Enhancement of the Spin Accumulation at the Interface Between a Spin-Polarized Tunnel Junction and a Semiconductor

We report on spin injection experiments at a Co/Al$_2$O$_3$/GaAs interface with electrical detection. The application of a transverse magnetic field induces a large voltage drop $\Delta V$ at the interface as high as 1.2mV for a current density of 0.34 nA.$\mu m^{-2}$. This represents a dramatic increase of the spin accumulation signal, well above the theoretical predictions for spin injection through a ferromagnet/semiconductor interface. Such an enhancement is consistent with a sequential tunneling process via localized states located in the vicinity of the Al$_2$O$_3$/GaAs interface. For spin-polarized carriers these states act as an accumulation layer where the spin lifetime is large. A model taking into account the spin lifetime and the escape tunneling time for carriers travelling back into the ferromagnetic contact reproduces accurately the experimental results

Hypoxia-induced long non-coding RNA Malat1 is dispensable for renal ischemia/reperfusion-injury

Renal ischemia-reperfusion (I/R) injury is a major cause of acute kidney injury (AKI). Non-coding RNAs are crucially involved in its pathophysiology. We identified hypoxia-induced long non-coding RNA Malat1 (Metastasis Associated Lung Adenocarcinoma Transcript 1) to be upregulated in renal I/R injury. We here elucidated the functional role of Malat1 in vitro and its potential contribution to kidney injury in vivo. Malat1 was upregulated in kidney biopsies and plasma of patients with AKI, in murine hypoxic kidney tissue as well as in cultured and ex vivo sorted hypoxic endothelial cells and tubular epithelial cells. Malat1 was transcriptionally activated by hypoxia-inducible factor 1-a. In vitro, Malat1 inhibition reduced proliferation and the number of endothelial cells in the S-phase of the cell cycle. In vivo, Malat1 knockout and wildtype mice showed similar degrees of outer medullary tubular epithelial injury, proliferation, capillary rarefaction, inflammation and fibrosis, survival and kidney function. Small-RNA sequencing and whole genome expression analysis revealed only minor changes between ischemic Malat1 knockout and wildtype mice. Contrary to previous studies, which suggested a prominent role of Malat1 in the induction of disease, we did not confirm an in vivo role of Malat1 concerning renal I/Rinjury

Pparγ2 Is a Key Driver of Longevity in the Mouse

Aging involves a progressive physiological remodeling that is controlled by both genetic and environmental factors. Many of these factors impact also on white adipose tissue (WAT), which has been shown to be a determinant of lifespan. Interrogating a transcriptional network for predicted causal regulatory interactions in a collection of mouse WAT from F2 crosses with a seed set of 60 known longevity genes, we identified a novel transcriptional subnetwork of 742 genes which represent thus-far-unknown longevity genes. Within this subnetwork, one gene was Pparg (Nr1c3), an adipose-enriched nuclear receptor previously not associated with longevity. In silico, both the PPAR signaling pathway and the transcriptional signature of Pparγ agonist rosiglitazone overlapped with the longevity subnetwork, while in vivo, lowered expression of Pparg reduced lifespan in both the lipodystrophic Pparg1/2-hypomorphic and the Pparg2-deficient mice. These results establish Pparγ2 as one of the determinants of longevity and suggest that lifespan may be rather determined by a purposeful genetic program than a random process

Integrative Analysis of Many Weighted Co-Expression Networks Using Tensor Computation

The rapid accumulation of biological networks poses new challenges and calls for powerful integrative analysis tools. Most existing methods capable of simultaneously analyzing a large number of networks were primarily designed for unweighted networks, and cannot easily be extended to weighted networks. However, it is known that transforming weighted into unweighted networks by dichotomizing the edges of weighted networks with a threshold generally leads to information loss. We have developed a novel, tensor-based computational framework for mining recurrent heavy subgraphs in a large set of massive weighted networks. Specifically, we formulate the recurrent heavy subgraph identification problem as a heavy 3D subtensor discovery problem with sparse constraints. We describe an effective approach to solving this problem by designing a multi-stage, convex relaxation protocol, and a non-uniform edge sampling technique. We applied our method to 130 co-expression networks, and identified 11,394 recurrent heavy subgraphs, grouped into 2,810 families. We demonstrated that the identified subgraphs represent meaningful biological modules by validating against a large set of compiled biological knowledge bases. We also showed that the likelihood for a heavy subgraph to be meaningful increases significantly with its recurrence in multiple networks, highlighting the importance of the integrative approach to biological network analysis. Moreover, our approach based on weighted graphs detects many patterns that would be overlooked using unweighted graphs. In addition, we identified a large number of modules that occur predominately under specific phenotypes. This analysis resulted in a genome-wide mapping of gene network modules onto the phenome. Finally, by comparing module activities across many datasets, we discovered high-order dynamic cooperativeness in protein complex networks and transcriptional regulatory networks

2018 57, (12) pp 7064-7076

International audiencePDF data obtained at 900°C for UO2, UO2.007, and UO2.16. Full spheres: Modeling results suggest a gradual change in the majority anion defect population from a monointerstitial to a di-interstitial to possibly an even more compact structure such as a cuboctahedron. This has also been reported in U4O9, indicating that in the high-temperature single-phase UO2+x they are present but have no regular arrangement as they do in U4O9