TASK DEFINITION: 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".
PROBLEM: Paragraph: Porcine epidemic diarrhea virus (PEDV), an enteropathogenic Alphacoronavirus, has caused enormous economic losses in the swine industry. p53 protein exists in a wide variety of animal cells, which is involved in cell cycle regulation, apoptosis, cell differentiation and other biological functions. In this study, we investigated the effects of PEDV infection on the cell cycle of Vero cells and p53 activation. The results demonstrated that PEDV infection induces cell cycle arrest at G0/G1 phase in Vero cells, while UV-inactivated PEDV does not cause cell cycle arrest. PEDV infection up-regulates the levels of p21, cdc2, cdk2, cdk4, Cyclin A protein and down-regulates Cyclin E protein. Further research results showed that inhibition of p53 signaling pathway can reverse the cell cycle arrest in G0/G1 phase induced by PEDV infection and cancel out the up-regulation of p21 and corresponding Cyclin/cdk mentioned above. In addition, PEDV infection of the cells synchronized in various stages of cell cycle showed that viral subgenomic RNA and virus titer were higher in the cells released from G0/G1 phase synchronized cells than that in the cells released from the G1/S phase and G2/M phase synchronized or asynchronous cells after 18 h p.i.. This is the first report to demonstrate that the p53-dependent pathway plays an important role in PEDV induced cell cycle arrest and beneficially contributes to viral infection. 
 Title: Porcine epidemic diarrhea virus through p53-dependent pathway causes cell cycle arrest in the G0/G1 phase

SOLUTION: False

PROBLEM: Paragraph: Background: The World Health Organization recommends periodic evaluations of influenza surveillance systems to identify areas for improvement and provide evidence of data reliability for policymaking. However, data about the performance of established influenza surveillance systems are limited in Africa, including in the Democratic Republic of Congo (DRC). Methods: We used the Centers for Disease Control and Prevention guidelines to evaluate the performance of the influenza sentinel surveillance system (ISSS) in DRC during 2012-2015. The performance of the system was evaluated using eight surveillance attributes: (i) data quality and completeness for key variables, (ii) timeliness, (iii) representativeness, (iv) flexibility, (v) simplicity, (vi) acceptability, (vii) stability and (viii) utility. For each attribute, specific indicators were developed and described using quantitative and qualitative methods. Scores for each indicator were as follows: < 60% weak performance; 60-79% moderate performance; ≥80% good performance. Results: During 2012-2015, we enrolled and tested 4339 patients with influenza-like illness (ILI) and 2869 patients with severe acute respiratory illness (SARI) from 11 sentinel sites situated in 5 of 11 provinces. Influenza viruses were detected in 446 (10.3%) samples from patients with ILI and in 151 (5.5%) samples from patients with SARI with higher detection during December-May. Data quality and completeness was > 90% for all evaluated indicators. Other strengths of the system were timeliness, simplicity, stability and utility that scored > 70% each. Representativeness, flexibility and acceptability had moderate performance. It was reported that the ISSS contributed to: (i) a better understanding of the epidemiology, circulating patterns and proportional contribution of influenza virus among patients with ILI or SARI; (ii) acquisition of new key competences related to influenza surveillance and diagnosis; and (iii) continuous education of surveillance staff and clinicians at sentinel sites about influenza. However, due to limited resources no actions were undertaken to mitigate the impact of seasonal influenza epidemics. Conclusions: The system performed overall satisfactorily and provided reliable and timely data about influenza circulation in DRC. The simplicity of the system contributed to its stability. A better use of the available data could be made to inform and promote prevention interventions especially among the most vulnerable groups. 
 Title: Evaluation of the influenza sentinel surveillance system in the Democratic Republic of Congo, 2012-2015

SOLUTION: True

PROBLEM: Paragraph: Background. Distinguishing between bacterial and viral lower respiratory tract infection (LRTI) remains challenging. Transcriptional profiling is a promising tool for improving diagnosis in LRTI. Methods. We performed whole blood transcriptional analysis in 118 patients (median age [interquartile range], 61 [50-76] years) hospitalized with LRTI and 40 age-matched healthy controls (median age, 60 [46-70] years). We applied class comparisons, modular analysis, and class prediction algorithms to identify and validate diagnostic biosignatures for bacterial and viral LRTI. Results. Patients were classified as having bacterial (n = 22), viral (n = 71), or bacterial-viral LRTI (n = 25) based on comprehensive microbiologic testing. Compared with healthy controls, statistical group comparisons (P < .01; multiple-test corrections) identified 3376 differentially expressed genes in patients with bacterial LRTI, 2391 in viral LRTI, and 2628 in bacterial-viral LRTI. Patients with bacterial LRTI showed significant overexpression of inflammation and neutrophil genes (bacterial > bacterial-viral > viral), and those with viral LRTI displayed significantly greater overexpression of interferon genes (viral > bacterial-viral > bacterial). The K-nearest neighbors algorithm identified 10 classifier genes that discriminated between bacterial and viral LRTI with a 95% sensitivity (95% confidence interval, 77%-100%) and 92% specificity (77%-98%), compared with a sensitivity of 38% (18%-62%) and a specificity of 91% (76%-98%) for procalcitonin. Conclusions. Transcriptional profiling is a helpful tool for diagnosis of LRTI. 
 Title: Superiority of Transcriptional Profiling Over Procalcitonin for Distinguishing Bacterial From Viral Lower Respiratory Tract Infections in Hospitalized Adults

SOLUTION:
False