High-throughput single cell arrays as a novel tool in biopreservation

Microwell array cytometry is a novel high-throughput experimental technique that makes it possible to correlate pre-stress cell phenotypes and post-stress outcomes with single cell resolution. Because the cells are seeded in a high density grid of cell-sized microwells, thousands of individual cells can be tracked and imaged through manipulations as extreme as freezing or drying. Unlike flow cytometry, measurements can be made at multiple time points for the same set of cells. Unlike conventional image cytometry, image analysis is greatly simplified by arranging the cells in a spatially defined pattern and physically separating them from one another. To demonstrate the utility of microwell array cytometry in the field of biopreservation, we have used it to investigate the role of mitochondrial membrane potential in the cryopreservation of primary hepatocytes. Even with optimized cryopreservation protocols, the stress of freezing almost always leads to dysfunction or death in part of the cell population. To a large extent, cell fate is dominated by the stochastic nature of ice crystal nucleation, membrane rupture, and other biophysical processes, but natural variation in the initial cell population almost certainly plays an important and under-studied role. Understanding why some cells in a population are more likely to survive preservation will be invaluable for the development of new approaches to improve preservation yields. For this paper, primary hepatocytes were seeded in microwell array devices, imaged using the mitochondrial dyes Rh123 or JC-1, cryopreserved for up to a week, rapidly thawed, and checked for viability after a short recovery period. Cells with a high mitochondrial membrane potential before freezing were significantly less likely to survive the freezing process, though the difference in short term viability was fairly small. The results demonstrate that intrinsic cell factors do play an important role in cryopreservation survival, even in the short term where extrinsic biophysical factors would be expected to dominate. We believe that microwell array cytometry will be an important tool for a wide range of studies in biopreservation and stress biology. © 2009 Elsevier Inc. All rights reserved

Sub‐nanometer thick gold nanosheets as highly efficient catalysts

2D metal nanomaterials offer exciting prospects in terms of their properties and functions. However, the ambient aqueous synthesis of atomically‐thin, 2D metallic nanomaterials represents a significant challenge. Herein, freestanding and atomically‐thin gold nanosheets with a thickness of only 0.47 nm (two atomic layers thick) are synthesized via a one‐step aqueous approach at 20 °C, using methyl orange as a confining agent. Owing to the high surface‐area‐to‐volume ratio, abundance of unsaturated atoms exposed on the surface and large interfacial areas arising from their ultrathin 2D nature, the as‐prepared Au nanosheets demonstrate excellent catalysis performance in the model reaction of 4‐nitrophenol reduction, and remarkable peroxidase‐mimicking activity, which enables a highly sensitive colorimetric sensing of H2O2 with a detection limit of 0.11 × 10−6 m. This work represents the first fabrication of freestanding 2D gold with a sub‐nanometer thickness, opens up an innovative pathway toward atomically‐thin metal nanomaterials that can serve as model systems for inspiring fundamental advances in materials science, and holds potential across a wide region of applications

Sub‐nanometer thick gold nanosheets: sub‐nanometer thick gold nanosheets as highly efficient catalysts (Adv. Sci. 21/2019)

In article number 1900911, Stephen D. Evans and co‐workers develop an ambient aqueous synthesis for preparing atomically‐thin gold nanosheets (termed gold nanoseaweed, AuNSW, because of its morphology, color and aqueous growth). These AuNSWs represent the first free‐standing 2D gold with a sub‐nanometer thickness (0.47 nm, e.g., two atomic layers thick), and exhibit excellent catalysis performance in the model reaction of 4‐nitrophenol reduction, as well as remarkable peroxidase‐mimicking activity

Sub‐nanometer thick gold nanosheets: sub‐nanometer thick gold nanosheets as highly efficient catalysts (Adv. Sci. 21/2019)

In article number 1900911, Stephen D. Evans and co‐workers develop an ambient aqueous synthesis for preparing atomically‐thin gold nanosheets (termed gold nanoseaweed, AuNSW, because of its morphology, color and aqueous growth). These AuNSWs represent the first free‐standing 2D gold with a sub‐nanometer thickness (0.47 nm, e.g., two atomic layers thick), and exhibit excellent catalysis performance in the model reaction of 4‐nitrophenol reduction, as well as remarkable peroxidase‐mimicking activity

Pathologic gene network rewiring implicates PPP1R3A as a central regulator in pressure overload heart failure

Heart failure is a leading cause of mortality, yet our understanding of the genetic interactions underlying this disease remains incomplete. Here, we harvest 1352 healthy and failing human hearts directly from transplant center operating rooms, and obtain genome-wide genotyping and gene expression measurements for a subset of 313. We build failing and non-failing cardiac regulatory gene networks, revealing important regulators and cardiac expression quantitative trait loci (eQTLs). PPP1R3A emerges as a regulator whose network connectivity changes significantly between health and disease. RNA sequencing after PPP1R3A knockdown validates network-based predictions, and highlights metabolic pathway regulation associated with increased cardiomyocyte size and perturbed respiratory metabolism. Mice lacking PPP1R3A are protected against pressure-overload heart failure. We present a global gene interaction map of the human heart failure transition, identify previously unreported cardiac eQTLs, and demonstrate the discovery potential of disease-specific networks through the description of PPP1R3A as a central regulator in heart failure

Manipulating ultracold atoms with a reconfigurable nanomagnetic system of domain walls

The divide between the realms of atomic-scale quantum particles and lithographically-defined nanostructures is rapidly being bridged. Hybrid quantum systems comprising ultracold gas-phase atoms and substrate-bound devices already offer exciting prospects for quantum sensors, quantum information and quantum control. Ideally, such devices should be scalable, versatile and support quantum interactions with long coherence times. Fulfilling these criteria is extremely challenging as it demands a stable and tractable interface between two disparate regimes. Here we demonstrate an architecture for atomic control based on domain walls (DWs) in planar magnetic nanowires that provides a tunable atomic interaction, manifested experimentally as the reflection of ultracold atoms from a nanowire array. We exploit the magnetic reconfigurability of the nanowires to quickly and remotely tune the interaction with high reliability. This proof-of-principle study shows the practicability of more elaborate atom chips based on magnetic nanowires being used to perform atom optics on the nanometre scale.Comment: 4 pages, 4 figure

Genomic, Pathway Network, and Immunologic Features Distinguishing Squamous Carcinomas

This integrated, multiplatform PanCancer Atlas study co-mapped and identified distinguishing molecular features of squamous cell carcinomas (SCCs) from five sites associated with smokin

Pan-Cancer Analysis of lncRNA Regulation Supports Their Targeting of Cancer Genes in Each Tumor Context

Long noncoding RNAs (lncRNAs) are commonly dys-regulated in tumors, but only a handful are known toplay pathophysiological roles in cancer. We inferredlncRNAs that dysregulate cancer pathways, onco-genes, and tumor suppressors (cancer genes) bymodeling their effects on the activity of transcriptionfactors, RNA-binding proteins, and microRNAs in5,185 TCGA tumors and 1,019 ENCODE assays.Our predictions included hundreds of candidateonco- and tumor-suppressor lncRNAs (cancerlncRNAs) whose somatic alterations account for thedysregulation of dozens of cancer genes and path-ways in each of 14 tumor contexts. To demonstrateproof of concept, we showed that perturbations tar-geting OIP5-AS1 (an inferred tumor suppressor) andTUG1 and WT1-AS (inferred onco-lncRNAs) dysre-gulated cancer genes and altered proliferation ofbreast and gynecologic cancer cells. Our analysis in-dicates that, although most lncRNAs are dysregu-lated in a tumor-specific manner, some, includingOIP5-AS1, TUG1, NEAT1, MEG3, and TSIX, synergis-tically dysregulate cancer pathways in multiple tumorcontexts

Pan-cancer Alterations of the MYC Oncogene and Its Proximal Network across the Cancer Genome Atlas

Although theMYConcogene has been implicated incancer, a systematic assessment of alterations ofMYC, related transcription factors, and co-regulatoryproteins, forming the proximal MYC network (PMN),across human cancers is lacking. Using computa-tional approaches, we define genomic and proteo-mic features associated with MYC and the PMNacross the 33 cancers of The Cancer Genome Atlas.Pan-cancer, 28% of all samples had at least one ofthe MYC paralogs amplified. In contrast, the MYCantagonists MGA and MNT were the most frequentlymutated or deleted members, proposing a roleas tumor suppressors.MYCalterations were mutu-ally exclusive withPIK3CA,PTEN,APC,orBRAFalterations, suggesting that MYC is a distinct onco-genic driver. Expression analysis revealed MYC-associated pathways in tumor subtypes, such asimmune response and growth factor signaling; chro-matin, translation, and DNA replication/repair wereconserved pan-cancer. This analysis reveals insightsinto MYC biology and is a reference for biomarkersand therapeutics for cancers with alterations ofMYC or the PMN

Spatial Organization and Molecular Correlation of Tumor-Infiltrating Lymphocytes Using Deep Learning on Pathology Images

Beyond sample curation and basic pathologic characterization, the digitized H&E-stained images of TCGA samples remain underutilized. To highlight this resource, we present mappings of tumorinfiltrating lymphocytes (TILs) based on H&E images from 13 TCGA tumor types. These TIL maps are derived through computational staining using a convolutional neural network trained to classify patches of images. Affinity propagation revealed local spatial structure in TIL patterns and correlation with overall survival. TIL map structural patterns were grouped using standard histopathological parameters. These patterns are enriched in particular T cell subpopulations derived from molecular measures. TIL densities and spatial structure were differentially enriched among tumor types, immune subtypes, and tumor molecular subtypes, implying that spatial infiltrate state could reflect particular tumor cell aberration states. Obtaining spatial lymphocytic patterns linked to the rich genomic characterization of TCGA samples demonstrates one use for the TCGA image archives with insights into the tumor-immune microenvironment