The Stigma of Migraine

Background People who have a disease often experience stigma, a socially and culturally embedded process through which individuals experience stereotyping, devaluation, and discrimination. Stigma has great impact on quality of life, behavior, and life chances. We do not know whether or not migraine is stigmatizing. Methods We studied 123 episodic migraine patients, 123 chronic migraine patients, and 62 epilepsy patients in a clinical setting to investigate the extent to which stigma attaches to migraine, using epilepsy as a comparison. We used the stigma scale for chronic illness, a 24-item questionnaire suitable for studying chronic neurologic diseases, and various disease impact measures. Results Patients with chronic migraine had higher scores (54.0±20.2) on the stigma scale for chronic illness than either episodic migraine (41.7±14.8) or epilepsy patients (44.6±16.3) (p\u3c0.001). Subjects with migraine reported greater inability to work than epilepsy subjects. Stigma correlated most strongly with the mental component score of the short form of the medical outcomes health survey (SF-12), then with ability to work and migraine disability score for chronic and episodic migraine and the Liverpool impact on epilepsy scale for epilepsy. Analysis of covariance showed adjusted scores for the stigma scale for chronic illness were similar for chronic migraine (49.3; 95% confidence interval, 46.2 to 52.4) and epilepsy (46.5; 95% confidence interval, 41.6 to 51.6), and lower for episodic migraine (43.7; 95% confidence interval, 40.9 to 46.6). Ability to work was the strongest predictor of stigma as measured by the stigma scale for chronic illness. Conclusion In our model, adjusted stigma was similar for chronic migraine and epilepsy, which were greater than for episodic migraine. Stigma correlated most strongly with inability to work, and was greater for chronic migraine than epilepsy or episodic migraine because chronic migraine patients had less ability to work

A Potential Role for Drosophila Mucins in Development and Physiology

Vital vertebrate organs are protected from the external environment by a barrier that to a large extent consists of mucins. These proteins are characterized by poorly conserved repeated sequences that are rich in prolines and potentially glycosylated threonines and serines (PTS). We have now used the characteristics of the PTS repeat domain to identify Drosophila mucins in a simple bioinformatics approach. Searching the predicted protein database for proteins with at least 4 repeats and a high ST content, more than 30 mucin-like proteins were identified, ranging from 300–23000 amino acids in length. We find that Drosophila mucins are present at all stages of the fly life cycle, and that their transcripts localize to selective organs analogous to sites of vertebrate mucin expression. The results could allow for addressing basic questions about human mucin-related diseases in this model system. Additionally, many of the mucins are expressed in selective tissues during embryogenesis, thus revealing new potential functions for mucins as apical matrix components during organ morphogenesis

BOLD Temporal Dynamics of Rat Superior Colliculus and Lateral Geniculate Nucleus following Short Duration Visual Stimulation

Background: The superior colliculus (SC) and lateral geniculate nucleus (LGN) are important subcortical structures for vision. Much of our understanding of vision was obtained using invasive and small field of view (FOV) techniques. In this study, we use non-invasive, large FOV blood oxygenation level-dependent (BOLD) fMRI to measure the SC and LGN's response temporal dynamics following short duration (1 s) visual stimulation. Methodology/Principal Findings: Experiments are performed at 7 tesla on Sprague Dawley rats stimulated in one eye with flashing light. Gradient-echo and spin-echo sequences are used to provide complementary information. An anatomical image is acquired from one rat after injection of monocrystalline iron oxide nanoparticles (MION), a blood vessel contrast agent. BOLD responses are concentrated in the contralateral SC and LGN. The SC BOLD signal measured with gradient-echo rises to 50% of maximum amplitude (PEAK) 0.2±0.2 s before the LGN signal (p<0.05). The LGN signal returns to 50% of PEAK 1.4±1.2 s before the SC signal (p<0.05). These results indicate the SC signal rises faster than the LGN signal but settles slower. Spin-echo results support these findings. The post-MION image shows the SC and LGN lie beneath large blood vessels. This subcortical vasculature is similar to that in the cortex, which also lies beneath large vessels. The LGN lies closer to the large vessels than much of the SC. Conclusions/Significance: The differences in response timing between SC and LGN are very similar to those between deep and shallow cortical layers following electrical stimulation, which are related to depth-dependent blood vessel dilation rates. This combined with the similarities in vasculature between subcortex and cortex suggest the SC and LGN timing differences are also related to depth-dependent dilation rates. This study shows for the first time that BOLD responses in the rat SC and LGN following short duration visual stimulation are temporally different. © 2011 Lau et al

The Consensus Molecular Subtypes of Colorectal Cancer

Users may view, print, copy, and download text and data-mine the content in such documents, for the purposes of academic research, subject always to the full Conditions of use -- https://www.nature.com/authors/policies/license.html#termsColorectal cancer (CRC) is a frequently lethal disease with heterogeneous outcomes and drug responses. To resolve inconsistencies among the reported gene expression-based CRC classifications and facilitate clinical translation, we formed an international consortium dedicated to large-scale data sharing and analytics across expert groups. We show marked interconnectivity between six independent classification systems coalescing into four consensus molecular subtypes (CMS) with distinguishing features: CMS1 (MSI Immune, 14%), hypermutated, microsatellite unstable, strong immune activation; CMS2 (Canonical, 37%), epithelial, chromosomally unstable, marked WNT and MYC signaling activation; CMS3 (Metabolic, 13%), epithelial, evident metabolic dysregulation; and CMS4 (Mesenchymal, 23%), prominent transforming growth factor β activation, stromal invasion, and angiogenesis. Samples with mixed features (13%) possibly represent a transition phenotype or intra-tumoral heterogeneity. We consider the CMS groups the most robust classification system currently available for CRC - with clear biological interpretability - and the basis for future clinical stratification and subtype-based targeted interventions

Retrospective evaluation of whole exome and genome mutation calls in 746 cancer samples

Funder: NCI U24CA211006Abstract: The Cancer Genome Atlas (TCGA) and International Cancer Genome Consortium (ICGC) curated consensus somatic mutation calls using whole exome sequencing (WES) and whole genome sequencing (WGS), respectively. Here, as part of the ICGC/TCGA Pan-Cancer Analysis of Whole Genomes (PCAWG) Consortium, which aggregated whole genome sequencing data from 2,658 cancers across 38 tumour types, we compare WES and WGS side-by-side from 746 TCGA samples, finding that ~80% of mutations overlap in covered exonic regions. We estimate that low variant allele fraction (VAF < 15%) and clonal heterogeneity contribute up to 68% of private WGS mutations and 71% of private WES mutations. We observe that ~30% of private WGS mutations trace to mutations identified by a single variant caller in WES consensus efforts. WGS captures both ~50% more variation in exonic regions and un-observed mutations in loci with variable GC-content. Together, our analysis highlights technological divergences between two reproducible somatic variant detection efforts

Correlations Between Scales.

<p>2-tailed Pearson correlation coefficients for variables associated with episodic (<b>A</b>) and chronic (<b>B</b>) migraine, and for epilepsy (<b>C</b>). The p-values are not adjusted for multiple comparisons.</p><p><b><u>Abbreviations:</u></b> SCCI = stigma scale for chronic illness; SSCI-I = internalized stigma; SSCI-E = enacted stigma; PCS = physical component subscale of SF-12; MCS = mental component subscale of SF-12; MIDAS = migraine disability scale.</p

Measurements of Stigma, Quality of Life, and Impact.

*<p>ANOVA, Bonferroni correction for multiple comparisons;</p>†<p>Mann-Whitney. Headache severity and frequency based on MIDAS questions 6 and 7.</p><p><b><u>Abbreviations:</u></b> SCCI = stigma scale for chronic illness; SSCI-I = internalized stigma; SSCI-E = enacted stigma; SF-12 = short form 12 in the medical outcomes study Quality of Life questionnaire; PCS = physical component subscale of SF-12; MCS = mental component subscale of SF-12; MIDAS = migraine disability scale; Liverpool impact scale = component of the Liverpool seizure severity scale.</p

Basic Demographics.

*<p> = ANOVA;</p>**<p>multiple comparisons with Bonferroni adjustment.</p><p>° = Chi Square test.</p>†<p> = Kruskal-Wallis;</p>††<p> = Mann-Whitney.</p

Effect on Need to Rest.

<p>Distribution of answers to questionnaire on the effect of migraine on need to rest and spending time in bed. Subjects with chronic migraine reported spending more time in bed and resting (p<0.001, Krushal-Wallis test).</p

Stigma Scores.

<p>Distribution of stigma scores for EM, CM, and Ep. Scores for CM are significantly higher than for EM or Ep. CM scores were higher than SSCI scores of 42.7+/−19.7 for an internet panel of diverse neurological patients used to validate the SSCI (p<0.001, z-test), while EM and Ep were not.</p