Ligand-independent oligomerization of TACI is controlled by the transmembrane domain and regulates proliferation of activated B cells.

In mature B cells, TACI controls class-switch recombination and differentiation into plasma cells during T cell-independent antibody responses. TACI binds the ligands BAFF and APRIL. Approximately 10% of patients with common variable immunodeficiency (CVID) carry TACI mutations, of which A181E and C172Y are in the transmembrane domain. Residues A181 and C172 are located on distinct sides of the transmembrane helix, which is predicted by molecular modeling to spontaneously assemble into trimers and dimers. In human B cells, these mutations impair ligand-dependent (C172Y) and -independent (A181E) TACI multimerization and signaling, as well as TACI-enhanced proliferation and/or IgA production. Genetic inactivation of TACI in primary human B cells impaired survival of CpG-activated cells in the absence of ligand. These results identify the transmembrane region of TACI as an active interface for TACI multimerization in signal transduction, in particular for ligand-independent signals. These functions are perturbed by CVID-associated mutations

Collaborative Database to Track Mass Mortality Events in the Mediterranean Sea

Anthropogenic climate change, and global warming in particular, has strong and increasing impacts on marine ecosystems (Poloczanska et al., 2013; Halpern et al., 2015; Smale et al., 2019). The Mediterranean Sea is considered a marine biodiversity hot-spot contributing to more than 7% of world's marine biodiversity including a high percentage of endemic species (Coll et al., 2010). The Mediterranean region is a climate change hotspot, where the respective impacts of warming are very pronounced and relatively well documented (Cramer et al., 2018). One of the major impacts of sea surface temperature rise in the marine coastal ecosystems is the occurrence of mass mortality events (MMEs). The first evidences of this phenomenon dated from the first half of'80 years affecting the Western Mediterranean and the Aegean Sea (Harmelin, 1984; Bavestrello and Boero, 1986; Gaino and Pronzato, 1989; Voultsiadou et al., 2011). The most impressive phenomenon happened in 1999 when an unprecedented large scale MME impacted populations of more than 30 species from different phyla along the French and Italian coasts (Cerrano et al., 2000; Perez et al., 2000). Following this event, several other large scale MMEs have been reported, along with numerous other minor ones, which are usually more restricted in geographic extend and/or number of affected species (Garrabou et al., 2009; Rivetti et al., 2014; Marbà et al., 2015; Rubio-Portillo et al., 2016, authors' personal observations). These events have generally been associated with strong and recurrent marine heat waves (Crisci et al., 2011; Kersting et al., 2013; Turicchia et al., 2018; Bensoussan et al., 2019) which are becoming more frequent globally (Smale et al., 2019). Both field observations and future projections using Regional Coupled Models (Adloff et al., 2015; Darmaraki et al., 2019) show the increase in Mediterranean sea surface temperature, with more frequent occurrence of extreme ocean warming events. As a result, new MMEs are expected during the coming years. To date, despite the efforts, neither updated nor comprehensive information can support scientific analysis of mortality events at a Mediterranean regional scale. Such information is vital to guide management and conservation strategies that can then inform adaptive management schemes that aim to face the impacts of climate change.MV-L was supported by a postdoctoral contract Juan de la Cierva-Incorporación (IJCI-2016-29329) of Ministerio de Ciencia, Innovación y Universidades. AI was supported by a Technical staff contract (PTA2015-10829-I) Ayudas Personal Técnico de Apoyo of Ministerio de Economía y Competitividad (2015). Interreg Med Programme (grant number Project MPA-Adapt 1MED15_3.2_M2_337) 85% cofunded by the European Regional Development Fund, the MIMOSA project funded by the Foundation Prince Albert II Monaco and the European Union's Horizon 2020 research and innovation programme under grant agreement no 689518 (MERCES). DG-G was supported by an FPU grant (FPU15/05457) from the Spanish Ministry of Education. J-BL was partially supported by the Strategic Funding UID/Multi/04423/2013 through national funds provided by FCT - Foundation for Science and Technology and European Regional Development Fund (ERDF), in the framework of the programme PT2020

Assessment of two complementary influenza surveillance systems : Sentinel primary care influenza-like illness versus severe hospitalized laboratory-confirmed influenza using the moving epidemic method

Monitoring seasonal influenza epidemics is the corner stone to epidemiological surveillance of acute respiratory virus infections worldwide. This work aims to compare two sentinel surveillance systems within the Daily Acute Respiratory Infection Information System of Catalonia (PIDIRAC), the primary care ILI and Influenza confirmed samples from primary care (PIDIRAC-ILI and PIDIRAC-FLU) and the severe hospitalized laboratory confirmed influenza system (SHLCI), in regard to how they behave in the forecasting of epidemic onset and severity allowing for healthcare preparedness. Epidemiological study carried out during seven influenza seasons (2010-2017) in Catalonia, with data from influenza sentinel surveillance of primary care physicians reporting ILI along with laboratory confirmation of influenza from systematic sampling of ILI cases and 12 hospitals that provided data on severe hospitalized cases with laboratory-confirmed influenza (SHLCI-FLU). Epidemic thresholds for ILI and SHLCI-FLU (overall) as well as influenza A (SHLCI-FLUA) and influenza B (SHLCI-FLUB) incidence rates were assessed by the Moving Epidemics Method. Epidemic thresholds for primary care sentinel surveillance influenza-like illness (PIDIRAC-ILI) incidence rates ranged from 83.65 to 503.92 per 100.000 h. Paired incidence rate curves for SHLCI-FLU/PIDIRAC-ILI and SHLCI-FLUA/PIDIRAC-FLUA showed best correlation index' (0.805 and 0.724 respectively). Assessing delay in reaching epidemic level, PIDIRAC-ILI source forecasts an average of 1.6 weeks before the rest of sources paired. Differences are higher when SHLCI cases are paired to PIDIRAC-ILI and PIDIRAC-FLUB although statistical significance was observed only for SHLCI-FLU/PIDIRAC-ILI (p-value Wilcoxon test = 0.039). The combined ILI and confirmed influenza from primary care along with the severe hospitalized laboratory confirmed influenza data from PIDIRAC sentinel surveillance system provides timely and accurate syndromic and virological surveillance of influenza from the community level to hospitalization of severe cases