190 research outputs found

    Spatial analysis of plague in California: niche modeling predictions of the current distribution and potential response to climate change

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    <p>Abstract</p> <p>Background</p> <p>Plague, caused by the bacterium <it>Yersinia pestis</it>, is a public and wildlife health concern in California and the western United States. This study explores the spatial characteristics of positive plague samples in California and tests Maxent, a machine-learning method that can be used to develop niche-based models from presence-only data, for mapping the potential distribution of plague foci. Maxent models were constructed using geocoded seroprevalence data from surveillance of California ground squirrels (<it>Spermophilus beecheyi</it>) as case points and Worldclim bioclimatic data as predictor variables, and compared and validated using area under the receiver operating curve (AUC) statistics. Additionally, model results were compared to locations of positive and negative coyote (<it>Canis latrans</it>) samples, in order to determine the correlation between Maxent model predictions and areas of plague risk as determined via wild carnivore surveillance.</p> <p>Results</p> <p>Models of plague activity in California ground squirrels, based on recent climate conditions, accurately identified case locations (AUC of 0.913 to 0.948) and were significantly correlated with coyote samples. The final models were used to identify potential plague risk areas based on an ensemble of six future climate scenarios. These models suggest that by 2050, climate conditions may reduce plague risk in the southern parts of California and increase risk along the northern coast and Sierras.</p> <p>Conclusion</p> <p>Because different modeling approaches can yield substantially different results, care should be taken when interpreting future model predictions. Nonetheless, niche modeling can be a useful tool for exploring and mapping the potential response of plague activity to climate change. The final models in this study were used to identify potential plague risk areas based on an ensemble of six future climate scenarios, which can help public managers decide where to allocate surveillance resources. In addition, Maxent model results were significantly correlated with coyote samples, indicating that carnivore surveillance programs will continue to be important for tracking the response of plague to future climate conditions.</p

    Phenotypic characterization of breast cancer: the role of CDC42

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    Purpose: The molecular landscape of breast cancer (BC), especially of the Luminal A subtype, remains to be fully delineated. Transcriptomic data shows that Luminal A tumours are enriched for aberrant expression of genes in the cell division control 42 homolog (CDC42) pathway. This study aims to investigate protein expression of CDC42 in BC and assess its clinicopathological significance. Methods: Expression of CDC42 protein was examined by immunohistochemistry on tissue microarrays in a well characterised cohort of 895 early stage (I-IIIa) primary invasive BCs. Results: CDC42 expression was observed in both the cytoplasm and nucleus of BC cells. High nuclear CDC42 expression demonstrated a significant correlation with ER positive, low-grade tumours and was more common in the lobular histological subtype (all p<0.001). In contrast, cytoplasmic CDC42 showed increased expression in the ductal subtype (p<0.001) and correlated with negative prognostic features such as larger size, higher grade (p<0.05), and higher Ki67 labelling index (p=0.001). Nuclear CDC42 expression was associated with a longer BC specific survival in all cases (p=0.025) and in luminal ER positive tumours (p=0.011). In multivariate analyses including size, grade, lymph node stage and intrinsic subtype, CDC42 was an independent prognostic factor (p=0.032). Conclusion: The results indicate that CDC42 is important molecule in luminal BC, with prognostic significance

    Sucrose transporter1 functions in phloem loading in maize leaves

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    In most plants, sucrose is exported from source leaves to carbon-importing sink tissues to sustain their growth and metabolism. Apoplastic phloem-loading species require sucrose transporters (SUTs) to transport sucrose into the phloem. In many dicot plants, genetic and biochemical evidence has established that SUT1-type proteins function in phloem loading. However, the role of SUT1 in phloem loading in monocot plants is not clear since the rice (Oryza sativa) and sugarcane (Saccharum hybrid) SUT1 orthologues do not appear to function in phloem loading of sucrose. A SUT1 gene was previously cloned from maize (Zea mays) and shown to have expression and biochemical activity consistent with a hypothesized role in phloem loading. To determine the biological function of SUT1 in maize, a sut1 mutant was isolated and characterized. sut1 mutant plants hyperaccumulate carbohydrates in mature leaves and display leaf chlorosis with premature senescence. In addition, sut1 mutants have greatly reduced stature, altered biomass partitioning, delayed flowering, and stunted tassel development. Cold-girdling wild-type leaves to block phloem transport phenocopied the sut1 mutants, supporting a role for maize SUT1 in sucrose export. Furthermore, application of 14C-sucrose to abraded sut1 mutant and wild-type leaves showed that sucrose export was greatly diminished in sut1 mutants compared with wild type. Collectively, these data demonstrate that SUT1 is crucial for efficient phloem loading of sucrose in maize leaves

    Fine mapping of copy number variations on two cattle genome assemblies using high density SNP array

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    Btau_4.0 and UMD3.1 are two distinct cattle reference genome assemblies. In our previous study using the low density BovineSNP50 array, we reported a copy number variation (CNV) analysis on Btau_4.0 with 521 animals of 21 cattle breeds, yielding 682 CNV regions with a total length of 139.8 megabases. In this study using the high density BovineHD SNP array, we performed high resolution CNV analyses on both Btau_4.0 and UMD3.1 with 674 animals of 27 cattle breeds. We first compared CNV results derived from these two different SNP array platforms on Btau_4.0. With two thirds of the animals shared between studies, on Btau_4.0 we identified 3,346 candidate CNV regions representing 142.7 megabases (~4.70%) of the genome. With a similar total length but 5 times more event counts, the average CNVR length of current Btau_4.0 dataset is significantly shorter than the previous one (42.7 kb vs. 205 kb). Although subsets of these two results overlapped, 64% (91.6 megabases) of current dataset was not present in the previous study. We also performed similar analyses on UMD3.1 using these BovineHD SNP array results. Approximately 50% more and 20% longer CNVs were called on UMD3.1 as compared to those on Btau_4.0. However, a comparable result of CNVRs (3,438 regions with a total length 146.9 megabases) was obtained. We suspect that these results are due to the UMD3.1 assembly's efforts of placing unplaced contigs and removing unmerged alleles. Selected CNVs were further experimentally validated, achieving a 73% PCR validation rate, which is considerably higher than the previous validation rate. About 20-45% of CNV regions overlapped with cattle RefSeq genes and Ensembl genes. Panther and IPA analyses indicated that these genes provide a wide spectrum of biological processes involving immune system, lipid metabolism, cell, organism and system development. In this study using the high density BovineHD SNP array, we performed high resolution CNV analyses on both Btau_4.0 and UMD3.1 with 674 animals of 27 cattle breeds. We first compared CNV results derived from these two different SNP array platforms on Btau_4.0. With two thirds of the animals shared between studies, on Btau_4.0 we identified 3,346 candidate CNV regions representing 142.7 megabases (~4.70%) of the genome. With a similar total length but 5 times more event counts, the average CNVR length of current Btau_4.0 dataset is significantly shorter than the previous one (42.7 kb vs. 205 kb). Although subsets of these two results overlapped, 64% (91.6 megabases) of current dataset was not present in the previous study. We also performed similar analyses on UMD3.1 using these BovineHD SNP array results. Approximately 50% more and 20% longer CNVs were called on UMD3.1 as compared to those on Btau_4.0. However, a comparable result of CNVRs (3,438 regions with a total length 146.9 megabases) was obtained. We suspect that these results are due to the UMD3.1 assembly's efforts of placing unplaced contigs and removing unmerged alleles. Selected CNVs were further experimentally validated, achieving a 73% PCR validation rate, which is considerably higher than the previous validation rate. About 20-45% of CNV regions overlapped with cattle RefSeq genes and Ensembl genes. Panther and IPA analyses indicated that these genes provide a wide spectrum of biological processes involving immune system, lipid metabolism, cell, organism and system development. We present a comprehensive result of cattle CNVs at a higher resolution and sensitivity. We identified over 3,000 candidate CNV regions on both Btau_4.0 and UMD3.1, further compared current datasets with previous results, and examined the impacts of genome assemblies on CNV calling.https://doi.org/10.1186/1471-2164-13-37

    A randomised clinical trial of subgrouping and targeted treatment for low back pain compared with best current care. The STarT Back Trial Study Protocol

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    Back pain is a major health problem and many sufferers develop persistent symptoms. Detecting relevant subgroups of patients with non-specific low back pain has been highlighted as a priority area for research, as this could enable better secondary prevention through the targeting of prognostic indicators for persistent, disabling symptoms. We plan to conduct a randomised controlled trial to establish whether subgrouping using a novel tool, combined with targeted treatment, is better than best current care at reducing long-term disability from low back pain
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