Characteristics of three sizes of silica nanoparticles in the osteoblastic cell line, MC3T3-E1

Abstract

Reconstruction of bone defects is still challenging for the clinician, owing to the little achievement in the effect of bone materials on osteoblastic cells. In this work, the size effect of silica nanoparticles (SNs) on cellular uptake, cytotoxicity, and cell function in the osteoblast cell line, MC3T3-E1, is studied to reveal the potentials of SNs for bone regeneration. The SNs with three different sizes are prepared using the Stöber approach and labeled with FITC. Confocal laser scanning microscopy, fluorescence-activated cell sorting and fluorescence spectrophotometry are used to evaluate the effects. All three different sized FITC-labeled silica nanoparticles have similar cellular uptake (>90%), determined by fluorescence-activated cell sorting (FACS) analysis, which suggest that all three silica nanoparticles generally have good cellular affinity. Fluorescence spectrophotometry results, however, indicate that cellular uptake is increased with a decrease in the size of the SN. Interestingly, the smaller silica nanoparticles could induce more MC3T3-E1 cell apoptosis than that of larger silica nanoparticles, and it is dose-dependent. MTT assays demonstrated that all three SNs are capable to decrease cell proliferation at a higher concentration (100 μg ml⁻¹). These results indicate that the SNs are cytotoxic, which is size and concentration-dependent. Importantly, all three SNs can directly stimulate mineralized nodule formation, which is also size-dependent. These results suggest that SNs are potentially applicable in bone regeneration, and it is possible to decrease unwanted side effects by controlling dose and size of SNs.

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1. Introduction

With the rapid development of nanotechnology, considerable attention has been attracted by its commercial and biomedical applications due to the unique physical properties and high chemical reactivity of nanoparticles.^1–3 Researchers are devoted to understand the interactions between nanoparticles and biological systems to optimize their diagnostic sensitivity and therapeutic efficacy.^4–6 Some fundamental studies have demonstrated that the size,⁷ shape,⁸ surface charge⁹ and surface modification¹⁰ of the nanoparticles have important effects on plasma proteins, cellular uptake, particle toxicity, and molecular response. For example, Tang's group reported that particles with larger aspect ratios were absorbed in larger amounts and had faster internalization rates.⁸ Most of these studies, however, are carried out using tumor cells or tumor models,^11–15 and fewer researches are related with bone. Therefore, the interactions between nanoparticles and normal cells or tissues should be given significant attention, in particular those with bone cells and tissues.

Bone is a highly dynamic organ that could be regenerated throughout the lifetime through a process termed as bone remodeling, during which old bone is resorbed by osteoclasts and new bone is synthesized by osteoblasts.¹⁶ It is important to seek an effective method to inhibit bone loss or bone fractures caused by aging and inflammatory conditions, including rheumatoid arthritis, bacterial and viral infections or estrogen deficiency.¹⁷ Drawbacks of existing treatment modalities, such as autologous bone and allograft, could cause poor shaping, secondary injury, and immunological rejection. Recently, it has been demonstrated that an engineered biomaterial combined with growth factors is a potential alternative novel treatment in bone repair and regeneration.¹⁸ Therefore, the biological effects of the material should be carefully studied.

Silica is widely applied in biomedicine because of its high stability, good biocompatibility and minimal immunogenicity.¹⁹ It was reported that Bioglass 45S5, which contains a high level of silica, could induce rapid bone bonding by forming an apatitic layer on the surface of ceramics.²⁰ Therefore, the interactions between silica and bone cells or bone tissues should be studied in order to use silica nanoparticles to stimulate bone formation. However, to the best of our knowledge, there has been no systematic assessment of the ability of different sized SNs on cellular uptake, cytotoxicity and mineralization of bone tissue. In this study we synthesized three different sizes of silica nanoparticles (SNs) and compared their physicochemical properties, cellular uptake, cytotoxicity and biological function in an osteoblastic cell line, MC3T3-E1, to understand their biocompatibility, and to determine if we can use SN to promote bone regeneration.

2. Experimental section

2.1 Synthesis and characteristics of SNs

In an ester–alcohol–water–alkali system, different-sized SNs were synthesized by applying the Stöber approach using diluted tetraethyl orthosilicate (TEOS) and ethyl alcohol conditions with a catalyst NH₃·H₂O.²¹ As described in Table 1, absolute ethyl alcohol was mixed with deionized water and NH₃·H₂O, stirred for 20 minutes, TEOS (Beijing Chemical Reagents Company, Beijing, China) was then added with stirring at 25 °C. The size of SNs was controlled by the molar ratio of reagents and reaction time (Table 1). Different-sized SNs were collected by centrifugation at 12 000 rpm, 8500 rpm and 7000 rpm for 10 minutes. These synthesized SNs were dispersed and alternately centrifuged three times with ethanol and deionized water. SNs were dried at 60 °C. Morphologies of the SNs were examined with a scanning electron microscope (SEM) (FESEM6700F, JEOL, Tokyo, Japan). The average hydrodynamic diameter and the zeta potential of nanoparticles were obtained using dynamic light scattering (DLS) (Zetasizer NanoZS, Malvern Instruments, Britain) at 25 °C.

Table 1 Summary of silica nanoparticle synthesis

Size (nm)	C2H5OH (ml)	NH3·H2O (ml)	H2O (ml)	TEOS (ml)	Reaction time (hour)
121	92	2.48	43.2	3.5	10
310	151.4	195.8	3.6	16.8	4
646	112.5	122.5	4.5	10.5	4

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2.2 Preparation of fluorescein isothiocyanate (FITC)-labeled SNs

To label SNs with FITC, the above mentioned protocol was slightly modified. Briefly, 5 mg of FITC (Sigma-Aldrich, St Louis, MO, USA) was dispersed in 5 ml of absolute ethyl alcohol and treated by ultrasonic dispersion at 100 Hz for 30 min. This solution was transferred into 500 μl of APTES (3-aminopropyl triethoxysilane, Sigma) to add amine groups to FITC and the solution was then stirred at room temperature for 24 h. 1 ml of this mixture was mixed with a certain amount of deionized water and ethyl alcohol as described in Table 1 for 1 h, and 0.3 ml of TEOS and various amount of aqueous ammonia, as described in Table 1, was added to this mixture and mixed. After 1 h, various amounts of TEOS for different sizes of SNs, as described in Table 1, were added with continuous stirring. The rest of the preparation was the same as described above. The preparation procedure was carried out in dark, and the FITC-labeled SNs were stored in the dark at room temperature.

2.3 Cell culture

MC3T3-E1 pre-osteoblasts of mice were obtained from the Chinese Academy of Sciences Cell Bank (Shanghai, People's Republic of China). This cell line was grown in α-MEM (Gibco, Grand Island, NY, USA) supplemented with 10% fetal bovine serum (FBS) (Gibco), 100 U ml⁻¹ penicillin (Gibco) and 100 μg ml⁻¹ streptomycin (Gibco), and incubated at 37 °C in a humidified 5% CO₂ atmosphere. The medium was changed every 2–3 days.

2.4 Cellular uptake assay

To evaluate the cellular uptake of each SN, MC3T3-E1 cells were seeded at 2 × 10⁵ cells per well in a six-well plate, which contained a glass cover, and were cultured for 24 hours. 20 μg ml⁻¹ of FITC-labeled SN was added into each corresponding well and cultured. After 24 hours, cells were washed twice with PBS, fixed in 4% formaldehyde (Beijing Dingguo, Beijing, China) at 37 °C for 10 min and stained with10 μg ml⁻¹ of DAPI for 10 min. The cells were then washed twice with PBS and studied using confocal laser scanning microscopy (CLSM, Olympus, Japan).

To compare the cellular uptake efficiency of different-sized SNs, all culturing and labeling procedures were the same as described in the above paragraph. After the cells were incubated with FITC-labeled SN, the cells were washed twice with PBS and harvested by trypsinization. Cells were centrifuged at 1500 rpm for 5 min, and cell pellets were re-suspended in ice-cold PBS and centrifuged twice. The cellular uptake efficiency of the SNs was quantitatively determined by fluorescence-activated cell sorting (FACS, Olympus, Japan) or were lysed with 0.2% (w/v) Triton X-100 and quantified by fluorescence spectrophotometry (Shimadzu RF-5301 PC, Japan),²² The fluorescence intensity measured by the fluorescence spectrophotometer was converted to the weight of silica uptake by the cells. Uptake efficiency was expressed as the percentage of fluorescence associated with cells versus the amount of fluorescence present in the cell culture medium.

2.5 Mineralization assays

Mineralization assays were evaluated by alizarin red staining. MC3T3-E1 cells were seeded at 1 × 10⁵ cells per well in 6-well plates and cultured for 24 hours. Growth medium was modified with the addition of 1 × 10⁻⁸ M of dexamethasone (Sigma), 10 mM of β-glycerophosphate (Sigma) and 0.15 mM of ascorbic acid (Sigma).²³ Subsequently, 20 μg ml⁻¹ of each SN was added into the corresponding well. After 14 days post-culture, all media were removed, and cells were fixed in 95% ethanol at 4 °C for 10 min, stained with 1% alizarin red (Sigma) for 30 min, then washed with distilled water five times and viewed under a light microscope. To quantify the mineralized nodules, stained cells were released from the plates with 10% cetylpyridinium chloride (Sigma) in 10 mM sodium phosphate (pH 7.0) for 30 min. Concentration of alizarin red was determined by measuring the absorbance at 562 nm using a spectrometer (RT-6000, Lei Du Life Science and Technology Co, Shenzhen, China).²⁴

2.6 Cell proliferation analysis

The MTT assay (Sigma) was used to evaluate the cell proliferation effects of different sizes of SNs on MC3T3-E1 cells. Briefly, 5 × 10³ MC3T3-E1 cells per well in a 96-well plate were cultured for 24 hours, then different sizes of SNs were added to the corresponding well. After 24 h, 20 μl of MTT reagent was added to each well and incubated for about 4 h at 37 °C until a purple precipitate was visible, 150 μl of dimethyl sulfoxide was then added to each well to dissolve formazan crystals. Optical density at 570 nm was detected by a microplate reader (Lei Du Life Science and Technology Co).

2.7 Cell apoptosis assays

To evaluate if the SNs created in this study induce MC3T3-E1 cell apoptosis, Annexin V-FITC/PI double staining assay kit (KeyGen, Nanjing, China) was used. MC3T3-E1 cells were seeded at 2 × 10⁵ cells per well in six-well plates and cultured for 24 h. Then, 20 μg ml⁻¹ of FITC-labeled SNs was added into each well and cultured for 24 h. Cells in each well were washed twice with PBS and harvested by trypsinization. After centrifugation, cell pellets were washed with ice-cold PBS and re-suspended in binding buffer and stained using Annexin V-FITC/PI apoptosis assay kit according to the manufacturer's instructions. Finally, the collected cells were detected by FACS within 15 min.

2.8 Statistical analysis

All the experiments were repeated three times. Data was presented as mean ± standard deviation (SD). A one-way ANOVA was used to test for statistical differences. Post-hoc comparisons were made using the Tukey–Kramer multiple comparisons test. Differences were statistically considered significant at P < 0.05.

3. Results

3.1 Characteristics of SNs

In our study, three sizes of SNs were fabricated by controlling the ratio of reactants and reaction time as described in the aforementioned procedure in the Experimental section. Hydrodynamic diameters of three SNs in aqueous solution were 121.8 ± 8.4 nm (SN121) (Fig. 1A and Table 2), 310.8 ± 7.5 nm (SN310) (Fig. 1D and Table 2) and 646.1 ± 3.3 nm (SN646) (Fig. 1G and Table 2), which was determined by DLS analysis. Images observed by SEM demonstrated that all three sizes of SNs were spherical with a smooth surface and there was good dispersion and a uniform size (Fig. 1A, D and G). The zeta potential of SN was negative at pH 7.0, which is consistent with the isoelectric point (IEP). Since the IEP of SNs is only about 3, the Si–OH on their surfaces can easily ionize into Si–O⁻ at pH 7.0, and therefore SNs possesses a negative zeta potential, which is well consistent with some previous reports.^25–27 Differences of zeta potential among SN121, SN310 and SN646 (P < 0.01) indicates that the absolute value of zeta potential increased with an increase of SN radius (Table 2).

Fig. 1 Images of SNs with or without FITC label from scanning electron microscopy and bar graph of size of SNs. A. D and G are the images of SNs without FITC label. B, E and H are bar graphs. C, F and I are the images of SNs with FITC label. A–C correspond to SN121. D–F correspond to SN310. G–I correspond to SN646. Bar graph data were obtained from >200 nanoparticles.

Table 2 Measurements of nanoparticle size and zeta-potential by dynamic light scattering

	Size (nm)	Zeta potential (mV)
a SN121, 121 nm silica nanoparticle.b SN310, 310 nm silica nanoparticle.c SN646, 646 nm silica nanoparticle.
SN121^a	121.8 ± 8.4	−34.9 ± 2.6
SN310^b	310.8 ± 7.5	−39.8 ± 0.5
SN646^c	646.1 ± 3.3	−47.6 ± 0.8

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To evaluate the effects of SNs on MC3T3-E1 cells, we used FITC to label SNs. The size of SN labeled with FITC could also be modulated by controlling the ratio of reactants and reaction time. No obvious changes in nanoparticle size, shape and dispersion could be observed by SEM after labeling with FITC (Fig. 1C, F and I).

3.2 Evaluation of cellular uptake

Table 2 demonstrates that the surface of all three SNs obtained in this study were negatively charged, which could discourage the interaction with the negatively charged cell membrane, resulting in difficulty in the internalization of SNs. To evaluate the effects of internalization of SNs, SNs were labeled with FITC to monitor the efficiency of SNs to cross the cell membrane into the cell. Fig. 2A–C shows that all three SNs could efficiently enter into the MC3T3-E1 cells. There was no difference among SNs by direct observation. FITC signals were mainly located near the nucleus.

Fig. 2 Results of cellular uptake by confocal microscope and fluorescence-activated cell sorting (FACS). A and B correspond to SN121, C and D correspond to SN310, E and F correspond to SN646. Cell nuclei are stained by DAPI. SNs were labeled with FITC. These experiments were repeated three times.

To quantify FITC positive cells, MC3T3-E1 cells were incubated with 20 μg ml⁻¹ of each FITC labeled SN for 24 h as described in the experimental section, then FACS was used to count the FITC positive cells. Fig. 2D–F show that the FITC positive cells were 92.2% for SN121, 94.8% for SN310, and 94.3% for SN646 with no difference among groups (P > 0.05). This suggested that all three SNs could efficiently enter into the MC3T3-E1 cells after 24 h post-incubation.

To further quantitatively compare the difference of uptake efficiency between the SNs, fluorescence spectrophotometry was used to measure the photoluminescence (PL) intensity of MC3T3-E1 cells incubated with the FITC-labeled SNs at different time points. The data in Fig. 3 clearly shows that the percentage of uptake efficiency of SN121, the smallest SN in this study, was highest at all the time points tested for all three SNs. The rank order of uptake efficiency was: SN121 > SN310 > SN646. These results indicate that the internalization process was size-dependent. At 24 h time point, the percentage of uptake was 77.1% for SN121, 55.4% for SN310 and 39.3% for SN646 with a significant difference among groups (P < 0.01). In addition, the uptake amount of SN121 at 1 h was almost the same as that of SN646 at 24 h, which suggested that smaller SN quickly internalized (Fig. 3). These results indicated that nanoparticle size could affect the cellular uptake efficiency.

Fig. 3 Cellular uptake efficiency by fluorescence spectrophotometry. (A) Photoluminescence (PL) spectra of FITC-labeled SN121 at different time points. (B) PL spectra of FITC-labeled SN310 at different time points. (C) PL spectra of FITC-labeled SN646 at different time points. D. Percent of control for SN cellular uptake efficiency. Data are represented as means ± SD from three experiments.

3.3 Effects of cell proliferation and apoptosis

To evaluate if SNs created in this study cause any cytotoxicity, MTT and apoptosis assays were performed. Fig. 4 shows the proliferation of MC3T3-E1 cells cultured with different-sized silica that were evaluated by MTT assays. MC3T3-E1 cells were incubated with a series of concentrations of three sizes of SNs for 24 h. The data in Fig. 4 shows that the proliferation of MC3T3-E1 cells significantly decreased at 100 μg ml⁻¹, which suggests that the toxicity was dose-dependent. At lower doses (10, 20 and 50 μg ml⁻¹), no obvious cytotoxicity was observed (Fig. 4).

Fig. 4 Results of MTT assays evaluating different SNs effect on MC3T3-E1 cellular proliferation at varying doses. Data are represented as means ± SD from three experiments.

Flow cytometry was selected to evaluate apoptosis for the further analysis of cytotoxicity at a concentration of 20 μg ml⁻¹, 50 μg ml⁻¹ and 100 μg ml⁻¹. After 24 h incubation, the results shown in Fig. 5 indicated that all three different-sized SNs could induce apoptosis to a certain degree. The percentage of apoptosis was larger with the increasing concentration, and particles with smaller size were easier to induce apoptosis, as shown in Fig. 5. These results confirmed that the cytotoxicity of SNs was size and dose-dependent.

Fig. 5 Results of MC3T3-E1 cell apoptosis assays evaluating the SN induced cellular apoptosis. (A) FACS data of MC3T3-E1 cell control. (B) Summary of FACS data of MC3T3-E1 cell control by bar graph. (C) FACS data of MC3T3-E1 cell with 20 μg ml⁻¹ of SN121. (D) FACS data of MC3T3-E1 cell with 20 μg ml⁻¹ of SN310. (E) FACS data of MC3T3-E1 cell with 20 μg ml⁻¹ of SN646. (F) Summary of FACS data of MC3T3-E1 cell with three different sizes of 20 μg ml⁻¹ SNs by bar graph. (G) FACS data of MC3T3-E1 cell with 50 μg ml⁻¹ of SN121. (H) FACS data of MC3T3-E1 cell with 50 μg ml⁻¹ of SN310. (I) FACS data of MC3T3-E1 cell with 50 μg ml⁻¹ of SN646. (J) Summary of FACS data of MC3T3-E1 cell with three different sizes of 50 μg ml⁻¹ SNs by bar graph. (K) FACS data of MC3T3-E1 cell with 100 μg ml⁻¹ of SN121. (L) FACS data of MC3T3-E1 cell with 100 μg ml⁻¹ of SN310. (M) FACS data of MC3T3-E1 cell with 100 μg ml⁻¹ of SN646. (N) Summary of FACS data of MC3T3-E1 cell with three different sizes of 100 μg ml⁻¹ SNs by bar graph. Data are represented as mean ± SD from three experiments. *: P < 0.05, **: P < 0.01.

3.4 Effects of mineralization

In this study, we tried to evaluate the effects of SNs on osteoblasts and decide if these SNs can be used to stimulate bone regeneration. We investigated whether the SNs obtained in this study could directly affect osteoblast differentiation. The osteoblast precursor cells, MC3T3-E1 cells, were cultured with SNs in an osteogenic medium. After 14 days, the cells were stained with Alizarin Red-S for calcium deposition. Positive nodules were observed from the control group and three SN groups (Fig. 6). Compared to the control group (Fig. 6A), the positive calcium deposition nodules from all three SN groups were significantly higher (Fig. 6B; P < 0.01). These results suggested that all three SNs could directly promote osteoblast differentiation and mineralization.

Fig. 6 SNs effects on mineralization of MC3T3-E1 cells. (A) Alizarin Red staining for MC3T3-E1 cells without SN (control), MC3T3-E1 cells with 20 μg ml⁻¹ of SN464, MC3T3-E1 cells with 20 μg ml⁻¹ of SN310 and MC3T3-E1 cells with 20 μg ml⁻¹ of SN121. (B) Quantitative data of alizarin red staining by spectrophotometry at 562 nm. Data are represented as means ± SD from three experiments. Each SN group is significantly different from the control group (**: P < 0.01).

4. Discussion

It is well known that silica has a higher biocompatibility and potential for affecting bone remodeling. Differences between silica nanoparticles with respect to shape, size, charge and surface chemistry can result in different biological effects.^28–30 In our present study, three different sizes of silica nanoparticles were obtained. The silica nanoparticles displayed good cell affinity, and varying effects in the osteoblast cell line, MC3T3-E1. These findings lead us to further evaluate their potential application value in the new bone formation.

Cellular uptake is a very complicated process, which can be affected by factors including particle size, composition, surface charge, and cell type.^31–33 Nanoparticles are mainly internalized by pinocytosis, which includes three types: (1) clathrin mediated endocytosis with a diameter <200 nm; (2) caveolae-mediated internalization appears as the size of nanoparticles increased to 500 nm; (3) macropinocytosis is possible for virtually any cell with only a few exceptions, such as macrophages and brain microvessel endothelial cells.³³ We evaluated the cellular uptake efficiency of SN121, SN310 and SN646. Although all three synthesized SNs in the current study are negatively charged, their cellular uptakes are not different as determined by the fluorescence-activated cell sorting (Fig. 2, Table 2). This indicates that the negative charge does not affect cellular affinity of these SNs. The cellular uptake, however, is different with further photoluminescence intensity measurements (Fig. 3). The smallest SNs, SN121, have the highest cellular uptake among all three SNs (Fig. 3). Herein, the FACS counts the FITC labeled MC3T3-E1 cells. The photoluminescence intensity, however, can be used to calculate uptake efficiency (percentage of intracellular silica). Previous studies found that the cellular uptake of PEGylated gold nanoshells on silica nanorattles (pGSNs) was highly size-dependent. The rank order was given as follows: pGSNs-84 (84 nm) > pGSNs-142 (142 nm) > pGSNs-315 (315 nm).³⁴ Another study demonstrated that the maximum uptake by cells occurred at 37 nm particle size.³⁵

Cellular uptake can be maximized when there are no unwanted effects from the synthesized nanoparticles. Cytotoxicity is one of the unwanted effects, which needs to be limited to as low level as possible. Previous studies demonstrated that SNs may affect cellular processes such as DNA replication, cell division, and intracellular signal transduction pathways.³⁶ Data from MTT assays indicate that as-synthesized SNs can inhibit MC3T3-E1 cell proliferation at relatively low percentages (Fig. 4). More importantly, these SNs can clearly cause MC3T3-E1 cell apoptosis, and the effects are size- and dose-dependent (Fig. 5). The smallest SNs, SN121, at a higher dose increase apoptosis among the three SNs (Fig. 5). Data from these two assays provide us with useful findings for further modification and application.

We have chosen silica as an optimum material to efficiently regenerate new bone because it has higher biocompatibility and potential effects for new bone formation. As shown in Fig. 4 and 5, apoptosis rate of MC3T3-E1 cells decreases with increasing the nanoparticle size and decreasing the dose (such as 20 μg ml⁻¹ treated group). Therefore, the dose at 20 μg ml⁻¹ was used to further evaluate mineralization. The data shows that all SN groups significantly stimulate osteoblast differentiation, especially SN121 treated group (Fig. 6). It is known that changes in the physicochemical properties of particles may cause distinction.^7–10,37 Previous studies showed that 50 nm silica nanoparticles had stronger effects in MC3T3-E1 cell differentiation.¹⁷ Differently charged mesoporous SNs, however, do not affect the osteogenic differentiation.⁹ Our data also indicates that the smallest SN has the strongest stimulation activity for osteoblast differentiation.

Conclusions

In summary, we have demonstrated that three different sizes of SNs can be efficiently internalized into MC3T3-E1 cells with different cellular uptake and cytotoxicity. Results suggest that smaller SNs have greater cellular uptake with greater levels of cytotoxicity. All three SNs directly stimulated osteoblast differentiation in a size-dependent manner. The smallest SN displayed the strongest stimulation of osteoblast differentiation. Our current study suggests that silica nanoparticles indeed have potential applications in new bone formation. In future studies, we will further optimize our current SNs and investigate the optimal combination between the dose and size of SN in order to achieve optimal bone formation ability.

Acknowledgements

This study was supported by grants from the National Natural Science Foundation of China (81320108011, 81271111, 30830108), the Science Technology Program of Jilin Province (2011I051, 200705350, 201201064) and the Graduate Innovation Fund of Jilin University (2014068, 20121128).

Notes and references

1. Y. Liu, K. Ai, J. Liu, M. Deng, Y. He and L. Lu, Adv. Mater., 2013, 25, 1353–1359.
2. M. De, P. S. Ghosh and V. M. Rotello, Adv. Mater., 2008, 20, 4225–4241.
3. L. A. Bauer, N. S. Birenbaum and G. J. Meyer, J. Mater. Chem., 2004, 14, 517.
4. Y. Guo, D. Shi, H. Cho, Z. Dong, A. Kulkarni, G. M. Pauletti, W. Wang, J. Lian, W. Liu, L. Ren, Q. Zhang, G. Liu, C. Huth, L. Wang and R. C. Ewing, Adv. Funct. Mater., 2008, 18, 2489–2497.
5. H. Jaganathan and B. Godin, Adv. Drug Delivery Rev., 2012, 64, 1800–1819.
6. V. Mohanraj and Y. Chen, Trop. J. Pharm. Res., 2006, 5, 561–573.
7. W. Jiang, B. Y. Kim, J. T. Rutka and W. C. Chan, Nat. Nanotechnol., 2008, 3, 145–150.
8. X. Huang, X. Teng, D. Chen, F. Tang and J. He, Biomaterials, 2010, 31, 438–448.
9. T. H. Chung, S. H. Wu, M. Yao, C. W. Lu, Y. S. Lin, Y. Hung, C. Y. Mou, Y. C. Chen and D. M. Huang, Biomaterials, 2007, 28, 2959–2966.
10. B. Mehravi, M. Ahmadi, M. Amanlou, A. Mostaar, M. S. Ardestani and N. Ghalandarlaki, Int. J. Nanomed., 2013, 8, 3209.
11. I. Brigger, C. Dubernet and P. Couvreur, Adv. Drug Delivery Rev., 2012, 64, 24–36.
12. J. H. Park, G. von Maltzahn, M. J. Xu, V. Fogal, V. R. Kotamraju, E. Ruoslahti, S. N. Bhatia and M. J. Sailor, Proc. Natl. Acad. Sci. U. S. A., 2010, 107, 981–986.
13. Y. Liu, H. Miyoshi and M. Nakamura, Int. J. Cancer, 2007, 120, 2527–2537.
14. M. V. Yezhelyev, X. Gao, Y. Xing, A. Al-Hajj, S. Nie and R. M. O'Regan, Lancet Oncol., 2006, 7, 657–667.
15. G. Zhang, G. M. Palmer, M. W. Dewhirst and C. L. Fraser, Nat. Mater., 2009, 8, 747–751.
16. K. I. Nakahama, Cell. Mol. Life Sci., 2010, 67, 4001–4009.
17. G. R. Beck Jr, S. W. Ha, C. E. Camalier, M. Yamaguchi, Y. Li, J. K. Lee and M. N. Weitzmann, Nanomedicine, 2012, 8, 793–803.
18. H. Nie, M. L. Ho, C. K. Wang, C. H. Wang and Y. C. Fu, Biomaterials, 2009, 30, 892–901.
19. Z. Mao, L. Wan, L. Hu, L. Ma and C. Gao, Colloids Surf., B, 2010, 75, 432–440.
20. Y. W. Yoo and W. K. Lee, Surf. Coat. Technol., 2012, 213, 291–298.
21. W. Stöber, A. Fink and E. Bohn, J. Colloid Interface Sci., 1968, 26, 62–69.
22. D. Zhou, M. Lin, Z. L. Chen, H. Z. Sun, H. Zhang, H. Sun and B. Yang, Chem. Mater., 2011, 23, 4857–4862.
23. Y. Zhao, B. Zou, Z. Shi, Q. Wu and G. Q. Chen, Biomaterials, 2007, 28, 3063–3073.
24. C. M. Stanford, P. A. Jacobson, E. D. Eanes, L. A. Lembke and R. J. Midura, J. Biol. Chem., 1995, 270, 9420–9428.
25. E. Mahon, D. R. Hristov and K. A. Dawson, Chem. Commun., 2012, 48, 7970–7972.
26. S. V. Patwardhan, F. S. Emami, R. J. Berry, S. E. Jones, R. R. Naik, O. Deschaume, H. Heinz and C. C. Perry, J. Am. Chem. Soc., 2012, 134, 6244–6256.
27. C. O. Metin, L. W. Lake, C. R. Miranda and Q. P. Nguyen, J. Nanopart. Res., 2010, 13, 839–850.
28. Z. Shi, X. Huang, Y. Cai, R. Tang and D. Yang, Acta Biomater., 2009, 5, 338–345.
29. S. W. Kim, K. T. Oh, Y. S. Youn and E. S. Lee, Colloids Surf., B, 2014, 116, 359–364.
30. Y. Cai, Y. Liu, W. Yan, Q. Hu, J. Tao, M. Zhang, Z. Shi and R. Tang, J. Mater. Chem., 2007, 17, 3780.
31. B. D. Chithrani, A. A. Ghazani and W. C. Chan, Nano Lett., 2006, 6, 662–668.
32. C. He, Y. Hu, L. Yin, C. Tang and C. Yin, Biomaterials, 2010, 31, 3657–3666.
33. J. Rejman, V. Oberle, I. S. Zuhorn and D. Hoekstra, Biochem. J., 2004, 377, 159–169.
34. H. Liu, T. Liu, L. Li, N. Hao, L. Tan, X. Meng, J. Ren, D. Chen and F. Tang, Nanoscale, 2012, 4, 3523–3529.
35. J. Huang, L. Bu, J. Xie, K. Chen, Z. Cheng, X. Li and X. Chen, ACS Nano, 2010, 4, 7151–7160.
36. Z. Y. Wang, Y. Zhao, L. Ren, L. H. Jin, L. P. Sun, P. Yin, Y. F. Zhang and Q. Q. Zhang, Nanotechnology, 2008, 19, 445103.
37. Y. Li, L. Sun, M. Jin, Z. Du, X. Liu, C. Guo, Y. Li, P. Huang and Z. Sun, Toxicol. In Vitro, 2011, 25, 1343–1352.

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Footnote

† Electronic supplementary information (ESI) available. See DOI: 10.1039/c4ra06863g

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