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Institute
The E-pathway of transmembrane proton transfer has been demonstrated previously to be essential for catalysis by the diheme-containing quinol:fumarate reductase (QFR) of Wolinella succinogenes. Two constituents of this pathway, Glu-C180 and heme b(D) ring C (b(D)-C-) propionate, have been validated experimentally. Here, we identify further constituents of the E-pathway by analysis of molecular dynamics simulations. The redox state of heme groups has a crucial effect on the connectivity patterns of mobile internal water molecules that can transiently support proton transfer from the b(D)-C-propionate to Glu-C180. The short H-bonding paths formed in the reduced states can lead to high proton conduction rates and thus provide a plausible explanation for the required opening of the E-pathway in reduced QFR. We found evidence that the b(D)-C-propionate group is the previously postulated branching point connecting proton transfer to the E-pathway from the quinol-oxidation site via interactions with the heme b(D) ligand His-C44. An essential functional role of His-C44 is supported experimentally by site-directed mutagenesis resulting in its replacement with Glu. Although the H44E variant enzyme retains both heme groups, it is unable to catalyze quinol oxidation. All results obtained are relevant to the QFR enzymes from the human pathogens Campylobacter jejuni and Helicobacter pylori.
Molecular cause and functional impact of altered synaptic lipid signaling due to a prg‐1 gene SNP
(2015)
Loss of plasticity-related gene 1 (PRG-1), which regulates synaptic phospholipid signaling, leads to hyperexcitability via increased glutamate release altering excitation/inhibition (E/I) balance in cortical networks. A recently reported SNP in prg-1 (R345T/mutPRG-1) affects ~5 million European and US citizens in a monoallelic variant. Our studies show that this mutation leads to a loss-of-PRG-1 function at the synapse due to its inability to control lysophosphatidic acid (LPA) levels via a cellular uptake mechanism which appears to depend on proper glycosylation altered by this SNP. PRG-1(+/-) mice, which are animal correlates of human PRG-1(+/mut) carriers, showed an altered cortical network function and stress-related behavioral changes indicating altered resilience against psychiatric disorders. These could be reversed by modulation of phospholipid signaling via pharmacological inhibition of the LPA-synthesizing molecule autotaxin. In line, EEG recordings in a human population-based cohort revealed an E/I balance shift in monoallelic mutPRG-1 carriers and an impaired sensory gating, which is regarded as an endophenotype of stress-related mental disorders. Intervention into bioactive lipid signaling is thus a promising strategy to interfere with glutamate-dependent symptoms in psychiatric diseases.
The experience of pain is mediated by a specialized sensory system, the nociceptive system. There is considerable evidence that the cGMP/cGMP kinase I (cGKI) signaling pathway modulates the nociceptive processing within the spinal cord. However, downstream targets of cGKI in this context have not been identified to date. In this study we investigated whether cysteine-rich protein 2 (CRP2) is a downstream effector of cGKI in the spinal cord and is involved in nociceptive processing. Immunohistochemistry of the mouse spinal cord revealed that CRP2 is expressed in superficial laminae of the dorsal horn. CRP2 is colocalized with cGKI and with markers of primary afferent C fibers. Importantly, the majority of CRP2 mRNA-positive dorsal root ganglion (DRG) neurons express cGKI and CRP2 is phosphorylated in a cGMP-dependent manner. To elucidate the functional role of CRP2 in nociception, we investigated the nociceptive behavior of CRP2-deficient (CRP2-/-) mice. Touch perception and acute thermal nociception were unaltered in CRP2-/- mice. However, CRP2-/- mice showed an increased nociceptive behavior in models of persistent pain as compared to wild type mice. Intrathecal administration of cGKI activating cGMP analogs increased the nociceptive behavior in wild type but not in CRP2-/- mice, indicating that the presence of CRP2 was essential for cGMP/cGKI-mediated nociception. These data indicate that CRP2 is a new downstream effector of cGKI-mediated spinal nociceptive processing and point to an inhibitory role of CRP2 in the generation of inflammatory pain.
Prostaglandin D2 (PGD2) is involved in a variety of physiological and pathophysiological processes, but its role in fever is poorly understood and the data obtained so far are rather controversial. Here we investigated the effects of central PGD2 delivery and of systemic prostaglandin D synthase (PGDS) or cyclooxygenase (COX) inhibition on core body temperature (TC) and on prostaglandin levels in the cerebrospinal fluid (CSF) of rats. Both PGE2 and PGD2 were detectable in CSF samples from control rats (6.2 ± 1.1 and 17.3 ± 3.1 pg/ml, respectively). Lipopolysaccharide (LPS) injection (50 μg i.p.) induced fever during the 5-hour observation period. Five hours after LPS injection, the levels of PGE2 and PGD2 were increased in the CSF about 90-fold (541.0 ± 47.5 pg/ml) and 5-fold (95.4 ± 23.1 pg/ml), respectively. Administration of PGD2 (50 - 500 ng) into the cisterna magna (i.c.m) evoked a delayed fever response in a dose-dependent manner that was accompanied by increased levels of PGE2 in the CSF. RT-PCR analyses revealed that the increased levels of PGE2 after PGD2 administration were not caused by up-regulation of COX-2 or microsomal prostaglandin E synthase 1 (mPGES-1) in the hypothalamus. Interestingly, i.c.m. pretreatment of animals with PGD2 considerably sustained the pyrogenic effects of i.c.m. administered PGE2. Pretreatment with a novel PGDS inhibitor, EDJ300520 (10 – 40 mg/kg p.o.), 1 h prior to the LPS injection impaired the LPS-induced increase of both PGD2 and PGE2 in the CSF and inhibited the fever response. In contrast, administration of EDJ300520 3 h after LPS injection did not ameliorate the LPS-induced fever. Accordingly, the concentration of PGE2 in the CSF was not decreased after EDJ300520 treatment. However, the CSF levels of PGD2 were reduced after administration of a high dose of EDJ300520 (40 mg/kg). We also investigated the effects of antipyretic drugs on the CSF levels of PGE2 and PGD2 during LPS-induced fever. Four antipyretic drugs with different mechanisms of action were used, including ibuprofen (5 - 20 mg/kg), celecoxib (10 - 50 mg/kg), SC560 5 - 20 mg/kg), and paracetamol (50 - 150 mg/kg). Each drug was used in three different doses and was orally administered 3 h after the LPS injection. All drugs were capable to attenuate the LPS-induced fever. The decrease of TC paralleled the reduction of PGE2 levels in the CSF. Of note, there was a tendency to reduced PGD2 levels in the CSF after treatment with the antipyretic drugs. However, only SC560 and the high dose of celecoxib (50 mg/kg) reduced the PGD2 levels significantly. In summary, our experiments underscore the pivotal role of PGE2 as the principal downstream mediator of fever. Moreover, we demonstrate that PGD2 is also involved in the mechanisms underlying fever. Our data suggest that PGD2 exerts an indirect pyrogenic effect by modulating the availability of PGE2 in the CSF. Additional studies are needed to explore the exact mechanism by
Background Synchronous neuronal firing has been discussed as a potential neuronal code. For testing first, if synchronous firing exists, second if it is modulated by the behaviour, and third if it is not by chance, a large set of tools has been developed. However, to test whether synchronous neuronal firing is really involved in information processing one needs a direct comparison of the amount of synchronous firing for different factors like experimental or behavioural conditions. To this end we present an extended version of a previously published method NeuroXidence [1], which tests, based on a bi- and multivariate test design, whether the amount of synchronous firing above the chance level is different for different factors.
Inclusive neutron spectra were measured at 0°, 4°, 8°, 15°, 30°, and 42° from Nb-Nb and Au-Au collisions at 800 MeV/nucleon. A peak that originates from neutron evaporation from the projectile appears in the spectra at angles out to 8°. The shapes and magnitudes of the spectra are compared with those calculated from models of nucleus-nucleus collisions. The differential cross sections for Au-Au collisions are about four times those for Nb-Nb collisions. The predictions of the Vlasov-Uehling-Uhlenbeck (VUU) and QMD theories agree with the angular distributions of the differential cross sections except at small angles; the VUU prediction overestimates the angular distributions from a few degrees to about 20°, whereas the QMD prediction underestimates the angular distributions below 8°. The Firestreak model overestimates the angular distribution for Nb-Nb collisions and underestimates it for Au-Au collisions. Also, the VUU and QMD models agree with the measured double-differential cross sections in more angular and energy regions than the Firestreak and intranuclear cascade models; however, none of the models can account for the peaks at small angles (θ≤15°).
Background: Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls.
Principal findings: In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10−6) and 14 (IGHV1-67 p = 7.9×10−8) which indexed novel susceptibility loci.
Significance: The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.
Mapping cortical brain asymmetry in 17,141 healthy individuals worldwide via the ENIGMA Consortium
(2017)
We measure the inclusive semielectronic decay branching fraction of the D+s meson. A double-tag technique is applied to e+e− annihilation data collected by the BESIII experiment at the BEPCII collider, operating in the center-of-mass energy range 4.178–4.230 GeV. We select positrons fromD+s→Xe+νe with momenta greater than 200 MeV/c and determine the laboratory momentum spectrum, accounting for the effects of detector efficiency and resolution. The total positron yield and semielectronic branching fraction are determined by extrapolating this spectrum below the momentum cutoff. We measure the D+s semielectronic branching fraction to be(6.30±0.13(stat.)±0.09(syst.)±0.04(ext.))%, showing no evidence for unobserved exclusive semielectronic modes. We combine this result with external data taken from literature to determine the ratio of the D+s and D0 semielectronic widths, Γ(D+s→Xe+νe)Γ(D0→Xe+νe)=0.790±0.016(stat.)±0.011(syst.)±0.016(ext.). Our results are consistent with and more precise than previous measurements.
Highlights
• We present the first results of a deep learning model based on a convolutional neural network for earthquake magnitude estimation, using HR-GNSS displacement time series.
• The influence of different dataset configurations, such as station numbers, epicentral distances, signal duration, and earthquake size, were analyzed to figure out how the model can be adapted to various scenarios.
• The model was tested using real data from different regions and magnitudes, resulting in the best cases with 0.09 ≤ RMS ≤ 0.33.
Abstract
High-rate Global Navigation Satellite System (HR-GNSS) data can be highly useful for earthquake analysis as it provides continuous high-frequency measurements of ground motion. This data can be used to analyze diverse parameters related to the seismic source and to assess the potential of an earthquake to prompt strong motions at certain distances and even generate tsunamis. In this work, we present the first results of a deep learning model based on a convolutional neural network for earthquake magnitude estimation, using HR-GNSS displacement time series. The influence of different dataset configurations, such as station numbers, epicentral distances, signal duration, and earthquake size, were analyzed to figure out how the model can be adapted to various scenarios. We explored the potential of the model for global application and compared its performance using both synthetic and real data from different seismogenic regions. The performance of our model at this stage was satisfactory in estimating earthquake magnitude from synthetic data with 0.07 ≤ RMS ≤ 0.11. Comparable results were observed in tests using synthetic data from a different region than the training data, with RMS ≤ 0.15. Furthermore, the model was tested using real data from different regions and magnitudes, resulting in the best cases with 0.09 ≤ RMS ≤ 0.33, provided that the data from a particular group of stations had similar epicentral distance constraints to those used during the model training. The robustness of the DL model can be improved to work independently from the window size of the time series and the number of stations, enabling faster estimation by the model using only near-field data. Overall, this study provides insights for the development of future DL approaches for earthquake magnitude estimation with HR-GNSS data, emphasizing the importance of proper handling and careful data selection for further model improvements.