Rheumatoid meningitis sine arthritis.

Rheumatoid meningitis is a rare and very serious extra-articular manifestation of rheumatoid arthritis. We present a case of a 7()year-old female with no history of arthritis who developed stroke-like symptoms, seizures, psychosis and compulsive behavior. Serial brain magnetic resonance images (MRI) over four months demonstrated progressive interhemispheric meningeal thickening. She had mild lymphocytic pleocytosis on the cerebrospinal fluid analysis and serum anti-cyclic citrullinated peptide antibodies resulted positive in high titers. She underwent a brain biopsy showing necrotizing granulomas consistent with rheumatoid meningitis. Her symptoms resolved with treatment with glucocorticoids and cyclophosphamide. She has not been diagnosed with rheumatoid arthritis even after 1 year of follow up. Clinicians should be aware of the possibility of rheumatoid meningitis without rheumatoid arthritis and keep it on the differential for patients with aseptic meningitis and otherwise negative work up

Amygdalar function reflects common individual differences in emotion and pain regulation success

Although the co-occurrence of negative affect and pain is well recognized, the mechanism underlying their association is unclear. To examine whether a common self-regulatory ability impacts the experience of both emotion and pain, we integrated neuroimaging, behavioral, and physiological measures obtained from three assessments separated by substantial temporal intervals. Out results demonstrated that individual differences in emotion regulation ability, as indexed by an objective measure of emotional state, corrugator electromyography, predicted self-reported success while regulating pain. In both emotion and pain paradigms, the amygdala reflected regulatory success. Notably, we found that greater emotion regulation success was associated with greater change of amygdalar activity following pain regulation. Furthermore, individual differences in degree of amygdalar change following emotion regulation were a strong predictor of pain regulation success, as well as of the degree of amygdalar engagement following pain regulation. These findings suggest that common individual differences in emotion and pain regulatory success are reflected in a neural structure known to contribute to appraisal processes

Diophantine approximation on manifolds and lower bounds for Hausdorff dimension

Given $n\in\mathbb{N}$ and $\tau>\frac1n$, let $\mathcal{S}_n(\tau)$ denote the classical set of $\tau$-approximable points in $\mathbb{R}^n$, which consists of ${\bf x}\in \mathbb{R}^n$ that lie within distance $q^{-\tau-1}$ from the lattice $\frac1q\mathbb{Z}^n$ for infinitely many $q\in\mathbb{N}$. In pioneering work, Kleinbock $\&$ Margulis showed that for any non-degenerate submanifold $\mathcal{M}$ of $\mathbb{R}^n$ and any $\tau>\frac1n$ almost all points on $\mathcal{M}$ are not $\tau$-approximable. Numerous subsequent papers have been geared towards strengthening this result through investigating the Hausdorff measure and dimension of the associated null set $\mathcal{M}\cap\mathcal{S}_n(\tau)$. In this paper we suggest a new approach based on the Mass Transference Principle, which enables us to find a sharp lower bound for $\dim \mathcal{M}\cap\mathcal{S}_n(\tau)$ for any $C^2$ submanifold $\mathcal{M}$ of $\mathbb{R}^n$ and any $\tau$ satisfying $\frac1n\le\tau<\frac1m$. Here $m$ is the codimension of $\mathcal{M}$. We also show that the condition on $\tau$ is best possible and extend the result to general approximating functions.Comment: 20 page

PhyloScan: identification of transcription factor binding sites using cross-species evidence

BACKGROUND: When transcription factor binding sites are known for a particular transcription factor, it is possible to construct a motif model that can be used to scan sequences for additional sites. However, few statistically significant sites are revealed when a transcription factor binding site motif model is used to scan a genome-scale database. METHODS: We have developed a scanning algorithm, PhyloScan, which combines evidence from matching sites found in orthologous data from several related species with evidence from multiple sites within an intergenic region, to better detect regulons. The orthologous sequence data may be multiply aligned, unaligned, or a combination of aligned and unaligned. In aligned data, PhyloScan statistically accounts for the phylogenetic dependence of the species contributing data to the alignment and, in unaligned data, the evidence for sites is combined assuming phylogenetic independence of the species. The statistical significance of the gene predictions is calculated directly, without employing training sets. RESULTS: In a test of our methodology on synthetic data modeled on seven Enterobacteriales, four Vibrionales, and three Pasteurellales species, PhyloScan produces better sensitivity and specificity than MONKEY, an advanced scanning approach that also searches a genome for transcription factor binding sites using phylogenetic information. The application of the algorithm to real sequence data from seven Enterobacteriales species identifies novel Crp and PurR transcription factor binding sites, thus providing several new potential sites for these transcription factors. These sites enable targeted experimental validation and thus further delineation of the Crp and PurR regulons in E. coli. CONCLUSION: Better sensitivity and specificity can be achieved through a combination of (1) using mixed alignable and non-alignable sequence data and (2) combining evidence from multiple sites within an intergenic region

Reconstructing the Regulatory Kinase Pathways of Myogenesis from Phosphopeptide Data

Multiple kinase activities are required for skeletal muscle differentiation. However, the mechanisms by which these kinase pathways converge to coordinate the myogenic process are unknown. Using multiple phosphoprotein and phosphopeptide enrichment techniques we obtained phosphopeptides from growing and differentiating C2C12 muscle cells and determined specific peptide sequences using LC-MS/MS. To place these phosphopeptides into a rational context, a bioinformatics approach was used. Phosphorylation sites were matched to known site-specific and to site non-specific kinase-substrate interactions, and then other substrates and upstream regulators of the implicated kinases were incorporated into a model network of protein-protein interactions. The model network implicated several kinases of known relevance to myogenesis including AKT, GSK3, CDK5, p38, DYRK, and MAPKAPK2 kinases. This combination of proteomics and bioinformatics technologies should offer great utility as the volume of protein-protein and kinase-substrate information continues to increase

White Matter Abnormalities in Patients with Treatment-Resistant Genetic Generalized Epilepsies.

BACKGROUND Genetic generalized epilepsies (GGEs) are associated with microstructural brain abnormalities that can be evaluated with diffusion tensor imaging (DTI). Available studies on GGEs have conflicting results. Our primary goal was to compare the white matter structure in a cohort of patients with video/EEG-confirmed GGEs to healthy controls (HCs). Our secondary goal was to assess the potential effect of age at GGE onset on the white matter structure. MATERIAL AND METHODS A convenience sample of 23 patients with well-characterized treatment-resistant GGEs (13 female) was compared to 23 HCs. All participants received MRI at 3T. DTI indices, including fractional anisotropy (FA) and mean diffusivity (MD), were compared between groups using Tract-Based Spatial Statistics (TBSS). RESULTS After controlling for differences between groups, abnormalities in DTI parameters were observed in patients with GGEs, including decreases in functional anisotropy (FA) in the hemispheric (left&gt;right) and brain stem white matter. The examination of the effect of age at GGE onset on the white matter integrity revealed a significant negative correlation in the left parietal white matter region FA (R=-0.504; p=0.017); similar trends were observed in the white matter underlying left motor cortex (R=-0.357; p=0.103) and left posterior limb of the internal capsule (R=-0.319; p=0.148). CONCLUSIONS Our study confirms the presence of widespread white matter abnormalities in patients with GGEs and provides evidence that the age at GGE onset may have an important effect on white matter integrity

Automatic Extraction of Protein Point Mutations Using a Graph Bigram Association

Protein point mutations are an essential component of the evolutionary and experimental analysis of protein structure and function. While many manually curated databases attempt to index point mutations, most experimentally generated point mutations and the biological impacts of the changes are described in the peer-reviewed published literature. We describe an application, Mutation GraB (Graph Bigram), that identifies, extracts, and verifies point mutations from biomedical literature. The principal problem of point mutation extraction is to link the point mutation with its associated protein and organism of origin. Our algorithm uses a graph-based bigram traversal to identify these relevant associations and exploits the Swiss-Prot protein database to verify this information. The graph bigram method is different from other models for point mutation extraction in that it incorporates frequency and positional data of all terms in an article to drive the point mutation–protein association. Our method was tested on 589 articles describing point mutations from the G protein–coupled receptor (GPCR), tyrosine kinase, and ion channel protein families. We evaluated our graph bigram metric against a word-proximity metric for term association on datasets of full-text literature in these three different protein families. Our testing shows that the graph bigram metric achieves a higher F-measure for the GPCRs (0.79 versus 0.76), protein tyrosine kinases (0.72 versus 0.69), and ion channel transporters (0.76 versus 0.74). Importantly, in situations where more than one protein can be assigned to a point mutation and disambiguation is required, the graph bigram metric achieves a precision of 0.84 compared with the word distance metric precision of 0.73. We believe the graph bigram search metric to be a significant improvement over previous search metrics for point mutation extraction and to be applicable to text-mining application requiring the association of words

Impacts of Health Information Exchange and Health Information Organization on Hospital Efficiency: A Data Envelopment Analysis

This paper aimed to determine if hospitals that participated in Health Information Exchange (HIE) and Health Information Organization (HIO) were more efficient than hospitals that did not participate. This study collected sample data from the 2017 American Hospital Association (AHA) U.S. Hospital Annual Survey dataset and the 2017 AHA IT Survey dataset. We created a DEA model to measure hospital efficiencies. Mann-Whitney Test performed the hypothesis test. Evidence showed that HIE/HIO participating hospital group had a significantly higher efficiency score than the non-participating hospital group