Design, synthesis and pharmacological evaluation of non-peptidergic ligands for the human CXCR3 receptor

Leurs, R. [Promotor]Timmerman, H. [Promotor]Esch, I.J.P. [Copromotor]de Wijtmans, M. [Copromotor

Implant supported cantilevered fixed dental rehabilitations in partially edentulous patients : systematic review of the literature. Part I

Objectives: To investigate in which clinical situations a cantilever fixed implant supported restorations can be a treatment alternative and which complications are reported. Materials and Methods: Two operators screened the literature (MEDLINE, EMBASE) and performed a hand search on the main journals dealing with implantology and prosthetics until 31 December 2017. Only articles that considered cantilever implant fixed restorations with at least 10 patients and with a mean follow-up of at least 5\ua0year were selected. The outcome variables were survival of implants and prosthesis, mechanical, technical and biological complications, marginal bone loss. The review was performed according to the PRISMA statements. Risk of bias assessment was evaluated. Failure and complication rates were analysed using random effect Poisson regression models to obtain summary estimate of 5- and 10-year survival and complication rates. Results: A total of nine papers were selected for partially edentulous patients and reported high survival rate of the prosthesis. The estimated survival rate for 5\u201310\ua0years was calculated to be 98.4% for the implants and 99.2% for the rehabilitations. Mechanical, technical and biological complications were reported with a cumulative 5\u201310\ua0years complication rate of 28.66% and 26.57% for the patients and for the prosthesis, respectively. Two papers for single implant supporting 2-unit cantilever were not sufficient to draw conclusions. Conclusions: There is evidence that cantilever can be successful treatment in partially edentulous patients. In two adjacent edentulous sites, data are not yet sufficient

Purple sulfur bacteria fix N-2 via molybdenum-nitrogenase in a low molybdenum Proterozoic ocean analogue

Biological N-2 fixation was key to the expansion of life on early Earth. The N-2-fixing microorganisms and the nitrogenase type used in the Proterozoic are unknown, although it has been proposed that the canonical molybdenum-nitrogenase was not used due to low molybdenum availability. We investigate N-2 fixation in Lake Cadagno, an analogue system to the sulfidic Proterozoic continental margins, using a combination of biogeochemical, molecular and single cell techniques. In Lake Cadagno, purple sulfur bacteria (PSB) are responsible for high N-2 fixation rates, to our knowledge providing the first direct evidence for PSB in situ N-2 fixation. Surprisingly, no alternative nitrogenases are detectable, and N-2 fixation is exclusively catalyzed by molybdenum-nitrogenase. Our results show that molybdenum-nitrogenase is functional at low molybdenum conditions in situ and that in contrast to previous beliefs, PSB may have driven N-2 fixation in the Proterozoic ocean. N-2 fixation was key to the expansion of life on Earth, but which organisms fixed N-2 and if Mo-nitrogenase was functional in the low Mo early ocean is unknown. Here, the authors show that purple sulfur bacteria fix N-2 using Mo-nitrogenase in a Proterozoic ocean analogue, despite low Mo conditions

Prediction of the information processing speed performance in multiple sclerosis using a machine learning approach in a large multicenter magnetic resonance imaging data set

Many patients with multiple sclerosis (MS) experience information processing speed (IPS) deficits, and the Symbol Digit Modalities Test (SDMT) has been recommended as a valid screening test. Magnetic resonance imaging (MRI) has markedly improved the understanding of the mechanisms associated with cognitive deficits in MS. However, which structural MRI markers are the most closely related to cognitive performance is still unclear. We used the multicenter 3T-MRI data set of the Italian Neuroimaging Network Initiative to extract multimodal data (i.e., demographic, clinical, neuropsychological, and structural MRIs) of 540 MS patients. We aimed to assess, through machine learning techniques, the contribution of brain MRI structural volumes in the prediction of IPS deficits when combined with demographic and clinical features. We trained and tested the eXtreme Gradient Boosting (XGBoost) model following a rigorous validation scheme to obtain reliable generalization performance. We carried out a classification and a regression task based on SDMT scores feeding each model with different combinations of features. For the classification task, the model trained with thalamus, cortical gray matter, hippocampus, and lesions volumes achieved an area under the receiver operating characteristic curve of 0.74. For the regression task, the model trained with cortical gray matter and thalamus volumes, EDSS, nucleus accumbens, lesions, and putamen volumes, and age reached a mean absolute error of 0.95. In conclusion, our results confirmed that damage to cortical gray matter and relevant deep and archaic gray matter structures, such as the thalamus and hippocampus, is among the most relevant predictors of cognitive performance in MS

A Semiautomatic Method for Multiple Sclerosis Lesion Segmentation on Dual-Echo MR Imaging: Application in a Multicenter Context

BACKGROUND AND PURPOSE: The automatic segmentation of MS lesions could reduce time required for image processing together with inter- and intraoperator variability for research and clinical trials. A multicenter validation of a proposed semiautomatic method for hyperintense MS lesion segmentation on dual-echo MR imaging is presented. MATERIALS AND METHODS: The classification technique used is based on a region-growing approach starting from manual lesion identification by an expert observer with a final segmentation-refinement step. The method was validated in a cohort of 52 patients with relapsing-remitting MS, with dual-echo images acquired in 6 different European centers. RESULTS: We found a mathematic expression that made the optimization of the method independent of the need for a training dataset. The automatic segmentation was in good agreement with the manual segmentation (dice similarity coefficient = 0.62 and root mean square error = 2 mL). Assessment of the segmentation errors showed no significant differences in algorithm performance between the different MR scanner manufacturers (P > .05). CONCLUSIONS: The method proved to be robust, and no center-specific training of the algorithm was required, offering the possibility for application in a clinical setting. Adoption of the method should lead to improved reliability and less operator time required for image analysis in research and clinical trials in MS

Design and validation of a DNA-microarray for phylogenetic analysis of bacterial communities in different oral samples and dental implants

The quali-quantitative characterization of the oral microbiota is crucial for an exhaustive knowledge of the oral ecology and the modifications of the microbial composition that occur during periodontal pathologies. In this study, we designed and validated a new phylogenetic DNA-microarray (OralArray) to quickly and reliably characterize the most representative bacterial groups that colonize the oral cavity. The OralArray is based on the Ligation Detection Reaction technology associated to Universal Arrays (LDR-UA), and includes 22 probe sets targeted to bacteria belonging to the phyla Firmicutes, Proteobacteria, Actinobacteria, Bacteroidetes, Fusobacteria, and Spirochaete. The tool is characterized by high specificity, sensitivity and reproducibility. The OralArray was successfully tested and validated on different oral samples (saliva, lingual plaque, supragingival plaque, and healing cap) collected from 10 healthy subjects. For each specimen, a microbial signature was obtained, and our results established the presence of an oral microbial profile specific for each subject. Moreover, the tool was applied to evaluate the efficacy of a disinfectant treatment on the healing caps before their usage. The OralArray is, thus, suitable to study the microbiota associated with various oral sites and to monitor changes arising from therapeutic treatments