The relationship between Higher Education and labour market in Greece : the weakest link?

The high level of graduate unemployment, even though it is acknowledged as one of the most distinctive characteristics of the Greek labour market, it has not attracted enough attention in the academic literature. This paper utilizes micro-data from the Labour Force Survey in order to investigate how the employment situation of young (aged 35 and below) graduates varies across fields of study. The findings suggest that graduates of disciplines that have high levels of private sector employment, such as Polytechnics and Computer Science, are in general better off in the Greek labour market. On the other hand, graduates of disciplines that are traditionally related to the needs of the public sector, such as Sociology and Humanities, face poor employment prospects. The findings of this study highlight the need for drastic reforms of the Higher Education system

Projected tt-SNE for batch correction

Biomedical research often produces high-dimensional data confounded by batch effects such as systematic experimental variations, different protocols and subject identifiers. Without proper correction, low-dimensional representation of high-dimensional data might encode and reproduce the same systematic variations observed in the original data, and compromise the interpretation of the results. In this article, we propose a novel procedure to remove batch effects from low-dimensional embeddings obtained with t-SNE dimensionality reduction. The proposed methods are based on linear algebra and constrained optimization, leading to efficient algorithms and fast computation in many high-dimensional settings. Results on artificial single-cell transcription profiling data show that the proposed procedure successfully removes multiple batch effects from t-SNE embeddings, while retaining fundamental information on cell types. When applied to single-cell gene expression data to investigate mouse medulloblastoma, the proposed method successfully removes batches related with mice identifiers and the date of the experiment, while preserving clusters of oligodendrocytes, astrocytes, and endothelial cells and microglia, which are expected to lie in the stroma within or adjacent to the tumors.Comment: 16 pages, 3 figure

Projected t-SNE for batch correction

Motivation: Low-dimensional representations of high-dimensional data are routinely employed in biomedical research to visualize, interpret and communicate results from different pipelines. In this article, we propose a novel procedure to directly estimate t-SNE embeddings that are not driven by batch effects. Without correction, interesting structure in the data can be obscured by batch effects. The proposed algorithm can therefore significantly aid visualization of high-dimensional data. Results: The proposed methods are based on linear algebra and constrained optimization, leading to efficient algorithms and fast computation in many high-dimensional settings. Results on artificial single-cell transcription profiling data show that the proposed procedure successfully removes multiple batch effects from t-SNE embeddings, while retaining fundamental information on cell types. When applied to single-cell gene expression data to investigate mouse medulloblastoma, the proposed method successfully removes batches related with mice identifiers and the date of the experiment, while preserving clusters of oligodendrocytes, astrocytes, and endothelial cells and microglia, which are expected to lie in the stroma within or adjacent to the tumours. Contact: [email protected]

Local and systemic glucocorticoid metabolism in inflammatory arthritis

Background: Isolated, primary synovial fibroblasts generate active glucocorticoids through expression of 11β-hydroxysteroid dehydrogenase type 1 (11β-HSD1). This enzyme produces cortisol from inactive cortisone (and prednisolone from prednisone). Objective: To determine how intact synovial tissue metabolises glucocorticoids and to identify the local and systemic consequences of this activity by examination of glucocorticoid metabolism in patients with rheumatoid arthritis (RA). Methods: Synovial tissue was taken from patients with RA during joint replacement surgery. Glucocorticoid metabolism in explants was assessed by thin-layer chromatography and specific enzyme inhibitors. RT-PCR and immunohistochemistry were used to determine expression and distribution of 11β-HSD enzymes. Systemic glucocorticoid metabolism was examined in patients with RA using gas chromatography/mass spectrometry. Results: Synovial tissue synthesised cortisol from cortisone, confirming functional 11β-HSD1 expression. In patients with RA, enzyme activity correlated with donor erythrocyte sedimentation rate (ESR). Synovial tissues could also convert cortisol back to cortisone. Inhibitor studies and immunohistochemistry suggested this was owing to 11β-HSD2 expression in synovial macrophages, whereas 11β-HSD1 expression occurred primarily in fibroblasts. Synovial fluids exhibited lower cortisone levels than matched serum samples, indicating net local steroid activation. Urinary analyses indicated high 11β-HSD1 activity in untreated patients with RA compared with controls and a significant correlation between total body 11β-HSD1 activity and ESR. Conclusions: Synovial tissue metabolises glucocorticoids, the predominant effect being glucocorticoid activation, and this increases with inflammation. Endogenous glucocorticoid production in the joint is likely to have an impact on local inflammation and bone integrity

Synergistic induction of local glucocorticoid generation by inflammatory cytokines and glucocorticoids: implications for inflammation associated bone loss

Objectives: Synovial fibroblasts and osteoblasts generate active glucocorticoids by means of the 11aβ-hydroxysteroid dehydrogenase type 1 (11aβ-HSD1) enzyme. This activity increases in response to proinflammatory cytokines or glucocorticoids. During inflammatory arthritis synovium and bone are exposed to both these factors. This study hypothesised that glucocorticoids magnify the effects of inflammatory cytokines on local glucocorticoid production in both synovium and bone. Methods: The effects of inflammatory cytokines (IL-1aβ/tumour necrosis factor alpha; TNFα) and glucocorticoids, alone or combined, were assessed on the expression and activity of 11β-HSD1 in primary synovial fibroblasts, primary human osteoblasts and MG-63 osteosarcoma cells. A range of other target genes and cell types were used to examine the specificity of effects. Functional consequences were assessed using IL-6 ELISA. Results: In synovial fibroblasts and osteoblasts, treatment with cytokines or glucocorticoids in isolation induced 11β-HSD1 expression and activity. However, in combination, 11β-HSD1 expression, activity and functional consequences were induced synergistically to a level not seen with isolated treatments. This effect was seen in normal skin fibroblasts but not foreskin fibroblasts or adipocytes and was only seen for the 11β-HSD1 gene. Synergistic induction had functional consequences on IL-6 production. Conclusions: Combined treatment with inflammatory cytokines and glucocorticoids synergistically induces 11aβ-HSD1 expression and activity in synovial fibroblasts and osteoblasts, providing a mechanism by which synovium and bone can interact to enhance anti-inflammatory responses by increasing localised glucocorticoid levels. However, the synergistic induction of 11β-HSD1 might also cause detrimental glucocorticoid accumulation in bone or surrounding tissues

Synovial tissue signatures enhance clinical classification and prognostic/treatment response algorithms in early inflammatory arthritis and predict requirement for subsequent biological therapy: results from the pathobiology of early arthritis cohort (PEAC)

Funding for PEAC MRC: Grant code 36661. Funding Infrastructure support to EMR, Arthritis Research UK Experimental Treatment Centre: Grant code 20022

Expression of FcRL4 defines a pro-inflammatory, RANKL-producing B cell subset in rheumatoid arthritis

OBJECTIVES: The success of B cell targeting therapies has highlighted the importance of B cells in rheumatoid arthritis pathogenesis. We have previously shown that B cells in the RA synovium are capable of producing pro-inflammatory and bone-destructive cytokines including RANKL. Here we sought to characterise the nature and functional relevance of the RANKL-producing B cell subset in the RA synovium. METHODS: Synovial fluid and peripheral blood B cells from patients with RA were analysed by flow cytometry for markers of B cell differentiation and activation and for chemokine receptors. FcRL4(+) and FcRL4(−) B cells sorted from synovial fluid were analysed for cytokine expression using Taqman low-density arrays. Synovial tissue biopsies obtained from patients with RA were analysed by immunofluorescence for CD20, RANKL and FcRL4. FCRL4 mRNA expression was determined in synovial tissue of RA patients and non-inflammatory control subjects by real-time PCR. RESULTS: RANKL-producing B cells in RA synovial tissue and fluid were identified as belonging to a distinct subset of B cells defined by expression of the transmembrane protein FcRL4. FcRL4+ B cells express a distinct combination of cytokines and surface proteins indicating a function distinct from that of FcRL4− B cells. Notably, FcRL4+ B cells expressed high levels of TNF-α and RANKL mRNA. CONCLUSIONS: We have identified a novel pro-inflammatory B cell population in the RA synovium which is defined by expression of FcRL4 and responsible for RANKL production. This B cell population expresses high levels of CD20, and its removal by rituximab may contribute to the anti-inflammatory effect of this drug

Alterations in the gut microbiome implicate key taxa and metabolic pathways across inflammatory arthritis phenotypes

Musculoskeletal diseases affect up to 20% of adults worldwide. The gut microbiome has been implicated in inflammatory conditions, but large-scale metagenomic evaluations have not yet traced the routes by which immunity in the gut affects inflammatory arthritis. To characterize the community structure and associated functional processes driving gut microbial involvement in arthritis, the Inflammatory Arthritis Microbiome Consortium investigated 440 stool shotgun metagenomes comprising 221 adults diagnosed with rheumatoid arthritis, ankylosing spondylitis, or psoriatic arthritis and 219 healthy controls and individuals with joint pain without an underlying inflammatory cause. Diagnosis explained about 2% of gut taxonomic variability, which is comparable in magnitude to inflammatory bowel disease. We identified several candidate microbes with differential carriage patterns in patients with elevated blood markers for inflammation. Our results confirm and extend previous findings of increased carriage of typically oral and inflammatory taxa and decreased abundance and prevalence of typical gut clades, indicating that distal inflammatory conditions, as well as local conditions, correspond to alterations to the gut microbial composition. We identified several differentially encoded pathways in the gut microbiome of patients with inflammatory arthritis, including changes in vitamin B salvage and biosynthesis and enrichment of iron sequestration. Although several of these changes characteristic of inflammation could have causal roles, we hypothesize that they are mainly positive feedback responses to changes in host physiology and immune homeostasis. By connecting taxonomic alternations to functional alterations, this work expands our understanding of the shifts in the gut ecosystem that occur in response to systemic inflammation during arthritis