Three-Dimensional Atlas of Iron, Copper, and Zinc in the Mouse Cerebrum and Brainstem

Hare, Dominic J.; Lee, Jason K.; Beavis, Alison; Gramberg, Amanda Van; George, Jessica; Adlard, Paul A.; Finkelstein, David I.; Doble, Philip

doi:10.1021/ac300374x

Cited by 108 publications

(103 citation statements)

References 41 publications

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“…Methods such as inductively coupled mass spectrometry (ICPMS) [56], laser ablation ICPMS (LA-ICPMS) [57], and T2*-weighted gradient-echo magnetic resonance imaging [58,59] are typically used to monitor total levels of iron and are optimal for measuring brain iron location. However, these require a high level of technical expertise and the instrumentation is costly.…”

Section: Methods Used To Investigate Iron Homeostasismentioning

confidence: 99%

Evaluating Iron Flux in the Brain

Wong

Lam

Tsatsanis

et al. 2017

Metals in the Brain

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Regulated efflux of iron from cells is a fundamental event in controlling the intracellular pool of labile iron. Imbalance to this pool can be detrimental to the cell either through impairment to metabolic pathways when deficient or production of hydroxyl radicals when in excess. While ferroportin is currently the only known iron export pore protein in all cell types of the brain, its functional location is established through protein complexes that vary between cell types. Here, we describe selected experimental techniques that can evaluate iron flux as well as the downstream changes to the labile intracellular pool of iron within the whole brain or select cell types. Our aim is to provide the reader with previously applied procedures using resources available in most biochemical laboratories for interrogating cellular location and movement of iron in cells and tissue that has derived from brain.

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Section: Methods Used To Investigate Iron Homeostasismentioning

confidence: 99%

Evaluating Iron Flux in the Brain

Wong

Lam

Tsatsanis

et al. 2017

Metals in the Brain

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“…Deep GM structures are particularly rich in iron (79,81,92). Furthermore, iron accumulates with age (80,93) and is abnormal in diseases such as Alzheimer's disease (94), Hallevorden-Spatz syndrome (95), Parkinson's disease (96)(97)(98), and MS (99-104).…”

Section: Brain Ironmentioning

confidence: 99%

Quantitative Magnetic Resonance Imaging of the Brain : Applications for Tissue Segmentation and Multiple Sclerosis

West¹

2014

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Magnetic resonance imaging (MRI) is a sensitive technique for assessing white matter (WM) lesions in multiple sclerosis (MS), but there is a low correlation between MRI findings and clinical disability. Because of this, other pathological changes are of interest, including changes in normal appearing white matter (NAWM) and diffusely abnormal white matter (DAWM). Even so, the mechanisms leading to permanent disability in MS remain unclear. In contrast to conventional MRI, quantitative MRI (qMRI) is aimed at the direct measurement of the physical tissue properties, such as the relaxation times, T1 and T2, as well as the proton density (PD). QMRI is promising for characterising and quantifying changes in MS and for brain tissue segmentation. The present work describes a novel method of qMRI for the human brain (QMAP), and a segmentation method based on this. The developed methods were validated in control subjects and MR phantoms. Furthermore, an application in diseased human brain was demonstrated in MS patients. In all, 50 healthy controls and 35 MS patients were scanned with qMRI in a total of 225 acquisitions. One major finding of this work was that qMRI was able to detect and quantify changes in the MS disease that were not visible using conventional MRI. In particular, it was found that DAWM appears to constitute an intermediate between focal white matter (WM) lesions and NAWM. These changes may be caused by pathological processes that are not entirely attributable to Wallerian degeneration. This study showed that the QMAP method had high accuracy and relatively high precision, within a clinically acceptable time. This work also demonstrated that qMRI could be used for brain tissue segmentation and volume estimation of the whole brain, using pre-defined tissue characteristics. The results showed that brain tissue segmentation had high repeatability, which was somewhat lower when different geometries were acquired or different field strengths used. In particular, small differences were found between 1.5 T and 3.0 T in deep brain structures, the cerebellum and the brain stem. This work leads the way for early clinical applications of qMRI, and the challenge for the years to come is to understand the connection between qMRI properties of the brain and underlying biology.Bildtagning med magnetresonanstomografi (MRT) är en teknik som kan användas för att upptäcka lesioner i vit substans hos patienter med multipel skleros (MS), men sambandet mellan lesioner och klinisk funktionsnedsättning är svagt. På grund av detta har intresset för andra patologiska processer i hjärnan ökat. Exempel är förändringar i vit substans som ser normal ut vid MRT (NAWM) och även så kallad diffus vit vävnad (DAWM). Det är emellertid fortfarande oklart vilka mekanismer i MS som leder till klinisk funktionsnedsättning. Med kvantitativ MRT (qMRT) kan fysiologiska egenskaper i vävnaden, som till exempel relaxationstiderna (T1 och T2) samt protontäthet (PD), mätas. QMRT kan användas för att mäta förändringar i hjärnan hos MS patienter och des...

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“…Cerebral bioimaging of Mn, Fe, Zn and Cu in a mouse model of Parkinson's disease using another common biogenomic metal imaging technique, Laser Ablation Inductively Coupled Plasma Mass Spectrometry (LA-ICP-MS), was carried out by Matusch et al [3] This study proved the advantages of micro-local analysis of elemental distribution in substructures for studying neurodegenerative diseases. A study by Hare et al [4] generated the first atlas of Fe, Zn and Cu in the cerebrum and brainstem of the C57BL/6 mouse, one of the most common mouse strains used in neuroscience research, using LA-ICP-MS. This study demonstrated that regional metal distributions can be associated with specific brain structures, but the consequential inferences obtained by bulk metal concentration measurements or digestion methods cannot be applied.…”

Section: Introductionmentioning

confidence: 99%