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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,

Z¨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

0cos(ωα·t+α0)sin (ωα·t+α0)

0−sin (ωα·t+α0)cos (ωα·t+α0)

·⎡

⎣

cos ωβ·t+β00−sin 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 4.5−cos (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

2−rZ,local ·sin(2·ω·t)

2

rX,local ·2·cos (ω ·t) −rY,local −rZ,local ·2·sin (ω ·t)

−rX,local ·sin(2·ω·t)

2−rZ,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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