Kernel density correlation based non-rigid point set matching for statistical model-based 2D/3D reconstruction

This paper presents a kernel density correlation based nonrigid point set matching method and shows its application in statistical model based 2D/3D reconstruction of a scaled, patient-specific model from an un-calibrated x-ray radiograph. In this method, both the reference point set and the floating point set are first represented using kernel density estimates. A correlation measure between these two kernel density estimates is then optimized to find a displacement field such that the floating point set is moved to the reference point set. Regularizations based on the overall deformation energy and the motion smoothness energy are used to constraint the displacement field for a robust point set matching. Incorporating this non-rigid point set matching method into a statistical model based 2D/3D reconstruction framework, we can reconstruct a scaled, patient-specific model from noisy edge points that are extracted directly from the x-ray radiograph by an edge detector. Our experiment conducted on datasets of two patients and six cadavers demonstrates a mean reconstruction error of 1.9 mm

Oral lichenoid contact lesions induced by areca nut and betel quid chewing: a mini review

Betel quid (BQ) and areca nut chewing is widely prevalent in many parts of Asia and Asian-migrant communities throughout the world. Global reports estimate 600 million users. Sufficient evidence of carcinogenicity has been found for BQ and its main ingredient, areca nut. BQ areca nut users have an increased risk of potentially malignant disorders. Among chewers, BQ remains in contact with the oral mucosa for prolonged periods. This review examines the clinical and pathological aspects of lichenoid lesions caused by areca nut and BQ, a condition that has received little attention in the published literature.

Clinicopathologic features and long-term outcomes of NUT midline carcinoma

NUT midline carcinoma (NMC) is a poorly differentiated squamous cancer characterized by rearrangement of the NUT gene. Research advances have provided opportunities for targeted therapy in NMC, yet the clinical features of this rare disease have not been systematically characterized. We report on a large population of such patients to identify the disease characteristics and treatments, correlate them with outcome, and to consider clinical recommendations.

A metabolomic approach to the metabolism of the areca nut alkaloids arecoline and arecaidine in the mouse

The areca alkaloids comprise arecoline, arecaidine, guvacoline, and guvacine. Approximately 600 million users of areca nut products, for example, betel quid chewers, are exposed to these alkaloids, principally arecoline and arecaidine. Metabolism of arecoline (20 mg/kg p.o. and i.p.) and arecaidine (20 mg/kg p.o. and i.p.) was investigated in the mouse using a metabolomic approach employing ultra-performance liquid chromatography-time-of-flight mass spectrometric analysis of urines. Eleven metabolites of arecoline were identified, including arecaidine, arecoline N-oxide, arecaidine N-oxide, N-methylnipecotic acid, N-methylnipecotylglycine, arecaidinylglycine, arecaidinylglycerol, arecaidine mercapturic acid, arecoline mercapturic acid, and arecoline N-oxide mercapturic acid, together with nine unidentified metabolites. Arecaidine shared six of these metabolites with arecoline. Unchanged arecoline comprised 0.3-0.4%, arecaidine 7.1-13.1%, arecoline N-oxide 7.4-19.0%, and N-methylnipecotic acid 13.5-30.3% of the dose excreted in 0-12 h urine after arecoline administration. Unchanged arecaidine comprised 15.1-23.0%, and N-methylnipecotic acid 14.8%-37.7% of the dose excreted in 0-12 h urine after arecaidine administration. The major metabolite of both arecoline and arecaidine, N-methylnipecotic acid, is a novel metabolite arising from carbon-carbon double-bond reduction. Another unusual metabolite found was the monoacylglyceride of arecaidine. What role, if any, that is played by these uncommon metabolites in the toxicology of arecoline and arecaidine is not known. However, the enhanced understanding of the metabolic transformation of arecoline and arecaidine should contribute to further research into the clinical toxicology of the areca alkaloids.

KDENS: Stata module for univariate kernel density estimation

kdens produces univariate kernel density estimates and graphs the result. kdens supplements official Stata's kdensity. Important additions are: adaptive (i.e. variable bandwidth) kernel density estimation, several automatic bandwidth selectors including the Sheather-Jones plug-in estimator, pointwise variability bands and confidence intervals, boundary correction for variables with bounded domain, fast binned approximation estimation. Note that the moremata package, also available from SSC, is required.