Deterministic lateral displacement (DLD) pillar arrays are an efficient technology to sort, separate and enrich micrometre-scale particles, which include parasites, bacteria, blood cells and circulating tumour cells in blood. However, this technology has not been translated to the true nanoscale, where it could function on biocolloids, such as exosomes. Exosomes, a key target of 'liquid biopsies', are secreted by cells and contain nucleic acid and protein information about their originating tissue. One challenge in the study of exosome biology is to sort exosomes by size and surface markers. We use manufacturable silicon processes to produce nanoscale DLD (nano-DLD) arrays of uniform gap sizes ranging from 25 to 235 nm. We show that at low Péclet (Pe) numbers, at which diffusion and deterministic displacement compete, nano-DLD arrays separate particles between 20 to 110 nm based on size with sharp resolution. Further, we demonstrate the size-based displacement of exosomes, and so open up the potential for on-chip sorting and quantification of these important biocolloids.

Graphical Abstract Highlights d The exRNA Atlas provides access to human exRNA profiles and web-accessible tools d Atlas analysis reveals six exRNA cargo types present across five human biofluids d Five of the cargo types associate with specific vesicular and non-vesicular carriers d These findings and resources empower studies of extracellular RNA communication An extracellular RNA atlas from five human biofluids (serum, plasma, cerebrospinal fluid, saliva, and urine) reveals six extracellular RNA cargo types, including both vesicular and nonvesicular carriers. SUMMARY To develop a map of cell-cell communication mediated by extracellular RNA (exRNA), the NIH Extracellular RNA Communication Consortium created the exRNA Atlas resource (https://exrna-atlas.org). The Atlas version 4P1 hosts 5,309 exRNA-seq and exRNA qPCR profiles from 19 studies and a suite of analysis and visualization tools. To analyze variation between profiles, we apply computational deconvolution. The analysis leads to a model with six exRNA cargo types (CT1, CT2, CT3A, CT3B, CT3C, CT4), each detectable in multiple biofluids (serum, plasma, CSF, saliva, urine). Five of the cargo types associate with known vesicular and non-vesicular (lipoprotein and ribonucleoprotein) exRNA carriers. To validate utility of this model, we re-analyze an exercise response study by deconvolution to identify physiologically relevant response pathways that were not detected previously.To enable wide application of this model, as part of the exRNA Atlas resource, we provide tools for deconvolution and analysis of user-provided case-control studies.

Performance of graphene electronics is limited by contact resistance associated with the metal-graphene (M-G) interface, where unique transport challenges arise as carriers are injected from a 3D metal into a 2D-graphene sheet. In this work, enhanced carrier injection is experimentally achieved in graphene devices by forming cuts in the graphene within the contact regions. These cuts are oriented normal to the channel and facilitate bonding between the contact metal and carbon atoms at the graphene cut edges, reproducibly maximizing "edge-contacted" injection. Despite the reduction in M-G contact area caused by these cuts, we find that a 32% reduction in contact resistance results in Cu-contacted, two-terminal devices, while a 22% reduction is achieved for top-gated graphene transistors with Pd contacts as compared to conventionally fabricated devices. The crucial role of contact annealing to facilitate this improvement is also elucidated. This simple approach provides a reliable and reproducible means of lowering contact resistance in graphene devices to bolster performance. Importantly, this enhancement requires no additional processing steps.

Rapid, continuous flow enrichment of EVs is enabled by integrating >1000 nanoDLD arrays.

Among the challenges hindering the integration of carbon nanotube (CNT) transistors in digital technology are the lack of a scalable self-aligned gate and complementary n- and p-type devices. We report CNT transistors with self-aligned gates scaled down to 20 nm in the ideal gate-all-around geometry. Uniformity of the gate wrapping the nanotube channels is confirmed, and the process is shown not to damage the CNTs. Further, both n- and p-type transistors were realized by using the appropriate gate dielectric-HfO2 yielded n-type and Al2O3 yielded p-type-with quantum simulations used to explore the impact of important device parameters on performance. These discoveries not only provide a promising platform for further research into gate-all-around CNT devices but also demonstrate that scalable digital switches with realistic technological potential can be achieved with carbon nanotubes.

Advances in colorectal cancer (CRC) diagnosis will be enhanced by development of more sensitive and reliable methods for early detection of the disease when treatment is more effective. Because many known disease biomarkers are membrane-bound glycoproteins with important biological functions, we chose to compare N-glycan profiles of membrane proteins from three phenotypically different CRC cell lines, LIM1215, LIM1899, and LIM2405, representing moderately differentiated metastatic, moderately differentiated primary, and poorly differentiated (aggressive) primary CRC cell lines, respectively. The N-glycan structures and their relative abundances were determined as their underivatized reduced forms, using porous graphitized carbon LC-ESI-MS/MS. A key observation was the similar N-glycan landscape in these cells with the dominance of high mannose type glycan structures (70-90%) in all three cell lines, suggesting an incomplete glycan processing. Importantly, unique glycan determinants such as bisecting N-acetylglucosamine were observed at a high level in the metastatic LIM1215 cells, with some expressed in the moderately differentiated LIM1899, while none were detected in the poorly differentiated LIM2405 cells. Conversely, α-2,3-sialylation was completely absent in LIM1215 and LIM1899 and present only in LIM2405. RNA-Seq and lectin immunofluorescence data correlated well with these data, showing the highest upregulation of Mgat3 and binding with PHA-E in LIM1215. Downregulation of Man1α1 and Mgat1 in LIM1215 also coincided with the higher degree of incomplete N-glycan processing and accumulation of high mannose type structures as well as bisecting N-glycans when compared to the other two cell lines. This study provides a comprehensive analysis of the membrane N-glycome in three CRC cell lines and identifies N-glycosylation differences that correlate with the histological and pathological features of the cell lines. The unique glycosylation phenotypes may therefore serve as a molecular feature to differentiate CRC disease stages.

The advent of microfluidics in the 1990s promised a revolution in multiple industries, from healthcare to chemical processing. Deterministic Lateral Displacement (DLD) is a continuous-flow microfluidic particle separation method discovered in 2004 that has been applied successfully and widely to the separation of blood cells, yeast, spores, bacteria, viruses, DNA, droplets, and more. DLD is conceptually simple and can deliver consistent performance over a wide range of flow rates and particle concentrations.Despite wide use and in-depth study, DLD has not yet been fully understood or fully optimised, with different approaches to the same problem yielding varying results. We endeavour here to provide an up-to-date expert opinion on the state-of-art and current fundamental, practical, and commercial challenges as well as experimental and modelling opportunities. Since these challenges and opportunities arise from constraints on hydrodynamics, fabrication and operation at the micro-and nano-scale, we expect this article to serve as a guide for the broader micro-and nanofluidic community to identify and address open questions in the field.

Deterministic lateral displacement (DLD) is a technique for size fractionation of particles in continuous flow that has shown great potential for biological applications. Several theoretical models have been proposed, but experimental evidence has demonstrated that a rich class of intermediate migration behavior exists, which is not predicted. We present a unified theoretical framework to infer the path of particles in the whole array on the basis of trajectories in a unit cell. This framework explains many of the unexpected particle trajectories reported and can be used to design arrays for even nanoscale particle fractionation. We performed experiments that verify these predictions and used our model to develop a condenser array that achieves full particle separation with a single fluidic input.nanofluidics | deterministic ratchet | particle tracking D eterministic lateral displacement (DLD) is an efficient technology used to sort and purify small particles (1). Since their introduction (2), DLD pillar arrays have been used in applications from cell sorting (3) to biosensors (4) and can efficiently sort, separate, and enrich a broad range of particles, including parasites (5), bacteria (6), blood cells (7-9), circulating tumor cells (10), and exosomes (11). The original theory (12) predicts that particle trajectories fall into one of two modes, bumping or zigzag, as determined by the critical diameter Dc defined by the array geometry (2, 12). However, experimental evidence is clear that a rich class of intermediate migration behavior exists between these modes (13,14). Although a few theoretical models (15-17) have been proposed to explain this behavior, a general framework to study how geometric symmetry caused by pillar array influences particle trajectories is still missing.The symmetry of the pillar array can be explained in a specifically chosen unit cell. A typical DLD pillar array and associated unit cell are schematically represented in Fig. 1 A and B. Rows of pillars with diameter D0 are located along the y direction, with the pillars separated by a distance Dy , leaving a gap G = Dy −D0 in between pillars in the y direction. Adjacent rows of pillars are separated by a distance Dx in the x direction and shifted a distance in the y direction. The shift between one row and the N -th nearest row is then N . If this shift is chosen to coincide with Dy , then the array is periodic, and invariant to a translation of NDx in the x direction. Therefore, the array geometry has a built-in angle θp (smallest angle in the red triangle in Fig. 1B), such that tan(θp) = 1/N when Dx = Dy . Note that two types of array designs have been studied in the literature: the row-shifted parallelogram array (or stretched array) and the rotated square lattice (18,19). Here, we only studied the stretched DLD array design as shown in Fig. 1A. Our results do not extend to the rotated square array layout.Because of the invariance of NDx translational transformation, the fluid streamlines are assumed to have the same symmetry. When a...