In this task, you're given a paragraph from the research paper and your task is to generate a suitable title for the research paper based on the given paper. Under 100 words is a good title length.

The emerging novel human betacoronavirus 2c EMC/2012 (HCoV-EMC) was recently isolated from patients with severe pneumonia and renal failure and was associated with an unexplained high crude fatality rate of 56%. We performed a cell line susceptibility study with 28 cell lines. HCoV-EMC was found to infect the human respiratory tract ( polarized airway epithelium cell line Calu-3, embryonic fibroblast cell line HFL, and lung adenocarcinoma cell line A549), kidney (embryonic kidney cell line HEK), intestinal tract (colorectal adenocarcinoma cell line Caco-2), liver cells (hepatocellular carcinoma cell line Huh-7), and histiocytes (malignant histiocytoma cell line His-1), as evident by detection of high or increasing viral load in culture supernatants, detection of viral nucleoprotein expression by immunostaining, and/or detection of cytopathic effects. Although an infected human neuronal cell line (NT2) and infected monocyte and T lymphocyte cell lines (THP-1, U937, and H9) had increased viral loads, their relatively lower viral production corroborated with absent nucleoprotein expression and cytopathic effects. This range of human tissue tropism is broader than that for all other HCoVs, including SARS coronavirus, HCoV-OC43, HCoV-HKU1, HCoV-229E, and HCoV-NL63, which may explain the high mortality associated with this disease. A recent cell line susceptibility study showed that HCoV-EMC can infect primate, porcine, and bat cells and therefore may jump interspecies barriers. We found that HCoV-EMC can also infect civet lung fibroblast and rabbit kidney cell lines. These findings have important implications for the diagnosis, pathogenesis, and transmission of HCoV-EMC.
Differential Cell Line Susceptibility to the Emerging Novel Human Betacoronavirus 2c EMC/2012: Implications for Disease Pathogenesis and Clinical Manifestation

Coronaviridae and causes highly contagious respiratory disease in chickens. Innate immunity plays significant roles in host defense against IBV. Here, we explored the interaction between IBV and the host innate immune system. Severe histopathological lesions were observed in the tracheal mucosa at 3-5 days post inoculation (dpi) and in the kidney at 8 dpi, with heavy viral loads at 1-11 and 1-28 dpi, respectively. The expression of mRNAs encoding Toll-like receptor (TLR) 3 and TLR7 were upregulated at 3-8 dpi, and that of TIR-domain-containing adapter-inducing interferon (IFN) (TRIF) was upregulated at 21 dpi in the trachea and kidney. Myeloid differentiation primary response protein 88 (MyD88) was upregulated in the trachea during early infection. Tumor necrosis factor receptor-associated factor (TRAF) 3 and TRAF6 were upregulated expression in both tissues. Moreover, melanoma differentiation-associated protein 5 (MDA5), laboratory of genetics and physiology 2 (LGP2), stimulator of IFN genes (STING), and mitochondrial antiviral signaling protein (MAVS), as well as TANK binding kinase 1 (TBK1), inhibitor of kappaB kinase (IKK) , IKK, IKK, IFN regulatory factor (IRF) 7, nuclear factor of kappaB (NF-B), IFN-, IFN-, various interleukins(ILs), and macrophage inflammatory protein-1 (MIP-1) were significantly upregulated in the trachea and downregulated in the kidney. These results suggested that the TLR and MDA5 signaling pathways and innate immune cytokine were induced after IBV infection. Additionally, consistent responses to IBV infection were observed during early infection, with differential and complicated responses in the kidney.
Responses of the Toll-like receptor and melanoma differentiation- associated protein 5 signaling pathways to avian infectious bronchitis virus infection in chicks

Objectives: Severe influenza can lead to Intensive Care Unit (ICU) admission. We explored whether ICU data reflect influenza like illness (ILI) activity in the general population, and whether ICU respiratory infections can predict influenza epidemics. Methods: We calculated the time lag and correlation between ILI incidence (from ILI sentinel surveillance, based on general practitioners (GP) consultations) and percentages of ICU admissions with a respiratory infection (from the Dutch National Intensive Care Registry) over the years 2003-2011. In addition, ICU data of the first three years was used to build three regression models to predict the start and end of influenza epidemics in the years thereafter, one to three weeks ahead. The predicted start and end of influenza epidemics were compared with observed start and end of such epidemics according to the incidence of ILI. Results: Peaks in respiratory ICU admissions lasted longer than peaks in ILI incidence rates. Increases in ICU admissions occurred on average two days earlier compared to ILI. Predicting influenza epidemics one, two, or three weeks ahead yielded positive predictive values ranging from 0.52 to 0.78, and sensitivities from 0.34 to 0.51.
Do Intensive Care Data on Respiratory Infections Reflect Influenza Epidemics?