Humboldt University of Berlin

About: Humboldt University of Berlin is a education organization based out in Berlin, Germany. It is known for research contribution in the topics: Population & Transplantation. The organization has 33671 authors who have published 61781 publications receiving 1908102 citations. The organization is also known as: Humboldt-Universität zu Berlin & Universitas Humboldtiana Berolinensis.

Gene expression-based classification of malignant gliomas correlates better with survival than histological classification.

Abstract: In modern clinical neuro-oncology, histopathological diagnosis affects therapeutic decisions and prognostic estimation more than any other variable. Among high-grade gliomas, histologically classic glioblastomas and anaplastic oligodendrogliomas follow markedly different clinical courses. Unfortunately, many malignant gliomas are diagnostically challenging; these nonclassic lesions are difficult to classify by histological features, generating considerable interobserver variability and limited diagnostic reproducibility. The resulting tentative pathological diagnoses create significant clinical confusion. We investigated whether gene expression profiling, coupled with class prediction methodology, could be used to classify high-grade gliomas in a manner more objective, explicit, and consistent than standard pathology. Microarray analysis was used to determine the expression of ∼12,000 genes in a set of 50 gliomas, 28 glioblastomas and 22 anaplastic oligodendrogliomas. Supervised learning approaches were used to build a two-class prediction model based on a subset of 14 glioblastomas and 7 anaplastic oligodendrogliomas with classic histology. A 20-feature k -nearest neighbor model correctly classified 18 of the 21 classic cases in leave-one-out cross-validation when compared with pathological diagnoses. This model was then used to predict the classification of clinically common, histologically nonclassic samples. When tumors were classified according to pathology, the survival of patients with nonclassic glioblastoma and nonclassic anaplastic oligodendroglioma was not significantly different ( P = 0.19). However, class distinctions according to the model were significantly associated with survival outcome ( P = 0.05). This class prediction model was capable of classifying high-grade, nonclassic glial tumors objectively and reproducibly. Moreover, the model provided a more accurate predictor of prognosis in these nonclassic lesions than did pathological classification. These data suggest that class prediction models, based on defined molecular profiles, classify diagnostically challenging malignant gliomas in a manner that better correlates with clinical outcome than does standard pathology.

The Topological Vertex

Abstract: We construct a cubic field theory which provides all genus amplitudes of the topological A-model for all non-compact toric Calabi-Yau threefolds. The topology of a given Feynman diagram encodes the topology of a fixed Calabi-Yau, with Schwinger parameters playing the role of Kahler classes of the threefold. We interpret this result as an operatorial computation of the amplitudes in the B-model mirror which is the quantum Kodaira-Spencer theory. The only degree of freedom of this theory is an unconventional chiral scalar on a Riemann surface. In this setup we identify the B-branes on the mirror Riemann surface as fermions related to the chiral boson by bosonization.

The Resting Brain: Unconstrained yet Reliable

Abstract: Recent years have witnessed an upsurge in the usage of resting-state functional magnetic resonance imaging (fMRI) to examine functional connectivity (fcMRI), both in normal and pathological populations. Despite this increasing popularity, concerns about the psychologically unconstrained nature of the “resting-state” remain. Across studies, the patterns of functional connectivity detected are remarkably consistent. However, the test–retest reliability for measures of resting state fcMRI measures has not been determined. Here, we quantify the test–retest reliability, using resting scans from 26 participants at 3 different time points. Specifically, we assessed intersession (>5 months apart), intrasession ( nonsignificant), 2) correlation valence (positive > negative), and 3) network membership (default mode > task positive network). Short- and long-term measures of the consistency of global connectivity patterns were highly robust. Finally, hierarchical clustering solutions were highly reproducible, both across participants and sessions. Our findings provide a solid foundation for continued examination of resting state fcMRI in typical and atypical populations.

Prevalence of spondylarthropathies in HLA‐B27 positive and negative blood donors

Abstract: Objective To determine the overall prevalence of spondylarthropathy (SpA) among whites. Methods To screen for SpA symptoms, such as inflammatory back pain (IBP), joint swelling, psoriasis, and uveitis, or a specific family history, questionnaires were mailed to 348 blood donors (174 HLA-B27 positive and 174 HLA-B27 negative). From the responding 273 persons (78%; 140 B27 positive, 133 B27 negative), 126 were selected for further evaluation based on the symptoms reported. Of this group, 90 persons agreed to undergo physical examination (71.4%; 46 B27 positive, 44 B27 negative). There was no difference between the B27-positive and -negative groups in terms of age (mean ± SD 38.4 ± 10 versus 39.5 ± 11 years) and sex ratio (67% versus 68% were men). In addition, 58 donors (32 B27 positive, 26 B27 negative) agreed to undergo magnetic resonance imaging (MRI) of the sacroiliac joints. A diagnosis of SpA and ankylosing spondylitis (AS) was made according to the European Spondylarthropathy Study Group criteria and the New York criteria. Results SpA was diagnosed in 20 persons: 19 of 140 B27-positive (13.6%) and 1 of 133 B27-negative (0.7%) subjects (15 male and 5 female). AS was diagnosed in 9 persons (7 male and 2 female; 45%), undifferentiated SpA (USpA) in 7 (5 male and 2 female; 35%), psoriatic arthritis (PsA) in 3 (2 male and 1 female; 15%), and chronic reactive arthritis (ReA; Reiter's syndrome) in 1 (male; 5%). On the basis of a B27 frequency of 9.3% among the population of Berlin (3.47 million persons), the estimated prevalence of SpA was 1.9%, AS was 0.86%, USpA was 0.67%, and PsA was 0.29%. The relative risk of developing SpA in B27-positive subjects was calculated as 20.7 (95% confidence interval 4.6-94.2; P = 0.001). Of 58 persons with IBP, sacroiliitis was detected by MRI in 15 of 32 B27-positive (46.9%) and 1 of 26 B27-negative (3.9%) subjects (P = 0.002). Four of these 16 donors did not fulfill diagnostic criteria for SpA. Conclusion With a calculated prevalence of 1.9%, spondylarthropathies are among the most frequent rheumatic diseases in the white population. HLA-B27 positive persons carry a 20-fold increased risk of developing SpA. AS and USpA are the most frequent SpA subtypes. Persons with IBP who are B27 positive have a 50% likelihood of having sacroiliitis.