Glioma IL13Rα2 Is Associated with Mesenchymal Signature Gene Expression and Poor Patient Prognosis

A major challenge for successful immunotherapy against glioma is the identification and characterization of validated targets. We have taken a bioinformatics approach towards understanding the biological context of IL-13 receptor α2 (IL13Rα2) expression in brain tumors, and its functional significance for patient survival. Querying multiple gene expression databases, we show that IL13Rα2 expression increases with glioma malignancy grade, and expression for high-grade tumors is bimodal, with approximately 58% of WHO grade IV gliomas over-expressing this receptor. By several measures, IL13Rα2 expression in patient samples and low-passage primary glioma lines most consistently correlates with the expression of signature genes defining mesenchymal subclass tumors and negatively correlates with proneural signature genes as defined by two studies. Positive associations were also noted with proliferative signature genes, whereas no consistent associations were found with either classical or neural signature genes. Probing the potential functional consequences of this mesenchymal association through IPA analysis suggests that IL13Rα2 expression is associated with activation of proinflammatory and immune pathways characteristic of mesenchymal subclass tumors. In addition, survival analyses indicate that IL13Rα2 over-expression is associated with poor patient prognosis, a single gene correlation ranking IL13Rα2 in the top ~1% of total gene expression probes with regard to survival association with WHO IV gliomas. This study better defines the functional consequences of IL13Rα2 expression by demonstrating association with mesenchymal signature gene expression and poor patient prognosis. It thus highlights the utility of IL13Rα2 as a therapeutic target, and helps define patient populations most likely to respond to immunotherapy in present and future clinical trials.     

Prospective study of bacterial meningitis in North East Thames region, 1991-3, during introduction of Haemophilus influenzae vaccine.

OBJECTIVE--To describe the epidemiology of primary bacterial meningitis in the North East Thames region over a three year period before and during the introduction of the vaccine for Haemophilus influenzae type b. DESIGN--Analysis of information on cases of primary bacterial meningitis identified by microbiology laboratories in the region, with collection of case data by questionnaire. MAIN OUTCOME MEASURES--Annual incidence rates for types of meningitis according to age and ethnic group. RESULTS--The annual incidence rates for the three major causes of bacterial meningitis in the general population were 1.9/100,000 for Neisseria meningitidis, 1.6/100,000 for Haemophilus influenzae before vaccination, and 1.0/100,000 for Streptococcus pneumoniae. Higher rates of H influenzae meningitis were found in Asians compared with white people (3.6/100,000 v 1.5/100,000, P = 0.01). As a result of the vaccine programme introduced in October 1992 the number of cases of H influenzae meningitis in children under 5 years has fallen by 87%. CONCLUSIONS--Bacterial meningitis is a serious problem especially in preschool children. There are differences in the incidence of some causes of bacterial meningitis in different ethnic groups; with H influenzae type b being significantly more common among black and Asian people than among white people. The immunisation programme for H influenzae type b in the North East Thames region has been successful in reducing the incidence of this type of meningitis in Asian and white populations. The numbers were too small to evaluate in the black population.     

Denaturing Reversed-Phase HPLC Using a Mobile Phase Containing Urea for Oligodeoxynucleotide Analysis

Denaturing reversed-phase (RP) high performance liquid chromatography (HPLC) is usually achieved by elevating column temperature. In this article, an alternative method involving using a mobile phase that contains urea and performing HPLC at room temperature is described. The efficacy of the new method was demonstrated by analyzing a 61-mer oligodeoxynucleotide (ODN) and double-stranded (ds) ODNs. The multiple peaks of the 61-mer ODN under normal conditions merged into one under the denaturing conditions. The broad single peaks of dsODNs under normal conditions were split into two sharp peaks.     

Genome‐wide detection of CNVs associated with beak deformity in chickens using high‐density 600K SNP arrays

Beak deformity (crossed beaks) is found in several indigenous chicken breeds including Beijing‐You studied here. Birds with deformed beaks have reduced feed intake and poor production performance. Recently, copy number variation (CNV) has been examined in many species and is recognized as a source of genetic variation, especially for disease phenotypes. In this study, to unravel the genetic mechanisms underlying beak deformity, we performed genome‐wide CNV detection using Affymetrix chicken high‐density 600K data on 48 deformed‐beak and 48 normal birds using penncnv . As a result, two and eight CNV regions (CNVRs) covering 0.32 and 2.45 Mb respectively on autosomes were identified in deformed‐beak and normal birds respectively. Further RT‐qPCR studies validated nine of the 10 CNVRs. The ratios of six CNVRs were significantly different between deformed‐beak and normal birds (P < 0.01). Within these six regions, three and 21 known genes were identified in deformed‐beak and normal birds respectively. Bioinformatics analysis showed that these genes were enriched in six GO terms and one KEGG pathway. Five candidate genes in the CNVRs were further validated using RT‐qPCR. The expression of LRIG2 (leucine rich repeats and immunoglobulin like domains 2) was lower in birds with deformed beaks (P < 0.01). Therefore, the LRIG2 gene could be considered a key factor in view of its known functions and its potential roles in beak deformity. Overall, our results will be helpful for future investigations of the genomic structural variations underlying beak deformity in chickens.     

The Optimal Solution of a Non-Convex State-Dependent LQR Problem and Its Applications

This paper studies a Non-convex State-dependent Linear Quadratic Regulator (NSLQR) problem, in which the control penalty weighting matrix in the performance index is state-dependent. A necessary and sufficient condition for the optimal solution is established with a rigorous proof by Euler-Lagrange Equation. It is found that the optimal solution of the NSLQR problem can be obtained by solving a Pseudo-Differential-Riccati-Equation (PDRE) simultaneously with the closed-loop system equation. A Comparison Theorem for the PDRE is given to facilitate solution methods for the PDRE. A linear time-variant system is employed as an example in simulation to verify the proposed optimal solution. As a non-trivial application, a goal pursuit process in psychology is modeled as a NSLQR problem and two typical goal pursuit behaviors found in human and animals are reproduced using different control weighting . It is found that these two behaviors save control energy and cause less stress over Conventional Control Behavior typified by the LQR control with a constant control weighting , in situations where only the goal discrepancy at the terminal time is of concern, such as in Marathon races and target hitting missions.