Nano Research
Nano Res
DOI 10.1007/s12274-015-0825-8
Nanostructure and mechanical property of the osteocyte
lacunar-canalicular network associated bone matrix
revealed by quantitative nanomechanical mapping
Shuai Zhang1, Fiona Linnea Bach-Gansmo1,2, Dan Xia1, Flemming Besenbacher1, Henrik Birkedal1,2 (),
and Mingdong Dong1 ()
Nano Res., Just Accepted Manuscript • DOI 10.1007/s12274-015-0825-8
http://www.thenanoresearch.com on June 1, 2015
© Tsinghua University Press 2015
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1
TABLE OF CONTENTS (TOC)
Nanostructure
and
Mechanical Properties of the
Osteocyte
Lacunar-Canalicular
Network
Associated
Bone
Revealed
by
Matrix
Quantitative
Nanomechanical Mapping
Shuai Zhang1, Fiona Linnea
Bach-Gansmo1,2,
Flemming
Dan
Xia1,
Besenbacher1,
Henrik
Birkedal1,2*,
Mingdong
Dong1,*
and
1The
Interdisciplinary
Nanoscience Center, Aarhus
University
2Department
of Chemistry,
Aarhus University
The reduced modulus maps localize and show the heterogeneous nanostructure and
mechanical property of osteocyte lacunar-canalicular network associated bone matrix.
They were captured by nanoindentation and quantitative nanomechnical mapping,
respectively.
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Nano Res (automatically inserted by the publisher)
DOI (automatically inserted by the publisher)
Review Article/Research Article
Research Article
Nanostructure and Mechanical Property of the Osteocyte
Lacunar-Canalicular Network Associated Bone Matrix
Revealed by Quantitative Nanomechanical Mapping
Shuai Zhang1, Fiona Linnea Bach-Gansmo1,2, Dan Xia1, Flemming Besenbacher1, Henrik Birkedal1,2(), and
Mingdong Dong1()
1 The
Interdisciplinary Nanoscience Center, Aarhus University
of Chemistry, Aarhus University
2 Department
Received: day month year / Revised: day month year / Accepted: day month year (automatically inserted by the publisher)
©The Author(s) 2010. This article is published with open access at Springerlink.com
Received: day month year
ABSTRACT
Revised: day month year
Osteocytes are the main bone cells embedded in the bone matrix where they
Accepted: day month year
form a large surface-area network called the lacunar-canalicular network (LCN)
(automatically inserted by
the publisher)
© Tsinghua University Press
by interconnecting their resident spaces, the lacunae, and the canaliculi. More
and more evidences point to osteocytes playing a pivotal role in maintaining
bone quality. On the one hand, osteocytes transmit mechanical strain and
and Springer-Verlag Berlin
micro-environmental signals through the LCN to regulate the activity of
Heidelberg 2014
osteoblasts and osteoclasts, and on the other hand, there are increasing
evidences that the LCN associated bone matrix can be remodeled by osteocytes
KEYWORDS
in a process called osteocytic osteolysis. However, due to the significant
Lacunar-canalicular
network,
osteocyte,
perilacunar bone matrix,
pericanalicular
bone
matrix, reduced modulus,
mechanical properties
challenges to assess and characterize the LCN associated bone matrix, little is
known about the structure and corresponding mechanical properties. In this
work, we used quantitative nanomechanical mapping, backscattered electron
imaging and nanoindentation to characterize the LCN associated bone matrix.
The results show that the techniques can be used to probe the LCN associated
bone matrix. Nanoindentation and quantitative mechanical mapping reveal
spatially inhomogeneous mechanical properties of the bone matrix associated
with osteocyte lacunae and canaliculi. The obtained nano-topography and
corresponding nano-mechanical maps reveal altered mechanical properties in
the immediate vicinity of the osteocyte lacunae and canaliculi, which cannot be
explained solely by the topographic change.
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1. Introduction
Osteocytes are the most abundant type of bone cells.
They are embedded within the mineralized bone
matrix. In the bone matrix, the osteocytes reside in
spaces called osteocyte lacunae, with typical lacunar
dimensions ranging between ~3-20 µ m. [1-5] The
lacunae are connected by canaliculi of ~200-500 nm
diameter,[6-8] to form a large surface-area
connected
network
referred
to
as
the
lacunar-canalicular network (LCN). Because the
osteocytes are buried in the mineralized bone matrix,
they are hard to access, and much less is known
about them than about the bone surface associated
osteoblasts and osteoclasts.[9] Recently, osteocytes
have gained massive attentions, as it is becoming
increasingly clear that they play a pivotal role in
maintaining bone quality.[2, 10, 11] It is now
established that osteocytes regulate the bone
remodeling activities of osteoblast and osteoclasts
by
sensing
mechanical
signals
and
micro-environmental conditions. [12-16] The
structure of the LCN and the characteristics of the
associated bone matrix have been proposed to
influence the efficiency of mechanosensing, thereby
affecting the bone repair system.[6, 17, 18]
Additionally, osteocytes have been suggested to be
involved in calcium homeostasis in a process called
osteocytic osteolysis, where the osteocytes dissolve
LCN associated bone matrix. [2, 19] While this
capability has been heavily debated in the literatures,
there is now mounting evidence supporting it. [11,
20, 21] Probing the local structure and mechanical
properties of the LCN associated bone matrix
(perilacunar and pericanalicular matrix) is therefore
essential to unravel how osteocytes and their
cellular processes affect the local bone matrix.
The LCN associated matrix and the topography of
osteocyte lacunae have been investigated using
sub-100 nm techniques including ptychography [22],
synchrotron nano-CT, [23] serial focused ion beam
scanning electron microscopy (FIB/SEM) based
backscattered electron imaging (BEI),[8, 24-27] and
serial FIB/SEM tomography on demineralized
samples [8] but detailed information on the
structural and mechanical properties, and the
relation between these are still lacking. Additionally,
high resolution mechanical mapping is crucial for
developing a complete model of the mechanical
properties of bone, covering the relevant length
scales from nano- to millimeter. [28, 29] Hence,
methods sensitive to both structural information
and local mechanical properties of the LCN
associated bone matrix are required.
Atomic force microscopy (AFM) based techniques
allow
exploring
the
relationship
between
topography and mechanical properties with
nanoscale resolution. These techniques have already
been used to characterize the structure of biological
materials such as bone.[30-33]
The recently
developed AFM-based quantitative nanomechnical
mapping technique allows gathering quantitative
mechanical
and
morphological
information
simultaneously. [34-36] Although it has been widely
applied to soft biomaterials, such as protein/peptide
based ones [37-39], its applicability to hard
biological materials remains less explored. Here we
applied quantitative nanomechanical mapping in
combination with BEI and nanoindentation to
characterize the LCN associated bone matrix.
Quantitative mechanical mapping with nanometer
spatial resolution enables mapping the topography
and mechanical properties of the LCN, and these
results are expected to be essential for
understanding the role of osteocytes and the LCN in
regulating bone quality and calcium homeostasis.
2. Experimental
2.1 Sample preparation
Bone samples from 4 months old female Wistar rats
obtained from a different study[40, 41] have been
measured. Cross sectional samples (400-500 µ m
thick) of cortical bone from the mid-femur of rat
hind limbs were sawed (Exakt Apparatebau,
Norderstedt,
Germany)
and
subsequently
embedded in Epofix (Struers, Ballerup, Denmark)
and polished (Knuth Rotor Polishing machine,
Struers, Ballerup, Denmark) using abrasive paper
and diamond grains (3 to 1/4 μm grain size). The
animal experiment was approved by the Danish
Animal Experiments Inspectorate.
2.2 Backscattered Electron Imaging (BEI)
For
Backscattered
Electron
Imaging
(BEI)
measurements, the polished cross sections from five
individual animals were rendered electrically
conductive by evaporative carbon coating ((Emitech
K950 evaporator, Ashford, UK, 25 nm thick layer) to
limit charging artefacts. The BEI measurements
were conducted according to the method adapted
by Bach-Gansmo [41] from the work of Roschger et
al.[42]and performed on a Nova NanoSEM600 (FEI
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Research
Company, Hillsboro, USA) with a GAD detector
(FEI, Eindhoven, The Netherlands) consisting of two
half circular silicon solid state detectors. The
accelerating voltage of the beam was adjusted to 20
kV, and the working distance was kept at 15 mm.
2.3 Nanoindentation
Indentation measurements were performed using a
Hysitron TriboIndenter (Hysitron, Minneapolis, MN)
with a Berkovitch tip as described by Bach-Gansmo
et al, [41] and the samples from three animals were
tested. The measurements in Fig. 1 consisted of 792
indents placed with 1 µ m spacing employing a
maximum load of 500 µ N. This combination of
indent spacing and maximum load has previously
been validated in indentation studies of compact
bone.[43] The small indent spacing is necessary to
map changes occurring close to the lacunar surface.
As each indent takes approximately 5 minutes
including 10 s load, 60 s hold time to relax
viscoelastic effects [44] and 10 s to unload and time
for instrument stabilization, the measurement is
laborious and slow. The unloading segment range of
95% to 20% Pmax in the load-displacement diagrams
were used for data fitting, and the reduced elastic
modulus (stiffness, Er) and hardness (H) calculated
using the Oliver-Pharr method.[45] The reduced
elastic modulus is reported due to uncertainties
introduced by estimating Poisson´s ratio for
bone.[46] Hence, the reported Er values are relative,
and not absolute values of stiffness for comparison
with table values of Young´s modulus. The
measurements were performed in dry conditions.
2.4 Quantitative Nanomechanical mapping
All topography and nanomechnical maps were
captured by MultiMode VIII AFM (Bruker, CA). The
probes used in the experiment is TAP525A (Bruker,
CA) with 8 nm typical tip radius and 200 N/m
typical spring constant. The samples from two
individual animals were tested. The spring constant
of each probe had been further calibrated by the
Thermal Noise method[47]. Offline analysis of
images and force curves were done with Nanoscope
Analysis (Bruker, CA) and Scanning Probe Image
Processor (SPIPTM, Image Metrology ApS, Lyngby,
Denmark).
3. Results and Discussion
Osteocyte lacunae and the perilacunar bone matrix
from rat cortical bone were imaged using BEI as
shown in Fig. 1a and 1b. The gray level of the
images captured by BEI effectively maps the local
degree of mineralization, with lighter pixel values
corresponding to a higher degree of mineralization.
[24, 25] Fig. 1a reveals several osteocyte lacunae (L)
and a few blood vessel cavities (V), both having
dark gray levels. The lacunae exhibit a large
variation in size, shape and orientation.
Furthermore, some lacunae have mineral deposits
(labeled as Partly Mineralized Lacunae (PML) or
Mineralized Lacunae (ML) in Fig. 1a), with the
mineral fillings possibly reflecting a near-apoptotic
state of the osteocyte. [48] There is also a
heterogeneity in the local degree of mineralization
of the perilacunar matrix, with some lacunae having
a more highly mineralized perilacunar matrix
(lighter gray level values, one example highlighted
by black dashed circle) than others. By increasing
the imaging magnification, the canalicular (C)
network is partly revealed (Fig. 1b) around a single
lacuna (L). The high degree of porosity in the
perilacunar bone reflects the vast number of
canaliculi connecting the imaged lacuna with its
neighboring lacunae. A few canaliculi can be seen
running more or less parallel to the imaged section,
whereas the numerous circular porosities represent
canaliculi intersecting the image plane. The high
degree of interconnectivity of the LCN is sketched in
a simple manner in Fig. 1c.
BEI provides maps of the local degree of
mineralization at the micro-scale, but does not
provide any information on mechanical properties.
It is well known that the micro- and macro-stiffness
of bone increase with mineral content, but the
mechanical properties are not only sensitive to the
level of mineralization but also to the collagen fibril
orientation. [49, 50] Hence, the mineral content
alone is not a sufficient measure to probe bone
quality.
At
the
nanoscale,
interfibrillar
non-collagenous macromolecules are expected to
result in additional mechanical heterogeneity.
Nanoindentation has been widely used in bone
research to map mechanical properties. [51, 52]
Herein, we applied it to map the local mechanical
properties of the bone matrix surrounding osteocyte
lacunae. Fig. 1d shows a representative map of the
reduced modulus (Er) of the bone matrix obtained
with 1 µ m indent spacing (which in turn defines the
lateral resolution). The Er is presented by rainbow
color with red and blue representing high and low
reduced moduli, respectively. The map reveals that
the reduced modulus of the perilacunar matrix is
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smaller than that of the bone matrix further away
from the osteocyte lacuna. The lower panel of Fig.
1d shows the average Er from the area marked by
gray dashed lines in the upper panel of the Fig. 1d.
The average line profile confirms the trend observed
in the upper panel: the bone further away from the
lacuna has the same stiffness on both sides, whereas
the Er of the bone matrix close to the lacuna is more
heterogeneous.
Although nanoindentation allows mapping local
mechanical properties quantitatively, the resolution
of the technique is limited , due to the radius of the
diamond probe and the finite indent depth, which
makes it very challenging to obtain high fidelity
maps at the spatial resolution needed to resolve
local variations in mechanical properties around the
~3-20 µ m diameter osteocyte lacunae. The limited
resolution makes it even more difficult to map the
~200-500 nm wide canaliculi and the pericanalicular
matrix, which is an indispensable part of the LCN.
The bone mineral crystals, the collagen fibrils and
non-collagenous proteins are of sub-100 nm size.
These nanoscale structural features determine the
mechanical response of the LCN and the associated
bone matrix. Hence, conventional nanoindentation
averages over several structural features relevant to
the mechanical performance of the LCN associated
bone matrix. To achieve higher resolution structural
and mechanical insights, we applied quantitative
nanomechnical mapping to characterize the
perilacunar and pericanalicular matrices.
A typical AFM topography image displayed in Fig.
2a shows a single osteocyte lacuna and the
associated bone matrix. The osteocytes were
removed during sample preparation; hence the
osteocyte lacuna is shown as a hole in the matrix
(dark contrast). Simultaneously, the in-situ reduced
modulus map has been recorded. It is shown as the
colored skin covering the reconstructed 3D
topography image of Fig. 2a (Fig. 2a’). This
illustrates the correlation between topography and
stiffness of the bone matrix. According to Fig. 2a’,
the perilacunar matrix is softer than the rest of the
matrix (the blue color level indicating lower stiffness,
green color level indicating medium stiffness, red
color level indicating higher stiffness). Additionally,
the perilacunar matrix around the osteocyte is
inhomogeneous in stiffness, with the area to the left
of the osteocyte lacuna being much softer than the
other regions.
Higher resolution maps provide much more detail
on the nature of the perilacunar matrix. Fig. 2b’
shows a higher resolution Er map of the area near
the left bottom corner of the osteocyte lacuna
contour. Blue & green dominate in Fig. 2b with
lower stiffness rather than red & green in Fig. 2c’. By
comparing the mechanical maps with the
topography images in Fig. 2b and 2c, it is obvious
that the variation in Er is not a direct function of the
variation in topography but rather must originate
from variations in matrix nano-structure and
composition.
The resolution of these nanomechnical maps is
remarkably improved compared to nanoindentation
and the standard AFM-based force volume maps.
Fig. 2d shows two typical curves, captured in
mature bone and in the perilacunar matrix,
respectively. The difference is obvious, reflecting a
smaller average stiffness of perilacunar matrix
compared to the bone matrix further away from the
lacuna. The local reduced moduli were determined
using the Derjaguin–Muller–Toporov model [53].
Thereby, the distributions of the logarithm of Er (Fig.
2e) on different areas (Fig. 2b and 2c) could be
constructed. The logarithm of Er is seen to be
normally distributed, reflecting that Er is lognormal
distributed. The peak value of the distribution of the
perilacunar matrix (i.e. data from Fig. 2b), 10.0±2.8
GPa, is much lower than that of the mature bone
matrix, 28.8±10.1 GPa (i.e. data from Fig. 2c) with a
student t-test p value far less than 0.0001. These data
agree well with the nanoindentation results (Fig. 1d),
but with much higher resolution, localization and
structural specificity.
After characterizing the nano-structure and
nano-mechanical properties of the perilacunar
matrix, our attention turned to the pericanalicular
matrix, the other main component of the LCN
associated bone matrix. Fig. 3a shows the
topography of the bone matrix around an osteocyte
lacuna. The contour line is drawn based on the
topography (the black solid line in Fig. 3a)
approximately,
and
some
of
the
several-hundred-nanometer wide canaliculi are
clearly identified according to the height (color)
contrast and highlighted by the white arrows
(labeled as canaliculus (C)). Furthermore, one
canaliculus and the surrounding pericanalicular
matrix (rectangular marked area in Fig. 3a) were
imaged at higher resolution (Fig. 3b and 3c). The
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Research
canaliculus branching into the pericanalicular bone
matrix is indicated by the blue contour line (Fig. 3b).
Again, the 3D topography map is combined with
the corresponding in-situ stiffness map as skin (Fig.
3c) and the results show that the pericanalicular
matrix is softer than the surrounding bone matrix.
After collecting force-distance curves (Fig. 3d), the Er
of the pericanalicular matrix (20.0±7.5 GPa, Fig. 3e)
was found to have a lower value than the bone
matrix (31.6±5.2 GPa, calculated from Fig. 3e) with
a student t-test p value less than 0.0001, but larger Er
than the perilacunar matrix with a student t-test p
value less than 0.0001. Interestingly, both the
diameter of the canaliculi and the stiffness of the
pericanalicular matrix seemed to vary with distance
from the osteocyte lacuna: the diameter of the
canaliculi decreases while the Er of pericanalicular
matrix increases with increasing distance from the
lacuna.
Not only the Young’s modulus, but also the energy
dissipation maps (Figure S1 and S2 in ES) indicate a
difference between pericanalicular matrix and bone
matrix further away from the canaliculi. The energy
dissipation maps represent the variations of the
energy dissipated during every tapping cycle. It
indicates that bone tissue is able to dissipate
mechanical energy in order to prevent dramatic
damage. Dissipation is influenced by several factors
including capillary forces and viscoelasticity of the
materials.[54] According to Figure S2E, the average
dissipated energy in the pericanalicular matrix is
larger than that of the bone matrix. It proves that the
pericanalicular matrix is different from the bone
matrix.
The present findings of the pericanalicular matrix
being different from the bone matrix further away is
in agreement with the recently published data of
Reznikov et al. who showed that the matrix
structure is remarkably different around canaliculi
both in terms of collagen fibril organization but also
in composition[8]. Herein, we show that this leads to
drastic changes in mechanical properties.
Collagen fiber bundles are the main organic
component in the bone matrix, and in the present
experiment, collagen fibers embedded in the
perilacunar matrix were also captured by the AFM
measurements. Fig. 5a shows bundles of collagen
fibers and individual collagen fibers are
recognizable from the high magnification image (Fig.
5b). The typical d-band periodic structure of type I
collagen fibers is visible with a period of 64.9±3.6 nm.
[41, 55] The correlation between topography and
stiffness maps (Fig. 5d) clearly reveals a much lower
stiffness of the collagen fibers compared to the
mineralized bone. The captured collagen fibers were
found by quantitative analysis (Fig. 5e and 5f) to
have a reduced modulus of 12.6 ±3.5 GPa, which is
in good agreement with previous finding of
mineralized collagen fibers.[56, 57] The mineralized
collagen fibers are proposed to resist LCN
deformation or crack formation/propagation. [32]
Collagen fibers making up bone have sub-micron
diameter and are here clearly localized by
quantitative nanomechnical mapping.
4. Conclusions
In this work, the feasibility of applying quantitative
nanomechanical mapping to explore hard
heterogeneous
biomaterials
with
nanoscale
resolution, was demonstrated. The local Young’s
modulus of the bone matrix, which was obtained by
quantitative nanomechnical mapping is of the same
magnitude as that obtained by nanoindentation. But
nanomechanical mapping provides much better
resolution, which allowed unravelling individual
parts of the LCN. Direct measurements of the
mechanical properties of the perilacunar and
pericanalicular bone matrix with nano-resolution
are essential for fully understanding the biological
functions of osteocytes and the LCN in bone. The
mechanical properties in the perilacunar regions
were found to be inhomogeneous and displayed
lower average stiffness than the bone matrix further
away from the osteocyte lacunae. The mapping of
local mechanical properties around and in canaliculi
showed that the local mechanical properties of the
canaliculi may depend on the spatial relation to the
parent osteocyte and/or the canalicular diameter
and in turn to the nanoscale organization and
composition of the extracellular matrix.
The inhomogeneous mechanical properties of the
LCN associate bone matrix will likely impact the
strain sensing capabilities of the LCN. The present
findings are also relevant for modeling work, where
assumptions on homogeneous bone matrix
properties have been employed until now.[6] While
further work is needed to establish the degree to
which these observations influence cell signaling
and whole organ response, such as the mechanical
variations between the bone matrixes from control
and treated animals with induced or inhibited
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osteocyte osteolysis/perilacunar remodeling, they
clearly demonstrate that bone structure and
mechanics is highly complex and most likely tuned
towards local conditions. The present work
demonstrates that the LCN associated bone matrix is
less stiff than the bone further away from the
osteocyte lacunae. Combining this finding with the
large density of osteocytes in bone and the
mounting evidence that osteocytes are able to
demineralize the perilacunar matrix indicates that
the LCN is likely to play a much more direct role in
bone nano- and micromechanics than hitherto
realized.
[6]
Acknowledgements
[7]
The authors gratefully acknowledge the financial
support from the Interdisciplinary Nanoscience
Center by the Danish National Research Foundation
to the Sino-Danish Center of excellence on “The
Self-assembly
and
Function
of
Molecular
Nanostructures on Surfaces” and from the Carlsberg
Foundation. M.D. acknowledges a STENO grant
from the Danish Research Council and the Young
Investigator Program from the Villum Foundation.
H.B. acknowledges the Human Frontiers Science
Program and the Danish Research Councils for
funding.
[8]
[9]
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Figures
Figure 1 a) BE image of rat cortical bone revealing numerous osteocyte lacunae (L), partially mineralized and mineralized lacunae
(PML & ML), and a few larger blood vessel cavities (V). A variation is seen in degree of mineralization (gray level) of the
perilacunar bone and one example of a more highly mineralized perilacunar matrix is highlighted by a black dashed circle. b) Higher
magnification of BEI reveals the beginning of the canalicular (C) network surrounding a single osteocyte lacuna (L). c) Sketch of
three lacunae (L) and canaliculus (C) to illustrate the LCN, and its high degree of connectivity. d) Reduced modulus map obtained
from nanoindentation measurements of bone matrix around a single lacuna. The osteocyte lacuna is located in the center with void
pixels corresponding to positions where no measurements were made in order to avoid tip crash. The resolution is 1 µm per pixel. A
corresponding line profile is presented in the lower panel, obtained by averaging the values in the area marked by dashed grey lines
in the upper panel.
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Figure 2 Topography images and reduced Young’s modulus maps of the bone matrix around an osteocyte lacuna. a) The overview
topography images. a’) 3D topography reconstruction of a) covered by the corresponding stiffness map. b), b’), c) and c’) Higher
magnification images of the areas indicated by the dashed squares on a) and a’), respectively. d) Two typical force-piezo movement
curves recorded on different areas showing the indent part of the full curves shown in the inset. e) Fitted distributions of the
logarithm of Er of Fig. 2b’ and 2c’.
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Figure 3 Topography images and reduced Young’s modulus maps of the bone matrix around lacunae and canaliculi. a) The
topography image of the bone matrix around an osteocyte lacunae; the dark contour line roughly indicates the lacunar surface and the
arrows mark the alignments of example canaliculi. b) Higher magnification image at the position indicated by the dashed square in a)
showing the topography of pericanalicular matrix; the blue contour line highlights the alignment of the canaliculus from the top-left
corner to the bottom-right of the image. c) 3D topography reconstruction of b) covered by the corresponding Er colour map. d) the
indent part of two typical force-distance curves recorded at different positions in c; the inset display the full curves. e) The
distributions of the logarithm of Er with accompanying fits indicated by dashed lines
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Figure 4 Morphology images and Er map of the collagen fibers on the perilacunar matrix, near the osteocyte lacunae in Fig. 2a. a)
The overview morphology image of the collagen fiber-bunch. b) The zoom-in morphology image, showing individual collagen
fibers. c) The line profiles of the corresponding dashed color lines along the fibers in Fig. 4b. d) The 3D morphology reconstruction
of the image zoom-in from Fig. 4a, 4b covered by the corresponding stiffness map. e) The two typical force-piezo movement curves
which were recorded on different areas; zoomed from the inset curves. e) The fitted distributions of the logarithm of Er of selected
collagen fibers.
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Electronic Supplementary Material
Nanostructure and Mechanical Property of the Osteocyte
Lacunar-Canalicular Network Associated Bone Matrix
Revealed by Quantitative Nanomechanical Mapping
Shuai Zhang1, Fiona Linnea Bach-Gansmo1,2, Dan Xia1, Flemming Besenbacher1, Henrik Birkedal1,2(), and
Mingdong Dong1()
1 The
Interdisciplinary Nanoscience Center, Aarhus University
of Chemistry, Aarhus University
2 Department
Supporting information to DOI 10.1007/s12274-****-****-* (automatically inserted by the publisher)
Figure S1 The topography and corresponding Yong’s modulus maps of LCN. The dashed squares
indicate the zoom-in position of Figure S2.
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Figure S2 The zoom-in topography, and corresponding energy dissipation, deformation and Young’s
modulus maps of pericanalicular matrix and bone matrix. (E) the distributions of energy dissipation
calculated from selected area of Figure S2B with a student t-test p value far less than 0.0001.
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Potential cover art, Nanomechnical maps LCN-bone matrix
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