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".

Ex Input:
Paragraph: Estimating the case-fatality risk (CFR)-the probability that a person dies from an infection given that they are a case-is a high priority in epidemiologic investigation of newly emerging infectious diseases and sometimes in new outbreaks of known infectious diseases. The data available to estimate the overall CFR are often gathered for other purposes (e.g., surveillance) in challenging circumstances. We describe two forms of bias that may affect the estimation of the overall CFR-preferential ascertainment of severe cases and bias from reporting delays-and review solutions that have been proposed and implemented in past epidemics. Also of interest is the estimation of the causal impact of specific interventions (e.g., hospitalization, or hospitalization at a particular hospital) on survival, which can be estimated as a relative CFR for two or more groups. When observational data are used for this purpose, three more sources of bias may arise: confounding, survivorship bias, and selection due to preferential inclusion in surveillance datasets of those who are hospitalized and/or die. We illustrate these biases and caution against causal interpretation of differential CFR among those receiving different interventions in observational datasets. Again, we discuss ways to reduce these biases, particularly by estimating outcomes in smaller but more systematically defined cohorts ascertained before the onset of symptoms, such as those identified by forward contact tracing. Finally, we discuss the circumstances in which these biases may affect non-causal interpretation of risk factors for death among cases. PLOS Neglected Tropical Diseases |
Title: Potential Biases in Estimating Absolute and Relative Case-Fatality Risks during Outbreaks

Ex Output:
False

Ex Input:
Paragraph: Spongiform degeneration is characterized by vacuolation in nervous tissue accompanied by neuronal death and gliosis. Although spongiform degeneration is a hallmark of prion diseases, this pathology is also present in the brains of patients suffering from Alzheimer's disease, diffuse Lewy body disease, human immunodeficiency virus (HIV) infection, and Canavan's spongiform leukodystrophy. The shared outcome of spongiform degeneration in these diverse diseases suggests that common cellular mechanisms must underlie the processes of spongiform change and neurodegeneration in the central nervous system. Immunohistochemical analysis of brain tissues reveals increased ubiquitin immunoreactivity in and around areas of spongiform change, suggesting the involvement of ubiquitin-proteasome system dysfunction in the pathogenesis of spongiform neurodegeneration. The link between aberrant ubiquitination and spongiform neurodegeneration has been strengthened by the discovery that a null mutation in the E3 ubiquitin-protein ligase mahogunin ring finger-1 (Mgrn1) causes an autosomal recessively inherited form of spongiform neurodegeneration in animals. Recent studies have begun to suggest that abnormal ubiquitination may alter intracellular signaling and cell functions via proteasome-dependent and proteasome-independent mechanisms, leading to spongiform degeneration and neuronal cell death. Further elucidation of the pathogenic pathways involved in spongiform neurodegeneration should facilitate the development of novel rational therapies for treating prion diseases, HIV infection, and other spongiform degenerative disorders. transmissible spongiform encephalopathy (TSE); retroviral infection; mahogunin ring finger-1 (Mgrn1); oxidative stress; autophagy; endocytic trafficking NIH Public Access
Title: The ubiquitin-proteasome system in spongiform degenerative disorders

Ex Output:
True

Ex Input:
Paragraph: In this work we propose a data-driven age-structured census-based SIRD-like epidemiological model capable of forecasting the spread of COVID-19 in Brazil. We model the current scenario of closed schools and universities, social distancing of people above sixty years old and voluntary home quarantine to show that it is still not enough to protect the health system by explicitly computing the demand for hospital intensive care units. We also show that an urgent intense quarantine might be the only solution to avoid the collapse of the health system and, consequently, to minimize the quantity of deaths. On the other hand, we demonstrate that the relaxation of the already imposed control measures in the next days would be catastrophic. . CC-BY 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity. is the (which was not peer-reviewed) The copyright holder for this preprint .
Title: Prediction of the Health System Failure in Brazil amid Diverse Intervention Strategies

Ex Output:
False