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".

Example Input: Paragraph: Xenotropic murine leukemia virus-related virus (XMRV) is a gammaretrovirus that was originally identified from human prostate cancer patients and subsequently linked to chronic fatigue syndrome. Recent studies showed that XMRV is a recombinant mouse retrovirus; hence, its association with human diseases has become questionable. Here, we demonstrated that XMRV envelope (Env)-mediated pseudoviral infection is not blocked by lysosomotropic agents and cellular protease inhibitors, suggesting that XMRV entry is not pH-dependent. The full length XMRV Env was unable to induce syncytia formation and cell-cell fusion, even in cells overexpressing the viral receptor, XPR1. However, truncation of the C-terminal 21 or 33 amino acid residues in the cytoplasmic tail (CT) of XMRV Env induced substantial membrane fusion, not only in the permissive 293 cells but also in the nonpermissive CHO cells that lack a functional XPR1 receptor. The increased fusion activities of these truncations correlated with their enhanced SU shedding into culture media, suggesting conformational changes in the ectodomain of XMRV Env. Noticeably, further truncation of the CT of XMRV Env proximal to the membrane-spanning domain severely impaired the Env fusogenicity, as well as dramatically decreased the Env incorporations into MoMLV oncoretroviral and HIV-1 lentiviral vectors resulting in greatly reduced viral transductions. Collectively, our studies reveal that XMRV entry does not require a low pH or low pH-dependent host proteases, and that the cytoplasmic tail of XMRV Env critically modulates membrane fusion and cell entry. Our data also imply that additional cellular factors besides XPR1 are likely to be involved in XMRV entry. Citation: Cô té M, Zheng Y-M, Liu S-L (2012) Membrane Fusion and Cell Entry of XMRV Are pH-Independent and Modulated by the Envelope Glycoprotein's Cytoplasmic Tail. PLoS ONE 7(3): e33734. 
 Title: Membrane Fusion and Cell Entry of XMRV Are pH- Independent and Modulated by the Envelope Glycoprotein's Cytoplasmic Tail
Example Output: True

Example Input: Paragraph: A major entry route for the gammaretrovirus amphotropic murine leukemia virus (A-MLV) into NIH 3T3 fibroblasts is via caveola-dependent endocytosis. However, during the infection time, few viral particles can be observed intracellularly. Analyzing the dynamics of the A-MLV infection process by using total internal reflection fluorescence microscopy, we show that the majority of viruses are extracellular and bound to the fibronectin matrix. Moreover, the amounts of bound virus and of fibronectin correlated. Using confocal microscopy, nanoparticles targeted to fibronectin by a III1C-fibronectin fragment or anti-fibronectin antibody were detected intracellularly in NIH 3T3 cells; unconjugated nanoparticles neither bound to cells nor were detectable intracellularly. Furthermore, A-MLV colocalized intracellularly with the fibronectin-targeted nanoparticles, suggesting that they were taken up by the same cellular pathway. Both A-MLV entry and fibronectin turnover depend on caveolar endocytosis, and we found that inhibiting viral binding to the extracellular NIH 3T3 fibronectin-matrix dramatically reduced A-MLV infection, indeed, showing an active role of fibronectin in infection. We suggest that binding to the cellular fibronectin matrix provides a new mechanism by which viruses can enter cells. 
 Title: Matrix Fibronectin Binds Gammaretrovirus and Assists in Entry: New Light on Viral Infections ᰔ † Downloaded from
Example Output: True

Example Input: Paragraph: There exists significant interest in developing statistical and computational tools for inferring 'who infected whom' in an infectious disease outbreak from densely sampled case data, with most recent studies focusing on the analysis of whole genome sequence data. However, genomic data can be poorly informative of transmission events if mutations accumulate too slowly to resolve individual transmission pairs or if there exist multiple pathogens lineages within-host, and there has been little focus on incorporating other types of outbreak data. We present here a methodology that uses contact data for the inference of transmission trees in a statistically rigorous manner, alongside genomic data and temporal data. Contact data is frequently collected in outbreaks of pathogens spread by close contact, including Ebola virus (EBOV), severe acute respiratory syndrome coronavirus (SARS-CoV) and Mycobacterium tuberculosis (TB), and routinely used to reconstruct transmission chains. As an improvement over previous, ad-hoc approaches, we developed a probabilistic model that relates a set of contact data to an underlying transmission tree and integrated this in the outbreaker2 inference framework. By analyzing simulated outbreaks under various contact tracing scenarios, we demonstrate that contact data significantly improves our ability to reconstruct transmission trees, even under realistic limitations on the coverage of the contact tracing effort and the amount of non-infectious mixing between cases. Indeed, contact data is equally or more informative than fully sampled whole genome sequence data in certain scenarios. We then use our method to analyze the early stages of the 2003 SARS outbreak in Singapore and describe the range of transmission scenarios consistent with contact data and genetic sequence in a probabilistic manner for the first time. This simple yet flexible model can easily be incorporated into existing tools for outbreak reconstruction and should permit a better integration of genomic and epidemiological data for inferring transmission chains. PLOS Computational Biology | https://doi. 
 Title: Bayesian inference of transmission chains using timing of symptoms, pathogen genomes and contact data
Example Output:
True