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.

Ex Input:
Objective: Tumor-treating fields are currently used to successfully treat various cancers; however, the specific pathways associated with its efficacy remain unknown in the immune responses. Here, we evaluated tumor-treating fields-mediated initiation of the macrophage-specific immune response. Materials and Methods: We subjected RAW 264.7 mouse macrophages to clinically relevant levels of tumor-treating fields (0.9 V/cm, 150 kHz) and evaluated alterations in cytokine expression and release, as well as cell viability. Additionally, we investigated the status of immunomodulatory pathways to determine their roles in tumor-treating fields-mediated immune activation. Results and Discussion: Our results indicated that tumor-treating fields treatment at 0.9 V/cm decreased cell viability and increased cytokine messenger RNA/protein levels, as well as levels of nitric oxide and reactive oxygen species, relative to controls. The levels of tumor necrosis factor a, interleukin 1b, and interleukin 6 were markedly increased in tumor-treating fields-treated RAW 264.7 cells cocultured with 4T1 murine mammary carcinoma cells compared with those in 4T1 or RAW 264.7 cells with or without tumor-treating fields treatment. Moreover, the viability of 4T1 cells treated with the conditioned medium of tumor-treating fields-stimulated RAW 264.7 cells decreased, indicating that macrophage activation by tumor-treating fields effectively killed the tumor cells. Moreover, tumor-treating fields treatment activated the nuclear factor kB and mitogen-activated protein kinase pathways involved in immunomodulatory signaling. Conclusion: These results provide critical insights into the mechanisms through which tumor-treating fields affect macrophagespecific immune responses and the efficacy of this method for cancer treatment.

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


Ex Input:
As expected, cats from endemic areas produce IFN-γ after ex vivo blood stimulation with LSA and therefore are able to activate a cell-mediated adaptive immune response against the parasite that is variably associated with antibody or blood PCR positivity. The association of this assay to serological and molecular tests provides a better estimate of cat exposure to L. infantum.

Ex Output:
1 - finding, 2 - finding


Ex Input:
In particular, 63% (12 of 19) of fecal samples from Miniopterus pusillus were positive for the virus. These findings suggest that this virus might be commonly circulating in M. pusillus in Hong Kong.

Ex Output:

1 - finding, 2 - finding