TY - JOUR A1 - Solovyev, N. A1 - El-Khatib, Ahmed A1 - Costas-Rodrigues, M. A1 - Schwab, K. A1 - Griffin, E. A1 - Raab, A. A1 - Platt, B. A1 - Theuring, F. A1 - Vogl, Jochen A1 - Vanhaecke, F. T1 - Cu, Fe and Zn isotope ratios in murine Alzheimer's disease models suggest specific signatures of amyloidogenesis and tauopathy N2 - Alzheimer’s disease (AD) is characterized by accumulation of tau and amyloid-beta in the brain, and recent evidence suggests a correlation between associated protein aggregates and trace elements, such as copper, iron and zinc. In AD, distorted brain redox homeostasis and complexation by amyloid-beta and hyperphosphorylated tau May alter the isotopic composition of essential mineral elements. Therefore, high-precision isotopic analysis may reveal changes in the homeostasis of these elements. We used inductively coupled plasma-mass spectrometry (ICP-MS)-based techniques to determine the total Cu, Fe and Zn contents in the brain, as well as their isotopic compositions in both mouse brain and serum. Results for male transgenic tau (Line 66, L66) and amyloid/presenilin (5xFAD) mice were compared to those for the corresponding age- and gendermatched wild-type control mice (WT). Our data show that L66 brains showed significantly higher Fe levels than the corresponding WT. Significantly less Cu, but more Zn was found in 5xFAD brains. We observed significantly lighter isotopic compositions of Fe (enrichment in the lighter isotopes) in the brain, and in serum of L66 mice compared to WT. For 5xFAD mice, Zn exhibited a trend towards a lighter isotopic composition in brain and a heavier isotopic composition in serum compared to WT. Neither mouse model yielded differences in the isotopic composition of Cu. Our findings indicate significant pathology-specific alterations of Fe and Zn brain homeostasis in mouse models of AD. The associated changes in isotopic composition May serve as a marker for proteinopathies Underlying AD and other types of dementia. KW - Alzheimer’s disease KW - Tau KW - Amyloid-beta KW - Copper KW - Iron KW - Zinc KW - Multi-collector inductively coupled plasma-mass spectrometry (ICP-MS) KW - Brain KW - Serum KW - Isotopic analysis KW - Total element determination PY - 2021 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-520214 DO - https://doi.org/10.1016/j.jbc.2021.100292 VL - 296 SP - 100292 PB - Elsevier Inc. CY - Amsterdam AN - OPUS4-52021 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER - TY - JOUR A1 - Li, Xunyu A1 - Riedel, Jens A1 - You, Yi T1 - Practical high-resolution spectroscopy with a spatial heterodyne spectrometer: Determination of instrumental function for lineshape recovery N2 - The spatial heterodyne spectrometer (SHS) is a well-recognized platform for its high resolving power in various use cases of spectroscopy. Same as other spectrometer topologies, the SHS, unfortunately, also suffers from classical challenges such as distorted lineshape due to the instrumental function. The goal of this work is to tackle this persisting issue through a simple numerical approach. With the inherent characteristics of an SHS interferogram, we report the direct extraction and determination of the instrumental function in its numerical representation from an SHS interferogram; this instrumental function was further used for spectral data processing that enables significant improvements in spectral resolution through deconvolution algorithms.Here, we systematically discuss the recognition of the embedded instrumental function among various ingredients within an interferogram. To verify the numerical approach, lithium was chosen as the model sample, resembling the use of SHS in an isotopic analysis application. Specifically, the resonance transition of lithium D-lines (2P1/2,3/2 ← 2S1/2) was selected to assess the performance of the spectral processing. With the spectral deconvolution, the spectral features that represent the 6Li and 7Li were nearly baseline-separated, allowing for the accurate measure of the isotopic abundance without external references or algorithm adjustments (e.g., curve fitting). KW - SHS KW - Isotopic analysis KW - High Resolution PY - 2024 UR - https://nbn-resolving.org/urn:nbn:de:kobv:b43-613401 DO - https://doi.org/10.1016/j.sab.2024.107053 SN - 0584-8547 VL - 221 SP - 1 EP - 5 PB - Elsevier AN - OPUS4-61340 LA - eng AD - Bundesanstalt fuer Materialforschung und -pruefung (BAM), Berlin, Germany ER -