Measuring Channel Planform Change From Image Time Series: A Generalizable, Spatially Distributed, Probabilistic Method for Quantifying Uncertainty

Abstract Channels change in response to natural or anthropogenic fluctuations in streamflow and/or sediment supply and measurements of channel change are critical to many river management applications. Whereas repeated field surveys are costly and time‐consuming, remote sensing can be used to detect channel change at multiple temporal and spatial scales. Repeat images have been widely used to measure long‐term channel change, but these measurements are only significant if the magnitude of change exceeds the uncertainty. Existing methods for characterizing uncertainty have two important limitations. First, while the use of a spatially variable image co‐registration error avoids the assumption that errors are spatially uniform, this type of error, as originally formulated, can only be applied to linear channel adjustments, which provide less information on channel change than polygons of erosion and deposition. Second, previous methods use a level‐of‐detection (LoD) threshold to remove non‐significant measurements, which is problematic because real changes that occurred but were smaller than the LoD threshold would be removed. In this study, we present a new method of quantifying uncertainty associated with channel change based on probabilistic, spatially varying estimates of co‐registration error and digitization uncertainty that obviates a LoD threshold. The spatially distributed probabilistic (SDP) method can be applied to both linear channel adjustments and polygons of erosion and deposition, making this the first uncertainty method generalizable to all metrics of channel change. Using a case study from the Yampa River, Colorado, we show that the SDP method reduced the magnitude of uncertainty and enabled us to detect smaller channel changes as significant. Additionally, the distributional information provided by the SDP method allowed us to report the magnitude of channel change with an appropriate level of confidence in cases where a simple LoD approach yielded an indeterminate result

Mapping the bathymetry of supraglacial lakes and streams on the Greenland Ice Sheet using field measurements and high resolution satellite images

Recent melt events on the Greenland ice sheet (GrIS) accentuate the need to constrain estimates of sea level rise through improved characterization of meltwater pathways. This effort will require more precise estimates of the volume of water stored on the surface of the GrIS. We assessed the potential to obtain such information by mapping the bathymetry of supraglacial lakes and streams from WorldView2 (WV2) satellite images. Simultaneous in situ observations of depth and reflectance from two streams and a lake with measured depths up to 10.45 m were used to test a spectrally based depth retrieval algorithm. We performed optimal band ratio analysis (OBRA) of continuous field spectra and spectra convolved to the bands of the WV2, Landsat 7 (ETM+), MODIS, and ASTER sensors. The field spectra yielded a strong relationship with depth (R² = 0.94), and OBRA R² values were nearly as high (0.87–0.92) for convolved spectra, suggesting that these sensors' broader bands would be sufficient for depth retrieval. Our field measurements thus indicated that remote sensing of supraglacial bathymetry is not only feasible but potentially highly accurate. OBRA of spectra from 2 m-pixel WV2 images acquired within 3–72 h of our field observations produced an optimal R² value of 0.92 and unbiased, precise depth estimates, with mean and root mean square errors < 1% and 10–25% of the mean depth. Bathymetric maps produced by applying OBRA relations revealed subtle features of lake and channel morphology. In addition to providing refined storage volume estimates for lakes of various sizes, this approach can help provide estimates of the transient flux of meltwater through stream

Mutant Huntingtin Fragments Form Oligomers in a Polyglutamine Length-Dependent Manner \u3cem\u3ein Vitro\u3c/em\u3e and \u3cem\u3ein Vivo\u3c/em\u3e

Huntington disease (HD) is caused by an expansion of more than 35–40 polyglutamine (polyQ) repeats in the huntingtin (htt) protein, resulting in accumulation of inclusion bodies containing fibrillar deposits of mutant htt fragments. Intriguingly, polyQ length is directly proportional to the propensity for htt to form fibrils and the severity of HD and is inversely correlated with age of onset. Although the structural basis for htt toxicity is unclear, the formation, abundance, and/or persistence of toxic conformers mediating neuronal dysfunction and degeneration in HD must also depend on polyQ length. Here we used atomic force microscopy to demonstrate mutant htt fragments and synthetic polyQ peptides form oligomers in a polyQ length-dependent manner. By time-lapse atomic force microscopy, oligomers form before fibrils, are transient in nature, and are occasionally direct precursors to fibrils. However, the vast majority of fibrils appear to form by monomer addition coinciding with the disappearance of oligomers. Thus, oligomers must undergo a major structural transition preceding fibril formation. In an immortalized striatal cell line and in brain homogenates from a mouse model of HD, a mutant htt fragment formed oligomers in a polyQ length-dependent manner that were similar in size to those formed in vitro, although these structures accumulated over time in vivo. Finally, using immunoelectron microscopy, we detected oligomeric-like structures in human HD brains. These results demonstrate that oligomer formation by a mutant htt fragment is strongly polyQ length-dependent in vitro and in vivo, consistent with a causative role for these structures, or subsets of these structures, in HD pathogenesis

Hsp70 and Hsp40 Functionally Interact with Soluble Mutant Huntingtin Oligomers in a Classic ATP-Dependent Reaction Cycle

Inclusion bodies of aggregated mutant huntingtin (htt) fragments are a neuropathological hallmark of Huntington disease (HD). The molecular chaperones Hsp70 and Hsp40 colocalize to inclusion bodies and are neuroprotective in HD animal models. How these chaperones suppress mutant htt toxicity is unclear but might involve direct effects on mutant htt misfolding and aggregation. Using size exclusion chromatography and atomic force microscopy, we found that mutant htt fragments assemble into soluble oligomeric species with a broad size distribution, some of which reacted with the conformation-specific antibody A11. Hsp70 associated with A11-reactive oligomers in an Hsp40- and ATP-dependent manner and inhibited their formation coincident with suppression of caspase 3 activity in PC12 cells. Thus, Hsp70 and Hsp40 (DNAJB1) dynamically target specific subsets of soluble oligomers in a classic ATP-dependent reaction cycle, supporting a pathogenic role for these structures in HD

Identical oligomeric and fibrillar structures captured from the brains of R6/2 and knock-in mouse models of Huntington's disease

Huntington's disease (HD) is a late-onset neurodegenerative disorder that is characterized neuropathologically by the presence of neuropil aggregates and nuclear inclusions. However, the profile of aggregate structures that are present in the brains of HD patients or of HD mouse models and the relative contribution of specific aggregate structures to disease pathogenesis is unknown. We have used the Seprion ligand to develop a highly sensitive enzyme-linked immunosorbent assay (ELISA)-based method for quantifying aggregated polyglutamine in tissues from HD mouse models. We used a combination of electron microscopy, atomic force microscopy (AFM) and sodium dodecyl sulphate–polyacrylamide gel electrophoresis (SDS–PAGE) to investigate the aggregate structures isolated by the ligand. We found that the oligomeric, proto-fibrillar and fibrillar aggregates extracted from the brains of R6/2 and HdhQ150 knock-in mice were remarkably similar. Using AFM, we determined that the nanometre globular oligomers isolated from the brains of both mouse models have dimensions identical to those generated from recombinant huntingtin exon 1 proteins. Finally, antibodies that detect exon 1 Htt epitopes differentially recognize the ligand-captured material on SDS–PAGE gels. The Seprion-ligand ELISA provides an assay with good statistical power for use in preclinical pharmacodynamic therapeutic trials or to assess the effects of the genetic manipulation of potential therapeutic targets on aggregate load. This, together with the ability to identify a spectrum of aggregate species in HD mouse tissues, will contribute to our understanding of how these structures relate to the pathogenesis of HD and whether their formation can be manipulated for therapeutic benefit

Interaction imaging with amplitude-dependence force spectroscopy

Knowledge of surface forces is the key to understanding a large number of processes in fields ranging from physics to material science and biology. The most common method to study surfaces is dynamic atomic force microscopy (AFM). Dynamic AFM has been enormously successful in imaging surface topography, even to atomic resolution, but the force between the AFM tip and the surface remains unknown during imaging. Here, we present a new approach that combines high accuracy force measurements and high resolution scanning. The method, called amplitude-dependence force spectroscopy (ADFS) is based on the amplitude-dependence of the cantilever's response near resonance and allows for separate determination of both conservative and dissipative tip-surface interactions. We use ADFS to quantitatively study and map the nano-mechanical interaction between the AFM tip and heterogeneous polymer surfaces. ADFS is compatible with commercial atomic force microscopes and we anticipate its wide-spread use in taking AFM toward quantitative microscopy

Point Mutations in Aβ Result in the Formation of Distinct Polymorphic Aggregates in the Presence of Lipid Bilayers

A hallmark of Alzheimer's disease (AD) is the rearrangement of the β-amyloid (Aβ) peptide to a non-native conformation that promotes the formation of toxic, nanoscale aggregates. Recent studies have pointed to the role of sample preparation in creating polymorphic fibrillar species. One of many potential pathways for Aβ toxicity may be modulation of lipid membrane function on cellular surfaces. There are several mutations clustered around the central hydrophobic core of Aβ near the α-secretase cleavage site (E22G Arctic mutation, E22K Italian mutation, D23N Iowa mutation, and A21G Flemish mutation). These point mutations are associated with hereditary diseases ranging from almost pure cerebral amyloid angiopathy (CAA) to typical Alzheimer's disease pathology with plaques and tangles. We investigated how these point mutations alter Aβ aggregation in the presence of supported lipid membranes comprised of total brain lipid extract. Brain lipid extract bilayers were used as a physiologically relevant model of a neuronal cell surface. Intact lipid bilayers were exposed to predominantly monomeric preparations of Wild Type or different mutant forms of Aβ, and atomic force microscopy was used to monitor aggregate formation and morphology as well as bilayer integrity over a 12 hour period. The goal of this study was to determine how point mutations in Aβ, which alter peptide charge and hydrophobic character, influence interactions between Aβ and the lipid surface. While fibril morphology did not appear to be significantly altered when mutants were prepped similarly and incubated under free solution conditions, aggregation in the lipid membranes resulted in a variety of polymorphic aggregates in a mutation dependent manner. The mutant peptides also had a variable ability to disrupt bilayer integrity