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".

Paragraph: Background: The Middle East respiratory syndrome (MERS) coronavirus has caused recurrent outbreaks in the Arabian Peninsula since 2012. Although MERS has low overall human-to-human transmission potential, there is occasional amplification in the healthcare setting, a pattern reminiscent of the dynamics of the severe acute respiratory syndrome (SARS) outbreaks in 2003. Here we provide a head-to-head comparison of exposure patterns and transmission dynamics of large hospital clusters of MERS and SARS, including the most recent South Korean outbreak of MERS in 2015. Methods: To assess the unexpected nature of the recent South Korean nosocomial outbreak of MERS and estimate the probability of future large hospital clusters, we compared exposure and transmission patterns for previously reported hospital clusters of MERS and SARS, based on individual-level data and transmission tree information. We carried out simulations of nosocomial outbreaks of MERS and SARS using branching process models rooted in transmission tree data, and inferred the probability and characteristics of large outbreaks. Results: A significant fraction of MERS cases were linked to the healthcare setting, ranging from 43.5 % for the nosocomial outbreak in Jeddah, Saudi Arabia, in 2014 to 100 % for both the outbreak in Al-Hasa, Saudi Arabia, in 2013 and the outbreak in South Korea in 2015. Both MERS and SARS nosocomial outbreaks are characterized by early nosocomial super-spreading events, with the reproduction number dropping below 1 within three to five disease generations. There was a systematic difference in the exposure patterns of MERS and SARS: a majority of MERS cases occurred among patients who sought care in the same facilities as the index case, whereas there was a greater concentration of SARS cases among healthcare workers throughout the outbreak. Exposure patterns differed slightly by disease generation, however, especially for SARS. Moreover, the distributions of secondary cases per single primary case varied highly across individual hospital outbreaks (Kruskal-Wallis test; P < 0.0001), with significantly higher transmission heterogeneity in the distribution of secondary cases for MERS than SARS. Simulations indicate a 2-fold higher probability of occurrence of large outbreaks (>100 cases) for SARS than MERS (2 % versus 1 %); however, owing to higher transmission heterogeneity, the largest outbreaks of MERS are characterized by sharper incidence peaks. The probability of occurrence of MERS outbreaks larger than the South Korean cluster (n = 186) is of the order of 1 %. Our study suggests that the South Korean outbreak followed a similar progression to previously described hospital clusters involving coronaviruses, with early super-spreading events generating a disproportionately large number of secondary infections, and the transmission potential diminishing greatly in subsequent generations. Differences in relative exposure patterns and transmission heterogeneity of MERS and SARS could point to changes in hospital practices since 2003 or differences in transmission mechanisms of these coronaviruses.
Title: Transmission characteristics of MERS and SARS in the healthcare setting: a comparative study
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Paragraph: Dendritic cells (DCs) are recognized as highly potent antigen-presenting cells that are able to stimulate cytotoxic T lymphocyte (CTL) responses with antitumor activity. Consequently, DCs have been explored as cellular vaccines in cancer immunotherapy. To that end, DCs are modified with tumor antigens to enable presentation of antigen-derived peptides to CTLs. In this review we discuss the use of viral vectors for in situ modification of DCs, focusing on their clinical applications as anticancer vaccines. Among the viral vectors discussed are those derived from viruses belonging to the families of the Poxviridae, Adenoviridae, Retroviridae, Togaviridae, Paramyxoviridae, and Rhabdoviridae. We will further shed light on how the combination of viral vector-based vaccination with T-cell supporting strategies will bring this strategy to the next level. Since their discovery in 1973, it was clear that dendritic cells (DCs) stood out above the immune cell pack (1, 2). They are morphologically distinct from all other immune cell types and are gifted with an unparalleled capacity to take up, process and present self and foreign antigens to both CD4 + and CD8 + T cells. DCs are critical intermediaries between the innate and adaptive immune systems, as they stimulate, regulate, and shape both immunity and tolerance in all its disguises. Ralph Steinmann, who discovered these cells, was awarded the Nobel Prize for Medicine in 2011, because the discovery of DCs changed medicine (3). Dendritic cells in both humans and mice represent a population of at least four different subtypes with distinct phenotypical and functional characteristics (4-7). These subsets are: plasmacytoid DCs (pDCs), two subsets of conventional DCs (cDC1 and cDC2), and inflammatory DCs. The latter represent a monocyte-derived subset that appears during inflammatory responses (Table 1) . Recently, additional types of human blood DCs, monocytes, and progenitors were revealed using single cell RNA-sequencing. The group of Prof. Nir Hacohen identified pDCs next to cDC progenitor-derived cDC1 (Clec9A + ) and two types of CD1c + cDC2, of which one can also be derived from CD14 + DCs. Furthermore they found a CD141 CD1c CD11c + DC subset derived from CD16 + monocytes and an AXL + Siglec6 + subset (8). Future research will have to unravel a possible murine representative for the human cDC2 and AXL + Siglec6 + DC subset. Also, Langerhans cells have been considered an important DC subset for vaccination as they are localized in the epidermis (HLA-DR + CD11c + CD1a + CD207 + ). However, recent evidence suggests that they are related to macrophages, another antigen-presenting cell (APC) type with potential antitumor activity (9).
Title: The Journey of in vivo Virus Engineered Dendritic Cells From Bench to Bedside: A Bumpy Road
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Paragraph: Background: Rapid and accurate laboratory diagnoses of viral infections are crucial for the management and treatment of patients with viral infections. Conventional methods for virus detection are labourious, time consuming, and only a single virus can be analysed in one assay. Objectives: The objective of this study was to develop a novel real-time PCR method for multiple virus detection by melting curve analysis using Taqman probes in a single reaction. Study design: As a model, six respiratory viruses were detected in one tube using three fluorophores. The specificity was assessed by cross-reaction tests with other common respiratory pathogens. The analytical sensitivity was assessed by testing the limit of detection of the assay using artificial plasmids as the positive template. The clinical evaluation of the established assay was evaluated for the detection of respiratory viruses in clinical samples, and the results were compared with direct fluorescent antibody testing (DFA). Results: The six respiratory viruses were clearly distinguished by their respective melting temperature values in the corresponding fluorescence detection channels. No cross reactions were observed by cross reaction tests. The detection limits of this assay were 2 to 2 10 3 copies per reaction for each virus. The clinical evaluation of this assay was demonstrated by analysing 352 clinical samples, and 67(19.0%) samples were positive for at least one virus. The accordance rate between the established PCR and DFA testing was high, and ranged from 94.57% to 100%. Conclusions: Taqman probe-based melting curve analysis is well suited for detection of multiple viruses in clinical and research laboratories because of its high throughput, reliability, and cost savings.
Title: A novel multiplex PCR for virus detection by melting curve analysis
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