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.

Although pneumococcal pneumonia is one of the most common causes of death due to infectious diseases, little is known about pneumococci-lung cell interaction. Herein we tested the hypothesis that pneumococci activated pulmonary epithelial cell cytokine release by c-Jun-NH 2 -terminal kinase (JNK) Methods: Human bronchial epithelial cells (BEAS-2B) or epithelial HEK293 cells were infected with S. pneumoniae R6x and cytokine induction was measured by RT-PCR, ELISA and Bioplex assay. JNKphosphorylation was detected by Western blot and nuclear signaling was assessed by electrophoretic mobility shift assay (EMSA) and chromatin immunoprecipitation (ChIP). JNK was modulated by the small molecule inhibitor SP600125 and AP1 by transfection of a dominant negative mutant. Results: S. pneumoniae induced the release of distinct CC and CXC, as well as Th1 and Th2 cytokines and growth factors by human lung epithelial cell line BEAS-2B. Furthermore, pneumococci infection resulted in JNK phosphorylation in BEAS-2B cells. Inhibition of JNK by small molecule inhibitor SP600125 reduced pneumococci-induced IL-8 mRNA expression and release of IL-8 and IL-6. One regulator of the il8 promoter is JNK-phosphorylated activator protein 1 (AP-1). We showed that S. pneumoniae timedependently induced DNA binding of AP-1 and its phosphorylated subunit c-Jun with a maximum at 3 to 5 h after infection. Recruitment of Ser 63/73 -phosphorylated c-Jun and RNA polymerase II to the endogenous il8 promoter was found 2 h after S. pneumoniae infection by chromatin immunoprecipitation. AP-1 repressor A-Fos reduced IL-8 release by TLR2-overexpressing HEK293 cells induced by pneumococci but not by TNFα. Antisense-constructs targeting the AP-1 subunits Fra1 and Fra2 had no inhibitory effect on pneumococci-induced IL-8 release. Conclusion: S. pneumoniae-induced IL-8 expression by human epithelial BEAS-2B cells depended on activation of JNK and recruitment of phosphorylated c-Jun to the il8 promoter.
Respiratory Research Streptococcus pneumoniae induced c-Jun-N-terminal kinase-and AP-1 -dependent IL-8 release by lung epithelial BEAS-2B cells

The requirement for negative pressure isolation procedures has been an accepted component of pediatric care to protect patients and staff from highly infectious respiratory agents. Surveys regarding airborne isolation were distributed to 43 pediatric emergency departments at US children's hospitals with 26 responses. There was a median of 5 airborne isolation rooms, a median of 4 of those with negative pressure, and 61% without an ante-room. Capacity to manage pediatric patients infected with a highly pathogenic airborne-transmitted organism during an epidemic is limited.
Airborne pathogen isolation capability in emergency departments of US children's hospitals

Background: Infectious disease surveillance is a process the product of which reflects both actual disease trends and public awareness of the disease. Decisions made by patients, health care providers, and public health professionals about seeking and providing health care and about reporting cases to health authorities are all influenced by the information environment, which changes constantly. Biases are therefore imbedded in surveillance systems; these biases need to be characterized to provide better situational awareness for decision-making purposes. Our goal is to develop a statistical framework to characterize influenza surveillance systems, particularly their correlation with the information environment. Methods: We identified Hong Kong influenza surveillance data systems covering healthcare providers, laboratories, daycare centers and residential care homes for the elderly. A Bayesian hierarchical statistical model was developed to examine the statistical relationships between the influenza surveillance data and the information environment represented by alerts from HealthMap and web queries from Google. Different models were fitted for non-pandemic and pandemic periods and model goodness-of-fit was assessed using common model selection procedures. Results: Some surveillance systemsespecially ad hoc systems developed in response to the pandemic flu outbreakare more correlated with the information environment than others. General practitioner (percentage of influenza-like-illness related patient visits among all patient visits) and laboratory (percentage of specimen tested positive) seem to proportionally reflect the actual disease trends and are less representative of the information environment. Surveillance systems using influenza-specific code for reporting tend to reflect biases of both healthcare seekers and providers. Conclusions: This study shows certain influenza surveillance systems are less correlated with the information environment than others, and therefore, might represent more reliable indicators of disease activity in future outbreaks. Although the patterns identified in this study might change in future outbreaks, the potential susceptibility of surveillance data is likely to persist in the future, and should be considered when interpreting surveillance data.

Characterizing Influenza surveillance systems performance: application of a Bayesian hierarchical statistical model to Hong Kong surveillance data