BackgroundExosomes, small extracellular vesicles of endosomal origin, have been suggested to be involved in both the metabolism and aggregation of Alzheimer’s disease (AD)-associated amyloid β-protein (Aβ). Despite their ubiquitous presence and the inclusion of components which can potentially interact with Aβ, the role of exosomes in regulating synaptic dysfunction induced by Aβ has not been explored.ResultsWe here provide in vivo evidence that exosomes derived from N2a cells or human cerebrospinal fluid can abrogate the synaptic-plasticity-disrupting activity of both synthetic and AD brain-derived Aβ. Mechanistically, this effect involves sequestration of synaptotoxic Aβ assemblies by exosomal surface proteins such as PrPC rather than Aβ proteolysis.ConclusionsThese data suggest that exosomes can counteract the inhibitory action of Aβ, which contributes to perpetual capability for synaptic plasticity.

This article investigates whether (a) lexical elaboration (LE), typographical enhancement (TE), or a combination, and (b) explicit or implicit LE affect 297 Korean learners' acquisition of English vocabulary. The learners were asked to read one of six versions of an experimental text that contained 26 target words. The study adopted a 2 × 3 MANOVA design with TE and LE as two independent variables and form‐ and meaning‐recognition vocabulary posttests as two dependent variables. The TE had two levels, enhanced and unenhanced, and the LE had three levels, explicit, implicit, and unelaborated. The results were (a) LE alone did not aid form recognition of vocabulary, (b) explicit LE alone aided meaning recognition of vocabulary, (c) TE alone did not aid form and meaning recognition of vocabulary, (d) LE and TE combined did not aid form recognition of vocabulary, (e) both explicit and implicit LE aided meaning recognition of vocabulary, (f) explicit and implicit LE did not differ in their effect on form and meaning recognition of vocabulary, and (g) whether a text was further enhanced in addition to either explicit or implicit LE did not seem to affect the acquisition of the previously unknown words' forms or meanings.

Traditional linear subspace reduced order models (LS-ROMs) are able to accelerate physical simulations in which the intrinsic solution space falls into a subspace with a small dimension, i.e., the solution space has a small Kolmogorov n-width. However, for physical phenomena not of this type, e.g., any advection-dominated flow phenomena such as in traffic flow, atmospheric flows, and air flow over vehicles, a low-dimensional linear subspace poorly approximates the solution. To address cases such as these, we have developed a fast and accurate physics-informed neural network ROM, namely nonlinear manifold ROM (NM-ROM), which can better approximate high-fidelity model solutions with a smaller latent space dimension than the LS-ROMs. Our method takes advantage of the existing numerical methods that are used to solve the corresponding full order models. The efficiency is achieved by developing a hyper-reduction technique in the context of the NM-ROM. Numerical results show that neural networks can learn a more efficient latent space representation on advection-dominated data from 1D and 2D Burgers' equations. A speedup of up to 2.6 for 1D Burgers' and a speedup of 11.7 for 2D Burgers' equations are achieved with an appropriate treatment of the nonlinear terms through a hyper-reduction technique. Finally, a posteriori error bounds for the NM-ROMs are derived that take account of the hyper-reduced operators.

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MicroRNAs (miRNAs) play critical roles in controlling various cellular processes, and the expression levels of individual miRNAs can be considerably altered in pathological conditions such as cancer. Accurate quantification of miRNA at the single-cell level will lead to a better understanding of miRNA function. Here, we present a direct and sensitive method for miRNA detection using atomic force microscopy (AFM). A hybrid binding domain (HBD)-tethered tip enabled mature miRNAs, but not premature miRNAs, to be located individually on an adhesion force map. By scanning several sections of a micrometer-sized DNA spot, we were able to quantify the copy number of miR-134 in a single neuron and demonstrate that the expression was increased upon cell activation. Moreover, we visualized individual miR-134s on fixed neurons after membrane removal and observed 2-4 miR-134s in the area of 1.0 × 1.0 μm(2) of soma. The number increased to 8-14 in stimulated neurons, and this change matches the ensemble-averaged increase in copy number. These findings indicate that miRNAs can be reliably quantified at the single cell level with AFM and that their distribution can be mapped at nanometric lateral resolution without modification or amplification. Furthermore, the analysis of miRNAs, mRNAs, and proteins in the same sample or region by scanning sequentially with different AFM tips would let us accurately understand the post-transcriptional regulation of biological processes.

Single-stranded 50-mer, 100-mer, and 150-mer DNAs were immobilized on a surface, and force-based atomic force microscopy (AFM) was employed to examine their behavior. A complementary 20-mer probe DNA on an AFM tip was used for the measurements. High-resolution maps were generated, and relevant parameters, including the force, stretching distance, unbinding probability, cluster size, and degree of distortion, were analyzed. Due to thermal drift, the cluster shape became increasingly distorted as the scan speed was decreased and as the map area was reduced. The cluster radius increased with the number of base (N), and the radius was proportional to N(0.6) (r = 0.977) and N(0.53) (r = 0.991). Due to the effect of the pulling angle, the apparent values of the stretching distance and the unbinding force decreased as the AFM probe was moved away from the center position; these values can be described as a function of sin θ.

Dendritic spines are major loci of excitatory inputs and undergo activity-dependent structural changes that contribute to synaptic plasticity and memory formation. Despite the existence of various classification types of spines, how they arise and which molecular components trigger their structural plasticity remain elusive. microRNAs (miRNAs) have emerged as critical regulators of synapse development and plasticity via their control of gene expression. Brain-specific miR-134s likely regulate the morphological maturation of spines, but their subcellular distributions and functional impacts have rarely been assessed. Here, we exploited atomic force microscopy to visualize in situ miR-134s, which indicated that they are mainly distributed at nearby dendritic shafts and necks of spines. The abundance of miR-134s varied between morphologically and functionally distinct spine types, and their amounts were inversely correlated with their postulated maturation stages. Moreover, spines exhibited reduced contents of miR-134s when selectively stimulated with beads containing brain-derived neurotropic factor (BDNF). Taken together, in situ visualizations of miRNAs provided unprecedented insights into the “inverse synaptic-tagging” roles of miR-134s that are selective to inactive/irrelevant synapses and potentially a molecular means for modifying synaptic connectivity via structural alteration.