230 research outputs found
PCR for the detection of pathogens in neonatal early onset sepsis.
BACKGROUND: A large proportion of neonates are treated for presumed bacterial sepsis with broad spectrum antibiotics even though their blood cultures subsequently show no growth. This study aimed to investigate PCR-based methods to identify pathogens not detected by conventional culture. METHODS: Whole blood samples of 208 neonates with suspected early onset sepsis were tested using a panel of multiplexed bacterial PCRs targeting Streptococcus pneumoniae, Streptococcus agalactiae (GBS), Staphylococcus aureus, Streptococcus pyogenes (GAS), Enterobacteriaceae, Enterococcus faecalis, Enterococcus faecium, Ureaplasma parvum, Ureaplasma urealyticum, Mycoplasma hominis and Mycoplasma genitalium, a 16S rRNA gene broad-range PCR and a multiplexed PCR for Candida spp. RESULTS: Two-hundred and eight samples were processed. In five of those samples, organisms were detected by conventional culture; all of those were also identified by PCR. PCR detected bacteria in 91 (45%) of the 203 samples that did not show bacterial growth in culture. S. aureus, Enterobacteriaceae and S. pneumoniae were the most frequently detected pathogens. A higher bacterial load detected by PCR was correlated positively with the number of clinical signs at presentation. CONCLUSION: Real-time PCR has the potential to be a valuable additional tool for the diagnosis of neonatal sepsis
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Obesity prevention in the early years: a mapping study of national policies in England from a behavioural science perspective
Background
Evidence indicates that early life is critical for determining future obesity risk. A sharper policy focus on pregnancy and early childhood could help improve obesity prevention efforts. This study aimed to systematically identify and categorise policy levers used in England with potential to influence early lifecourse (pregnancy, 0-5 years) and identify how these interface with energy balance behaviours. The objective is to identify gaps and where further policy actions could most effectively focus.
Methods
A behavioural science approach was taken using the Capability-Opportunity-Motivation-Behaviour (COM-B) model and Behaviour Change Wheel (BCW) framework. The key determinants of energy balance in the early years were identified from the Foresight Systems Map. Policy actions were scoped systematically from available literature, including any health or non-health policies which could impact on energy balance behaviours. Foresight variables and policy actions were considered in terms of COM-B and the BCW to determine approaches likely to be effective for obesity prevention and treatment. Existing policies were overlaid across the map of key risk factors to identify gaps in obesity prevention and treatment provision.
Results
A wide range of policy actions were identified (n=115) to address obesity-relevant risk factors. These were most commonly educational or guidelines relating to environmental restructuring (i.e. changing the physical or social context). Scope for strengthening policies relating to the food system (e.g. the market price of food) and psychological factors contributing to obesity were identified. Policies acted via all aspects of the COM-B model, but there was scope for improving policies to increase capability through skills acquisition and both reflective and automatic motivation.
Conclusions
There is substantial policy activity to address early years obesity but much is focused on education. Scope exists to strengthen actions relating to upstream policies which act on food systems and those targeting psychological factors contributing to obesity risk
Viral factors in influenza pandemic risk assessment
The threat of an influenza A virus pandemic stems from continual virus spillovers from reservoir species, a tiny fraction of which spark sustained transmission in humans. To date, no pandemic emergence of a new influenza strain has been preceded by detection of a closely related precursor in an animal or human. Nonetheless, influenza surveillance efforts are expanding, prompting a need for tools to assess the pandemic risk posed by a detected virus. The goal would be to use genetic sequence and/or biological assays of viral traits to identify those non-human influenza viruses with the greatest risk of evolving into pandemic threats, and/or to understand drivers of such evolution, to prioritize pandemic prevention or response measures. We describe such efforts, identify progress and ongoing challenges, and discuss three specific traits of influenza viruses (hemagglutinin receptor binding specificity, hemagglutinin pH of activation, and polymerase complex efficiency) that contribute to pandemic risk
Canalization of the evolutionary trajectory of the human influenza virus
Since its emergence in 1968, influenza A (H3N2) has evolved extensively in
genotype and antigenic phenotype. Antigenic evolution occurs in the context of
a two-dimensional 'antigenic map', while genetic evolution shows a
characteristic ladder-like genealogical tree. Here, we use a large-scale
individual-based model to show that evolution in a Euclidean antigenic space
provides a remarkable correspondence between model behavior and the
epidemiological, antigenic, genealogical and geographic patterns observed in
influenza virus. We find that evolution away from existing human immunity
results in rapid population turnover in the influenza virus and that this
population turnover occurs primarily along a single antigenic axis. Thus,
selective dynamics induce a canalized evolutionary trajectory, in which the
evolutionary fate of the influenza population is surprisingly repeatable and
hence, in theory, predictable.Comment: 29 pages, 5 figures, 10 supporting figure
Prediction, dynamics, and visualization of antigenic phenotypes of seasonal influenza viruses
Human seasonal influenza viruses evolve rapidly, enabling the virus population to evade immunity and reinfect previously infected individuals. Antigenic properties are largely determined by the surface glycoprotein hemagglutinin (HA), and amino acid substitutions at exposed epitope sites in HA mediate loss of recognition by antibodies. Here, we show that antigenic differences measured through serological assay data are well described by a sum of antigenic changes along the path connecting viruses in a phylogenetic tree. This mapping onto the tree allows prediction of antigenicity from HA sequence data alone. The mapping can further be used to make predictions about the makeup of the future A(H3N2) seasonal influenza virus population, and we compare predictions between models with serological and sequence data. To make timely model output readily available, we developed a web browser-based application that visualizes antigenic data on a continuously updated phylogeny
Global circulation patterns of seasonal influenza viruses vary with antigenic drift.
Understanding the spatiotemporal patterns of emergence and circulation of new human seasonal influenza virus variants is a key scientific and public health challenge. The global circulation patterns of influenza A/H3N2 viruses are well characterized, but the patterns of A/H1N1 and B viruses have remained largely unexplored. Here we show that the global circulation patterns of A/H1N1 (up to 2009), B/Victoria, and B/Yamagata viruses differ substantially from those of A/H3N2 viruses, on the basis of analyses of 9,604 haemagglutinin sequences of human seasonal influenza viruses from 2000 to 2012. Whereas genetic variants of A/H3N2 viruses did not persist locally between epidemics and were reseeded from East and Southeast Asia, genetic variants of A/H1N1 and B viruses persisted across several seasons and exhibited complex global dynamics with East and Southeast Asia playing a limited role in disseminating new variants. The less frequent global movement of influenza A/H1N1 and B viruses coincided with slower rates of antigenic evolution, lower ages of infection, and smaller, less frequent epidemics compared to A/H3N2 viruses. Detailed epidemic models support differences in age of infection, combined with the less frequent travel of children, as probable drivers of the differences in the patterns of global circulation, suggesting a complex interaction between virus evolution, epidemiology, and human behaviour.T.B.
was
supported
by
a
Newton
International
Fellowship
from
the
Royal
Society
and
through
NIH
U54
GM111274.
S.R.
was
supported
by
MRC
(UK,
Project
MR/J008761/1),
Wellcome
Trust
(UK,
Project
093488/Z/10/Z),
Fogarty
International
Centre
(USA,
R01
TW008246‐01),
DHS
(USA,
RAPIDD
program),
NIGMS
(USA,
MIDAS
U01
GM110721‐01)
and
NIHR
(UK,
Health
Protection
Research
Unit
funding).
The
Melbourne
WHO
Collaborating
Centre
for
Reference
and
Research
on
Influenza
was
supported
by
the
Australian
Government
Department
of
Health
and
thanks
N.
Komadina
and
Y.‐M.
Deng.
The
Atlanta
WHO
Collaborating
Center
for
Surveillance,
Epidemiology
and
Control
of
Influenza
was
supported
by
the
U.S.
Department
of
13
Health
and
Human
Services.
NIV
thanks
A.C.
Mishra,
M.
Chawla‐Sarkar,
A.M.
Abraham,
D.
Biswas,
S.
Shrikhande,
AnuKumar
B,
and
A.
Jain.
Influenza
surveillance
in
India
was
expanded,
in
part,
through
US
Cooperative
Agreements
(5U50C1024407
and
U51IP000333)
and
by
the
Indian
Council
of
Medical
Research.
M.A.S.
was
supported
through
NSF
DMS
1264153
and
NIH
R01
AI
107034.
Work
of
the
WHO
Collaborating
Centre
for
Reference
and
Research
on
Influenza
at
the
MRC
National
Institute
for
Medical
Research
was
supported
by
U117512723.
P.L.,
A.R.
&
M.A.S
were
supported
by
EU
Seventh
Framework
Programme
[FP7/2007‐2013]
under
Grant
Agreement
no.
278433-‐PREDEMICS
and
ERC
Grant
agreement
no.
260864.
C.A.R.
was
supported
by
a
University
Research
Fellowship
from
the
Royal
Society.This is the author accepted manuscript. It is currently under infinite embargo pending publication of the final version
Genome-wide evolutionary dynamics of influenza B viruses on a global scale
The global-scale epidemiology and genome-wide evolutionary dynamics of influenza B remain poorly understood compared with influenza A viruses. We compiled a spatio-temporally comprehensive dataset of influenza B viruses, comprising over 2,500 genomes sampled worldwide between 1987 and 2015, including 382 newly-sequenced genomes that fill substantial gaps in previous molecular surveillance studies. Our contributed data increase the number of available influenza B virus genomes in Europe, Africa and Central Asia, improving the global context to study influenza B viruses. We reveal Yamagata-lineage diversity results from co-circulation of two antigenically-distinct groups that also segregate genetically across the entire genome, without evidence of intra-lineage reassortment. In contrast, Victoria-lineage diversity stems from geographic segregation of different genetic clades, with variability in the degree of geographic spread among clades. Differences between the lineages are reflected in their antigenic dynamics, as Yamagata-lineage viruses show alternating dominance between antigenic groups, while Victoria-lineage viruses show antigenic drift of a single lineage. Structural mapping of amino acid substitutions on trunk branches of influenza B gene phylogenies further supports these antigenic differences and highlights two potential mechanisms of adaptation for polymerase activity. Our study provides new insights into the epidemiological and molecular processes shaping influenza B virus evolution globally
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