17 research outputs found
Multi-messenger observations of a binary neutron star merger
On 2017 August 17 a binary neutron star coalescence candidate (later designated GW170817) with merger time 12:41:04 UTC was observed through gravitational waves by the Advanced LIGO and Advanced Virgo detectors. The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray burst (GRB 170817A) with a time delay of ~1.7 s with respect to the merger time. From the gravitational-wave signal, the source was initially localized to a sky region of 31 deg2 at a luminosity distance of 40+8-8 Mpc and with component masses consistent with neutron stars. The component masses were later measured to be in the range 0.86 to 2.26 Mo. An extensive observing campaign was launched across the electromagnetic spectrum leading to the discovery of a bright optical transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC 4993 (at ~40 Mpc) less than 11 hours after the merger by the One- Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The optical transient was independently detected by multiple teams within an hour. Subsequent observations targeted the object and its environment. Early ultraviolet observations revealed a blue transient that faded within 48 hours. Optical and infrared observations showed a redward evolution over ~10 days. Following early non-detections, X-ray and radio emission were discovered at the transientâs position ~9 and ~16 days, respectively, after the merger. Both the X-ray and radio emission likely arise from a physical process that is distinct from the one that generates the UV/optical/near-infrared emission. No ultra-high-energy gamma-rays and no neutrino candidates consistent with the source were found in follow-up searches. These observations support the hypothesis that GW170817 was produced by the merger of two neutron stars in NGC4993 followed by a short gamma-ray burst (GRB 170817A) and a kilonova/macronova powered by the radioactive decay of r-process nuclei synthesized in the ejecta
Multi-messenger Observations of a Binary Neutron Star Merger
On 2017 August 17 a binary neutron star coalescence candidate (later
designated GW170817) with merger time 12:41:04 UTC was observed through
gravitational waves by the Advanced LIGO and Advanced Virgo detectors.
The Fermi Gamma-ray Burst Monitor independently detected a gamma-ray
burst (GRB 170817A) with a time delay of ⌠1.7 {{s}} with respect to
the merger time. From the gravitational-wave signal, the source was
initially localized to a sky region of 31 deg2 at a
luminosity distance of {40}-8+8 Mpc and with
component masses consistent with neutron stars. The component masses
were later measured to be in the range 0.86 to 2.26 {M}ÈŻ
. An extensive observing campaign was launched across the
electromagnetic spectrum leading to the discovery of a bright optical
transient (SSS17a, now with the IAU identification of AT 2017gfo) in NGC
4993 (at ⌠40 {{Mpc}}) less than 11 hours after the merger by the
One-Meter, Two Hemisphere (1M2H) team using the 1 m Swope Telescope. The
optical transient was independently detected by multiple teams within an
hour. Subsequent observations targeted the object and its environment.
Early ultraviolet observations revealed a blue transient that faded
within 48 hours. Optical and infrared observations showed a redward
evolution over âŒ10 days. Following early non-detections, X-ray and
radio emission were discovered at the transientâs position ⌠9
and ⌠16 days, respectively, after the merger. Both the X-ray and
radio emission likely arise from a physical process that is distinct
from the one that generates the UV/optical/near-infrared emission. No
ultra-high-energy gamma-rays and no neutrino candidates consistent with
the source were found in follow-up searches. These observations support
the hypothesis that GW170817 was produced by the merger of two neutron
stars in NGC 4993 followed by a short gamma-ray burst (GRB 170817A) and
a kilonova/macronova powered by the radioactive decay of r-process
nuclei synthesized in the ejecta.</p
Proton MR spectroscopy in Connatal Pelizaeus-Merzbacher disease
In questo articolo vengono discussi gli aspetti clinici , evolutivi, genetici e neuroradiologici della malattia di Pelizaeus- Merzbacher, una sindrome dismielinizzante ad esordio frequentemente neonatale ed in prima infanzia.Background. Pelizaeus-Merzbacher disease (PMD) is a rare dysmyelinating disorder characterised by early pendular nystagmus, often rotatory and muscular hypotonia with subsequent ataxia, spasticity and mental retardation. Various point mutations or duplications in the PLP gene on the X chromosome are responsible for PMD in the majority of patients. Autosomal recessive inheritance, particularly in the connatal form, cannot be excluded. Three different forms of the disease have been identified based on their onset, progression and severity of myelin pathology indicated by MRI features.
Objective. To determine if MR spectroscopy is useful in the diagnosis of the connatal form of PMD. Materials and methods. Proton MR spectroscopy was performed on two children with connatal PMD. Results. Our patients showed a markedly decreased peak of Cho. This alteration is well represented by quantitative analysis of the NAA-to-Cho ratio, which is the most important ratio affected. A significant decrease of the Cho-to-Cr ratio is also present. In the connatal form of PMD, global lack of myelination may be relevant, as demonstrated by a significant Cho peak reduction.
Conclusions. Proton MR spectroscopy may be of diagnostic value in metabolic and destructive disorders of the brain. A greater number of patients with connatal PMD is needed in order to elucidate the significance of reduction of the Cho peak
Heritability of amygdala reactivity to angry faces and its replicable association with the schizophrenia risk locus ofmiR-137
Background: Among healthy participants, the interindividual variability of brain response to facial emotions is associated with genetic variation, including common risk variants for schizophrenia, a heritable brain disorder characterized by anomalies in emotion processing. We aimed to identify genetic variants associated with heritable brain activity during processing of facial emotions among healthy participants and to explore the impact of these identified variants among patients with schizophrenia. Methods: We conducted a data-driven stepwise study including samples of healthy twins, unrelated healthy participants and patients with schizophrenia. Participants approached or avoided pictures of faces with negative emotional valence during functional magnetic resonance imaging (fMRI). Results: We investigated 3 samples of healthy participants - including 28 healthy twin pairs, 289 unrelated healthy participants (genome-wide association study [GWAS] discovery sample) and 90 unrelated healthy participants (replication sample) - and 1 sample of 48 patients with schizophrenia. Among healthy twins, we identified the amygdala as the brain region with the highest heritability during processing of angry faces (heritability estimate 0.54, p < 0.001). Subsequent GWAS in both discovery and replication samples of healthy non-twins indicated that amygdala activity was associated with a polymorphism in the miR-137 locus (rs1198575), a micro-RNA strongly involved in risk for schizophrenia. A significant effect in the same direction was found among patients with schizophrenia (p = 0.03). Limitations: The limited sample size available for GWAS analyses may require further replication of results. Conclusion: Our data-driven approach shows preliminary evidence that amygdala activity, as evaluated with our task, is heritable. Our genetic associations preliminarily suggest a role for miR-137 in brain activity during explicit processing of facial emotions among healthy participants and patients with schizophrenia, pointing to the amygdala as a brain region whose activity is related to miR-137
Grey Matter Volume Patterns in Thalamic Nuclei are Associated with Familial Risk for Schizophrenia
Previous evidence suggests reduced thalamic grey matter volume (GMV) in patients with schizophrenia (SCZ).
However, it is not considered an intermediate phenotype for schizophrenia, possibly because previous studies
did not assess the contribution of individual thalamic nuclei and employed univariate statistics.Here,we hypothesized
that multivariate statistics would reveal an association of GMV in different thalamic nuclei with familial
risk for schizophrenia.We also hypothesized that accounting for the heterogeneity of thalamic GMV in healthy
controls would improve the detection of subjects at familial risk for the disorder.
We acquired MRI scans for 96 clinically stable SCZ, 55 non-affected siblings of patients with schizophrenia (SIB),
and 249 HC. The thalamus was parceled into seven regions of interest (ROIs). After a canonical univariate analysis,
we used GMV estimates of thalamic ROIs, together with total thalamic GMV and premorbid intelligence, as
features in Random Forests to classify HC, SIB, and SCZ. Then, we computed aMisclassification Index for each individual
and tested the improvement in SIB detection after excluding a subsample of HCmisclassified as patients.
Random Forests discriminated SCZ from HC (accuracy = 81%) and SIB from HC (accuracy = 75%). Left
anteromedial thalamic volumeswere significantly associatedwith bothmultivariate classifications (p b 0.05). Excluding
HCmisclassified as SCZ improved greatly HC vs. SIB classification (Cohen's d=1.39). These findings suggest
that multivariate statistics identify a familial background associated with thalamic GMV reduction in SCZ.
They also suggest the relevance of inter-individual variability of GMV patterns for the discrimination of individuals
at familial risk for the disorder
Thalamic connectivity measured with fMRI is associated with a polygenic index predicting thalamo-prefrontal gene co-expression
The functional connectivity between thalamic medio-dorsal nucleus (MD) and cortical regions, especially the dorsolateral prefrontal cortex (DLPFC), is implicated in attentional processing and is anomalous in schizophrenia, a brain disease associated with polygenic risk and attentional deficits. However, the molecular and genetic underpinnings of thalamic connectivity anomalies are unclear. Given that gene co-expression across brain areas promotes synchronous interregional activity, our aim was to investigate whether coordinated expression of genes relevant to schizophrenia in MD and DLPFC may reflect thalamic connectivity anomalies in an attention-related network including the DLPFC. With this aim, we identified in datasets of post-mortem prefrontal mRNA expression from healthy controls a gene module with robust overrepresentation of genes with coordinated MD-DLPFC expression and enriched for schizophrenia genes according to the largest genome-wide association study to date. To link this gene cluster with imaging phenotypes, we computed a Polygenic Co-Expression Index (PCI) combining single-nucleotide polymorphisms predicting module co-expression. Finally, we investigated the association between PCI and thalamic functional connectivity during attention through fMRI Independent Component Analysis in 265 healthy participants. We found that PCI was positively associated with connectivity strength of a thalamic region overlapping with the MD within an attention brain circuit. These findings identify a novel association between schizophrenia-related genes and thalamic functional connectivity. Furthermore, they highlight the association between gene expression co-regulation and brain connectivity, such that genes with coordinated MD-DLPFC expression are associated with coordinated activity between the same brain regions. We suggest that gene co-expression is a plausible mechanism underlying biological phenotypes of schizophrenia
The interaction between cannabis use and a CB1-related polygenic co-expression index modulates dorsolateral prefrontal activity during working memory processing
Convergent findings indicate that cannabis use and variation in the cannabinoid CB1 receptor coding gene (CNR1) modulate prefrontal function during working memory (WM). Other results also suggest that cannabis modifies the physiological relationship between genetically induced expression of CNR1 and prefrontal WM processing. However, it is possible that cannabis exerts its modifying effect on prefrontal physiology by interacting with complex molecular ensembles co-regulated with CB1. Since co-regulated genes are likely co-expressed, we investigated how genetically predicted co-expression of a molecular network including CNR1 interacts with cannabis use in modulating WM processing in humans. Using post-mortem human prefrontal data, we first computed a polygenic score (CNR1-PCI), combining the effects of single nucleotide polymorphisms (SNPs) on co-expression of a cohesive gene set including CNR1, and positively correlated with such co-expression. Then, in an in vivo study, we computed CNR1-PCI in 88 cannabis users and 147 non-users and investigated its interaction with cannabis use on brain activity during WM. Results revealed an interaction between cannabis use and CNR1-PCI in the dorsolateral prefrontal cortex (DLPFC), with a positive relationship between CNR1-PCI and DLPFC activity in cannabis users and a negative relationship in non-users. Furthermore, DLPFC activity in cannabis users was positively correlated with the frequency of cannabis use. Taken together, our results suggest that co-expression of a CNR1-related network predicts WM-related prefrontal activation as a function of cannabis use. Furthermore, they offer novel insights into the biological mechanisms associated with the use of cannabis
Search for intermediate mass black hole binaries in the first observing run of Advanced LIGO
International audienceDuring their first observational run, the two Advanced LIGO detectors attained an unprecedented sensitivity, resulting in the first direct detections of gravitational-wave signals produced by stellar-mass binary black hole systems. This paper reports on an all-sky search for gravitational waves (GWs) from merging intermediate mass black hole binaries (IMBHBs). The combined results from two independent search techniques were used in this study: the first employs a matched-filter algorithm that uses a bank of filters covering the GW signal parameter space, while the second is a generic search for GW transients (bursts). No GWs from IMBHBs were detected; therefore, we constrain the rate of several classes of IMBHB mergers. The most stringent limit is obtained for black holes of individual mass 100ââMâ, with spins aligned with the binary orbital angular momentum. For such systems, the merger rate is constrained to be less than 0.93ââGpcâ3âyrâ1 in comoving units at the 90%Â confidence level, an improvement of nearly 2 orders of magnitude over previous upper limits
First low-frequency Einstein@Home all-sky search for continuous gravitational waves in Advanced LIGO data
International audienceWe report results of a deep all-sky search for periodic gravitational waves from isolated neutron stars in data from the first Advanced LIGO observing run. This search investigates the low frequency range of Advanced LIGO data, between 20 and 100Â Hz, much of which was not explored in initial LIGO. The search was made possible by the computing power provided by the volunteers of the Einstein@Home project. We find no significant signal candidate and set the most stringent upper limits to date on the amplitude of gravitational wave signals from the target population, corresponding to a sensitivity depth of 48.7ââ[1/Hz]. At the frequency of best strain sensitivity, near 100Â Hz, we set 90% confidence upper limits of 1.8Ă10-25. At the low end of our frequency range, 20Â Hz, we achieve upper limits of 3.9Ă10-24. At 55Â Hz we can exclude sources with ellipticities greater than 10-5 within 100Â pc of Earth with fiducial value of the principal moment of inertia of 1038ââkgâm2