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- W4313462988 abstract "Discovery of diagnostic biomarkers for age-related neurodegenerative pathologies (NDDs) is essential for accurate diagnosis, following disease progression and drug development. Blood plasma and blood cells are important peripheral sources for NDDs’ biomarkers that, although present in lower concentrations than in cerebrospinal fluid, would allow noninvasive diagnostics. To identify new biomarkers for Parkinson’s disease (PD) and amyotrophic lateral sclerosis (ALS), in this work we have evaluated the modifications in the thermodynamic behavior of blood plasma proteome exploring differential scanning calorimetry. The plasma thermodynamics reflected the complexity and heterogeneity of the two pathologies. The unfolding temperature of the most abundant plasma protein albumin and the weighted average center of the calorimetric profile appeared as the two thermodynamic signatures that reflected modifications of the plasma proteome, i.e., strong thermal stabilization of albumin and plasma proteins’ interaction network, related to both pathologies. Based on those two signatures, both PD and ALS patients were stratified in two sets, except several cases with thermodynamic parameters that strongly differed from those of the calorimetric sets. Along with modifications of the plasma thermodynamic behavior, we found altered globulin levels in all PD and ALS patients’ plasma (higher level of α- and β-globulin fractions and lower level of γ-globulin fraction than the respective reference values) employing capillary electrophoresis. The presented results reveal the potential of calorimetry to indirectly identify NDDs’ biomarkers in blood plasma." @default.
- W4313462988 created "2023-01-06" @default.
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- W4313462988 date "2023-01-02" @default.
- W4313462988 modified "2023-10-14" @default.
- W4313462988 title "Thermodynamic Signatures of Blood Plasma Proteome in Neurodegenerative Pathologies" @default.
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- W4313462988 doi "https://doi.org/10.3390/ijms24010789" @default.
- W4313462988 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/36614231" @default.
- W4313462988 hasPublicationYear "2023" @default.
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