Comparison of linear model and artificial neural network using antler beam diameter and length of white-tailed deer (Odocoileus virginianus) dataset.

Evaluation of harvest data remains one of the most important sources of information in the development of strategies to manage regional populations of white-tailed deer. While descriptive statistics and simple linear models are utilized extensively, the use of artificial neural networks for this type of data analyses is unexplored. Linear model was compared to Artificial Neural Networks (ANN) models with Levenberg-Marquardt (L-M), Bayesian Regularization (BR) and Scaled Conjugate Gradient (SCG) learning algorithms, to evaluate the relative accuracy in predicting antler beam diameter and length using age and dressed body weight in white-tailed deer. Data utilized for this study were obtained from male animals harvested by hunters between 1977-2009 at the Berry College Wildlife Management Area. Metrics for evaluating model performance indicated that linear and ANN models resulted in close match and good agreement between predicted and observed values and thus good performance for all models. However, metrics values of Mean Absolute Error and Root Mean Squared Error for linear model and the ANN-BR model indicated smaller error and lower deviation relative to the mean values of antler beam diameter and length in comparison to other ANN models, demonstrating better agreement of the predicted and observed values of antler beam diameter and length. ANN-SCG model resulted in the highest error within the models. Overall, metrics for evaluating model performance from the ANN model with BR learning algorithm and linear model indicated better agreement of the predicted and observed values of antler beam diameter and length. Results of this study suggest the use of ANN generated results that are comparable to Linear Models of harvest data to aid in the development of strategies to manage white-tailed deer.

Idiopathic gingival papillokeratosis with crypt formation, a report of 7 cases of a previously undescribed entity: possible unusual oral epithelial nevus?

We report 7 cases of hitherto undescribed keratotic papillary plaques of uncertain etiology involving the gingiva. All 7 cases presented on the anterior maxillary attached gingiva of patients in the second decade. The lesions were asymptomatic and 86% (6 of 7 cases) presented in a bilateral symmetric distribution. Microscopically, the lesions exhibited parakeratosis and papillary acanthosis with parakeratin-filled crypts. No specific etiology such as a factitial habit or a common exogenous agent has been identified. The possibility of a developmental etiology such as an oral epithelial nevus cannot be entirely excluded. We propose the descriptive term idiopathic gingival papillokeratosis with crypt formation (IGPC) for this condition.

The root of the problem: Occurrence of typical and atypical periapical pathoses.

BACKGROUND: A preponderance of periapical radiolucencies are of inflammatory etiology (radicular cysts or periapical granulomas) secondary to pulpal disease. In some instances, however, a suspected periapical inflammatory lesion is not a consequence of pulpal disease but instead represents a lesion of noninflammatory origin. The differential diagnosis for such lesions is broad, ranging from odontogenic cysts and tumors to metastatic disease. As the biological behavior of such lesions is varied, the distinction between inflammatory odontogenic periapical lesions and lesions of noninflammatory origin in a periapical location is critical. METHODS: A retrospective study of 5,993 archival periapical biopsies over a span of 15 years from the database of the Oral Pathology Biopsy Service in the Henry M. Goldman School of Dental Medicine at Boston University recorded the incidence of various lesions in a periapical location. RESULTS: Of the cases studied, 97.2% represented lesions of inflammatory origin with histopathologic diagnoses as follows: periapical granuloma (60.0%), radicular cyst (36.7%), periapical fibrous scar (0.27 %), and periapical abscess (0.23 %). The remaining 2.8% cases were lesions of noninflammatory origin with histopathologic diagnoses of odontogenic keratocyst (also known as keratocystic odontogenic tumor), benign fibro-osseous lesions, and ameloblastoma. One patient had Langerhans cell disease, and 1 had central giant cell granuloma. CONCLUSIONS: Although most periapical specimens biopsied represented expected inflammatory periapical lesions, the biological behavior of underdiagnosed lesions may have considerable consequences for both the patient and the clinician. PRACTICAL IMPLICATIONS: This article serves to inform clinicians regarding the diversity of lesions arising in the periapical region of the jaws, to assist in the formulation of differential diagnoses, and to highlight the importance of submission of lesional tissue for histopathologic evaluation and definitive diagnosis when biopsy is clinically indicated.

PDGFRß Is a Novel Marker of Stromal Activation in Oral Squamous Cell Carcinomas.

Carcinoma associated fibroblasts (CAFs) form the main constituents of tumor stroma and play an important role in tumor growth and invasion. The presence of CAFs is a strong predictor of poor prognosis of head and neck squamous cell carcinoma. Despite significant progress in determining the role of CAFs in tumor progression, the mechanisms contributing to their activation remain poorly characterized, in part due to fibroblast heterogeneity and the scarcity of reliable fibroblast surface markers. To search for such markers in oral squamous cell carcinoma (OSCC), we applied a novel approach that uses RNA-sequencing data derived from the cancer genome atlas (TCGA). Specifically, our strategy allowed for an unbiased identification of genes whose expression was closely associated with a set of bona fide stroma-specific transcripts, namely the interstitial collagens COL1A1, COL1A2, and COL3A1. Among the top hits were genes involved in cellular matrix remodeling and tumor invasion and migration, including platelet-derived growth factor receptor beta (PDGFRß), which was found to be the highest-ranking receptor protein genome-wide. Similar analyses performed on ten additional TCGA cancer datasets revealed that other tumor types shared CAF markers with OSCC, including PDGFRß, which was found to significantly correlate with the reference collagen expression in ten of the 11 cancer types tested. Subsequent immunostaining of OSCC specimens demonstrated that PDGFRß was abundantly expressed in stromal fibroblasts of all tested cases (12/12), while it was absent in tumor cells, with greater specificity than other known markers such as alpha smooth muscle actin or podoplanin (3/11). Overall, this study identified PDGFRß as a novel marker of stromal activation in OSCC, and further characterized a list of promising candidate CAF markers that may be relevant to other carcinomas. Our novel approach provides for a fast and accurate method to identify CAF markers without the need for large-scale immunostaining experiments.

Intraoral removal of a giant submandibular sialolith obstructing Wharton's duct: a case report.

Sialolithiasis is one of the most common pathologies of the submandibular gland; sialoliths account for about 80 percent of all salivary duct calculi. This report presents the unusual case of a large asymptomatic sialolith of the submandibular duct, initially diagnosed as a possible tumor. The giant sialolith was removed via an intraoral approach under local anesthesia. The etiology, pathogenesis, and management of such giant sialoliths are discussed.

Anatomy-based algorithms for detecting oral cancer using reflectance and fluorescence spectroscopy.

OBJECTIVES: We used reflectance and fluorescence spectroscopy to noninvasively and quantitatively distinguish benign from dysplastic/malignant oral lesions. We designed diagnostic algorithms to account for differences in the spectral properties among anatomic sites (gingiva, buccal mucosa, etc). METHODS: In vivo reflectance and fluorescence spectra were collected from 71 patients with oral lesions. The tissue was then biopsied and the specimen evaluated by histopathology. Quantitative parameters related to tissue morphology and biochemistry were extracted from the spectra. Diagnostic algorithms specific for combinations of sites with similar spectral properties were developed. RESULTS: Discrimination of benign from dysplastic/malignant lesions was most successful when algorithms were designed for individual sites (area under the receiver operator characteristic curve [ROC-AUC],0.75 for the lateral surface of the tongue) and was least accurate when all sites were combined (ROC-AUC, 0.60). The combination of sites with similar spectral properties (floor of mouth and lateral surface of the tongue) yielded an ROC-AUC of 0.71. CONCLUSIONS: Accurate spectroscopic detection of oral disease must account for spectral variations among anatomic sites. Anatomy-based algorithms for single sites or combinations of sites demonstrated good diagnostic performance in distinguishing benign lesions from dysplastic/malignant lesions and consistently performed better than algorithms developed for all sites combined.

AAOMP case challenge: a mass of the tuberosity.

A 72-year-old male presented with a raised lesion in the area of the maxillary right tuberosity. The patient had become aware of the lesion only recently when his upper complete denture would not seat properly.