Citations

AbstractPhakomatous choristoma (PC) is a rare benign congenital lesion of lenticular anlage. It presents in young patients as a firm subcutaneous mass in the medial eyelid or orbit and may raise clinical concern for neoplasms such as rhabdomyosarcoma, but its histopathology is distinct, consisting of dense collagenous stroma and eosinophilic cuboidal epithelial cells forming nests, tubules, cords, or pseudoglands. We present a case of PC in a 10‐week‐old boy to illustrate the unique clinical, histopathologic, and immunophenotypic features of this condition and to reaffirm that familiarity with this rare entity aids accurate diagnosis.

AbstractBackgroundLate‐onset Alzheimer's disease (AD) is heritable with 20 genes showing genome‐wide association in the International Genomics of Alzheimer's Project (IGAP). To identify the biology underlying the disease, we extended these genetic data in a pathway analysis.MethodsThe ALIGATOR and GSEA algorithms were used in the IGAP data to identify associated functional pathways and correlated gene expression networks in human brain.ResultsALIGATOR identified an excess of curated biological pathways showing enrichment of association. Enriched areas of biology included the immune response (P = 3.27 × 10−12 after multiple testing correction for pathways), regulation of endocytosis (P = 1.31 × 10−11), cholesterol transport (P = 2.96 × 10−9), and proteasome‐ubiquitin activity (P = 1.34 × 10−6). Correlated gene expression analysis identified four significant network modules, all related to the immune response (corrected P = .002–.05).ConclusionsThe immune response, regulation of endocytosis, cholesterol transport, and protein ubiquitination represent prime targets for AD therapeutics.

ABSTRACTPURPOSETo determine interobserver spatial variability in language area localization using three commonly employed language tasks.MATERIALS AND METHODSWith institutional review board approval, 125 fMRI time series from 50 different clinical language cases were retrospectively reviewed by three blinded readers who selected 3‐dimensional points representing the perceived center of Wernicke's and Broca's areas using three language tasks (semantic decision, SD; sentence comprehension, SC; and silent word generation, WG). Point dispersion values were then calculated using the perimeter of the 3‐dimensional triangle defined by the three readers’ selections.RESULTSAfter resolving interobserver laterality disagreements, there was no difference in spatial variability between the three tasks (P = .069). The SD task had the fewest interobserver laterality disagreements (P = .028) and the SC task had fewer failed localizations for Broca's area (P = .050) and Wernicke's area (P = .013).CONCLUSIONWhile there were no differences between interobserver spatial variability in language area localization between the three tasks, language task choice impacts the accuracy of fMRI language area identification because tasks vary in their rates of interobserver laterality disagreements and failed localizations. A combination of tasks including one with low laterality disagreements (eg, SD) and one with few failed localizations (eg, SC) may offer the best combination.

Key Points High-throughput RNAi screening identified lenalidomide sensitizer genes, including RSK2, RAB, peroxisome, and potassium channel family members. Knockdown or inhibition of RSK2 synergized with lenalidomide to induce myeloma cytotoxicity and downregulation of interferon regulatory factor 4 and MYC.

Background and Purpose— NINDS (National Institute of Neurological Disorders and Stroke)-SiGN (Stroke Genetics Network) is an international consortium of ischemic stroke studies that aims to generate high-quality phenotype data to identify the genetic basis of pathogenic stroke subtypes. This analysis characterizes the etiopathogenetic basis of ischemic stroke and reliability of stroke classification in the consortium. Methods— Fifty-two trained and certified adjudicators determined both phenotypic (abnormal test findings categorized in major pathogenic groups without weighting toward the most likely cause) and causative ischemic stroke subtypes in 16 954 subjects with imaging-confirmed ischemic stroke from 12 US studies and 11 studies from 8 European countries using the web-based Causative Classification of Stroke System. Classification reliability was assessed with blinded readjudication of 1509 randomly selected cases. Results— The distribution of pathogenic categories varied by study, age, sex, and race ( P <0.001 for each). Overall, only 40% to 54% of cases with a given major ischemic stroke pathogenesis (phenotypic subtype) were classified into the same final causative category with high confidence. There was good agreement for both causative (κ 0.72; 95% confidence interval, 0.69–0.75) and phenotypic classifications (κ 0.73; 95% confidence interval, 0.70–0.75). Conclusions— This study demonstrates that pathogenic subtypes can be determined with good reliability in studies that include investigators with different expertise and background, institutions with different stroke evaluation protocols and geographic location, and patient populations with different epidemiological characteristics. The discordance between phenotypic and causative stroke subtypes highlights the fact that the presence of an abnormality in a patient with stroke does not necessarily mean that it is the cause of stroke.