In this task, you are given an abstract of article. Your task is to generate label "True" if abstract is structured, otherwise generate "False". A structured abstract is composed of a topic sentence (or key sentence), relevant supporting sentences, and a closing (or transition) sentence. This structure is key to keeping your abstract focused on the main idea and creating a clear and concise image.

Gold standard datasets on protein complexes are key to inferring and validating protein-protein interactions. Despite much progress in characterizing protein complexes in the yeast Saccharomyces cerevisiae, numerous researchers still use as reference the manually curated complexes catalogued by the Munich Information Center of Protein Sequences database. Although this catalogue has served the community extremely well, it no longer reflects the current state of knowledge. Here, we report two catalogues of yeast protein complexes as results of systematic curation efforts. The first one, denoted as CYC2008, is a comprehensive catalogue of 408 manually curated heteromeric protein complexes reliably backed by small-scale experiments reported in the current literature. This catalogue represents an up-to-date reference set for biologists interested in discovering protein interactions and protein complexes. The second catalogue, denoted as YHTP2008, comprises 400 high-throughput complexes annotated with current literature evidence. Among them, 262 correspond, at least partially, to CYC2008 complexes. Evidence for interacting subunits is collected for 68 complexes that have only partial or no overlap with CYC2008 complexes, whereas no literature evidence was found for 100 complexes. Some of these partially supported and as yet unsupported complexes may be interesting candidates for experimental follow up. Both catalogues are freely available at: http://wodaklab.org/cyc2008/.
False

Myelin-directed autoimmunity is considered to play a key role in the pathogenesis of multiple sclerosis (MS). Increased production of both pro- and anti-inflammatory cytokines is a common finding in MS. Interleukin-17 (IL-17) is a recently described cytokine produced in humans almost exclusively by activated memory T cells, which can induce the production of proinflammatory cytokines and chemokines from parenchymal cells and macrophages. In situ hybridisation with synthetic oligonucleotide probes was adopted to detect and enumerate IL-17 mRNA expressing mononuclear cells (MNC) in blood and cerebrospinal fluid (CSF) from patients with MS and control individuals. Numbers of IL-17 mRNA expressing blood MNC were higher in patients with MS and acute aseptic meningoencephalitis (AM) compared to healthy individuals. Higher numbers of IL-17 mRNA expressing blood MNC were detected in MS patients examined during clinical exacerbation compared to remission. Patients with MS had higher numbers of IL-17 mRNA expressing MNC in CSF compared to blood. This increase in numbers of IL-17 mRNA expressing MNC in CSF was not observed in patients with AM. Our results thus demonstrate increased numbers of IL-17 mRNA expressing MNC in MS with higher numbers in CSF than blood, and with the highest numbers in blood during clinical exacerbations.
False

SUMMARY ModLoop is a web server for automated modeling of loops in protein structures. The input is the atomic coordinates of the protein structure in the Protein Data Bank format, and the specification of the starting and ending residues of one or more segments to be modeled, containing no more than 20 residues in total. The output is the coordinates of the non-hydrogen atoms in the modeled segments. A user provides the input to the server via a simple web interface, and receives the output by e-mail. The server relies on the loop modeling routine in MODELLER that predicts the loop conformations by satisfaction of spatial restraints, without relying on a database of known protein structures. For a rapid response, ModLoop runs on a cluster of Linux PC computers. AVAILABILITY The server is freely accessible to academic users at http://salilab.org/modloop
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