Butyrylcholinesterase as a prognostic marker: a review of the literature.

BACKGROUND: Butyrylcholinesterase (BChE) is an α-glycoprotein synthesized in the liver. Its serum level decreases in many clinical conditions such as acute and chronic liver damage, inflammation, injury and infections, and malnutrition. METHODS AND RESULTS: This review collects the main evidence on the emerging role of butyrylcholinesterase as a prognostic marker of liver and nonliver diseases as well as a marker of protein-energy malnutrition and obesity. In fact, serum concentrations and BChE activity seem to accurately reflect the availability of amino acidic substrates and/or derangement in protein synthesis due to hepatocellular damage. In cancer, with or without liver impairment, serum BChE levels serve as an accurate functional and prognostic indicator, useful for monitoring clinical and therapeutic interventions according to patients’ prognosis. In the absence of inflammation, BChE could also serve as an index of the effectiveness of nutritional support. CONCLUSIONS: Serum BChE assessment should be included in routine clinical diagnostic procedures to evaluate patient clinical conditions, in particular in cases of inflammation and/or protein-energy malnutrition

Cancer initiation and progression: an unsimplifiable complexity

BACKGROUND: Cancer remains one of the most complex diseases affecting humans and, despite the impressive advances that have been made in molecular and cell biology, how cancer cells progress through carcinogenesis and acquire their metastatic ability is still widely debated. CONCLUSION: There is no doubt that human carcinogenesis is a dynamic process that depends on a large number of variables and is regulated at multiple spatial and temporal scales. Viewing cancer as a system that is dynamically complex in time and space will, however, probably reveal more about its underlying behavioural characteristics. It is encouraging that mathematicians, biologists and clinicians continue to contribute together towards a common quantitative understanding of cancer complexity. This way of thinking may further help to clarify concepts, interpret new and old experimental data, indicate alternative experiments and categorize the acquired knowledge on the basis of the similarities and/or shared behaviours of very different tumours

Abnormal lipid metabolism in metabolic syndrome: an epigenetic perspective

Metabolic syndrome is a complex pathology including central obesity, impaired glucose tolerance/diabetes, an atherogenic dyslipidemia and a prothrombotic state

A Hypothetical-Mathematical Model of Acute Myeloid Leukaemia Pathogenesis

Acute myeloid leukaemia is defined by the expansion of a mutated haematopoietic stem cell clone, with the inhibition of surrounding normal clones. Haematopoiesis can be seen as an evolutionary tree, starting with one cell that undergoes several divisions during the expansion phase, afterwards losing functional cells during the aging-related contraction phase. During divisions, offspring cells acquire ‘variations’, which can be either normal or abnormal. If an abnormal variation is present in more than 25% of the final cells, a monoclonal, leukemic pattern occurs. Such a pattern develops if: (A1) The abnormal variation occurs early, during the first or second divisions; (A2) The variation confers exceptional proliferative capacity; (B) A sizable proportion of the normal clones are destroyed and a previously non-significant abnormal clone gains relative dominance over a depleted environment; (C) The abnormal variation confers relative ‘immortality’, rendering it significant during the contraction phase. Combinations of these pathways further enhance the leukemic risk of the system. A simple mathematical model is used in order to characterize normal and leukemic states and to explain the above cellular processes generating monoclonal leukemic patterns