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A special issue of Biomedicines (ISSN 2227-9059). This special issue belongs to the section "Molecular and Translational Medicine".

Deadline for manuscript submissions: closed (29 February 2024) | Viewed by 51231

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Special Issue Editors

Dr. Fernando Capela e Silva

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1. Department of Medical and Health Sciences, School of Health and Human Development, University of Évora, 7000-671 Évora, Portugal
2. Mediterranean Institute for Agriculture, Environment and Development (MED), University of Évora, 7000-671 Évora, Portugal
Interests: biology of oral tissues; eating behavior and its effects on the health of people and populations; food, health and society and the “One Health” approach
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Dr. Elsa Lamy

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Guest Editor

Mediterranean Institute for Agriculture, Environment and Development (MED), University of Évora, 7002-554 Évora, Portugal
Interests: biological determinants of eating behavior; oral perception and salivary biochemistry associated with this perception; Mediterranean diet
Special Issues, Collections and Topics in MDPI journals

Dr. Paula Midori Castelo

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Guest Editor

Department of Pharmaceutical Sciences, Institute of Environmental, Chemical and Pharmaceutical Sciences, Universidade Federal de São Paulo (UNIFESP), Diadema, Brazil
Interests: clinical oral physiology; salivary biomarkers; masticatory behavior

Special Issue Information

Dear Colleagues,

Oral biology is a diverse scientific field involving several disciplines, such as molecular biology, genetics, microbiology, immunology, biochemistry, biophysics, craniofacial development, pharmacology, physiology, and cancer biology. The complex and unique dynamics of the various tissues, fluids, and functions of the oral cavity and craniofacial structures requires the development of new strategies and approaches to understand, prevent, manage, or cure various human diseases associated with these systems. Much of the oral biology knowledge is based on the results of research conducted on different models. Biological models are experimental systems that recreate aspects of the function or disease of human tissues, including certain cell lines of transgenic and non-transgenic animals and of traditional and emerging species, and in silico models, among others, that can serve as models in the study of oral biology.

This Special Issue aims to gather high-quality research, highlighting the importance of the use of models in the study of oral biology. The submission of new and comparative methodologies to understand the biology of diseases using new analysis methods is welcomed. Review articles are also welcomed. Potential topics include but are not limited to the following:

Comparative anatomy and physiology;
Salivary biology;
Mastication and swallowing;
Mechanisms of pellicle and biofilm formation, mechanisms, and regulation of exocrine processes;
In vitro tissue culture systems;
In vitro applications of three-dimensional oral mucosal models;
Human embryonic stem cells as a model to study craniofacial development;
Human stem cells for applications in dental and craniofacial tissue regeneration;
Emerging model systems;
In silico models for the study of oral biology;
Aging and oral health;
Diseases of the mouth and related structures such as salivary glands, temporomandibular joints, masticatory and facial muscles, and perioral skin;
Biomedical engineering, tissue engineering, and stem cells;
Biomarkers for oral and periodontal diseases;
Oral biology and physiopathology;
Oral microbiology and immunology;
Sensory neuroscience;
Mineralized tissue biology and craniofacial development;
Molecular and cellular aspects of oral cancer to develop novel therapeutic opportunities.

Dr. Fernando Capela e Silva
Dr. Elsa Lamy
Dr. Paula Midori Castelo
Guest Editors

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Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Biomedicines is an international peer-reviewed open access monthly journal published by MDPI.

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Keywords

oral biology
salivary biology
oral microbiology
oral immunology
models

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Published Papers (9 papers)

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Editorial

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5 pages, 209 KiB

Open AccessEditorial

Models for Oral Biology Research 2.0

by Fernando Capela e Silva, Elsa Lamy and Paula Midori Castelo

Biomedicines 2024, 12(12), 2804; https://doi.org/10.3390/biomedicines12122804 - 10 Dec 2024

Viewed by 764

Abstract

The oral cavity constitutes a unique and complex system and environment [...] Full article

(This article belongs to the Special Issue Models for Oral Biology Research 2.0)

Research

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15 pages, 3196 KiB

Open AccessArticle

Arecoline Induces ROS Accumulation, Transcription of Proinflammatory Factors, and Expression of KRT6 in Oral Epithelial Cells

by Tong-Hong Wang, Yen-Wen Shen, Hsin-Ying Chen, Chih-Chieh Chen, Nan-Chin Lin, Yin-Hwa Shih, Shih-Min Hsia, Kuo-Chou Chiu and Tzong-Ming Shieh

Biomedicines 2024, 12(2), 412; https://doi.org/10.3390/biomedicines12020412 - 9 Feb 2024

Cited by 3 | Viewed by 2045

Abstract

Areca nut is a major contributor to the high prevalence of oral cancer in Asia. The precise mechanisms by which areca nut stimulates mucosal cells and contributes to the progression of oral cancer urgently require clarification. The current study aimed to assess the effects of arecoline on the normal human gingival epithelium cell line S-G. Cell viability, levels of reactive oxygen species (ROS), protein expression, cellular morphology, and gene expression were evaluated using the MTT test, flow cytometry, Western blot analysis, optical or confocal microscopy, and RT-qPCR. Keratin (KRT6) analysis involved matched normal and cancer tissues from clinical head and neck specimens. The results demonstrated that 12.5 µg/mL of arecoline induced ROS production, tumor necrosis factor-α (TNF-α), and interleukin-6 (IL-6) mRNA expression in S-G cells. This activation of the MAPK/ERK pathway increased KRT6 expression while limiting cell migration. In head and neck cancer tissues, KRT6B gene expression exceeded that of normal tissues. This study confirms that arecoline induces ROS accumulation in normal cells, leading to the secretion of proinflammatory factors and KRT6 expression. This impedes oral mucosal healing, thereby promoting the progression of oral cancer. Full article

(This article belongs to the Special Issue Models for Oral Biology Research 2.0)

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21 pages, 10915 KiB

Open AccessArticle

Development of New Models of Oral Mucosa to Investigate the Impact of the Structure of Transmembrane Mucin-1 on the Mucosal Pellicle Formation and Its Physicochemical Properties

by Clément Nivet, Irma Custovic, Laure Avoscan, Floris J. Bikker, Aline Bonnotte, Eric Bourillot, Loïc Briand, Hélène Brignot, Jean-Marie Heydel, Noémie Herrmann, Mélanie Lelièvre, Eric Lesniewska, Fabrice Neiers, Olivier Piétrement, Mathieu Schwartz, Christine Belloir and Francis Canon

Biomedicines 2024, 12(1), 139; https://doi.org/10.3390/biomedicines12010139 - 9 Jan 2024

Cited by 1 | Viewed by 2273

Abstract

The mucosal pellicle (MP) is a biological film protecting the oral mucosa. It is composed of bounded salivary proteins and transmembrane mucin MUC1 expressed by oral epithelial cells. Previous research indicates that MUC1 expression enhances the binding of the main salivary protein forming the MP, MUC5B. This study investigated the influence of MUC1 structure on MP formation. A TR146 cell line, which does not express MUC1 natively, was stably transfected with genes coding for three MUC1 isoforms differing in the structure of the two main extracellular domains: the VNTR domain, exhibiting a variable number of tandem repeats, and the SEA domain, maintaining the two bound subunits of MUC1. Semi-quantification of MUC1 using dot blot chemiluminescence showed comparable expression levels in all transfected cell lines. Semi-quantification of MUC5B by immunostaining after incubation with saliva revealed that MUC1 expression significantly increased MUC5B adsorption. Neither the VNTR domain nor the SEA domain was influenced MUC5B anchoring, suggesting the key role of the MUC1 N-terminal domain. AFM-IR nanospectroscopy revealed discernible shifts indicative of changes in the chemical properties at the cell surface due to the expression of the MUC1 isoform. Furthermore, the observed chemical shifts suggest the involvement of hydrophobic effects in the interaction between MUC1 and salivary proteins. Full article

(This article belongs to the Special Issue Models for Oral Biology Research 2.0)

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18 pages, 1977 KiB

Open AccessArticle

Diagnosis and Assessment of Dental Caries Using Novel Bioactive Caries Detecting Dye Solution

by Shashirekha Govind, Amit Jena, Sushanta Kumar Kamilla, Neeta Mohanty, Rachappa M. Mallikarjuna, Triveni Nalawade, Sanjay Saraf, Naseer Al Khaldi, Salma Al Jahdhami and Vinay Shivagange

Biomedicines 2023, 11(2), 500; https://doi.org/10.3390/biomedicines11020500 - 9 Feb 2023

Cited by 6 | Viewed by 5501

Abstract

Background: The goal of materials should be early caries detection, removal of carious lesions, and reduction of dentin hypersensitivity. Thus, the study aims to determine the efficacy of a bioactive caries detecting dye (BCD) for the diagnosing and mechanical removal of occlusal and proximal dental caries. Methods: Patients with occlusal (A1, A2) and proximal carious lesions (B1, B2) were treated with the rotary technique and BCD solution on 120 teeth (n = 60 for each). Group 1: Excavation was performed using diamond points. Group 2: 0.5 mL of BCD solution was scrubbed for 20 sec and excavation was performed with a sharp spoon excavator. Post-excavation cavity volume analysis was performed using a 3D scanner. The time required, VAS for pain, VAS for facial expression, and sound eye motor scoring were scored during excavation. Post-restoration evaluation was performed at 3, 6, and 12 months (FDI criteria). Results: The chi-square test revealed that the A1 (197.90 30.97 s) and B1 (273.06 69.95 s) had significantly less mean procedural time than the A2 (292.13 44.87 s) and B2 (411.86 88.34 s). BCD (A2, B2) group showed good patient acceptance, less pain during caries excavation VAS (p = 0.001, FACE (p = 0.001), and SEM (p < 0.001) analysis than the rotary group. There was a statistically insignificant difference between groups immediately (p = 0.235), (p = 0.475) and after 24 h (p = 0.561), (p = 0.688). Color score, hardness of excavated surface, and caries removal score for occlusal and proximal groups showed insignificant differences between the groups. BCD group showed significantly less mean caries excavated volume for the occlusal group (p = 0.003) as compared to the proximal group (p = 0.417) evaluated by 3D scanner. Evaluation of restoration after 3-, 6-, and 12 months intervals (Occlusal caries group (p = 0.247), (p = 0.330), and (0.489) and Proximal caries group (p = 0.299), (p = 0.594), and (0.494)) was acceptable for both the groups. Conclusion: BCD helps in identification of dental caries clinically, radiographically, and in effective removal of denatured teeth with less pain or sensitivity. Full article

(This article belongs to the Special Issue Models for Oral Biology Research 2.0)

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11 pages, 282 KiB

Open AccessArticle

Air Pollution as a Risk Indicator for Periodontitis

by Crystal Marruganti, Hye-Sun Shin, Seon-Ju Sim, Simone Grandini, Andreina Laforí and Mario Romandini

Biomedicines 2023, 11(2), 443; https://doi.org/10.3390/biomedicines11020443 - 2 Feb 2023

Cited by 23 | Viewed by 3084

Abstract

Background: Air pollutants can influence local and systemic inflammation, oxidative stress and microbiome composition. Therefore, air pollution may potentially represent an unexplored modifiable risk indicator for periodontitis. The aim of the current cross-sectional study was to investigate the epidemiological association between outdoor air pollution and periodontitis in a representative sample of the South Korean population. Methods: A total of 42,020 individuals, which were representative of 35.2 million South Koreans, were examined. The mean annual levels of particulate matter of 10 μm (PM10), ozone, sulfur dioxide (SO₂), nitrogen dioxide (NO₂) and humidity, were studied. Periodontitis was defined according to the Community Periodontal Index (CPI ≥ 3). Simple and multiple regression analyses using four different models were applied. Results: Every 5-μg/m³ increase in PM10 (OR = 1.17; 95% confidence interval—CI: 1.11–1.24) and of 0.005 ppm in ozone levels (OR = 1.4; 95% CI: 1.00–1.30) were positively associated with periodontitis prevalence. Conversely, every 5% increase in humidity (OR = 0.94; 95% CI: 0.90–0.99) and 0.003 ppm increase in NO₂ levels (OR = 0.93; 95% CI: 0.89–0.96) were inversely associated with periodontitis occurrence. Conclusions: In this nationally representative population several air pollutants were found to be associated with periodontitis occurrence. Hence, the present results suggest that air pollution may be a new modifiable risk indicator for periodontitis. Full article

(This article belongs to the Special Issue Models for Oral Biology Research 2.0)

Review

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16 pages, 1087 KiB

Open AccessReview

Neopterin, the Cell-Mediated Immune Response Biomarker, in Inflammatory Periodontal Diseases: A Narrative Review of a More than Fifty Years Old Biomarker

by Ondrej Heneberk, Eliska Wurfelova and Vladimira Radochova

Biomedicines 2023, 11(5), 1294; https://doi.org/10.3390/biomedicines11051294 - 27 Apr 2023

Cited by 11 | Viewed by 4372

Abstract

Neopterin is a biomarker of the activation of cellular immunity. The purpose of this review is to summarise neopterin metabolism, methods of its detection, and its role in inflammation, focusing on periodontal inflammatory diseases. This derivative of guanosine is a non-enzymatic product of 7,8-dihydroneopterin oxidation caused by free radicals which protect activated macrophages from oxidative stress. Various methods, usually based on enzyme-linked immunosorbent essay, high-performance liquid chromatography, or radioimmunoassay were developed for the isolation of neopterin. A wide spectrum of diseases and conditions are known to affect neopterin levels, including cardiovascular, bacterial, viral, and degenerative diseases, as well as malignant tumours. Neopterin levels were found to increase in subjects with periodontitis, especially when the oral fluid and gingival crevicular fluid were evaluated. These findings confirm the role of activated macrophages and cellular immunity in periodontal inflammatory diseases. The gingival crevicular fluid and the oral fluid appear to be the most valuable biologic fluids for the evaluation of neopterin levels in periodontitis. For gingival crevicular fluid, neopterin can be determined as the concentration or the so-called total amount. Nonsurgical periodontal treatment was associated with a decrease in neopterin levels, but an increase was also reported, suggesting the possible role of macrophages in the resolution of the periodontal lesion. Full article

(This article belongs to the Special Issue Models for Oral Biology Research 2.0)

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20 pages, 669 KiB

Open AccessReview

Recent Clinical Treatment and Basic Research on the Alveolar Bone

by Sachio Tsuchida and Tomohiro Nakayama

Biomedicines 2023, 11(3), 843; https://doi.org/10.3390/biomedicines11030843 - 10 Mar 2023

Cited by 34 | Viewed by 11248

Abstract

The periodontal ligament is located between the bone (alveolar bone) and the cementum of the tooth, and it is connected by tough fibers called Sharpey’s fibers. To maintain healthy teeth, the foundation supporting the teeth must be healthy. Periodontal diseases, also known as tooth loss, cause the alveolar bone to dissolve. The alveolar bone, similar to the bones in other body parts, is repeatedly resorbed by osteoclasts and renewed by osteogenic cells. This means that an old bone is constantly being resorbed and replaced by a new bone. In periodontal diseases, the alveolar bone around the teeth is absorbed, and as the disease progresses, the alveolar bone shrinks gradually. In most cases, the resorbed alveolar bone does not return to its original form even after periodontal disease is cured. Gum covers the tooth surface so that it matches the shape of the resorbed alveolar bone, exposing more of the tooth surface than before, making the teeth look longer, leaving gaps between the teeth, and in some cases causing teeth to sting. Previously, the only treatment for periodontal diseases was to stop the disease from progressing further before the teeth fell out, and restoration to the original condition was almost impossible. However, a treatment method that can help in the regeneration of the supporting tissues of the teeth destroyed by periodontal diseases and the restoration of the teeth to their original healthy state as much as possible is introduced. Recently, with improvements in implant material properties, implant therapy has become an indispensable treatment method in dentistry and an important prosthetic option. Treatment methods and techniques, which are mainly based on experience, have gradually accumulated scientific evidence, and the number of indications for treatment has increased. The development of bone augmentation methods has contributed remarkably to the expansion of indications, and this has been made possible by various advances in materials science. The induced pluripotent stem cell (iPS) cell technology for regenerating periodontal tissues, including alveolar bone, is expected to be applied in the treatment of diseases, such as tooth loss and periodontitis. This review focuses on the alveolar bone and describes clinical practice, techniques, and the latest basic research. Full article

(This article belongs to the Special Issue Models for Oral Biology Research 2.0)

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19 pages, 1305 KiB

Open AccessReview

Artificial Intelligence Its Uses and Application in Pediatric Dentistry: A Review

by Satish Vishwanathaiah, Hytham N. Fageeh, Sanjeev B. Khanagar and Prabhadevi C. Maganur

Biomedicines 2023, 11(3), 788; https://doi.org/10.3390/biomedicines11030788 - 5 Mar 2023

Cited by 42 | Viewed by 11601

Abstract

In the global epidemic era, oral problems significantly impact a major population of children. The key to a child’s optimal health is early diagnosis, prevention, and treatment of these disorders. In recent years, the field of artificial intelligence (AI) has seen tremendous pace and progress. As a result, AI’s infiltration is witnessed even in those areas that were traditionally thought to be best left to human specialists. The ultimate ability to improve patient care and make precise diagnoses of illnesses has revolutionized the world of healthcare. In the field of dentistry, the competence to execute treatment measures while still providing appropriate patient behavior counseling is in high demand, particularly in the field of pediatric dental care. As a result, we decided to conduct this review specifically to examine the applications of AI models in pediatric dentistry. A comprehensive search of the subjects was done using a wide range of databases to look for studies that have been published in peer-reviewed journals from its inception until 31 December 2022. After the application of the criteria, only 25 of the 351 articles were taken into consideration for this review. According to the literature, AI is frequently used in pediatric dentistry for the purpose of making an accurate diagnosis and assisting clinicians, dentists, and pediatric dentists in clinical decision making, developing preventive strategies, and establishing an appropriate treatment plan. Full article

(This article belongs to the Special Issue Models for Oral Biology Research 2.0)

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Other

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17 pages, 633 KiB

Open AccessSystematic Review

Application and Performance of Artificial Intelligence (AI) in Oral Cancer Diagnosis and Prediction Using Histopathological Images: A Systematic Review

by Sanjeev B. Khanagar, Lubna Alkadi, Maryam A. Alghilan, Sara Kalagi, Mohammed Awawdeh, Lalitytha Kumar Bijai, Satish Vishwanathaiah, Ali Aldhebaib and Oinam Gokulchandra Singh

Biomedicines 2023, 11(6), 1612; https://doi.org/10.3390/biomedicines11061612 - 1 Jun 2023

Cited by 30 | Viewed by 8653

Abstract

Oral cancer (OC) is one of the most common forms of head and neck cancer and continues to have the lowest survival rates worldwide, even with advancements in research and therapy. The prognosis of OC has not significantly improved in recent years, presenting a persistent challenge in the biomedical field. In the field of oncology, artificial intelligence (AI) has seen rapid development, with notable successes being reported in recent times. This systematic review aimed to critically appraise the available evidence regarding the utilization of AI in the diagnosis, classification, and prediction of oral cancer (OC) using histopathological images. An electronic search of several databases, including PubMed, Scopus, Embase, the Cochrane Library, Web of Science, Google Scholar, and the Saudi Digital Library, was conducted for articles published between January 2000 and January 2023. Nineteen articles that met the inclusion criteria were then subjected to critical analysis utilizing QUADAS-2, and the certainty of the evidence was assessed using the GRADE approach. AI models have been widely applied in diagnosing oral cancer, differentiating normal and malignant regions, predicting the survival of OC patients, and grading OC. The AI models used in these studies displayed an accuracy in a range from 89.47% to 100%, sensitivity from 97.76% to 99.26%, and specificity ranging from 92% to 99.42%. The models’ abilities to diagnose, classify, and predict the occurrence of OC outperform existing clinical approaches. This demonstrates the potential for AI to deliver a superior level of precision and accuracy, helping pathologists significantly improve their diagnostic outcomes and reduce the probability of errors. Considering these advantages, regulatory bodies and policymakers should expedite the process of approval and marketing of these products for application in clinical scenarios. Full article

(This article belongs to the Special Issue Models for Oral Biology Research 2.0)

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