An emerging infectious disease triggering large-scale hyperpredation.
Ontology highlight
ABSTRACT:
SUBMITTER: Moleon M
PROVIDER: S-EPMC2390756 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Epidemiological theory generally suggests that pathogens will not cause host extinctions because the pathogen should fade out when the host population is driven below some threshold density. An emerging infectious disease, chytridiomycosis, caused by the fungal pathogen Batrachochytrium dendrobatidis (Bd) is directly linked to the recent extinction or serious decline of hundreds of amphibian species. Despite continued spread of this pathogen into uninfected areas, the dynamics of the host-pathogen interaction remain unknown. We use fine-scale spatiotemporal data to describe (i) the invasion and spread of Bd through three lake basins, each containing multiple populations of the mountain yellow-legged frog, and (ii) the accompanying host-pathogen dynamics. Despite intensive sampling, Bd was not detected on frogs in study basins until just before epidemics began. Following Bd arrival in a basin, the disease spread to neighboring populations at approximately 700 m/yr in a wave-like pattern until all populations were infected. Within a population, infection prevalence rapidly reached 100% and infection intensity on individual frogs increased in parallel. Frog mass mortality began only when infection intensity reached a critical threshold and repeatedly led to extinction of populations. Our results indicate that the high growth rate and virulence of Bd allow the near-simultaneous infection and buildup of high infection intensities in all host individuals; subsequent host population crashes therefore occur before Bd is limited by density-dependent factors. Preventing infection intensities in host populations from reaching this threshold could provide an effective strategy to avoid the extinction of susceptible amphibian species in the wild.
| S-EPMC2906868 | biostudies-other
Project description:Infectious bursal disease virus (IBDV) is the pathogenic agent of infectious bursal disease (IBD). Scine it was observed in 1957, IBD spread worldwidely in the chicken flocks, is a important immunosuppressive disease and an threat to poultry industry. Although many studies have be done about IBDV, interaction of IBDV infection and IBDV-encoding genes to host cell gene expression are little known. In this study, the LongSAGE library of Vero-cell, IBDV- infected vero cell, Vero-cell transfected with IBDV-VP5 gene, Vero-cell transfected with IBDV A frament and Vero-cell transfected with IBDV VP243 frament were obtained. We got 96,213 gene tags (17 nucleotides), which represented 24,475 transcripts. Keywords: Transcripts of different state vero-cell
2007-11-05 | GSE6243 | GEO
Project description:Infectious bursal disease virus (IBDV) is the pathogenic agent of infectious bursal disease (IBD). Scine it was observed in 1957, IBD spread worldwidely in the chicken flocks, is a important immunosuppressive disease and an threat to poultry industry. Although many studies have be done about IBDV, interaction of IBDV infection and IBDV-encoding genes to host cell gene expression are little known. In this study, the LongSAGE library of Vero-cell, IBDV- infected vero cell, Vero-cell transfected with IBDV-VP5 gene, Vero-cell transfected with IBDV A frament and Vero-cell transfected with IBDV VP243 frament were obtained. We got 96,213 gene tags (17 nucleotides), which represented 24,475 transcripts. Keywords: Transcripts of different state vero-cell 1.Cloning of the full-length genomic A-segment, VP5 ORF cDNA, VP243 ORF cDNA of IBDV 2.Establishing cloned Vero cell lines expressing VP5, VP243 and A fragment of IBDV 3.Construction of Long-SAGE libraries 4. Sequencing
2007-11-04 | E-GEOD-6243 | biostudies-arrayexpress
Project description:Plasma biomarkers that reflect molecular states of the cardiovascular system are central for clinical decision making. Routinely used plasma biomarkers include troponins, natriuretic peptides, and lipoprotein particles, yet interrogate only a modest subset of pathways relevant to cardiovascular disease. Systematic profiling of a larger portion of circulating plasma proteins (the plasma proteome) will provide opportunities for unbiased discovery of novel markers to improve diagnostic or predictive accuracy. In addition, proteomic profiling may inform pathophysiological understanding and point to novel therapeutic targets. Obstacles for comprehensive proteomic profiling include the immense size and structural heterogeneity of the proteome, and the broad range of abundance levels, as well. Proteome-wide, untargeted profiling can be performed in tissues and cells with tandem mass spectrometry. However, applications to plasma are limited by the need for complex preanalytical sample preparation stages limiting sample throughput. Multiplexing of targeted methods based on capture and detection of specific proteins are therefore receiving increasing attention in plasma proteomics. Immunoaffinity assays are the workhorse for measuring individual proteins but have been limited for proteomic applications by long development times, cross-reactivity preventing multiplexing, specificity issues, and incomplete sensitivity to detect proteins in the lower range of the abundance spectrum (below picograms per milliliter). Emerging technologies to address these issues include nucleotide-labeled immunoassays and aptamer reagents that can be automated for efficient multiplexing of thousands of proteins at high sample throughput, coupling of affinity capture methods to mass spectrometry for improved specificity, and ultrasensitive detection systems to measure low-abundance proteins. In addition, proteomics can now be integrated with modern genomics tools to comprehensively relate proteomic profiles to genetic variants, which may both influence binding of affinity reagents and serve to validate the target specificity of affinity assays. The application of deep quantitative proteomic profiling to large cohorts has thus become increasingly feasible with emerging affinity methods. The aims of this article are to provide the broad readership of Circulation with a timely overview of emerging methods for affinity proteomics and recent progress in cardiovascular medicine based on such methods.
| S-EPMC5555416 | biostudies-literature
Project description:The increasing number of emerging infectious disease events that have spread internationally, such as severe acute respiratory syndrome (SARS) and the 2009 pandemic A/H1N1, highlight the need for improvements in global outbreak surveillance. It is expected that the proliferation of Internet-based reports has resulted in greater communication and improved surveillance and reporting frameworks, especially with the revision of the World Health Organization's (WHO) International Health Regulations (IHR 2005), which went into force in 2007. However, there has been no global quantitative assessment of whether and how outbreak detection and communication processes have actually changed over time. In this study, we analyzed the entire WHO public record of Disease Outbreak News reports from 1996 to 2009 to characterize spatial-temporal trends in the timeliness of outbreak discovery and public communication about the outbreak relative to the estimated outbreak start date. Cox proportional hazards regression analyses show that overall, the timeliness of outbreak discovery improved by 7.3% [hazard ratio (HR) = 1.073, 95% CI (1.038; 1.110)] per year, and public communication improved by 6.2% [HR = 1.062, 95% CI (1.028; 1.096)] per year. However, the degree of improvement varied by geographic region; the only WHO region with statistically significant (? = 0.05) improvement in outbreak discovery was the Western Pacific region [HR = 1.102 per year, 95% CI (1.008; 1.205)], whereas the Eastern Mediterranean [HR = 1.201 per year, 95% CI (1.066; 1.353)] and Western Pacific regions [HR = 1.119 per year, 95% CI (1.025; 1.221)] showed improvement in public communication. These findings provide quantitative historical assessment of timeliness in infectious disease detection and public reporting of outbreaks.
| S-EPMC3003006 | biostudies-literature
Project description:Tularemia is a bacterial disease of humans, wild, and domestic animals. Francisella tularensis, which is a Gram-negative coccobacillus-shaped bacterium, is the causative agent of tularemia. Recently, an increase in the number of human tularemia cases has been noticed in several countries around the world. It has been reported mostly from North America, several Scandinavian countries, and certain Asian countries. The disease spreads through vectors such as mosquitoes, horseflies, deer flies, and ticks. Humans can acquire the disease through direct contact of sick animals, consumption of infected animals, drinking or direct contact of contaminated water, and inhalation of bacteria-loaded aerosols. Low infectious dose, aerosol route of infection, and its ability to induce fatal disease make it a potential agent of biological warfare. Tularemia leads to several clinical forms, such as glandular, ulceroglandular, oculoglandular, oropharyngeal, respiratory, and typhoidal forms. The disease is diagnosed through the use of culture, serology, or molecular methods. Quinolones, tetracyclines, or aminoglycosides are frequently used in the treatment of tularemia. No licensed vaccine is available in the prophylaxis of tularemia and this is need of the time and high-priority research area. This review mostly focuses on general features, importance, current status, and preventive measures of this disease.
| S-EPMC7521936 | biostudies-literature
Project description:The disease chytridiomycosis, caused by the fungus Batrachochytrium dendrobatidis (Bd), has caused dramatic amphibian population declines and extinctions in Australia, Central and North America, and Europe. Bd is associated with >200 species extinctions of amphibians, but not all species that become infected are susceptible to the disease. Specifically, Bd has rapidly emerged in some areas of the world, such as in Australia, USA, and throughout Central and South America, causing population and species collapse. The mechanism behind the rapid global emergence of the disease is poorly understood, in part due to an incomplete picture of the global distribution of Bd. At present, there is a considerable amount of geographic bias in survey effort for Bd, with Asia being the most neglected continent. To date, Bd surveys have been published for few Asian countries, and infected amphibians have been reported only from Indonesia, South Korea, China and Japan. Thus far, there have been no substantiated reports of enigmatic or suspected disease-caused population declines of the kind that has been attributed to Bd in other areas. In order to gain a more detailed picture of the distribution of Bd in Asia, we undertook a widespread, opportunistic survey of over 3,000 amphibians for Bd throughout Asia and adjoining Papua New Guinea. Survey sites spanned 15 countries, approximately 36° latitude, 111° longitude, and over 2000 m in elevation. Bd prevalence was very low throughout our survey area (2.35% overall) and infected animals were not clumped as would be expected in epizootic events. This suggests that Bd is either newly emerging in Asia, endemic at low prevalence, or that some other ecological factor is preventing Bd from fully invading Asian amphibians. The current observed pattern in Asia differs from that in many other parts of the world.
| S-EPMC3156717 | biostudies-literature
Project description:Emerging infectious diseases (EIDs), including the latest COVID-19 pandemic, have emerged and raised global public health crises in recent decades. Without existing protective immunity, an EID may spread rapidly and cause mass casualties in a very short time. Therefore, it is imperative to identify cases with risk of disease progression for the optimized allocation of medical resources in case medical facilities are overwhelmed with a flood of patients. This study has aimed to cope with this challenge from the aspect of preventive medicine by exploiting machine learning technologies. The study has been based on 83,227 hospital admissions with influenza-like illness and we analysed the risk effects of 19 comorbidities along with age and gender for severe illness or mortality risk. The experimental results revealed that the decision rules derived from the machine learning based prediction models can provide valuable guidelines for the healthcare policy makers to develop an effective vaccination strategy. Furthermore, in case the healthcare facilities are overwhelmed by patients with EID, which frequently occurred in the recent COVID-19 pandemic, the frontline physicians can incorporate the proposed prediction models to triage patients suffering minor symptoms without laboratory tests, which may become scarce during an EID disaster. In conclusion, our study has demonstrated an effective approach to exploit machine learning technologies to cope with the challenges faced during the outbreak of an EID.
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Project description:The emergence and global impact of the novel influenza A(H1N1)v highlights the continuous threat to public health posed by a steady stream of new and unexpected infectious disease outbreaks in animals and humans. Once an emerging epidemic is detected, public health authorities will attempt to mitigate the epidemic by, among other measures, reducing further spread as much as possible. Scarce and/or costly control measures such as vaccines, anti-infective drugs, and social distancing must be allocated while epidemiological characteristics of the disease remain uncertain. Here we present first principles for allocating scarce resources with limited data. We show that under a broad class of assumptions, the simple rule of targeting intervention measures at the group with the highest risk of infection per individual will achieve the largest reduction in the transmission potential of a novel infection. For vaccination of susceptible persons, the appropriate risk measure is force of infection; for social distancing, the appropriate risk measure is incidence of infection. Unlike existing methods that rely on detailed knowledge of group-specific transmission rates, the method described here can be implemented using only data that are readily available during an epidemic, and allows ready adaptation as the epidemic progresses. The need to observe risk of infection helps to focus the ongoing planning and design of new infectious disease surveillance programs; from the presented first principles for allocating scarce resources, we can adjust the prioritization of groups for intervention when new observations on an emerging epidemic become available.
| S-EPMC2818907 | biostudies-literature
Project description: Not available
| S-EPMC11017537 | biostudies-literature