The attenuation of central angiotensin II-dependent pressor response and intra-neuronal signaling by intracarotid injection of nanoformulated copper/zinc superoxide dismutase

Adenoviral-mediated overexpression of the intracellular superoxide (O2·-) scavenging enzyme copper/zinc superoxide dismutase (CuZnSOD) in the brain attenuates central angiotensin II (AngII)-induced cardiovascular responses. However, the therapeutic potential for adenoviral vectors is weakened by toxicity and the inability of adenoviral vectors to target the brain following peripheral administration. Therefore, we developed a non-viral delivery system in which CuZnSOD protein is electrostatically bound to a synthetic poly(ethyleneimine)-poly(ethyleneglycol) (PEI-PEG) polymer to form a polyion complex (CuZnSOD nanozyme). We hypothesized that PEI-PEG polymer increases transport of functional CuZnSOD to neurons, which inhibits AngII intra-neuronal signaling. The AngII-induced increase in O2·-, as measured by dihydroethidium fluorescence and electron paramagnetic resonance spectroscopy, was significantly inhibited in CuZnSOD nanozyme-treated neurons compared to free CuZnSOD- and non-treated neurons. CuZnSOD nanozyme also attenuated the AngII-induced inhibition of K+ current in neurons. Intracarotid injection of CuZnSOD nanozyme into rabbits significantly inhibited the pressor response of intracerebroventricular-delivered AngII; however, intracarotid injection of free CuZnSOD or PEI-PEG polymer alone failed to inhibit this response. Importantly, neither the PEI-PEG polymer alone nor the CuZnSOD nanozyme induced neuronal toxicity. These findings indicate that CuZnSOD nanozyme inhibits AngII intra-neuronal signaling in vitro and in vivo

Narrowband Searches for Continuous and Long-duration Transient Gravitational Waves from Known Pulsars in the LIGO-Virgo Third Observing Run

Isolated neutron stars that are asymmetric with respect to their spin axis are possible sources of detectable continuous gravitational waves. This paper presents a fully coherent search for such signals from eighteen pulsars in data from LIGO and Virgo's third observing run (O3). For known pulsars, efficient and sensitive matched-filter searches can be carried out if one assumes the gravitational radiation is phase-locked to the electromagnetic emission. In the search presented here, we relax this assumption and allow both the frequency and the time derivative of the frequency of the gravitational waves to vary in a small range around those inferred from electromagnetic observations. We find no evidence for continuous gravitational waves, and set upper limits on the strain amplitude for each target. These limits are more constraining for seven of the targets than the spin-down limit defined by ascribing all rotational energy loss to gravitational radiation. In an additional search, we look in O3 data for long-duration (hours-months) transient gravitational waves in the aftermath of pulsar glitches for six targets with a total of nine glitches. We report two marginal outliers from this search, but find no clear evidence for such emission either. The resulting duration-dependent strain upper limits do not surpass indirect energy constraints for any of these targets. © 2022. The Author(s). Published by the American Astronomical Society

A generalized joint inference approach for citation matching

Citation matching is the problem of extracting bibliographic records from citation lists in technical papers, and merging records that represent the same publication. Generally, there are three types of data- sets in citation matching, i.e., sparse, dense and hybrid types. Typical approaches for citation matching are Joint Segmentation (Jnt-Seg) and Joint Segmentation Entity Resolution (Jnt-Seg-ER). Jnt-Seg method is effective at processing sparse type datasets, but often produces many errors when applied to dense type datasets. On the contrary, Jnt-Seg-ER method is good at dealing with dense type datasets, but insufficient when sparse type datasets are presented. In this paper we propose an alternative joint inference approach&ndash;Generalized Joint Segmentation (Generalized-Jnt-Seg). It can effectively deal with the situation when the dataset type is unknown. Especially, in hybrid type datasets analysis there is often no a priori information for choosing Jnt-Seg method or Jnt-Seg-ER method to process segmentation and entity resolution. Both methods may produce many errors. Fortunately, our method can effectively avoid error of segmentation and produce well field boundaries. Experimental results on both types of citation datasets show that our method outperforms many alternative approaches for citation matching.<br /