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: Basic and translational research on lung biology has discovered multiple progenitor cell types, specialized or facultative, responsible for turnover, renewal, and repair. Isolation of populations of resident lung progenitor cells (LPCs) has been described by multiple protocols, and some have been successfully applied to healthy human lung tissue. We aimed at understanding how different cell culture conditions may affect, in vitro, the phenotype of LPCs to create an ideal niche-like microenvironment. The influence of different substrates (i.e., fibronectin, gelatin, laminin) and the impact of a three-dimensional/two-dimensional (3D/2D) culture switch on the biology of LPCs isolated as lung spheroids (LSs) from normal adult human lung biopsy specimens were investigated. We applied a spheroid culture system as the selective/inductive step for progenitor cell culture, as described in many biological systems. The data showed a niche-like proepithelial microenvironment inside the LS, highly sensitive to the 3D culture system and significantly affecting the phenotype of adult LPCs more than culture substrate. LSs favor epithelial phenotypes and LPC maintenance and contain cells more responsive to specific commitment stimuli than 2D monolayer cultures, while secreting a distinctive set of paracrine factors. We have shown for the first time, to our knowledge, how culture as 3D LSs can affect LPC epithelial phenotype and produce strong paracrine signals with a distinctive secretomic profile compared with 2D monolayer conditions. These findings suggest novel approaches to maintain ex vivo LPCs for basic and translational studies. STEM CELLS TRANSLATIONAL MEDICINE 2016;5:1-11 SIGNIFICANCE A lung niche-like microenvironment was created ex vivo inside the pneumosphere. Pneumospheres have a distinctive secretomic profile compared with two-dimensional culture. Three-dimensional culture switch significantly affects lung progenitor phenotype. Lung progenitors in pneumospheres were more committed toward epithelial lineages. 
 Title: Tissue-Specific Progenitor and Stem Cells Human Lung Spheroids as In Vitro Niches of Lung Progenitor Cells With Distinctive Paracrine and Plasticity Properties

A: True
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Q: Paragraph: In February 2014, health officials from around the world announced the Global Health Security Agenda, a critical effort to strengthen national and global systems to prevent, detect, and respond to infectious disease threats and to foster stronger collaboration across borders. With its increasing global roles and broad range of regulatory responsibilities in ensuring the availability, safety, and security of medical and food products, the US Food and Drug Administration (FDA) is engaged in a range of efforts in support of global health security. This article provides an overview of FDA's global health security roles, focusing on its responsibilities related to the development and use of medical countermeasures (MCMs) for preventing, detecting, and responding to global infectious disease and other public health emergency threats. The article also discusses several areas-antimicrobial resistance, food safety, and supply chain integrity-in which FDA's global health security roles continue to evolve and extend beyond MCMs and, in some cases, beyond traditional infectious disease threats. Brooke Courtney, JD, MPH, is Senior Regulatory Counsel, Office of Counterterrorism and Emerging Threats, Office of the Chief Scientist, Office of the Commissioner; Katherine C. Bond, ScD, is Director, Office 
 Title: Regulatory Underpinnings of Global Health Security: FDA's Roles in Preventing, Detecting, and Responding to Global Health Threats

A: True
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Q: Paragraph: Necessary screenings must be performed to control the spread of the Corona Virus in daily life and to make a preliminary diagnosis of suspicious cases. The long duration of pathological laboratory tests and the wrong test results led the researchers to focus on different fields. Fast and accurate diagnoses are essential for effective interventions with COVID-19. The information obtained by using X-ray and Computed Tomography (CT) images is vital in making clinical diagnoses. Therefore it was aimed to develop a machine learning method for the detection of viral epidemics by analyzing X-ray images. In this study, images belonging to 6 situations, including coronavirus images, are classified. Since the number of images in the dataset is deficient and unbalanced, it is more convenient to analyze these images with hand-crafted feature extraction methods. For this purpose, firstly, all the images in the dataset are extracted with the help of four feature extraction algorithms. These extracted features are combined in raw form. The unbalanced data problem is eliminated by producing feature vectors with the SMOTE algorithm. Finally, the feature vector is reduced in size by using a stacked auto-encoder and principal component analysis to remove interconnected features in the feature vector. According to the obtained results, it is seen that the proposed method has leveraging performance, especially in order to make the diagnosis of COVID-19 in a short time and effectively. 
 Title: Classification of Coronavirus Images using Shrunken Features

A:
False
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