitro. The drug, a lectin
extracted from lentil seeds, exerts this effect by mimick-
ing the antigen-presenting process occurring during spe-
cific antigen-activation. The transmembrane protein CD25,
which is highly expressed on the surface of activated
Fig. 9 T lymphocyte activation by Con A/CD28 under 1 g and
simulated microgravity. Two healthy donors were tested
T lymphocytes, is used as a marker for the activation.
Several experiments have already shown that T lympho-
cytes reduce their activation substantially on exposure to
reduced gravity (either during space flights, sounding rocket
or RPM)(Cogoli-Greuter et al. 1994; Cogoli et al. 1984).
We use this effect to validate the quality of the algorithm
running on the novel RPM that generates simulated micro-
gravity for samples in the center of the rotating frames. By
comparing the activation values of samples under normal 1 g
conditions, simulated microgravity (created by the old and
established RPM as well as by the novel RPM), as well as
real space conditions, it appears that the simulated reduction
of the gravity field leads to a reduction of the T lymphocytes
activation by about 80–90 % (Fig. 9). These results are in
agreement with previous publications (Cogoli et al. 1984;
Gmunder et al. 1990; Cogoli-Greuter et al. 1994).
Conclusions
Here, we present a novel version of a RPM that is applicable
for experiments in the field of life science concerning micro-
gravity and 3D cell culturing. Our new machine applies
the well-established core principle of gravity nullification, a
concept that was introduced decades ago (van Loon 2007;
Borst and Van Loon 2009). In this novel RPM includes
features like stable environmental conditions (temperature,
CO2etc.) in the culture chamber as well as a constant sup-
ply of culture media or CO2to the samples, which creates
much better long-term cell culturing conditions than before.
A major objective of the novelRPM is to simulate micro-
gravity as accurately as possible. Thus, a major effort was
put into the theoretical concept of gravity nullification as
well as the conversion of that concept into the algorithm
controlling the movement of the frames. As we have shown
here, by applying the newly designed algorithm, the mean
gravity falls below 0.1 g within a few minutes and stabi-
lizes below 0.03 g thereafter within 2 h. The mathematical
analysis further demonstrated that samples placed anywhere
in the incubator experience low gravity levels. Despite the
difficulty to completely control kinematic accelerations,
they are limited to a given range, only depending on the rota-
tion velocity and the samples’ distance from the center of
rotation. These two parameters should therefore be kept as
low as possible. This novel RPM represents a valid tool for
simulating microgravity. This was confirmed by conduct-
ing experiments with human T lymphocytes. Their behavior
under microgravity (simulated on real space microgravity)
is well known and has been described in numerous pub-
lications (Cogoli et al. 1984; Cogoli-Greuter et al. 1994;
Gmunder et al. 1990). As illustrated in Fig. 9, exposing T
lymphocytes to reduced gravity leads to a severe reduction
of the activation. The figure further elucidates that there is
Microgravity Sci. Technol.
no difference between the old and well-established RPM
and our novel version of the RPM (Fig. 9). This indicates
that the algorithm of the novel RPM is comparable to the
one of the old RPM.
However, the novel version of the RPM is not only an
interesting tool for microgravity-related biological studies.
Long-term cultivation of cells under low gravity condi-
tions offers new aspects for tissue engineering. By adding
the described features, long-term cultivation of cells under
simulated microgravity is now possible for the first time
and is of a comparable quality to regular (stationary) cell
cultures. Permanent exchange of culture media can be pre-
cisely controlled by the novel RPM, as well as the addition
of particular drugs to the cell cultures at a particular time of
day for a defined period of time. Built in log files record any
action of the system allowing a retrospective analysis of the
experiment. Our former studies have already demonstrated
that long-term cultivation of endothelial cells under sim-
ulated microgravity conditions leads to spheroidal growth
behavior, including vascularization (Pietsch et al. 2011).
Thus, this novel version of the RPM offers an ideal platform
for studies such as tumor growth.
It will be interesting in future studies to show how other
cell types respond to cultivation under reduced gravity or
under mechanical unloading. It is likely that this culture
method bears new options and possibilities for cell culturing
in general, allowing tissue to grow that shows unexpected
features.
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... 2021, 22, 6331 2 of 12 on these simulated microgravity platforms. Current procedures for biological studies primarily use relatively large vessels to carry out experiments (e.g., T-25 and T-75 cell culture flasks) [12][13][14][15][16] (Figure 1) or custom-made cell culture vessels [17][18][19]. Comparatively, these larger vessels require a copious amount of cells and cell culture media which is cost intensive, uses large amounts of single use plasticware, and limits biological studies that necessitate smaller amounts of media, for example the analysis of cytokine secretion profiles. Larger vessels also limit the number of experimental replicates (low throughput) to be run concurrently which ultimately requires more time for experimental completion with sufficient statistical relevance and will eliminate batch-to-batch discrepancies between samples. ...
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The first experiments using machines and instruments to manipulate gravity and thus learn about its impact to this force onto living systems were performed by Sir Thomas Andrew Knight in 1806, exactly two centuries ago. What have we learned from these experiments and in particular what have we learned about the use of instruments to reveal the impact of gravity and rotation on plants and other living systems? In this essay I want to go into the use of instruments in gravity related research with emphases on the Random Positioning Machine, RPM. Going from water wheel via clinostat to RPM, we will address the usefulness and possible working principles of these hypergravity and mostly called microgravity, or better, micro-weight simulation techniques.
Article
The mitogenic activation of human lymphocytes resuspended in vitro is dramatically reduced in microgravity. As cell-cell contacts are one of the elements essential for activation, the behaviour of human leukocytes (mainly lymphocytes and monocytes as accessory cells) in the presence of the mitogen concanavalin A was studied in the centrifuge microscope NIZEMI at 0 × g. Aggregates (formed by intercellular bindings of membrane glycoproteins via the tetravalent α-glucoside ligand concanavalin A) were found at 0 × g as well as at 1 × g already 12 h after the addition of the mitogen. In general, the aggregates observed at 0 × g after an incubation time of 46 and 78 h were smaller than the corresponding aggregates in the ground control. The findings are of primary importance since they confirm the indirect evidence we had from earlier Spacelab experiments and demonstrate that cell-cell contacts are occurring also in microgravity. In addition, single cells in 0 × g show a significant higher locomotion velocity than the cells at 1 × g. The fact that the locomotion capability is not decreased during the 78-h incubation with concanavalin A provides further evidence that the cells are not proceeding through the cell cycle.
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The human cell lines FTC-133 and CGTH W-1, both derived from patients with thyroid cancer, assemble to form different types of spheroids when cultured on a random positioning machine. In order to obtain a possible explanation for their distinguishable aggregation behaviour under equal culturing conditions, we evaluated a proteomic analysis emphasising cytoskeletal and membrane-associated proteins. For this analysis, we treated the cells by ultrasound, which freed up some of the proteins into the supernatant but left some attached to the cell fragments. Both types of proteins were further separated by free-flow IEF and SDS gel electrophoresis until their identity was determined by MS. The MS data revealed differences between the two cell lines with regard to various structural proteins such as vimentin, tubulins and actin. Interestingly, integrin α-5 chains, myosin-10 and filamin B were only found in FTC-133 cells, while collagen was only detected in CGTH W-1 cells. These analyses suggest that FTC-133 cells express surface proteins that bind fibronectin, strengthening the three-dimensional cell cohesion.
Article
Hyaluronic acid (HA), an immunoneutral polysaccharide that is ubiquitous in the human body, is crucial for many cellular and tissue functions and has been in clinical use for over thirty years. When chemically modified, HA can be transformed into many physical forms-viscoelastic solutions, soft or stiff hydrogels, electrospun fibers, non-woven meshes, macroporous and fibrillar sponges, flexible sheets, and nanoparticulate fluids-for use in a range of preclinical and clinical settings. Many of these forms are derived from the chemical crosslinking of pendant reactive groups by addition/condensation chemistry or by radical polymerization. Clinical products for cell therapy and regenerative medicine require crosslinking chemistry that is compatible with the encapsulation of cells and injection into tissues. Moreover, an injectable clinical biomaterial must meet marketing, regulatory, and financial constraints to provide affordable products that can be approved, deployed to the clinic, and used by physicians. Many HA-derived hydrogels meet these criteria, and can deliver cells and therapeutic agents for tissue repair and regeneration. This progress report covers both basic concepts and recent advances in the development of HA-based hydrogels for biomedical applications.