SOCS2 Can Enhance Interleukin-2 (IL-2) and IL-3 Signalling by Accelerating SOCS3 Degradation

Cytokine responses can be regulated by a family of proteins termed suppressors of cytokine signaling (SOCS) which can inhibit the JAK/STAT pathway in a classical negative-feedback manner. While the SOCS are thought to target signaling intermediates for degradation, relatively little is known about how their turnover is regulated. Unlike other SOCS family members, we find that SOCS2 can enhance interleukin-2 (IL-2)- and IL-3-induced STAT phosphorylation following and potentiate proliferation in response to cytokine stimulation. As a clear mechanism for these effects, we demonstrate that expression of SOCS2 results in marked proteasome-dependent reduction of SOCS3 and SOCS1 protein expression. Furthermore, we provide evidence that this degradation is dependent on the presence of an intact SOCS box and that the loss of SOCS3 is enhanced by coexpression of elongin B/C. This suggests that SOCS2 can bind to SOCS3 and elongin B/C to form an E3 ligase complex resulting in the degradation of SOCS3. Therefore, SOCS2 can enhance cytokine responses by accelerating proteasome-dependent turnover of SOCS3, suggesting a mechanism for the gigantism observed in SOCS2 transgenic mice.

The trade unions membership dynamics and union members’ trajectories

This text presents an analysis of aggregated membership’s dynamics for Spanish trade unions, using ECVT data, as well as union memberships’ trajectories, or members’ decisions about joining the organization, permanency and responsibilities, and subsequent attrition. For the analysis of trajectories we make use of information of the records of actual memberships and the record of quitting of CCOO, and of a survey-questionnaire to a sample of leavers of the same union. This study allows us to confirm a linkage between the decision and motivations to become union member, to participate in union activities, the time of permanency, and the motives to quit the organization. We also identify five types of union members’ trajectories, indicating that, far from views that assert a monolithic structure, unions are complex organizations.

Polymorphisms in the interleukin-4 and IL-4 receptor genes modify risk for chronic inflammatory arthropathies in women.

Rheumatoid and juvenile idiopathic arthritis (RA, JIA) are chronic inflammatory arthropathies with polygenic autoimmune background. We analysed the IL-4 +33 C/T and IL-4R Q551R single nucleotide polymorphisms (SNPs) in 294 RA, 72 JIA and 165 controls from Northern Ireland. Analysis of the individual phenotypes (RA or JIA) showed that both the IL-4 +33 TT (P = 0.02; OR: 0.25, 95% CI: 0.07-0.87) and the IL-4R Q551R CC genotypes (P = 0.001; OR: 0.19, 95% CI: 0.06-0.56) were exclusively decreased in female RA patients compared to female controls. Similar non-significant trends were observed in female JIA patients (OR: 0.25, 95% CI: 0.03-2.11 and OR: 0.31, 95% CI: 0.07-1.47, respectively). Analysis of the common phenotype (inflammatory arthropathy; i.e. JIA and RA combined) corroborated the unique association of these polymorphisms with female inflammatory arthropathy (P = 0.013 and 0.002, respectively). This is the first demonstration of sex-specific association of the two foremost genes of the IL-4 signalling cascade with chronic inflammatory arthropathies.

An Extended Implementation of the Great Deluge Algorithm for Course Timetabling

Course Scheduling consists of assigning lecture events to a limited set of specific timeslots and rooms. The objective is to satisfy as many soft constraints as possible, while maintaining a feasible solution timetable. The most successful techniques to date require a compute-intensive examination of the solution neighbourhood to direct searches to an optimum solution. Although they may require fewer neighbourhood moves than more exhaustive techniques to gain comparable results, they can take considerably longer to achieve success. This paper introduces an extended version of the Great Deluge Algorithm for the Course Timetabling problem which, while avoiding the problem of getting trapped in local optima, uses simple Neighbourhood search heuristics to obtain solutions in a relatively short amount of time. The paper presents results based on a standard set of benchmark datasets, beating over half of the currently published best results with in some cases up to 60% of an improvement.