36 research outputs found

    Distributing abstract machines

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    Today's distributed programs are often written using either explicit message passing or Remote Procedure Calls (RPCs) that are not natively integrated in the language. It is difficult to establish the correctness of programs written this way compared to programs written for a single computer. We propose a generalisation of RPCs that are natively integrated in a functional programming language meaning that they have support for higher-order calls across node boundaries. Our focus is on how such languages can be compiled correctly and efficiently. We present four different solutions. Two of them are based on interaction semantics --- the Geometry of Interaction and game semantics --- and two are extensions of conventional abstract machines --- the Krivine machine and the SECD machine. To target as general distributed systems as possible our solutions support RPCs without sending code. We prove the correctness of the abstract machines with respect to their single-node execution, and show their viability for use for compilation by implementing prototype compilers based on them. The conventionally based machines are shown to enable efficient programs. Our intention is that these abstract machines can form the foundation for future programming languages that use the idea of higher-order RPCs

    Towards native higher-order remote procedure calls

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    We present a new abstract machine, called DCESH, which mod-els the execution of higher-order programs running in distributed architectures. DCESH implements a native general remote higher-order function call across node boundaries. It is a modernised ver-sion of SECD enriched with specialised communication features required for implementing the remote procedure call mechanism. The key correctness result is that the termination behaviour of the remote procedure call is indistinguishable (bisimilar) to that of a local call. The correctness proofs and the requisite definitions for DCESH and other related abstract machines are formalised using Agda. We also formalise a generic transactional mechanism for transparently handling failure in DCESHs. We use the DCESH as a target architecture for compiling a conventional call-by-value functional language ("Floskel") whic

    A dual-tag microarray platform for high-performance nucleic acid and protein analyses

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    DNA microarrays serve to monitor a wide range of molecular events, but emerging applications like measurements of weakly expressed genes or of proteins and their interaction patterns will require enhanced performance to improve specificity of detection and dynamic range. To further extend the utility of DNA microarray-based approaches we present a high-performance tag microarray procedure that enables probe-based analysis of as little as 100 target cDNA molecules, and with a linear dynamic range close to 105. Furthermore, the protocol radically decreases the risk of cross-hybridization on microarrays compared to current approaches, and it also allows for quantification by single-molecule analysis and real-time on-chip monitoring of rolling-circle amplification. We provide proof of concept for microarray-based measurement of both mRNA molecules and of proteins, converted to tag DNA sequences by padlock and proximity probe ligation, respectively

    ProteinSeq: High-Performance Proteomic Analyses by Proximity Ligation and Next Generation Sequencing

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    Despite intense interest, methods that provide enhanced sensitivity and specificity in parallel measurements of candidate protein biomarkers in numerous samples have been lacking. We present herein a multiplex proximity ligation assay with readout via realtime PCR or DNA sequencing (ProteinSeq). We demonstrate improved sensitivity over conventional sandwich assays for simultaneous analysis of sets of 35 proteins in 5 µl of blood plasma. Importantly, we observe a minimal tendency to increased background with multiplexing, compared to a sandwich assay, suggesting that higher levels of multiplexing are possible. We used ProteinSeq to analyze proteins in plasma samples from cardiovascular disease (CVD) patient cohorts and matched controls. Three proteins, namely P-selectin, Cystatin-B and Kallikrein-6, were identified as putative diagnostic biomarkers for CVD. The latter two have not been previously reported in the literature and their potential roles must be validated in larger patient cohorts. We conclude that ProteinSeq is promising for screening large numbers of proteins and samples while the technology can provide a much-needed platform for validation of diagnostic markers in biobank samples and in clinical use

    Gene expression profiling in primary breast cancer distinguishes patients developing local recurrence after breast-conservation surgery, with or without postoperative radiotherapy

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    Introduction Some patients with breast cancer develop local recurrence after breast-conservation surgery despite postoperative radiotherapy, whereas others remain free of local recurrence even in the absence of radiotherapy. As clinical parameters are insufficient for identifying these two groups of patients, we investigated whether gene expression profiling would add further information. Methods We performed gene expression analysis (oligonucleotide arrays, 26,824 reporters) on 143 patients with lymph node-negative disease and tumor-free margins. A support vector machine was employed to build classifiers using leave-one-out cross-validation. Results Within the estrogen receptor-positive (ER+) subgroup, the gene expression profile clearly distinguished patients with local recurrence after radiotherapy (n = 20) from those without local recurrence (n = 80 with or without radiotherapy). The receiver operating characteristic (ROC) area was 0.91, and 5,237 of 26,824 reporters had a P value of less than 0.001 (false discovery rate = 0.005). This gene expression profile provides substantially added value to conventional clinical markers (for example, age, histological grade, and tumor size) in predicting local recurrence despite radiotherapy. Within the ER- subgroup, a weaker, but still significant, signal was found (ROC area = 0.74). The ROC area for distinguishing patients who develop local recurrence from those who remain local recurrence-free in the absence of radiotherapy was 0.66 (combined ER+/ER-). Conclusion A highly distinct gene expression profile for patients developing local recurrence after breast-conservation surgery despite radiotherapy has been identified. If verified in further studies, this profile might be a most important tool in the decision making for surgery and adjuvant therapy

    Targeted resequencing of candidate genes using selector probes

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    Targeted genome enrichment is a powerful tool for making use of the massive throughput of novel DNA-sequencing instruments. We herein present a simple and scalable protocol for multiplex amplification of target regions based on the Selector technique. The updated version exhibits improved coverage and compatibility with next-generation-sequencing (NGS) library-construction procedures for shotgun sequencing with NGS platforms. To demonstrate the performance of the technique, all 501 exons from 28 genes frequently involved in cancer were enriched for and sequenced in specimens derived from cell lines and tumor biopsies. DNA from both fresh frozen and formalin-fixed paraffin-embedded biopsies were analyzed and 94% specificity and 98% coverage of the targeted region was achieved. Reproducibility between replicates was high (R2 = 0, 98) and readily enabled detection of copy-number variations. The procedure can be carried out in <24 h and does not require any dedicated instrumentation

    Large trees drive forest aboveground biomass variation in moist lowland forests accross the tropics

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    peer reviewedaudience: researcher, professional, studentAim Large trees (d.b.h. 70 cm) store large amounts of biomass. Several studies suggest that large trees may be vulnerable to changing climate, potentially leading to declining forest biomass storage. Here we determine the importance of large trees for tropical forest biomass storage and explore which intrinsic (species trait) and extrinsic (environment) variables are associated with the density of large trees and forest biomass at continental and pan-tropical scales. Location Pan-tropical. Methods Aboveground biomass (AGB) was calculated for 120 intact lowland moist forest locations. Linear regression was used to calculate variation in AGB explained by the density of large trees. Akaike information criterion weights (AICcwi) were used to calculate averaged correlation coefficients for all possible multiple regression models between AGB/density of large trees and environmental and species trait variables correcting for spatial autocorrelation. Results Density of large trees explained c. 70% of the variation in pan-tropical AGB and was also responsible for significantly lower AGB in Neotropical [287.8 (mean) 105.0 (SD) Mg ha-1] versus Palaeotropical forests (Africa 418.3 91.8 Mg ha-1; Asia 393.3 109.3 Mg ha-1). Pan-tropical variation in density of large trees and AGB was associated with soil coarseness (negative), soil fertility (positive), community wood density (positive) and dominance of wind dispersed species (positive), temperature in the coldest month (negative), temperature in the warmest month (negative) and rainfall in the wettest month (positive), but results were not always consistent among continents. Main conclusions Density of large trees and AGB were significantly associated with climatic variables, indicating that climate change will affect tropical forest biomass storage. Species trait composition will interact with these future biomass changes as they are also affected by a warmer climate. Given the importance of large trees for variation in AGB across the tropics, and their sensitivity to climate change, we emphasize the need for in-depth analyses of the community dynamics of large trees

    An estimate of the number of tropical tree species

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    The high species richness of tropical forests has long been recognized, yet there remains substantial uncertainty regarding the actual number of tropical tree species. Using a pantropical tree inventory database from closed canopy forests, consisting of 657,630 trees belonging to 11,371 species, we use a fitted value of Fisher’s alpha and an approximate pantropical stem total to estimate the minimum number of tropical forest tree species to fall between ∼40,000 and ∼53,000, i.e. at the high end of previous estimates. Contrary to common assumption, the Indo-Pacific region was found to be as species-rich as the Neotropics, with both regions having a minimum of ∼19,000–25,000 tree species. Continental Africa is relatively depauperate with a minimum of ∼4,500–6,000 tree species. Very few species are shared among the African, American, and the Indo-Pacific regions. We provide a methodological framework for estimating species richness in trees that may help refine species richness estimates of tree-dependent taxa

    Large trees drive forest aboveground biomass variation in moist lowland forests across the tropics, Global

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    ABSTRACT Aim Large trees (d.b.h. Ն 70 cm) store large amounts of biomass. Several studies suggest that large trees may be vulnerable to changing climate, potentially leading to declining forest biomass storage. Here we determine the importance of large trees for tropical forest biomass storage and explore which intrinsic (species trait) and extrinsic (environment) variables are associated with the density of large trees and forest biomass at continental and pan-tropical scales. Location Pan-tropical. Methods Aboveground biomass (AGB) was calculated for 120 intact lowland moist forest locations. Linear regression was used to calculate variation in AGB explained by the density of large trees. Akaike information criterion weights (AICcwi) were used to calculate averaged correlation coefficients for all possible multiple regression models between AGB/density of large trees and environmental and species trait variables correcting for spatial autocorrelation. Results Density of large trees explained c. 70% of the variation in pan-tropical AGB and was also responsible for significantly lower AGB in Neotropical [287.8 (mean) Ϯ 105.0 (SD) Mg ha ). Pan-tropical variation in density of large trees and AGB was associated with soil coarseness (negative), soil fertility (positive), community wood density (positive) and dominance of wind dispersed species (positive), temperature in the coldest month (negative), temperature in the warmest month (negative) and rainfall in the wettest month (positive), but results were not always consistent among continents. Main conclusions Density of large trees and AGB were significantly associated with climatic variables, indicating that climate change will affect tropical forest biomass storage. Species trait composition will interact with these future biomass changes as they are also affected by a warmer climate. Given the importance of large trees for variation in AGB across the tropics, and their sensitivity to climate change, we emphasize the need for in-depth analyses of the community dynamics of large trees. bs_bs_banner Global Ecology and Biogeography, (Global Ecol. Biogeogr.
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