Immunosuppressive mechanisms of human bone marrow derived mesenchymal stromal cells in BALB/c host graft versus host disease murine models

published_or_final_versio

Industrial cyber physical systems supported by distributed advanced data analytics

The industry digitization is transforming its business models, organizational structures and operations, mainly promoted by the advances and the mass utilization of smart methods, devices and products, being leveraged by initiatives like Industrie 4.0. In this context, the data is a valuable asset that can support the smart factory features through the use of Big Data and advanced analytics approaches. In order to address such requirements and related challenges, Cyber Physical Systems (CPS) promote the development of more intelligent, adaptable and responsiveness supervisory and control systems capable to overcome the inherent complexity and dynamics of industrial environments. In this context, this work presents an agent-based industrial CPS, where agents are endowed with data analysis capabilities for distributed, collaborative and adaptive process supervision and control. Additionally, to address the different industrial levels’ requirements, this work combines two main data analysis scopes: at operational level, applying distributed data stream analysis for rapid response monitoring and control, and at supervisory level, applying big data analysis for decision-making, planning and optimization. Some experiments have been performed in the context of an electric micro grid where agents were able to perform distributed data analysis to predict the renewable energy production.info:eu-repo/semantics/publishedVersio

Cutting-edge biotechnological advancement in islet delivery using pancreatic and cellular approaches.

There are approximately 1 billion prediabetic people worldwide, and the global cost for diabetes mellitus (DM) is estimated to be $825 billion. In regard to Type 1 DM, transplanting a whole pancreas or its islets has gained the attention of researchers in the last few decades. Recent studies showed that islet transplantation (ILT) containing insulin-producing β cells is the most notable advancement cure for Type 1 DM. However, this procedure has been hindered by shortage and lack of sufficient islet donors and the need for long-term immunosuppression of any potential graft rejection. The strategy of encapsulation may avoid the rejection of stem-cell-derived allogeneic islets or xenogeneic islets. This review article describes various biotechnology features in encapsulation-of-islet-cell therapy for humans, including the use of bile acids

Superconductivity at the Border of Electron Localization and Itinerancy

The superconducting state of iron pnictides and chalcogenides exists at the border of antiferromagnetic order. Consequently, these materials could provide clues about the relationship between magnetism and unconventional superconductivity. One explanation, motivated by the so-called bad-metal behaviour of these materials, proposes that magnetism and superconductivity develop out of quasi-localized magnetic moments which are generated by strong electron-electron correlations. Another suggests that these phenomena are the result of weakly interacting electron states that lie on nested Fermi surfaces. Here we address the issue by comparing the newly discovered alkaline iron selenide superconductors, which exhibit no Fermi-surface nesting, to their iron pnictide counterparts. We show that the strong-coupling approach leads to similar pairing amplitudes in these materials, despite their different Fermi surfaces. We also find that the pairing amplitudes are largest at the boundary between electronic localization and itinerancy, suggesting that new superconductors might be found in materials with similar characteristics.Comment: Version of the published manuscript prior to final journal-editting. Main text (23 pages, 4 figures) + Supplementary Information (14 pages, 7 figures, 3 tables). Calculation on the single-layer FeSe is added. Enhancement of the pairing amplitude in the vicinity of the Mott transition is highlighted. Published version is at http://www.nature.com/ncomms/2013/131115/ncomms3783/full/ncomms3783.htm

Effective Dark Matter Model: Relic density, CDMS II, Fermi LAT and LHC

The Cryogenic Dark Matter Search recently announced the observation of two signal events with a 77% confidence level. Although statistically inconclusive, it is nevertheless suggestive. In this work we present a model-independent analysis on the implication of a positive signal in dark matter scattering off nuclei. Assuming the interaction between (scalar, fermion or vector) dark matter and the standard model induced by unknown new physics at the scale $\Lambda$, we examine various dimension-6 tree-level induced operators and constrain them using the current experimental data, e.g. the WMAP data of the relic abundance, CDMS II direct detection of the spin-independent scattering, and indirect detection data (Fermi LAT cosmic gamma-ray), etc. Finally, the LHC reach is also explored

The significance of macrophage phenotype in cancer and biomaterials

Macrophages have long been known to exhibit heterogeneous and plastic phenotypes. They show functional diversity with roles in homeostasis, tissue repair, immunity and disease. There exists a spectrum of macrophage phenotypes with varied effector functions, molecular determinants, cytokine and chemokine profiles, as well as receptor expression. In tumor microenvironments, the subset of macrophages known as tumor-associated macrophages generates byproducts that enhance tumor growth and angiogenesis, making them attractive targets for anti-cancer therapeutics. With respect to wound healing and the foreign body response, there is a necessity for balance between pro-inflammatory, wound healing, and regulatory macrophages in order to achieve successful implantation of a scaffold for tissue engineering. In this review, we discuss the multitude of ways macrophages are known to be important in cancer therapies and implanted biomaterials

Singlet-doublet Higgs mixing and its implications on the Higgs mass in the PQ-NMSSM

We examine the implications of singlet-doublet Higgs mixing on the properties of a Standard Model (SM)-like Higgs boson within the Peccei-Quinn invariant extension of the NMSSM (PQ-NMSSM). The SM singlet added to the Higgs sector connects the PQ and visible sectors through a PQ-invariant non-renormalizable K\"ahler potential term, making the model free from the tadpole and domain-wall problems. For the case that the lightest Higgs boson is dominated by the singlet scalar, the Higgs mixing increases the mass of a SM-like Higgs boson while reducing its signal rate at collider experiments compared to the SM case. The Higgs mixing is important also in the region of parameter space where the NMSSM contribution to the Higgs mass is small, but its size is limited by the experimental constraints on the singlet-like Higgs boson and on the lightest neutralino constituted mainly by the singlino whose Majorana mass term is forbidden by the PQ symmetry. Nonetheless the Higgs mixing can increase the SM-like Higgs boson mass by a few GeV or more even when the Higgs signal rate is close to the SM prediction, and thus may be crucial for achieving a 125 GeV Higgs mass, as hinted by the recent ATLAS and CMS data. Such an effect can reduce the role of stop mixing.Comment: 26 pages, 3 figures; published in JHE

A close examination of double filtering with fold change and t test in microarray analysis

<p>Abstract</p> <p>Background</p> <p>Many researchers use the double filtering procedure with fold change and <it>t </it>test to identify differentially expressed genes, in the hope that the double filtering will provide extra confidence in the results. Due to its simplicity, the double filtering procedure has been popular with applied researchers despite the development of more sophisticated methods.</p> <p>Results</p> <p>This paper, for the first time to our knowledge, provides theoretical insight on the drawback of the double filtering procedure. We show that fold change assumes all genes to have a common variance while <it>t </it>statistic assumes gene-specific variances. The two statistics are based on contradicting assumptions. Under the assumption that gene variances arise from a mixture of a common variance and gene-specific variances, we develop the theoretically most powerful likelihood ratio test statistic. We further demonstrate that the posterior inference based on a Bayesian mixture model and the widely used significance analysis of microarrays (SAM) statistic are better approximations to the likelihood ratio test than the double filtering procedure.</p> <p>Conclusion</p> <p>We demonstrate through hypothesis testing theory, simulation studies and real data examples, that well constructed shrinkage testing methods, which can be united under the mixture gene variance assumption, can considerably outperform the double filtering procedure.</p

Strain engineering and one-dimensional organization of metal-insulator domains in single-crystal VO2 beams

Spatial phase inhomogeneity at the nano- to microscale is widely observed in strongly-correlated electron materials. The underlying mechanism and possibility of artificially controlling the phase inhomogeneity are still open questions of critical importance for both the phase transition physics and device applications. Lattice strain has been shown to cause the coexistence of metallic and insulating phases in the Mott insulator VO2. By continuously tuning strain over a wide range in single-crystal VO2 micro- and nanobeams, here we demonstrate the nucleation and manipulation of one-dimensionally ordered metal-insulator domain arrays along the beams. Mott transition is achieved in these beams at room temperature by active control of strain. The ability to engineer phase inhomogeneity with strain lends insight into correlated electron materials in general, and opens opportunities for designing and controlling the phase inhomogeneity of correlated electron materials for micro- and nanoscale device applications.Comment: 14 pages, 4 figures, with supplementary informatio

Enhanced insulin sensitivity associated with provision of mono and polyunsaturated fatty acids in skeletal muscle cells involves counter modulation of PP2A

International audienceAims/Hypothesis: Reduced skeletal muscle insulin sensitivity is a feature associated with sustained exposure to excess saturated fatty acids (SFA), whereas mono and polyunsaturated fatty acids (MUFA and PUFA) not only improve insulin sensitivity but blunt SFA-induced insulin resistance. The mechanisms by which MUFAs and PUFAs institute these favourable changes remain unclear, but may involve stimulating insulin signalling by counter-modulation/repression of protein phosphatase 2A (PP2A). This study investigated the effects of oleic acid (OA; a MUFA), linoleic acid (LOA; a PUFA) and palmitate (PA; a SFA) in cultured myotubes and determined whether changes in insulin signalling can be attributed to PP2A regulation. Principal Findings: We treated cultured skeletal myotubes with unsaturated and saturated fatty acids and evaluated insulin signalling, phosphorylation and methylation status of the catalytic subunit of PP2A. Unlike PA, sustained incubation of rat or human myotubes with OA or LOA significantly enhanced Akt-and ERK1/2-directed insulin signalling. This was not due to heightened upstream IRS1 or PI3K signalling nor to changes in expression of proteins involved in proximal insulin signalling, but was associated with reduced dephosphorylation/inactivation of Akt and ERK1/2. Consistent with this, PA reduced PP2Ac demethylation and tyrosine 307 phosphorylation-events associated with PP2A activation. In contrast, OA and LOA strongly opposed these PA-induced changes in PP2Ac thus exerting a repressive effect on PP2A.Conclusions/Interpretation: Beneficial gains in insulin sensitivity and the ability of unsaturated fatty acids to oppose palmitate-induced insulin resistance in muscle cells may partly be accounted for by counter-modulation of PP2A