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.

Ex Input:
Background. In April 2012, the Jordan Ministry of Health investigated an outbreak of lower respiratory illnesses at a hospital in Jordan; 2 fatal cases were retrospectively confirmed by real-time reverse transcription polymerase chain reaction (rRT-PCR) to be the first detected cases of Middle East respiratory syndrome (MERS-CoV). Methods. Epidemiologic and clinical characteristics of selected potential cases were assessed through serum blood specimens, medical record reviews, and interviews with surviving outbreak members, household contacts, and healthcare personnel. Cases of MERS-CoV infection were identified using 3 US Centers for Disease Control and Prevention serologic tests for detection of anti-MERS-CoV antibodies. Results. Specimens and interviews were obtained from 124 subjects. Seven previously unconfirmed individuals tested positive for anti-MERS-CoV antibodies by at least 2 of 3 serologic tests, in addition to 2 fatal cases identified by rRT-PCR. The case-fatality rate among the 9 total cases was 22%. Six subjects were healthcare workers at the outbreak hospital, yielding an attack rate of 10% among potentially exposed outbreak hospital personnel. There was no evidence of MERS-CoV transmission at 2 transfer hospitals having acceptable infection control practices. Conclusions. Novel serologic tests allowed for the detection of otherwise unrecognized cases of MERS-CoV infection among contacts in a Jordanian hospital-associated respiratory illness outbreak in April 2012, resulting in a total of 9 test-positive cases. Serologic results suggest that further spread of this outbreak to transfer hospitals did not occur. Most subjects had no major, underlying medical conditions; none were on hemodialysis. Our observed casefatality rate was lower than has been reported from outbreaks elsewhere.

Ex Output:
Eastern Mediterranean Public Health Network, and 6 Field Epidemiology Training Program


Ex Input:
Scorpions are well known for their dangerous stings that can result in severe consequences for human beings, including death. Neurotoxins present in their venoms are responsible for their toxicity. Due to their medical relevance, toxins have been the driving force in the scorpion natural compounds research field. On the other hand, for thousands of years, scorpions and their venoms have been applied in traditional medicine, mainly in Asia and Africa. With the remarkable growth in the number of characterized scorpion venom components, several drug candidates have been found with the potential to tackle many of the emerging global medical threats. Scorpions have become a valuable source of biologically active molecules, from novel antibiotics to potential anticancer therapeutics. Other venom components have drawn attention as useful scaffolds for the development of drugs. This review summarizes the most promising candidates for drug development that have been isolated from scorpion venoms.

Ex Output:
Scorpion venom components as potential candidates for drug development


Ex Input:
The peptides derived from envelope proteins have been shown to inhibit the protein-protein interactions in the virus membrane fusion process and thus have a great potential to be developed into effective antiviral therapies. There are three types of envelope proteins each exhibiting distinct structure folds. Although the exact fusion mechanism remains elusive, it was suggested that the three classes of viral fusion proteins share a similar mechanism of membrane fusion. The common mechanism of action makes it possible to correlate the properties of self-derived peptide inhibitors with their activities. Here we developed a support vector machine model using sequence-based statistical scores of self-derived peptide inhibitors as input features to correlate with their activities. The model displayed 92% prediction accuracy with the Matthew's correlation coefficient of 0.84, obviously superior to those using physicochemical properties and amino acid decomposition as input. The predictive support vector machine model for self-derived peptides of envelope proteins would be useful in development of antiviral peptide inhibitors targeting the virus fusion process. * The sequences in bold were used in the 75p+75n training set; the rest sequences were used in the 26p+26n test set.

Ex Output:

Identification of Peptide Inhibitors of Enveloped Viruses Using Support Vector Machine