Browse
Submit Data
Databases
API
Help

Dataset Information

0 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Identifying sources of human exposure to plague.

ABSTRACT: Yersinia pestis, the etiologic agent of plague, has shaped the course of human history, killing millions of people in three major pandemics. This bacterium is still endemic in parts of Asia, Africa, and the Americas, where it poses a natural disease threat to human populations. Y. pestis has also recently received attention as a possible bioterrorism agent. Thus, rapid methods to distinguish between bioterrorism and naturally occurring plague infections are of major importance. Our study is the first to demonstrate that variable-number tandem repeats (VNTRs) in the Y. pestis genome can link human case isolates to those obtained from suspected environmental sources of infection. We demonstrate the valuable utility of VNTR markers in epidemiological investigations of naturally occurring plague and the forensic analysis of possible bioterrorism events.

SUBMITTER: Lowell JL

PROVIDER: S-EPMC548095 | biostudies-literature | 2005 Feb

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Publications

Identifying sources of human exposure to plague.

Lowell Jennifer L JL Wagner David M DM Atshabar Bakyt B Antolin Michael F MF Vogler Amy J AJ Keim Paul P Chu May C MC Gage Kenneth L KL

Journal of clinical microbiology 20050201 2

Yersinia pestis, the etiologic agent of plague, has shaped the course of human history, killing millions of people in three major pandemics. This bacterium is still endemic in parts of Asia, Africa, and the Americas, where it poses a natural disease threat to human populations. Y. pestis has also recently received attention as a possible bioterrorism agent. Thus, rapid methods to distinguish between bioterrorism and naturally occurring plague infections are of major importance. Our study is the ...[more]

PMID: 15695659

Similar Datasets

Modeling the ecologic niche of plague in sylvan and domestic animal hosts to delineate sources of human exposure in the western United States.

Project description:Plague has been established in the western United States (US) since 1900 following the West Coast introduction of commensal rodents infected with Yersinia pestis via early industrial shipping. Over the last century, plague ecology has transitioned through cycles of widespread human transmission, urban domestic transmission among commensal rodents, and ultimately settled into the predominantly sylvan foci that remain today where it is maintained alternatively by enzootic and epizootic transmission. While zoonotic transmission to humans is much less common in modern times, significant plague risk remains in parts of the western US. Moreover, risk to some threatened species that are part of the epizootic cycle can be quite substantive. This investigation attempted to predict the risk of plague across the western US by modeling the ecologic niche of plague in sylvan and domestic animals identified between 2000 and 2015. A Maxent machine learning algorithm was used to predict this niche based on climate, altitude, land cover, and the presence of an important enzootic species, Peromyscus maniculatus. This model demonstrated good predictive ability (AUC = 86%) and identified areas of high risk in central Colorado, north-central New Mexico, and southwestern and northeastern California. The presence of P. maniculatus, altitude, precipitation during the driest and wettest quarters, and distance to artificial surfaces, all contributed substantively to maximizing the gain function. These findings add to the known landscape epidemiology and infection ecology of plague in the western US and may suggest locations of particular risk to be targeted for wild and domestic animal intervention.

| S-EPMC4690378 | biostudies-literature

Identifying Human SIRT1 Substrates by Integrating Heterogeneous Information from Various Sources.

Project description:Most proteins undergo different kinds of modification after translation. Protein acetylation is one of the most crucial post-translational modifications, which causes direct or indirect impact on various biological activities in vivo. As a member of Class III HDACs, SIRT1 was the closest one to the yeast sir2 and drew most attention, while a small number of known SIRT1 substrates caused difficulties to clarify its function. In this work, we designed a novel computational method to screen SIRT1 substrates based on manually collected data and Support Vector Machines (SVMs). Unlike other approaches, we took both primary sequence and protein functional features into consideration. Through integrating functional features, the Matthews correlation coefficient (MCC) for the prediction increased from 0.10 to 0.65. The prediction results were verified by independent dataset and biological experiments. The validation results demostrated that our classifier could effectively identify SIRT1 substrates and filter appropriate candidates for further research. Furthermore, we provide online tool to support SIRT1 substrates prediction, which is freely available at http://bioinfo.bjmu.edu.cn/huac/ .

| S-EPMC5496887 | biostudies-other

Identifying Multiple Propagation Sources

Project description:The global diffusion of epidemics, computer viruses and rumors causes great damage to our society. One critical issue to identify the multiple diffusion sources so as to timely quarantine them. However, most methods proposed so far are unsuitable for diffusion with multiple sources because of the high computational cost and the complex spatiotemporal diffusion processes. In this chapter, we introduce an effective method to identify multiple diffusion sources, which can address three main issues in this area: (1) How many sources are there? (2) Where did the diffusion emerge? (3) When did the diffusion break out? For simplicity, we use rumor source identification to present the approach.

| S-EPMC7122829 | biostudies-literature

Assessing sources of human methylmercury exposure using stable mercury isotopes.

Project description:Seafood consumption is the primary route of methylmercury (MeHg) exposure for most populations. Inherent uncertainties in dietary survey data point to the need for an empirical tool to confirm exposure sources. We therefore explore the utility of Hg stable isotope ratios in human hair as a new method for discerning MeHg exposure sources. We characterized Hg isotope fractionation between humans and their diets using hair samples from Faroese whalers exposed to MeHg predominantly from pilot whales. We observed an increase of 1.75‰ in δ(202)Hg values between pilot whale muscle tissue and Faroese whalers' hair but no mass-independent fractionation. We found a similar offset in δ(202)Hg between consumed seafood and hair samples from Gulf of Mexico recreational anglers who are exposed to lower levels of MeHg from a variety of seafood sources. An isotope mixing model was used to estimate individual MeHg exposure sources and confirmed that both Δ(199)Hg and δ(202)Hg values in human hair can help identify dietary MeHg sources. Variability in isotopic signatures among coastal fish consumers in the Gulf of Mexico likely reflects both differences in environmental sources of MeHg to coastal fish and uncertainty in dietary recall data. Additional data are needed to fully refine this approach for individuals with complex seafood consumption patterns.

| S-EPMC4123924 | biostudies-literature

IDENTIFYING SOURCES OF INEFFICIENCY IN HEALTHCARE.

Project description:In medicine, the reasons for variation in treatment rates across hospitals serving similar patients are not well understood. Some interpret this variation as unwarranted, and push standardization of care as a way of reducing allocative inefficiency. An alternative interpretation is that hospitals with greater expertise in a treatment use it more because of their comparative advantage, suggesting that standardization is misguided. A simple economic model provides an empirical framework to separate these explanations. Estimating this model with data for heart attack patients, we find evidence of substantial variation across hospitals in both allocative inefficiency and comparative advantage, with most hospitals overusing treatment in part because of incorrect beliefs about their comparative advantage. A stylized welfare-calculation suggests that eliminating allocative inefficiency would increase the total benefits from the treatment that we study by 44%.

| S-EPMC7755154 | biostudies-literature

Identifying human kinase-specific protein phosphorylation sites by integrating heterogeneous information from various sources.

Project description:Phosphorylation is an important type of protein post-translational modification. Identification of possible phosphorylation sites of a protein is important for understanding its functions. Unbiased screening for phosphorylation sites by in vitro or in vivo experiments is time consuming and expensive; in silico prediction can provide functional candidates and help narrow down the experimental efforts. Most of the existing prediction algorithms take only the polypeptide sequence around the phosphorylation sites into consideration. However, protein phosphorylation is a very complex biological process in vivo. The polypeptide sequences around the potential sites are not sufficient to determine the phosphorylation status of those residues. In the current work, we integrated various data sources such as protein functional domains, protein subcellular location and protein-protein interactions, along with the polypeptide sequences to predict protein phosphorylation sites. The heterogeneous information significantly boosted the prediction accuracy for some kinase families. To demonstrate potential application of our method, we scanned a set of human proteins and predicted putative phosphorylation sites for Cyclin-dependent kinases, Casein kinase 2, Glycogen synthase kinase 3, Mitogen-activated protein kinases, protein kinase A, and protein kinase C families (available at http://cmbi.bjmu.edu.cn/huphospho). The predicted phosphorylation sites can serve as candidates for further experimental validation. Our strategy may also be applicable for the in silico identification of other post-translational modification substrates.

| S-EPMC2981550 | biostudies-literature

Identifying sources of variation in parasite aggregation.

Project description:Aggregation of macroparasites among hosts is a near-universal pattern, and has important consequences for the stability of host-parasite associations and the impacts of disease. Identifying which potential drivers are contributing to levels of aggregation observed in parasite-host associations is challenging, particularly for observational studies. We apply beta regressions in a Bayesian framework to determine predictors of aggregation, quantified using Poulin's index of discrepancy (D), for 13 species of parasites infecting Icelandic Rock Ptarmigan (Lagopus muta) collected over 12 years. 1,140 ptarmigan were collected using sampling protocols maximizing consistency of sample sizes and of composition of host ages and sexes represented across years from 2006-2017. Parasite species, taxonomic group (insect, mite, coccidian, or nematode), and whether the parasite was an ecto- or endoparasite were tested as predictors of aggregation, either alone or by modulating an effect of parasite mean abundance on D. Parasite species was an important predictor of aggregation in models. Despite variation in D across samples and years, relatively consistent aggregation was demonstrated for each specific host-parasite association, but not for broader taxonomic groups, after taking sample mean abundance into account. Furthermore, sample mean abundance was consistently and inversely related to aggregation among the nine ectoparasites, however no relationship between mean abundance and aggregation was observed among the four endoparasites. We discuss sources of variation in observed aggregation, sources both statistical and biological in nature, and show that aggregation is predictable, and distinguishable, among infecting species. We propose explanations for observed patterns and call for the review and re-analysis of parasite and other symbiont distributions using beta regression to identify important drivers of aggregation-both broad and association-specific.

| S-EPMC9419717 | biostudies-literature

Trends of Human Plague, Madagascar, 1998-2016.

Project description:Madagascar is more seriously affected by plague, a zoonosis caused by Yersinia pestis, than any other country. The Plague National Control Program was established in 1993 and includes human surveillance. During 1998-2016, a total of 13,234 suspected cases were recorded, mainly from the central highlands; 27% were confirmed cases, and 17% were presumptive cases. Patients with bubonic plague (median age 13 years) represented 93% of confirmed and presumptive cases, and patients with pneumonic plague (median age 29 years) represented 7%. Deaths were associated with delay of consultation, pneumonic form, contact with other cases, occurrence after 2009, and not reporting dead rats. A seasonal pattern was observed with recrudescence during September-March. Annual cases peaked in 2004 and decreased to the lowest incidence in 2016. This overall reduction occurred primarily for suspected cases and might be caused by improved adherence to case criteria during widespread implementation of the F1 rapid diagnostic test in 2002.

| S-EPMC6346457 | biostudies-literature

Predicting Arsenic (As) Exposure on Human Health for Better Management of Drinking Water Sources.

Project description:Chemical pollution in the transboundary Langat River in Malaysia is common both from point and non-point sources. Therefore, the water treatment plants (WTPS) at the Langat River Basin have experienced frequent shutdown incidents. However, the Langat River is one of the main sources of drinking water to almost one-third of the population in Selangor state. Meanwhile, several studies have reported a high concentration of Arsenic (As) in the Langat River that is toxic if ingested via drinking water. However, this is a pioneer study that predicts the As concentration in the Langat River based on time-series data from 2005-2014 to estimate the health risk associated with As ingestion via drinking water at the Langat River Basin. Several time-series prediction models were tested and Gradient Boosted Tree (GBT) gained the best result. This GBT model also fits better to predict the As concentration until December 2024. The mean concentration of As in the Langat River for both 2014 and 2024, as well as the carcinogenic and non-carcinogenic health risks of As ingestion via drinking water, were within the drinking water quality standards proposed by the World Health Organization and Ministry of Health Malaysia. However, the ingestion of trace amounts of As over a long period might be detrimental to human health because of its non-biodegradable characteristics. Therefore, it is important to manage the drinking water sources to minimise As exposure risks to human health.

| S-EPMC8345792 | biostudies-literature

Identifying affordable sources of medical care among uninsured persons.

Project description:ObjectiveTo examine the effects of policy, health system, and sociodemographic characteristics on the likelihood that uninsured persons pay a lower price at their regular source of care, or that they are aware of lower priced providers in their community.Data sourcesThe 2003 Community Tracking Study household survey, a nationally representative sample of the U.S. population and 60 randomly selected communities.Study designThe survey asked uninsured persons if they paid full or reduced cost at their usual source of medical care, or if they were aware of providers in their community that charge less for uninsured people. We use binomial and multinomial logistic regression analysis to examine the effects of various policy, health system, and sociodemographic characteristics on use and awareness of lower priced providers. We focus especially on the effects of safety-net capacity, measured by safety-net hospitals, community health centers, physicians' charity care, and Community Access Program (CAP) grants.Principal findingsLess than half of the uninsured (47.5 percent) reported that they used or were aware of a lower priced provider in their community. Multivariate regression analysis shows that greater safety-net capacity is associated with a higher likelihood of having a lower priced provider as the regular source of care and greater awareness of lower priced providers. Lower incomes and racial/ethnic minorities also had a higher likelihood of having a lower priced provider, although health status did not have statistically significant effects.ConclusionAlthough increased safety-net capacity may lead to more uninsured having a lower priced provider, many uninsured who live near safety-net providers are not aware of their presence. Greater outreach designed to increase awareness may be needed in order to increase the effectiveness of safety-net providers in improving access to care for the uninsured.

| S-EPMC1955746 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data