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".

Example Input: Paragraph: Intravascular-thrombosis and extravascular-lipid-deposit are the two key pathogenic events considered to interrupt intraosseous blood supply during development of steroid-associated osteonecrosis (ON). However, there are no clinically employed agents capable of simultaneously targeting these two key pathogenic events. The present experimental study demonstrated that constitutional flavonoid glycosides derived from herb Epimedium (EF, composed of seven flavonoid compounds with common stem nuclear) exerted dose-dependent effect on inhibition of both thrombosis and lipiddeposition and accordingly reducing incidence of steroid-associated ON in rabbits, which was not via direct action by themselves rather by their common metabolite on potential cellular targets involved in the two pathogenic pathways. The underlying mechanism could be explained by counteracting endothelium injury and excessive adipogenesis. These findings encourage designing clinical trials to investigate potential of EF in prevention of steroid-associated ON.
Title: Constitutional Flavonoids Derived from Epimedium Dose-Dependently Reduce Incidence of Steroid- Associated Osteonecrosis Not via Direct Action by Themselves on Potential Cellular Targets
Example Output: True

Example Input: Paragraph: Italy is currently experiencing the largest COVID-19 outbreak in Europe so far, with more than 100,000 confirmed cases. Following the identification of the first infections, on February 21, 2020, national authorities have put in place an increasing number of restrictions aimed at containing the outbreak and delaying the epidemic peak. Since March 12, the whole country is under lockdown. Here we provide the first quantitative assessment of the impact of such measures on the mobility and the spatial proximity of Italians, through the analysis of a large-scale dataset on deidentified, geo-located smartphone users. With respect to pre-outbreak averages, we estimate a reduction of 50% of the total trips between Italian provinces, following the lockdown. In the same week, the average users' radius of gyration has declined by about 50% and the average degree of the users' proximity network has dropped by 47% at national level.
Title: COVID-19 outbreak response: a first assessment of mobility changes in Italy following national lockdown
Example Output: True

Example Input: Paragraph: Estimating key infectious disease parameters from the COVID-19 outbreak is quintessential for modelling studies and guiding intervention strategies. Whereas different estimates for the incubation period distribution and the serial interval distribution have been reported, estimates of the generation interval for COVID-19 have not been provided. Methods: We used outbreak data from clusters in Singapore and Tianjin, China to estimate the generation interval from symptom onset data while acknowledging uncertainty about the incubation period distribution and the underlying transmission network. From those estimates we obtained the proportions pre-symptomatic transmission and reproduction numbers. Results: The mean generation interval was 5.20 (95%CI 3.78-6.78) days for Singapore and 3.95 (95%CI 3.01-4.91) days for Tianjin, China when relying on a previously reported incubation period with mean 5.2 and SD 2.8 days. The proportion of pre-symptomatic transmission was 48% (95%CI 32-67%) for Singapore and 62% (95%CI 50-76%) for Tianjin, China. Estimates of the reproduction number based on the generation interval distribution were slightly higher than those based on the serial interval distribution. Conclusions: Estimating generation and serial interval distributions from outbreak 1 . CC-BY-NC-ND 4.0 International license It is made available under a author/funder, who has granted medRxiv a license to display the preprint in perpetuity. is the (which was not peer-reviewed) The copyright holder for this preprint .
Title: Estimating the generation interval for COVID-19 based on symptom onset data
Example Output:
True