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".

Input: Consider Input: Paragraph: Insults to the alveoli usually lead to inefficient gas exchange or even respiratory failure, which is difficult to model in animal studies. Over the past decade, stem cell-derived self-organizing three-dimensional organoids have emerged as a new avenue to recapitulate respiratory diseases in a dish. Alveolar organoids have improved our understanding of the mechanisms underlying tissue homeostasis and pathological alterations in alveoli. From this perspective, we review the state-of-the-art technology on establishing alveolar organoids from endogenous lung epithelial stem/progenitor cells or pluripotent stem cells, as well as the use of alveolar organoids for the study of respiratory diseases, including idiopathic pulmonary fibrosis, tuberculosis infection, and respiratory virus infection. We also discuss challenges that need to be overcome for future application of alveolar organoids in individualized medicine. 
 Title: Organoids as a Powerful Model for Respiratory Diseases

Output: True


Input: Consider Input: Paragraph: Background: Adverse events are associated with significant morbidity, mortality and cost in hospitalized patients. Measuring adverse events is necessary for quality improvement, but current detection methods are inaccurate, untimely and expensive. The advent of electronic health records and the development of automated methods for encoding and classifying electronic narrative data, such as natural language processing, offer an opportunity to identify potentially better methods. The objective of this study is to determine the accuracy of using automated methods for detecting three highly prevalent adverse events: a) hospital-acquired pneumonia, b) catheter-associated bloodstream infections, and c) in-hospital falls. Methods/design: This validation study will be conducted at two large Canadian academic health centres: the McGill University Health Centre (MUHC) and The Ottawa Hospital (TOH). The study population consists of all medical, surgical and intensive care unit patients admitted to these centres between 2008 and 2014. An automated detection algorithm will be developed and validated for each of the three adverse events using electronic data extracted from multiple clinical databases. A random sample of MUHC patients will be used to develop the automated detection algorithms (cohort 1, development set). The accuracy of these algorithms will be assessed using chart review as the reference standard. Then, receiver operating characteristic curves will be used to identify optimal cut points for each of the data sources. Multivariate logistic regression and the areas under curve (AUC) will be used to identify the optimal combination of data sources that maximize the accuracy of adverse event detection. The most accurate algorithms will then be validated on a second random sample of MUHC patients (cohort 1, validation set), and accuracy will be measured using chart review as the reference standard. The most accurate algorithms validated at the MUHC will then be applied to TOH data (cohort 2), and their accuracy will be assessed using a reference standard assessment of the medical chart. Discussion: There is a need for more accurate, timely and efficient measures of adverse events in acute care hospitals. This is a critical requirement for evaluating the effectiveness of preventive interventions and for tracking progress in patient safety through time. 
 Title: Accuracy of using automated methods for detecting adverse events from electronic health record data: a research protocol

Output: True


Input: Consider Input: Paragraph: Wenxiang diagram is a new two-dimensional representation that characterizes the disposition of hydrophobic and hydrophilic residues in a-helices. In this research, the hydrophobic and hydrophilic residues of two leucine zipper coiled-coil (LZCC) structural proteins, cGKIa 1 À 59 and MBS CT35 are dispositioned on the wenxiang diagrams according to heptad repeat pattern (abcdefg) n , respectively. Their wenxiang diagrams clearly demonstrate that the residues with same repeat letters are laid on same side of the spiral diagrams, where most hydrophobic residues are positioned at a and d, and most hydrophilic residues are localized on b, c, e, f and g polar position regions. The wenxiang diagrams of a dimetric LZCC can be represented by the combination of two monomeric wenxiang diagrams, and the wenxiang diagrams of the two LZCC (tetramer) complex structures can also be assembled by using two pairs of their wenxiang diagrams. Furthermore, by comparing the wenxiang diagrams of cGKIa 1 À 59 and MBS CT35 , the interaction between cGKIa 1 À 59 and MBS CT35 is suggested to be weaker. By analyzing the wenxiang diagram of the cGKIa 1 À 59. ÁMBS CT42 complex structure, most affected residues of cGKIa 1 À 59 by the interaction with MBS CT42 are proposed at positions d, a, e and g of the LZCC structure. These findings are consistent with our previous NMR results. Incorporating NMR spectroscopy, the wenxiang diagrams of LZCC structures may provide novel insights into the interaction mechanisms between dimeric, trimeric, tetrameric coiled-coil structures. 
 Title: The disposition of the LZCC protein residues in wenxiang diagram provides new insights into the protein-protein interaction mechanism


Output: True