Aspartoacylase-LacZ Knockin Mice: An Engineered Model of Canavan Disease

Canavan Disease (CD) is a recessive leukodystrophy caused by loss of function mutations in the gene encoding aspartoacylase (ASPA), an oligodendrocyte-enriched enzyme that hydrolyses N-acetylaspartate (NAA) to acetate and aspartate. The neurological phenotypes of different rodent models of CD vary considerably. Here we report on a novel targeted aspa mouse mutant expressing the bacterial β-Galactosidase (lacZ) gene under the control of the aspa regulatory elements. X-Gal staining in known ASPA expression domains confirms the integrity of the modified locus in heterozygous aspa lacZ-knockin (aspalacZ/+) mice. In addition, abundant ASPA expression was detected in Schwann cells. Homozygous (aspalacZ/lacZ) mutants are ASPA-deficient, show CD-like histopathology and moderate neurological impairment with behavioural deficits that are more pronounced in aspalacZ/lacZ males than females. Non-invasive ultrahigh field proton magnetic resonance spectroscopy revealed increased levels of NAA, myo-inositol and taurine in the aspalacZ/lacZ brain. Spongy degeneration was prominent in hippocampus, thalamus, brain stem, and cerebellum, whereas white matter of optic nerve and corpus callosum was spared. Intracellular vacuolisation in astrocytes coincides with axonal swellings in cerebellum and brain stem of aspalacZ/lacZ mutants indicating that astroglia may act as an osmolyte buffer in the aspa-deficient CNS. In summary, the aspalacZ mouse is an accurate model of CD and an important tool to identify novel aspects of its complex pathology

Search for neutral heavy leptons produced in ZZ decays

Weak isosinglet Neutral Heavy Leptons (νm) have been searched for using data collected by the DELPHI detector corresponding to 3.3 × 106 hadronic Z0 decays at LEP1. Four separate searches have been performed, for short-lived νm production giving monojet or acollinear jet topologies, and for long-lived νm giving detectable secondary vertices or calorimeter clusters. No indication of the existence of these particles has been found, leading to an upper limit for the branching ratio BR(Z0 → νmν̄) of about 1.3 × 10-6 at 95% confidence level for νm masses between 3.5 and 50 GeV/c2. Outside this range the limit weakens rapidly with the νm mass. The results are also interpreted in terms of limits for the single production of excited neutrinos. © Springer-Verlag 1997

Potential of Core-Collapse Supernova Neutrino Detection at JUNO

JUNO is an underground neutrino observatory under construction in Jiangmen, China. It uses 20kton liquid scintillator as target, which enables it to detect supernova burst neutrinos of a large statistics for the next galactic core-collapse supernova (CCSN) and also pre-supernova neutrinos from the nearby CCSN progenitors. All flavors of supernova burst neutrinos can be detected by JUNO via several interaction channels, including inverse beta decay, elastic scattering on electron and proton, interactions on C12 nuclei, etc. This retains the possibility for JUNO to reconstruct the energy spectra of supernova burst neutrinos of all flavors. The real time monitoring systems based on FPGA and DAQ are under development in JUNO, which allow prompt alert and trigger-less data acquisition of CCSN events. The alert performances of both monitoring systems have been thoroughly studied using simulations. Moreover, once a CCSN is tagged, the system can give fast characterizations, such as directionality and light curve

Detection of the Diffuse Supernova Neutrino Background with JUNO

As an underground multi-purpose neutrino detector with 20 kton liquid scintillator, Jiangmen Underground Neutrino Observatory (JUNO) is competitive with and complementary to the water-Cherenkov detectors on the search for the diffuse supernova neutrino background (DSNB). Typical supernova models predict 2-4 events per year within the optimal observation window in the JUNO detector. The dominant background is from the neutral-current (NC) interaction of atmospheric neutrinos with 12C nuclei, which surpasses the DSNB by more than one order of magnitude. We evaluated the systematic uncertainty of NC background from the spread of a variety of data-driven models and further developed a method to determine NC background within 15\% with {\it{in}} {\it{situ}} measurements after ten years of running. Besides, the NC-like backgrounds can be effectively suppressed by the intrinsic pulse-shape discrimination (PSD) capabilities of liquid scintillators. In this talk, I will present in detail the improvements on NC background uncertainty evaluation, PSD discriminator development, and finally, the potential of DSNB sensitivity in JUNO

Real-time Monitoring for the Next Core-Collapse Supernova in JUNO

Core-collapse supernova (CCSN) is one of the most energetic astrophysical events in the Universe. The early and prompt detection of neutrinos before (pre-SN) and during the SN burst is a unique opportunity to realize the multi-messenger observation of the CCSN events. In this work, we describe the monitoring concept and present the sensitivity of the system to the pre-SN and SN neutrinos at the Jiangmen Underground Neutrino Observatory (JUNO), which is a 20 kton liquid scintillator detector under construction in South China. The real-time monitoring system is designed with both the prompt monitors on the electronic board and online monitors at the data acquisition stage, in order to ensure both the alert speed and alert coverage of progenitor stars. By assuming a false alert rate of 1 per year, this monitoring system can be sensitive to the pre-SN neutrinos up to the distance of about 1.6 (0.9) kpc and SN neutrinos up to about 370 (360) kpc for a progenitor mass of 30$M_{\odot}$ for the case of normal (inverted) mass ordering. The pointing ability of the CCSN is evaluated by using the accumulated event anisotropy of the inverse beta decay interactions from pre-SN or SN neutrinos, which, along with the early alert, can play important roles for the followup multi-messenger observations of the next Galactic or nearby extragalactic CCSN.Comment: 24 pages, 9 figure

Convergent functional genomics of schizophrenia: from comprehensive understanding to genetic risk prediction

We have used a translational convergent functional genomics (CFG) approach to identify and prioritize genes involved in schizophrenia, by gene-level integration of genome-wide association study data with other genetic and gene expression studies in humans and animal models. Using this polyevidence scoring and pathway analyses, we identify top genes (DISC1, TCF4, MBP, MOBP, NCAM1, NRCAM, NDUFV2, RAB18, as well as ADCYAP1, BDNF, CNR1, COMT, DRD2, DTNBP1, GAD1, GRIA1, GRIN2B, HTR2A, NRG1, RELN, SNAP-25, TNIK), brain development, myelination, cell adhesion, glutamate receptor signaling, G-protein–coupled receptor signaling and cAMP-mediated signaling as key to pathophysiology and as targets for therapeutic intervention. Overall, the data are consistent with a model of disrupted connectivity in schizophrenia, resulting from the effects of neurodevelopmental environmental stress on a background of genetic vulnerability. In addition, we show how the top candidate genes identified by CFG can be used to generate a genetic risk prediction score (GRPS) to aid schizophrenia diagnostics, with predictive ability in independent cohorts. The GRPS also differentiates classic age of onset schizophrenia from early onset and late-onset disease. We also show, in three independent cohorts, two European American and one African American, increasing overlap, reproducibility and consistency of findings from single-nucleotide polymorphisms to genes, then genes prioritized by CFG, and ultimately at the level of biological pathways and mechanisms. Finally, we compared our top candidate genes for schizophrenia from this analysis with top candidate genes for bipolar disorder and anxiety disorders from previous CFG analyses conducted by us, as well as findings from the fields of autism and Alzheimer. Overall, our work maps the genomic and biological landscape for schizophrenia, providing leads towards a better understanding of illness, diagnostics and therapeutics. It also reveals the significant genetic overlap with other major psychiatric disorder domains, suggesting the need for improved nosology