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MORPHOLOGY OF OSTEOCYTE CELLS IN

NORMAL AND HYPER-GRAVITY

Huan Yuan

BEng (Hons)

Submitted in fulfilment of the requirements for the degree of

Master of Engineering (Research)

Chemistry, Physics, Mechanical Engineering

Faculty of Science and Engineering

Queensland University of Technology

04/2013

Morphology of osteocyte cells in normal and hyper-gravity i

Keywords

Cellular morphology

Empirical model

Hyper-gravity

Image-analysis

Osteocyte cell line (MLO-Y4)

Quantitative study

Morphology of osteocyte cells in normal and hyper-gravity ii

Abstract

Osteocyte cells are the most abundant cells in human bone tissue. Due to their

unique morphology and location, osteocyte cells are thought to act as regulators in

the bone remodelling process, and are believed to play an important role in

astronauts’ bone mass loss after long-term space missions. There is increasing

evidence showing that an osteocyte’s functions are highly affected by its morphology.

However, changes in an osteocyte’s morphology under an altered gravity

environment are still not well documented.

Several in vitro studies have been recently conducted to investigate the

morphological response of osteocyte cells to the microgravity environment, where

osteocyte cells were cultured on a two-dimensional flat surface for at least 24 hours

before microgravity experiments. Morphology changes of osteocyte cells in

microgravity were then studied by comparing the cell area to 1g control cells.

However, osteocyte cells found in vivo are with a more 3D morphology, and both cell

body and dendritic processes are found sensitive to mechanical loadings. A round

shape osteocyte’s cells support a less stiff cytoskeleton and are more sensitive to

mechanical stimulations compared with flat cellular morphology. Thus, the relative

flat and spread shape of isolated osteocytes in 2D culture may greatly hamper their

sensitivity to a mechanical stimulus, and the lack of knowledge on the osteocyte’s

morphological characteristics in culture may lead to subjective and non-

comprehensive conclusions of how altered gravity impacts on an osteocyte’s

morphology.

Through this work empirical models were developed to quantitatively predicate

the changes of morphology in osteocyte cell lines (MLO-Y4) in culture, and the

Morphology of osteocyte cells in normal and hyper-gravity iii

response of osteocyte cells, which are relatively round in shape, to hyper-gravity

stimulation has also been investigated.

The morphology changes of MLO-Y4 cells in culture were quantified by

measuring cell area and three dimensionless shape features including aspect ratio,

circularity and solidity by using widely accepted image analysis software (ImageJTM

).

MLO-Y4 cells were cultured at low density (5×103 per well) and the changes in

morphology were recorded over 10 hours. Based on the data obtained from the

imaging analysis, empirical models were developed using the non-linear regression

method. The developed empirical models accurately predict the morphology of

MLO-Y4 cells for different culture times and can, therefore, be used as a reference

model for analysing MLO-Y4 cell morphology changes within various

biological/mechanical studies, as necessary.

The morphological response of MLO-Y4 cells with a relatively round

morphology to hyper-gravity environment has been investigated using a centrifuge.

After 2 hours culture, MLO-Y4 cells were exposed to 20g for 30mins. Changes in

the morphology of MLO-Y4 cells are quantitatively analysed by measuring the

average value of cell area and dimensionless shape factors such as aspect ratio,

solidity and circularity. In this study, no significant morphology changes were

detected in MLO-Y4 cells under a hyper-gravity environment (20g for 30 mins)

compared with 1g control cells.

Morphology of osteocyte cells in normal and hyper-gravity iv

Table of Contents

Keywords..............................................................................................................................i

Abstract ...............................................................................................................................ii

Table of Contents ................................................................................................................ iv

List of Figures ..................................................................................................................... vi

List of Tables ...................................................................................................................... ix

List of Abbreviations............................................................................................................ x

Statement of Original Authorship ........................................................................................ xi

Acknowledgements ............................................................................................................ xii

Publications ......................................................................................................................xiii

Chapter 1: Introduction ......................................................................................... 1

1.1 Research Background & Motivations.............................................................................. 1

1.2 Project Aims .................................................................................................................. 4

1.3 Thesis Outline ................................................................................................................ 4 1.3.1 Chapter 2: Literature Review ............................................................................. 4 1.3.2 Chapter 3: Quantitative Morphology Study on Osteocyte Cells .......................... 4 1.3.3 Chapter 4: Osteocyte Cells under Hyper-gravity Stimulation .............................. 5 1.3.4 Chapter 5: Conclusions and Future Works ......................................................... 5

Chapter 2: Literature Review ................................................................................ 6

2.1 Osteocytes as Descendants of Osteoblasts ....................................................................... 6

2.2 The Function of Osteocyte Cells ..................................................................................... 7 2.2.1 Mechanosensation of Osteocyte Cells ................................................................ 7 2.2.2 Mechanotransdution of Osteocyte Cells ........................................................... 12

2.3 Osteocyte Cell Models: Osteocyte-Like Cell Line (MLO-Y4) ....................................... 15

2.4 Hypo- and Hyper-gravity Simulation Technologies ...................................................... 16

2.4 Response of Osteocyte Cells to Altered Gravity ............................................................ 20

2.5 Osteocyte Cell Morphology, Function and Mechanical Properties ................................. 22

2.6 Quantitative Cell Morphology Analysis ........................................................................ 23

Chapter 3: Quantitative Morphology Study on Osteocyte-Like Cell Line (MLO-

Y4)…………………………………………………………………………………..29

3.1 Introduction .................................................................................................................. 29

3.2 Methods ....................................................................................................................... 30 3.2.1 Cell Culture and Fixation ................................................................................. 30 3.2.2 Fluorescence Staining ...................................................................................... 30 3.2.3 Cell Segmentation ........................................................................................... 31 3.2.4 Morphologic Feature Extraction....................................................................... 31 3.2.5 Statistical Analysis .......................................................................................... 36 3.2.6 Curve Fitting ................................................................................................... 36

Morphology of osteocyte cells in normal and hyper-gravity v

3.3 Results ......................................................................................................................... 38 3.3.1 Cell Area & Culturing Time............................................................................. 38 3.3.2 Cell Shape & Culturing Time ........................................................................... 38 3.3.3 Model Selection for Curve Fitting .................................................................... 41 3.3.4 Fitted Curves and Developed Emprical Models ................................................ 42

3.4 Discussion .................................................................................................................... 47

3.5 Conclusion ................................................................................................................... 49

Chapter 4: Osteocyte Cells under Hyper-gravity Stimulation ............................ 50

4.1 Introduction .................................................................................................................. 50

4.2 Materials and Methods ................................................................................................. 51 4.2.1 Cell Culture ..................................................................................................... 51 4.2.2 Centrifuge Experiment ..................................................................................... 51 4.2.3 Post-Centrifugation Processing of MLO-Y4 Cells ............................................ 52 4.2.4 Statistics .......................................................................................................... 53

4.3 Results ......................................................................................................................... 53 4.3.1 Cell Area under Hyper-gravity ......................................................................... 53 4.3.2 Cell Shape under Hyper-gravity ....................................................................... 54

4.4 Discussion .................................................................................................................... 56

4.5 Conclusion ................................................................................................................... 59

Chapter 5: Conclusions and Future Works ......................................................... 60

Bibliography .......................................................................................................... 63

Appendix 1: Results from Centrifuge Experiments ............................................ 68

Cell Area under Hyper-gravity ........................................................................................... 68 Experiment One: ...................................................................................................... 68 Experiment Two:...................................................................................................... 69

Cell Shape under Hyper-gravity ......................................................................................... 70 Experiment One: ...................................................................................................... 70 Experiment Two:...................................................................................................... 73

Appendix 2: Preliminary Design for Side-View Optical System ......................... 76

Preliminary Design for Optical System Configurations ....................................................... 76

Preliminary Design for Optical System Dimensions ........................................................... 76

Preliminary Design for Optical Path Modulation ................................................................ 78

Morphology of osteocyte cells in normal and hyper-gravity vi

List of Figures

Figure 1The process of osteoblast differentiation from osteoblast precursors

to mature osteocytes [27] ................................................................... 7

Figure 2 Schematic view of the lacuno-canalicular network (middle),

formed by osteocyte lacunae and interconnecting canaliculi

(left), and of the connected cellular network (right) ............................ 7

Figure 3 Osteocytes modulate bone remodelling at loaded and unloaded

condition through the Sost and Rankl. The thickness of the

lines and arrows in A and B reflects the strength of the effects

[50] .................................................................................................. 12

Figure 4 Schematic overview of the role of osteocytes in the process of

bone remodelling [26] ...................................................................... 15

Figure 5 Random Position Machine [3] ............................................................... 18

Figure 6 Diagram for dropping package. [32] ...................................................... 19

Figure 7 The inertial shear force increase laterally from the centre of

centrifugation [64] ........................................................................... 20

Figure 8 Three families of shapes originating from a circle: (a) ellipses of

various elongation (top), (b) shape having various edge

irregularity (middle), and (c) a combination of the two (bottom)

[67] .................................................................................................. 24

Figure 9 Diagram shows the determination of cells with different aspect

ratio ................................................................................................. 25

Figure 10 Diagram shows cellular boundaries with different roughness ............... 26

Figure 11 Diagram shows the determination of cells with different solidity ......... 27

Figure 12 Diagram shows the determinations of spherity which is sensitive

to most irregularity and elongation ................................................... 28

Figure 13 Cell Segmentation procedure: (a) Original fluorescent image; (b)

Fluorescent image with enhanced contrast; (c) 8-bit image; (d)

Binary mask image .......................................................................... 34

Figure 14 the protocol of determining shape features (a) the original

fluorescent image; (b) Fitted ellipse to extracted cell shape; (c)

Extracted cell area and perimeter; (d) Convex hull of extracted

cell shape. ........................................................................................ 35

Figure 15 Cell Area changes of MLO-Y4 cells measured from two tests ............. 43

Figure 16 Aspect ratio changes of MLO-Y4 cells measured from two tests ......... 44

Figure 17 Solidity changes of MLO-Y4 cells measured from two tests ................ 44

Figure 18 Circularity changes of MLO-Y4 cells measured from two tests ........... 45

Figure 19 MLO-Y4 cell morphological appearance in culture. (a) 1hr; (b)

2hr; (c) 3hr; (d) 4hr; (e) 8hr; (f) 10hr (scale bar:50μm) ..................... 46

Morphology of osteocyte cells in normal and hyper-gravity vii

Figure 20 Four wells located at the centre of the 24-well plate were used ............ 51

Figure 21 (a): Side view of the rotor at speed; (b) Top view of the rotor at

rest. .................................................................................................. 52

Figure 22 Graphical illustration of cell area measured for MLO-Y4 cells

cultured at 20g (blue bar) and 1g (purple bar) for 30 mins from

two experiments. (a) The mean area measured for experiment

sample is 853.52μm2 and 874.06 μm

2 for control sample in

experiment 1 (P=0.388). (b) The mean area measured for

experiment sample is 866.1μm2 and 876.73μm

2 for control

sample in experiment 2 (p=0.669). n=500 ........................................ 53

Figure 23 Graphical illustration of aspect ratio measured for MLO-Y4 cells


two experiments. (a) The mean aspect ratio measured for

experiment sample is 0.843 and 0.851 for control sample in

experiment one (P=0.232). (b) The mean area measured for


experiment two (p=0.846). n=500 .................................................... 54

Figure 24 Graphical illustration of solidity measured for MLO-Y4 cells







Figure 25 Graphical illustration of circularity measured for MLO-Y4 cells







Figure 26 Distribution of cell area measured at 20g ............................................. 68

Figure 27 Distribution of cell area measured at 1g ............................................... 68

Figure 28 Distribution of cell area measured at 1g ............................................... 69

Figure 29 Distribution of cell area measured at 20g ............................................. 69

Figure 30 Distribution of circularity measured at 1g ............................................ 70

Figure 31Distribution of circularity measured at 20g ........................................... 70

Figure 32Distribution of aspect ratio measured at 1g ........................................... 71

Figure 33 Distribution of aspect ratio measured at 20g ........................................ 71

Figure 34 Distribution of solidity measured at 1g ................................................ 72

Figure 35 Distribution of solidity measured at 20g .............................................. 72

Figure 36 Distribution of circularity measured at 1g ............................................ 73

Figure 37 Distribution of circularity measured at 20g .......................................... 73

Morphology of osteocyte cells in normal and hyper-gravity viii

Figure 38 Distribution of aspect ratio measured at 1g .......................................... 74

Figure 39 Distribution of aspect ratio measured at 20g ........................................ 74

Figure 40 Distribution of solidity measured at 1g ................................................ 75

Figure 41 Distribution of solidity measured at 20g .............................................. 75

Figure 42 Over view of the preliminary design for side-view optical system ....... 76

Figure 43 Working distance for side-view optical system .................................... 76

Figure 44 Plastic ruler placed under 40x magnification lens, showing that

the microscope filed is 2mm ............................................................ 77

Figure 45 Preliminary design of the size of the optical system ............................. 77

Figure 46 Optical path length with different refractive index medium ................. 78

Morphology of osteocyte cells in normal and hyper-gravity ix

List of Tables

Table 1 MLO-Y4 cell mean area measured with different culturing time ............. 38

Table 2 Aspect Ratio measured for MLO-Y4 cells in culture from two

experiments. .................................................................................... 39

Table 3 Solidity measured for MLO-Y4 cells in culture from two

experiments. .................................................................................... 40

Table 4 Circularity measured for MLO-Y4 cells in culture from two

experiments ..................................................................................... 41

Table 5 Goodness of fit for cell area in culture .................................................... 41

Table 6 Goodness of fit for shape factor in culture ............................................... 42

Morphology of osteocyte cells in normal and hyper-gravity x

List of Abbreviations

AFM: Atomic force microscope

ATP: Adenosine triphosphate

BSA: Bovine serum albumin

Cx43: Connexion 43

DMEM: Dulbecco’s Modified Eagle medium

ECM: Extracellular matrix

FBS: Fetal bovine serum

GFP: Green fluorescent protein

G6PD: Glucose 6-phosphate-dehydrogenas

LCN: Lacuna-canalicular network

NO: Nitric oxide

P/S: Penicillin/Streptomycin

PFA: Paraformaldehyde

PBS: Phosphate-buffered saline

PKA: Protein kinase A

RANKL: Receptor activator of NFkB ligand

RPM: Random position machine

Morphology of osteocyte cells in normal and hyper-gravity xii

Acknowledgements

First and foremost, I wish to take this opportunity to gratefully acknowledge

the enthusiastic supervision of my principal supervisor, Professor Ted Steinberg,

who was extremely helpful and offered invaluable assistance, support and guidance

during this work. I also would like to express my sincere gratitude to Associate

Professor Yuantong Gu for the technical discussions on the cell morphology

quantitative study and Professor Yin Xiao for his help with cell culture works and

related discussions; without their knowledge and encouragement this study would

not have been successful.

I also extend my thanks to other postgraduates from the Numerical Modelling

Group for sharing literature and providing general advice. Special thanks also go to

Anjali Tumkur Jaiprakash, Dr. Nishant Chakravorty and Dr. Sanjleena Singh for

teaching me to perform cell culture works and for their valuable assistance as well

with all types of technical problems. Further, I would like to thank the Queensland

University of Technology (QUT) for providing a comfortable research environment

and facilities while I completed this project.

Finally, I would like to express my love and gratitude to my beloved

grandparents, parents and my wife, for their understanding, support and

encouragement throughout my candidature.

Morphology of osteocyte cells in normal and hyper-gravity xiii

Publications

This research has resulted in the following fully peer-review paper:

H.Yuan, Y.Xiao, Y.T. Gu, and T. Steinberg, Morphology-based Model for

Predicting Osteocyte-Like Cell Line (MLO-Y4) Growth Process. in 4th

International

Conference on Computational Methods, Australia, Gold Coast, 2012.

Journal paper in preparation:

H.Yuan, Y.Xiao, Y.T. Gu, and T. Steinberg, Morphology of osteocyte cells in normal

and hyper-gravity. (To be submitted to Journal of Bone).

Chapter 1: Introduction 1

Chapter 1: Introduction

1.1 Research Background & Motivations

Cell morphology, one of the most intuitionist characteristics for cell type

identification, is regulated by the interactions between the cytoskeleton, the

membrane and the extracellular environment [1]. Cells of different shape operate

differently in the human body. A round adipocyte allows for maximal lipid storage,

the extended dendrites of nerve cells facilitate electrical and biochemical signal

transmissions, while stellate osteocyte cells are essential for bone remodelling [2-4].

Different cell morphologies are considered to arise from changes in the expression of

integrins, cadherins, and cytoskeletal proteins during stem cell commitment, the

process by which stem cells differentiate into various cell lineages, leading to

different morphologic phenotypes and specialized cellular functions [5]. Intriguingly,

two research groups have recently shown that the various shapes of stem cell can

directly regulate stem cell commitment to different lineages; in other words, cell fate

can be artificially determined through shape-dependent control [2, 6]. These findings

clearly indicate that the function of cells is closely related to their morphology [7].

Likewise, studies conducted in the field of biomechanics have shown that changes in

cell morphology caused by external mechanical loadings can greatly impact on

cellular behaviour including growth, proliferation, differentiation, apoptosis, signal

transduction, gene expression and extracellular matrix remodelling [2, 8-10].

The most common mechanical stimulation which is constantly applied on

living cells throughout their life is gravity. The results from previous studies which

have been carried out on cellular biology in an altered gravity environment have


shown that changes in gravity can have direct influence on cellular proliferation,

differentiation, motility and growth [11-18]. Astronauts have been found to have

significant bone mass loss after long-term space missions, which is considered to be

one of the most common and serious health risks during space activity [12]. Under a

weightless environment, bones no longer have to fight against Earth's gravity during

locomotion and less mechanical strain is then applied to the skeletal system [19]. It

is widely accepted that the reduced strain on bones may lead to the speed of bone

removal outpacing replacement and causing the progressive bone loss seen in long-

term residents of space [20, 21].

Mammalian bones comprise three major cell types including osteoblasts,

osteoclasts and osteocytes [22]. Osteoblasts are responsible for constantly building

new bone, while osteoclasts are continually destroying the old ones. The balance

between the bone formation and resorption is crucial for maintaining bone mass [22].

Daily activities of osteoblasts and osteoclasts are believed to be regulated by

osteocytes, the most abundant cell in bone, which account for 90%-95% of all bone

cells [23, 24]. They are embedded in the hard bone matrix of the lacunae, and form

an intercellular network between neighboring osteocytes and the cells on the bone

surface such as osteoblasts and osteoclasts through their dendritic processes within

narrow bony tubes of caliculi [4, 23]. Osteocytes are thought of as the

mechanosensory cells of the bone tissue. They sense and respond to mechanical

loadings, and accordingly transmit the signals to osteoblasts and osteoclasts through

the osteocyte network, and thus regulate bone remolding [4, 23]. It is believed that

osteocytes are playing a central role in space bone mass loss. However, how

osteocytes respond to altered gravity is still not well documented.


As a result of the rapid technological improvements in microscopy over

recent years, cell morphology has been commonly used as a key parameter for

investigating cellular response to altered gravity environment. However, in culture,

cells exhibit a wide range of shape and appearance. In previous studies, the

morphology changes in osteocyte cells under various gravity levels are mainly

described based on visual inspection, and investigated by comparing the cell area

with control samples, which may lead to subjective and non-comprehensive

conclusions of how altered gravity impacts on osteocyte morphology. Therefore,

quantitative analysis is required for objectively and accurately studying osteocyte

morphology changes under an altered gravity environment. To date, no attempt has

been made to quantify the morphological changes of osteocytes, which grow in

culture.

There is increasing evidence showing that the osteocyte’s function and

mechanical properties are highly affected by its morphology. It was found that

osteocyte cells with a round* cellular morphology support a less stiff cytoskeleton

and are more sensitive to mechanical stimulations compared with flat cellular

morphology [7]. Studies conducted on flat adherent osteocyte cells have shown there

are no significant changes in the morphology of osteocytes under an altered gravity

environment [21, 24, 25]. However, osteocyte cells found in vivo are with a more 3D

morphology. The impact of altered gravity on osteocytes with a relatively round

shape is still poorly understood.

(*The body of the cells spread during cell culture, thus cells under longer

culturing time are thought have a more flat shape comparing with cells which are

cultured for a shorter time. The terms of ‘round’ and ‘flat’ used in this thesis refers to

the shape of cells observed under normal light microscope (2D)).


1.2 Project Aims

This study aims to quantify the morphology of osteocytes in culture for the first

time, and to propose an empirical model based on the collected data to predict the

osteocyte cells’ growth process in culture.

The second aim of this study is to investigate the response of the osteocyte

cells which have a relatively round shape to altered gravity environment. Since it is

not easy to simulate weightlessness on earth, the study will be conducted under a

simulated hyper-gravity environment by using a centrifuge. It is hypothesized that

hyper-gravity often induces the opposite effects to those of microgravity.

1.3 Thesis Outline

The following is a brief synopsis of the chapters to follow:

1.3.1 Chapter 2: Literature Review

This chapter provides a comprehensive review on the functions of osteocyte

cells and the relationship between the osteocyte’s morphology and its functions. This

is then followed by introduction on ground-based altered gravity simulators and a

review of previous morphological studies on osteocyte cells under an altered gravity

environment. A summary of the mathematical shape factors which may be able to be

used to quantify the osteocyte’s morphology is also presented in this chapter.

1.3.2 Chapter 3: Quantitative Morphology Study on Osteocyte Cells

Chapter 3 describes the details of study carried on when quantifying the

morphology of osteocyte cells in culture. Morphology changes of osteocyte cells

recorded for 10 hours in culture, and the consequently developed empirical model are

shown in this chapter.


1.3.3 Chapter 4: Osteocyte Cells under Hyper-gravity Stimulation

In this chapter, osteocytes with round shape morphology were applied with 20g

centrifugal force for 30 mins, to investigate the morphology changes under hyper-

gravity environment. The response of osteocyte cells, in terms of morphological

change, including cell area, circularity, aspect ratio and solidity are investigated.

1.3.4 Chapter 5: Conclusions and Future Works

The last chapter re-summarizes the completed work and research findings.

Based on the knowledge gained from this study, the potential future research

direction of the gravitational biology is also proposed in this chapter.

Chapter 2: Literature Review 6

Chapter 2: Literature Review

To ascertain the significance and original contribution of the proposed

research, a comprehensive literature review is performed in Chapter 2. This chapter

summarizes the nature function and the role of osteocyte cells in bone tissue and how

the cellular morphology changes affect their function and mechanical properties.

This is followed by a brief introduction on the application of the most frequently

used gravity stimulation facilities. Previous space biological studies conducted on

osteocyte cells are then shown next. Finally, mathematical shape factors which are

commonly used in quantitative morphology analysis are outlined in this chapter.

2.1 Osteocytes as Descendants of Osteoblasts

The osteocyte cells comprise 90%-95% of the whole bone cell population in

the human body [26]. They are descended from mesenchymal stem cells through

osteoblast differentiation. As osteoblasts become embedded in the newly formed

bone matrix, they continue their differentiation and transform finally into osteocytes.

This process involves several differentiation steps including a reduction of cell

organelles, changes in the cell mechanical properties and cellular morphology.

Osteoblast cells undergo a dramatic transformation from a polygonal cell to a cell

extending dendrites toward the mineralizing front during differentiation. Dendritic

processes are found extending to either the vascular space or bone surface in mature

osteocytes (Figure 1) [27-29].


Figure 1The process of osteoblast differentiation from osteoblast precursors to mature osteocytes [27]

2.2 The Function of Osteocyte Cells

2.2.1 Mechanosensation of Osteocyte Cells

Bone remodelling and functional adaption are generally considered to be

achieved by concerted action of osteoblasts and osteoclasts [30]. As the most

abundant cells in bone tissue, osteocyte cells are believed to be involved in these

bone homeostasis processes as dominating regulatory cells. Osteocyte cells are

embedded in the calcified bone matrix, where osteocyte cell body resides in the

fluid-filled spaces known as lacunae and the cell dendritic processes pass through the

bone in thin canals called canaliculi, forming a lacuna-canalicular network (LCN).

This network connects neighbouring osteocyte cells and cells on the bone surface,

such as osteoblasts, osteoclasts and bone lining cells (Figure2) [4, 31].

Figure 2 Schematic view of the lacuno-canalicular network (middle), formed by osteocyte lacunae

and interconnecting canaliculi (left), and of the connected cellular network (right)


Aarden et al. theorized that cells dispread throughout the matrix can perform

more productively in detecting loading-induced strain than cells located on the bone

surface, such as osteoblasts, osteoclasts and bone lining cells [30]. In accordance

with this theory, as the only cells located at bone matrix, osteocytes are postulated as

mechanosensory cells in bone tissue. The advantage of osteocyte cells in sensing

mechanical stimulations was proved by Mullerder and his colleagues. In order to

evaluate the best candidate for mechano-sensor in bone, Mullerder et al. [32]

investigated the mechanical sensibility of osteocytes and bone lining cells. By

monitoring the structural changes in both the proposed bone lining cell and osteocyte

models under external loading, they concluded that osteocyte cells are several orders

of magnitude more sensitive to mechanical stimulations than bone lining cells.

Several reports from the group of Lanyon have further confirmed the

sensitivity of osteocytes to mechanical loading. In vivo experiments that were

conducted on isolated turkey ulna, embryonic chicken tibia-tarsi and cores of adult

dog cancellous have shown that intermittent loading which applied at the

physiological strain magnitude (varied between 500-2,000 microstrain), produces

rapid strain-related changes in osteocyte’s metabolic activities by introducing the

increased activity of glucose 6-phosphate-dehydrogenas(eG 6PD) and a loading-

related rise in 3H-Uridine uptake in osteocyte cells, separately [33-36].

Previous studies quantified the magnitude of local strain. Bone routinely

experiences mechanical strain between 1000-3,000 microstrain [30, 37]. It is not

clear what is the allowable strain magnitude osteocytes can withstand, however, it is

believed that the damage and resorption of bone occurs if strains exceed 3,500

microstrain, and fracture of bone occurring more than 4,000 microstrain [37].


In vitro experiments found that the minimum strain level to introduce an

appreciable biochemical response in osteocyte cells is 10,000 microstrain, which

would damage the extracellular bone matrix. Thus, it is believed that some form of

strain amplification occurs during strain transfer to osteocyte in vivo [37]. With the

applied load 2,000 microstrain on bone, the measured perilacunar strain is 35,000

microstrain [37].

The loading frequency and number of loading cycles affect the biomechanical

response of osteocytes is not well documented. One Low-Magnitude, High-

Frequency (LMHF) vibration experiment showed that osteocytes are sensitive to this

vibration (magnitude: 0.39g at the frequency 30, 60, 90 Hz) [38]. Since the effects of

loading frequency and number of loading cycles are not related to current work, no

further detailed investigation has been made.

The mechanism of how osteocytes sense the mechanical loads on bone and

how the mechanical loading-induced signal activates osteocyte cells are not yet

completely understood [26]. However, biomechanical studies conducted on osteocyte

cells during the past decade, have shown the high sensitivity of osteocytes to various

mechanical loading-induced physical signals, with changes in the cell structure,

signalling molecules’ secretion and cell metabolic activities. Load that is placed on

bone is found pressurizes the interstitial fluid surrounding the osteocytes before the

fluid is driven to flow. Load in the form of hydraulic pressure, tissue strain and fluid

shear stress are then successively applied on osteocyte cells [39]. Osteocytes were

found particularly sensitive to fluid shear stress. A number of theoretical and

experimental studies have put forth evidence suggesting that rather than hydrostatic

pressure, interstitial fluid flow and direct cell strain are the most likely mechanism

for activating mechanosensation in osteocyte cells. The less response of osteocytes to


hydrostatic stress found in vitro could be due to the low magnitude of hydrostatic

pressure applied (i.e. 13kPa) in the experiment, comparing with the hydrostatic

pressure applied on osteocytes in vivo [26, 40-42]. Zhang[43] estimated that the fluid

component could carry as much as 12% of the applied mechanical load and produce

peak pressures of 2-3MPa. More recently, Gardinier et al.[41] have predicted that

magnitude of the pressure experienced by osteocytes in vivo could reach up to 5MPa.

Research conducted by Liu et al. in 2010 indicated that cyclic hydraulic pressure of

68kPa can modulate signalling molecule production in cells of the MLO-Y4

osteocyte-like cell line, suggesting that fluid pressure may be also a potent stimulus

to the bone and may play a role in regulating bone remodelling in vivo [39].

A well-known early response to mechanical stimulation of osteocytes, both in

vitro and in vivo, is an increase in intracellular calcium concentration [39, 44].

Calcium ions are released from internal stores and passing through ion channels in

the plasma membrane of osteocytes [41, 44]. Calcium is the essential element

required for bone formation; the increased calcification activates many downstream

signalling cascades such as protein kinase C and phospholipase A2, and is necessary

for activation of calcium dependent proteins, such as the constitutive forms of nitric

oxide synthase (NOS). The activation of phospholipase A2 also causes the activation

of releasing prostaglandin E2 (PGE2), one of the substances that can enhance the new

bone formation [39, 45]. Prostaglandins are abundantly produced by osteocytes; they

play a key role in the bone formation response to mechanical loading in vivo. A

rapidly increased prostaglandin production in response to mechanical loading is

observed in several in vitro osteocytes studies [46-48].

A wide range of studies have clearly demonstrated that mechanical stimulation,

both via direct manipulation of cells and via application of a fluid flow to cultured


osteocytes increases the nitric oxide (NO) production [49]. NO has been shown to

modulate the bone remodelling process by promoting bone formation and inhibiting

osteoclast activities[27]. Previous results from the in vitro fluid flow stimulation

studies suggest that NO is a mediator of mechanical effects in bone, and can enhance

PGE2 release in bone tissue [50, 51].

The inhibition of bone formation and activation of osteoclasts are mainly

achieved through the induction of sclerostin and the receptor activator of NFkB

ligand (RANKL) in osteocytes under physiological loading condition [52].

Sclerostin is highly expressed in osteocytes and encoded by the SOST gene. Under

the unloading condition, the increased expression of sclerostin inhibits bone mass

accrual by reducing the activity of osteoblasts [53]. On the contrary, the mice lacking

scelrostin used in Nulend’s experiment, exhibit an increased bone mass, resembling

the human condition of sclerosteosis [42]. Sclerostin was reported down-regulated in

bone cells under mechanical stimulation [42, 52].

As the essential factor for osteoclast formation [54], RANKL inhibits the

increase of bone mass by encouraging the formation osteoclasts. Compared with

osteoblasts and bone marrow stromal cells, osteocytes has been identified as the

major source of RANKL for bone remodelling [54, 55]. Moriishi et al. have recently

found the osteocyte network inhibits osteoblast function and stimulates

osteoclastogensis at physiological loading condition [52]. Both in vitro and in vivo

studies have confirmed the fact that osteocytes produce osteoclast-formation factors

in the absence of external mechanical loading, but not after being subject to a

mechanical stimulus [42]. The study conducted on wild-type mice showed both Sost

and RANKL expressions in osteocytes were significantly up-regulated in the

unloaded condition. Osteocytes further augment the inhibitory effect on osteoblasts


through the induction of Sost and the stimulatory effect on osteoclastogenesis

through the induction of RANKL in the unloaded condition (Figure3) [52]. In

addition, it was found that mice lacking RANKL in osteocytes are protected from

bone loss caused by unloading [54].

Figure 3 Osteocytes modulate bone remodelling at loaded and unloaded condition through the Sost

and Rankl. The thickness of the lines and arrows in A and B reflects the strength of the effects [52]

2.2.2 Mechanotransdution of Osteocyte Cells

As mentioned in last section, osteocyte cells act as a mechanosensor in bone

tissue and respond to mechanical loads by producing biochemical molecules such as

calcium ions, prostaglandins, NO, sclerostin and RANKL, which are considered as

modulators for bone remodelling. To obtain a meaningful change of the existing

bone tissue, osteoblasts and osteoclasts require information on local needs of tissue

increase or tissue reduction, depending on the extracellular mechanical environment

[30]. As the most abundant cells in bone tissue, osteocytes are thought not only


responsible to sense mechanical strain, but also to serve as the messenger to send

converted biochemical signals of bone resorption or formation [4, 31]. This raises an

important issue, that is, to ascertain which part of the osteocytes, its process or cell

body is mechanosensing organelle, and which part is responsible for signal

transduction.

To address this question experimentally, Burra and his research team [4]

isolated the dendrites from the osteocyte cell body using a Transwell filter system;

and investigated the osteocyte’s response to mechanical stimulation through the

determination of connexin 43 hemichannel activity, which is the pathway involved in

communicating cellular signals with extracellular environment. Hemichannel

openings were detected in a cell body when either cell body or dendrites was

mechanically stimulated. However, no significant hemichannel activities were

induced in cell dendrites when mechanical loading was applied to either cell body or

dendritic side. Their results provided a direct evidence suggesting that both cell body

and dendrites are able to sense the external mechanical stimulation and the cell

dendrites are playing a specific role in transducing mechanical-induced signals[4].

Consistently, a study conducted by Adachi et al. showed a higher intracellular

calcium response in osteocyte’s dendritic processes compared to cell bodies under

mechanical stimulation. They concluded that mechanosensitivity of the cell

dendrites was higher than that of the cell body [56].

Cellular signals transduction from deeply embedded osteoytes to bone surface

cells is made possible by the unique three-dimensional morphology of the

lacunocanalicular network formed by osteocytes dendritic processes. Osteocyte’s

processes are radiated in different directions and directly connected with each other

through the gap junctions, formed by proteins called connexions, which are also


known as connexons if they are in hmexameric form [42]. Two connexons present on

adjacent cells dock onto each other to form a gap junction channel which plays an

important role in conveying cellular signals[42]. The canliculi, where the cell

processes are resided is filled with a proteoglycan rich matrix with tethering fibre

that attach the processes to the canalicular wall [42]. The interaction of the

pericellular matrix and the osteocyte cellular process could amplify the physiological

amplitude of loads to the bone tissue, thus producing sufficient levels of force to

induce cellular response [23].

In the original fluid flow hypothesis, loading-induced fluid flow through the

canalicular network has been thought to cause a fluid shear stress on the cell process

membrane, which is considered as the stimuli to activate osteocytes [42]. Previous

research on MLO-Y4 cells showed an increase in the expression of E11, the protein

required for osteocyte cell process elongation, under fluid flow shear stress [57].

Interestingly, the highest expression of E11 was detected in a region of potential

bone remodelling, not in regions of maximal stain, suggesting that dendrite

elongation may be occurring during bone remodelling process [57]. It is unknown

exactly how the changes in the length of dendtritic process will alter the function of

osteocyte cells, but it is clear that changes in ostecoyte cell dendritic phenotype could

have a dramatic effect on the interaction between adjacent ostoecytes and the

structure of LCN, which may lead to the modification in mechanotransduction of

osteocyte cells.

In summary, osteocyte cells are highly sensitive to mechanical loadings. By

translating the mechanical strain into biomechanical signals, osteocytes are playing

as the key regulator for osteoblast and osteoclast activity during the bone

remodelling process. Both cell body and dendritic process are found responsible for


sensing mechanical strain, and cell process is believed to also act as the

mechanotransducer in osteocytes. The function of osteocyte cells is thought to be

highly related to their unique location in bone and their morphology. The effect of

cellular morphology changes on osteocyte’s mechanical property has already been

reported, and will be discussed in the later section of this chapter. Changes in cell

morphology such as the area of cell body and the development of cell process may be

able to lead to the changes in mechanosensation and mechanotransduction of

osteocytes. The proposed study on investigating osteocytes morphology changes in

hyper-gravity can provide valuable insights into how the functions of osteocytes are

going to change in space. A schematic overview of the role of osteocytes in bone

remodelling process is shown below (Figure 4).

Figure 4 Schematic overview of the role of osteocytes in the process of bone remodelling [26]

2.3 Osteocyte Cell Models: Osteocyte-Like Cell Line (MLO-Y4)

While osteocytes are the most abundant cell type in bone tissue, it is also the

type of cell of which we know the least. Over the last two decades, osteoclasts and


osteoblasts have been extensively studied. However, only a few studies have

successfully been conducted to investigate the function and mechanical property of

osteocyte cells by using primary osteocyte cells. This is mainly due to the difficulties

in isolating the osteocytes from the mineralized matrix and maintaining the sufficient

numbers of osteocytes for many in vitro biomechanical studies [3]. To compensate

for these difficulties, scientists have attempted to create osteocyte cell lines by using

a transgenic technique to replace primary osteocyte cells in biomechanical studies.

To date, there are two cell lines with osteocyte characteristics that have been

successfully developed. One model is known as HOB-01 C1 human bone cell line

which is a temperature-sensitive cell line, expressing the property of pre- or called

early osteocytes. Another model is the MLO-Y4 cell line. This cell line was derived

from a transgenic mouse in which the immortalizing T-antigen was expressed under

control of oseocalcin promoter.

MLO-Y4 cell line is the most successful osteocyte cell line developed so far

which exhibits the properties of osteocytes including high expression of osteocalcin,

connexion 43 and antigen E11 proteins and low expression of alkine phosphatease.

Furthermore, MLO-Y4 cells retain a dendritic morphology, similar to that observed

in primary osteocyte cultures. Thus, the MLO-Y4 cell line is now been widely used

to study the function and mechanical properties of osteocyte cells in biomechanical

and biological studies, in vitro. In this study, MLO-Y4 cells will be used to

morphology quantification and hyper-gravity study.

2.4 Hypo- and Hyper-gravity Simulation Technologies

A gravitational biology study is made possible through a number of space-,

flight- and ground- based facilities [58]. Conducting reduced gravity tests by means

of a spaced-based facility such as space shuttle or international space station (ISS) is


difficult and extremely expensive [58, 59]. Several cell biology experiments

conducted in space have failed in collecting results due to unforeseen hardware

failures [60, 61]. Therefore, instead of sending samples to space, researchers are

creating simulated hypo- and hyper-gravity using ground- based facilities such as

magnetic levitation technology, random position machines (RPM), dropping towers

and centrifuges.

A complex biological system, such as a living cell, is diamagnetic, which

means repelled by a magnetic field. Thus the technology of magnetic levitation is

able to provide reduced gravity simulation by creating a stable levitation to living

cells through exerting a magnetic force on the system to counterbalance the

gravitational force [62]. Magnetic levitation can create various gravity levels by

altering the magnetic field strength, and allowing the study of relatively fast process

because of the ability to instantly create the reduced gravity simulation [62].

However, the cellular response observed in magnetic levitation experiments may not

solely be caused by reduced gravity but also by the magnetic field applied [62].

Therefore, further investigation of the application of magnetic levitation in

microgravity study is required.

Random position machines (RPM) are the most frequently used ground-based

reduced gravity simulator (Figure 5). This system is constructed by two separate

rotating frames (inner and outer) which are respectively driven by two motors and

rotate independently at random speeds and directions [63, 64]. The orientation of the

experimental sample mounted at the centre of the inner frame, relative to the

gravity’s vector, is continuously changed during rotating. When the changes are

faster than the sample’s response time to gravity, the effect of gravity on the

experiment sample is considered to be eliminated [65]. Therefore, rotating speed is a


crucial factor for RPMs, and is normally applied at the speed between 60˚/s-120˚/s

[62]. Reduced gravity tests conducted on living cells by using RPMs can last for days

and even weeks, however, providing the required living environment such as

temperature (37˚C) and 5% carbon dioxide supply for these cells is always the

challenge in a long-term reduced gravity study [62].

Figure 5 Random Position Machine [3]

A dropping tower is another ground-based microgravity research facility. The

dropping tower that is available at Queensland University of Technology is 20

metres high and able to generate 2.0 seconds of high quality reduced gravity by free-

falling a dropping package down a vertical corridor. The dropping package contains

the experiment platform which is protected from air resistance by being enclosed

inside the drag shield. The experiment platform is not attached to the drag shield, but

instead falls independently within the enclosed space (Figure 6). All samples

mounted on the platform will experience reduced gravity for approximately 2.0

seconds, then followed by an approximately 0.25 seconds deceleration caused by the

airbag that is designed for safely decelerating the drop package at the bottom of the


tower [58]. This dropping tower has been mainly used to study the effects of

microgravity on physical phenomena such as fluid dynamics and combustion safety.

Figure 6 Diagram for dropping package. [32]

A centrifuge is the most widely available facility which can be used to simulate

hyper-gravity environments to study the responses of living cells to altered gravity.

To conduct hyper-gravity experiments successfully, it is important to fully

understand all possible influences of the acceleration which may cause crucial

differences between the sample exposed to hyper-gravity environment and the 1g

control. Inertial shear forces are caused by the acceleration act perpendicular to the

gravity acceleration vector. The level of inertial shear force that is applied on an

adherent cell layer depends on the radius of the centrifuge and the location of the

cells within the sample surface area [66]. Adherent cells attached to a flat surface

will experience the minimum inertial shear force when located at the point where the

radius is perpendicular to the monolayer surface [66]. In addition, inertial shear force

is found greater in a centrifuge with a smaller radius (See Figure 7) [66]. Another

phenomenon which is also influenced by gravity is hydrostatic pressure. Hydrostatic

pressure is proportional to gravity and height of the liquid (culture medium) [67].


Both inertial shear force and hydrostatic pressure need to be properly controlled

when conducting hyper-gravity experiments on adherent cells.

Figure 7 The inertial shear force increase laterally from the centre of centrifugation [66]

2.4 Response of Osteocyte Cells to Altered Gravity

In order to understand the effects of altered gravity on osteocyte cells, several

studies have already been conducted so far. The first attempt in conducting

microgravity research on osteocytes by using spaceflight, failed due to an

unforeseen hardware complication [60]. By using ground- and flight- based testing

facilities, Shang and his group have recently conducted some studies on MLO-Y4

cells [21, 24, 25]. However, the results shown in their reports are inconsistent. The

first ground-based experiment was conducted by using diamagnetic levitation

technology. A significant decrease in cellular morphology such as cell area, nucleus

size, the number of dendrites and the expression of focal adhesion proteins were

observed after 48 hours diamagnetic-levitation (μg), in addition, the modification in

cytoskeleton organization was also reported. However, no significant changes in cell


morphology, cytoskeleton structure and focal adhesion protein expression were

found under hyper-gravity (2g) stimulation. By comparing the response of MLO-Y4

cells cultured at normal gravity and those applied with magnetic-induced 1g force,

they concluded that there is no magnetic effect on MLO-Y4 cells and all the changes

detected in osteocyte cells are caused by the magnetic-induced microgravity[24].

Another study from this group was started in the year of 2010, using the ZERO-G

A300 aircraft. The altered gravity environment was achieved through the parabolic

flight, where MLO-Y4 cells underwent approximately 22 seconds microgravity (0.5g)

and two hyper-gravity (1.8g) periods before and after each parabola; in total 30

parabolic manoeuvers were performed [21]. Samples collected from parabolic flight

have shown the reduced expression of the connexin 43 proteins and the re-organized

cellular cytoskeleton structure. Interestingly, no significant change in MLO-Y4 cell

area was found in this study [21] in that the cell area of MLO-Y4 reported in this

paper (approx 230 μm2) is dramatically smaller than those measured in the previous

study (approx 3900μm2). More recently, the response of MLO-Y4 cells to a

clinorotation-induced weightless environment has been investigated. No significant

changes in cell morphology were found and the re-organization of cellular

cytoskeleton was only detected after 48hrs of exposure of weightlessness.

Furthermore, the secretions of nitric oxide and prostaglandin E2 were found

decreased after 12hrs weightless stimulation[25].

It is unclear what the reason is for the delayed response of MLO-Y4 cells under

clinostat-induced weightlessness and why there is a dramatic difference between the

cell areas reported from diamagnetic levitation and parabolic flight studies. Based on

the information obtained from the diamagnetic levitation experiment (sample size

10), the inconsistent results may have been caused by the small sample size.


2.5 Osteocyte Cell Morphology, Function and Mechanical Properties

As discussed previously, the unique location and the dendritic cellular

morphology make the osteocyte cells the ideal mechanosensor and

mechanotransducer in bone. It is widely accepted that external mechanical forces

make a direct effect on cytoskeletal structure and thus cell morphology. This implies

that the morphology of osteocytes is determined by their extracellular mechanical

environment; osteocyte cells located in the region which is regularly loaded should

have a different morphology than those found in marginally loaded bones [68]. This

was confirmed by Vatsa al et., who conducted a three-dimensional imaging study on

osteocyte cells located in different parts of the bodies of mice. It was observed that

osteocytes in fibular bone were stretched and aligned along the principal loading

direction, whereas osteocytes in calverial bone had a more spherical shape and were

randomly aligned [68].

In vitro study on MLO-Y4 cells revealed that osteocytes in different

morphology have different mechanical properties [7]. The elastic constant of flat

adherent MLO-Y4 osteocytes was found to be near ten times higher than the elastic

constant measured in the round partially adherent MLO-Y4 cells. Meanwhile, high

NO release from round suspended MLO-Y4 osteocytes was detected when

stimulated with a force of ~5pN. In contrast, lesser NO production was released from

flat adherent MLO-Y4 cells under the force of 150-550-pN. These data suggest that

osteocyte cells in round morphology support a less stiff cytoskeleton configuration

and are much more sensitive to mechanical stimulations compared with flat cellular

morphology[7].

Based on these findings, the relatively round osteocyte morphology observed

by Vasta et al. in calvaria should be more mechanosenstive than fibular oteocytes,


which provide a possible explanation of efficient physiological load bearing for the

maintenance of calvarial bone despite its condition of relative mechanical disuse [68].

In addition, it may also partly explain the reason why no significant morphology

changes in osteocyte cells were observed in the previously discussed microgravity

experiments, where the MLO-Y4 cells were cultured in 2D on a flat surface.

However, osteocytes with a more 3D morphology, such as occurs in vivo, may be

able to sense and respond to such small loading [42].

2.6 Quantitative Cell Morphology Analysis

The term of cell morphology can be interpreted as the description of both

cellular size and shape. Cellular size can be easily presented as cell area in 2-D or

volume of the cell in three-dimensional circumstance. The major difficulty in cellular

morphology quantification is to accurately describe cell shape; this is mainly caused

by the lack of a precise, universal definition of the term [69]. In order to correctly

quantify the shape of living cells, the ideal shape descriptor should be firstly

independent to the size of the cell where values are kept unaltered in the case of cells

of the same shape but different size. Secondly, they need to be able to quantitatively

show how far a given shape deviates from a model, or theoretically ideal shape.

Lastly they should be sensitive to particular shape changes that occur in a process

under consideration (i.e. cell culture or under mechanical stimulation) [69].

The parameters applied extensively in cellular shape quantification in

biomechanical studies are known as shape factors, which are sensitive to the changes

in shape [21, 24, 25, 70, 71]. It is important to define a universal shape factor that is

applicable in all the type of cellular shape analysis. A sphere is a good reference

shape to discuss properties of shape factor because it is the simplest geometrical

model for three-dimensional objects [69]. Images of the spheres are in the form of


circles. Therefore, numerous shape factors are used in images analysis to determine

how much a given shape differs from a circle [69]. However, the name and definition

of shape factors vary with different image analysis software, which always causes

some confusion [72].

The shapes observed in living cells can deviate significantly from a circle, but

finding a ‘reference’ circle is intuitively easy, as illustrated using the series of

sketches shown in figure 8. Elongation, irregularity and composition are illustrated in

Fig 8(a), (b), and (c), respectively, which are considered as three essential cellular

shape change models during cell growth [69].

Figure 8 Three families of shapes originating from a circle: (a) ellipses of various elongation (top), (b)

shape having various edge irregularity (middle), and (c) a combination of the two (bottom) [69]

Cell elongation process can be defined by the shape factor called aspect ratio. It

is mathematically defined as (Equation 2.1):


where a and b are the length and width of the minimum bounding rectangle.

Aspect ratio reaches a minimum value of 1 for an ideal circle and has higher values

for elongated shapes:

Figure 9 Diagram shows the determination of cells with different aspect ratio

The parameter of a which is shown above can also be defined as the maximum

Feret diameter, while b is the Feret diameter measured perpendicular to it, or

alternatively the length of the major and minor axis of best fitted ellipse, depending

on the method used in the different image analysis software. These three sets of

values used to determine elongation can produce slightly different values of the

shape factor due to the digital nature of computer image, but in general, they all can

quantitatively show the degree of the elongation in cells [69].

The irregularity can be quantitatively described by the number of shape factors

including circularity, convexity and solidity. Circularity is one of the most popular

shape factors used in numerous papers. It is also known as roundness in some papers,

where it has been used to determine the degree of the cellular elongation. However,

the name of the roundness may sometimes mislead people, since circularity is found

to be much more sensitive to any irregularity than to elongation [69]. Considering the

natural cell shape, especially for bone cells, they are highly irregular. Thus, in the

cellular morphological analysis study; the different values of circularity collected


may be caused by cellular irregularity rather than the elongation. As a result, the

conclusion of cell elongation made, based on the value of circularity, may not be able

to present the ‘real’ degree of cell elongation. The mathematical definition of

circularity is shown as the following equation [72-76](Equation 2.2):

where P is the perimeter and A is the surface area of the analysed cell. It has a

maximum value of 1 for a circle and lower values for all other shapes. This shape

factor is motivated by the fact that attachment caused shape changes at the early

stage of cell culture will have a similar round shape to floating cells but much more

irregular bumpy cellular boundaries, caused by the appearance of the cellular

dendrites.

Convexity is another good solution to quantify the irregular cells. It measures

the ratio of the perimeter of the convex object to the original perimeter [72, 73]

(Equation 2.3):

Figure 10 Diagram shows cellular boundaries with different roughness

The value of convexity is 1 for a circle and the value will be lower when the

perimeter of the cell is rough [73].


Solidity may more widely be known as compactness, or convexity in some

image analysis software. It is another shape factor that can be used to quantify the

irregularity of cell shape. In two dimensional images, solidity has been

mathematically defined as the ratio of the surface area of the cell and the area

enclosed by the imaginary smallest hull bordering all points of the particle [72, 74,

77] (Equation 2.4):

Figure 11 Diagram shows the determination of cells with different solidity

In some cases, solidity is also defined as the ratio of the cell’s area and the

bounding rectangular with the least surface that can contain the cell. A cell with a

regular cell boundary has a higher value of solidity, and the lower value of solidity

indicates the irregular cell shape.

Cell shape changes during cell growth process involving both cell elongation

and the appearance of the cell dendrites, which causes the increased irregularity.

This transition of cell shape cannot effectively be described using any of the shape

factors shown previously alone. The shape factor called spherity shown below is

sensitive to both elongation and irregularity, and can be mathematically defined as

[69, 73]:


where d1 and d2 are the diameters of the maximum inscribed and circumscribed

circles, respectively. It quantitatively describes the complex deviation from the ideal

circle due to both elongation and irregularity. However, the single number calculated

for the spherity cannot directly interpret the cell elongation and the development of

the cell dendrites; it is thought to be quite insufficient for correct cell shape

classification [69].

Figure 12 Diagram shows the determinations of spherity which is sensitive to most irregularity and

elongation

In summary, there is still some confusion in terms of shape factor name and

definition, caused by the different methods used to estimate the basic dimensions of

the cell in different image analysis software. An appropriately selected shape factor

carries sufficient information for the identification of the cell shape. However, it is

important to keep in mind that it is not possible to accurately describe any shape by a

single number. Even the best shape factor available can only quantify either

elongation or irregularity of cell, thus, usually more than one parameter must be

applied for the purpose of classification [69, 73].

Chapter 3 Quantitative morphology study on osteocyte-like cell line (MLO-Y4) 29

Chapter 3: Quantitative Morphology Study on Osteocyte-

Like Cell Line (MLO-Y4)

3.1 Introduction

Cell morphology has been commonly used as a key parameter for quantitative

study in various research disciplines. In cell culture research, the various cell shapes

indicate the different status of the cells including differentiation, proliferation and

apoptosis [1]. Hence, by monitoring the morphology of cells in culture a quick and

easy way to determine the quality of a culture sample is made possible. In addition,

measuring cell morphology changes under various mechanical loadings is also a

widely applied method to evaluate cellular mechanical properties in biomechanical

studies.

As mentioned in the literature review, it is believed that osteocyte cells act as

mechanosensor/transducers in bone tissue and are playing a very important role in

bone remodelling process [32, 78]. Thus, it is hypothesized that osteocytes may be

responsible for astronauts’ bone mass lost observed after long term space missions,

and the gravity induced morphology change will highly affect their functions of

ostecoyte cells. Numbers of in vitro researches have been conducted to find out

morphology changes of osteocyte cells under an microgravity environment. However,

it is surprising to find that no study has been conducted to quantitatively investigate

the morphology development of osteocytes in culture. In other words, people are

using the cultured osteocyte cells to study the gravity-induced morphological

changes without the knowledge of the morphological characteristics of osteocyte

cells in culture.


In this chapter, we have quantitatively investigated the changes of

morphology for osteocyte-like cell line (MLO-Y4) in culture over time period of up

to 10 hours. The morphology changes of MLO-Y4 cells are studied in details by

measuring the average value of cell area and dimensionless shape factors at different

culturing time. An empirical mathematical model is then developed based upon this

acquired data to predict the MLO-Y4 cells’ growth process in culture.

To ensure the representativeness of the result shown in this study, the

morphological study of MLO-Y4 was performed twice under the same experimental

conditions, by using different groups of MLO-Y4 cells

3.2 Methods

3.2.1 Cell Culture and Fixation

MLO-Y4 osteocyte-like cells (passages 53) were seeded on collagen-coated

cover slips in a 24-well plate and cultured in Dulbecco’s Modified Eagle medium

(DMEM) supplemented with 10% fetal bovine serum (FBS) and 1%

Penicillin/Streptomycin (P/S). In order to accurately characterize the cellular

morphology, MLO-Y4 cells were cultured at low density (5×103 cells per well).

Starting from the end of the first culturing hour, one well of cells was fixed using 4%

paraformaldehyde (PFA). This was repeated every hour for 10 hours. .

3.2.2 Fluorescence Staining

After 30 minutes fixation with PFA, MLO-Y4 cells were washed in phosphate-

buffered saline (PBS) and permeabilized with freshly prepared 0.1% triton X-100 in

PBS for 5 minutes, followed by two washes with PBS. The MLO-Y4 cells were then

incubated in blocking solution prepared with 1% bovine serum albumin (BSA) in

PBS for 10 minutes at room temperature. F-actin filaments were then stained by

Alexa Fluor 568 phalloidin and the cell nucleus was marked by Hoechst stain. In


order to obtain higher accuracy of the osteocytes morphologic characteristics, a large

number of fluorescent images were collected by using Zeiss fluorescent microscope

(Zeiss, Germany) for subsequent analysis.

3.2.3 Cell Segmentation

To accurately find the outline of a cell is an important but difficult task, which

requires correct isolation of cells from background. In this study, MLO-Y4 cells’

morphological features were determined using the widely accepted image analysis

software (ImageJTM, v.1.45s, National Institute of Health, Bethesda, MD). In order

to facilitate the segmentation, the uneven background illumination was corrected by

the application of contrast-enhance function in ImageJ. All fluorescent images were

then converted into 8-bit-grayscale images before starting to measure the

morphological parameters. Cell morphological features of MLO-Y4 cells were

extracted by visually choosing a threshold intensity value which most closely

coincides with the outline of the cells as perceived by the operator (Figure 13). The

intensity of background is relatively lower that fluorescent stained cells, the signal-

to-noise ratio is high, thus making the selection of threshold value highly reliable.

3.2.4 Morphologic Feature Extraction

Correct cell characterization requires the extraction of meaningful parameters

which accurately represent cell morphological changes over time from collected

images. As mentioned in the last chapter, osteocytes are described as stellate shape

cells; the dendrites of osteocytes are playing crucial role in regulating bone

remodelling. Thus, mathematic shape factors used here should not only represent the

size and shape changes of the osteocytes over the culturing time, but also need to

accurately quantify the dendrite development of osteocytes in culture.


In this study, cell area was measured to investigate the size changes of MLO-

Y4 cells and three dimensionless shape factors, including aspect ratio, circularity and

solidity, were measured and subsequently used to quantitatively define the MLO-Y4

cell shape changes as a function of culture time (Figure 14).

Aspect Ratio

Aspect ratio was used to identify the elongation of MLO-Y4 cells in culture. In

ImageJ (National Institute of Health, Bethesda, MD), aspect ratio is defined as

follows:

Where a and b are the length of the major-axis and semi-axis of the best fit

ellipse to the selected cell, respectively. The fitted ellipse has the same area,

orientation and centroid as the extracted cell (Figure 13-b). In order to normalize the

value of dimensional shape factors in the region between 0.0-1.0, the reciprocal value

of the calculated aspect ratio (

) is used to determine the cell elongation in this

study. Thus, a perfect circle will have the maximum aspect ratio value of 1.0 while

an elongated shape will have a lower aspect ratio approaching zero.

Solidity

The solidity is used to investigate dendrite development of osteocytes. In two

dimensional images, solidity is defined as the ratio between the cell area and its

convex area (Figure 13-d). The elongated dendrites are thought to create a larger gap

between the outline of the convex and the outline of the cell:

Thus, a solid cell will have the solidity value of 1.0; the cell with extended

dendrites will have a lower solidity value.


Circularity

As mentioned before, circularity is the most common shape factor used to

describe cell morphology in many studies. A perfect circle will have the circularity

of 1.0; a value of zero indicates a highly elongated cell shape. However, the

circularity is mathematically defined as the relationship between the area and

perimeter (Equation 2.2), where A is the cell area and P is the perimeter of cell. In

the case of the cell with highly irregular boundary, circularity may be unable to

accurately indicate the degree of cellular elongation.

Thus, in this study, circularity was used with aspect ratio to investigate the

irregularity of cells at an early stage of culture. If two cells have a similar aspect ratio,

the one with a higher circularity has a “bumpier” boundary.

In this study, we assumed that all MOL-Y4 cells are perfectly spherical before

attached to the collagen-coated substrate at time zero, and having the aspect ratio,

solidity and circularity value of 1.0 at time zero.


Figure 13 Cell Segmentation procedure: (a) Original fluorescent image; (b) Fluorescent image with

enhanced contrast; (c) 8-bit image; (d) Binary mask image

a

b

c

d


Figure 14 the protocol of determining shape features (a) the original fluorescent image; (b) Fitted

ellipse to extracted cell shape; (c) Extracted cell area and perimeter; (d) Convex hull of extracted cell shape.

a

c d

b


3.2.5 Statistical Analysis

Although a large number of fluorescent images were collected for MLO-Y4

cell morphology characterization, compared with the whole population the sample

size is still relatively ‘small’. To minimize the influence of the limited sample size on

the accuracy of calculated mean values of extracted morphology features,

bootstrapping tests were performed on all collected data with the aid of Fathom

statistics software (KCP Tehcnologies,Inc). Bootstrapping was applied by repeatedly

re-sampling the original data using sampling with replacement, and calculating the

mean for new samples (bootstrap samples). Bootstrapping was performed 500 times

for each group of data. The mean value calculated from the re-sampled data was used

to represent the ‘real’ morphological features at different culturing times and thus

provided a better representation of the entire population.

3.2.6 Curve Fitting

3.2.6 (a) Mathematical models for measured cell area

Non-linear regression was performed to fit the mathematical models to the

experiment data using biostatistics program, GraphPad Prism 6 (GraphPad Software,

Inc, USA). Based on the tendency of the data, one phase exponential association

equations (Equation 3.1) and hyperbolic tangent function (Equation 3.2) were

preliminarily picked as two potential models for fitting the data of MLO-Y4 cell area

changes in culture.

One-phase exponential association model:

Where t is the culturing time in the unit of hour, t0 has the same unit of t and is

determined to be 1. Ya starts at A0, then goes up to plateau with one phase. A0 and

plateau are in the same units as Ya (μm2). Cell area is equal to A0 when t=0, hence,


A0 has been defined to be greater than zero during curve fitting. k is the rate

constant of cell area spreading, which in units are the reciprocal of the x-axis units

(hr-1).

Hyperbolic tangent function:

Where t is the culturing time in the unit of hour, t0 has the same unit of t and is

determined to be 1. k1 is the cell area spreading rate, S1 and A1 are constant numbers

and in the same unit as Ya. According to the hyperbolic tangent function shown

above, cell area (Ya) is equal to the constant number A1, when t=0. Thus, the constant

A1 is constricted in a range between zero and the value of cell area measured at the

first hour in culture. The parameter of S1 is defined as the span of the curve.

3.2.6 (b) Mathematical models for dimensionless shape factors

The reciprocal equation (Equation 3.3) and one-phase exponential decay model

(Equation 3.4) were chosen as two initial models to fit the three dimensionless shape

factors.

Reciprocal equation

Where, t is the culture time; k2 is decay rate of the curve. As it is assumed that

MLO-Y4 cells are in perfect sphere when t=0, b1 is then determined to be constant

value 1.

One-phase exponential decay:

Where, t is the culture time, k3 is the rate constant. Curve starts at b2 and decays

down to the unknown constant c2. The constant b2 was determined to be 1.


3.3 Results

3.3.1 Cell Area & Culturing Time

Data collected from two experiments have shown the same trend in cell area

changes. In the cell cultures, it was observed that MLO-Y4 cells adhered rapidly to

the collagen-coated substrate. The mean area of MLO-Y4 cells after 1 hour culture

was measured as 407.54 μm2

and 473.21 μm2 in two experiments, respectively.

MLO-Y4 cells have experienced a rapid-growth in their cell area at early stage of

cell culture, where the area MLO-Y4 cells were found to be nearly tripled in the first

three hours. After that, cell area was then gradually increased until approximately

1400 μm2. No significant changes in cell area were observed after 5

th hour (Table 1).

Table 1 MLO-Y4 cell mean area measured with different culturing time

Time(hours) Mean Area (μm2)

Experiment 1 Experiment 2

1 407.54 473.21

2 839.85 888.52

3 1214.09 1235.84

4 1273.55 1291.97

5 1432.25 1498.82

6 1408.73 1434.63

7 1463.44 1421.03

8 1471.22 1411.89

9 1487.09 1532.65

10 1425.82 1456.9

3.3.2 Cell Shape & Culturing Time

The results of three dimensionless shape factors measured from two

experiments over 10 hours culture time are shown in the following tables. The data

of shape factors collected from two separate experiments have shown the same


tendency in cell shape changes. Changes in these shape factors quantitatively

indicated the shape development of MLO-Y4 cells in culture.

Data from Table 2 shows the changes in the value of aspect ratio which

indicate the elongation of MLO-Y4 cells in culture. High aspect ratio seen at the 1st

of culturing suggests that MLO-Y4 cells keep as round shapes at early stage of cell

culture. The reduced aspect ratio obtained at 2nd

hour shows that the elongation

process starts as soon as the cell attachment occurred. The biggest drop in the value

of aspect ratio is found at the 4th hour and no significant changes in aspect ratio are

observed afterwards. The major-axis of the best fit ellipse of fully developed MLO-

Y4 cells is found about 1.5 times longer than the semi-axis.

Table 2 Aspect Ratio measured for MLO-Y4 cells in culture from two experiments.

Time(hours) Mean Aspect Ratio


0 1 1

1 0.822 0.823

2 0.781 0.794

3 0.721 0.755

4 0.638 0.651

5 0.635 0.660

6 0.636 0.652

7 0.619 0.615

8 0.650 0.620

9 0.641 0.659

10 0.610 0.606

Changes in data of solidity presented in Table 3 provide a sign of how cellular

dendrites are developed in culture. The decreased ratio of cell area and its convex

area at an early culturing hour reveals the fact of high vitality of MLO-Y4 cellular


dendrites. According to the data collected for aspect ratio and the solidity, it is

suggested that the development of cellular dendrites occurs in parallel with the cell

elongation. Interestingly, the biggest drop in the value of solidity is also found

between the 3rd

and 4th hour culturing time. As a result of proliferation and the

development of cellular dendrites, cells were starting make contact with other. The

elongated dendrites are thought to be the cause of some fluctuation in the results of

solidity as seen in Table 3.

Table 3 Solidity measured for MLO-Y4 cells in culture from two experiments.

Time(hours) Mean Solidity


0 1 1

1 0.866 0.876

2 0.794 0.768

3 0.668 0.684

4 0.536 0.482

5 0.511 0.489

6 0.479 0.472

7 0.452 0.468

8 0.488 0.399

9 0.341 0.481

10 0.395 0.423

The table below shows the changes in circularity measured from two

experiments. The low circularity values are caused by the irregular cell boundaries,

which indicate rapid attachment of MLO-Y4 cells and the appearance of the cellular

dendrites. The extremely low circularity obtained at the later cell culture hours is

thought to be the result of cell elongation as well as the development of cellular

dendrites.


Table 4 Circularity measured for MLO-Y4 cells in culture from two experiments

Time(hours) Mean Circularity


0 1 1

1 0.602 0.622

2 0.437 0.407

3 0.271 0.283

4 0.153 0.131

5 0.146 0.121

6 0.118 0.110

7 0.100 0.114

8 0.119 0.080

9 0.062 0.110

10 0.082 0.098

3.3.3 Model Selection for Curve Fitting

The goal of the non-linear regression is to fit a model to the two experiment

data with the best-fit values. The best model for fitting the experiment data is

determined by using the least second square method.

As shown in Table 5, both one-phase exponential association and hyperbolic

tangent models fit well to the data of osteocytes cell area changes in culture. The

hyperbolic tangent model has the absolute sum of squares 20590, which is slightly

higher than the absolute sum of squares in the one phase association model. Hence,

the one phase association model (Equation 3.1) is used to fit the data of cell area

changes in culture.

Table 5Goodness of fit for cell area in culture

Model R2 (%) Absolute Sum of Squares

One-phase Exponential Association

Model 98.61 14738

Hyperbolic Model 98.06 20590


Reciprocal equation and one-phase exponential decay models are used to fit the

three dimensionless shape factors. One-phase exponential decay model shows less

absolute squares and higher coefficient of determination (R2) in all three shape

factors. Thus, the one-phase decay model (Equation 3.4) is used to fit the data of

shape factors change in culture (Table 6).

Table 6 Goodness of fit for shape factor in culture

Model Shape Factors R2 (%) Absolute Sum of Squares

Reciprocal Equation

Model

Circularity 97.25 0.0234

Solidity 96.87 0.0132

Aspect Ratio 69.50 0.0440

One-phase

Exponential Decay

Model

Circularity 99.62 0.0032

Solidity 97.80 0.0092

Aspect Ratio 96.88 0.0045

3.3.4 Fitted Curves and Developed Emprical Models

By using the selected models, the fitted curves and developed emprical models

for call area and three dimensionless shape factors are shown below:


Cell Area

0 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2

0

2 0 0

4 0 0

6 0 0

8 0 0

1 0 0 0

1 2 0 0

1 4 0 0

1 6 0 0

C e ll A re a

T im e (h r )

Ce

ll A

re

a (

um

^2

)E x p e rim e n t O n e

E x p e r im e n t T w o

Figure 15 Cell Area changes of MLO-Y4 cells measured from two tests

MLO-Y4 cell area change in cell culture is mathematically defined as:

The empirical model developed from the obtained data shows that MLO-Y4

cells are spreading at the constant rate of 0.1704 hour-1

in culture. Based on the

empirical model, the predicted cell area of a MLO-Y4 cell before the attachment is

μm2.


Aspect Ratio:

Figure 16 Aspect ratio changes of MLO-Y4 cells measured from two tests

Aspect ratio change in MLO-4 cells is mathematically defined as:

The empirical model of aspect ratio changes in culture suggested that MLO-Y4

cells were elongated at the constant ratio of hr-1

during cell culture.

Solidity

Figure 17 Solidity changes of MLO-Y4 cells measured from two tests


Solidity changes with culturing can be defined as:

)

Where, the span of the curve on the Y axis is and the solidity dropped

at the rate of hr-1

.

Circularity

0 1 2 3 4 5 6 7 8 9 1 0 1 1 1 2

0 .0

0 .1

0 .2

0 .3

0 .4

0 .5

0 .6

0 .7

0 .8

0 .9

1 .0

1 .1

C ir c u la r ity

T i me (h r )

Cir

cul

arit

y

E xp e r i m e nt O n e

E x p e r im e n t T wo

Figure 18 Circularity changes of MLO-Y4 cells measured from two tests

The relationship between the circularity and culturing time is then defined as:

Where the empirical model shows that the circularity of MLO-Y4 cell is

changed at rate of 0.533 hr-1


Figure 19 MLO-Y4 cell morphological appearance in culture. (a) 1hr; (b) 2hr; (c) 3hr; (d) 4hr; (e) 8hr;

(f) 10hr (scale bar:50μm)

b

c

e f

a

d


3.4 Discussion

Previous study has already confirmed that the cell growth in culture will

produce significant morphology changes in MLO-Y4 cells [3]. However, the MLO-

Y4 cell growing process described in the past paper was slightly delayed compared

with the data obtained in this study. Kato et al. reported that MLO-Y4 cells were

small and stellate after 3- 6 hours of cell culture and became elongated and started

branching after 1 day. On the other hand, cell elongation and the development of

cellular dendrites observed in this study are found to start as soon as the cell

attachment has occurred. The difference in MLO-Y4 cell growth speed observed in

two studies would possibly be caused by using the different passage numbers of

MLO-Y4 cells and the influence of cell culture method. Cells used in Kato’s

experiment are very early generations of MLO-Y4 cells which were directly isolated

from the transgenic mice. Thus, the cells which were used in their study could

possibly have some other type of cells mixed, even though the probability is very low.

In addition, comparing with the early passage numbers, the subsequent passages

might be selecting the cells that can keep on proliferating, and therefore lose the slow

dividing cells and the ability to grow faster. Besides the different passage numbers

used, the different times that cells are incubated in trypsin during subculture will also

highly affect the vitality of MLO-Y4 cells as well as the cell morphology at early

stages of cell culture, which may also delay the cell growth process.

In this study, MLO-Y4 cells were cultured at the density of 5×103 cells per

well in a 24-well plate. Cells are growing very slowly in an extremely low density

environment and the limitation of space for cells to spread into will also affect the

cell growth process if the initial culture density is too high or the culture is in the


confluent phase. Therefore, cell density is another very important factor which will

affect cell growth as well as cellular morphology in culture.

To quantify cell shape changes of MLO-Y4 cells with growth and proliferation,

three dimensionless shape factors were used in this study. The selection of shape

factors was based on the expression of the dendritic phenotype of osteocyte cells.

Aspect ratio was used to quantify the elongation of MLO-Y4 cells in culture, solidity

was selected to describe the development of cellular dendrites and the changes in the

value of circularity provide a sign of cell attachment caused irregularity at the early

stage of cell culture. It is important to keep in mind that there is no possibility to

define a cell shape by using only one signal shape factor, thus, in order to intuitively

describe a cell shape different shape factors are needed. Different shape factors may

be required for different cell types depending on their morphological characteristics

in culture.

Cell morphology varies for individual MLO-Y4 cells at the same culturing

time point. To generate an empirical model that can accurately predict morphology

changes at different culture times, an accurate mean value of measured

morphological features is crucial. In this study, the high signal-to-noise ratio of

fluorescent images ensures the reliability of the measured morphological parameters.

The large sample size measured in this study and the application of the bootstrapping

technique increases the statistical precision of the measured parameters. Compared

with other statistical re-sampling methods such as Cross-validation and Jackknife,

bootstrapping re-sampling original samples using sampling with replacement is more

accurate than sampling without replacement in terms of simulating chance.


3.5 Conclusion

This study quantitatively defined the relationship between cellular morphology

and culturing time for MLO-Y4 cell line. The quantified morphological parameters

of MLO-Y4 cell can be used as the reference data for investigating morphological

response of MLO-Y4 cells to mechanical stimulations. The different morphology

parameters measured under loadings may indirectly reflect the modification of

cellular downstream signalling activity, which then can lead to further studies at

molecular level. With the aid of powerful image processing tools and the advanced

curve fitting software, empirical models were successfully developed based on the

obtained data to quantitatively predicate the morphological changes of MLO-Y4

cells in culture. By using the developed empirical models, all morphological

parameters of MLO-Y4 cells can be simply calculated and can be used to efficiently

monitor the quality of the cell culture. The rate of size change, elongation and

dendrites development of MLO-Y4 cells, defined from empirical models provide the

chance to investigate the effect of altered gravity to MLO-Y4 cell growing process.

Chapter 4: Osteocyte cells under hyper-gravity stimulation 50

Chapter 4: Osteocyte Cells under Hyper-gravity Stimulation

4.1 Introduction

Cellular mechanical property is highly related to cell morphology. As

mentioned previously, round shape MLO-Y4 cells are found to have a less stiff

cytoskeleton configuration and are more sensitive to mechanical stimulus than flat

adherent MLO-Y4 cells. Most in vitro studies are cultured MLO-Y4 cells on two-

dimensional (2D) flat surfaces, however, by using confocal microscopy, osteocyte

cells are found have three-dimensional conformation in bone tissue[31, 79, 80]. The

relative flat and spread shape of isolated osteocytes in 2D culture may greatly

hamper their sensitivity to a mechanical stimulus[7], thus, previous in vitro space

studies that investigate flat adherent MLO-Y4 cells may not be able to accurately

reflect the response of in vivo osteocytes to altered gravity.

In this chapter, the morphological response of MLO-Y4 cells with a relatively

round morphology under hyper-gravity environment has been quantitatively

investigated. The ideal MLO-Y4 cell model used in this study has the dendritic

phenotype and a spherical cell body. Based on the data as detailed in the last chapter,

MLO-Y4 cells cultured for two hours were used. Changes in the morphology of

MLO-Y4 cells are quantitatively analysed by measuring the average value of cell

area and dimensionless shape factors such as aspect ratio, solidity and circularity.

To ensure the representativeness of the result shown in this study, centrifuge

experiment has been performed twice under the same conditions.


4.2 Materials and Methods

4.2.1 Cell Culture

Osteocyte-like cells (passage number 46) were seeded on collagen-coated

cover slips placed in 24-well plates, and cultured in Dulbecco’s Modified Eagle

medium (DMEM) supplemented with 10% fetal bovine serum (FBS) and 1%

Penicillin/Streptomycin (P/S). Cells were incubated at 37oC in humidified 5% CO2

for 2 hours before the experiment to allow cell attachment. The seeding density was

5.0×103 cells per slide and 1.0 microlitre (μL) culture medium was filled in each well.

In order to minimize the unwanted inertial shear force generated via the rotating of

the centrifuge, only the central 4 wells were used in the 24-well plate (Figure 20).

Figure 20 Four wells located at the centre of the 24-well plate were used

4.2.2 Centrifuge Experiment

Centrifugal force was applied by using Allegra X-15R centrifuge (Beckman

Coulter. Inc) equipped with an SX4750 swinging bucket rotor which allows

centrifugation of multi-well plates (Figure 21). The multi-well plate carriers were

reached vertical at the minimum permitted system operation speed (200rpm). Two

24-well plates were placed symmetrically with respect to the rotation axis. The

centrifuge experiment was then performed at 390 rpm (20g) for 30mins at room


temperature. Culture plates for controls were placed on the lid of the centrifuge, as a

control for vibration effects.

Figure 21 (a): Side view of the rotor at speed; (b) Top view of the rotor at rest.

4.2.3 Post-Centrifugation Processing of MLO-Y4 Cells

Cell fixation was applied immediately after the centrifuge experiment was

finished. Culture medium was aspirated and MLO-Y4 cells were rinsed twice in

phosphate-buffered saline (PBS); cultures then underwent 30 mins fixation by

immersion in 4% paraformaldehyde (PFA) at room temperature. Following fixation

Alexa Fluor 568 phalloidine and Hoechst stain were used to stain the F-actin

filaments and cell nucleus, respectively. The details of florescent staining are

described in the last chapter of this work. Large amount of fluorescent images of

MLO-Y4 cells were collected by using Zeiss fluorescent microscope (Carl Zeiss Inc,

Germany) for subsequent analysis.

Similarly as described in the last chapter, the morphological features of MLO-

Y4 cells were determined using the widely accepted image analysis software, ImageJ

(ImageJTM

, v.1.45s, National Institute of Health, Bethesda, MD). Image analysis was

performed as described previously in the last chapter. Cell area, aspect ratio, solidity

(a) (b)


and circularity were applied to quantify the effect of hyper-gravity to the morphology

of MLO-Y4 cells.

4.2.4 Statistics

Statistical analysis was performed using Minitab 16 statistics software (Minitab

Inc, State College, PA, USA). All data were expressed as mean± standard deviation

(SD). T-tests were performed on all morphological data and a value of p<0.05 was

considered significant in all analysis.

4.3 Results

4.3.1 Cell Area under Hyper-gravity

The average area of MLO-Y4 cells measured in both centrifuge and control

samples from two experiments are shown below. No significant changes in cell area

were observed in MLO-Y4 cells simulated with hyper-gravity, compared with

control samples (Figure 22).

Figure 22 Graphical illustration of cell area measured for MLO-Y4 cells cultured at 20g (blue bar)

and 1g (purple bar) for 30 mins from two experiments. (a) The mean area measured for experiment

sample is 853.52μm2 and 874.06 μm2 for control sample in experiment 1 (P=0.388). (b) The mean area measured for experiment sample is 866.1μm2 and 876.73μm2 for control sample in experiment 2

(p=0.669). n=500


4.3.2 Cell Shape under Hyper-gravity

The average values of aspect ratio, solidity and circularity, collected from two

centrifuge experiments, are shown blow in Figure23, 24 and 25, respectively. No

significant changes in the value of aspect ratio, solidity or circularity were found in

the MLO-Y4 cells exposed to the hypergravity environment, compared to control

cells, which indicate that increased gravitational force does not affect cellular

elongation and dendrites development.

Figure 23 Graphical illustration of aspect ratio measured for MLO-Y4 cells cultured at 20g (blue bar)

and 1g (purple bar) for 30 mins from two experiments. (a) The mean aspect ratio measured for

experiment sample is 0.843 and 0.851 for control sample in experiment one (P=0.232). (b) The mean

area measured for experiment sample is 0.846 and 0.847 for control sample in experiment two (p=0.846). n=500


Figure 24 Graphical illustration of solidity measured for MLO-Y4 cells cultured at 20g (blue bar) and

1g (purple bar) for 30 mins from two experiments. (a) The mean aspect ratio measured for experiment

sample is 0.864 and 0.863 for control sample in experiment one (P=0.791). (b) The mean area

measured for experiment sample is 0.866 and 0.864 for control sample in experiment two (p=0.718).

n=500

Figure 25 Graphical illustration of circularity measured for MLO-Y4 cells cultured at 20g (blue bar)

and 1g (purple bar) for 30 mins from two experiments. (a) The mean aspect ratio measured for

experiment sample is 0.573 and 0.562 for control sample in experiment one (P=0.053). (b) The mean

area measured for experiment sample is 0.581 and 0.562 for control sample in experiment two

(p=0.256). n=500


4.4 Discussion

Round shape ostecoytes are thought to have less stiffness, which makes them

easier to deform compared with flat adhesion cells. It is also believed that compared

with highly spread osteocytes, a relatively round shape osteocyte has the mechanical

property which is closer to osteocytes in vivo. Therefore, instead investigating flat

adhesion osteocytes, centrifugal study was conducted on round shape MLO-Y4 cells.

MLO-Y4 cells were exposed to 20g for 30mins at room temperature; however, our

initial results show that there are no significant changes, neither in cell area nor the

shape of MLO-Y4 cells under hyper-gravity environment. No attempt has been made

before to investigate the effect of hyper-gravity to osteocyte cells but few

microgravity studies were conducted. As described previously, conflicting results in

cell morphological response to simulated microgravity stimulations were reported

from Sheng and his group. Cell area of osteocytes was found dramatically decreased

under the diamagnetic levitation environment, however, both two-dimensional

clinorotation and parabolic flight experiments showed that no morphological

difference was detected in ostoecyte cells exposed to simulated microgravity,

compared to 1g control cells[21, 24, 25].

Several hypergravity studies have already been conducted on osteoblasts which

are the progenitors to osteocyte cells, and the results appear contradictory. Kacena

and his colleagues [81] reported an approximately 4%-24% and 33%-58% increase

in osteoblasts cell area, with centrifugation at 3.3g and 4.0g, respectively. However,

Gebken et al. showed no changes in osteoblast’s morphology after being centrifuged

at 13g for 24 hours [82]. Similar results were also reported by Searby et al., who

concluded that the morphology of osteoblasts exposed to 10g for 3 hours was

indistinguishable to that of the controls [83]. These varying results may be explained


by the different passage number used, the type of cells studied and the G-level,

duration of exposed to altered gravity environment. Kacena et al. [81] claimed that :

‘For shorter growth durations, a higher G-level may be required to induce

cytoskeleton changes in osteoblasts, alternatively, a lower G-level can also induce

significant changes if the growth duration is extended.’

Based on this theory, we further examined the effect of extended exposure time

to MLO-Y4 cells by increasing the centrifuge time to 3hours, using the cells only

cultured for 1hour, which are thought to be more sensitive to mechanical stimulus

compared with MLO-Y4 cells cultured for 2 hours. Similarly to the previous test, no

significant changes in cell are were found in centrifuged MLO-Y4 cells, compared to

1g control cells (data not shown).

Although no hypergravity-induced morphology change in osteoblasts was

reported in Searby’s study, the height of osteoblast was found to be decreased.

Around 7% and 26% decrease in cell height was respectively measured at 5g and 50g

levels [83]. The observation of height changes in osteoblast under a hypergravity

environment was further confirmed by Van et al. By taking the advantages of atomic

force microscope (AFM), Van and his colleagues have successfully measured the

height change in osteoblasts under increased gravitational stimulation, in situ. The

height of osteoblasts was found reduced by around 30%-50% at only 2g-3g loadings

within 4 mins [84]. In comparison with Van’s results, the reason for less decrease in

cell height with higher G-level reported by Searby could be due to the fixation

method used. Chemical fixation normally needs at least 20mins to fully fix the

cellular cytoskeleton at room temperature. However, changes in cell morphology can

be quite fast. Previous study showed chondrocyte deformed and reached an

equilibrium displacement within 2mins, after application of stress by using


micropipette aspiration [85]. Results from the study conducted by McGrath et al.

suggested that the typical turnover time of cytoskeleton actin filaments appears to be

around 6mins [86]. Thus, morphology recovery may occur during chemical fixation

period, leading to the inaccurate measurement of cell morphology changes in hyper-

gravity/microgravity studies.

Previous studies showed that osteocytes and osteoblasts have similar cell

stiffness. The elastic constant measure for osteoblast cells was in the range of 1.4kPa

to 1.9kPa [87], and the elastic constant of osteocyte cell is found around 143Pa-

300Pa for round shape osetcoytes, and from 2.6kPa to 4.3kPa for flat osteocytes [7].

Thus, theoretically speaking, osteocytes should have similar or even better

deformability, in the case of round osteocytes, than osteoblasts under hypergravity

stimulation. Results from our centrifuge study, which showed no morphology change

under hypergravity (20g) stimulation, implies that cell height is probably a more

appropriate parameter than cell area for morphology analysis in gravity studies.

Shape factor values shown in this centrifuge study are much higher than these

measured at the 2nd

hour of culture under standard cell culture conditions (37oC and 5%

CO2), reported in last chapter. The higher aspect ratio indicates that the lesser cell

elongation, and higher value of solidity and circularity, reflect the interruption of cell

dendrites development. Cell dendrites formation is an active process. By monitoring

living osteocytes, cellular dendritic process was found to keep extending and

retracting over 24 hrs, and the dynamic structure of cell dendrites are able to be

altered in response to external environment [36]. Due to the limitation of the used

centrifuge, our experiments were conducted at room temperature. Shape factors

measured in this centrifuge study suggest that cell culture environment including

temperature and concentrations of carbon dioxide highly affect osteocyte dendrites


development, even for a short growth period (30mins). Later study showed a

suspended dendrites growth in osteocytes cultured at room temperature for 10 hours,

indicating that rather than temporary effect, the influence of culture environment on

cell growth is continuous (data not shown). As mentioned in the literature view,

dendritic processes are playing an important role in osteocyte mechanosensation. The

retraction of cell dendrites caused by the experimental environment may adversely

affect the sensitivity of osteocyte cells to mechanical stimulation and therefore lead

osteocyte cells to fail to respond to the applied gravitational loading.

4.5 Conclusion

This study quantitatively investigated the cellular morphology changes of

osteocytes under a hypergravity environment. No significant morphology changes

were found in MLO-Y4 cells which were exposed to 20g for 30 mins. The failure

response in osteocyte morphology to increased G levels, as observed in this study,

can be explained by the fixation method used, the experimental environment and

inappropriate parameter for morphology analysis under altered gravity (e.g. cell

height may show more sensitivity to gravity changes than cell area).

Chapter 5: Conclusions and Future Work 60

Chapter 5: Conclusions and Future Works

Numerous gravity-related research works were conducted to investigate the

influence of gravity on living cells worldwide over the past two decades. As a large-

scale expression of many highly regulated biological processes, cell morphology thus

has been long used as a proxy measure for global cell state under an altered gravity

environment [1]. As microscopy moves into an increasingly quantitative and high-

throughput era, it can be expected that the analysis of cell morphology will play a

more important role in future gravitational biological study.

Osteocytes are believed to play an important role in bone mass loss occurring

in astronauts after long-term space missions. Dendritic phenotype of osteocytes is

essential to maintain their mechanosensation and mechanotransduction functions in

bone tissue. Thus, investigation of cell morphology changes of osteocyte cells in

altered gravity can provide important information on the influence of altered gravity

on osteocyte’s biological functions. Unlike these biomechanical studies which

investigated cell mechanical properties using techniques such as optical and

magnetic tweezers, atomic force microscopy and micropipette, gravity simulators are

normally performed in environments featuring high-speed movement, which causes

huge difficulty in quantifying the cell morphology change under altered gravity

stimulations. As a result, cellular morphological responses to altered gravity

reported from different studies are always found inconsistent.

One of the challenges gravity-related research faces today is that it is extremely

difficult to compare the cell morphology of osteocyte cell under altered gravity to

normal gravity by using the same individual osteocyte cell. The most common way

used to solve this problem is to set up a control sample, the changes of cell


morphology being then determined by comparing the difference between mean

values of cell morphology measured from altered gravity and control samples.

However, the morphology of osteocyte cells at 1g in culture was poorly investigated.

This study has successfully quantified the morphological development of MLO-Y4

cells cultured on the collagen coated surface for the first time. Quantification

analysis of osteocyte cells and the developed empirical models showed this study

have provided a base line for quantitatively studying the morphological change of

osteocyte cells under altered gravity. As cell morphology analysis is exceedingly

time-consuming, two osteocyte cell morphology studies were finished and used to

create the empirical models. In future, it would be advantageous to conduct further

morphology studies of osteocyte cells in culture.

Empirical models developed in this study were based on the data of

morphological changes of osteocyte cells in culture, seeded at the density of 5×103

cells per well. Cell density and the trypsinizing time applied in cell culture may vary

from study to study. However, different cell density and the trypsinizing time applied

in different studies may affect cell growth, which may lead to the incomparable

results from different gravitational studies. Thus, further investigation is required to

find out the effects of different cell culture density and trypsinizing time applied in

culture to osteocyte cells growth process.

In addition, morphological response of osteocytes with a relatively round shape

has been quantitatively investigated at a hyper-gravity environment. It was

hypothesized that compared with highly spread osteocytes used in previous studies; a

relatively round shape osteocyte has mechanical properties closer to osteocytes in

vivo. No significant morphology changes were observed in MLO-Y4 cells after

exposed to 20g for 30 mins. The response of MLO-Y4 in this hyper-gravity study


might be affected by the experimental environment, which can be considered as one

of the limitations of this study.

Another problem need to be dealt with in future gravitational biology study is

the cell recovery during fixation period. One possible solution is to fix the cell during

microgravity/hyper-gravity experiments. This requires designing a system which is

able to remove the culture medium and insert fixation solution at the predetermined

time in the experiment. The in situ fixation of cells may also be done by putting cells

into the gels which keep the liquid form at 37oC and slowly fixing the cell by

solidification at room temperature. This proposed fixation method can only used for

suspended cells in short-term (10-20 mins) gravitational study and the influence of

gels on the cellular sensitivity to mechanical signs needs to be further investigated.

Furthermore, current gravity-related studies investigate the cell morphology in

2D. However, three-dimensional morphology analysis and in situ measurement

might be the development trends for future cellular morphological study under

altered gravity. The first successful in situ measurement of the effects of changing

gravitational load on cell shape was done by Van et al. through mounting an atomic

force microscope (AFM) into a large-diameter centrifuge [84]. An atomic force

microscope is very expensive device; instead using AFM, another possible way to in

situ measure the three-dimensional morphology under different gravity is to develop

an optical system which is able to show both top and side view of the cells. A

preliminary design for this optical system is shown in Appendix 2. To improve space

research capability in Queensland University of Technology, the possibility to create

the combined AFM and centrifuge system and the proposed side-view optical system

should be further investigated.

Bibliography 63

Bibliography

1. Pincus, Z. and J. Theriot, Comparison of quantitative methods for cell‐shape analysis. Journal of microscopy, 2007. 227(2): p. 140-156.

2. McBeath, R., et al., Cell shape, cytoskeletal tension, and RhoA regulate stem cell lineage commitment. Developmental Cell, 2004. 6(4): p. 483-495.

3. Kato, Y., et al., Establishment of an Osteocyte‐like Cell Line, MLO‐Y4. Journal of Bone and Mineral Research, 2010. 12(12): p. 2014-2023.

4. Burra, S., et al., Dendritic processes of osteocytes are mechanotransducers that induce the opening of hemichannels. Proceedings of the National Academy of Sciences, 2010. 107(31): p. 13648-13653.

5. Hu, E., P. Tontonoz, and B.M. Spiegelman, Transdifferentiation of myoblasts by the adipogenic transcription factors PPAR gamma and C/EBP alpha. Proceedings of the National Academy of Sciences, 1995. 92(21): p. 9856-9860.

6. Mathieu, P.S. and E.G. Loboa, Cytoskeletal and Focal Adhesion Influences on Mesenchymal Stem Cell Shape, Mechanical Properties, and Differentiation Down Osteogenic, Adipogenic, and Chondrogenic Pathways. Tissue Engineering Part B: Reviews, 2012.

7. Bacabac, R.G., et al., Round versus flat: Bone cell morphology, elasticity, and mechanosensing. Journal of Biomechanics, 2008. 41(Compendex): p. 1590-1598.

8. Sung Sik, H., et al. Three-dimensional forces and molecular dynamics of live cells. in Biosensing III, 1-3 Aug. 2010. 2010. USA: SPIE - The International Society for Optical Engineering.

9. Chicurel, M.E., C.S. Chen, and D.E. Ingber, Cellular control lies in the balance of forces. Current Opinion in Cell Biology, 1998. 10(2): p. 232-239.

10. Chen, C.S., et al., Geometric control of cell life and death. Science, 1997. 276(5317): p. 1425-1428.

11. Buravkova, L.B. and Y.A. Romanov. The role of cytoskeleton in cell changes under condition of simulated microgravity. 2001. Elsevier Ltd.

12. Paulsen, K., et al., Microgravity-induced alterations in signal transduction in cells of the immune system. Acta Astronautica, 2010. 67(Compendex): p. 1116-1125.

13. Meloni, M.A., et al., Cytoskeleton changes and impaired motility of monocytes at modelled low gravity. Protoplasma, 2006. 229(2-4): p. 243-249.

14. HughesFulford, M. and M.L. Lewis, Effects of microgravity on osteoblast growth activation. Experimental Cell Research, 1996. 224(1): p. 103-109.

15. Boonstra, J., Growth factor-induced signal transduction in adherent mammalian cells is sensitive to gravity. Faseb Journal, 1999. 13: p. S35-S42.

16. Ulbrich, C., et al., Effects of basic fibroblast growth factor on endothelial cells under conditions of simulated microgravity. Journal of Cellular Biochemistry, 2008. 104(4): p. 1324-1341.

17. Grimm, D., et al., Different Responsiveness of Endothelial Cells to Vascular Endothelial Growth Factor and Basic Fibroblast Growth Factor Added to Culture Media Under Gravity and Simulated Microgravity. Tissue Engineering Part A, 2010. 16(5): p. 1559-1573.

18. Monici, M., et al., An in Vitro Study on Tissue Repair: Impact of Unloading on Cells Involved in the Remodelling Phase. 2011(Compendex): p. 1-11.

19. Administration, N.A.a.S. Space Bones. 2001; Available from: http://science.nasa.gov/science-news/science-at-nasa/2001/ast01oct_1/.

http://science.nasa.gov/science-news/science-at-nasa/2001/ast01oct_1/

Bibliography 64

20. Hughes-Fulford, M., Function of the cytoskeleton in gravisensing during spaceflight, in Space Life Sciences: Gravitational Biology: 2002, L.L. Bruce, K. Ijiri, and G. Perbal, Editors. 2003, Pergamon-Elsevier Science Ltd: Kidlington. p. 1585-1593.

21. Di, S.M., et al., Graviresponses of osteocytes under altered gravity. Advances in Space Research, 2011. 48(6): p. 1161-1166.

22. Cao, L., et al., Comparative morphology of the osteocyte lacunocanalicular system in various vertebrates. Journal of Bone and Mineral Metabolism, 2011. 29(6): p. 662-670.

23. Himeno-Ando, A., et al., Structural differences in the osteocyte network between the calvaria and long bone revealed by three-dimensional fluorescence morphometry, possibly reflecting distinct mechano-adaptations and sensitivities. Biochemical and biophysical research communications, 2012. 417(2): p. 765-770.

24. Qian, A.R., et al., Diamagnetic Levitation Causes Changes in the Morphology, Cytoskeleton, and Focal Adhesion Proteins Expression in Osteocytes. Ieee Transactions on Biomedical Engineering, 2012. 59(1): p. 68-77.

25. Xu, H.Y., et al., Two-dimensional clinorotation influences cellular morphology, cytoskeleton and secretion of MLO-Y4 osteocyte-like cells. Biologia, 2012. 67(1): p. 255-262.

26. Bonewald, L.F., Mechanosensation and transduction in osteocytes. BoneKEy osteovision, 2006. 3(10): p. 7.

27. Bonewald, L.F., The amazing osteocyte. Journal of Bone and Mineral Research, 2011. 26(2): p. 229-238.

28. Burger, E.H., et al., Function of osteocytes in bone: their role in mechanotransduction. The Journal of nutrition, 1995. 125(7): p. 2020S-2023S.

29. Lanyon, L., Osteocytes, strain detection, bone modeling and remodeling. Calcified Tissue International, 1993. 53: p. 102-107.

30. Aarden, E.M., P.J. Nijweide, and E.H. Burger, Function of osteocytes in bone. Journal of Cellular Biochemistry, 2004. 55(3): p. 287-299.

31. Schneider, P., et al., Towards quantitative 3D imaging of the osteocyte lacuno-canalicular network. Bone, 2010. 47(5): p. 848-858.

32. Mullender, M. and R. Huiskes, Osteocytes and bone lining cells: Which are the best candidates for mechano-sensors in cancellous bone? Bone, 1997. 20(6): p. 527-532.

33. Skerry, T.M., et al., Early strain‐related changes in enzyme activity in osteocytes following bone loading in vivo. Journal of Bone and Mineral Research, 1989. 4(5): p. 783-788.

34. Pead, M., et al., Increased 3 H-uridine levels in osteocytes following a single short period of dynamic bone loadingin vivo. Calcified Tissue International, 1988. 43(2): p. 92-96.

35. Haj, A.J.E., et al., Cellular responses to mechanical loading in vitro. Journal of Bone and Mineral Research, 1990. 5(9): p. 923-932.

36. Dallas, S.L., et al., Early strain‐related changes in cultured embryonic chick tibiotarsi parallel those associated with adaptive modeling in vivo. Journal of Bone and Mineral Research, 1993. 8(3): p. 251-259.

37. Verbruggen, S.W., T.J. Vaughan, and L.M. McNamara, Strain amplification in bone mechanobiology: a computational investigation of the in vivo mechanics of osteocytes. Journal of The Royal Society Interface, 2012. 9(75): p. 2735-2744.

38. Lau, E., et al., Effect of low-magnitude, high-frequency vibration on osteocytes in the regulation of osteoclasts. Bone, 2010. 46(6): p. 1508-1515.

39. Liu, C., et al., Effects of cyclic hydraulic pressure on osteocytes. Bone, 2010. 46(5): p. 1449-1456.

40. Klein-Nulend, J., et al., Sensitivity of osteocytes to biomechanical stress in vitro. The FASEB journal, 1995. 9(5): p. 441-445.

Bibliography 65

41. Gardinier, J.D., et al., In situ permeability measurement of the mammalian lacunar–canalicular system. Bone, 2010. 46(4): p. 1075-1081.

42. Klein-Nulend, J., et al., Mechanosensation and transduction in osteocytes. Bone, 2012.

43. Zhang, D., S. Weinbaum, and S.C. Cowin, Electrical signal transmission in a bone cell network: the influence of a discrete gap junction. Annals of Biomedical Engineering, 1998. 26(4): p. 644-659.

44. Hung, C.T., et al., Intracellular Ca2+ stores and extracellular Ca2+ are required in the real-time Ca2+ response of bone cells experiencing fluid flow. Journal of Biomechanics, 1996. 29(11): p. 1411-1417.

45. Ajubi, N., et al., Signal transduction pathways involved in fluid flow-induced PGE2 production by cultured osteocytes. American Journal of Physiology-Endocrinology And Metabolism, 1999. 276(1): p. E171-E178.

46. Ajubi, N., et al., Pulsating fluid flow increases prostaglandin production by cultured chicken osteocytes—a cytoskeleton-dependent process. Biochemical and biophysical research communications, 1996. 225(1): p. 62-68.

47. Raisz, L., C. Pilbeam, and P. Fall, Prostaglandins: mechanisms of action and regulation of production in bone. Osteoporosis International, 1993. 3: p. 136-140.

48. Klein‐Nulend, J., et al., Pulsating fluid flow stimulates prostaglandin release and inducible prostaglandin G/H synthase mRNA expression in primary mouse bone cells. Journal of Bone and Mineral Research, 1997. 12(1): p. 45-51.

49. Vatsa, A., T.H. Smit, and J. Klein-Nulend, Extracellular NO signalling from a mechanically stimulated osteocyte. Journal of Biomechanics, 2007. 40: p. S89-S95.

50. Kleinnulend, J., et al., Pulsating fluid flow increases nitric oxide (NO) synthesis by osteocytes but not periosteal fibroblasts-correlation with prostaglandin upregulation. Biochemical and biophysical research communications, 1995. 217(2): p. 640-648.

51. Bakker, A.D., et al., The production of nitric oxide and prostaglandin E< sub> 2</sub> by primary bone cells is shear stress dependent. Journal of Biomechanics, 2001. 34(5): p. 671-677.

52. Moriishi, T., et al., Osteocyte Network; a Negative Regulatory System for Bone Mass Augmented by the Induction of Rankl in Osteoblasts and Sost in Osteocytes at Unloading. Plos One, 2012. 7(6).

53. Kennedy, O.D. and M.B. Schaffler, The Roles of Osteocyte Signaling in Bone. Journal of the American Academy of Orthopaedic Surgeons, 2012. 20(10): p. 670-671.

54. Xiong, J., et al., Matrix-embedded cells control osteoclast formation. Nature medicine, 2011.

55. Nakashima, T., et al., Evidence for osteocyte regulation of bone homeostasis through RANKL expression. Nature medicine, 2011. 17(10): p. 1231-1234.

56. Adachi, T., et al., Calcium response in single osteocytes to locally applied mechanical stimulus: differences in cell process and cell body. Journal of Biomechanics, 2009. 42(12): p. 1989-1995.

57. Zhang, K., et al., E11/gp38 selective expression in osteocytes: regulation by mechanical strain and role in dendrite elongation. Molecular and cellular biology, 2006. 26(12): p. 4539-4552.

58. Steinberg, T., Reduced Gravity Testing and Research Capabilities at Queensland University of Technology’s New 2.0 Second Drop Tower. Advanced Materials Research, 2008. 32: p. 21-24.

59. Schwarzenberg, M., et al., Microgravity simulations with human lymphocytes in the free fall machine and in the random positioning machine. Journal of gravitational physiology: a journal of the International Society for Gravitational Physiology, 1998. 5(1): p. P23.

Bibliography 66

60. Bacabac, R.G., et al., Microgravity and bone cell mechanosensitivity: flow experiment during the DELTA mission. Microgravity Science and Technology, 2007. 19(Copyright 2008, The Institution of Engineering and Technology): p. 133-7.

61. Nusgens, B., Signaling through rho gtpases in microgravity (rho signaling) on iss (soyuz tma-1) belgian soyuz mission "odissea". Microgravity Science and Technology, 2007. 19(Copyright 2008, The Institution of Engineering and Technology): p. 184-6.

62. Moes, M.J.A., et al., Simulation of Microgravity by Magnetic Levitation and Random Positioning: Effect on Human A431 Cell Morphology. 2010(Compendex): p. 1-13.

63. van Loon, J., Some history and use of the random positioning machine, RPM, in gravity related research. Advances in Space Research, 2007. 39(7): p. 1161-1165.

64. Hoson, T., et al., Evaluation of the three-dimensional clinostat as a simulator of weightlessness. Planta, 1997. 203: p. S187-S197.

65. Borst, A.G. and J. van Loon, Technology and Developments for the Random Positioning Machine, RPM. Microgravity Science and Technology, 2009. 21(4): p. 287-292.

66. van Loon, J., et al., Inertial shear forces and the use of centrifuges in gravity research. What is the proper control? Journal of Biomechanical Engineering-Transactions of the Asme, 2003. 125(3): p. 342-346.

67. Brinckmann, E., Biology in space and life on earth2008: Wiley-VCH. 68. Vatsa, A., et al., Osteocyte morphology in fibula and calvaria—Is there a role for

mechanosensing? Bone, 2008. 43(3): p. 452-458. 69. Friel, J.J., J.C. Grande, and D. Hetzner, Practical Guide to Image Analysis2000,

Materials Park, OH, USA: ASM International. 70. Lipski, A.M., et al., The effect of silica nanoparticle-modified surfaces on cell

morphology, cytoskeletal organization and function. Biomaterials, 2008. 29(28): p. 3836-3846.

71. Xu, H.Y., et al., Oscillatory fluid flow elicits changes in morphology, cytoskeleton and integrin-associated molecules in MLO-Y4 cells, but not in MC3T3-E1 cells. Biological Research, 2012. 45(2): p. 163-169.

72. Saad, M., et al., Morphological characterization of wheat powders, how to characterize the shape of particles? Journal of Food Engineering, 2011. 102(4): p. 293-301.

73. Huque, E., Shape Analysis and Measurement for the HeLa cell classification of cultured cells in high throughput screening, 2006, University of Skövde.

74. Molina-Boisseau, S., N. Le Bolay, and M.-N. Pons, Fragmentation mechanism of poly (vinyl acetate) particles during size reduction in a vibrated bead mill. Powder technology, 2002. 123(2): p. 282-291.

75. Belaroui, K., M. Pons, and H. Vivier, Morphological characterisation of gibbsite and alumina. Powder technology, 2002. 127(3): p. 246-256.

76. Mancia, A., et al., Quantitative methods to characterize morphological properties of cell lines. Biotechnology Progress, 2012.

77. Mora, C. and A. Kwan, Sphericity, shape factor, and convexity measurement of coarse aggregate for concrete using digital image processing. Cement and concrete research, 2000. 30(3): p. 351-358.

78. Mullender, M., et al., Osteocyte density changes in aging and osteoporosis. Bone, 1996. 18(2): p. 109-113.

79. Kamioka, H., T. Honjo, and T. Takano-Yamamoto, A three-dimensional distribution of osteocyte processes revealed by the combination of confocal laser scanning microscopy and differential interference contrast microscopy. Bone, 2001. 28(2): p. 145-149.

Bibliography 67

80. Sugawara, Y., et al., Three-dimensional reconstruction of chick calvarial osteocytes and their cell processes using confocal microscopy. Bone, 2005. 36(5): p. 877-883.

81. Kacena, M.A., et al., Experiments with osteoblasts cultured under hypergravity conditions. Microgravity Science and Technology, 2004. 15(1): p. 28-34.

82. Gebken, J., et al., Hypergravity stimulates collagen synthesis in human osteoblast-like cells: evidence for the involvement of p44/42 MAP-kinases (ERK 1/2). Journal of biochemistry, 1999. 126(4): p. 676-682.

83. Searby, N.D., C.R. Steele, and R.K. Globus, Influence of increased mechanical loading by hypergravity on the microtubule cytoskeleton and prostaglandin E2 release in primary osteoblasts. American Journal of Physiology-Cell Physiology, 2005. 289(1): p. C148-C158.

84. Van Loon, J., et al., An atomic force microscope operating at hypergravity for in situ measurement of cellular mechano-response. Journal of Microscopy-Oxford, 2009. 233(2): p. 234-243.

85. Zhou, E.H., C.T. Lim, and S.T. Quek, Finite element simulation of the micropipette aspiration of a living cell undergoing large viscoelastic deformation. Mechanics of Advanced Materials and Structures, 2005. 12(6): p. 501-512.

86. McGrath, J., et al., Simultaneous measurements of actin filament turnover, filament fraction, and monomer diffusion in endothelial cells. Biophysical Journal, 1998. 75(4): p. 2070-2078.

87. Takai, E., et al., Osteoblast elastic modulus measured by atomic force microscopy is substrate dependent. Annals of Biomedical Engineering, 2005. 33(7): p. 963-971.

Appendix 1 Results from Centrifuge Experiments 68

Appendix 1: Results from Centrifuge Experiments

Cell Area under Hyper-gravity

Experiment One:

33003000270024002100180015001200900600300

90

80

70

60

50

40

30

20

10

0

Cell Area (um^2)

Fre

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Distribution of Cell Area (Test Sample)

Figure 26 Distribution of cell area measured at 20g

33003000270024002100180015001200900600300

90

80

70

60

50

40

30

20

10

0

Cell Area (um^2)

Fre

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Distribution of Cell Area (Control Sample)


Two-sample T for C1 vs T1

N Mean StDev SE Mean

C1 500 874 345 15

T1 500 854 405 18


Difference = mu (C1) - mu (T1)

Estimate for difference: 20.5

95% CI for difference: (-26.2, 67.2)

T-Test of difference = 0 (vs not =): T-Value = 0.86 P-Value = 0.388 DF = 998

Both use Pooled StDev = 376.1868

Experiment Two:

420039003600330030002700240021001800150012009006003000

140

120

100

80

60

40

20

0

Cell Area (um^2)

Fre

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Distribution of Cell Area (Control Sample)


330030002700240021001800150012009006003000

90

80

70

60

50

40

30

20

10

0

Cell Area (um^2)

Fre

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Distribution of Cell Area (Test Sample)




C2 500 877 382 17

T2 500 866 403 18





T-Test of difference = 0 (vs not =): T-Value = 0.43 P-Value = 0.669 DF =

998


Cell Shape under Hyper-gravity

Experiment One:

Circularity:

0.900.750.600.450.300.150.00

90

80

70

60

50

40

30

20

10

0

Circularity

Fre

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Distirbution of Cicurlarity (Contol Sample)

Figure 30 Distribution of circularity measured at 1g

0.900.750.600.450.300.150.00

80

70

60

50

40

30

20

10

0

Circularity

Fre

qu

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cy

Distribution of Circularity (Test Sample)

Figure 31Distribution of circularity measured at 20g



C1 500 0.581 0.157 0.0070

T1 500 0.562 0.150 0.0067






998


Aspect Ratio:

1.080.960.840.720.600.480.36

120

100

80

60

40

20

0

Aspect Ratio

Fre

qu

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cy

Distribution of Aspect Ratio (Control Sample)

Figure 32Distribution of aspect ratio measured at 1g

0.960.840.720.600.480.360.24

90

80

70

60

50

40

30

20

10

0

Aspect Ratio

Fre

qu

en

cy

Distribution of Aspect Ratio (Test Sample)

Figure 33 Distribution of aspect ratio measured at 20g



APC1 500 0.8510 0.0956 0.0043

APT1 500 0.843 0.109 0.0049

Difference = mu (APC1) - mu (APT1)





998


Solidity:

1.000.950.900.850.800.750.700.650.600.550.500.45

90

80

70

60

50

40

30

20

10

0

Solidity

Fre

qu

en

cy

Distribution of Solidity (Control Sample)

Figure 34 Distribution of solidity measured at 1g

1.000.950.900.850.800.750.700.650.600.550.500.45

140

120

100

80

60

40

20

0

Solidity

Fre

qu

en

cy

Distribution of Solidity (Test Sample)




SC1 500 0.8625 0.0706 0.0032

ST1 500 0.8637 0.0768 0.0034

Difference = mu (SC1) - mu (ST1)

Estimate for difference: -0.00123


T-Test of difference = 0 (vs not =): T-Value = -0.26 P-Value = 0.791 DF =

998



Experiment Two:

Circularity:

0.900.750.600.450.300.15

80

70

60

50

40

30

20

10

0

Circularity

Fre

qu

en

cy

Distribution of Circularity (Control Sample)


0.900.750.600.450.300.150.00

70

60

50

40

30

20

10

0

Circularity

Fre

qu

en

cy

Distribution of Circularity (Test Sample)




C2 500 0.573 0.162 0.0073

T2 500 0.562 0.150 0.0067





998



Aspect ratio:

0.960.840.720.600.48

100

80

60

40

20

0

Aspect Ratio

Fre

qu

en

cy

Distribution of Aspect Ratio(Control Sample)


0.960.840.720.600.480.36

100

80

60

40

20

0

Aspect Ratio

Fre

qu

en

cy

Distribution if Aspect Ratio (Test Sample)




C2 500 0.8472 0.0925 0.0041

T2 500 0.8460 0.0982 0.0044





998



Solidity:

1.000.900.850.800.750.700.650.600.550.500.45

120

100

80

60

40

20

0

Solidity

Fre

qu

en

cy

Distribution of Solidity (Control Sample)


1.000.900.850.800.750.700.650.600.550.500.45

120

100

80

60

40

20

0

Solidity

Fre

qu

en

cy

Distribution of Solidity (Test Sample)




C2 500 0.8640 0.0724 0.0032

T2 500 0.8657 0.0753 0.0034


Estimate for difference: -0.00169


T-Test of difference = 0 (vs not =): T-Value = -0.36 P-Value = 0.718 DF =

998


Appendix 2 Preliminary Design for Side-view Optical System 76

Appendix 2: Preliminary Design for Side-View Optical System

Preliminary Design for Optical System Configurations

• Based on the previous developed side-view chamber, the configuration of my

preliminary design is shown below:

Figure 42 Over view of the preliminary design for side-view optical system

• Instead of two separate mirrors, build two mirrors on a base to form as one system

ensure that two mirrors will be always in parallel (Easy to set up).

• The thickness of rectangular tube lift up the position of cell ensures side-view image

can be captured properly by the mirror.

Preliminary Design for Optical System Dimensions

• The dimensions of this optical system is restricted by two main factors:

1: The width of the system (AB) need to within the microscope field of objective lens;

2: The working distance of objective lens: optical path length of side view must smaller than

objective working distance: (C+D+E).

Figure 43 Working distance for side-view optical system

Chromium coated mirrors

Cell Borosilicate cell chamber


• Working distances various for different types of objectives:

• Microscope field measured by put clear plastic ruler with mm markings on top of the

stage of microscope. Microscope field measured under 40X magnification is 2mm:

Figure 44 Plastic ruler placed under 40x magnification lens, showing that the microscope filed is 2mm

• Assuming the objective we are going to use has the magnification of 40X (microscope

field: 2mm, working distance 2.1mm). Then the ideal dimensions of this optical

system is shown below:

Figure 45 Preliminary design of the size of the optical system


• The suggested dimension picked for cell chamber is based on the available

commercial products, and the thickness of the mirror base is restricted by the

microscope filed and objective working distance.

A+B= 0.84+0.84=1.68mm which is in the microscope filed 2mm

C+D+E= 0.6+0.12+0.72+0.12+0.4=1.94mm which is within the maximum working

distance of the 40x objective.

Preliminary Design for Optical Path Modulation

• The side view reflected by the mirror has a longer optical path length than top view.

However, the specimen appears sharp on objective lens only within the depth of field

(DOF);

• Due to the longer optical path length, DOF may do not cover side view image, thus, in

order to obtain the side- and top view images both in focus, one of the optical path

length should be modulated

• It is know that the working distance of the objective determined by:

1: The material (refractive index) of the objective lens

2: The refractive index of the medium

• A preliminary solution is to add a high refractive index medium (e.g. glass) between

objective lens and specimen to expand the working distance of the objective:

Figure 46 Optical path length with different refractive index medium

morphology of osteocyte cells in normal and …eprints.qut.edu.au/62160/1/huan_yuan_thesis.pdf ·...

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