Narrative enhancement and cognitive therapy (NECT) to improve social functioning in people with serious mental illness: study protocol for a stepped-wedge cluster randomized controlled trial.

Background: Self-stigma is highly prevalent in serious mental illness (SMI) and is associated with poorer clinical and functional outcomes. Narrative enhancement and cognitive therapy (NECT) is a group-based intervention combining psychoeducation, cognitive restructuring and story-telling exercises to reduce self-stigma and its impact on recovery-related outcomes. Despite evidence of its effectiveness on self-stigma in schizophrenia-related disorders, it is unclear whether NECT can impact social functioning.

Improving social function with real-world social-cognitive remediation in schizophrenia: Results from the RemedRugby quasi-experimental trial.

Background: Functional capacity (FC) has been identified as a key outcome to improve real-world functioning in schizophrenia. FC is influenced by cognitive impairments, negative symptoms, self-stigma and reduced physical activity (PA). Psychosocial interventions targeting FC are still under-developed.

Towards an improved access to psychiatric rehabilitation: availability and effectiveness at 1-year follow-up of psychoeducation, cognitive remediation therapy, cognitive behaviour therapy and social skills training in the FondaMental Advanced Centers of Expertise-Schizophrenia (FACE-SZ) national cohort.

Psychosocial Interventions (PIs) have shown positive effects on clinical and functional outcomes of schizophrenia (SZ) in randomized controlled trials. However their effectiveness and accessibility remain unclear to date in "real world" schizophrenia. The objectives of the present study were (i) to assess the proportion of SZ outpatients who benefited from PIs between 2010 and 2015 in France after an Expert Center Intervention in a national multicentric non-selected community-dwelling sample; (ii) to assess PIs' effectiveness at 1-year follow-up.

Correction: Unbiased Estimation of Mutation Rates under Fluctuating Final Counts.

[This corrects the article DOI: 10.1371/journal.pone.

Large-scale microarray profiling reveals four stages of immune escape in non-Hodgkin lymphomas.

Non-Hodgkin B-cell lymphoma (B-NHL) are aggressive lymphoid malignancies that develop in patients due to oncogenic activation, chemo-resistance, and immune evasion. Tumor biopsies show that B-NHL frequently uses several immune escape strategies, which has hindered the development of checkpoint blockade immunotherapies in these diseases. To gain a better understanding of B-NHL immune editing, we hypothesized that the transcriptional hallmarks of immune escape associated with these diseases could be identified from the meta-analysis of large series of microarrays from B-NHL biopsies.

Several immune escape patterns in non-Hodgkin's lymphomas.

Follicular Lymphomas (FL) and diffuse large B cell lymphomas (DLBCL) must evolve some immune escape strategy to develop from lymphoid organs, but their immune evasion pathways remain poorly characterized. We investigated this issue by transcriptome data mining and immunohistochemistry (IHC) of FL and DLBCL lymphoma biopsies. A set of genes involved in cancer immune-evasion pathways (Immune Escape Gene Set, IEGS) was defined and the distribution of the expression levels of these genes was compared in FL, DLBCL and normal B cell transcriptomes downloaded from the GEO database.

Weighted Kolmogorov Smirnov testing: an alternative for Gene Set Enrichment Analysis.

Gene Set Enrichment Analysis (GSEA) is a basic tool for genomic data treatment. Its test statistic is based on a cumulated weight function, and its distribution under the null hypothesis is evaluated by Monte-Carlo simulation. Here, it is proposed to subtract to the cumulated weight function its asymptotic expectation, then scale it.

A six gene expression signature defines aggressive subtypes and predicts outcome in childhood and adult acute lymphoblastic leukemia.

Abnormal gene expression in cancer represents an under-explored source of cancer markers and therapeutic targets. In order to identify gene expression signatures associated with survival in acute lymphoblastic leukemia (ALL), a strategy was designed to search for aberrant gene activity, which consists of applying several filters to transcriptomic datasets from two pediatric ALL studies. Six genes whose expression in leukemic blasts was associated with prognosis were identified:three genes predicting poor prognosis (AK022211, FASTKD1 and STARD4) and three genes associated with a favorable outcome (CAMSAP1, PCGF6 and SH3RF3).

Unbiased estimation of mutation rates under fluctuating final counts.

Estimation methods for mutation rates (or probabilities) in Luria-Delbrück fluctuation analysis usually assume that the final number of cells remains constant from one culture to another. We show that this leads to systematically underestimate the mutation rate. Two levels of information on final numbers are considered: either the coefficient of variation has been independently estimated, or the final number of cells in each culture is known.

Fluctuation analysis: can estimates be trusted?

The estimation of mutation rates and relative fitnesses in fluctuation analysis is based on the unrealistic hypothesis that the single-cell times to division are exponentially distributed. Using the classical Luria-Delbrück distribution outside its modelling hypotheses induces an important bias on the estimation of the relative fitness. The model is extended here to any division time distribution.

Curbing false discovery rates in interpretation of genome-wide expression profiles.

Fisher's exact test is widely used in biomedical research, particularly in genomic profile analysis. Since in most databases, the frequency distribution of genes is right skewed, we show here that its use can lead to excessive false-positive discoveries. We propose to apply Zelen's exact test on a stratification of the gene set; this solves the false discovery problem, and should avoid misleading interpretations of lists of genes produced by various genome-wide analysis technologies.

The gene expression profile of phosphoantigen-specific human γδ T lymphocytes is a blend of αβ T-cell and NK-cell signatures.

Global transcriptional technologies have revolutionised the study of lymphoid cell populations, but human γδ T lymphocytes specific for phosphoantigens remain far less deeply characterised by these methods despite the great therapeutic potential of these cells. Here we analyse the transcriptome of circulating TCRVγ(+) γδ T cells isolated from healthy individuals, and their relation with those from other lymphoid cell subsets. We report that the gene signature of phosphoantigen-specific TCRVγ(+) γδ T cells is a hybrid of those from αβ T and NK cells, with more 'NK-cell' genes than αβ T cells have and more 'T-cell' genes than NK cells.