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<p>Calorimetry-based disease diagnosis is increasingly positioned as a promising noninvasive tool that can complement clinical data. During recent years, the complex calorimetric profiles reflecting the thermal unfolding of blood plasma proteins and the thermal stability of the plasma proteome have been proved to distinguish between the healthy state and a number of pathologies. More details in the complexity of calorimetric profiles and discovering of reliable specific calorimetric markers can be achieved by the use of different mathematical routines that allow building models for differentiation of disease from healthy conditions. In this work, we applied intercriteria analysis (ICrA) and identified an ICrA-based set of specific intercriteria dependences, underpinning key relationships across the calorimetric dataset. The findings strongly suggest that immunoglobulins are the predominant drivers of the evaluated interdependencies.</p>

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Multicriteria decision-making analysis for identifying interrelations between thermodynamic parameters of blood plasma

  • 期刊论文

  • 发表日期：

    2026年1月26日

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  • Stefka G. Taneva,
  • Svetla Todinova,
  • Avgustina Danailova,
  • Krassimir Atanassov,
  • Vassia Atanassova

摘要

Calorimetry-based disease diagnosis is increasingly positioned as a promising noninvasive tool that can complement clinical data. During recent years, the complex calorimetric profiles reflecting the thermal unfolding of blood plasma proteins and the thermal stability of the plasma proteome have been proved to distinguish between the healthy state and a number of pathologies. More details in the complexity of calorimetric profiles and discovering of reliable specific calorimetric markers can be achieved by the use of different mathematical routines that allow building models for differentiation of disease from healthy conditions. In this work, we applied intercriteria analysis (ICrA) and identified an ICrA-based set of specific intercriteria dependences, underpinning key relationships across the calorimetric dataset. The findings strongly suggest that immunoglobulins are the predominant drivers of the evaluated interdependencies.