A new spin on a compositionalist predictive modelling framework for conservation planning: a tropical case study in Ecuador

Knowledge about spatial biodiversity patterns is a basic criterion for reserve network design. Although herbarium collections hold large quantities of information, the data are often scattered and cannot supply complete spatial coverage. Alternatively, herbarium data can be used to fit species distribution models and their predictions can be used to provide complete spatial coverage and derive species richness maps. Here, we build on previous effort to propose an improved compositionalist framework for using species distribution models to better inform conservation management. We illustrate the approach with models fitted with six different methods and combined using an ensemble approach for 408 plant species in a tropical and megadiverse country (Ecuador). As a complementary view to the traditional richness hotspots methodology, consisting of a simple stacking of species distribution maps, the compositionalist modelling approach used here combines separate predictions for different pools of species to identify areas of alternative suitability for conservation. Our results show that the compositionalist approach better captures the established protected areas than the traditional richness hotspots strategies and allows the identification of areas in Ecuador that would optimally complement the current protection network. Further studies should aim at refining the approach with more groups and additional species information.

High pressure induced changes in beef muscle proteome: correlation with quality parameters

The relationship between pressure induced changes on individual proteins and selected quality parameters in bovine longissimus thoracis et lumborum (LTL) muscle was studied. Pressures ranging from 200 to 600 MPa at 20 °C were used. High pressure processing (HPP) at pressures above 200 MPa induced strong modifications of protein solubility, meat colour and water holding capacity (WHC). The protein profiles of non-treated and pressure treated meat were observed using two dimensional electrophoresis. Proteins showing significant differences in abundance among treatments were identified by mass spectrometry. Pressure levels above 200 MPa strongly modified bovine LTL proteome with main effects being insolubilisation of sarcoplasmic proteins and solubilisation of myofibrillar proteins. Sarcoplasmic proteins were more susceptible to HPP effects than myofibrillar. Individual protein changes were significantly correlated with protein solubility, L*, b* and WHC, providing further insights into the mechanistic processes underlying HPP influence on quality and providing the basis for the future development of protein markers to assess the quality of processed meats.

Dynamic Modelling of Material Flows and Sustainable Resource Use: Case Studies in Regional Metabolism and Space Life Support Systems

Sustainable resource use is one of the most important environmental issues of our times. It is closely related to discussions on the 'peaking' of various natural resources serving as energy sources, agricultural nutrients, or metals indispensable in high-technology applications. Although the peaking theory remains controversial, it is commonly recognized that a more sustainable use of resources would alleviate negative environmental impacts related to resource use. In this thesis, sustainable resource use is analysed from a practical standpoint, through several different case studies. Four of these case studies relate to resource metabolism in the Canton of Geneva in Switzerland: the aim was to model the evolution of chosen resource stocks and flows in the coming decades. The studied resources were copper (a bulk metal), phosphorus (a vital agricultural nutrient), and wood (a renewable resource). In addition, the case of lithium (a critical metal) was analysed briefly in a qualitative manner and in an electric mobility perspective. In addition to the Geneva case studies, this thesis includes a case study on the sustainability of space life support systems. Space life support systems are systems whose aim is to provide the crew of a spacecraft with the necessary metabolic consumables over the course of a mission. Sustainability was again analysed from a resource use perspective. In this case study, the functioning of two different types of life support systems, ARES and BIORAT, were evaluated and compared; these systems represent, respectively, physico-chemical and biological life support systems. Space life support systems could in fact be used as a kind of 'laboratory of sustainability' given that they represent closed and relatively simple systems compared to complex and open terrestrial systems such as the Canton of Geneva. The chosen analysis method used in the Geneva case studies was dynamic material flow analysis: dynamic material flow models were constructed for the resources copper, phosphorus, and wood. Besides a baseline scenario, various alternative scenarios (notably involving increased recycling) were also examined. In the case of space life support systems, the methodology of material flow analysis was also employed, but as the data available on the dynamic behaviour of the systems was insufficient, only static simulations could be performed. The results of the case studies in the Canton of Geneva show the following: were resource use to follow population growth, resource consumption would be multiplied by nearly 1.2 by 2030 and by 1.5 by 2080. A complete transition to electric mobility would be expected to only slightly (+5%) increase the copper consumption per capita while the lithium demand in cars would increase 350 fold. For example, phosphorus imports could be decreased by recycling sewage sludge or human urine; however, the health and environmental impacts of these options have yet to be studied. Increasing the wood production in the Canton would not significantly decrease the dependence on wood imports as the Canton's production represents only 5% of total consumption. In the comparison of space life support systems ARES and BIORAT, BIORAT outperforms ARES in resource use but not in energy use. However, as the systems are dimensioned very differently, it remains questionable whether they can be compared outright. In conclusion, the use of dynamic material flow analysis can provide useful information for policy makers and strategic decision-making; however, uncertainty in reference data greatly influences the precision of the results. Space life support systems constitute an extreme case of resource-using systems; nevertheless, it is not clear how their example could be of immediate use to terrestrial systems.

Stand dynamics modelling approaches for multicohort management of eastern Canadian boreal forests

Abstract

Beta-catenin Status in P?aediatric Medulloblastomas: correlation of immunohistochemical expression with mutational status, genetic profiles, and clinical characteristics.

Medulloblastoma is the most frequent malignant paediatric brain tumour. The activation of the Wnt/beta-catenin pathway occurs in 10-15% of medulloblastomas and has been recently described as a marker for favourable patient outcome. We report a series of 72 paediatric medulloblastomas evaluated for beta-catenin protein expression, CTNNB1 mutations, and comparative genomic hybridization. Gene expression profiles were also available in a subset of 40 cases. Immunostaining of beta-catenin showed extensive nuclear staining (>50% of the tumour cells) in six cases and focal nuclear staining (<10% of cells) in three cases. The other cases either exhibited a signal strictly limited to the cytoplasm (58 cases) or were negative (five cases). CTNNB1 mutations were detected in all beta-catenin extensively nucleopositive cases. The expression profiles of these cases documented strong activation of the Wnt/beta-catenin pathway. Remarkably, five out of these six tumours showed a complete loss of chromosome 6. In contrast, cases with focal nuclear beta-catenin staining, as well as tumours with negative or cytoplasmic staining, never demonstrated CTNNB1 mutation, Wnt/beta-catenin pathway activation or chromosome 6 loss. Patients with extensive nuclear staining were significantly older at diagnosis and were in continuous complete remission after a mean follow-up of 75.7 months (range 27.5-121.2 months) from diagnosis. All three patients with focal nuclear staining of beta-catenin died within 36 months from diagnosis. Altogether, these data confirm and extend previous observations that CTNNB1-mutated tumours represent a distinct molecular subgroup of medulloblastomas with favourable outcome, indicating that therapy de-escalation should be considered. International consensus on the definition criteria of this distinct medulloblastoma subgroup should be achieved.

Review of CT features of saprophytic aspergillosis (Aspergilloma) and correlation with final diagnosis : P21

Purpose: 1. To review Ct features suggestive of saprophytic aspergillosis (aspergilloma) and to correlate them with the final pathological results. 2. To illustrate the wide range of differential diagnosis. Methods and materials: The electronic database of our department from 1995 to 2007 revealed CT reports of 48 patients that had been considered very suggestive of aspergilloma. Two radiologists with 6 and 12 years experience in thoracic radiology jointly reviewed the corresponding CT features including ancillary findings and the underlying lung diseases and correlated them with the final pathological diagnosis. Results: Forty patients could be included in the study (12 women, mean age 52), while in 8 patients there was no adequate clinical follow-up. In 17 patients the diagnosis "mycetoma" due to aspergillus fumigatus infection was confirmed, either by surgery, biopsy or bronchoscopy. In 23 patients, differential diagnoses were found, such as cavitating bronchial carcinoma (n = 7), bacterial abscess (n = 3), typical (n = 2) and atypical (n = 2) tuberculosis, as well as inflammatory changes due to mucoviscidosis (n = 1), Wegener's disease (n = 1) or chronic obstructive pulmonary disease (n = 3). Fibromyxoide hamartoma, lung infarction and bronchomucocele were responsible for the typical CT feature in one patient each. Conclusion: 1. The typical CT feature suggesting mycetoma is softtissue proliferation within a pre-existing wall-thickened lung cavity, oten even considered "pathognomonic". However, this diagnosis was finally confirmed by surgery or laboratory findings in less than 50% of patients only. 2. Since differential diagnoses are very large, not only including cavitating lung cancer and tuberculosis, the individual underlying lung disease needs strongly being taken into account often giving the best clue for the correct diagnosis.

Analysis of sensitivity with respect to a compositional parameter : A comment on 'Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling' by L. Loosvelt and co-authors

A comment about the article “Local sensitivity analysis for compositional data with application to soil texture in hydrologic modelling” writen by L. Loosvelt and co-authors. The present comment is centered in three specific points. The first one is related to the fact that the authors avoid the use of ilr-coordinates. The second one refers to some generalization of sensitivity analysis when input parameters are compositional. The third tries to show that the role of the Dirichlet distribution in the sensitivity analysis is irrelevant

Partial correlation : Network analysis

The final year project came to us as an opportunity to get involved in a topic which has appeared to be attractive during the learning process of majoring in economics: statistics and its application to the analysis of economic data, i.e. econometrics.Moreover, the combination of econometrics and computer science is a very hot topic nowadays, given the Information Technologies boom in the last decades and the consequent exponential increase in the amount of data collected and stored day by day. Data analysts able to deal with Big Data and to find useful results from it are verydemanded in these days and, according to our understanding, the work they do, although sometimes controversial in terms of ethics, is a clear source of value added both for private corporations and the public sector. For these reasons, the essence of this project is the study of a statistical instrument valid for the analysis of large datasets which is directly related to computer science: Partial Correlation Networks.The structure of the project has been determined by our objectives through the development of it. At first, the characteristics of the studied instrument are explained, from the basic ideas up to the features of the model behind it, with the final goal of presenting SPACE model as a tool for estimating interconnections in between elements in large data sets. Afterwards, an illustrated simulation is performed in order to show the power and efficiency of the model presented. And at last, the model is put into practice by analyzing a relatively large data set of real world data, with the objective of assessing whether the proposed statistical instrument is valid and useful when applied to a real multivariate time series. In short, our main goals are to present the model and evaluate if Partial Correlation Network Analysis is an effective, useful instrument and allows finding valuable results from Big Data.As a result, the findings all along this project suggest the Partial Correlation Estimation by Joint Sparse Regression Models approach presented by Peng et al. (2009) to work well under the assumption of sparsity of data. Moreover, partial correlation networks are shown to be a very valid tool to represent cross-sectional interconnections in between elements in large data sets.The scope of this project is however limited, as there are some sections in which deeper analysis would have been appropriate. Considering intertemporal connections in between elements, the choice of the tuning parameter lambda, or a deeper analysis of the results in the real data application are examples of aspects in which this project could be completed.To sum up, the analyzed statistical tool has been proved to be a very useful instrument to find relationships that connect the elements present in a large data set. And after all, partial correlation networks allow the owner of this set to observe and analyze the existing linkages that could have been omitted otherwise.

Modelling variation of needle density of Scots pine at high latitudes

[Abstract]