Glucuronidation mediated by UDP-glucuronosyltransferases (UGTs) is a significant metabolic pathway that facilitates efficient elimination of numerous endo- and xenobiotics including phenolics. UGT genetic deficiency and polymorphisms or inhibition of glucuronidation by concomitant use of drugs are associated with inherited physiological disorders or drug induced toxicities. Moreover, extensive glucuronidation can be a barrier to oral bioavailability as the first-pass glucuronidation (or premature clearance by UGTs) of orally administered agents usually results in the poor oral bioavailability and lack of efficacies. This review focused on the first-pass glucuronidation of phenolics including natural polyphenols and pharmaceuticals. The complexity of UGT-mediated metabolism of phenolics is highlighted with species-, gender-, organ- and isoform-dependent specificity, as well as functional compensation between UGT1A and 2B subfamily. In addition, recent advances are discussed with respect to the mechanisms of enzymatic actions including the important properties such as binding pocket size and phosphorylation requirements.

We introduce a new approach to the machine-assisted grading of short answer questions. We follow past work in automated grading by first training a similarity metric between student responses, but then go on to use this metric to group responses into clusters and subclusters. The resulting groupings allow teachers to grade multiple responses with a single action, provide rich feedback to groups of similar answers, and discover modalities of misunderstanding among students; we refer to this amplification of grader effort as “powergrading.” We develop the means to further reduce teacher effort by automatically performing actions when an answer key is available. We show results in terms of grading progress with a small “budget” of human actions, both from our method and an LDA-based approach, on a test corpus of 10 questions answered by 698 respondents.

This paper describes a method for the robust tracking of rigid head motion from video. This method uses a 3D ellipsoidal model of the head and interprets the optical flow in terms of the possible rigid motions of the model. This method is robust to large angular and translational motions of the head and is not subject to the singularities of a 2D model. The method has been successfully applied to heads with a variety of shapes, hair styles, etc. This method also has the advantage of accurately capturing the 3D motion parameters of the head. This accuracy is shown through comparison with a ground truth synthetic sequence (a rendered 3D animation of a model head). In addition, the ellipsoidal model is robust to small variations in the initial fit, enabling the automation of the model initialization. Lastly, due to its consideration of the entire 3D aspect of the head, the tracking is very stable over a large number of frames. This robustness extends even to sequences with very low frame rates and noisy camera images.

We develop an approach for generating deep (i.e, high-level) comprehension questions from novel text that bypasses the myriad challenges of creating a full semantic representation. We do this by decomposing the task into an ontologycrowd-relevance workflow, consisting of first representing the original text in a low-dimensional ontology, then crowdsourcing candidate question templates aligned with that space, and finally ranking potentially relevant templates for a novel region of text. If ontological labels are not available, we infer them from the text. We demonstrate the effectiveness of this method on a corpus of articles from Wikipedia alongside human judgments, and find that we can generate relevant deep questions with a precision of over 85% while maintaining a recall of 70%.

The phase II metabolism sulfation and glucuronidation, mediated by sulfotransferases (SULTs) and UDP-glucuronosyltransferases (UGTs) respectively, are significant metabolic pathways for numerous endo- and xenobiotics. Understanding of SULT/UGT substrate specificity (including regioselectivity (i.e., position preference)) is of great importance in predicting contribution of sulfation/glucuronidation to drug and metabolite disposition in vivo. This review summarizes regioselective sulfation and glucuronidation of phenolic compounds with multiple hydroxyl (OH) groups as the potential conjugation sites. The strict regioselective patterns were highlighted for several SULT and UGT isoforms towards flavonoids, a large class of natural polyphenols. To seek for a molecular-level explanation, the enzyme structures (i.e., SULT crystal structures and homology-based UGT structure models) combined with molecular docking was employed. In particular, the structural bases for regioselective metabolism of flavonoids by SULT1A3 and UGT1A1 were discussed. It was concluded that the regioselective nature of these phase II enzymes was determined by the size and shape of binding pocket. While the molecular structures of the enzymes can be used to explain regioselective metabolism regarding the binding property, predicting the turnover at different positions remains a particularly difficult task.