The SIB Swiss Institute of Bioinformatics' resources: focus on curated databases

The SIB Swiss Institute of Bioinformatics (www.isb-sib.ch) provides world-class bioinformatics databases, software tools, services and training to the international life science community in academia and industry. These solutions allow life scientists to turn the exponentially growing amount of data into knowledge. Here, we provide an overview of SIB's resources and competence areas, with a strong focus on curated databases and SIB's most popular and widely used resources. In particular, SIB's Bioinformatics resource portal ExPASy features over 150 resources, including UniProtKB/Swiss-Prot, ENZYME, PROSITE, neXtProt, STRING, UniCarbKB, SugarBindDB, SwissRegulon, EPD, arrayMap, Bgee, SWISS-MODEL Repository, OMA, OrthoDB and other databases, which are briefly described in this article

A Finite Element Simulation of the Electrochemical Growth of a Single Hemispherical Silver Nucleus

Understanding the early stages of electrochemical nucleation and growth is the cornerstone for nanoscale electrodeposition. Although studied since decades, the process is not yet fully understood. In this paper, we introduce a new modelling approach to study the growth of a single hemispherical nucleus: Multi-Ion Transport and Reaction Model (MITReM). This approach takes into account the transport driven by diffusion and migration of all species in the electrolyte together with the electrochemical reactions at the electrode boundary. A Finite Element Method (FEM) is used to solve the balance equations for the concentration of all the active species and the electrolyte potential. In contrast to analytical models or discrete scale modelling techniques, the strength of this approach is that no assumptions on the diffusional or kinetic limitations have to be made. In addition, this novel platform allows to add further levels of complexity, such as multiple nuclei, adatom surface diffusion, aggregation, particle detachment, etc. The simulation results prove that, the initial growth stage of a 10 nm single hemispherical silver nucleus always starts under kinetic control, regardless of concentration and electrode potential. Later on, a transition from kinetic to diffusion control takes place. The time of transition depends on the imposed concentration and electrode potential. Moreover, the simulations clearly show that the growth rate is strongly affected by the imposed concentration and electrode potential, as it has been proven experimentally in countless occasions. Numerical simulation by MITReM proves to be of great interest to gain knowledge towards unravelling the early stages of electrochemical nucleation and growth processes.info:eu-repo/semantics/publishe

Modelling of hydrogen permeation experiments in iron alloys : characterization of the accessible parameters : part I : the entry side

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Siglec-9 Regulates an Effector Memory CD8 T-cell Subset That Congregates in the Melanoma Tumor Microenvironment.

Emerging evidence suggests an immunosuppressive role of altered tumor glycosylation due to downregulation of innate immune responses via immunoregulatory Siglecs. In contrast, human T cells, a major anticancer effector cell, only rarely express Siglecs. However, here, we report that the majority of intratumoral, but not peripheral blood, cytotoxic CD8 T cells expressed Siglec-9 in melanoma. We identified Siglec-9 CD8 T cells as a subset of effector memory cells with high functional capacity and signatures of clonal expansion. This cytotoxic T-cell subset was functionally inhibited in the presence of Siglec-9 ligands or by Siglec-9 engagement by specific antibodies. TCR signaling pathways and key effector functions (cytotoxicity, cytokine production) of CD8 T cells were suppressed by Siglec-9 engagement, which was associated with the phosphorylation of the inhibitory protein tyrosine phosphatase SHP-1, but not SHP-2. Expression of cognate Siglec-9 ligands was observed on the majority of tumor cells in primary and metastatic melanoma specimens. Targeting the tumor-restricted, glycosylation-dependent Siglec-9 axis may unleash this intratumoral T-cell subset, while confining T-cell activation to the tumor microenvironment