Download PDF
Facial Plast Surg 2023; 39(05): 466-473
DOI: 10.1055/a-2113-5023
Original Article

Translational Research Techniques for the Facial Plastic Surgeon: An Overview

William Mason
1   Department of Otolaryngology, Henry Ford Hospital, Detroit, Michigan
,
Albert M. Levin
2   Department of Public Health Science, Henry Ford Health, Detroit, Michigan
3   Center for Bioinformatics, Henry Ford Health, Detroit, Michigan
,
Katherine Buhl
1   Department of Otolaryngology, Henry Ford Hospital, Detroit, Michigan
,
Takahiro Ouchi
1   Department of Otolaryngology, Henry Ford Hospital, Detroit, Michigan
,
Bianca Parker
1   Department of Otolaryngology, Henry Ford Hospital, Detroit, Michigan
,
Jessica Tan
1   Department of Otolaryngology, Henry Ford Hospital, Detroit, Michigan
,
Nureddin Ashammakhi
4   Institute for Quantitative Health Science and Engineering, Michigan State University, Michigan
5   Department of Biomedical Engineering, College of Engineering, Michigan State University, Michigan
6   College of Human Medicine, Michigan State University, Michigan
,
Lamont R. Jones
1   Department of Otolaryngology, Henry Ford Hospital, Detroit, Michigan
› Author Affiliations Funding The authors acknowledge the funding received from the National Institutes of Health (1UG3TR003148-01) (N.A.).
› Further Information
    Permissions and Reprints

Abstract

The field of facial plastic and reconstructive surgery (FPRS) is an incredibly diverse, multispecialty field that seeks innovative and novel solutions for the management of physical defects on the head and neck. To aid in the advancement of medical and surgical treatments for these defects, there has been a recent emphasis on the importance of translational research. With recent technological advancements, there are now a myriad of research techniques that are widely accessible for physician and scientist use in translational research. Such techniques include integrated multiomics, advanced cell culture and microfluidic tissue models, established animal models, and emerging computer models generated using bioinformatics. This study discusses these various research techniques and how they have and can be used for research in the context of various important diseases within the field of FPRS.

Keywords

translational research - multiomics - facial plastic and reconstructive surgery - keloid disease


Publication History

Accepted Manuscript online:
20 June 2023

Article published online:
20 July 2023

© 2023. Thieme. All rights reserved.

Thieme Medical Publishers, Inc.
333 Seventh Avenue, 18th Floor, New York, NY 10001, USA

 

  • References

  • 1 Bhattacharya S. Jacques Joseph: father of modern aesthetic surgery. Indian J Plast Surg 2008; 41 (Suppl): S3-S8
    Article in Thieme ConnectPubMedGoogle Scholar
  • 2 Bersanelli M, Mosca E, Remondini D. et al. Methods for the integration of multi-omics data: mathematical aspects. BMC Bioinformatics 2016; 17 (Suppl. 02) 15
    CrossrefPubMedGoogle Scholar
  • 3 Bock C, Farlik M, Sheffield NC. Multi-omics of single cells: strategies and applications. Trends Biotechnol 2016; 34 (08) 605-608
    CrossrefPubMedGoogle Scholar
  • 4 Vilanova C, Porcar M. Are multi-omics enough?. Nat Microbiol 2016; 1 (08) 16101
    CrossrefPubMedGoogle Scholar
  • 5 National Cancer Institute (US). Dictionary of Cancer Terms. Bethesda, MD: National Cancer Institute; US; 2002. Accessed June 19, 2023 at: https://www.ncbi.nlm.nih.gov/books/NBK65951/
    Google Scholar
  • 6 Wilkie AO, Slaney SF, Oldridge M. et al. Apert syndrome results from localized mutations of FGFR2 and is allelic with Crouzon syndrome. Nat Genet 1995; 9 (02) 165-172
    CrossrefPubMedGoogle Scholar
  • 7 Scambler PJ, Kelly D, Lindsay E. et al. Velo-cardio-facial syndrome associated with chromosome 22 deletions encompassing the DiGeorge locus. Lancet 1992; 339 (8802): 1138-1139
    CrossrefPubMedGoogle Scholar
  • 8 Glass II DA. Current understanding of the genetic causes of keloid formation. J Investig Dermatol Symp Proc 2017; 18 (02) S50-S53
    CrossrefPubMedGoogle Scholar
  • 9 Durmaz AA, Karaca E, Demkow U, Toruner G, Schoumans J, Cogulu O. Evolution of genetic techniques: past, present, and beyond. BioMed Res Int 2015; 2015: 461524
    CrossrefPubMedGoogle Scholar
  • 10 Halim AS, Emami A, Salahshourifar I, Kannan TP. Keloid scarring: understanding the genetic basis, advances, and prospects. Arch Plast Surg 2012; 39 (03) 184-189
    Article in Thieme ConnectPubMedGoogle Scholar
  • 11 Ahmed A, Almohanna H, Griggs J, Tosti A. Genetic hair disorders: a review. Dermatol Ther (Heidelb) 2019; 9 (03) 421-448
    CrossrefPubMedGoogle Scholar
  • 12 Makrantonaki E, Bekou V, Zouboulis CC. Genetics and skin aging. Dermatoendocrinol 2012; 4 (03) 280-284
    CrossrefPubMedGoogle Scholar
  • 13 Dixon MJ, Marazita ML, Beaty TH, Murray JC. Cleft lip and palate: understanding genetic and environmental influences. Nat Rev Genet 2011; 12 (03) 167-178
    CrossrefPubMedGoogle Scholar
  • 14 Butali A, Mossey PA, Adeyemo WL. et al. Genomic analyses in African populations identify novel risk loci for cleft palate. Hum Mol Genet 2019; 28 (06) 1038-1051
    CrossrefPubMedGoogle Scholar
  • 15 Grant SF, Wang K, Zhang H. et al. A genome-wide association study identifies a locus for nonsyndromic cleft lip with or without cleft palate on 8q24. J Pediatr 2009; 155 (06) 909-913
    CrossrefPubMedGoogle Scholar
  • 16 Birnbaum S, Ludwig KU, Reutter H. et al. Key susceptibility locus for nonsyndromic cleft lip with or without cleft palate on chromosome 8q24. Nat Genet 2009; 41 (04) 473-477
    CrossrefPubMedGoogle Scholar
  • 17 Mangold E, Ludwig KU, Birnbaum S. et al. Genome-wide association study identifies two susceptibility loci for nonsyndromic cleft lip with or without cleft palate. Nat Genet 2010; 42 (01) 24-26
    CrossrefPubMedGoogle Scholar
  • 18 Beaty TH, Murray JC, Marazita ML. et al. A genome-wide association study of cleft lip with and without cleft palate identifies risk variants near MAFB and ABCA4. Nat Genet 2010; 42 (06) 525-529
    CrossrefPubMedGoogle Scholar
  • 19 Ludwig KU, Mangold E, Herms S. et al. Genome-wide meta-analyses of nonsyndromic cleft lip with or without cleft palate identify six new risk loci. Nat Genet 2012; 44 (09) 968-971
    CrossrefPubMedGoogle Scholar
  • 20 Sun Y, Huang Y, Yin A. et al. Genome-wide association study identifies a new susceptibility locus for cleft lip with or without a cleft palate. Nat Commun 2015; 6: 6414
    CrossrefPubMedGoogle Scholar
  • 21 Leslie EJ, Carlson JC, Shaffer JR. et al. A multi-ethnic genome-wide association study identifies novel loci for non-syndromic cleft lip with or without cleft palate on 2p24.2, 17q23 and 19q13. Hum Mol Genet 2016; 25 (13) 2862-2872
    PubMedGoogle Scholar
  • 22 Leslie EJ, Liu H, Carlson JC. et al. A genome-wide association study of nonsyndromic cleft palate identifies an etiologic missense variant in GRHL3. Am J Hum Genet 2016; 98 (04) 744-754
    CrossrefPubMedGoogle Scholar
  • 23 Mangold E, Böhmer AC, Ishorst N. et al. Sequencing the GRHL3 coding region reveals rare truncating mutations and a common susceptibility variant for nonsyndromic cleft palate. Am J Hum Genet 2016; 98 (04) 755-762
    CrossrefPubMedGoogle Scholar
  • 24 Leslie EJ, Carlson JC, Shaffer JR. et al. Genome-wide meta-analyses of nonsyndromic orofacial clefts identify novel associations between FOXE1 and all orofacial clefts, and TP63 and cleft lip with or without cleft palate. Hum Genet 2017; 136 (03) 275-286
    CrossrefPubMedGoogle Scholar
  • 25 Ludwig KU, Ahmed ST, Böhmer AC. et al. Meta-analysis reveals genome-wide significance at 15q13 for nonsyndromic clefting of both the lip and the palate, and functional analyses implicate GREM1 as a plausible causative gene. PLoS Genet 2016; 12 (03) e1005914
    CrossrefPubMedGoogle Scholar
  • 26 Yu Y, Zuo X, He M. et al. Genome-wide analyses of non-syndromic cleft lip with palate identify 14 novel loci and genetic heterogeneity. Nat Commun 2017; 8: 14364
    CrossrefPubMedGoogle Scholar
  • 27 Shabalina SA, Spiridonov NA. The mammalian transcriptome and the function of non-coding DNA sequences. Genome Biol 2004; 5 (04) 105
    CrossrefPubMedGoogle Scholar
  • 28 Lowe R, Shirley N, Bleackley M, Dolan S, Shafee T. Transcriptomics technologies. PLOS Comput Biol 2017; 13 (05) e1005457
    CrossrefPubMedGoogle Scholar
  • 29 Stark R, Grzelak M, Hadfield J. RNA sequencing: the teenage years. Nat Rev Genet 2019; 20 (11) 631-656
    CrossrefPubMedGoogle Scholar
  • 30 Zou Z, Tao T, Li H, Zhu X. mTOR signaling pathway and mTOR inhibitors in cancer: progress and challenges. Cell Biosci 2020; 10: 31
    CrossrefPubMedGoogle Scholar
  • 31 Wong VW, You F, Januszyk M, Gurtner GC, Kuang AA. Transcriptional profiling of rapamycin-treated fibroblasts from hypertrophic and keloid scars. Ann Plast Surg 2014; 72 (06) 711-719
    CrossrefPubMedGoogle Scholar
  • 32 Dupont C, Armant DR, Brenner CA. Epigenetics: definition, mechanisms and clinical perspective. Semin Reprod Med 2009; 27 (05) 351-357
    Article in Thieme ConnectPubMedGoogle Scholar
  • 33 Jones LR, Young W, Divine G. et al. Genome-wide scan for methylation profiles in keloids. Dis Markers 2015; 2015: 943176
    CrossrefPubMedGoogle Scholar
  • 34 Simeone P, Alberti S. Epigenetic heredity of human height. Physiol Rep 2014; 2 (06) e12047
    CrossrefPubMedGoogle Scholar
  • 35 Lim JP, Brunet A. Bridging the transgenerational gap with epigenetic memory. Trends Genet 2013; 29 (03) 176-186
    CrossrefPubMedGoogle Scholar
  • 36 Gapp K, Jawaid A, Sarkies P. et al. Implication of sperm RNAs in transgenerational inheritance of the effects of early trauma in mice. Nat Neurosci 2014; 17 (05) 667-669
    CrossrefPubMedGoogle Scholar
  • 37 Iqbal K, Tran DA, Li AX. et al. Deleterious effects of endocrine disruptors are corrected in the mammalian germline by epigenome reprogramming. Genome Biol 2015; 16 (01) 59
    CrossrefPubMedGoogle Scholar
  • 38 Shea JM, Serra RW, Carone BR. et al. Genetic and epigenetic variation, but not diet, shape the sperm methylome. Dev Cell 2015; 35 (06) 750-758
    CrossrefPubMedGoogle Scholar
  • 39 Kaati G, Bygren LO, Pembrey M, Sjöström M. Transgenerational response to nutrition, early life circumstances and longevity. Eur J Hum Genet 2007; 15 (07) 784-790
    CrossrefPubMedGoogle Scholar
  • 40 Bartel DP. Metazoan microRNAs. Cell 2018; 173 (01) 20-51
    CrossrefPubMedGoogle Scholar
  • 41 Baker MA, Davis SJ, Liu P. et al. Tissue-specific microRNA expression patterns in four types of kidney disease. J Am Soc Nephrol 2017; 28 (10) 2985-2992
    CrossrefPubMedGoogle Scholar
  • 42 Tang W, Wan S, Yang Z, Teschendorff AE, Zou Q. Tumor origin detection with tissue-specific miRNA and DNA methylation markers. Bioinformatics 2018; 34 (03) 398-406
    CrossrefPubMedGoogle Scholar
  • 43 Zhang J, Xu D, Li N. et al. Downregulation of microRNA-31 inhibits proliferation and induces apoptosis by targeting HIF1AN in human keloid. Oncotarget 2017; 8 (43) 74623-74634
    CrossrefPubMedGoogle Scholar
  • 44 Li C, Bai Y, Liu H. et al. Comparative study of microRNA profiling in keloid fibroblast and annotation of differential expressed microRNAs. Acta Biochim Biophys Sin (Shanghai) 2013; 45 (08) 692-699
    CrossrefPubMedGoogle Scholar
  • 45 Zhu C, Wang S, Zheng M. et al. miR-31-5p modulates cell progression in lung adenocarcinoma through TNS1/p53 axis. Strahlenther Onkol 2022; 198 (03) 304-314
    CrossrefPubMedGoogle Scholar
  • 46 Fu H, Zhou F, Yuan Q. et al. miRNA-31-5p mediates the proliferation and apoptosis of human spermatogonial stem cells via targeting JAZF1 and cyclin A2. Mol Ther Nucleic Acids 2019; 14: 90-100
    CrossrefPubMedGoogle Scholar
  • 47 Lu Z, He Q, Liang J. et al. miR-31-5p is a potential circulating biomarker and therapeutic target for oral cancer. Mol Ther Nucleic Acids 2019; 16: 471-480
    CrossrefPubMedGoogle Scholar
  • 48 Liu CJ, Tsai MM, Hung PS. et al. miR-31 ablates expression of the HIF regulatory factor FIH to activate the HIF pathway in head and neck carcinoma. Cancer Res 2010; 70 (04) 1635-1644
    CrossrefPubMedGoogle Scholar
  • 49 Lei SL, Zhao H, Yao HL. et al. Regulatory roles of microRNA-708 and microRNA-31 in proliferation, apoptosis and invasion of colorectal cancer cells. Oncol Lett 2014; 8 (04) 1768-1774
    CrossrefPubMedGoogle Scholar
  • 50 Wang A, Landén NX, Meisgen F. et al. MicroRNA-31 is overexpressed in cutaneous squamous cell carcinoma and regulates cell motility and colony formation ability of tumor cells. PLoS One 2014; 9 (07) e103206
    CrossrefPubMedGoogle Scholar
  • 51 Laurila EM, Kallioniemi A. The diverse role of miR-31 in regulating cancer associated phenotypes. Genes Chromosomes Cancer 2013; 52 (12) 1103-1113
    CrossrefPubMedGoogle Scholar
  • 52 Li Y, Quan J, Chen F. et al. MiR-31-5p acts as a tumor suppressor in renal cell carcinoma by targeting cyclin-dependent kinase 1 (CDK1). Biomed Pharmacother 2019; 111: 517-526
    CrossrefPubMedGoogle Scholar
  • 53 Wang S, Hu J, Zhang D, Li J, Fei Q, Sun Y. Prognostic role of microRNA-31 in various cancers: a meta-analysis. Tumour Biol 2014; 35 (11) 11639-11645
    CrossrefPubMedGoogle Scholar
  • 54 Wei J, Wang Z, Wang Z. et al. MicroRNA-31 function as a suppressor was regulated by epigenetic mechanisms in gastric cancer. BioMed Res Int 2017; 2017: 5348490
    PubMedGoogle Scholar
  • 55 Peng B, Chen Y, Leong KW. MicroRNA delivery for regenerative medicine. Adv Drug Deliv Rev 2015; 88: 108-122
    CrossrefPubMedGoogle Scholar
  • 56 Turker MS. Gene silencing in mammalian cells and the spread of DNA methylation. Oncogene 2002; 21 (35) 5388-5393
    CrossrefPubMedGoogle Scholar
  • 57 Stephen JK, Vaught LE, Chen KM. et al. An epigenetically derived monoclonal origin for recurrent respiratory papillomatosis. Arch Otolaryngol Head Neck Surg 2007; 133 (07) 684-692
    CrossrefPubMedGoogle Scholar
  • 58 Stephen JK, Chen KM, Shah V. et al. Consistent DNA hypermethylation patterns in laryngeal papillomas. Int J Head Neck Surg 2010; 1 (02) 69-77
    CrossrefPubMedGoogle Scholar
  • 59 Worsham MJ, Stephen JK, Chen KM. et al. Delineating an epigenetic continuum in head and neck cancer. Cancer Lett 2014; 342 (02) 178-184
    CrossrefPubMedGoogle Scholar
  • 60 Pease M, Ling C, Mack WJ, Wang K, Zada G. The role of epigenetic modification in tumorigenesis and progression of pituitary adenomas: a systematic review of the literature. PLoS One 2013; 8 (12) e82619
    CrossrefPubMedGoogle Scholar
  • 61 Jones PA, Baylin SB. The epigenomics of cancer. Cell 2007; 128 (04) 683-692
    CrossrefPubMedGoogle Scholar
  • 62 Jones PA, Baylin SB. The fundamental role of epigenetic events in cancer. Nat Rev Genet 2002; 3 (06) 415-428
    CrossrefPubMedGoogle Scholar
  • 63 Jones LR, Greene J, Chen KM. et al. Biological significance of genome-wide DNA methylation profiles in keloids. Laryngoscope 2017; 127 (01) 70-78
    CrossrefPubMedGoogle Scholar
  • 64 Alghamdi MA, Wallace HJ, Melton PE. et al. Identification of differentially methylated CpG sites in fibroblasts from keloid scars. Biomedicines 2020; 8 (07) 181
    CrossrefPubMedGoogle Scholar
  • 65 Stevenson AW, Deng Z, Allahham A, Prêle CM, Wood FM, Fear MW. The epigenetics of keloids. Exp Dermatol 2021; 30 (08) 1099-1114
    CrossrefPubMedGoogle Scholar
  • 66 Smith CM, Haimberger ZW, Johnson CO. et al. Heritable chromatin structure: mapping “memory” in histones H3 and H4. Proc Natl Acad Sci U S A 2002; 99 (Suppl. 04) 16454-16461
    CrossrefPubMedGoogle Scholar
  • 67 Russell SB, Russell JD, Trupin KM. et al. Epigenetically altered wound healing in keloid fibroblasts. J Invest Dermatol 2010; 130 (10) 2489-2496
    CrossrefPubMedGoogle Scholar
  • 68 Glenisson W, Castronovo V, Waltregny D. Histone deacetylase 4 is required for TGFbeta1-induced myofibroblastic differentiation. Biochim Biophys Acta 2007; 1773 (10) 1572-1582
    CrossrefPubMedGoogle Scholar
  • 69 Ghosh AK, Mori Y, Dowling E, Varga J. Trichostatin A blocks TGF-beta-induced collagen gene expression in skin fibroblasts: involvement of Sp1. Biochem Biophys Res Commun 2007; 354 (02) 420-426
    CrossrefPubMedGoogle Scholar
  • 70 Rombouts K, Niki T, Greenwel P. et al. Trichostatin A, a histone deacetylase inhibitor, suppresses collagen synthesis and prevents TGF-beta(1)-induced fibrogenesis in skin fibroblasts. Exp Cell Res 2002; 278 (02) 184-197
    CrossrefPubMedGoogle Scholar
  • 71 Huber LC, Distler JH, Moritz F. et al. Trichostatin A prevents the accumulation of extracellular matrix in a mouse model of bleomycin-induced skin fibrosis. Arthritis Rheum 2007; 56 (08) 2755-2764
    CrossrefPubMedGoogle Scholar
  • 72 Hsu CK, Lin HH, Harn HI. et al. Caveolin-1 controls hyperresponsiveness to mechanical stimuli and fibrogenesis-associated RUNX2 activation in keloid fibroblasts. J Invest Dermatol 2018; 138 (01) 208-218
    CrossrefPubMedGoogle Scholar
  • 73 Jian X, Qu L, Wang Y. et al. Trichostatin A-induced miR-30a-5p regulates apoptosis and proliferation of keloid fibroblasts via targeting BCL2. Mol Med Rep 2019; 19 (06) 5251-5262
    PubMedGoogle Scholar
  • 74 Tu T, Huang J, Lin M. et al. CUDC-907 reverses pathological phenotype of keloid fibroblasts in vitro and in vivo via dual inhibition of PI3K/Akt/mTOR signaling and HDAC2. Int J Mol Med 2019; 44 (05) 1789-1800
    PubMedGoogle Scholar
  • 75 Yoon S, Kang G, Eom GH. HDAC inhibitors: therapeutic potential in fibrosis-associated human diseases. Int J Mol Sci 2019; 20 (06) 1329
    CrossrefPubMedGoogle Scholar
  • 76 Hiebert CA. The carcinogenic action of methylcholanthrene on mouse skin in organ culture. Cancer 1959; 12 (04) 663-672
    CrossrefPubMedGoogle Scholar
  • 77 Bell E, Ivarsson B, Merrill C. Production of a tissue-like structure by contraction of collagen lattices by human fibroblasts of different proliferative potential in vitro. Proc Natl Acad Sci U S A 1979; 76 (03) 1274-1278
    CrossrefPubMedGoogle Scholar
  • 78 Yin B, Ni J, Witherel CE. et al. Harnessing tissue-derived extracellular vesicles for osteoarthritis theranostics. Theranostics 2022; 12 (01) 207-231
    CrossrefPubMedGoogle Scholar
  • 79 Amsar RM, Wijaya CH, Ana ID. et al. Extracellular vesicles: a promising cell-free therapy for cartilage repair. Future Sci OA 2021; 8 (02) FSO774
    CrossrefPubMedGoogle Scholar
  • 80 Bajada S, Mazakova I, Richardson JB, Ashammakhi N. Updates on stem cells and their applications in regenerative medicine. J Tissue Eng Regen Med 2008; 2 (04) 169-183
    CrossrefPubMedGoogle Scholar
  • 81 Schmidt C. FDA approves first cell therapy for wrinkle-free visage. Nat Biotechnol 2011; 29 (08) 674-675
    CrossrefPubMedGoogle Scholar
  • 82 Eça LP, Pinto DG, de Pinho AM, Mazzetti MP, Odo ME. Autologous fibroblast culture in the repair of aging skin. Dermatol Surg 2012; 38 (02) 180-184
    PubMedGoogle Scholar
  • 83 Khodadadi L, Shafieyan S, Sotoudeh M. et al. Intraepidermal injection of dissociated epidermal cell suspension improves vitiligo. Arch Dermatol Res 2010; 302 (08) 593-599
    CrossrefPubMedGoogle Scholar
  • 84 Kim JH, Jung M, Kim HS, Kim YM, Choi EH. Adipose-derived stem cells as a new therapeutic modality for ageing skin. Exp Dermatol 2011; 20 (05) 383-387
    CrossrefPubMedGoogle Scholar
  • 85 Leung CM, de Haan P, Ronaldson-Bouchard K. et al. A guide to the organ-on-a-chip. Nat Rev Methods Primers 2022; 2: 33
    CrossrefPubMedGoogle Scholar
  • 86 Amirifar L, Shamloo A, Nasiri R. et al. Brain-on-a-chip: recent advances in design and techniques for microfluidic models of the brain in health and disease. Biomaterials 2022; 285: 121531
    CrossrefPubMedGoogle Scholar
  • 87 Van Gele M, Geusens B, Brochez L, Speeckaert R, Lambert J. Three-dimensional skin models as tools for transdermal drug delivery: challenges and limitations. Expert Opin Drug Deliv 2011; 8 (06) 705-720
    CrossrefPubMedGoogle Scholar
  • 88 Küchler S, Strüver K, Friess W. Reconstructed skin models as emerging tools for drug absorption studies. Expert Opin Drug Metab Toxicol 2013; 9 (10) 1255-1263
    CrossrefPubMedGoogle Scholar
  • 89 Flaten GE, Palac Z, Engesland A, Filipović-Grčić J, Vanić Ž, Škalko-Basnet N. In vitro skin models as a tool in optimization of drug formulation. Eur J Pharm Sci 2015; 75: 10-24
    CrossrefPubMedGoogle Scholar
  • 90 Zhang Q, Sito L, Mao M, He J, Zhang YS, Zhao X. Current advances in skin-on-a-chip models for drug testing. Microphysiol Syst 2018; 2: 4
    PubMedGoogle Scholar
  • 91 Kim K, Kim J, Kim H, Sung GY. Effect of α-lipoic acid on the development of human skin equivalents using a pumpless skin-on-a-chip model. Int J Mol Sci 2021; 22 (04) 2160
    CrossrefPubMedGoogle Scholar
  • 92 Fetah KL, DiPardo BJ, Kongadzem E-M. et al. Cancer modeling-on-a-chip with future artificial intelligence integration. Small 2019; 15 (50) e1901985
    CrossrefPubMedGoogle Scholar
  • 93 Elmusrati M, Ashammakhi N. Cancer-on-a-chip and artificial intelligence: tomorrow's cancer management. J Craniofac Surg 2018; 29 (07) 1682-1683
    CrossrefPubMedGoogle Scholar
  • 94 Abaci HE, Shuler ML. Human-on-a-chip design strategies and principles for physiologically based pharmacokinetics/pharmacodynamics modeling. Integr Biol 2015; 7 (04) 383-391
    CrossrefPubMedGoogle Scholar
  • 95 Zor F, Bozkurt M, Nair D, Siemionow M. A new composite midface allotransplantation model with sensory and motor reinnervation. Transpl Int 2010; 23 (06) 649-656
    CrossrefPubMedGoogle Scholar
  • 96 Kulahci Y, Siemionow M. A new composite hemiface/mandible/tongue transplantation model in rats. Ann Plast Surg 2010; 64 (01) 114-121
    CrossrefPubMedGoogle Scholar
  • 97 Morris DE, Wu L, Zhao LL. et al. Acute and chronic animal models for excessive dermal scarring: quantitative studies. Plast Reconstr Surg 1997; 100 (03) 674-681
    CrossrefPubMedGoogle Scholar
  • 98 Gupta A, Bhat S, Jagdale PR. et al. Evaluation of three-dimensional chitosan-agarose-gelatin cryogel scaffold for the repair of subchondral cartilage defects: an in vivo study in a rabbit model. Tissue Eng Part A 2014; 20 (23–24): 3101-3111
    CrossrefPubMedGoogle Scholar
  • 99 Hallermann W, Olsen S, Bardyn T, Taghizadeh F, Banic A, Iizuka T. A new method for computer-aided operation planning for extensive mandibular reconstruction. Plast Reconstr Surg 2006; 117 (07) 2431-2437
    CrossrefPubMedGoogle Scholar
  • 100 Mohanty AJ, Cleveland P, Shang Z. et al. Facial nerve high-resolution visualization and topographic microanatomy analysis from the distal intratemporal to extracranial pes segment - reconstructive implications. Plast Reconstr Surg 2023; 152 (01) 175-182
    CrossrefPubMedGoogle Scholar