Tori are reactive or developmental localized overgrowths of alveolar bone that are not cancerous. A thin, weakly vascularized mucosa surrounds a densely cortical, low-density mass of bone marrow known as tori or exostosis. Tori are more frequently observed in middle age. Both the maxilla (torus palatinus) and the mandible (torus mandibularis) exhibit tori. Difficulty in speaking and other issues are common obstacles associated with tori. Tori range in diameter from a few millimeters to several centimeters. Surgical excision of tori is the mainstay of treatment for large tori obstructing speech, mastication, or tongue position. The following case study includes a 36-year-old male patient with an association of mandibular canine and premolar regions with bony outgrowth.

Dentists, especially those who are not oral lesion specialists and live in rural areas, need an artificial intelligence (AI) system for accurately assisting them in screening for oral cancer that may appear in smartphone images. Not many literatures present a viable model that addresses the needs, especially in the context of oral lesion segmentation in smartphone images. This study demonstrates the use of a deep learning-based AI for simultaneously identifying types of oral cancer lesions as well as precisely outlining the boundary of the lesions in the images for the first time. The lesions of interest were oral potentially malignant disorders (OPMDs) and oral squamous cell carcinoma (OSCC) lesions. The model could successfully (1) detect if the images contained the oral lesions, (2) determine types of the lesions, and (3) precisely outline the boundary of the lesions. With future success of our project, patients will be diagnosed and treated early before the pre-cancer lesions can progress into deadly cancerous ones.

Oral pathology is a challenging yet intriguing subject. By comparing pathological traits to things we typically encounter, it is possible to reduce the difficulty of memorising these qualities. Hence, the usage of various analogical methods, like the usage of metaphors, conveys likeliness or similarities between two items and can help the students. A lot of pathological features have a resemblance to animals we see on a frequent basis. Students might find comparing, examining and comprehending oral pathology easier when the information is compared with familiar animals. This article is an attempt to compile animal metaphors related to oral pathology.

Plasma cell mucositis (PCM) is a rare inflammatory condition affecting the oral tissues, often triggered by allergens or inflammation. Autism spectrum disorder (ASD), a neurodevelopmental condition, poses unique challenges in oral care and hygiene due to behavioral and sensory issues. These conditions have not previously been reported in concert but may share risk factors including through the development of inflammation. We present a case of severe PCM in a 23-year-old male with ASD, illustrating diagnostic complexities and management strategies. The patient presented with widespread and severe lesions, raising the possibility of underlying causes. After multiple interventions, including topical steroids and trigger avoidance, the patient achieved near-complete resolution of the oral lesions. Immunohistochemical and serological investigations suggested an underlying monoclonal gammopathy, warranting hematological evaluation. Our case shows how PCM and ASD can affect each other, highlighting the importance of understanding how these conditions interact, and the need for tailored approaches to oral health in this population. Further research is needed to elucidate any pathophysiological or risk-based link between ASD and inflammatory oral conditions and to refine management strategies for PCM in patients with neurodevelopmental disorders.

OBJECTIVE: Several factors such as unavailability of specialists, dental phobia, and financial difficulties may lead to a delay between receiving an oral radiology report and consulting a dentist. The primary aim of this study was to distinguish between high-risk and low-risk oral lesions according to the radiologist\'s reports of cone beam computed tomography (CBCT) images. Such a facility may be employed by dentist or his/her assistant to make the patient aware of the severity and the grade of the oral lesion and referral for immediate treatment or other follow-up care.
METHODS: A total number of 1134 CBCT radiography reports owned by Shiraz University of Medical Sciences were collected. The severity level of each sample was specified by three experts, and an annotation was carried out accordingly. After preprocessing the data, a deep learning model, referred to as CNN-LSTM, was developed, which aims to detect the degree of severity of the problem based on analysis of the radiologist\'s report. Unlike traditional models which usually use a simple collection of words, the proposed deep model uses words embedded in dense vector representations, which empowers it to effectively capture semantic similarities.
RESULTS: The results indicated that the proposed model outperformed its counterparts in terms of precision, recall, and F1 criteria. This suggests its potential as a reliable tool for early estimation of the severity of oral lesions.
CONCLUSIONS: This study shows the effectiveness of deep learning in the analysis of textual reports and accurately distinguishing between high-risk and low-risk lesions. Employing the proposed model which can Provide timely warnings about the need for follow-up and prompt treatment can shield the patient from the risks associated with delays.
CONCLUSIONS: Our collaboratively collected and expert-annotated dataset serves as a valuable resource for exploratory research. The results demonstrate the pivotal role of our deep learning model could play in assessing the severity of oral lesions in dental reports.

The diagnosis of oral lichen planus (OLP) poses many challenges due to its nonspecific clinical symptoms and histopathological features. Therefore, the diagnostic process should include a thorough clinical history, immunological tests, and histopathology. Our study aimed to enhance the diagnostic accuracy of OLP by integrating direct immunofluorescence (DIF) results with clinical data to develop a multivariate predictive model based on the Artificial Neural Network. Eighty patients were assessed using DIF for various markers (immunoglobulins of classes G, A, and M; complement 3; fibrinogen type 1 and 2) and clinical characteristics such as age, gender, and lesion location. Statistical analysis was performed using machine learning techniques in Statistica 13. The following variables were assessed: gender, age on the day of lesion onset, results of direct immunofluorescence, location of white patches, locations of erosions, treatment history, medications and dietary supplement intake, dental status, smoking status, flossing, and using mouthwash. Four statistically significant variables were selected for machine learning after the initial assessment. The final predictive model, based on neural networks, achieved 85% in the testing sample and 71% accuracy in the validation sample. Significant predictors included stress at onset, white patches under the tongue, and erosions on the mandibular gingiva. In conclusion, while the model shows promise, larger datasets and more comprehensive variables are needed to improve diagnostic accuracy for OLP, highlighting the need for further research and collaborative data collection efforts.

Although rare, oral manifestations of hypersensitivity reactions in orthodontic patients pose a significant clinical challenge due to their heterogeneous presentations, and can cause discomfort and pain, possibly impacting patients\' quality of life and orthodontic treatment duration and outcomes. This comprehensive review aimed to elucidate the oral, perioral, and systemic manifestations of hypersensitivity reactions in orthodontic subjects, focusing on patients with fixed appliances, removable appliances, and clear aligners, and detailing their epidemiology, macroscopic and microscopic features, allergy testing, clinical implications, and specific management strategies. Oral and extra-oral manifestations of (immediate and delayed) hypersensitivity reactions occur rarely and are due to the release of metal and non-metal ions from orthodontic appliances. They typically present as erythema, erosive-ulcerative lesions, and gingival hyperplasia, with histopathological findings showing inflammatory infiltrates. Nickel is a significant allergen, and diagnostic tests like patch tests are essential for managing these reactions. Likely due to prolonged contact with oral tissues, fixed orthodontic appliances pose a higher risk compared to removable appliances and clear aligners. Early identification and removal of allergenic materials, combined with effective treatments, can resolve symptoms and prevent recurrence. Keeping dental and medical records updated and knowing family and personal medical histories helps clinicians choose appropriate materials and counsel patients about potential risks. Proper patient education, regular monitoring, and using hypoallergenic materials are key strategies for managing these reactions.

OBJECTIVE: To investigate the clinical features and risk factors of Sjogren\'s Syndrome (SS) patients suffering from oral candidiasis and to provide a foundation for the prevention and treatment of oral candidiasis in SS patients.
METHODS: The medical records of 479 SS patients admitted to the Second Hospital of Shanxi Medical University from 2018 to 2020 were analysed to determine the clinical characteristics and risk factors that influence the occurrence of oral candidiasis infection in SS patients.
RESULTS: Patients with oral candidiasis were older than those without oral candidiasis (P < 0.05). Male SS patients had greater oral candidiasis rates (P < 0.05). Unstimulated whole saliva (UWS) and stimulated whole saliva (SWS) were both shown to be adversely associated with oral Candida infections (P < 0.001). Logistic regression revealed that a low UWS was an independent risk factor for oral Candida infections in SS patients (OR: 0.004, P = 0.023). Greater WBC counts (OR: 1.22, P < 0.001), lower haemoglobin levels (OR: 0.97, P = 0.007), lower serum albumin levels (OR: 0.88, P < 0.001), lower IgG levels (OR: 0.91, P = 0.011), lower IgA levels (OR: 0.75, P = 0.011), and lower IgM levels (OR: 0.91, P = 0.015) were found in patients with oral Candida infections. Patients on immunosuppressive medications (OR: 0.32, P = 0.011), particularly rapamycin (P < 0.001), had a decreased rate of oral Candida infections.
CONCLUSIONS: Patients with oral candidiasis were older than those without oral candidiasis. Male SS patients are more likely to have oral candidiasis. Individuals with lower UWS and SWS are more susceptible to oral Candida infection. Oral Candida infections in SS patients depend on their immunological status. Rapamycin may increase the abundance of Treg cells to reduce oral Candida infection in SS patients.

Approximately 39 million people worldwide live with human immunodeficiency virus (HIV), and antiretroviral therapy (ART) has improved life expectancy for these individuals, with quality of life (QoL) being a crucial aspect. However, there is limited information on oral health-related quality of life (OHRQoL) for institutionalized patients with HIV. This study used a cross-sectional design and included 43 residents of a non-governmental institution who had a confirmed HIV diagnosis and a history of intravenous drug use. The Spanish version of the Oral Health Index Profile-14 (OHIPsp) was used to assess the OHRQoL, with the 50th percentile serving as the cutoff for good or poor quality of life. All 43 patients had one or more oral lesions, with 44.1% having AIDS-related oral lesions (AROLs). Over half of the participants (48.8%) reported a poor OHRQoL, and females experienced worse quality of life in all dimensions compared to males. Subjects with AROLs were three times more likely to have poor OHRQoL than those without AROLs (p = 0.03; OR = 3.1 IC 1.04-9.6). These results highlight the need for a comprehensive treatment plan for patients with HIV that includes oral health, particularly for women living in precarious conditions or who are institutionalized. Improving oral health can significantly enhance quality of life.

OBJECTIVE: Current scales for Pemphigus vulgaris (PV) do not adequately represent the clinical variability of oral lesions. This study aimed to develop an independent scale, the Pemphigus Oral Lesions Area Index (POLAI), for assessment of oral PV exclusively, and compare POLAI, Pemphigus Disease Area Index (PDAI), Autoimmune Bullous Skin Disorder Intensity Score (ABSIS) and Oral Disease Severity Score (ODSS) regarding inter- and intra-observer reliability and validity.
METHODS: Retrospective cohort included 209 sets of digital-photographs. Additional clinical cohort included 32 PV patients. All visits were assessed by four clinicians using the PDAI, ABSIS, ODSS and POLAI, and were rated by three specialists using the Physician\'s Global Assessment (PGA).
RESULTS: The intraclass correlation coefficient showed the inter-observer reliability with 0.89 and 0.86 for PDAI, 0.87 for ABSIS, 0.93 for ODSS, 0.96 for POLAI, and 0.97 and 0.96 for PGA. Intra-observer agreements showed excellent reliability for all 4 scores. Highest correlation was observed between PGA and POLAI (correlation coefficients were 0.96). The mean time taken to complete each scale was within 1.5 min.
CONCLUSIONS: POLAI is valid for the assessment of oral PV with superior inter- and intra-observer reliability to PDAI, ABSIS and ODSS, and is feasible in clinic.