Lithospheric flexural modelling of the seaward and trenchward of the subducting oceanic plates

Based on a two-segment plate flexural modelling, we investigated the effective elastic thickness of global subducting oceanic lithosphere. Our results show that for the plate age of 0 to 50 Ma, the seaward effective elastic thickness TeM values are located between 600 and 900°C isotherms, and do not track any isotherm, while the majority of the trenchward effective elastic thickness Tem values are located between 300 and 600°C isotherms. For the plate age older than 50 Ma, TeM values basically matches the 600°C isotherm with some fluctuations for the age older than 110 Ma, while Tem values mainly fall between 200 and 400°C isotherms. The reduction in effective elastic thickness (TeM-Tem) varies from 2.6 to 30.1 km, or 11–68% of seaward TeM. Thus, the absolute value of the decrease in the effective elastic thicknesses (TeM-Tem) increases with the plate age, while the percentage reduction in the effective elastic thickness (1-Tem/TeM) has no obvious relationship with the age, but more related to the curvature of bending plate. Almost all bending-related earthquakes occurred above the TeM line, but many normal-faulting earthquakes are deeper than the TeM-Tem line, implying that the plate may still retain some thickness of an elastic property core in the areas (depth) where earthquakes occur.</p

Multi-scale MRI of a 9L brain tumor model.

<p>(a) In vivo T₂-weighted MRI at the ‘systemic’ scale (∼150 µm); ex vivo μMRI at two ‘intermediate’ scales: (b) ∼60 µm, and (c) ∼30 µm. (d) Ultra-high resolution vascular μMRI image in which vessels have been segmented into tumor vessels (gold) and normal vessels (red). One can clearly visualize the abnormal tumor vessel architecture and changes in vessel morphology at the tumor-host tissue interface (arrows).</p

Segmentation of the Vasculature from μMRI Data.

<p>Image processing steps involved in the extraction of the 3D vasculature from the raw GE μMRI data for a 9L tumor (arrow in all panels) bearing mouse brain: (a) <i>Ex vivo</i> T₂*-weighted image corresponding to the 1^st TE; (b) Blood vessels (red) segmented out using the “tubeness” filter overlaid on the raw data in (a). (c) Binarized vasculature obtained by thresholding the tubeness data in (b) followed by removal of isolated voxels. (d) Volume rendering of the μMRI-derived vasculature, color-coded by average vessel radius.</p

Simultaneous imaging of brain tumor angiogenesis and invasion with μMRI.

<p>(a) FA map of a patient-derived, invasive primary glioma model. (b) Zoomed view of the hatched region in (a) showing two ROIs in the corpus callosum for which the FA was analyzed. (c) Histograms of the FA from the ROIs in (b), wherein one can see that the FAs from ROI-1 are shifted toward lower values than those from ROI-2. (d) Histology (H&E) from the same region as in (b) in which one can see the white matter tract (WM) being infiltrated by a tuft of tumor cells (I). The tumor margin (T) is also visible in (d). (e) Visualization of the DTI tensors as 3D ellipsoid glyphs for one μMRI slice, wherein each ellipsoid is scaled according the values of the three principal eigen-vectors and color coded according to the FA. The invasive primary tumor (hatched outline) is identifiable by its lower FA in contrast to the contralateral brain. (f) Visualization of the 3D vasculature for the whole brain. Tumor vasculature (hatched outline) is dense and chaotic relative to that of the contralateral brain. (g) The image in (e) overlaid with that in (f) allows us to simultaneously assess the interaction between brain tumor angiogenesis and the effects of tumor invasion on the integrity of white matter tracts. The tumor ROI is highlighted by a hatched outline.</p

3D imaging of the murine neurovasculature with μMRI and validation with μCT and optical microscopy.

<p>(a) Photograph of a freshly excised mouse brain showing blue Microfil® perfused vessels (arrows). (b) X-ray radiograph of the same brain in which radio-opaque microfilled vessels are clearly visible. Arrows indicate major vessels that are also visible in (a). (c) Slice through the 3D R₂* map of the same brain. The Microfil-brain tissue interface is characterized by elevated R2* (hot colors) values. Note that background voxels are assigned R2* of zero. (d) ∼1.2 mm slab from another intact brain, in which μMRI-derived vasculature (gold) is overlaid on that acquired using μCT (purple). One can clearly visualize the vascular architecture and the agreement between μMRI and μCT. (e) Bright-field images (2×) of ROIs corresponding to colored squares in (d). Images are from a 1 mm thick, unstained brain section. Dark microfilled vessels provide corroboration of the μMRI data in (d). Arrows indicate major vessels that are also visible in (d). μCT data were resampled to match the μMRI spatial resolution, and the fractional vascular volume (FV) computed within 8×8×1 subvolumes for each dataset. The correlation between the μMRI and μCT-derived FVs for the 1 mm thick slice is plotted in (f). A similar analysis was conducted for the <i>whole</i> brain, wherein the FV was computed within 8×8×8 subvolumes for each dataset. The correlation between the μMRI and μCT-derived FVs for the <i>whole</i> brain is plotted in (g) and demonstrate good agreement between μMRI and μCT-derived vasculature. The red lines in (f) and (g) are the best linear fit to the data, and blue lines indicate the 95% confidence limits about the mean.</p

Bridging macroscale and microscale MRI.

<p>(a) In vivo macrovascular CBV (ΔR₂*) map. (b) Co-registered <i>ex vivo</i> fractional blood volume (FV) map obtained from μMRI. The tumor ROI is highlighted by hatched lines in each panel and FV ranges from 0 to 1. (c) Histograms showing the relative distribution of the ΔR₂* between tumor and contralateral ROIs. (d) Histograms showing the relative distribution of the FV between tumor and contralateral ROIs. Tumor blood volume is elevated relative to the contralateral brain across these “multi-scale” data. (e) 2D histograms of the macrovascular CBV measured <i>in vivo</i> versus the fractional blood volume assessed <i>ex vivo</i>. These data further demonstrate the utility of multi-scale imaging of brain tumor vascularization.</p

Ultra-high resolution 3D μMRI and “zonal” analyses of the neurovasculature.

<p>(a) 3D rendering of the neurovasculature in a non-invasive, 9L tumor bearing mouse brain acquired using ultra-high resolution (30 µm×30 µm×30 µm) μMRI. The vasculature has been color coded into three different “zones”: normal vessels (blue), tumor vessels (red) and vessels at the tumor-brain interface or transition zone (green). The transition-zone or tumor-brain tissue interface is crucial to understanding both, brain tumor angiogenesis and invasion. The radius and length of every individual vessel segment was measured in each zone. (b) Box plot of the average vessel length in each zone, wherein the width of each box includes 75% of the measured lengths and the median length is indicated by a horizontal line in each box. In addition, the radius of every vessel segment is plotted for each zone, with the color and size of each symbol proportional to the vessel radius. The normal zone exhibited significantly longer vessel segments compare to the transition (p = 0.002) and tumor zones (p<0.001), respectively. At this tumor stage, vessel radii were similar between the tumor and normal zones. These data demonstrate our ability to characterize the neurovasculature in physiologically relevant “zones”, and could provide new insight into the relationship between brain tumor angiogenesis and invasion. (c) T₂-weighted μMRI slice through a 9L brain tumor (gold rendering) bearing brain. (d) 3D overlay of the neurovasculature acquired using ultra-high resolution μMRI. (e) 3D DTI image showing reorganization of the fibers of the anterior commissure (<i>ac</i>) and internal capsule (<i>ic</i>) around the tumor. (f) Overlay of (d) and (e) illustrating simultaneous changes in vascular and white matter structures.</p

EPO reverses GD1a/GT1b–2b mAb-mediated inhibition of neurite outgrowth in primary neuronal cultures.

<p>(A) Primary DRG neurons extend long neurites under control conditions. (B) DRG neurons treated with GD1a/GT1b–2b mAb have shorter neurites. (C) EPO reverses Ab-mediated inhibition of neurite outgrowth. Scale bar, 20 µm. (D<b>)</b> EPO induces a dose-responsive reversal of Ab-mediated inhibition of neurite outgrowth in embryonic rat DRG neurons (ER DRG). Quantified data showing that EPO (100 pM) reverses Ab-mediated inhibition of neurite outgrowth in adult mouse DRG (AM DRG), * <i>p</i><0.05 (E), and spinal motor neurons (MN), * <i>p</i><0.01 (F).</p

EPO does not modulate the activation of RhoA, Rac1 and Cdc42 in primary DRG cultures.

<p>(A) Anti-ganglioside Abs (GD1a/GT1b–2b; Ab) induced significant RhoA activation; co-incubation with EPO did not alter the anti-ganglioside Ab-mediated activation of RhoA. EPO did not induce RhoA activation compared to control. EPO did not modulate the activation of Rac1 (B) or Cdc42 (C) in the presence of control or anti-ganglioside Abs. * <i>p</i><0.001.</p

EPO enhances target/muscle reinnervation as assessed by nerve conductions and MRI volumetric measurements.

<p>Representative CMAP recordings from GD1a/GT1b–2b mAb+vehicle (Ab+vehicle)-treated animals (A) and GD1a/GT1b–2b mAb+EPO (Ab+EPO)-treated group (B). (C) Quantified data showing significantly increase CMAP amplitudes in Ab+EPO-treated group compared to Ab+vehicle-treated animals on days 26 and 30 after the nerve crush. MRI 3D reconstructions of calf muscles in Ab+vehicle-treated animals (D) and Ab+EPO-treated group (E). (F) Quantified data show significantly lower calf muscle volume in Ab+vehicle-treated animals compared to Ab+EPO-treated group. * <i>p</i><0.05.</p