329 research outputs found
Eimeria species occurrence varies between geographic regions and poultry production systems and may influence parasite genetic diversity
Coccidiosis is one of the biggest challenges faced by the global poultry industry. Recent studies have highlighted the ubiquitous distribution of all Eimeria species which can cause this disease in chickens, but intriguingly revealed a regional divide in genetic diversity and population structure for at least one species, Eimeria tenella. The drivers associated with such distinct geographic variation are unclear, but may impact on the occurrence and extent of resistance to anticoccidial drugs and future subunit vaccines. India is one of the largest poultry producers in the world and includes a transition between E. tenella populations defined by high and low genetic diversity. The aim of this study was to identify risk factors associated with the prevalence of Eimeria species defined by high and low pathogenicity in northern and southern states of India, and seek to understand factors which vary between the regions as possible drivers for differential genetic variation. Faecal samples and data relating to farm characteristics and management were collected from 107 farms from northern India and 133 farms from southern India. Faecal samples were analysed using microscopy and PCR to identify Eimeria occurrence. Multiple correspondence analysis was applied to transform correlated putative risk factors into a smaller number of synthetic uncorrelated factors. Hierarchical cluster analysis was used to identify poultry farm typologies, revealing three distinct clusters in the studied regions. The association between clusters and presence of Eimeria species was assessed by logistic regression. The study found that large-scale broiler farms in the north were at greatest risk of harbouring any Eimeria species and a larger proportion of such farms were positive for E. necatrix, the most pathogenic species. Comparison revealed a more even distribution for E. tenella across production systems in south India, but with a lower overall occurrence. Such a polarised region- and system-specific distribution may contribute to the different levels of genetic diversity observed previously in India and may influence parasite population structure across much of Asia and Africa. The findings of the study can be used to prioritise target farms to launch and optimise appropriate anticoccidial strategies for long-term control
The structure of a major surface antigen SAG19 from Eimeria tenella unifies the Eimeria SAG family
In infections by apicomplexan parasites including Plasmodium, Toxoplasma gondii, and Eimeria, host interactions are mediated by proteins including families of membrane-anchored cysteine-rich surface antigens (SAGs) and SAG-related sequences (SRS). Eimeria tenella causes caecal coccidiosis in chickens and has a SAG family with over 80 members making up 1% of the proteome. We have solved the structure of a representative E. tenella SAG, EtSAG19, revealing that, despite a low level of sequence similarity, the entire Eimeria SAG family is unified by its three-layer αβα fold which is related to that of the CAP superfamily. Furthermore, sequence comparisons show that the Eimeria SAG fold is conserved in surface antigens of the human coccidial parasite Cyclospora cayetanensis but this fold is unrelated to that of the SAGs/SRS proteins expressed in other apicomplexans including Plasmodium species and the cyst-forming coccidia Toxoplasma gondii, Neospora caninum and Besnoitia besnoiti. However, despite having very different structures, Consurf analysis showed that Eimeria SAG and Toxoplasma SRS families each exhibit marked hotspots of sequence hypervariability that map to their surfaces distal to the membrane anchor. This suggests that the primary and convergent purpose of the different structures is to provide a platform onto which sequence variability can be imposed
Deviation From \Lambda CDM With Cosmic Strings Networks
In this work, we consider a network of cosmic strings to explain possible
deviation from \Lambda CDM behaviour. We use different observational data to
constrain the model and show that a small but non zero contribution from the
string network is allowed by the observational data which can result in a
reasonable departure from \Lambda CDM evolution. But by calculating the
Bayesian Evidence, we show that the present data still strongly favour the
concordance \Lambda CDM model irrespective of the choice of the prior.Comment: 15 Pages, Latex Style, 4 eps figures, Revised Version, Accepted for
publication in European Physical Journal
Measurements of long-range near-side angular correlations in TeV proton-lead collisions in the forward region
Two-particle angular correlations are studied in proton-lead collisions at a
nucleon-nucleon centre-of-mass energy of TeV, collected
with the LHCb detector at the LHC. The analysis is based on data recorded in
two beam configurations, in which either the direction of the proton or that of
the lead ion is analysed. The correlations are measured in the laboratory
system as a function of relative pseudorapidity, , and relative
azimuthal angle, , for events in different classes of event
activity and for different bins of particle transverse momentum. In
high-activity events a long-range correlation on the near side, , is observed in the pseudorapidity range . This
measurement of long-range correlations on the near side in proton-lead
collisions extends previous observations into the forward region up to
. The correlation increases with growing event activity and is found
to be more pronounced in the direction of the lead beam. However, the
correlation in the direction of the lead and proton beams are found to be
compatible when comparing events with similar absolute activity in the
direction analysed.Comment: All figures and tables, along with any supplementary material and
additional information, are available at
https://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2015-040.htm
Study of the production of and hadrons in collisions and first measurement of the branching fraction
The product of the () differential production
cross-section and the branching fraction of the decay () is
measured as a function of the beauty hadron transverse momentum, ,
and rapidity, . The kinematic region of the measurements is and . The measurements use a data sample
corresponding to an integrated luminosity of collected by the
LHCb detector in collisions at centre-of-mass energies in 2011 and in 2012. Based on previous LHCb
results of the fragmentation fraction ratio, , the
branching fraction of the decay is
measured to be \begin{equation*} \mathcal{B}(\Lambda_b^0\rightarrow J/\psi
pK^-)= (3.17\pm0.04\pm0.07\pm0.34^{+0.45}_{-0.28})\times10^{-4},
\end{equation*} where the first uncertainty is statistical, the second is
systematic, the third is due to the uncertainty on the branching fraction of
the decay , and the
fourth is due to the knowledge of . The sum of the
asymmetries in the production and decay between and
is also measured as a function of and .
The previously published branching fraction of , relative to that of , is updated.
The branching fractions of are determined.Comment: 29 pages, 19figures. All figures and tables, along with any
supplementary material and additional information, are available at
https://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2015-032.htm
flavour tagging using charm decays at the LHCb experiment
An algorithm is described for tagging the flavour content at production of
neutral mesons in the LHCb experiment. The algorithm exploits the
correlation of the flavour of a meson with the charge of a reconstructed
secondary charm hadron from the decay of the other hadron produced in the
proton-proton collision. Charm hadron candidates are identified in a number of
fully or partially reconstructed Cabibbo-favoured decay modes. The algorithm is
calibrated on the self-tagged decay modes and using of data collected by the LHCb
experiment at centre-of-mass energies of and
. Its tagging power on these samples of
decays is .Comment: All figures and tables, along with any supplementary material and
additional information, are available at
http://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2015-027.htm
Evidence for the strangeness-changing weak decay
Using a collision data sample corresponding to an integrated luminosity
of 3.0~fb, collected by the LHCb detector, we present the first search
for the strangeness-changing weak decay . No
hadron decay of this type has been seen before. A signal for this decay,
corresponding to a significance of 3.2 standard deviations, is reported. The
relative rate is measured to be
, where and
are the and fragmentation
fractions, and is the branching
fraction. Assuming is bounded between 0.1 and
0.3, the branching fraction would lie
in the range from to .Comment: 7 pages, 2 figures, All figures and tables, along with any
supplementary material and additional information, are available at
https://lhcbproject.web.cern.ch/lhcbproject/Publications/LHCbProjectPublic/LHCb-PAPER-2015-047.htm
Shared genetics underlying epidemiological association between endometriosis and ovarian cancer
Epidemiological studies have demonstrated associations between endometriosis and certain histotypes of ovarian cancer, including clear cell, low-grade serous and endometrioid carcinomas. We aimed to determine whether the observed associations might be due to shared genetic aetiology. To address this, we used two endometriosis datasets genotyped on common arrays with full-genome coverage (3194 cases and 7060 controls) and a large ovarian cancer dataset genotyped on the customized Illumina Infinium iSelect (iCOGS) arrays (10 065 cases and 21 663 controls). Previous work has suggested that a large number of genetic variants contribute to endometriosis and ovarian cancer (all histotypes combined) susceptibility. Here, using the iCOGS data, we confirmed polygenic architecture for most histotypes of ovarian cancer. This led us to evaluate if the polygenic effects are shared across diseases. We found evidence for shared genetic risks between endometriosis and all histotypes of ovarian cancer, except for the intestinal mucinous type. Clear cell carcinoma showed the strongest genetic correlation with endometriosis (0.51, 95% CI = 0.18-0.84). Endometrioid and low-grade serous carcinomas had similar correlation coefficients (0.48, 95% CI = 0.07-0.89 and 0.40, 95% CI = 0.05-0.75, respectively). High-grade serous carcinoma, which often arises from the fallopian tubes, showed a weaker genetic correlation with endometriosis (0.25, 95% CI = 0.11-0.39), despite the absence of a known epidemiological association. These results suggest that the epidemiological association between endometriosis and ovarian adenocarcinoma may be attributable to shared genetic susceptibility loci.Other Research Uni
Gene expression profiling of mucinous ovarian tumors and comparison with upper and lower gastrointestinal tumors identifies markers associated with adverse outcomes.
PURPOSE: Advanced-stage mucinous ovarian carcinoma (MOC) has poor chemotherapy response and prognosis and lacks biomarkers to aid stage I adjuvant treatment. Differentiating primary MOC from gastrointestinal (GI) metastases to the ovary is also challenging due to phenotypic similarities. Clinicopathologic and gene-expression data were analyzed to identify prognostic and diagnostic features. EXPERIMENTAL DESIGN: Discovery analyses selected 19 genes with prognostic/diagnostic potential. Validation was performed through the Ovarian Tumor Tissue Analysis consortium and GI cancer biobanks comprising 604 patients with MOC (n = 333), mucinous borderline ovarian tumors (MBOT, n = 151), and upper GI (n = 65) and lower GI tumors (n = 55). RESULTS: Infiltrative pattern of invasion was associated with decreased overall survival (OS) within 2 years from diagnosis, compared with expansile pattern in stage I MOC [hazard ratio (HR), 2.77; 95% confidence interval (CI), 1.04–7.41, P = 0.042]. Increased expression of THBS2 and TAGLN was associated with shorter OS in MOC patients (HR, 1.25; 95% CI, 1.04–1.51, P = 0.016) and (HR, 1.21; 95% CI, 1.01–1.45, P = 0.043), respectively. ERBB2 (HER2) amplification or high mRNA expression was evident in 64 of 243 (26%) of MOCs, but only 8 of 243 (3%) were also infiltrative (4/39, 10%) or stage III/IV (4/31, 13%). CONCLUSIONS: An infiltrative growth pattern infers poor prognosis within 2 years from diagnosis and may help select stage I patients for adjuvant therapy. High expression of THBS2 and TAGLN in MOC confers an adverse prognosis and is upregulated in the infiltrative subtype, which warrants further investigation. Anti-HER2 therapy should be investigated in a subset of patients. MOC samples clustered with upper GI, yet markers to differentiate these entities remain elusive, suggesting similar underlying biology and shared treatment strategies
Effects of sleep deprivation on neural functioning: an integrative review
Sleep deprivation has a broad variety of effects on human performance and neural functioning that manifest themselves at different levels of description. On a macroscopic level, sleep deprivation mainly affects executive functions, especially in novel tasks. Macroscopic and mesoscopic effects of sleep deprivation on brain activity include reduced cortical responsiveness to incoming stimuli, reflecting reduced attention. On a microscopic level, sleep deprivation is associated with increased levels of adenosine, a neuromodulator that has a general inhibitory effect on neural activity. The inhibition of cholinergic nuclei appears particularly relevant, as the associated decrease in cortical acetylcholine seems to cause effects of sleep deprivation on macroscopic brain activity. In general, however, the relationships between the neural effects of sleep deprivation across observation scales are poorly understood and uncovering these relationships should be a primary target in future research
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