ECOPLAN-SE: Ruimtelijke analyse van ecosysteemdiensten in Vlaanderen, een Q-GIS plugin

ECOPLAN-SE is een ruimtelijk expliciete tool (QGIS) voor het beoordelen van de impact van landgebruikveranderingen op de levering van ecosysteemdiensten. De ontwikkeling van deze tool kadert in het het SBO-project “ECOPLAN” (Planning for Ecosystem Services). ECOPLAN ontwikkelt ruimtelijk expliciete informatie en instrumenten voor de beoordeling van ecosysteemdiensten. Het ontwerpt instrumenten voor de evaluatie van functionele ecosystemen als een kostenefficiënte strategie om de landgebruiksefficiëntie en milieukwaliteit te verbeteren. Het ontwikkelt open source eindproducten voor het identificeren, kwantificeren, waarderen, valideren en monitoren van ecosysteemdiensten. Deze producten kunnen door administraties en consultants worden ingezet in projectontwikkeling, kosten-baten analyses, milieueffecten rapportering, etc

Preclinical in vivo longitudinal assessment of KG207-M as a disease-modifying Alzheimer's disease therapeutic

In vivo biomarker abnormalities provide measures to monitor therapeutic interventions targeting amyloid-β pathology as well as its effects on downstream processes associated with Alzheimer’s disease pathophysiology. Here, we applied an in vivo longitudinal study design combined with imaging and cerebrospinal fluid biomarkers, mirroring those used in human clinical trials to assess the efficacy of a novel brain-penetrating anti-amyloid fusion protein treatment in the McGill-R-Thy1-APP transgenic rat model. The bi-functional fusion protein consisted of a blood-brain barrier crossing single domain antibody (FC5) fused to an amyloid-β oligomer-binding peptide (ABP) via Fc fragment of mouse IgG (FC5-mFc2a-ABP). A five-week treatment with FC5-mFc2a-ABP (loading dose of 30 mg/Kg/iv followed by 15 mg/Kg/week/iv for four weeks) substantially reduced brain amyloid-β levels as measured by positron emission tomography and increased the cerebrospinal fluid amyloid-β42/40 ratio. In addition, the 5-week treatment rectified the cerebrospinal fluid neurofilament light chain concentrations, resting-state functional connectivity, and hippocampal atrophy measured using magnetic resonance imaging. Finally, FC5-mFc2a-ABP (referred to as KG207-M) treatment did not induce amyloid-related imaging abnormalities such as microhemorrhage. Together, this study demonstrates the translational values of the designed preclinical studies for the assessment of novel therapies based on the clinical biomarkers providing tangible metrics for designing early-stage clinical trials

Some generalizations of the Anderson-Darling statistic

The Anderson-Darling statistic is basically a weighted average of Pearson statistics. In this paper, we first propose to use other weights and next we generalize the Anderson-Darling statistic by inserting the Cressie-and-Read family of statistics into the Anderson-Darling statistic.Anderson-Darling Goodness-of-fit Sample space partitions

EMLasso: Logistic lasso with missing data

In clinical settings, missing data in the covariates occur frequently. For example, some markers are expensive or hard to measure. When this sort of data is used for model selection, the missingness is often resolved through a complete case analysis or a form of single imputation. An alternative sometimes comes in the form of leaving the most damaged covariates out. All these strategies jeopardise the goal of model selection.In earlier work, we have applied the logistic Lasso in combination with multiple imputation to obtain results in such settings, but we only provided heuristic arguments to advocate the method. In this paper, we propose an improved method that builds on firm statistical arguments and that is developed along the lines of the stochastic expectation-maximisation algorithm. We show that our method can be used to handle missing data in both categorical and continuous predictors, as well as in a nonpenalised regression. We demonstrate the method by applying it to data of 273 lung cancer patients. The objective is to select a model for the prediction of acute dysphagia, starting from a large set of potential predictors, including clinical and treatment covariates as well as a set of single-nucleotide polymorphisms

Graphical Models: Applicability and Software

A class of models for mixed continuous and nominal data was proposed by Lauritzen and Wermuth. Log-linear models, linear regression and (M)ANOVA are special cases of these mixed graphical models. Their clear interpretation by means of independence graphs based on Markov properties makes them useful in applied multivariate statistics. Only few statistical software is developed yet for these models. MIM and CoCo are briefly discussed in this paper. XLISP-STAT seems to be an attractive environment for further software development in this area. 1 Introduction Mixed graphical association models were introduced by Lauritzen and Wermuth in 1989. In this key paper they brought together two streams in graphical modelling: conditional modelling with continuous variables and with discrete variables. Although both were based upon the same principles of path analysis (Wright, 1921), they were developed separately. In discrete analysis the techniques are related to log-linear modelling. For the con..

Extreme value statistics: Potential benefits in water quality management

Recently extreme value statistics have proven useful in environmental applications like the assessment of sea-levels, wind speeds and ozone concentrations. In this paper, after a brief overview of the statistical theory of extreme values, modelling issues are discussed with stress on applications in water quality management. Risk analysis procedures are presented that consider the extremal behaviour of water quality in the design stage of environmental constructions