instruction:
In this task, you're given a paragraph and title from the research paper. Your task is to classify whether the given title is suitable or not for the research paper based on the given paragraph. Return "True" if title is proper according to paragraph else "False".
question:
Paragraph: The chemokine CXCL10 is produced during infection and inflammation to activate the chemokine receptor CXCR3, an important regulator of lymphocyte trafficking and activation. The goal of this study was to assess the contributions of CXCL10 to the pathogenesis of experimental septic shock in mice. Methods: Septic shock was induced by cecal ligation and puncture (CLP) in mice resuscitated with lactated Ringer's solution and, in some cases, the broad spectrum antibiotic Primaxin. Studies were performed in CXCL10 knockout mice and mice treated with anti-CXCL10 immunoglobulin G (IgG). Endpoints included leukocyte trafficking and activation, core body temperature, plasma cytokine concentrations, bacterial clearance and survival. Results: CXCL10 was present at high concentrations in plasma and peritoneal cavity during CLP-induced septic shock. Survival was significantly improved in CXCL10 knockout (CXCL10KO) mice and mice treated with anti-CXCL10 IgG compared to controls. CXCL10KO mice and mice treated with anti-CXCL10 IgG showed attenuated hypothermia, lower concentrations of interleukin-6 (IL-6) and macrophage inhibitory protein-2 (MIP-2) in plasma and lessened natural killer (NK) cell activation compared to control mice. Compared to control mice, bacterial burden in blood and lungs was lower in CXCL10-deficient mice but not in mice treated with anti-CXCL10 IgG. Treatment of mice with anti-CXCL10 IgG plus fluids and Primaxin at 2 or 6 hours after CLP significantly improved survival compared to mice treated with non-specific IgG under the same conditions. Conclusions: CXCL10 plays a role in the pathogenesis of CLP-induced septic shock and could serve as a therapeutic target during the acute phase of septic shock.
Title: The role of CXCL10 in the pathogenesis of experimental septic shock
answer:
False

question:
Paragraph: Infectious diseases are a leading cause of death globally. Decisions surrounding how to control an infectious disease outbreak currently rely on a subjective process involving surveillance and expert opinion. However, there are many situations where neither may be available. Modeling can fill gaps in the decision making process by using available data to provide quantitative estimates of outbreak trajectories. Effective reduction of the spread of infectious diseases can be achieved through collaboration between the modeling community and public health policy community. However, such collaboration is rare, resulting in a lack of models that meet the needs of the public health community. Here we show a Susceptible-Infectious-Recovered (SIR) model modified to include control measures that allows parameter ranges, rather than parameter point estimates, and includes a web user interface for broad adoption. We apply the model to three diseases, measles, norovirus and influenza, to show the feasibility of its use and describe a research agenda to further promote interactions between decision makers and the modeling community. Despite substantial public health improvements in the last century, infectious diseases remain one of the leading causes of both morbidity and mortality 1,2 . When confronted with an infectious disease outbreak, public health officials typically work to control the outbreak by performing assessments, analyzing surveillance data, identifying resources and interacting with subject mater experts 2-4 . Control measures are then implemented based on the cumulative information collected. These approaches rely heavily on good surveillance systems, access to experts, and good intuition about which control measures to use. As such, they are largely subjective, time consuming, and the infrastructure required is often not present in high disease burden areas. Modeling is an attractive supplemental method because of the ability to estimate an outbreak's trajectory and the effects of possible control measures in a timely manner. Compartmental models are historically common; they divide individuals into categories based on their disease status. The most common variant is the SIR model, named after the categories used-"susceptible", "infectious" and "recovered". Models of this nature have small computational requirements, and are thus commonly used as first pass attempts to characterize outbreaks or infections quickly 5 . For example, after the sudden emergence of Severe Acute Respiratory Syndrome (SARS) in the early 2000s, researchers used modeling to characterize the virus' epidemiology. Several used compartmental models with control measures like quarantine or isolation in various settings (e.g., hospitals or cities) to describe effects of possible interventions 6-9 . Similar work exists for essentially all well known infectious diseases. For example, Mandal et al. provide a review of models used for malaria 10 and Bauch et al. explore model use with respect to SARS and other emerging infectious diseases 6 . Methods among these groups are often similar, but tend to focus on specific diseases and locations of interest. In contrast, agent-based models use a bottom-up approach where the agents (these are often people) interact with particular rules to simulate outbreaks 11 . This allows simulations at high resolutions, but requires large amounts of data to parameterize the models, as well as substantial computational power. It is thought that they may reflect real world scenarios more accurately, but the lack of available epidemiological data necessitates assumptions that are difficult or impossible to test 11 . These models further require computational resources inaccessible to an average health department. Both agent-based and compartmental models exhibit additional features that are problematic to wide-spread model adoption. The first is the focus on particular disease-location pairs. This emphasis precludes application to
Title: An approach to and web-based tool for infectious disease outbreak intervention analysis OPEN
answer:
False

question:
Paragraph: The effect of newly emerging or re-emerging infectious diseases of zoonotic origin in human populations can be potentially catastrophic, and large-scale investigations of such diseases are highly challenging. The monitoring of emergence events is subject to ascertainment bias, whether at the level of species discovery, emerging disease events, or disease outbreaks in human populations. Disease surveillance is generally performed post hoc, driven by a response to recent events and by the availability of detection and identification technologies. Additionally, the inventory of pathogens that exist in mammalian and other reservoirs is incomplete, and identifying those with the potential to cause disease in humans is rarely possible in advance. A major step in understanding the burden and diversity of zoonotic infections, the local behavioral and demographic risks of infection, and the risk of emergence of these pathogens in human populations is to establish surveillance networks in populations that maintain regular contact with diverse animal populations, Maia A Rabaa, Ngo Tri Tue, and Tran My Phuc contributed equally to this work. O 2015 The Author (s) and to simultaneously characterize pathogen diversity in human and animal populations. Vietnam has been an epicenter of disease emergence over the last decade, and practices at the human/animal interface may facilitate the likelihood of spillover of zoonotic pathogens into humans. To tackle the scientific issues surrounding the origins and emergence of zoonotic infections in Vietnam, we have established The Vietnam Initiative on Zoonotic Infections (VIZIONS). This countrywide project, in which several international institutions collaborate with Vietnamese organizations, is combining clinical data, epidemiology, high-throughput sequencing, and social sciences to address relevant one-health questions. Here, we describe the primary aims of the project, the infrastructure established to address our scientific questions, and the current status of the project. Our principal objective is to develop an integrated approach to the surveillance of pathogens circulating in both human and animal populations and assess how frequently they are exchanged. This infrastructure will facilitate systematic investigations of pathogen ecology and evolution, enhance understanding of viral cross-species transmission events, and identify relevant risk factors and drivers of zoonotic disease emergence.
Title: The Vietnam Initiative on Zoonotic Infections (VIZIONS): A Strategic Approach to Studying Emerging Zoonotic Infectious Diseases
answer:
True