Dexmedetomidine Prevents Lipopolysaccharide-Induced MicroRNA Expression in the Adult Rat Brain

During surgery or infection, peripheral inflammation can lead to neuroinflammation, which is associated with cognitive impairment, neurodegeneration, and several neurodegenerative diseases. Dexmedetomidine, an α-2-adrenoceptor agonist, is known to exert anti-inflammatory and neuroprotective properties and reduces the incidence of postoperative cognitive impairments. However, on the whole the molecular mechanisms are poorly understood. This study aims to explore whether dexmedetomidine influences microRNAs (miRNAs) in a rat model of lipopolysaccharide (LPS)-induced neuroinflammation. Adult Wistar rats were injected with 1 mg/kg LPS intraperitoneal (i.p.) in the presence or absence of 5 µg/kg dexmedetomidine. After 6 h, 24 h, and 7 days, gene expressions of interleukin 1-β (IL1-β), tumor necrosis factor-α (TNF-α), and microRNA expressions of miR 124, 132, 134, and 155 were measured in the hippocampus, cortex, and plasma. Dexmedetomidine decreased the LPS-induced neuroinflammation in the hippocampus and cortex via significant reduction of the IL1-β and TNF-α gene expressions after 24 h. Moreover, the LPS-mediated increased expressions of miR 124, 132, 134, and 155 were significantly decreased after dexmedetomidine treatment in both brain regions. In plasma, dexmedetomidine significantly reduced LPS- induced miR 155 after 6 h. Furthermore, there is evidence that miR 132 and 134 may be suitable as potential biomarkers for the detection of neuroinflammation. View Full-Tex

Quantitative single-molecule microscopy reveals that CENP-A(Cnp1) deposition occurs during G2 in fission yeast

The inheritance of the histone H3 variant CENP-A in nucleosomes at centromeres following DNA replication is mediated by an epigenetic mechanism. To understand the process of epigenetic inheritance, or propagation of histones and histone variants, as nucleosomes are disassembled and reassembled in living eukaryotic cells, we have explored the feasibility of exploiting photo-activated localization microscopy (PALM). PALM of single molecules in living cells has the potential to reveal new concepts in cell biology, providing insights into stochastic variation in cellular states. However, thus far, its use has been limited to studies in bacteria or to processes occurring near the surface of eukaryotic cells. With PALM, one literally observes and 'counts' individual molecules in cells one-by-one and this allows the recording of images with a resolution higher than that determined by the diffraction of light (the so-called super-resolution microscopy). Here, we investigate the use of different fluorophores and develop procedures to count the centromere-specific histone H3 variant CENP-A(Cnp1) with single-molecule sensitivity in fission yeast (Schizosaccharomyces pombe). The results obtained are validated by and compared with ChIP-seq analyses. Using this approach, CENP-A(Cnp1) levels at fission yeast (S. pombe) centromeres were followed as they change during the cell cycle. Our measurements show that CENP-A(Cnp1) is deposited solely during the G2 phase of the cell cycle

Spectrally red-shifted fluorescent fiducial markers for optimal drift correction in localization microscopy

Precise drift correction is crucial for every single-molecule localization-based microscopy experiment. We evaluate commonly used fiducial markers such as gold nanoparticles, TetraSpeck microspheres, FluoSpheres and nanodiamonds. We introduce spectrally red-shifted fluorescent particles as optimal fiducial markers. Our concept exploits exciting the fluorescent particles at low efficiency far away from their absorption maximum. A fluorescent particle that is covered by a multitude of dyes will nevertheless yield a bright fiducial signal. This represents a simple yet powerful approach to alleviate common problems in drift corrections caused by photobleaching, sudden signal intensity changes or saturation effects of fiducial markers. We adapt our approach for PALM, sptPALM and DNA-PAINT experiments and demonstrate its simple use for varying imaging conditions in different spectral channels

Dexmedetomidine Restores Autophagic Flux, Modulates Associated microRNAs and the Cholinergic Anti-inflammatory Pathway upon LPS-Treatment in Rats

Infections and perioperative stress can lead to neuroinflammation, which in turn is linked to cognitive impairments such as postoperative delirium or postoperative cognitive dysfunctions. The alpha 2-adrenoceptor agonist dexmedetomidine (DEX) prevents cognitive impairments and has organo-protective and anti-inflammatory properties. Macroautophagy (autophagy) regulates many biological processes, but its role in DEX-mediated anti-inflammation and the underlying mechanism of DEX remains largely unclear. We were interested how a pretreatment with DEX protects against lipopolysaccharide (LPS)-induced inflammation in adult male Wistar rats. We used Western blot and activity assays to study how DEX modulated autophagy- and apoptosis-associated proteins as well as molecules of the cholinergic anti-inflammatory pathway, and qPCR to analyse the expression of autophagy and inflammation-associated microRNAs (miRNA) in the spleen, cortex and hippocampus at different time points (6 h, 24 h, 7 d). We showed that a DEX pretreatment prevents LPS-induced impairments in autophagic flux and attenuates the LPS-induced increase in the apoptosis-associated protein cleaved poly(ADP-ribose)-polymerase (PARP) in the spleen. Both, DEX and LPS altered miRNA expression and molecules of the cholinergic anti-inflammatory pathway in the spleen and brain. While only a certain set of miRNAs was up- and/or downregulated by LPS in each tissue, which was prevented or attenuated by a DEX pretreatment in the spleen and hippocampus, all miRNAs were up- and/or downregulated by DEX itself - independent of whether or not they were altered by LPS. Our results indicate that the organo-protective effect of DEX may be mediated by autophagy, possibly by acting on associated miRNAs, and the cholinergic anti-inflammatory pathway

Path Integral Approach to the Scattering Theory of Quantum Transport

The scattering theory of quantum transport relates transport properties of disordered mesoscopic conductors to their transfer matrix \bbox{T}. We introduce a novel approach to the statistics of transport quantities which expresses the probability distribution of \bbox{T} as a path integral. The path integal is derived for a model of conductors with broken time reversal invariance in arbitrary dimensions. It is applied to the Dorokhov-Mello-Pereyra-Kumar (DMPK) equation which describes quasi-one-dimensional wires. We use the equivalent channel model whose probability distribution for the eigenvalues of \bbox{TT}^{\dagger} is equivalent to the DMPK equation independent of the values of the forward scattering mean free paths. We find that infinitely strong forward scattering corresponds to diffusion on the coset space of the transfer matrix group. It is shown that the saddle point of the path integral corresponds to ballistic conductors with large conductances. We solve the saddle point equation and recover random matrix theory from the saddle point approximation to the path integral.Comment: REVTEX, 9 pages, no figure

Fokker-Planck description of the transfer matrix limiting distribution in the scattering approach to quantum transport

The scattering approach to quantum transport through a disordered quasi-one-dimensional conductor in the insulating regime is discussed in terms of its transfer matrix \bbox{T}. A model of $N$ one-dimensional wires which are coupled by random hopping matrix elements is compared with the transfer matrix model of Mello and Tomsovic. We derive and discuss the complete Fokker-Planck equation which describes the evolution of the probability distribution of \bbox{TT}^{\dagger} with system length in the insulating regime. It is demonstrated that the eigenvalues of \ln\bbox{TT}^{\dagger} have a multivariate Gaussian limiting probability distribution. The parameters of the distribution are expressed in terms of averages over the stationary distribution of the eigenvectors of \bbox{TT}^{\dagger}. We compare the general form of the limiting distribution with results of random matrix theory and the Dorokhov-Mello-Pereyra-Kumar equation.Comment: 25 pages, revtex, no figure

Theory of anyon excitons: Relation to excitons of nu=1/3 and nu=2/3 incompressible liquids

Elementary excitations of incompressible quantum liquids (IQL's) are anyons, i.e., quasiparticles carrying fractional charges and obeying fractional statistics. To find out how the properties of these quasiparticles manifest themselves in the optical spectra, we have developed the anyon exciton model (AEM) and compared the results with the finite-size data for excitons of nu=1/3 and nu=2/3 IQL's. The model considers an exciton as a neutral composite consisting of three quasielectrons and a single hole. The AEM works well when the separation between electron and hole confinement planes, h, is larger than the magnetic length l. In the framework of the AEM an exciton possesses momentum k and two internal quantum numbers, one of which can be chosen as the angular momentum, L, of the k=0 state. Existence of the internal degrees of freedom results in the multiple branch energy spectrum, crater-like electron density shape and 120 degrees density correlations for k=0 excitons, and the splitting of the electron shell into bunches for non-zero k excitons. For h larger than 2l the bottom states obey the superselection rule L=3m (m are integers starting from 2), all of them are hard core states. For h nearly 2l there is one-to-one correspondence between the low-energy spectra found for the AEM and the many- electron exciton spectra of the nu=2/3 IQL, whereas some states are absent from the many-electron spectra of the nu=1/3 IQL. We argue that this striking difference in the spectra originates from the different populational statistics of the quasielectrons of charge conjugate IQL's and show that the proper account of the statistical requirements eliminates excessive states from the spectrum. Apparently, this phenomenon is the first manifestation of the exclusion statistics in the anyon bound states.Comment: 26 pages with 9 figures, typos correcte

Three-Dimensional, Tomographic Super-Resolution Fluorescence Imaging of Serially Sectioned Thick Samples

Three-dimensional fluorescence imaging of thick tissue samples with near-molecular resolution remains a fundamental challenge in the life sciences. To tackle this, we developed tomoSTORM, an approach combining single-molecule localization-based super-resolution microscopy with array tomography of structurally intact brain tissue. Consecutive sections organized in a ribbon were serially imaged with a lateral resolution of 28 nm and an axial resolution of 40 nm in tissue volumes of up to 50 µm×50 µm×2.5 µm. Using targeted expression of membrane bound (m)GFP and immunohistochemistry at the calyx of Held, a model synapse for central glutamatergic neurotransmission, we delineated the course of the membrane and fine-structure of mitochondria. This method allows multiplexed super-resolution imaging in large tissue volumes with a resolution three orders of magnitude better than confocal microscopy

Boolean analysis reveals systematic interactions among low-abundance species in the human gut microbiome

The analysis of microbiome compositions in the human gut has gained increasing interest due to the broader availability of data and functional databases and substantial progress in data analysis methods, but also due to the high relevance of the microbiome in human health and disease. While most analyses infer interactions among highly abundant species, the large number of low-abundance species has received less attention. Here we present a novel analysis method based on Boolean operations applied to microbial co-occurrence patterns. We calibrate our approach with simulated data based on a dynamical Boolean network model from which we interpret the statistics of attractor states as a theoretical proxy for microbiome composition. We show that for given fractions of synergistic and competitive interactions in the model our Boolean abundance analysis can reliably detect these interactions. Analyzing a novel data set of 822 microbiome compositions of the human gut, we find a large number of highly significant synergistic interactions among these low-abundance species, forming a connected network, and a few isolated competitive interactions