Objective: To study the relationship of the expressions of p53 and mdm2 in leukoplakia cancer.
Methods: RT-PCR was used to detect the mRNA of p53, mdm2 in patients with leukoplakia cancer. The frequencies of p53, mdm2 in peripheral blood were detected by flow cytometric analysis.
Results: The expression of p53mRNA in normal oral mucosa, simple oral leukoplakia, no-simple oral leukoplakia and leukoplakia cancer were 7.7%, 27.3%,33.3%, 56.8%, respectively. The frequencies of p53 in normal oral mucosa, simple oral leukoplakia, no-simple oral leukoplakia and leukoplakia cancer were (0.3±0.1)%, (1.6±0.9)%, (1.9±1.1)%, (3.4±1.8)%. The expression of mdm2 mRNA in normal oral mucosa, simple oral leukoplakia, no-simple oral leukoplakia and leukoplakia cancer were 0.0%, 6.8%, 11.1%, 37.8%, respectively. The frequencies of mdm2 in normal oral mucosa, simple oral leukoplakia, no-simple oral leukoplakia and leukoplakia cancer were (0.1±0.1)%, (0.8±0.6)%, (1.2±0.8)%, (1.2±0.8)%. There was a positively correlation between p53 mRNA and mdm2 mRNA.
Conclusions: The positive rate of p53 and mdm2 cells in the peripheral blood increases in patients with leukoplakia cancer tissue and has positive correlation with the severity of leukoplakia cancer.
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http://dx.doi.org/10.1016/S1995-7645(13)60147-9 | DOI Listing |
Am J Otolaryngol
December 2024
Department of Otorhinolaryngology Head and Neck Surgery, Tianjin First Central Hospital, Tianjin 300192, China; Institute of Otolaryngology of Tianjin, Tianjin, China; Key Laboratory of Auditory Speech and Balance Medicine, Tianjin, China; Key Clinical Discipline of Tianjin (Otolaryngology), Tianjin, China; Otolaryngology Clinical Quality Control Centre, Tianjin, China.
Purpose: To use deep learning technology to design and implement a model that can automatically classify laryngoscope images and assist doctors in diagnosing laryngeal diseases.
Materials And Methods: The experiment was based on 3057 images (normal, glottic cancer, granuloma, Reinke's Edema, vocal cord cyst, leukoplakia, nodules and polyps) from the dataset Laryngoscope8. A classification model based on deep neural networks was developed and tested.
BMC Oral Health
December 2024
Dental Sciences Graduate Program. Federal University of Espirito Santo (UFES), Avenida Maruípe 1468, Maruípe, Vitória, 29040-090, ES, Brazil.
Background: Clinicopathological diagnosis and follow-up of oral lichen planus and leukoplakia are necessary due to its potential for malignant transformation and the need to differentiate it from other lichenoid diseases and proliferative verrucous leukoplakia. This study aimed to classify and compare sociodemographic and clinicopathological features among patients with oral lichen planus, oral lichenoid lesions and proliferative verrucous leukoplakia.
Methods: A transversal observational study in which oral leukoplakia and oral lichen planus patients were surveyed at the Oral Pathological Anatomy Service and Applied Biotechnology Laboratory was conducted.
Oral Dis
December 2024
Dipartimento di Scienze Biomediche Chirurgiche e Odontoiatriche, Università Degli Studi di Milano, Milan, Italy.
Medicine (Baltimore)
December 2024
Department of Medical Biology, Faculty of Medicine, Pavol Jozef Šafárik University in Košice, Košice, Slovak Republic.
Front Immunol
December 2024
Department of Experimental Medicine (DIMES), University of Genoa, Genoa, Italy.
Oral leukoplakia is classified among oral potentially malignant disorders (OPMDs) by the World Health Organization (WHO). The visual oral examination (VOE) is the most used method for identifying lesions in their early stages. Given that the diagnosis of oral cancer is often late, there is an urgent need for early detection and examination of oral lesions.
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