Cells from the mesenchymal lineage in the dental area, including but not limited to PDL fibroblasts, osteoblasts, and dental stem cells, are exposed to mechanical stress in physiological (e.g., chewing) and nonphysiological/therapeutic (e.g., orthodontic tooth movement) situations. Close and complex interaction of these different cell types results in the physiological and nonphysiological adaptation of these tissues to mechanical stress. Currently, different
The aim of orthodontics is to move an abnormally positioned tooth through the application of a continuous force on its surface. This force stimulates bone remodelling in the surrounding tissue, namely, the periodontal ligament (PDL) and the alveolar bone, resulting in the bone removal in the direction of the tooth movement and bone apposition in the opposite direction (Figure
Bone remodelling during orthodontic tooth movement. (a) Initial displacement of the tooth due to stretching of the fibres within the PDL on the tension side and compression on the opposite with the application of the orthodontic force. (b) Bone apposition on the tension side and resorption on the compression side as the result of the long-term force application.
Histologically, the effects of orthodontic force on the tooth and its surrounding tissues are now well understood and the underlying stages in OTM are identified [
In order to better understand morphological changes during OTM, it is important to elucidate molecular and cellular signaling mechanisms between and within these cell types. The complex
On the basis of the most commonly used approaches to apply mechanical stress on cells, present
Weight-based
Schematic illustration of the static 2D (a) and 3D (b)
The primary aim of this review was to identify all articles related to the field of orthodontics using either a 2D or 3D WAB
To conduct this review, the “Preferred Reporting Items for Systematic Review and Meta-Analysis Protocols” (PRISMA-P) 2015 statement was consulted [
Inclusion criteria were as follows:
Studies in the field of dentistry that examined the effect of mechanical stress on tooth surrounding tissues Application of the 2D or 3D WAB …on hPDLCs, hOBs, or all bone-like cell types/lines of human or animal origin Only studies written in English language, identified on the PubMed database until 01.12.2017, were taken into consideration
Separate search strategies were created for studies using either the 2D or the 3D
After identification of relevant studies in the PubMed database, the downloaded records from each search were imported into the bibliographic software EndNote X8 (Clarivate Analytics, Philadelphia, Pennsylvania, USA). All records were examined by two reviewers independently (MJ and UB), according to predefined inclusion and exclusion criteria (see above): first by title, then by abstract. If the abstract was not available, the full text of the report was obtained. Records that were obviously irrelevant were excluded, and the full texts of all remaining records were acquired. After the full-text assessment, the final list of included articles was generated. Any disagreements during this process were dissolved through discussion with another review author (DD) until reaching a consensus. The articles that did not meet all inclusion criteria after full-text assessment were excluded from further examination. Additional relevant studies were further identified through forward and backward reference chaining and hand-search of specific journals. Study quality assessment of the included studies was not performed, since the goal of this article was to provide an overview of all findings in the field only.
The following information was extracted from each study obtained in full length: author, journal, year of publication, and used cell type. Force magnitude and duration, examined genes or substances, gene expression, or substance secretion details were recorded only if their response was directly connected to mechanical force stimulus. Gene symbols were used in the tables whenever possible. In case the identity or variant of a gene was doubtful or not clear primer sequences were examined using Primer-BLAST (URL:
The following tables were prepared to summarize the findings: (1) studies applying the 2D WAB
The examined genes and metabolites using the 2D approach were summarized in two separate lists: one for hPDLFs and one for hOBs and other human bone-derived cell lines. Protein-protein interaction (PPI) networks were generated for both lists separately using the STRING database (10.5, URL:
Figure
PRISMA flow diagram of the review process.
The search formula applied to identify 2D WAB
Additionally, 7 articles were identified through forward and backward reference chaining and hand-search of specific journals. After reading the titles and abstracts of all identified studies, we excluded 2184. The remaining 107 articles were then checked by full-text reading. Fifty-six of them meet our inclusion criteria and were included for further analysis. The remaining did not meet the inclusion criteria. Reasons for their exclusion are listed in Supplement
The search formula applied to identify 3D WAB
All studies fulfilling the inclusion criteria were organised into three different supplementary tables: Supplement
In these studies, compression forces ranging from 0.25 g/cm2 to 5 g/cm2 were applied on cells in 2D culture. The most commonly used compressive force was 2 g/cm2, irrespectively which cell type was used in the study. In most of the studies, the force was applied for 24 h (Supplements
Force duration and magnitude depended on the scaffold used (Supplement
Forty of these studies used human primary cells isolated from the tooth surrounding tissues (Supplement
hPDLCs and human gingival fibroblasts were used in 13 studies (Supplement
Taken together, the most commonly used cells were hPDLCs. They were used in total 51 studies (2D: 38; 3D: 13) (Supplements
A complete overview of genes and metabolites examined in 2D and 3D WAB studies and details of their expression can be found in Supplements
In this review, special attention was paid to hPDLCs as the most examined cell type among studies and their prominent role in OTM. The most examined genes and metabolites in relation to hPDLCs were TNF superfamily member 11 (TNFSF11), TNF receptor superfamily member 11B (TNFRSF11B), prostaglandin-endoperoxide synthase 2 (PTGS2), and prostaglandin E2 (PGE2). In Table
Top four examined genes or substances in studies applying 2D or 3D
Gene symbol or metabolite | Cell culture | Reference | Examined force applied | Gene expression | Substance secretion | |||||
---|---|---|---|---|---|---|---|---|---|---|
Duration (h) | Magnitude (g/cm2) | Increase/decrease/no change | Change in relation to force duration (h) | Change in relation to force magnitude (g/cm2) | Increase/decrease/no change | Change in relation to force duration (h) | Change in relation to force magnitude (g/cm2) | |||
PGE2 | 2D | Benjakul et al. in press [ |
48 | 1.5 | na | Increase (qPCR: GAPDH) | 48 | 1.5 | ||
Jin et al. 2015 [ |
0; 0.5; 3; 6; 12 | 2.0 | na | Increase (ELISA) | 12 | 2.0 | ||||
Kang et al. 2010 [ |
0.5; 2; 6; 24; 48 | 2.0 | na | Increase (ELISA) | 48 | 2.0 | ||||
Kanzaki et al. 2002 [ |
0.5; 1.5; 6; 24; 48 (+ELISA: 60) | 0.5; 1.0; 2.0; 3.0; 4.0 (ELISA: 2.0) | na | Increase (ELISA) | 60 | 2.0 | ||||
Kirschneck et al. 2015 [ |
24 | 2.0 | na | Not explicitly stated (ELISA) | ||||||
Liu et al. 2006 [ |
48 | 2.0 | na | Increase (ELISA) | 48 | 2.0 | ||||
Mayahara et al. 2007 [ |
3; 6; 12; 24; 48 | 2 | na | Increase (ELISA) | 48 | 2 | ||||
Premaraj et al. 2013 [ |
0.5; 1; 3; 6 | 5.0 | na | Increase (ELISA) | 1 | 5.0 | ||||
Proff et al. 2014 [ |
24 | 2 | na | Increase (ELISA) | 24 | 2 | ||||
Römer et al. 2013 [ |
24 | 2 | na | Increase (ELISA) | 24 | 2 | ||||
3D (Coll. gel) | de Araujo et al. 2007 [ |
3; 12; 24; 48; 72 | 6.0 | Increase (EIA) | 72 | 6.0 | ||||
3D (PLGA) | Li et al. 2016 [ |
6; 24; 72 | 5.0; 15.0; 25.0 | na | Increase (ELISA) | 24 | 15.0…25.0 | |||
Yi et al. 2016 [ |
24 | 25.0 | Increase (ELISA) | 24 | 25.0 | |||||
2D | Jin et al. 2015 [ |
0; 0.5; 3; 6; 12 | 2.0 | Increase (qPCR: GAPDH) | 12 | 2.0 | ||||
Kang et al. 2010 [ |
0.5; 2; 6; 24; 48 | 2.0 | Increase (qPCR: GAPDH) | 48 | ||||||
Kanzaki et al. 2002 [ |
0.5; 1.5; 6; 24; 48 | 0.5; 1.0; 2.0; 3.0; 4.0 | Increase (sqPCR: ACTNB) | 6 | 2.0 | |||||
Kirschneck et al. 2015 [ |
24 | 2.0 | Increase (qPCR: POL2RA) | 24 | 2.0 | |||||
Liu et al. 2006 [ |
48 | 2.0 | Increase (sqPCR: ACTNB) | 48 | 2.0 | |||||
Mayahara et al. 2007 [ |
3; 6; 12; 24; 48 | 2 | Increase (qPCR: GAPDH) | 48 | 2 | |||||
Mayahara et al. 2010 [ |
3; 6; 12; 24; 48 | 2.0 | Increase (qPCR: GAPDH) | 48 | 2 | |||||
Premaraj et al. 2013 [ |
6 | 0.2; 2.2; 5.0 | nd | Increase (WB) | 6 | 5.0 | ||||
Proff et al. 2014 [ |
24 | 2 | Increase (qPCR: POL2RA) | 24 | 2 | Increase (WB) | 24 | 2 | ||
Römer et al. 2013 [ |
24 | 2 | Increase (qPCR: POL2RA) | 24 | 2 | |||||
Wongkhantee et al. 2007 [ |
24 | 0; 1.25; 2.5 | Increase (sqPCR: GAPDH) | 24 | 2.5 | |||||
3D (Coll. gel) | de Araujo et al. 2007 [ |
1; 3; 6; 12; 24; 48; 72 | 3.6; 6.0; 7.1; 9.5 | Increase (sqPCR: GAPDH) | 6 | 7.1 | ||||
3D (PLGA) | Li et al. 2016 [ |
6; 24; 72 | 25.0 | Increase (qPCR: GAPDH) | 6 | 25.0 | ||||
Li et al. 2013 [ |
6; 24; 72 | 25.0 | Increase (qPCR: GAPDH) | 6 | 25.0 | |||||
Li et al. 2016 [ |
6; 24; 72 | 5.0; 15.0; 25.0 | Increase (qPCR: GAPDH) | 6 | 25.0 | |||||
Li et al. 2011 [ |
6 | 5; 15; 25; 35 | Increase (qPCR: GAPDH) | 6 | 35.0 | |||||
Yi et al. 2016 [ |
24 | 25.0 | Increase (qPCR: GAPDH) | 24 | 25.0 | Increase (WB) | 24 | 25.0 | ||
2D | Benjakul et al. in press [ |
48 | 1.5 | No change (qPCR: GAPDH) | No change | |||||
Jin et al. 2015 [ |
0; 0.5; 3; 6; 12 | 2.0 | No change (qPCR: GAPDH) | |||||||
Kanzaki et al. 2002 [ |
0.5; 1.5; 6; 24; 48 | 0.5; 1.0; 2.0; 3.0; 4.0 | No change (sqPCR: ACTNB) | |||||||
Kim et al. 2013 [ |
0.5; 2; 6; 24; 48 | 2.0 | Transitory downregulated. (qPCR: GAPDH) | 6 | 2.0 | Transitory downregulation (ELISA) | 6 | 2.0 | ||
Kirschneck et al. 2015 [ |
24 | 2.0 | No change (qPCR: POL2RA) | |||||||
Lee et al. 2015 [ |
0; 2; 4; 8; 24; 48 | 2.5 | No change (qPCR: ACTNB) | |||||||
Liu et al. 2017 [ |
6; 12; 24 | 0.5; 1.0; 1.5 | nd | Decrease (WB) | n. g. | 1.5 | ||||
Luckprom et al. 2011 [ |
2; 4 | 2.5 | No change (sqPCR: GAPDH) | |||||||
Mitsuhashi et al. 2011 [ |
1; 3; 6; 9; 12; 24 | 4.0 | No change (qPCR: ACTNB) | |||||||
Nakajima et al. 2008 [ |
0; 1; 3; 6; 9; 12; 24 | 0.5; 1.0; 2.0; 3.0; 4.0 | nd | Increase (ELISA) | 24 | 0.5 | ||||
Nishijima et al. 2006 [ |
48 | 0; 0.5; 1.0; 2.0; 3.0 | nd | Decrease (ELISA) | 48 | 2.0 | ||||
Römer et al. 2013 [ |
24 | 2 | No change (qPCR: RNA-polymerase-2-polypeptide A) | |||||||
Yamada et al. 2013 [ |
12 | 4.0 | Decrease (qPCR: GAPDH) | 12 | 4.0 | Decrease (ELISA) | 12 | 4.0 | ||
Yamaguchi et al. 2006 [ |
0; 3; 6; 9; 12; 24; 48 | 0.5; 1.0; 2.0; 3.0 | n. d. | Decrease (ELISA) | 12…48 | 2.0 | ||||
3D (Coll. gel) | Kaku et al. 2016 [ |
12; 24 | 0.5; 1.0; 2.0 | Increase (qPCR: GAPDH) | 12 | 1.0 | ||||
3D (PLLA modif.) | Liao et al. 2016 [ |
1 d; 3 d; 7 d; 14 d | 5.0; 15.0; 25.0; 35.0 | No change (qPCR: GAPDH) | ||||||
3D (PLGA) | Jianru et al. 2015 [ |
3; 6; 12 (WB: 12) | 25.0 | Decrease followed by increase (qPCR: GAPDH) | 3 (decrease) |
25.0 | Increase (WB) | 12 | 25.0 | |
Li et al. 2016 [ |
6; 24; 72 | 25.0 | Decrease followed by Increase (qPCR: GAPDH) | 6 (decrease) |
25.0 | |||||
Li et al. 2016 [ |
6; 24; 72 | 5.0; 15.0; 25.0 | Decrease followed by increase (qPCR: GAPDH) | 6 (decrease) |
15.0 (decrease) |
Decrease followed by Increase (qPCR: GAPDH) | 6 (decrease) |
25.0 (decrease) | ||
Li et al. 2011 [ |
6; 24; 72 | 25 | Decrease followed by increase (qPCR: GAPDH) | 6 (decrease) |
25.0 | |||||
Yi et al. 2016 [ |
24 | 25.0 | Decrease (qPCR: GAPDH) | 24 | 25.0 | No change (WB) | ||||
2D | Benjakul et al. in press [ |
48 | 1.5 | Increase (qPCR: GAPDH) | 48 | 1.5 | Increase (qPCR: GAPDH) | 48 | 1.5 | |
Jin et al. 2015 [ |
0; 0.5; 3; 6; 12 | 2.0 | Increase (qPCR: GAPDH) | 12 | 2.0 | |||||
Kang et al. 2013 [ |
2; 48 | 2.0 | Increase (qPCR: GAPDH) | 48 | 2.0 | |||||
Kanzaki et al. 2002 [ |
0.5; 1.5; 6; 24; 48 | 0.5; 1.0; 2.0; 3.0; 4.0 | Increase (sqPCR: ACTNB) | 48 | 2.0 | Increase (WB): 40-kDa+ 55-kDa | 48 | 2.0 | ||
Kikuta et al. 2015 [ |
1; 3; 6; 9; 12; 24 (+ELISA: 48) | 4.0 | Increase (qPCR: GAPDH) | 12 | 4.0 | Increase (ELISA) | 24 | 4.0 | ||
Kim et al. 2013 [ |
0.5; 2; 6; 24; 48 | 2.0 ++ | Increase (qPCR: GAPDH) | 24 | 2.0 | Increase (ELISA) | 48 | 2.0 | ||
Kirschneck et al. 2015 [ |
24 | 2.0 | Increase (qPCR: POL2RA) | 24 | 2.0 | |||||
Lee et al. 2015 [ |
0; 2; 4; 8; 24; 48 | 2.5 | Increase (qPCR: ACTNB) | 24 | 2.5 | |||||
Liu et al. 2017 [ |
6, 12, 24 | 0.5; 1.0; 1.5 | nd | Increase (WB: GAPDH) | ng | 1.5 | ||||
Liu et al. 2006 [ |
48 | 2.0 | Increase (sqPCR: ACTNB) | 48 | 2.0 | |||||
Luckprom et al. 2011 [ |
2; 4 | 2.5 | Increase (sqPCR: GAPDH) | 2 | 2.5 | Increase (WB) | 4 | 2.5 | ||
Mitsuhashi et al. 2011 [ |
1; 3; 6; 9; 12; 24 | 4.0 | Temporary increase (qPCR: ACTNB) | 6…9 | 4.0 | |||||
Nakajima et al. 2008 [ |
0; 1; 3; 6; 9; 12; 24 | 0.5; 1.0; 2.0; 3.0; 4.0 | nd | Increase (ELISA) | 24 | 4.0 | ||||
Nishijima et al. 2006 [ |
48 | 0; 0.5; 1.0; 2.0; 3.0 | nd | Increase (ELISA) | 12…48 | 2.0 | ||||
Römer et al. 2013 [ |
24 | 2 | Increase (qPCR: RNA-polymerase-2-polypeptide A) | 24 | 2 | |||||
Wongkhantee et al. 2007 [ |
24 | 0; 1.25; 2.5 | Increase (sqPCR: GAPDH) | 24 | 2.5 | Increase (WB; ACTNB) | 24 | 2.5 | ||
Yamada et al. 2013 [ |
12 | 4.0 | Increase (qPCR: GAPDH) | 12 | 4.0 | Increase (ELISA) | 12 | 4.0 | ||
Yamaguchi et al. 2006 [ |
0; 3; 6; 9; 12; 24; 48 | 0.5; 1.0; 2.0; 3.0 | nd | Increase (ELISA): sRANKL |
12…48 |
2.0 | ||||
3D (Coll. gel) | Kang et al. 2013 [ |
2; 48 | 2.0 | Increase (qPCR: GAPDH) | 2 | 2.0 | ||||
3D (PLLA modif.) | Liao et al. 2016 [ |
1 d; 3 d; 7 d; 14 d | 5.0; 15.0; 25.0; 35.0 | Increase (qPCR: GAPDH) | Day 14 | 35.0 | ||||
3D (PLGA) | Jianru et al. 2015 [ |
3; 6; 12 (WB: 12) | 25.0 | Increase (qPCR: GAPDH) | 6 | 25.0 | Increase (WB) | 12 | 25.0 | |
Li et al. 2016 [ |
6; 24; 72 | 25.0 | Increase (qPCR: GAPDH) | 6 | 25.0 | |||||
Li et al. 2016 [ |
6; 24; 72 | 5.0; 15.0; 25.0 | Increase (qPCR: GAPDH) | 6 | 25.0 | Decrease (ELISA) | 72 | 25.0 | ||
Li et al. 2011 [ |
6; 24; 72 | 5; 15; 25; 35 | Increase (qPCR: GAPDH) |
6 |
25…35.0 | |||||
Yi et al. 2016 [ |
24 | 25.0 | Increase (qPCR: GAPDH) | 24 | 25.0 | Increase (WB) | 24 | 25.0 |
2D: two-dimensional cell culture; 3D (Coll. gel): three-dimensional cell culture, collagen gel; 3D (PLGA): three-dimensional cell culture using PLGA scaffolds; 3D (PLLA modif.): three-dimensional cell culture, hydrophilically modified PLLA scaffolds; qPCR: quantitative polymerase chain reaction (e.g., real-time PCR); sqPCR: semiquantitative polymerase chain reaction, followed by reference gene used; nr: not reported; na: not applicable; ELISA: enzyme-linked immune absorbent assay; WB: Western blot; IF: immunofluorescence; FLM: fluorescence microscopy; EIA: enzyme immunoassay.
In order to elucidate the molecular mechanisms of OTM and the role of the hPDLCs and bone cells in this process, we used STRING to construct PPI networks. Two separate gene lists were compiled from those studies using hPDLCs (“hPDLC list”; data from Supplement
Protein-protein interaction networks for the (a) “hPDLC list” and the (b) “hOB list”. The gene lists are shown in the lower left part of each subfigure. Those genes with the highest number of interactions (“top 10”) are given in tables in the lower right part of each subfigure.
Two separate PPI networks were obtained, based on the interactions with a high level of confidence (>0.700) (Figure
According to our STRING analysis, KEGG pathways relevant for OTM for each set of genes are listed in Table
KEGG pathways relevant for OTM with false discovery rates below 1.00
KEGG ID | 4060 | 4668 | 4510 | 4620 | 4370 | 4062 | 4380 | 4010 | 4064 |
---|---|---|---|---|---|---|---|---|---|
KEGG name | Cytokine-cytokine receptor interaction | TNF signaling pathway | Focal adhesion | Toll-like receptor signaling pathway | VEGF signaling pathway | Chemokine signaling pathway | Osteoclast differentiation | MAPK signaling pathway | NF-kappa B signaling pathway |
False discovery rate | 2.62 |
2.06 |
3.90 |
2.04 |
9.47 |
1.33 |
2.29 |
1.42 |
1.86 |
ADRB2 | |||||||||
AKT1 | X | X | X | X | X | X | X | ||
ALPL | |||||||||
BGLAP | |||||||||
CBS | |||||||||
CCL2 | X | X | X | ||||||
CCL3 | X | X | X | ||||||
CCL5 | X | X | X | X | |||||
CCND1 | X | ||||||||
CCR5 | X | X | |||||||
CDH11 | |||||||||
COL1A1 | X | ||||||||
COL3A1 | X | ||||||||
COL5A1 | X | ||||||||
CSF1 | X | X | X | ||||||
CTNNB1 | X | ||||||||
CTSB | |||||||||
CTSL | |||||||||
CXCL8 (= IL8) | X | X | X | X | |||||
FGF2 | X | ||||||||
GJA1 | |||||||||
GSK3b | X | X | |||||||
HMGB1 | |||||||||
HSP90AA1 | |||||||||
HSPA4 | |||||||||
HSPB1 | X | X | |||||||
IGF1 | X | ||||||||
IL17A | X | ||||||||
IL1B | X | X | X | X | X | X | |||
IL6 | X | X | X | ||||||
JAG1 | X | ||||||||
LGALS3BP | |||||||||
MMP13 | |||||||||
MMP3 | X | ||||||||
PIEZO1 | |||||||||
PLA2G4A | X | X | |||||||
POSTN | |||||||||
PTGS1 | |||||||||
PTGS2 | X | X | X | ||||||
PTK2 | X | X | X | ||||||
RUNX2 | |||||||||
SPP1 | X | X | |||||||
TGFB1 | X | X | |||||||
TGFB3 | X | X | X | ||||||
TNF | X | X | X | X | X | X | |||
TNFRSF11B | X | X | |||||||
TNFSF11 | X | X | X | ||||||
VEGFA | X | X | X |
KEGG ID | 4350 | 4060 | 4064 | 4390 | 4668 | 4210 | 4380 | 4620 | 4066 |
---|---|---|---|---|---|---|---|---|---|
KEGG name | TGF-beta signaling pathway | Cytokine-cytokine receptor interaction | NF-kappa B signaling pathway | Hippo signaling pathway | TNF signaling pathway | Apoptosis | Osteoclast differentiation | Toll-like receptor signaling pathway | HIF-1 signaling pathway |
False discovery rate | 8.33 |
2.37 |
8.32 |
5.07 |
1. |
6.26 |
1.02 |
6.79 |
7.16 |
ACVR1 | X | X | |||||||
ACVR2A | X | X | |||||||
ACVR2B | X | X | |||||||
ALPL | |||||||||
BAX | X | ||||||||
BCL2 | X | X | X | ||||||
BGLAP | |||||||||
BMP2 | X | X | X | ||||||
BMP4 | X | X | |||||||
BMP6 | X | X | |||||||
BMP7 | X | X | X | ||||||
BMPR1A | X | X | X | ||||||
BMPR1B | X | X | X | ||||||
BMPR2 | X | X | X | ||||||
Casp3 | X | X | |||||||
CHRD | X | ||||||||
CXCR1 | X | ||||||||
FST | X | ||||||||
GREM1 | |||||||||
IBSP | |||||||||
IL11 | X | ||||||||
IL11RA | |||||||||
IL1b | X | X | X | X | X | X | |||
IL1r1 | X | X | X | X | |||||
IL6 | X | X | X | X | |||||
IL6R | X | X | |||||||
IL8 | X | X | X | X | |||||
MKI67 | |||||||||
MMP1 | |||||||||
MMP13 | |||||||||
MMP14 | |||||||||
MMP2 | |||||||||
MMP3 | |||||||||
NOG | X | ||||||||
PLAT | |||||||||
PLAU | X | ||||||||
PTGS2 | X | ||||||||
RUNX2 | |||||||||
SERPINE1 | X | X | |||||||
SMAD1 | X | X | |||||||
SP7 | |||||||||
SPP1 | X | X | |||||||
TIMP1 | X | ||||||||
TIMP2 | |||||||||
TIMP3 | |||||||||
TIMP4 | |||||||||
TNF | X | X | X | X | X | X | X | ||
TNFRSF11B | X | ||||||||
TNFRSF1A | X | X | X | X | |||||
TNFSF11 | X | X | |||||||
ZNF354C |
In vitro
The advantages of WAB It reduces the need for animal studies, which are costly and time consuming. It enables the analysis of specific cell types independently or in cocultures with other cells of interest. Human primary cells can be used for better approximation to clinical situation.
From our point of view, the main disadvantage is its missing impact of the natural surrounding environment. There has been an increasing interest in the development of the 3D cell culture WAB
During the last years, more studies have been using cells incorporated into biological scaffolds instead of monolayer cultures. This is due to the demand of mimicking an extracellular matrix, which is beneficial for cell behaviour, instead of growing cells on artificial plastic cell culture surface [
According to Schwarz [
In 2D cell culture WAB
In studies applying the 3D WAB
The length of the force application in the studies rarely exceeded 72 h. In most of the cases, force was applied up to 24 and 48 h. Considering the fact that the first 10 days are of crucial importance for OTM ([
Due to lack of PDL, ankylosed teeth and implants cannot undergo OTM, which depict best PDL’s key role in transmitting the mechanical stimulus and initiating the process of bone remodelling [
To explain the contribution of hPDLCs in OTM on the molecular level, we summarised all data regarding the most commonly examined genes and substances in this cell type (Table
Gene expression of
Taken together, there seems to be some inconsistency between studies using the 2D and the 3D WAB
We performed STRING PPI analysis for two selected sets of genes (“hPDLC list” and “hOB list”). PPI enrichment
In addition, KEGG pathways relevant for OTM, identified for each set of genes in STRING analysis (Table
In summary, the WAB
3D WAB
Two-dimensional
Three-dimensional
Adenosine triphosphate
Cyclic adenosine monophosphate
Extracellular matrix
Enzyme-linked immunosorbent assay
Hydrogen sulfide
Human oral bone marrow cells
Human osteoblasts
Human periodontal ligament cells
Kyoto encyclopedia of genes and genomes
Nitric oxide
Optimal orthodontic force
Osteoprotegerin
Orthodontic tooth movement
Periodontal ligament
Prostaglandin E2
Polylactic-co-glycolic acid
Poly-L-lactide acid
Protein-protein interaction
Prostaglandin-endoperoxide synthase 2
Receptor activator of nuclear factor kappa-
Reactive oxygen species
Search tool for the retrieval of interacting genes/proteins
Tumor necrosis factor
TNF receptor superfamily member 11b
TNF superfamily member 11
Weight approach based.
The authors declare that there is no conflict of interest regarding the publication of this manuscript.
Mila Janjic received a study grant from BAYHOST (Bayerisches Hochschulzentrum für Mittel-, Ost- und Südosteuropa, Regensburg, Germany) and from the Fund for Young Talents of the Republic of Serbia (Government of the Republic of Serbia, Ministry of Youth and Sports, Belgrade, Serbia).
Search strategy designed for the studies applying the
Studies applying the 2D weight approach on human primary cells from the orofacial region, that is, human periodontal ligament cells (hPDLC), human oral bone marrow cells (hOBMC), and human alveolar bone osteoblasts (hOB). For each gene or metabolite force magnitude and force duration, the change in gene expression or substance secretion (increase, decrease, and no change) and the techniques applied are given.
Studies applying the 2D weight approach on human and nonhuman cells and cell lines not included in Supplement 2 (i.e., human primary cells from the orofacial region). For each gene or metabolite force magnitude and force duration, the change in gene expression or substance secretion (increase, decrease, and no change) and the techniques applied are given.
Studies applying the 3D weight approach on human and nonhuman cells and cell lines. For each gene or metabolite force magnitude and force duration, the change in gene expression or substance secretion (increase, decrease, and no change) and the techniques applied are given.