Recent advances in tissue engineering offer innovative clinical alternatives in dentistry and regenerative medicine. Tissue engineering combines human cells with compatible biomaterials to induce tissue regeneration. Shortening the fabrication time of biomaterials used in tissue engineering will contribute to treatment improvement, and biomaterial functionalization can be exploited to enhance scaffold properties. In this work, we have tested an alternative biofabrication method by directly including human oral mucosa tissue explants within the biomaterial for the generation of human bioengineered mouth and dental tissues for use in tissue engineering. To achieve this, acellular fibrin–agarose scaffolds (AFAS), non-functionalized fibrin-agarose oral mucosa stroma substitutes (n-FAOM), and novel functionalized fibrin-agarose oral mucosa stroma substitutes (F-FAOM) were developed and analyzed after 1, 2, and 3 weeks of in vitro development to determine extracellular matrix components as compared to native oral mucosa controls by using histochemistry and immunohistochemistry. Results demonstrate that functionalization speeds up the biofabrication method and contributes to improve the biomimetic characteristics of the scaffold in terms of extracellular matrix components and reduce the time required for in vitro tissue development.

There is an error in the title

Background: Children affected by unilateral cleft lip and palate (UCLP) represent a therapeutic challenge requiring the development of novel therapies, such as the implant of a bioengineered tissue—BIOCLEFT—or the use of nasoalveolar molding (NAM). The objective of this work was to evaluate the effects of NAM on the surgical and aesthetic outcomes of children with UCLP. Methods: A total of 36 children with UCLP treated at a craniofacial malformations management unit were evaluated, including 23 patients treated with presurgical NAM followed by palate surgical correction (NAM group) and 13 patients treated surgically without previous NAM (non-NAM group). Measurements were obtained from each patient immediately before palate surgery, including four linear measurements: nasal ala projection length (NAPL), nasal dome height (NDH), superoinferior alar groove position (S-I AGP), and nasal dome position (M-L NDP), and two angular measurements: columellar deviation (CD) and nasal bridge deviation (NBD). Results: When NAM was used, a significant improvement of the basilar view linear measurements of the patient’s nose was found, including the NAPL and NDH, and the frontal view linear measurement M-L NDP, but not S-I AGP. Significant improvements were also observed in the angular measurements of nasal symmetry CD and NBD. All these variables, except the S-I AGP, significantly correlated with the treatment group, and two variables—NAPL and CD—significantly contributed to generate a predictive model developed using binary logistic regression. Conclusions: These findings support the use of NAM to efficiently improve the nasal symmetry and the presurgical outcomes of patients with UCLP.

Background/Objectives: Periodontitis is a highly prevalent inflammatory disease and a major cause of tooth loss worldwide. Accurate diagnosis requires integration of clinical and radiographic findings, but interpretation of panoramic radiographs is subject to variability. Artificial intelligence (AI) has emerged as a promising adjunct for radiographic assessment. This systematic review evaluated the diagnostic performance of AI-based models for detecting periodontitis using panoramic radiographic images. Methods: A systematic search of PubMed, Scopus, and Web of Science identified studies published between 1 January 2015 and 1 March 2026. Eligible studies assessed AI models for periodontitis detection on panoramic radiographs and used either clinically confirmed periodontal diagnosis or expert radiographic annotation as the reference standard. Data extraction and quality assessment were performed independently by two reviewers using the QUADAS-2 tool. Owing to heterogeneity in AI architectures, datasets, and outcome measures, a narrative synthesis was conducted. Results: Nine studies met the inclusion criteria, comprising more than 20,000 radiographs. AI models included convolutional neural networks (CNNs), segmentation-based systems, and hybrid architectures. Sensitivity ranged from 0.795 to 1.00, specificity from 0.784 to 0.99, and AUC values from 0.843 to 0.967. Studies using clinical periodontal diagnosis as the reference standard generally reported lower performance than those relying solely on expert annotation. Only four studies performed external validation, and dataset sizes varied widely. One study combining panoramic and periapical radiographs showed moderate diagnostic performance. Conclusions: AI-based diagnostic models demonstrate promising performance for detecting periodontitis on panoramic radiographs, with several studies reporting high sensitivity and AUC values. However, heterogeneity in reference standards, limited external validation, and inconsistent dataset quality restrict generalizability. AI should be considered an adjunct to, rather than a replacement for, comprehensive clinical periodontal examination. Standardized datasets and robust external validation are needed to support clinical implementation.

Background/Objectives: Patients with cleft lip and palate (CLP) typically experience feeding difficulties due to an abnormal communication between the oral and nasal cavities, and novel therapies such as palate tissue engineering and nasoalveolar molding (NAM) are in need to improve the final outcomes. This study aims to evaluate the parents and caregivers perceptions on the potential of NAM to improve feeding in patients with CLP. Methods: 42 infants with unilateral or bilateral CLP treated with NAM at a reference craniofacial unit were included in the study. Parents or caregivers completed a four-item questionnaire at 3 months of age, before cheiloplasty, evaluating the effects of NAM to improve nasal regurgitation, choking, air swallowing, and feeding time using a 4-point Likert scale. A total perceived feeding benefit score (range 4–16) was calculated. Results: Parents and caregivers perceived a positive effect of NAM to improve choking (3.67 ± 0.53), nasal regurgitation (3.62 ± 0.58), and feeding time (3.50 ± 0.67), while air swallowing showed lower scores (3.19 ± 0.55). The total perceived feeding benefit score was 13.98 ± 1.57, indicating a high perceived benefit. No significant differences were found between males and females or between unilateral and bilateral clefts. Conclusions: Parents and caregivers consistently perceived a beneficial effect of NAM on patients’ feeding. Although further research is required to determine the actual effectiveness of NAM, examining the perspectives reported by parents and caregivers could contribute to understand treatment experiences and guide family-centered care.