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.

[Q]: Background: The development of a protective vaccine against canine visceral leishmaniasis (CVL) is an alternative approach for interrupting the domestic cycle of Leishmania infantum. Given the importance of sand fly salivary proteins as potent immunogens obligatorily co-deposited during transmission of Leishmania parasites, their inclusion in an anti-Leishmania vaccine has been investigated in the last few decades. In this context, we previously immunized dogs with a vaccine composed of L. braziliensis antigens plus saponin as the adjuvant and sand fly salivary gland extract (LBSapSal vaccine). This vaccine elicited an increase in both anti-saliva and anti-Leishmania IgG isotypes, higher counts of specific circulating CD8 + T cells, and high NO production. Methods: We investigated the immunogenicity and protective effect of LBSapSal vaccination after intradermal challenge with 1 10 7 late-log-phase L. infantum promastigotes in the presence of sand fly saliva of Lutzomyia longipalpis. The dogs were followed for up to 885 days after challenge. Results: The LBSapSal vaccine presents extensive antigenic diversity with persistent humoral and cellular immune responses, indicating resistance against CVL is triggered by high levels of total IgG and its subtypes (IgG1 and IgG2); expansion of circulating CD5 + , CD4 + , and CD8 + T lymphocytes and is Leishmania-specific; and reduction of splenic parasite load. Conclusions: These results encourage further study of vaccine strategies addressing Leishmania antigens in combination with proteins present in the saliva of the vector.
[A]: LBSapSal-vaccinated dogs exhibit increased circulating T-lymphocyte subsets (CD4 + and CD8 + ) as well as a reduction of parasitism after challenge with Leishmania infantum plus salivary gland of Lutzomyia longipalpis

[Q]: a b s t r a c t H1N1 is an infectious virus which, when spread affects a large volume of the population. It is an airborne disease that spreads easily and has a high death rate. Development of healthcare support systems using cloud computing is emerging as an effective solution with the benefits of better quality of service, reduced costs and flexibility. In this paper, an effective cloud computing architecture is proposed which predicts H1N1 infected patients and provides preventions to control infection rate. It consists of four processing components along with secure cloud storage medical database. The random decision tree is used to initially assess the infection in any patient depending on his/her symptoms. Social Network Analysis (SNA) is used to present the state of the outbreak. The proposed architecture is tested on synthetic data generated for two million users. The system provided 94% accuracy for the classification and around 81% of the resource utilization on Amazon EC2 cloud. The key point of the paper is the use of SNA graphs to calculate role of an infected user in spreading the outbreak known as Outbreak Role Index (ORI). It will help government agencies and healthcare departments to present, analyze and prevent outbreak effectively.
[A]: Smart monitoring and controlling of Pandemic Influenza A (H1N1) using Social Network Analysis and cloud computing

[Q]: The equilibrium solubility of ribavirin in solvent mixtures of {methanol (1) + water (2)}, {n-propanol (1) + water (2)}, {acetonitrile (1) + water (2)} and {1,4-dioxane (1) + water (2)} was determined experimentally by using isothermal dissolution equilibrium method within the temperature range from (278.15 to 318.15) K under atmospheric pressure (101.1 kPa). At the same temperature and mass fraction of methanol (n-propanol, acetonitrile or 1,4-dioxane), the mole fraction solubility of ribavirin is greater in (methanol + water) than in the other three solvent mixtures. The preferential solvation parameters were derived from their thermodynamic solution properties by means of the inverse Kirkwood-Buff integrals. The preferential solvation parameters for methanol, n-propanol, acetonitrile or 1,4-dioxane (dx 1,3 ) were negative in the four solvent mixtures with a very wide compositions, which indicated that ribavirin was preferentially solvated by water. Temperature had little effect on the preferential solvation magnitudes. The higher solvation by water could be explained in terms of the higher acidic behaviour of water interacting with the Lewis basic groups of the ribavirin. Besides, the solubility of the drugs was mathematically represented by using the Jouyban-Acree model, van't Hoff-Jouyban-Acree model and Apelblat-Jouyban-Acree model obtaining average relative deviations lower than 1.57% for correlative studies. It is noteworthy that the solubility data presented in this work contribute to expansion of the physicochemical information about the solubility of drugs in binary solvent mixtures and also allows the thermodynamic analysis of the respective dissolution and specific solvation process.
[A]:
Thermodynamic modelling of solubility and preferential solvation for ribavirin (II) in co-solvent mixtures of (methanol, n-propanol, acetonitrile or 1,4-dioxane) + water