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The 23Al(p, γ)24Si stellar reaction rate has a significant impact on the light-curve emitted in X-ray bursts. Theoretical calculations show that the reaction rate is mainly determined by the properties of direct capture as well as low-lying 2+ states and a possible 4+ state in 24Si. Currently, there is little experimental information on the properties of these states.
In this proceeding we will present a new experimental study to investigate this reaction, using the surrogate reaction 23Al(d,n) at 47 AMeV at the National Superconducting Cyclotron Laboratory (NSCL). We will discuss our new experimental setup which allows us to use full kinematics employing the Gamma-Ray Energy Tracking In-beam Nuclear Array (GRETINA) to detect the γ-rays following the de-excitation of excited states of the reaction products and the Low Energy Neutron Detector Array (LENDA) to detect the recoiling neutrons. The S800 was used for identification of the 24Si recoils. As a proof of principle to show the feasibility of this concept the Q-value spectrum of 22Mg(d,n)23Al is reconstructed.
We present a measurement of e+e− pair production in central PbAu collisions at 158A GeV/c. As reported earlier, a significant excess of the e+e− pair yield over the expectation from hadron decays is observed. The improved mass resolution of the present data set, recorded with the upgraded CERES experiment at the CERN-SPS, allows for a comparison of the data with different theoretical approaches. The data clearly favor a substantial in-medium broadening of the ρ spectral function over a density-dependent shift of the ρ pole mass. The in-medium broadening model implies that baryon induced interactions are the key mechanism to the observed modifications of the ρ meson at SPS energy.
The adaptor molecule stimulator of IFN genes (STING) is central to production of type I IFNs in response to infection with DNA viruses and to presence of host DNA in the cytosol. Excessive release of type I IFNs through STING-dependent mechanisms has emerged as a central driver of several interferonopathies, including systemic lupus erythematosus (SLE), Aicardi–Goutières syndrome (AGS), and stimulator of IFN genes-associated vasculopathy with onset in infancy (SAVI). The involvement of STING in these diseases points to an unmet need for the development of agents that inhibit STING signaling. Here, we report that endogenously formed nitro-fatty acids can covalently modify STING by nitro-alkylation. These nitro-alkylations inhibit STING palmitoylation, STING signaling, and subsequently, the release of type I IFN in both human and murine cells. Furthermore, treatment with nitro-fatty acids was sufficient to inhibit production of type I IFN in fibroblasts derived from SAVI patients with a gain-of-function mutation in STING. In conclusion, we have identified nitro-fatty acids as endogenously formed inhibitors of STING signaling and propose for these lipids to be considered in the treatment of STING-dependent inflammatory diseases.
PolarCAP – A deep learning approach for first motion polarity classification of earthquake waveforms
(2022)
Highlights
• We present PolarCAP, a deep learning model that can classify the polarity of a waveform with a 98% accuracy.
• The first-motion polarity of seismograms is a useful parameter, but its manual determination can be laborious and imprecise.
• We demonstrate that in several cases the model can assign trace polar-ity more accurately than a human analyst.
Abstract
The polarity of first P-wave arrivals plays a significant role in the effective determination of focal mechanisms specially for smaller earthquakes. Manual estimation of polarities is not only time-consuming but also prone to human errors. This warrants a need for an automated algorithm for first motion polarity determination. We present a deep learning model - PolarCAP that uses an autoencoder architecture to identify first-motion polarities of earth-quake waveforms. PolarCAP is trained in a supervised fashion using more than 130,000 labelled traces from the Italian seismic dataset (INSTANCE) and is cross-validated on 22,000 traces to choose the most optimal set of hyperparameters. We obtain an accuracy of 0.98 on a completely unseen test dataset of almost 33,000 traces. Furthermore, we check the model generalizability by testing it on the datasets provided by previous works and show that our model achieves a higher recall on both positive and negative polarities.
Pertusarialean lichens include more than 300 species belonging to several independent phylogenetic lineages. Only some of these phylogenetic clades have been comprehensively sampled for molecular data, and formally described as genera. Here we present a taxonomic treatment of a group of pertusarialean lichens formerly known as "Pertusaria amara-group", "Monomurata-group", or "Variolaria-group", which includes widespread and well-known taxa such as P. amara, P. albescens, or P. ophthalmiza. We generated a 6-locus data set with 79 OTUs representing 75 species. The distinction of the Variolaria clade is supported and consequently, the resurrection of the genus Lepra is followed. Thirty-five new combinations into Lepra are proposed and the new species Lepra austropacifica is described from mangroves in the South Pacific. Lepra is circumscribed to include species with disciform ascomata, a weakly to non-amyloid hymenial gel, strongly amyloid asci without clear apical amyloid structures, containing 1 or 2, single-layered, thin-walled ascospores. Chlorinated xanthones are not present, but thamnolic and picrolichenic acids occur frequently, as well as orcinol depsides. Seventy-one species are accepted in the genus. Although the distinction of the genus from Pertusaria is strongly supported, the relationships of Lepra remain unresolved and the genus is tentatively placed in Pertusariales incertae sedis.
Oral presentation from 4th International Conference of cGMP Generators, Effectors and Therapeutic Implications ; Regensburg, Germany. 19–21 June 2009 Background: An exaggerated pain sensitivity is the dominant feature of inflammatory and neuropathic pain both in the clinical setting and in experimental animal models. It manifests as pain in response to normally innocuous stimuli (allodynia), increased response to noxious stimuli (hyperalgesia) or spontaneous pain, and can persist long after the initial injury is resolved. Research over the last decades has revealed that several signaling pathways in the spinal cord essentially contribute to the pain sensitization. To test the contribution of cGMP produced by NO-sensitive guanylyl cyclase (NO-GC) to pain sensitization, we investigated the localization of NO-GC in the spinal cord and in dorsal root ganglia, and we characterized the nociceptive behavior of mice deficient in NO-GC (GC-KO mice). Results: We show that NO-GC (β1 subunit) is distinctly expressed in neurons of the mouse spinal cord, while its distribution in dorsal root ganglia is restricted to non-neuronal cells. GC-KO mice exhibited a considerably reduced nociceptive behavior in models of inflammatory or neuropathic pain, but their responses to acute pain were not impaired. Moreover, GC-KO mice failed to develop pain sensitization induced by spinal administration of drugs releasing NO. Surprisingly, during spinal nociceptive processing cGMP produced by NO-GC may activate signaling pathways different from cGMP-dependent protein kinase I (cGKI), while cGKI can be activated by natriuretic peptide receptor-B (NPR-B) dependent cGMP production. Conclusion: Taken together, our results provide evidence that NO-GC has a dominant role in the development of exaggerated pain sensitivity during inflammatory and neuropathic pain. Furthermore, beside the NO-mediated cGMP synthesis, cGMP produced by NPR-B contributes to pain sensitization by activation of cGKI.
Nontarget screening exhibits a seasonal cycle of PM2.5 organic aerosol composition in Beijing
(2022)
The molecular composition of atmospheric particulate matter (PM) in the urban environment is complex, and it remains a challenge to identify its sources and formation pathways. Here, we report the seasonal variation of the molecular composition of organic aerosols (OA), based on 172 PM2.5 filter samples collected in Beijing, China, from February 2018 to March 2019. We applied a hierarchical cluster analysis (HCA) on a large nontarget-screening data set and found a strong seasonal difference in the OA chemical composition. Molecular fingerprints of the major compound clusters exhibit a unique molecular pattern in the Van Krevelen-space. We found that summer OA in Beijing features a higher degree of oxidation and a higher proportion of organosulfates (OSs) in comparison to OA during wintertime, which exhibits a high contribution from (nitro-)aromatic compounds. OSs appeared with a high intensity in summer-haze conditions, indicating the importance of anthropogenic enhancement of secondary OA in summer Beijing. Furthermore, we quantified the contribution of the four main compound clusters to total OA using surrogate standards. With this approach, we are able to explain a small fraction of the OA (∼11–14%) monitored by the Time-of-Flight Aerosol Chemical Speciation Monitor (ToF-ACSM). However, we observe a strong correlation between the sum of the quantified clusters and OA measured by the ToF-ACSM, indicating that the identified clusters represent the major variability of OA seasonal cycles. This study highlights the potential of using nontarget screening in combination with HCA for gaining a better understanding of the molecular composition and the origin of OA in the urban environment.
Background: Bipolar disorder is associated with circadian disruption and a high risk of suicidal behavior. In a previous exploratory study of patients with bipolar I disorder, we found that a history of suicide attempts was associated with differences between winter and summer levels of solar insolation. The purpose of this study was to confirm this finding using international data from 42% more collection sites and 25% more countries. Methods: Data analyzed were from 71 prior and new collection sites in 40 countries at a wide range of latitudes. The analysis included 4876 patients with bipolar I disorder, 45% more data than previously analyzed. Of the patients, 1496 (30.7%) had a history of suicide attempt. Solar insolation data, the amount of the sun’s electromagnetic energy striking the surface of the earth, was obtained for each onset location (479 locations in 64 countries). Results: This analysis confirmed the results of the exploratory study with the same best model and slightly better statistical significance. There was a significant inverse association between a history of suicide attempts and the ratio of mean winter insolation to mean summer insolation (mean winter insolation/mean summer insolation). This ratio is largest near the equator which has little change in solar insolation over the year, and smallest near the poles where the winter insolation is very small compared to the summer insolation. Other variables in the model associated with an increased risk of suicide attempts were a history of alcohol or substance abuse, female gender, and younger birth cohort. The winter/summer insolation ratio was also replaced with the ratio of minimum mean monthly insolation to the maximum mean monthly insolation to accommodate insolation patterns in the tropics, and nearly identical results were found. All estimated coefficients were significant at p < 0.01. Conclusion: A large change in solar insolation, both between winter and summer and between the minimum and maximum monthly values, may increase the risk of suicide attempts in bipolar I disorder. With frequent circadian rhythm dysfunction and suicidal behavior in bipolar disorder, greater understanding of the optimal roles of daylight and electric lighting in circadian entrainment is needed.
A point mutation in the Ncr1 signal peptide impairs the development of innate lymphoid cell subsets
(2018)
NKp46 (CD335) is a surface receptor shared by both human and mouse natural killer (NK) cells and innate lymphoid cells (ILCs) that transduces activating signals necessary to eliminate virus-infected cells and tumors. Here, we describe a spontaneous point mutation of cysteine to arginine (C14R) in the signal peptide of the NKp46 protein in congenic Ly5.1 mice and the newly generated NCRB6C14R strain. Ly5.1C14R NK cells expressed similar levels of Ncr1 mRNA as C57BL/6, but showed impaired surface NKp46 and reduced ability to control melanoma tumors in vivo. Expression of the mutant NKp46C14R in 293T cells showed that NKp46 protein trafficking to the cell surface was compromised. Although Ly5.1C14R mice had normal number of NK cells, they showed an increased number of early maturation stage NK cells. CD49a+ILC1s were also increased but these cells lacked the expression of TRAIL. ILC3s that expressed NKp46 were not detectable and were not apparent when examined by T-bet expression. Thus, the C14R mutation reveals that NKp46 is important for NK cell and ILC differentiation, maturation and function.
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.