In this article, we consider the role of heterogeneous nucleation in β‐amyloid aggregation. Heterogeneous nucleation is more common and occurs at lower levels of supersaturation than homogeneous nucleation. The nucleation period is also the stage at which most of the polymorphism of amyloids arises, this being one of the defining features of amyloids. We focus on several well‐known heterogeneous nucleators of β‐amyloid, including lipid surfaces, especially those enriched in gangliosides and cholesterol, and divalent metal ions. These two broad classes of nucleators affect β‐amyloid particularly in light of the amphiphilicity of these peptides: the N‐terminal region, which is largely polar and charged, contains the metal binding site, whereas the C‐terminal region is aliphatic and is important in lipid binding. Notably, these two classes of nucleators can interact cooperatively, aggregation begetting greater aggregation.

To evaluate and quantify inter-directional and inter-acquisition variation in diffusion-weighted imaging (DWI) and emphasize signals that report restricted diffusion to enhance cancer conspicuity, while reducing the effects of local microscopic motion and magnetic field fluctuations. Methods: Ten patients with biopsy-proven prostate cancer were studied under an Institutional Review Board-approved protocol. Individual acquisitions of DWI signal intensities were reconstructed to calculate inter-acquisition distributions and their statistics, which were compared for healthy versus cancer tissue. A method was proposed to detect and filter the acquisitions affected by motion-induced signal loss. First, signals that reflect restricted diffusion were separated from the acquisitions that suffer from signal loss, likely due to microscopic motion, by imposing a cutoff value. Furthermore, corrected apparent diffusion coefficient maps were calculated by employing a weighted sum of the multiple acquisitions, instead of conventional averaging. These weights were calculated by applying a soft-max function to the set of acquisitions per-voxel, making the analysis immune to acquisitions with significant signal loss, even if the number of such acquisitions is high. Results: Inter-acquisition variation is much larger than the Rician noise variance, local spatial variations, and the estimates of diffusion anisotropy based on the current data, as well as the published values of anisotropy. The proposed method increases the contrast for cancers and yields a sensitivity of 98.8% with a false positive rate of 3.9%. Conclusion: Motion-induced signal loss makes conventional signal-averaging suboptimal and can obscure signals from areas with restricted diffusion. Filtering or weighting individual acquisitions prior to image analysis can overcome this problem.

Using atomic force microscopy (AFM) and nuclear magnetic resonance (NMR), we describe small Aβ40 oligomers, termed nanodroplet oligomers (NanDOs), which form rapidly and at Aβ40 concentrations too low for fibril formation. NanDOs were observed in putatively monomeric solutions of Aβ40 (e.g., by size exclusion chromatography). Video-rate scanning AFM shows rapid fusion and dissolution of small oligomer-sized particles, of which the median size increases with peptide concentration. In NMR ( 13 C HSQC), a small number of chemical shifts changed with a change in peptide concentration. Paramagnetic relaxation enhancement NMR experiments also support the formation of NanDOs and suggest prominent interactions in hydrophobic domains of Aβ40. Addition of Zn 2+ to Aβ40 solutions caused flocculation of NanDO-containing solutions, and selective loss of signal intensity in NMR spectra from residues in the N-terminal domain of Aβ40. NanDOs may represent the earliest aggregated form of Aβ40 in the aggregation pathway and are akin to premicelles in solutions of amphiphilies.

No abstract

The mechanism by which a disordered peptide nucleates and forms amyloid is incompletely understood. A central domain of β-amyloid (Aβ21-30) has been proposed to have intrinsic structural propensities that guide the limited formation of structure in the process of fibrillization. In order to test this hypothesis, we examine several internal fragments of Aβ, and variants of these either cyclized or with an N-terminal Cys. While Aβ21-30 and variants were always monomeric and unstructured (circular dichroism (CD) and nuclear magnetic resonance spectroscopy (NMRS)), we found that the addition of flanking hydrophobic residues in Aβ16-34 led to formation of typical amyloid fibrils. NMR showed no long-range nuclear overhauser effect (nOes) in Aβ21-30, Aβ16-34, or their variants, however. Serial 1 H-15 N-heteronuclear single quantum coherence spectroscopy, 1 H-1 H nuclear overhauser effect spectroscopy, and 1 H-1 H total correlational spectroscopy spectra were used to follow aggregation of Aβ16-34 and Cys-Aβ16-34 at a site-specific level. The addition of an N-terminal Cys residue (in Cys-Aβ16-34) increased the rate of fibrillization which was attributable to disulfide bond formation. We propose a scheme comparing the aggregation pathways for Aβ16-34 and Cys-Aβ16-34, according to which Cys-Aβ16-34 dimerizes, which accelerates fibril formation. In this context, cysteine residues form a focal point that guides fibrillization, a role which, in native peptides, can be assumed by heterogeneous nucleators of aggregation.

Diffusion-weighted MR images are typically obtained as multiple acquisitions with multiple diffusion-sensitizing gradient directions. Due to molecular motion, some acquisitions suffer from signal loss at random locations. This affects cancer conspicuity and degrades the diagnostic efficacy of DWI. We propose an agglomerative clustering-based unsupervised method to address this. The model automatically rejects acquisitions of voxels that are likely to be corrupted by bulk motion and lack coherence with the rest of the acquisitions. We observed that this method both reduces the DWI signal variability and enhances the cancer detection accuracy.

No abstract

Understanding the conformational ensemble of an intrinsically disordered protein (IDP) is of great interest due to its relevance to important intracellular functions and diseases. We have recently shown that the polymer scaling exponent characterizing the dependence of protein size on chain length is a crucial factor as it strongly correlates with liquid-liquid phase behavior of an IDP. Previously, sequence properties from charged amino acids, including both fraction of positive/negative charges and charge patterning have been acknowledged to affect the size of an IDP. However, IDP sequences are composed of a significant amount of uncharged amino acids and how these uncharged amino acids impact the size of an IDP is not well understood. Here, we first investigate if average hydrophobicity can be used to obtain quantitative insights into the polymer scaling properties of IDP sequences. Based on the coarse-grained simulation data for a large number of uncharged IDPs, we find that incorporating the information about the patterning of residues is necessary to model the size of an IDP faithfully. The newly developed sequence hydrophobicity decoration (SHD) parameter, together with the previously known sequence charge decoration (SCD) parameter, can be used to predict the size of an IDP. Our results are, therefore, a significant step forward to elucidate the fundamental principles governing the sequence-structure relationships of disordered proteins.