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: Among the causes for pregnancy loss, viruses and non-infectious factors are among the most important. In both dogs and cats, research and clinical evidence provide proof that there is an increasing incidence of pregnancy loss associated with infectious diseases like herpesvirus, as well as the presence of toxicants or chemicals in the animal's diet and environment. Endocrine causes must be taken into consideration when dealing with pregnancy loss. This review will cover the most recent knowledge regarding viral and non-infectious of pregnancy losses in the dog and cat. # 
 Title: Canine and feline pregnancy loss due to viral and non-infectious causes: A review

Ex Output:
True


Ex Input:
Paragraph: The apical and basolateral surfaces of airway epithelial cells demonstrate directional responses to pathogen exposure in vivo. Thus, ideal in vitro models for examining cellular responses to respiratory pathogens polarize, forming apical and basolateral surfaces. One such model is differentiated normal human bronchial epithelial cells (NHBE). However, this system requires lung tissue samples, expertise isolating and culturing epithelial cells from tissue, and time to generate an air-liquid interface culture. Calu-3 cells, derived from a human bronchial adenocarcinoma, are an alternative model for examining the response of proximal airway epithelial cells to respiratory insult Safety Measures: Perform all procedures in a biosafety cabinet using sterile culture technique. 
 Title: Establishing a Liquid-covered Culture of Polarized Human Airway Epithelial Calu-3 Cells to Study Host Cell Response to Respiratory Pathogens In vitro

Ex Output:
False


Ex Input:
Paragraph: Low cost, high throughput, easy quantitation, and rich descriptions have made gene expression profiling generated by DNA microarrays an optimal approach for describing host transcriptional responses (HTRs). However, efforts to characterize the landscape of HTRs to diverse pathogens are far from offering a comprehensive view. Here, we developed an HTR Connectivity Map based on systematic assessment of pairwise similarities of HTRs to 50 clinically important human pathogens using 1353 gene-expression profiles generated from >60 human cells/tissues. These 50 pathogens were further partitioned into eight robust "HTR communities" (i.e., groups with more consensus internal HTR similarities). These communities showed enrichment in specific infection attributes and differential gene expression patterns. Using query signatures of HTRs to external pathogens, we demonstrated four distinct modes of HTR associations among different pathogens types/class, and validated the reliability of the HTR community divisions for differentiating and categorizing pathogens from a host-oriented perspective. These findings provide a first-generation HTR Connectivity Map of 50 diverse pathogens, and demonstrate the potential for using annotated HTR community to detect functional associations among infectious pathogens. 
 Title: Inferring Infection Patterns Based on a Connectivity Map of Host Transcriptional Responses

Ex Output:

False