In this task, you are given a paragraph (from a research paper) and your task is to classify each sentence of the paragraph (assume n sentence) into the following categories: Background, Purpose, Method, Finding/Contribution, or Other. Return the output in this format: 1 - category of sentence 1, 2 - category of sentence 2, ..., n - category of sentence n; where each number indicates the order of the sentence. The categories can be identified using the following questions: 
 Background: - Why is this problem important? - What relevant works have been done before? - What did the previous works miss? - What are the high-level research questions? - How might this help other researchers?
 Purpose: - What specific things do the researchers want to do? - What specific knowledge do the researchers want to know? - What specific hypothesis do the researchers want to test?
 Method: - How did the researchers do it or find it out? - What are the procedures and steps of this research?
 Finding/Contribution: - What did the researchers find out? Did the proposed methods work? - Did things behave as the researchers expected?
Other: put every text fragment that does not fit into any of the categories above here. Put a sentence here if its not in English, is not part of the article, contains numbers and dates, is a caption of a figure or a table, is a formatting error, or you are not sure about it.

Input: Consider Input: The average accuracy based on leave-one-out (LOO) cross validation of a Bayesian classifier generated from 143 amyloidogenic sequences is 60.84%. This is consistent with the average accuracy of 61.15% for a holdout test set comprised of 103 AM and 28 non-amyloidogenic sequences. The LOO cross validation accuracy increases to 81.08% when the training set is augmented by the holdout test set. In comparison, the average classification accuracy for the holdout test set obtained using a decision tree is 78.64%. Non-amyloidogenic sequences are predicted with average LOO cross validation accuracies between 74.05% and 77.24% using the Bayesian classifier, depending on the training set size. The accuracy for the holdout test set was 89%. For the decision tree, the nonamyloidogenic prediction accuracy is 75.00%. Conclusions: This exploratory study indicates that both classification methods may be promising in providing straightforward predictions on the amyloidogenicity of a sequence. Nevertheless, the number of available sequences that satisfy the premises of this study are limited, and are consequently smaller than the ideal training set size. Increasing the size of the training set clearly increases the accuracy, and the expansion of the training set to include not only more derivatives, but more alignments, would make the method more sound. The accuracy of the classifiers may also be improved when additional factors, such as structural and physico-chemical data, are considered. The development of this type of classifier has significant applications in evaluating engineered antibodies, and may be adapted for evaluating engineered proteins in general.

Output: 1 - finding, 2 - finding, 3 - finding, 4 - finding, 5 - finding, 6 - finding, 7 - finding, 8 - finding, 9 - finding, 10 - finding, 11 - finding, 12 - finding, 13 - finding, 14 - finding, 15 - finding, 16 - finding, 17 - finding, 18 - finding


Input: Consider Input: BJORKSTRAND, E. AND K. UVN,~S-MOBERG. Central oxytocin increases food intake and daily weight gain in rats. PHYSIOL BEHAV 59(4/5) 947-952, 1996.--The present study was performed to investigate the effects of

Output: 1 - other, 2 - background, 3 - other, 4 - purpose


Input: Consider Input: Repurposing antimalarials as dengue antivirals Chloroquine Primaquine Stable replicon cell lines for dengue and West Nile viruses Inhibition of dengue virus replication and infectivity Amodiaquine therapeutic index a b s t r a c t Dengue virus serotypes 1-4 (DENV1-4) are transmitted by mosquitoes which cause most frequent arboviral infections in the world resulting in $390 million cases with $25,000 deaths annually. There is no vaccine or antiviral drug currently available for human use. Compounds containing quinoline scaffold were shown to inhibit flavivirus NS2B-NS3 protease (NS2B-NS3pro) with good potencies. In this study, we screened quinoline derivatives, which are known antimalarial drugs for inhibition of DENV2 and West Nile virus (WNV) replication using the corresponding replicon expressing cell-based assays. Amodiaquine (AQ), one of the 4-aminoquinoline drugs, inhibited DENV2 infectivity measured by plaque assays, with EC 50 and EC 90 values of 1.08 ± 0.09 lM and 2.69 ± 0.47 lM, respectively, and DENV2 RNA replication measured by Renilla luciferase reporter assay, with EC 50 value of 7.41 ± 1.09 lM in the replicon expressing cells. Cytotoxic concentration (CC 50 ) in BHK-21 cells was 52.09 ± 4.25 lM. The replication inhibition was confirmed by plaque assay of the extracellular virions as well as by qRT-PCR of the intracellular and extracellular viral RNA levels. AQ was stable for at least 96 h and had minor inhibitory effect on entry, translation, and post-replication stages in the viral life cycle. DENV protease, 5 0 -methyltransferase, and RNA-dependent RNA polymerase do not seem to be targets of AQ. Both p-hydroxyanilino and diethylaminomethyl moieties are important for AQ to inhibit DENV2 replication and infectivity. Our results support AQ as a promising candidate for anti-flaviviral therapy.


Output: 1 - background, 2 - background, 3 - background, 4 - purpose, 5 - method, 6 - finding, 7 - finding, 8 - finding, 9 - finding, 10 - finding, 11 - finding, 12 - finding, 13 - finding, 14 - finding, 15 - finding, 16 - finding, 17 - finding, 18 - finding