ABSTRACT
α-Synuclein (α-Syn) aggregation, proceeding from oligomers to fibrils, is one central hallmark of neurodegeneration in synucleinopathies. α-Syn oligomers are toxic by triggering neurodegenerative processes in in vitro and in vivo models. However, the precise contribution of α-Syn oligomers to neurite pathology in human neurons and the underlying mechanisms remain unclear. Here, we demonstrate the formation of oligomeric α-Syn intermediates and reduced axonal mitochondrial transport in human neurons derived from induced pluripotent stem cells (iPSC) from a Parkinson's disease patient carrying an α-Syn gene duplication. We further show that increased levels of α-Syn oligomers disrupt axonal integrity in human neurons. We apply an α-Syn oligomerization model by expressing α-Syn oligomer-forming mutants (E46K and E57K) and wild-type α-Syn in human iPSC-derived neurons. Pronounced α-Syn oligomerization led to impaired anterograde axonal transport of mitochondria, which can be restored by the inhibition of α-Syn oligomer formation. Furthermore, α-Syn oligomers were associated with a subcellular relocation of transport-regulating proteins Miro1, KLC1, and Tau as well as reduced ATP levels, underlying axonal transport deficits. Consequently, reduced axonal density and structural synaptic degeneration were observed in human neurons in the presence of high levels of α-Syn oligomers. Together, increased dosage of α-Syn resulting in α-Syn oligomerization causes axonal transport disruption and energy deficits, leading to synapse loss in human neurons. This study identifies α-Syn oligomers as the critical species triggering early axonal dysfunction in synucleinopathies.
Subject(s)
Axonal Transport , Axons/metabolism , Induced Pluripotent Stem Cells/metabolism , Models, Biological , Neurodegenerative Diseases/metabolism , Protein Multimerization , Axons/pathology , Cell Line , Energy Metabolism/genetics , Humans , Induced Pluripotent Stem Cells/pathology , Kinesins , Microtubule-Associated Proteins/genetics , Microtubule-Associated Proteins/metabolism , Mitochondria/genetics , Mitochondria/metabolism , Mitochondria/pathology , Mitochondrial Proteins/genetics , Mitochondrial Proteins/metabolism , Mutation, Missense , Neurodegenerative Diseases/genetics , Neurodegenerative Diseases/pathology , alpha-Synuclein , rho GTP-Binding Proteins/genetics , rho GTP-Binding Proteins/metabolism , tau Proteins/genetics , tau Proteins/metabolismABSTRACT
In this work we present a new method to reduce artifacts, produced by high-density objects, especially metal implants, in X-ray cone beam computed tomography (CBCT). These artifacts influence clinical diagnostics and treatments using CT data, if metal objects are located in the field of view (FOV). Our novel method reduces metal artifacts by virtually replacing the metal objects with tissue objects of the same shape. First, the considered objects must be segmented in the original 2D projection data as well as in a reconstructed 3D volume. The attenuation coefficients of the segmented voxels are replaced with adequate attenuation coefficients of tissue (or water), then the required parts of the volume are projected onto the segmented 2D pixels, to replace the original information. This corrected 2D data can then be reconstructed with reduced artifacts, i. e. all metal objects virtually vanished. After the reconstruction, the segmented 3D metal objects were re-inserted into the corrected 3D volume. Our method was developed for mobile C-arm CBCTs; as it is necessary that they are of low weight, the C-arm results in unpredictable distortion. This misalignment between the original 2D data and the forward projection of the reconstructed 3D volume must be adjusted before the correction of the segmented 2D pixels. We applied this technique to clinical data and will now present the results.
Subject(s)
Artifacts , Cone-Beam Computed Tomography/methods , Metals , Algorithms , Humans , Imaging, Three-DimensionalABSTRACT
We have previously reported a comparison between edge-corrected near-infrared optical mammograms and those that have undergone a further image-processing step based on a spatial second derivative. In this work, we go a step further by combining the second-derivative images from four wavelengths (690, 750, 788, and 856 nm) to obtain oxygenation-index images. While the spatial second derivative improves contrast and allows for visibility of fine structures in the images, thereby improving the sensitivity to tumor detection, additional information is needed to avoid false-positive results. The oxygenation-index images are introduced to address this issue. Oxygenation information may help discriminate benign from malignant breast lesions, thereby effectively complementing single-wavelength optical mammograms that display optically dense regions within the breast with high sensitivity.
Subject(s)
Breast Neoplasms/metabolism , Breast Neoplasms/pathology , Breast/blood supply , Breast/metabolism , Hemoglobins/metabolism , Image Interpretation, Computer-Assisted/methods , Oxygen/metabolism , Spectrophotometry, Infrared/methods , Aged , Aged, 80 and over , Algorithms , Biomarkers, Tumor/metabolism , Breast/pathology , Female , Hemoglobins/analysis , Humans , Middle Aged , Oxygen/analysis , Reproducibility of Results , Sensitivity and Specificity , Statistics as Topic , Subtraction Technique , Tomography, Optical/methodsABSTRACT
We present an image-processing method that enhances the detection of regions of higher absorbance in optical mammograms. At the heart of this method lies a second-derivative operator that is commonly employed in edge-detection algorithms. The resulting images possess a high contrast, an automatic display scale, and a greater sensitivity to smaller departures from the local background absorbance. Moreover, the images are free of artifacts near the breast edge. This second-derivative method enhances the display of structural information in optical mammograms and may be used to robustly select areas of interest to be further analyzed spectrally to determine the oxygenation level of breast lesions.
