Eye position modulates retinotopic responses in early visual areas: a bias for the straight-ahead direction

Even though the eyes constantly change position, the location of a stimulus can be accurately represented by a population of neurons with retinotopic receptive fields modulated by eye position gain fields. Recent electrophysiological studies, however, indicate that eye position gain fields may serve an additional function since they have a non-uniform spatial distribution that increases the neural response to stimuli in the straight-ahead direction. We used functional magnetic resonance imaging and a wide-field stimulus display to determine whether gaze modulations in early human visual cortex enhance the blood-oxygenation-level dependent (BOLD) response to stimuli that are straight-ahead. Subjects viewed rotating polar angle wedge stimuli centered straight-ahead or vertically displaced by ±20° eccentricity. Gaze position did not affect the topography of polar phase-angle maps, confirming that coding was retinotopic, but did affect the amplitude of the BOLD response, consistent with a gain field. In agreement with recent electrophysiological studies, BOLD responses in V1 and V2 to a wedge stimulus at a fixed retinal locus decreased when the wedge location in head-centered coordinates was farther from the straight-ahead direction. We conclude that stimulus-evoked BOLD signals are modulated by a systematic, non-uniform distribution of eye-position gain fields

B cells in the formation of Tertiary Lymphoid Organs in autoimmunity, transplantation and tumorigenesis.

TLS develop in target organs of autoimmune diseases, transplantation and cancer. • TLS can function as germinal centres supporting B-cell selection/differentiation. • TLS can be destructive or have beneficial effects at the site of inflammation/disease. • Therapeutic targeting of TLS results in beneficial effects in patients, though inhibition may lead to immune suppression while stimulation may lead to autoimmunity. Tertiary lymphoid organs named also tertiary lymphoid structures (TLS) often occur at sites of autoimmune inflammation, organ transplantation and cancer. Although the mechanisms for their formation/function are not entirely understood, it is known that TLS can display features of active germinal centres supporting the proliferation and differentiation of (auto)-reactive B cells. In this Review, we discuss current knowledge on TLS-associated B cells with particular reference on how within diseased tissues these structures are linked to either deleterious or protective outcomes in patients and the potential for therapeutic targeting of TLS through novel drugs

Activation of WNT and BMP signaling in adult human articular cartilage following mechanical injury

Peer reviewedPublisher PD

Spectrum: Fast density-aware spectral clustering for single and multi-omic data

Abstract Clustering of single or multi-omic data is key to developing personalised medicine and identifying new cell types. We present Spectrum, a fast spectral clustering method for single and multi-omic expression data. Spectrum is flexible and performs well on single-cell RNA-seq data. The method uses a new density-aware kernel that adapts to data scale and density. It uses a tensor product graph data integration and diffusion technique to reveal underlying structures and reduce noise. We developed a powerful method of eigenvector analysis to determine the number of clusters. Benchmarking Spectrum on 21 datasets demonstrated improvements in runtime and performance relative to other state-of-the-art methods. Contact: [email protected]

M3C: Monte Carlo reference-based consensus clustering.

Genome-wide data is used to stratify patients into classes for precision medicine using clustering algorithms. A common problem in this area is selection of the number of clusters (K). The Monti consensus clustering algorithm is a widely used method which uses stability selection to estimate K. However, the method has bias towards higher values of K and yields high numbers of false positives. As a solution, we developed Monte Carlo reference-based consensus clustering (M3C), which is based on this algorithm. M3C simulates null distributions of stability scores for a range of K values thus enabling a comparison with real data to remove bias and statistically test for the presence of structure. M3C corrects the inherent bias of consensus clustering as demonstrated on simulated and real expression data from The Cancer Genome Atlas (TCGA). For testing M3C, we developed clusterlab, a new method for simulating multivariate Gaussian clusters

Targeted delivery of anti-inflammatory therapy to rheumatoid tissue by fusion proteins containing an IL-4-linked synovial targeting peptide

We provide first-time evidence that the synovial endothelium-targeting peptide (SyETP) CKSTHDRLC successfully delivers conjugated IL-4 to human rheumatoid synovium transplanted into SCID mice. SyETP, previously isolated by in vivo phage display and shown to preferentially localize to synovial xenografts, was linked by recombinant technology to hIL-4 via an MMP-cleavable sequence. Both IL-4 and the MMP-cleavable sequence were shown to be functional. IL-4-SyETP augmented production of IL-1ra by synoviocytes stimulated with IL-1[beta] in a dose-dependent manner. In vivo imaging confirmed increased retention of SyETP-linked-IL-4 in synovial grafts which was enhanced by increasing number of copies (one to three) in the constructs. Strikingly, SyETP delivered bioactive IL-4 in vivo as demonstrated by increased pSTAT6 in synovial grafts. Thus, this study provides proof of concept for peptide-tissue-specific targeted immunotherapy in rheumatoid arthritis. This technology is potentially applicable to other biological therapies providing enhanced potency to inflammatory sites and reducing systemic toxicity

M3C: Monte Carlo reference-based consensus clustering

Genome-wide data is used to stratify patients into classes for precision medicine using clustering algorithms. A common problem in this area is selection of the number of clusters (K). The Monti consensus clustering algorithm is a widely used method which uses stability selection to estimate K. However, the method has bias towards higher values of K and yields high numbers of false positives. As a solution, we developed Monte Carlo reference-based consensus clustering (M3C), which is based on this algorithm. M3C simulates null distributions of stability scores for a range of K values thus enabling a comparison with real data to remove bias and statistically test for the presence of structure. M3C corrects the inherent bias of consensus clustering as demonstrated on simulated and real expression data from The Cancer Genome Atlas (TCGA). For testing M3C, we developed clusterlab, a new method for simulating multivariate Gaussian clusters

Single cell cloning and recombinant monoclonal antibodies generation from RA synovial B cells reveal frequent targeting of citrullinated histones of NETs

This work was funded by research grants from Arthritis Research UK (grant 20089 to MB; grant 20858 to ECo; Arthritis Research UK Experimental Arthritis Treatment Centre - grant 20022 to CP) and the William Harvey Research Foundation (WHRF grant 2011–2013 to MB); Elisa Corsiero was recipient of short-term travel fellowships from EMBO (ASTF 318-2010 and ASTF 102-2013