Simultaneous new onset of neuromyelitis optica spectrum disorder in identical twins.

Objective: To present a case of two identical twins presenting concurrently with symptoms and subsequent initial diagnosis of neuromyelitis optica spectrum disorder (NMOSD).

Methods: Clinical, laboratory and MRI findings for both twins were reviewed and presented here.

Results: Twin A presented with right eye pain and subsequent blurred vision in right eye.

Learning Concave Conditional Likelihood Models for Improved Analysis of Tandem Mass Spectra.

The most widely used technology to identify the proteins present in a complex biological sample is tandem mass spectrometry, which quickly produces a large collection of spectra representative of the (i.e., protein subsequences) present in the original sample.

Speeding Up Percolator.

The processing of peptide tandem mass spectrometry data involves matching observed spectra against a sequence database. The ranking and calibration of these peptide-spectrum matches can be improved substantially using a machine learning postprocessor. Here, we describe our efforts to speed up one widely used postprocessor, Percolator.

Analyzing Tandem Mass Spectra Using the DRIP Toolkit: Training, Searching, and Post-Processing.

Tandem mass spectrometry (MS/MS) is a high-throughput technology used to identify the proteins present in a complex, biological sample. Critical to MS/MS is the ability to accurately identify the peptide responsible for producing each observed spectrum. Recently, a dynamic Bayesian network (DBN) approach was shown to achieve state-of-the-art accuracy for this peptide identification problem.

A Matter of Time: Faster Percolator Analysis via Efficient SVM Learning for Large-Scale Proteomics.

Percolator is an important tool for greatly improving the results of a database search and subsequent downstream analysis. Using support vector machines (SVMs), Percolator recalibrates peptide-spectrum matches based on the learned decision boundary between targets and decoys. To improve analysis time for large-scale data sets, we update Percolator's SVM learning engine through software and algorithmic optimizations rather than heuristic approaches that necessitate the careful study of their impact on learned parameters across different search settings and data sets.

Comprehensive statistical inference of the clonal structure of cancer from multiple biopsies.

A comprehensive characterization of tumor genetic heterogeneity is critical for understanding how cancers evolve and escape treatment. Although many algorithms have been developed for capturing tumor heterogeneity, they are designed for analyzing either a single type of genomic aberration or individual biopsies. Here we present THEMIS (Tumor Heterogeneity Extensible Modeling via an Integrative System), which allows for the joint analysis of different types of genomic aberrations from multiple biopsies taken from the same patient, using a dynamic graphical model.

Gradients of Generative Models for Improved Discriminative Analysis of Tandem Mass Spectra.

Tandem mass spectrometry () is a high-throughput technology used to identify the proteins in a complex biological sample, such as a drop of blood. A collection of spectra is generated at the output of the process, each spectrum of which is representative of a peptide (protein subsequence) present in the original complex sample. In this work, we leverage the log-likelihood gradients of generative models to improve the identification of such spectra.

Foster Care Dynamics and System Science: Implications for Research and Policy.

Although system is a word frequently invoked in discussions of foster care policy and practice, there have been few if any attempts by child welfare researchers to understand the ways in which the foster care system is a system. As a consequence, insights from system science have yet to be applied in meaningful ways to the problem of making foster care systems more effective. In this study, we draw on population biology to organize a study of admissions and discharges to foster care over a 15-year period.

Dynamic Bayesian Network for Accurate Detection of Peptides from Tandem Mass Spectra.

A central problem in mass spectrometry analysis involves identifying, for each observed tandem mass spectrum, the corresponding generating peptide. We present a dynamic Bayesian network (DBN) toolkit that addresses this problem by using a machine learning approach. At the heart of this toolkit is a DBN for Rapid Identification (DRIP), which can be trained from collections of high-confidence peptide-spectrum matches (PSMs).

Faster and more accurate graphical model identification of tandem mass spectra using trellises.

Unlabelled: Tandem mass spectrometry (MS/MS) is the dominant high throughput technology for identifying and quantifying proteins in complex biological samples. Analysis of the tens of thousands of fragmentation spectra produced by an MS/MS experiment begins by assigning to each observed spectrum the peptide that is hypothesized to be responsible for generating the spectrum. This assignment is typically done by searching each spectrum against a database of peptides.

Learning Peptide-Spectrum Alignment Models for Tandem Mass Spectrometry.

We present a peptide-spectrum alignment strategy that employs a dynamic Bayesian network (DBN) for the identification of spectra produced by tandem mass spectrometry (MS/MS). Our method is fundamentally generative in that it models peptide fragmentation in MS/MS as a physical process. The model traverses an observed MS/MS spectrum and a peptide-based theoretical spectrum to calculate the best alignment between the two spectra.

Spectrum Identification using a Dynamic Bayesian Network Model of Tandem Mass Spectra.

Shotgun proteomics is a high-throughput technology used to identify unknown proteins in a complex mixture. At the heart of this process is a prediction task, the , in which each fragmentation spectrum produced by a shotgun proteomics experiment must be mapped to the peptide (protein subsequence) which generated the spectrum. We propose a new algorithm for spectrum identification, based on dynamic Bayesian networks, which significantly out-performs the de-facto standard tools for this task: SEQUEST and Mascot.

Effects of different potato cropping system approaches and water management on soilborne diseases and soil microbial communities.

Four different potato cropping systems, designed to address specific management goals of soil conservation, soil improvement, disease suppression, and a status quo standard rotation control, were evaluated for their effects on soilborne diseases of potato and soil microbial community characteristics. The status quo system (SQ) consisted of barley underseeded with red clover followed by potato (2-year). The soil-conserving system (SC) featured an additional year of forage grass and reduced tillage (3-year, barley/timothy-timothy-potato).

Increased osteoblast adhesion on nanograined hydroxyapatite and tricalcium phosphate containing calcium titanate.

Depending on the coating method utilized and subsequent heat treatments (such as through the use of plasma-spray deposition), inter-diffusion of atomic species across titanium (Ti) and hydroxyapatite (HA) coatings may result. These events may lead to structural and compositional changes that consequently cause unanticipated HA phase transformations which may clearly influence the performance of an orthopedic implant. Thus, the objective of the present in vitro study was to compare the cytocompatibility properties of chemistries that may form at the Ti:HA interface, specifically HA, tricalcium phosphate (TCP), HA doped with Ti, and those containing calcium titanate (CaTiO(3)).

Study of an adaptive bolus chasing CT angiography.

To improve imaging quality and to reduce contrast dose and radiation exposure, an adaptive bolus chasing CT angiography was proposed so that the bolus peak position and the imaging aperture can be synchronized. The performance of the proposed adaptive bolus chasing CT angiography was experimentally evaluated based on the actual bolus dynamics. The experimental results show that the controlled table position and the bolus peak position were highly consistent.

Unsuccessful tissue plasminogen activator treatment of acute stroke caused by a calcific embolus.

Intravenous (IV) administration of tissue plasminogen activator (tPA) given to patients during acute cerebral ischemia according to National Institute of Neurological Disorders and Stroke (NINDS) guidelines improves clinical outcome by 11% to 14%. The success of IV tPA stroke therapy is dependent on several previously reported factors. The authors suggest that the presence of calcification within an embolus may represent an additional important factor.

Meningocele-induced positional syncope and retinal hemorrhage.

Meningocele is recognized as a rare, usually asymptomatic condition not associated with acute neurologic symptoms. We herein describe the case of a patient with a longstanding history of a lower back "mass" and recurrent syncope who became acutely unresponsive and developed bilateral retinal hemorrhages when she was placed in the supine position to undergo carotid sonography. MR imaging revealed a large, dorsal lumbar meningocele.

Mechanical and in vivo performance of hydroxyapatite implants with controlled architectures.

Internal architecture has a direct impact on the mechanical and biological behaviors of porous hydroxyapatite (HA) implant. However, traditional processing methods provide minimal control in this regard. To address the issue, we developed a new processing method combining image-based design and solid free-form fabrication.