The effect of dark and equiluminant occlusion on the interocular transfer of visual aftereffects

Because changes in intracellular Ca2+ affect progression through the mitotic cell cycle, we investigated the role of Ca2+-binding proteins in regulating cell cycle progression. Evidence was found demonstrating that the activation of Ca2+/calmodulin-dependent protein kinase (CaM kinase) inhibits cell cycle progression in small cell lung carcinoma (SCLC) cells. We also demonstrated that SCLC cells express both CaM kinase type II (CaMKII) and CaM kinase type IV (CaMKIV). Five independent SCLC cell lines expressed proteins reactive with antibody to the CaMKII beta subunit, but none expressed detectable proteins reactive with antibody to the CaMKII alpha subunit. All SCLC cell lines tested expressed both the alpha and beta isoforms of CaMKIV. Immunoprecipitation of CaMKII from SCLC cells yielded multiple proteins that autophosphorylated in the presence of Ca2+ / calmodulin. Autophosphorylation was inhibited by the CaMKII(281-302) peptide, which corresponds to the CaMKII autoinhibitory domain, and by 1-[N,O-bis(5-isoquinolinesulfonyl)-N-methyl-L-tyrosyl]-4- phenylpiperazine (KN-62), a specific CaM kinase antagonist. Influx of Ca2+ through voltage-gated Ca2+ channels stimulated phosphorylation of CaMKII in SCLC cells, and this was inhibited by KN-62. Incubation of SCLC cells of KN-62 potently inhibited DNA synthesis, and slowed progression through S phase. Similar anti-proliferative effects of KN-62 occurred in SK-N-SH human neuroblastoma cells, which express both CaMKII and CaMKIV, and in K562 human chronic myelogenous leukemia cells, which express CaMKII but not CaMKIV. The expression of both CaMKII and CaMKIV by SCLC cells, and the sensitivity of these cells to the anti-proliferative effects of KN-62, suggest a role for CaM kinase in regulating SCLC proliferation.     

The traveling heads: multicenter brain imaging at 7 Tesla

Objective

This study evaluates the inter-site and intra-site reproducibility of 7 Tesla brain imaging and compares it to literature values for other field strengths.

Materials and methods

The same two subjects were imaged at eight different 7 T sites. MP2RAGE, TSE, TOF, SWI, EPI as well as B1 and B0 field maps were analyzed quantitatively to assess inter-site reproducibility. Intra-site reproducibility was measured with rescans at three sites.

Results

Quantitative measures of MP2RAGE scans showed high agreement. Inter-site and intra-site reproducibility errors were comparable to 1.5 and 3 T. Other sequences also showed high reproducibility between the sites, but differences were also revealed. The different RF coils used were the main source for systematic differences between the sites.

Conclusion

Our results show for the first time that multi-center brain imaging studies of the supratentorial brain can be performed at 7 T with high reproducibility and similar reliability as at 3T. This study develops the basis for future large-scale 7 T multi-site studies.

     

Phase stability and microstructural formations in the niobium carbides

The phase stability and microstructural formations for a series of hot isostatically pressed (HIP) NbC_x compositions was investigated. Based on the composition, single-phase B1 (Fm$\overline{3}$m) NbC or (P$\overline{3}$1m) β?Nb₂C equiaxed grains were observed as well as β-Nb₂C lath precipitation within NbC. Particular discussion is given to the complexities of X-ray and electron diffraction for proper identification for the various poly-types of Nb₂C that have been computationally predicted. The phase transformation pathways for these microstructures was revealed by a NbC-Nb diffusion couple from the HIP powders. The migration of vacancies towards the NbC side resulted in a refinement of the NbC grains whereas carbon’s migration into the Nb formed an uniform and distinct reaction front with a mixture of β-Nb₂C and Nb grains. This latter microstructure suggests carbon’s reaction through the matrix grain is as significant in the conversion process as is the precipitation of β-Nb₂C at the grain boundaries.     

Boosted multi-task learning

In this paper we propose a novel algorithm for multi-task learning with boosted decision trees. We learn several different learning tasks with a joint model, explicitly addressing their commonalities through shared parameters and their differences with task-specific ones. This enables implicit data sharing and regularization. Our algorithm is derived using the relationship between ? ₁-regularization and boosting. We evaluate our learning method on web-search ranking data sets from several countries. Here, multi-task learning is particularly helpful as data sets from different countries vary largely in size because of the cost of editorial judgments. Further, the proposed method obtains state-of-the-art results on a publicly available multi-task dataset. Our experiments validate that learning various tasks jointly can lead to significant improvements in performance with surprising reliability.