Oral diseases最新文献

Objective: To review the effect of outer membrane vesicles (OMVs) of the periodontal pathogen Porphyromonas gingivalis (P. gingivalis) on macrophages during periodontitis development.

Method: Literature pertaining to P. gingivalis OMVs and macrophages was reviewed and discussed, with a focus on the immunomodulatory effects of P. gingivalis OMVs on macrophages.

Results: P. gingivalis OMVs affect the recognition, phagocytosis, polarization, and apoptosis functions of macrophages. However, information on their antigen-presenting effect remains lacking, and further research is required for clinical applications.

Conclusion: P. gingivalis OMVs can influence the development of periodontitis through immune modulation of macrophages; however, further research is required to provide novel ideas for the prevention and treatment of periodontitis.

Objective: To summarize the evidence on the relationship between hereditary family history and nonsyndromic orofacial clefts (NSOC) in patients from various Brazilian states.

Methods: This cross-sectional multicenter study was conducted at six specialized orofacial cleft services across different regions of Brazil. The sample consisted of 1899 patients with NSOC, including cleft lip only (NSCLO), cleft palate only (NSCPO), and cleft lip and palate (NSCLP). Data were collected from clinical records between June 2023 and May 2024. Family history was classified as positive or negative, with additional details on the number of affected relatives, degree of kinship, and type of oral cleft. Statistical analysis was performed using SPSS version 27.0, with chi-square tests and z tests to assess associations between variables, and Student's t test to compare the mean number of affected relatives among cleft types.

Results: Of 1899 patients, 52.6% had NSCLP, 24.11% had NSCPO, and 23.27% had NSCLO. NSCLP and NSCLO were more common in males, while NSCPO was more frequent in females. NSCLP and NSCLO showed similar rates of positive family history, whereas NSCPO had significantly fewer cases with hereditary links. Third-degree relatives were the most affected across all groups.

Conclusion: NSCLP and NSCLO showed a higher frequency in males and more cases of positive family history compared to NSCPO. Further studies are needed to explore the genetic basis of NSOC, particularly in genetically diverse populations like Brazil.

Aims: Trimethylamine N-oxide (TMAO) is a compound involved in the pathogenesis of various systemic inflammatory diseases, including cardiovascular conditions. The aim of this study was to determine differences in saliva and serum levels of TMAO between periodontitis and healthy patients according to smoking status.

Methods: The study included four systemically healthy groups: periodontally healthy non-smokers (NS-Control; n = 25), non-smokers with Stage-III-Grade-B periodontitis (NS-Periodontitis; n = 25), periodontally healthy smokers (S-Control; n = 25), and smokers with Stage-III Grade-C periodontitis (S-Periodontitis; n = 25). Periodontal parameters were recorded. TMAO levels were determined in saliva and serum samples using liquid chromatography-mass spectrometry (LC-MS/MS). TNF-α levels were measured by the ELISA method.

Results: Salivary TNF-α and TMAO levels were significantly elevated in the smoking periodontitis group compared to other groups (p < 0.001 and p = 0.003, respectively). Serum TMAO levels were also significantly higher in the smoking periodontitis group compared to non-smoking controls and non-smoking periodontitis. TMAO/SFR ratios were notably higher in the smoking periodontitis group compared to other groups, and a strong positive correlation was observed between salivary TMAO and TNF-α levels (r = 0.892, p < 0.001).

Conclusion: The data suggested that TMAO and TNF-α are associated with inflammatory mechanisms of periodontitis in cases where periodontitis coexists with smoking.

Trial registration: NCT06580431.

Objectives: Utilizing a deep learning approach is an emerging trend to improve the efficiency of periodontitis diagnosis and classification. This study aimed to use an object detection model to automatically annotate the anatomic structure and subsequently classify the stages of radiographic bone loss (RBL).

Materials and methods: In all, 558 panoramic radiographs were cropped to 7359 pieces of individual teeth. The detection performance of the model was assessed using mean average precision (mAP), root mean squared error (RMSE). The classification performance was evaluated using accuracy, precision, recall, and F1 score. Additionally, receiver operating characteristic (ROC) curves and confusion matrices were presented, and the area under the ROC curve (AUC) was calculated.

Results: The mAP was 0.88 when the difference between the ground truth and prediction was 10 pixels, and 0.99 when the difference was 25 pixels. For all images, the mean RMSE was 7.30 pixels. Overall, the accuracy, precision, recall, F1 score, and micro-average AUC of the prediction were 0.72, 0.76, 0.64, 0.68, and 0.79, respectively.

Conclusions: The current model is reliable in assisting with the detection and staging of radiographic bone levels.

Objective: Tumour-associated macrophages (TAMs) are crucial in the progression and treatment response of oral squamous cell carcinoma (OSCC). TAMs infiltrate OSCC, adopting an M2-like phenotype that promotes tumour growth, metastasis and immune suppression. The current narrative review explored the roles of TAMs in OSCC, focusing on their impact on the tumour microenvironment, invasion, metastasis, angiogenesis, immunosuppression and potential therapeutic targeting.

Methods: A comprehensive analysis of the current literature on TAMs in OSCC was conducted. Specifically, we evaluated the biological functions of TAMs, their interactions within the tumour microenvironment, and their influence on disease progression and treatment outcomes.

Results: TAMs contribute to OSCC progression by secreting cytokines, such as IL-10 and TGF-β, that inhibit effector immune cells. They facilitate angiogenesis, extracellular matrix remodelling and the epithelial-mesenchymal transition, which are essential for tumour invasion and metastasis. TAMs support cancer stem cells and recruit regulatory T cells and myeloid-derived suppressor cells, enhancing resistance to therapies. Their presence correlates with advanced OSCC stages, lymph node metastasis and poor prognosis.

Conclusion: TAMs regulate OSCC progression and therapy resistance. Reprogramming them to an M1-like phenotype or depleting them enhances treatments. Understanding TAM-OSCC interactions is crucial for developing interventions against their tumour-promoting functions and restoring anti-tumour immunity.

Objective: To review current knowledge of the various processes of programmed cell death and their roles in immunoregulation in periodontitis.

Methods: Relevant literature in the PubMed, Medline, and Scopus databases was searched, and a narrative review was performed. Programmed cell death and the regulation of its various pathways implicated in periodontal infection were reviewed.

Results: Multicellular organisms dispose of unnecessary or damaged cells via programmed cell death. Programmed cell death lies at the core of the balance of cell death and survival in pathological progress and infection. Periodontitis is a complex infectious disease involving virulence factors of periodontal pathogens and tightly regulated immune responses of the host. Different types of programmed cell death can play opposite roles in periodontitis or exert their action combinatorially.

Conclusion: The coordinated system of various programmed cell death pathways and the extensive crosstalk among them play a fundamental role in the pathophysiology of periodontitis. Illuminating the precise roles and mechanisms of programmed cell death in periodontitis could open up novel therapeutic approaches.

Objectives: The aim of this study is to estimate the economic burden of oral cancer in Australia from the societal perspective.

Methods: The population consisted of the prevalence of lip and oral cavity cancer, and other lip, oral cavity, and pharynx cancers for ages 40 years and older. Healthcare costs of oral cancer were estimated using 2019-2020 Australian Disease Expenditure Data. Productivity losses were estimated using disability-adjusted life years, derived from the 2019 Global Burden of Disease Study and 2019 Australian gross domestic product per capita.

Results: The estimated annual healthcare costs for oral cancer in Australia were approximately AUD$113.2 million. Over half of the total healthcare costs (54%) were attributable to public hospital admissions (AUD$61.2 million), followed by private hospital services (28%) and pharmaceutical benefits (8%). The total costs, including healthcare and productivity losses, were around AUD$2.1 billion. The productivity losses due to oral cancer were higher for males compared to females (AUD$1.5 billion versus AUD$0.6 billion).

Conclusions: The study reveals a significant economic burden of oral cancer for 2019 in Australia at AUD$2.1 billion, largely due to productivity losses and public hospital admissions. This highlights the need for effective screening and prevention programs.

Background: This study aimed to investigate potential cellular senescence inhibitory genes (CSIGs) and discover novel therapeutic targets in head and neck squamous cell carcinoma.

Methods: Dysregulated CSIGs were identified based on The Cancer Genome Atlas (TCGA) and the Human Aging Genomic Resources (HAGR) database. Prognostic value and immune infiltration were assessed through bioinformatic analysis. Cell proliferation was evaluated using CCK-8, Edu assay, and colony formation assays in vitro. Western blotting and real-time PCR were used to evaluate LIMA1 expression. Clinical validation of LIMA1 expression was performed in our validated cohort.

Results: In this study, differential analysis and functional enrichment analysis identified 26 differentially expressed senescence inhibitory genes. Among them, LIMA1 was found to be an independent prognostic marker and associated immune infiltration. Knockdown of LIMA1 inhibited HNSCC cell growth and increased the expression of senescence markers. Further experiments revealed that LIMA1 expression was partially regulated by the IL6/STAT3 signaling pathway. Immunohistochemistry further validated the clinical significance of LIMA1 expression and its association with IL6 and CD8⁺ T cells in our hospital's HNSCC tissues.

Conclusion: LIMA1 is a prognostic senescence-inhibitory gene in HNSCC. The IL6/STAT3/LIMA1 axis represents a novel molecular mechanism underlying cellular senescence resistance in HNSCC.