Threshold Static Automated Perimetry of the Full Visual Field in Idiopathic Intracranial Hypertension.

Purpose: To characterize visual loss across the full visual field in idiopathic intracranial hypertension (IIH) patients with mild central visual loss.

Methods: We tested the full visual field (50° nasal, 80° temporal, 30° superior, 45° inferior) of 1 eye of 39 IIH patients by using static perimetry (size V) with the Open Perimetry Interface. Participants met the Dandy criteria for IIH and had at least Frisén grade 1 papilledema with better than -5 dB mean deviation (MD) centrally.

Pediatric idiopathic retroperitoneal fibrosis.

Retroperitoneal fibrosis (RPF) is a very rare disease that is even more rare in the pediatric population. Even less common are idiopathic pediatric cases of retroperitoneal fibrosis, with a majority of reported pediatric retroperitoneal fibrosis cases being associated with secondary etiologies. We present an 11-year-old Caucasian female that was diagnosed with idiopathic retroperitoneal fibrosis using magnetic resonance imaging (MRI) to work-up severe bilateral hydronephrosis that was identified with retroperitoneal ultrasound.

β-sheet topology prediction with high precision and recall for β and mixed α/β proteins.

The prediction of the correct β-sheet topology for pure β and mixed α/β proteins is a critical intermediate step toward the three dimensional protein structure prediction. The predicted beta sheet topology provides distance constraints between sequentially separated residues, which reduces the three dimensional search space for a protein structure prediction algorithm. Here, we present a novel mixed integer linear optimization based framework for the prediction of β-sheet topology in β and mixed α/β proteins.

A novel framework for predicting in vivo toxicities from in vitro data using optimal methods for dense and sparse matrix reordering and logistic regression.

In this work, we combine the strengths of mixed-integer linear optimization (MILP) and logistic regression for predicting the in vivo toxicity of chemicals using only their measured in vitro assay data. The proposed approach utilizes a biclustering method based on iterative optimal reordering (DiMaggio, P. A.

Selecting high quality protein structures from diverse conformational ensembles.

Protein structure prediction encompasses two major challenges: 1), the generation of a large ensemble of high resolution structures for a given amino-acid sequence; and 2), the identification of the structure closest to the native structure for a blind prediction. In this article, we address the second challenge, by proposing what is, to our knowledge, a novel iterative traveling-salesman problem-based clustering method to identify the structures of a protein, in a given ensemble, which are closest to the native structure. The method consists of an iterative procedure, which aims at eliminating clusters of structures at each iteration, which are unlikely to be of similar fold to the native, based on a statistical analysis of cluster density and average spherical radius.