1,841 research outputs found
Growth Factors Regulate Expression of Mineral Associated Genes in Cementoblasts
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141778/1/jper1591.pd
Correction: An intrinsically stretchable humidity sensor based on anti-drying, self-healing and transparent organohydrogels
Correction for âAn intrinsically stretchable humidity sensor based on anti-drying, self-healing and transparent organohydrogelsâ by Jin Wu et al., Mater. Horiz., 2019, 6, 595â603, DOI: 10.1039/C8MH01160E
Ligand substitution reactions of a phenolic quinolyl hydrazone; oxidovanadium (IV) complexes
<p>Abstract</p> <p>Background</p> <p>Quinoline ring has therapeutic and biological activities. Quinolyl hydrazones constitute a class of excellent chelating agents. Recently, the physiological and biological activities of quinolyl hydrazones arise from their tendency to form metal chelates with transition metal ions. In this context, we have aimed to study the competency effect of a phenolic quinolyl hydrazone (H<sub>2</sub>L; primary ligand) with some auxiliary ligands (Tmen, Phen or Oxine; secondary ligands) towards oxidovanadium (IV) ions.</p> <p>Results</p> <p>Mono- and binuclear oxidovanadium (IV) - complexes were obtained from the reaction of a phenolic quinolyl hydrazone with oxidovanadium (IV)- ion in absence and presence of N,N,N',N'- tetramethylethylenediamine (Tmen), 1,10-phenanthroline (Phen) or 8-hydroxyquinoline (Oxine). The phenolic quinolyl hydrazone ligand behaves as monobasic bidentate (NO- donor with O- bridging). All the obtained complexes have the preferable octahedral geometry except the oxinato complex (<b>2</b>) which has a square pyramid geometry with no axial interaction; the only homoleptic complex in this study.</p> <p>Conclusion</p> <p>The ligand exchange (substitution/replacement) reactions reflect the strong competency power of the auxiliary aromatic ligands (Phen/Oxine) compared to the phenolic quinolyl hydrazone (H<sub>2</sub>L) towards oxidovanadium (IV) ion; (complexes <b>2 </b>and <b>3</b>). By contrast, in case of the more flexible aliphatic competitor (Tmen), an adduct was obtained (<b>4</b>). The obtained complexes reflect the strength of the ligand field towards the oxidovanadium (IV)- ion; Oxine or Phen >> phenolic hydrazone (H<sub>2</sub>L) > Tmen.</p
Growth Factors Regulate Expression of OsteoblastâAssociated Genes
Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/141995/1/jper1345.pd
Neuroinflammation, Mast Cells, and Glia: Dangerous Liaisons
The perspective of neuroinflammation as an epiphenomenon following neuron damage is being replaced by the awareness of glia and their importance in neural functions and disorders. Systemic inflammation generates signals that communicate with the brain and leads to changes in metabolism and behavior, with microglia assuming a pro-inflammatory phenotype. Identification of potential peripheral-to-central cellular links is thus a critical step in designing effective therapeutics. Mast cells may fulfill such a role. These resident immune cells are found close to and within peripheral nerves and in brain parenchyma/meninges, where they exercise a key role in orchestrating the inflammatory process from initiation through chronic activation. Mast cells and glia engage in crosstalk that contributes to accelerate disease progression; such interactions become exaggerated with aging and increased cell sensitivity to stress. Emerging evidence for oligodendrocytes, independent of myelin and support of axonal integrity, points to their having strong immune functions, innate immune receptor expression, and production/response to chemokines and cytokines that modulate immune responses in the central nervous system while engaging in crosstalk with microglia and astrocytes. In this review, we summarize the findings related to our understanding of the biology and cellular signaling mechanisms of neuroinflammation, with emphasis on mast cell-glia interactions
Quantifying MRI frequency shifts due to structures with anisotropic magnetic susceptibility using pyrolytic graphite sheet
Magnetic susceptibility is an important source of contrast in magnetic resonance imaging (MRI), with spatial variations in the susceptibility of tissue affecting both the magnitude and phase of the measured signals. This contrast has generally been interpreted by assuming that tissues have isotropic magnetic susceptibility, but recent work has shown that the anisotropic magnetic susceptibility of ordered biological tissues, such as myelinated nerves and cardiac muscle fibers, gives rise to unexpected image contrast. This behavior occurs because the pattern of field variation generated by microstructural elements formed from material of anisotropic susceptibility can be very different from that predicted by modelling the effects in terms of isotropic susceptibility. In MR images of tissue, such elements are manifested at a sub-voxel length-scale, so the patterns of field variation that they generate cannot be directly visualized. Here, we used pyrolytic graphite sheet which has a large magnetic susceptibility anisotropy to form structures of known geometry with sizes large enough that the pattern of field variation could be mapped directly using MRI. This allowed direct validation of theoretical expressions describing the pattern of field variation from anisotropic structures with biologically relevant shapes (slabs, spherical shells and cylindrical shells)
Evolution of nuclear structure in neutron-rich odd-Zn isotopes and isomers
Collinear laser spectroscopy was performed on Zn (Z=30) isotopes at ISOLDE, CERN. The study of hyperfine spectra of nuclei across the Zn isotopic chain, N=33â49, allowed the measurement of nuclear spins for the ground and isomeric states in odd-A neutron-rich nuclei up to N=50. Exactly one long-lived (>10 ms) isomeric state has been established in each 69â79Zn isotope. The nuclear magnetic dipole moments and spectroscopic quadrupole moments are well reproduced by large-scale shellâmodel calculations in the f5pg9 and fpg9d5 model spaces, thus establishing the dominant term in their wave function. The magnetic moment of the intruder IÏ=1/2+ isomer in 79Zn is reproduced only if the Îœs1/2 orbital is added to the valence space, as realized in the recently developed PFSDG-U interaction. The spin and moments of the low-lying isomeric state in 73Zn suggest a strong onset of deformation at N=43, while the progression towards 79Zn points to the stability of the Z=28 and N=50 shell gaps, supporting the magicity of 78Ni
Observation of a ppb mass threshoud enhancement in \psi^\prime\to\pi^+\pi^-J/\psi(J/\psi\to\gamma p\bar{p}) decay
The decay channel
is studied using a sample of events collected
by the BESIII experiment at BEPCII. A strong enhancement at threshold is
observed in the invariant mass spectrum. The enhancement can be fit
with an -wave Breit-Wigner resonance function with a resulting peak mass of
and a
narrow width that is at the 90% confidence level.
These results are consistent with published BESII results. These mass and width
values do not match with those of any known meson resonance.Comment: 5 pages, 3 figures, submitted to Chinese Physics
Inferring transcriptional compensation interactions in yeast via stepwise structure equation modeling
<p>Abstract</p> <p>Background</p> <p>With the abundant information produced by microarray technology, various approaches have been proposed to infer transcriptional regulatory networks. However, few approaches have studied subtle and indirect interaction such as genetic compensation, the existence of which is widely recognized although its mechanism has yet to be clarified. Furthermore, when inferring gene networks most models include only observed variables whereas latent factors, such as proteins and mRNA degradation that are not measured by microarrays, do participate in networks in reality.</p> <p>Results</p> <p>Motivated by inferring transcriptional compensation (TC) interactions in yeast, a stepwise structural equation modeling algorithm (SSEM) is developed. In addition to observed variables, SSEM also incorporates hidden variables to capture interactions (or regulations) from latent factors. Simulated gene networks are used to determine with which of six possible model selection criteria (MSC) SSEM works best. SSEM with Bayesian information criterion (BIC) results in the highest true positive rates, the largest percentage of correctly predicted interactions from all existing interactions, and the highest true negative (non-existing interactions) rates. Next, we apply SSEM using real microarray data to infer TC interactions among (1) small groups of genes that are synthetic sick or lethal (SSL) to SGS1, and (2) a group of SSL pairs of 51 yeast genes involved in DNA synthesis and repair that are of interest. For (1), SSEM with BIC is shown to outperform three Bayesian network algorithms and a multivariate autoregressive model, checked against the results of qRT-PCR experiments. The predictions for (2) are shown to coincide with several known pathways of Sgs1 and its partners that are involved in DNA replication, recombination and repair. In addition, experimentally testable interactions of Rad27 are predicted.</p> <p>Conclusion</p> <p>SSEM is a useful tool for inferring genetic networks, and the results reinforce the possibility of predicting pathways of protein complexes via genetic interactions.</p
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