Mapping landscape-scale peatland degradation using airborne lidar and multispectral data

This is the final version. Available on open access from Springer via the DOI in this recordContext An increased interest in the restoration of peatlands for delivering multiple benefits requires a greater understanding of the extent and location of natural and artificial features that contribute to degradation. Objectives We assessed the utility of multiple, fine-grained remote sensing datasets for mapping peatland features and associated degraded areas at a landscape-scale. Specifically, we developed an integrated approach to identify and quantify multiple types of peatland degradation including: anthropogenic drainage ditches and peat cuttings; erosional gullies and bare peat areas. Methods Airborne LiDAR, CASI and aerial image datasets of the South West UK, were combined to identify features within Dartmoor National Park peatland area that contribute to degradation. These features were digitised and quantified using ArcGIS before appropriate buffers were applied to estimate the wider ecohydrologically affected area. Results Using fine-scale, large-extent remotely sensed data, combined with aerial imagery enabled key features within the wider expanse of peatland to be successfully identified and mapped at a resolution appropriate to future targeted restoration. Combining multiple datasets increased our understanding of spatial distribution and connectivity within the landscape. An area of 29 km2 or 9.2% of the Dartmoor peatland area was identified as significantly and directly ecohydrologically degraded. Conclusions Using a combination of fine-grained remotely sensed datasets has advantages over traditional ground survey methods for identification and mapping of anthropogenic and natural erosion features at a landscape scale. The method is accurate, robust and cost-effective particularly given the remote locations and large extent of these landscapes, facilitating effective and targeted restoration planning, management and monitoring.Dartmoor National Park AuthorityDartmoor Peatland PartnershipDuchy of CornwallEnvironment AgencyForestry CommissionMinistry of DefenceNatural EnglandSouth West partnership for Environmental and Economic Prosperity (SWEEP)South West WaterNatural Environment Research Council (NERC

Drain blocking has limited short-term effects on greenhouse gas fluxes in a Molinia caerulea dominated shallow peatland (article)

This is the final version. Available on open access from Elsevier via the DOI in this recordThe dataset associated with this article is available in ORE at https://doi.org/10.24378/exe.2723Drained peatlands dominated by purple moor grass (Molinia caerulea) are widespread in the UK and Western Europe. Although substantial carbon stores may be present in these peatlands, in this degraded state they are not currently acting as carbon sinks. Therefore, M.caerulea dominated peatlands have been identified as potential sites for ecohydrological restoration to tackle the current climate emergency. However, at present little is known about whether ditch blocking can raise water tables and promote the recovery of bog plant species, and the subsequent effects on carbon sequestration in these peatlands. To investigate the potential for restoration, we measured changes in water table depth, vegetation composition, photosynthesis at 1000 μmol Photons m−2 s−1 (PG1000), ecosystem respiration (REco) and partitioned below-ground respiration in two M.caerulea dominated peatlands in which drainage ditches had been blocked located in Exmoor National Park, southwest England. Measurements were made in two headwater catchments at ⅛, ¼ and ½ of the distance between adjacent drainage ditches at four control-restored paired sites, during the growing seasons pre- (2012) and post- (2014, 2016 & 2018) restoration. Restoration had a small but significant (p = 0.009) effect on water table depths however, this did not result in a significant change in vegetation composition (p > 0.350). Ecosystem respiration increased in both the control and restored locations following restoration however, this increase was significantly smaller (p = 0.010) at the restored locations, possibly due to a similarly reduced increase in photosynthesis, although this change was not significant (p = 0.116). Below-ground respiration showed no significant changes following restoration. This research illustrates how degraded these shallow peatlands are, and raises concerns that ditch blocking alone may not bring about the high and stable water tables required to perturb the existing Molinia caerulea-dominated ecosystem and substantially alter the carbon balance. Additional restoration measures may be required.South West Water (SWW)University of ExeterTechnology Strategy Board CouncilNatural Environment Research Council (NERC

Scaling properties of protein family phylogenies

One of the classical questions in evolutionary biology is how evolutionary processes are coupled at the gene and species level. With this motivation, we compare the topological properties (mainly the depth scaling, as a characterization of balance) of a large set of protein phylogenies with a set of species phylogenies. The comparative analysis shows that both sets of phylogenies share remarkably similar scaling behavior, suggesting the universality of branching rules and of the evolutionary processes that drive biological diversification from gene to species level. In order to explain such generality, we propose a simple model which allows us to estimate the proportion of evolvability/robustness needed to approximate the scaling behavior observed in the phylogenies, highlighting the relevance of the robustness of a biological system (species or protein) in the scaling properties of the phylogenetic trees. Thus, the rules that govern the incapability of a biological system to diversify are equally relevant both at the gene and at the species level.Comment: Replaced with final published versio

A comparison of sunlight exposure in men with prostate cancer and basal cell carcinoma

Ultraviolet radiation exposure increases basal cell carcinoma (BCC) risk, but may be protective against prostate cancer. We attempted to identify exposure patterns that confer reduced prostate cancer risk without increasing that of BCC. We used a questionnaire to assess exposure in 528 prostate cancer patients and 442 men with basal cell carcinoma, using 365 benign prostatic hypertrophy patients as controls. Skin type 1 (odds ratio (OR)=0.47, 95% CI=0.26–0.86), childhood sunburning (OR=0.38, 95% CI=0.26–0.57), occasional/frequent sunbathing (OR=0.21, 95% CI=0.14–0.31), lifetime weekday (OR=0.85, 95% CI=0.80–0.91) and weekend exposure (OR=0.79, 95% CI=0.73–0.86) were associated with reduced prostate cancer risk. Skin type 1 (OR=4.00, 95% CI=2.16–7.41), childhood sunburning (OR=1.91, 95% CI=1.36–2.68), regular foreign holidays (OR=6.91, 95% CI=5.00-9.55) and weekend (OR=1.17, 95% CI=1.08–1.27) but not weekday exposure were linked with increased BCC risk. Combinations of one or two parameters were associated with a progressive decrease in the ORs for prostate cancer risk (OR=0.54–0.25) with correspondingly increased BCC risk (OR=1.60–2.54). Our data do not define exposure patterns that reduce prostate cancer risk without increasing BCC risk

EL_PSSM-RT:DNA-binding residue prediction by integrating ensemble learning with PSSM Relation Transformation

Background: Prediction of DNA-binding residue is important for understanding the protein-DNA recognition mechanism. Many computational methods have been proposed for the prediction, but most of them do not consider the relationships of evolutionary information between residues. Results: In this paper, we first propose a novel residue encoding method, referred to as the Position Specific Score Matrix (PSSM) Relation Transformation (PSSM-RT), to encode residues by utilizing the relationships of evolutionary information between residues. PDNA-62 and PDNA-224 are used to evaluate PSSM-RT and two existing PSSM encoding methods by five-fold cross-validation. Performance evaluations indicate that PSSM-RT is more effective than previous methods. This validates the point that the relationship of evolutionary information between residues is indeed useful in DNA-binding residue prediction. An ensemble learning classifier (EL_PSSM-RT) is also proposed by combining ensemble learning model and PSSM-RT to better handle the imbalance between binding and non-binding residues in datasets. EL_PSSM-RT is evaluated by five-fold cross-validation using PDNA-62 and PDNA-224 as well as two independent datasets TS-72 and TS-61. Performance comparisons with existing predictors on the four datasets demonstrate that EL_PSSM-RT is the best-performing method among all the predicting methods with improvement between 0.02-0.07 for MCC, 4.18-21.47% for ST and 0.013-0.131 for AUC. Furthermore, we analyze the importance of the pair-relationships extracted by PSSM-RT and the results validates the usefulness of PSSM-RT for encoding DNA-binding residues. Conclusions: We propose a novel prediction method for the prediction of DNA-binding residue with the inclusion of relationship of evolutionary information and ensemble learning. Performance evaluation shows that the relationship of evolutionary information between residues is indeed useful in DNA-binding residue prediction and ensemble learning can be used to address the data imbalance issue between binding and non-binding residues. A web service of EL_PSSM-RT ( http://hlt.hitsz.edu.cn:8080/PSSM-RT_SVM/ ) is provided for free access to the biological research community

The Information Coded in the Yeast Response Elements Accounts for Most of the Topological Properties of Its Transcriptional Regulation Network

The regulation of gene expression in a cell relies to a major extent on transcription factors, proteins which recognize and bind the DNA at specific binding sites (response elements) within promoter regions associated with each gene. We present an information theoretic approach to modeling transcriptional regulatory networks, in terms of a simple “sequence-matching” rule and the statistics of the occurrence of binding sequences of given specificity in random promoter regions. The crucial biological input is the distribution of the amount of information coded in these cognate response elements and the length distribution of the promoter regions. We provide an analysis of the transcriptional regulatory network of yeast Saccharomyces cerevisiae, which we extract from the available databases, with respect to the degree distributions, clustering coefficient, degree correlations, rich-club coefficient and the k-core structure. We find that these topological features are in remarkable agreement with those predicted by our model, on the basis of the amount of information coded in the interaction between the transcription factors and response elements

Transcriptional landscape of bone marrow-derived very small embryonic-like stem cells during hypoxia

<p>Abstract</p> <p>Background</p> <p>Hypoxia is a ubiquitous feature of many lung diseases and elicits cell-specific responses. While the effects of hypoxia on stem cells have been examined under <it>in vitro </it>conditions, the consequences of <it>in vivo </it>oxygen deprivation have not been studied.</p> <p>Methods</p> <p>We investigated the effects of <it>in vivo </it>hypoxia on a recently characterized population of pluripotent stem cells known as very small embryonic-like stem cells (VSELs) by whole-genome expression profiling and measuring peripheral blood stem cell chemokine levels.</p> <p>Results</p> <p>We found that exposure to hypoxia in mice mobilized VSELs from the bone marrow to peripheral blood, and induced a distinct genome-wide transcriptional signature. Applying a computationally-intensive methodology, we identified a hypoxia-induced gene interaction network that was functionally enriched in a diverse array of programs including organ-specific development, stress response, and wound repair. Topographic analysis of the network highlighted a number of densely connected hubs that may represent key controllers of stem cell response during hypoxia and, therefore, serve as putative targets for altering the pathophysiologic consequences of hypoxic burden.</p> <p>Conclusions</p> <p>A brief exposure to hypoxia recruits pluripotent stem cells to the peripheral circulation and actives diverse transcriptional programs that are orchestrated by a selective number of key genes.</p

Metabolome Based Reaction Graphs of M. tuberculosis and M. leprae: A Comparative Network Analysis

BACKGROUND: Several types of networks, such as transcriptional, metabolic or protein-protein interaction networks of various organisms have been constructed, that have provided a variety of insights into metabolism and regulation. Here, we seek to exploit the reaction-based networks of three organisms for comparative genomics. We use concepts from spectral graph theory to systematically determine how differences in basic metabolism of organisms are reflected at the systems level and in the overall topological structures of their metabolic networks. METHODOLOGY/PRINCIPAL FINDINGS: Metabolome-based reaction networks of Mycobacterium tuberculosis, Mycobacterium leprae and Escherichia coli have been constructed based on the KEGG LIGAND database, followed by graph spectral analysis of the network to identify hubs as well as the sub-clustering of reactions. The shortest and alternate paths in the reaction networks have also been examined. Sub-cluster profiling demonstrates that reactions of the mycolic acid pathway in mycobacteria form a tightly connected sub-cluster. Identification of hubs reveals reactions involving glutamate to be central to mycobacterial metabolism, and pyruvate to be at the centre of the E. coli metabolome. The analysis of shortest paths between reactions has revealed several paths that are shorter than well established pathways. CONCLUSIONS: We conclude that severe downsizing of the leprae genome has not significantly altered the global structure of its reaction network but has reduced the total number of alternate paths between its reactions while keeping the shortest paths between them intact. The hubs in the mycobacterial networks that are absent in the human metabolome can be explored as potential drug targets. This work demonstrates the usefulness of constructing metabolome based networks of organisms and the feasibility of their analyses through graph spectral methods. The insights obtained from such studies provide a broad overview of the similarities and differences between organisms, taking comparative genomics studies to a higher dimension

Oxford Phase 3 unicompartmental knee arthroplasty: medium-term results of a minimally invasive surgical procedure

PURPOSE: In the last decade, a major increase in the use of and interest in unicompartmental knee arthroplasty (UKA) has developed. The Oxford Phase 3 UKA is implanted with a minimally invasive technique using newly developed instruments. The objective of this prospective study was to evaluate the outcome of UKA in patients with medial osteoarthritis of the knee in a high-volume unit. METHODS: Two-hundred and forty-four UKAs were performed with a minimally invasive approach. The median age was 72 (43-91) years. The median follow-up was 4.2 years (range 1-10.4 years). Fourteen patients died, and nine were considered to be lost to follow-up, but all had a well-functioning prosthesis in situ until their last follow-up. Pain, function and health-related quality of life were evaluated pre- and postoperatively using patient- and assessor-based outcome scores, as well as radiographic evidence. RESULTS: The mean Knee Society knee and function scores, WOMAC-scores, Oxford-score and VAS pain and satisfaction all improved. Nine knees required revision. Eleven patients required an additional arthroscopic procedure due to persisting pain secondary to intra-articular pathology, and four patients required manipulation under anaesthesia because of limited range of motion. The 7-year cumulative survival rate of the arthroplasty was 94.4%. A low incidence (21%) of a radiolucent line beneath the tibial component was observed at 5 years of follow-up. CONCLUSION: This study showed a high survival rate of the Oxford Phase 3 UKA. Patient satisfaction and functional performance were also very high. Major complication rate was low; in addition, the incidence of radiolucency under the tibial component, when compared to present literature, was low. When strict indication criteria are followed, excellent, durable, and in our opinion reliable, results can be expected for this procedur

Inferring Condition-Specific Modulation of Transcription Factor Activity in Yeast through Regulon-Based Analysis of Genomewide Expression

Background: A key goal of systems biology is to understand how genomewide mRNA expression levels are controlled by transcription factors (TFs) in a condition-specific fashion. TF activity is frequently modulated at the post-translational level through ligand binding, covalent modification, or changes in sub-cellular localization. In this paper, we demonstrate how prior information about regulatory network connectivity can be exploited to infer condition-specific TF activity as a hidden variable from the genomewide mRNA expression pattern in the yeast Saccharomyces cerevisiae. Methodology/Principal Findings: We first validate experimentally that by scoring differential expression at the level of gene sets or "regulons" comprised of the putative targets of a TF, we can accurately predict modulation of TF activity at the post-translational level. Next, we create an interactive database of inferred activities for a large number of TFs across a large number of experimental conditions in S. cerevisiae. This allows us to perform TF-centric analysis of the yeast regulatory network. Conclusions/Significance: We analyze the degree to which the mRNA expression level of each TF is predictive of its regulatory activity. We also organize TFs into "co-modulation networks" based on their inferred activity profile across conditions, and find that this reveals functional and mechanistic relationships. Finally, we present evidence that the PAC and rRPE motifs antagonize TBP-dependent regulation, and function as core promoter elements governed by the transcription regulator NC2. Regulon-based monitoring of TF activity modulation is a powerful tool for analyzing regulatory network function that should be applicable in other organisms. Tools and results are available online at http://bussemakerlab.org/RegulonProfiler/