instruction:
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".
question:
Paragraph: The yeast Kre2p/Mntlp cxl,2-mannosyltransferase is a type II membrane protein with a short cytoplasmic amino terminus, a membrane-spanning region, and a large catalytic luminal domain containing one N-glycosylation site. Anti-Kre2p/Mntlp antibodies identify a 60-kD integral membrane protein that is progressively N-glycosylated in an MNNl-dependent manner. Kre2p/Mntlp is localized in a Golgi compartment that overlaps with that containing the medial-Golgi mannosyltransferase Mnnlp, and distinct from that including the late Golgi protein Kexlp. To determine which regions of Kre2p/Mntlp are required for Golgi localization, Kre2p/Mntlp mutant proteins were assem-bled by substitution of Kre2p domains with equivalent sequences from the vacuolar proteins DPAP B and Pho8p. Chimeric proteins were tested for correct topology, in vitro and in vivo activity, and were localized intracellularly by indirect immunofluorescence. The resuits demonstrate that the NH2-terminal cytoplasmic domain is necessary for correct Kre2p Golgi localization whereas, the membrane-spanning and stem domains are dispensable. However, in a test of targeting sufficiency, the presence of the entire Kre2p cytoplasmic tail, plus the transmembrane domain and a 36-amino acid residue luminal stem region was required to localize a Pho8p reporter protein to the yeast Golgi. T HE Golgi apparatus plays a fundamental role in glycan processing and sorting of newly synthesized proteins in the secretory pathway of eukaryotic cells. The Golgi apparatus of a typical mammalian cell is composed of a polarized stack of membranous saccules that are differentiated into functionally distinct subcompartments. After the addition of core N-linked sugar moieties in the endoplasmic reticulum, glycoproteins proceed through the cis-Golgi network, the cis-, medial-, and transcisternae, and the trans-Golgi network, where further modifications take place. These include the addition of O-linked sugars and the elaboration, in a protein-specific manner, of complex N-linked carbohydrate structures. The Golgi apparatus also constitutes a major organelle responsible for protein trafficking where particular proteins are directed to precise cellular locations. Two specific Golgi subcompartments have been found to be involved in protein sorting. The cis-Golgi network constitutes the site from which many resident ER proteins are retrieved, and the main function of the TGN is to direct glycoproteins exiting the Golgi complex to either the lysosome or the cell surface ( 
 Title: Localization and Targeting of the Saccharomyces cerevisiae Kre2p/Mnt lp oL 1,2-Mannosyltransferase to a medial.Gol Compartment
answer:
False


question:
Paragraph: Using sequence data to infer population dynamics is playing an increasing role in the analysis of outbreaks. The most common methods in use, based on coalescent inference, have been widely used but not extensively tested against simulated epidemics. Here, we use simulated data to test the ability of both parametric and non-parametric methods for inference of effective population size (coded in the popular BEAST package) to reconstruct epidemic dynamics. We consider a range of simulations centred on scenarios considered plausible for pandemic influenza, but our conclusions are generic for any exponentially growing epidemic. We highlight systematic biases in non-parametric effective population size estimation. The most prominent such bias leads to the false inference of slowing of epidemic spread in the recent past even when the real epidemic is growing exponentially. We suggest some sampling strategies that could reduce (but not eliminate) some of the biases. Parametric methods can correct for these biases if the infected population size is large. We also explore how some poor sampling strategies (e.g. that over-represent epidemiologically linked clusters of cases) could dramatically exacerbate bias in an uncontrolled manner. Finally, we present a simple diagnostic indicator, based on coalescent density and which can easily be applied to reconstructed phylogenies, that identifies time-periods for which effective population size estimates are less likely to be biased. We illustrate this with an application to the 2009 H1N1 pandemic. Pandemic growth rates from sequences E. de Silva et al. 1799 Pandemic growth rates from sequences E. de Silva et al. 1807  
 Title: Inferring pandemic growth rates from sequence data
answer:
True


question:
Paragraph: The World Health Organization (WHO) has recently declared coronavirus disease 2019 (COVID-19) a public health emergency of global concern. Updated analysis of cases might help identify the characteristic and risk factors of the illness severity. We extracted data regarding 47 patients with confirmed COVID-19 from Renmin Hospital of Wuhan University between February 1 and February 18, 2020. The degree of severity of COVID-19 patients (severe vs. non-severe) was defined at the time of admission according to American Thoracic Society (ATS) guidelines for communityacquired pneumonia (CAP). The median age was 64.91 years, 26 cases (55.31%) were male of which, and 70.83% were severe cases. Severe patients had higher APACHE II (9.92 vs 4.74) and SOFA (3.0 vs 1.0) scores on admission, as well as the higher PSI (86.13 vs 61.39), Curb-65 (1.14 vs 0.48) and CT semiquantitative scores (5.0 vs 2.0) when compared with nonsevere patients. Among all univariable parameters, APACHE II, SOFA, lymphocytes, CRP, LDH, AST, cTnI, BNP, et al were significantly independent risk factors of COVID-19 severity. Among which, LDH was most positively related both with APACHE II (R = 0.682) and SOFA (R = 0.790) scores, as well as PSI (R = 0.465) and CT (R = 0.837) scores. To assess the diagnostic value of these selected parameters, LDH (0.9727) had maximum sensitivity (100.00%) and specificity (86.67%), with the cutoff value of 283. As a protective factor, lymphocyte counts less than 1.045 x 10 9 /L showed a good accuracy for identification of severe patients with AUC = 0.9845 (95%CI 0.959-1.01), the maximum specificity (91.30%) and sensitivity (95.24%). In addition, LDH was positively correlated with CRP, AST, BNP and cTnI, while negatively correlated with lymphocyte cells and its subsets, including CD3 + , CD4 + and CD8 + T cells (P < 0.01). 
 Title: Lactate dehydrogenase, a Risk Factor of Severe COVID-19 Patients: A Retrospective and Observational Study
answer:

False