Asymmetric cyclopropanation of olefins catalysed by Cu(I) complexes of chiral pyridine-containing macrocyclic ligands (Pc-L*)

The synthesis and characterisation of copper(I) complexes of chiral pyridine-containing macrocyclic ligands (Pc-L*) and their use as catalysts in asymmetric cyclopropanation reactions are reported. All ligands and metal complexes were fully characterised, including crystal structures of some species determined by X-ray diffraction on single crystals. This allowed characterising the very different conformations of the macrocycles which could be induced by different substituents or by metal complexation. The strategy adopted for the ligand synthesis is very flexible allowing several structural modifications. A small library of macrocyclic ligands possessing the same donor properties but with either C-1 or C-2 symmetry was synthesized. Cyclopropane products with both aromatic and aliphatic olefins were obtained in good yields and enantiomeric excesses up to 99%.

Weathering geochemistry and Sr-Nd fingerprints of equatorial upper Nile and Congo muds

This study investigates processes of sediment generation in equatorial central Africa. An original, complete and integrated mineralogical-geochemical database on silt-sized sediments derived from different parent rocks (basalt, granite, gneiss, metapsammite, sandstone) along the East African Rift from 5°S in Tanzania to 5°N in Sudan is presented and used to assess the incidence of diverse factors controlling sediment composition (source-rock lithology, geomorphology, hydraulic sorting, grain size, recycling), with particular emphasis on chemical weathering.

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Computer simulation of glioma growth and morphology.

Despite major advances in the study of glioma, the quantitative links between intra-tumor molecular/cellular properties, clinically observable properties such as morphology, and critical tumor behaviors such as growth and invasiveness remain unclear, hampering more effective coupling of tumor physical characteristics with implications for prognosis and therapy. Although molecular biology, histopathology, and radiological imaging are employed in this endeavor, studies are severely challenged by the multitude of different physical scales involved in tumor growth, i.e., from molecular nanoscale to cell microscale and finally to tissue centimeter scale. Consequently, it is often difficult to determine the underlying dynamics across dimensions. New techniques are needed to tackle these issues. Here, we address this multi-scalar problem by employing a novel predictive three-dimensional mathematical and computational model based on first-principle equations (conservation laws of physics) that describe mathematically the diffusion of cell substrates and other processes determining tumor mass growth and invasion. The model uses conserved variables to represent known determinants of glioma behavior, e.g., cell density and oxygen concentration, as well as biological functional relationships and parameters linking phenomena at different scales whose specific forms and values are hypothesized and calculated based on in vitro and in vivo experiments and from histopathology of tissue specimens from human gliomas. This model enables correlation of glioma morphology to tumor growth by quantifying interdependence of tumor mass on the microenvironment (e.g., hypoxia, tissue disruption) and on the cellular phenotypes (e.g., mitosis and apoptosis rates, cell adhesion strength). Once functional relationships between variables and associated parameter values have been informed, e.g., from histopathology or intra-operative analysis, this model can be used for disease diagnosis/prognosis, hypothesis testing, and to guide surgery and therapy. In particular, this tool identifies and quantifies the effects of vascularization and other cell-scale glioma morphological characteristics as predictors of tumor-scale growth and invasion.

Predictive oncology: a review of multidisciplinary, multiscale in silico modeling linking phenotype, morphology and growth.

Empirical evidence and theoretical studies suggest that the phenotype, i.e., cellular- and molecular-scale dynamics, including proliferation rate and adhesiveness due to microenvironmental factors and gene expression that govern tumor growth and invasiveness, also determine gross tumor-scale morphology. It has been difficult to quantify the relative effect of these links on disease progression and prognosis using conventional clinical and experimental methods and observables. As a result, successful individualized treatment of highly malignant and invasive cancers, such as glioblastoma, via surgical resection and chemotherapy cannot be offered and outcomes are generally poor. What is needed is a deterministic, quantifiable method to enable understanding of the connections between phenotype and tumor morphology. Here, we critically assess advantages and disadvantages of recent computational modeling efforts (e.g., continuum, discrete, and cellular automata models) that have pursued this understanding. Based on this assessment, we review a multiscale, i.e., from the molecular to the gross tumor scale, mathematical and computational "first-principle" approach based on mass conservation and other physical laws, such as employed in reaction-diffusion systems. Model variables describe known characteristics of tumor behavior, and parameters and functional relationships across scales are informed from in vitro, in vivo and ex vivo biology. We review the feasibility of this methodology that, once coupled to tumor imaging and tumor biopsy or cell culture data, should enable prediction of tumor growth and therapy outcome through quantification of the relation between the underlying dynamics and morphological characteristics. In particular, morphologic stability analysis of this mathematical model reveals that tumor cell patterning at the tumor-host interface is regulated by cell proliferation, adhesion and other phenotypic characteristics: histopathology information of tumor boundary can be inputted to the mathematical model and used as a phenotype-diagnostic tool to predict collective and individual tumor cell invasion of surrounding tissue. This approach further provides a means to deterministically test effects of novel and hypothetical therapy strategies on tumor behavior.

Secondary prevention in the clinical management of patients with cardiovascular diseases. Core components, standards and outcome measures for referral and delivery

Despite major improvements in diagnostics and interventional therapies, cardiovascular diseases remain a major health care and socio-economic burden both in western and developing countries, in which this burden is increasing in close correlation to economic growth. Health authorities and the general population have started to recognize that the fight against these diseases can only be won if their burden is faced by increasing our investment on interventions in lifestyle changes and prevention. There is an overwhelming evidence of the efficacy of secondary prevention initiatives including cardiac rehabilitation in terms of reduction in morbidity and mortality. However, secondary prevention is still too poorly implemented in clinical practice, often only on selected populations and over a limited period of time. The development of systematic and full comprehensive preventive programmes is warranted, integrated in the organization of national health systems. Furthermore, systematic monitoring of the process of delivery and outcomes is a necessity. Cardiology and secondary prevention, including cardiac rehabilitation, have evolved almost independently of each other and although each makes a unique contribution it is now time to join forces under the banner of preventive cardiology and create a comprehensive model that optimizes long term outcomes for patients and reduces the future burden on health care services. These are the aims that the Cardiac Rehabilitation Section of the European Association for Cardiovascular Prevention & Rehabilitation has foreseen to promote secondary preventive cardiology in clinical practice.