In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".

Q: Paragraph: Severe acute respiratory syndrome coronavirus (SARS-CoV) envelope (E) protein is a viroporin involved in virulence. E protein ion channel (IC) activity is specifically correlated with enhanced pulmonary damage, edema accumulation and death. IL-1β driven proinflammation is associated with those pathological signatures, however its link to IC activity remains unknown. In this report, we demonstrate that SARS-CoV E protein forms protein-lipid channels in ERGIC/Golgi membranes that are permeable to calcium ions, a highly relevant feature never reported before. Calcium ions together with pH modulated E protein pore charge and selectivity. Interestingly, E protein IC activity boosted the activation of the NLRP3 inflammasome, leading to IL-1β overproduction. Calcium transport through the E protein IC was the main trigger of this process. These findings strikingly link SARS-CoV E protein IC induced ionic disturbances at the cell level to immunopathological consequences and disease worsening in the infected organism. 
 Title: Severe acute respiratory syndrome coronavirus E protein transports calcium ions and activates the NLRP3 inflammasome

A: False
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Q: Paragraph: The binding between peptide epitopes and major histocompatibility complex proteins (MHCs) is an important event in the cellular immune response. Accurate prediction of the binding between short peptides and the MHC molecules has long been a principal challenge for immunoinformatics. Recently, the modeling of MHC-peptide binding has come to emphasize quantitative predictions: instead of categorizing peptides as "binders" or "non-binders" or as "strong binders" and "weak binders", recent methods seek to make predictions about precise binding affinities. We developed a quantitative support vector machine regression (SVR) approach, called SVRMHC, to model peptide-MHC binding affinities. As a non-linear method, SVRMHC was able to generate models that out-performed existing linear models, such as the "additive method". By adopting a new "11-factor encoding" scheme, SVRMHC takes into account similarities in the physicochemical properties of the amino acids constituting the input peptides. When applied to MHC-peptide binding data for three mouse class I MHC alleles, the SVRMHC models produced more accurate predictions than those produced previously. Furthermore, comparisons based on Receiver Operating Characteristic (ROC) analysis indicated that SVRMHC was able to outperform several prominent methods in identifying strongly binding peptides. As a method with demonstrated performance in the quantitative modeling of MHCpeptide binding and in identifying strong binders, SVRMHC is a promising immunoinformatics tool with not inconsiderable future potential. 
 Title: Quantitative prediction of mouse class I MHC peptide binding affinity using support vector machine regression (SVR) models

A: False
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Q: Paragraph: Steroid-associated osteonecrosis (SAON) is a common orthopaedic problem caused by administration of corticosteroids prescribed for many nonorthopaedic medical conditions. We summarised different pathophysiologies of SAON which have adverse effects on multiple systems such as bone marrow stem cells (BMSCs) pool, bone matrix, cell apoptosis, lipid metabolism, and angiogenesis. Different animal models were introduced to mimic the pathophysiology of SAON and for testing the efficacy of both prevention and treatment effects of various chemical drugs, biological, and physical therapies. According to the classification of SAON, several prevention and treatment methods are applied at the different stages of SAON. For the current period, Chinese herbs may also have the potential to prevent the occurrence of SAON. In the future, genetic analysis might also be helpful to effectively predict the development of ON and provide information for personalised prevention and treatment of patients with SAON. 
 Title: Steroid-associated osteonecrosis: Epidemiology, pathophysiology, animal model, prevention, and potential treatments (an overview)-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

A:
True
****