Tumor cell invasion of model 3‐dimensional matrices: demonstration of migratory pathways, collagen disruption, and intercellular cooperation

We report a novel 3‐dimensional model for visualizing tumor cell migration across a nylon mesh‐supported gelatin matrix. To visualize migration across these model barriers, cell proteolytic activity of the pericellular matrix was detected using Bodipy‐BSA (fluorescent upon proteolysis) and DQ™ collagen (fluorescent upon collagenase activity). For 3‐dimensional image reconstruction, multiple optical images at sequential z axis positions were deconvoluted by computer analysis. Specificity was indicated using well‐known inhibitors. Using these fluorescent proteolysis markers and imaging methods, we have directly demonstrated proteolytic and collagenolytic activity during tumor cell invasion. Moreover, it is possible to visualize migratory pathways followed by tumor cells during matrix invasion. Using cells of differing invasive potentials (uPAR‐negative T‐47D wild‐type and uPAR‐positive T‐47D A2–1 cells), we show that the presence of the T‐47D‐A2–1 cells facilitates the entry of T‐47D wild‐type cells into the matrix. In some cases, wild‐type cells follow T‐47D A2–1 cells into the matrix whereas other T‐47D‐wild‐type cells appear to enter without the direct intervention of T‐47D A2–1 cells. Thus, we have developed a new 3‐dimensional model of tumor cell invasion, demonstrated protein and collagen disruption, mapped the pathways followed by tumor cells during migration through an extracellular matrix, and illustrated cross‐talk among tumor cell populations during invasion.—Horino, K., Kindezelskii, A. L., Elner, V. M., Hughes, B. A., Petty, H. R. Tumor cell invasion of model 3‐dimensional matrices: demonstration of migratory pathways, collagen disruption, and intercellular cooperation. FASEB J. 15, 932–939 (2001)Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/154275/1/fsb2fj000392com.pd

Toll-Like Receptor 4 (TLR4) of Retinal Pigment Epithelial Cells Participates in Transmembrane Signaling in Response to Photoreceptor Outer Segments

Retinal pigment epithelial (RPE) cells mediate the recognition and clearance of effete photoreceptor outer segments (POS), a process central to the maintenance of normal vision. Given the emerging importance of Toll-like receptors (TLRs) in transmembrane signaling in response to invading pathogens as well as endogenous substances, we hypothesized that TLRs are associated with RPE cell management of POS. TLR4 clusters on human RPE cells in response to human, but not bovine, POS. However, TLR4 clustering could be inhibited by saturating concentrations of an inhibitory anti-TLR4 mAb. Furthermore, human POS binding to human RPE cells elicited transmembrane metabolic and calcium signals within RPE cells, which could be blocked by saturating doses of an inhibitory anti-TLR4 mAb. However, the heterologous combination of bovine POS and human RPE did not trigger these signals. The pattern recognition receptor CD36 collected at the POS–RPE cell interface for both homologous and heterologous samples, but human TLR4 only collected at the human POS–human RPE cell interface. Kinetic experiments of human POS binding to human RPE cells revealed that CD36 arrives at the POS–RPE interface followed by TLR4 accumulation within 2 min. Metabolic and calcium signals immediately follow. Similarly, the production of reactive oxygen metabolites (ROMs) was observed for the homologous human system, but not the heterologous bovine POS–human RPE cell system. As (a) the bovine POS/human RPE combination did not elicit TLR4 accumulation, RPE signaling, or ROM release, (b) TLR4 arrives at the POS–RPE cell interface just before signaling, (c) TLR4 blockade with an inhibitory anti-TLR4 mAb inhibited TLR4 clustering, signaling, and ROM release in the human POS–human RPE system, and (d) TLR4 demonstrates similar clustering and signaling responses to POS in confluent RPE monolayers, we suggest that TLR4 of RPE cells participates in transmembrane signaling events that contribute to the management of human POS

Measurements and Analysis of Secondary User Device Effects on Digital Television Receivers

This is the published version. Copyright © 2009 Newman et al.This article presents results from a study of the potential effects of secondary users operating in unoccupied television spectrum. Television spectrum is known within the wireless communications community as being underutilized, making it a prime candidate for dynamic spectrum access. The proposed use of this open spectrum has prompted questions concerning the quantity of available channel space that could be used without negative impact on consumers who view digital television broadcasts and the viability of secondary use of open channels immediately adjacent to a digital television broadcast channel. In this work, we investigate secondary device operation in the channels directly adjacent to a desired television channel, and the effects upon a selection of consumer digital television (DTV) receivers. Our observations strongly suggest that secondary users could operate "White Space Devices" (WSDs) in unoccupied channel bandwidth directly adjacent to a desired digital television (DTV) channel, with no observable adverse impact upon the reception of the desired channel content

Engineering Molecular Ligand Shells on Quantum Dots for Quantitative Harvesting of Triplet Excitons Generated by Singlet Fission.

Singlet fission is an exciton multiplication process in organic molecules in which a photogenerated spin-singlet exciton is rapidly and efficiently converted to two spin-triplet excitons. This process offers a mechanism to break the Shockley-Queisser limit by overcoming the thermalization losses inherent to all single-junction photovoltaics. One of the most promising methods to harness the singlet fission process is via the efficient extraction of the dark triplet excitons into quantum dots (QDs) where they can recombine radiatively, thereby converting high-energy photons to pairs of low-energy photons, which can then be captured in traditional inorganic PVs such as Si. Such a singlet fission photon multiplication (SF-PM) process could increase the efficiency of the best Si cells from 26.7% to 32.5%, breaking the Shockley-Queisser limit. However, there has been no demonstration of such a singlet fission photon multiplication (SF-PM) process in a bulk system to date. Here, we demonstrate a solution-based bulk SF-PM system based on the singlet fission material TIPS-Tc combined with PbS QDs. Using a range of steady-state and time-resolved measurements combined with analytical modeling we study the dynamics and mechanism of the triplet harvesting process. We show that the system absorbs >95% of incident photons within the singlet fission material to form singlet excitons, which then undergo efficient singlet fission in the solution phase (135 ± 5%) before quantitative harvesting of the triplet excitons (95 ± 5%) via a low concentration of QD acceptors, followed by the emission of IR photons. We find that in order to achieve efficient triplet harvesting it is critical to engineer the surface of the QD with a triplet transfer ligand and that bimolecular decay of triplets is potentially a major loss pathway which can be controlled via tuning the concentration of QD acceptors. We demonstrate that the photon multiplication efficiency is maintained up to solar fluence. Our results establish the solution-based SF-PM system as a simple and highly tunable platform to understand the dynamics of a triplet energy transfer process between organic semiconductors and QDs, one that can provide clear design rules for new materials.ER

Evidence and Ideology in Macroeconomics: The Case of Investment Cycles

The paper reports the principal findings of a long term research project on the description and explanation of business cycles. The research strongly confirmed the older view that business cycles have large systematic components that take the form of investment cycles. These quasi-periodic movements can be represented as low order, stochastic, dynamic processes with complex eigenvalues. Specifically, there is a fixed investment cycle of about 8 years and an inventory cycle of about 4 years. Maximum entropy spectral analysis was employed for the description of the cycles and continuous time econometrics for the explanatory models. The central explanatory mechanism is the second order accelerator, which incorporates adjustment costs both in relation to the capital stock and the rate of investment. By means of parametric resonance it was possible to show, both theoretically and empirically how cycles aggregate from the micro to the macro level. The same mathematical tool was also used to explain the international convergence of cycles. I argue that the theory of investment cycles was abandoned for ideological, not for evidential reasons. Methodological issues are also discussed

Genetic Drivers of Heterogeneity in Type 2 Diabetes Pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P \u3c 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care

Genetic drivers of heterogeneity in type 2 diabetes pathophysiology

Type 2 diabetes (T2D) is a heterogeneous disease that develops through diverse pathophysiological processes1,2 and molecular mechanisms that are often specific to cell type3,4. Here, to characterize the genetic contribution to these processes across ancestry groups, we aggregate genome-wide association study data from 2,535,601 individuals (39.7% not of European ancestry), including 428,452 cases of T2D. We identify 1,289 independent association signals at genome-wide significance (P &lt; 5 × 10-8) that map to 611 loci, of which 145 loci are, to our knowledge, previously unreported. We define eight non-overlapping clusters of T2D signals that are characterized by distinct profiles of cardiometabolic trait associations. These clusters are differentially enriched for cell-type-specific regions of open chromatin, including pancreatic islets, adipocytes, endothelial cells and enteroendocrine cells. We build cluster-specific partitioned polygenic scores5 in a further 279,552 individuals of diverse ancestry, including 30,288 cases of T2D, and test their association with T2D-related vascular outcomes. Cluster-specific partitioned polygenic scores are associated with coronary artery disease, peripheral artery disease and end-stage diabetic nephropathy across ancestry groups, highlighting the importance of obesity-related processes in the development of vascular outcomes. Our findings show the value of integrating multi-ancestry genome-wide association study data with single-cell epigenomics to disentangle the aetiological heterogeneity that drives the development and progression of T2D. This might offer a route to optimize global access to genetically informed diabetes care.</p

SARS-CoV-2 susceptibility and COVID-19 disease severity are associated with genetic variants affecting gene expression in a variety of tissues

Variability in SARS-CoV-2 susceptibility and COVID-19 disease severity between individuals is partly due to genetic factors. Here, we identify 4 genomic loci with suggestive associations for SARS-CoV-2 susceptibility and 19 for COVID-19 disease severity. Four of these 23 loci likely have an ethnicity-specific component. Genome-wide association study (GWAS) signals in 11 loci colocalize with expression quantitative trait loci (eQTLs) associated with the expression of 20 genes in 62 tissues/cell types (range: 1:43 tissues/gene), including lung, brain, heart, muscle, and skin as well as the digestive system and immune system. We perform genetic fine mapping to compute 99% credible SNP sets, which identify 10 GWAS loci that have eight or fewer SNPs in the credible set, including three loci with one single likely causal SNP. Our study suggests that the diverse symptoms and disease severity of COVID-19 observed between individuals is associated with variants across the genome, affecting gene expression levels in a wide variety of tissue types

A first update on mapping the human genetic architecture of COVID-19

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