@article{SchibornSchulze2022,
  author    = {Schiborn, Catarina and Schulze, Matthias Bernd},
  title     = {Precision prognostics for the development of complications in diabetes},
  series = {Diabetologia : journal of the European Association for the Study of Diabetes (EASD)},
  journal   = {Diabetologia : journal of the European Association for the Study of Diabetes (EASD)},
  publisher = {Springer},
  address   = {New York},
  issn      = {0012-186X},
  doi       = {10.1007/s00125-022-05731-4},
  pages     = {16},
  year      = {2022},
  abstract  = {Individuals with diabetes face higher risks for macro- and microvascular complications than their non-diabetic counterparts. The concept of precision medicine in diabetes aims to optimise treatment decisions for individual patients to reduce the risk of major diabetic complications, including cardiovascular outcomes, retinopathy, nephropathy, neuropathy and overall mortality. In this context, prognostic models can be used to estimate an individual's risk for relevant complications based on individual risk profiles. This review aims to place the concept of prediction modelling into the context of precision prognostics. As opposed to identification of diabetes subsets, the development of prediction models, including the selection of predictors based on their longitudinal association with the outcome of interest and their discriminatory ability, allows estimation of an individual's absolute risk of complications. As a consequence, such models provide information about potential patient subgroups and their treatment needs. This review provides insight into the methodological issues specifically related to the development and validation of prediction models for diabetes complications. We summarise existing prediction models for macro- and microvascular complications, commonly included predictors, and examples of available validation studies. The review also discusses the potential of non-classical risk markers and omics-based predictors. Finally, it gives insight into the requirements and challenges related to the clinical applications and implementation of developed predictions models to optimise medical decision making.},
  language  = {en}
}
@article{YarmanWollenbergerScheller2013,
  author    = {Yarman, Aysu and Wollenberger, Ursula and Scheller, Frieder W.},
  title     = {Sensors based on cytochrome P450 and CYP mimicking systems},
  series = {ELECTROCHIMICA ACTA},
  volume    = {110},
  journal   = {ELECTROCHIMICA ACTA},
  publisher = {PERGAMON-ELSEVIER SCIENCE LTD},
  address   = {OXFORD},
  issn      = {0013-4686},
  doi       = {10.1016/j.electacta.2013.03.154},
  pages     = {63 -- 72},
  year      = {2013},
  abstract  = {Cytochrome P450 enzymes (CYPs) act on more than 90 percent of all drugs currently on the market. The catalytic cycle requires electron supply to the heme iron in the presence of oxygen. Electrochemistry allows to characterise the reaction mechanism of these redox enzymes by observing the electron transfer in real time. According to the number of publications on protein electrochemistry CYP has the third position after glucose oxidase and cytochrome c. CYP based enzyme electrodes for the quantification of drugs, metabolites or pesticides have been developed using different iso-enzymes. A crucial step in the sensor development is the efficiency of coupling the biocatalytic systems with the electrode is. In the 1970s the direct electron transfer of heme and heme peptides called microperoxidases (MPs) was used as model of oxidoreductases. They exhibit a broad substrate spectrum including hydroxylation of selected aromatic substrates, demethylation and epoxidation by means of hydrogen peroxide. It overlaps with that of P450 making heme and MPs to alternate recognition elements in biosensors for the detection of typical CYP substrates. In these enzyme electrodes the signal is generated by the conversion of all substrates thus representing in complex media an overall parameter. By combining the biocatalytic substrate conversion with selective binding to a molecularly imprinted polymer layer the specificity has been improved. Here we discuss different approaches of biosensors based on CYP, microperoxidases and catalytically active MIPs and discuss their potential as recognition elements in biosensors. The performance of these sensors and their further development are discussed. (C) 2013 Elsevier Ltd. All rights reserved.},
  language  = {en}
}