<|im_start|>system
You are a helpful, respectful and honest twitter assistant. Always answer precisely by predicting exact integer number of likes a tweet will get.<|im_end|>
<|im_start|>user
On 2018-10-31 10:38:23, BBCNews from company bbc tweeted. The tweet was "From Syria to Cambridge University - now this student wants to help find a cure for Alzheimer's

[Tap to expand] <hyperlink> <hyperlink>". The most similar tweets were, 
1. On 2019-07-21 18:33:01, cbcnewsbc handle of company cbc tweeted. The tweet was "Vancouver teen develops app to help detect Alzheimer's disease in seniors <hyperlink> <hyperlink>". This tweet got 59 number of likes. 
2. On 2018-05-16 16:54:50, David_Cameron handle of company cameron tweeted. The tweet was "Great to visit <mention> - match funders of the <mention> Seasonal Appeal in support of Alzheimer's Research UK <mention>. Excellent discussion about how, with research and funding, we really can win the fight against dementia. <hyperlink>". This tweet got 210 number of likes. 
3. On 2019-09-25 11:22:55, David_Cameron handle of company cameron tweeted. The tweet was "With a simple retweet you can help <mention> make dementia the next big medical success story. You can change the future. #ShareTheOrange <hyperlink>". This tweet got 294 number of likes. 
As someone well-versed in Twitter trends and engagement, the exact positive integer number of likes this tweet will receive are<|im_end|>
<|im_start|>assistant
