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]: Electron microscopy (EM) allows fast visualization of viruses in a wide range of clinical specimens. Viruses are grouped into families based on their morphology. Viruses from various families look distinctly and these morphological variances are the basis for identification of viruses by EM. The identification to the family level is often sufficient for the clinician or recognition of an unknown infectious agent. Diagnostic EM has two advantages over enzyme-linked immunosorbent assay and nucleic acid amplification tests. After a simple and fast negative staining, EM allows fast morphological identification and differential diagnosis of infectious agents contained in the specimen without the need for special considerations and/or reagents. Nevertheless, EM has the disadvantage of being unsuitable as a screening method. Abbreviations CSF cerebrospinal fluid PBS phosphate-buffered saline ELISA enzyme-linked immunosorbent assay PCR polymerase chain reaction EM electron microscopy PTA phosphotungstic acid IEM immune electron microscopy SARS severe acute respiratory syndrome NAT nucleic acid amplification (techniques) SPIEM solid phase immune electron microscopy NRL/ELM
[A]: The Role of Electron Microscopy in the Rapid Diagnosis of Viral Infections -review and Foreign Cell in Clinical Specimens CONTENTS


[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]: Infectious disease outbreaks often have consequences beyond human health, including concern among the population, economic instability, and sometimes violence. A warning system capable of anticipating social disruptions resulting from disease outbreaks is urgently needed to help decision makers prepare appropriately. We designed a system that operates in near real-time to identify and predict social response. Over 150,000 Internet-based news articles related to outbreaks of 16 diseases in 72 countries and territories were provided by HealthMap. These articles were automatically tagged with indicators of the disease activity and population reaction. An anomaly detection algorithm was implemented on the population reaction indicators to identify periods of unusually severe social response. Then a model was developed to predict the probability of these periods of unusually severe social response occurring in the coming week, 2 and 3 weeks. This model exhibited remarkably strong performance for diseases with substantial media coverage. For country-disease pairs with a median of 20 or more articles per year, the onset of social response in the next week was correctly predicted over 60% of the time, and 87% of weeks were correctly predicted. Performance was weaker for diseases with little media coverage, and, for these diseases, the main utility of our system is in identifying social response when it occurs, rather than predicting when it will happen in the future. Overall, the developed near real-time prediction approach is a promising step toward developing predictive models to inform responders of the likely social consequences of disease spread. This research was funded by Defense Threat Reduction Agency (www.dtra.mil) contact HDTRA1-12-C-0061.
[A]:
Predicting social response to infectious disease outbreaks from internet-based news streams