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

Role of polymers in solution and tablet-based carbamazepine cocrystal formulations

The aim of this study was to evaluate the influence of three chemically diverse polymers, namely hydroxypropylmethylcellulose acetate succinate (HPMCAS), polyvinylpyrrolidone (PVP) and polyethylene glycol (PEG) on the phase transformation of three carbamazepine (CBZ) cocrystals including carbamazepine–nicotinamide (CBZ–NIC), carbamazepine–saccharin (CBZ–SAC) and carbamazepine–cinnamic acid (CBZ–CIN) in solution and tablet-based formulations. Based on the solubility and powder dissolution studies, it is demonstrated that cocrystals can be easily formulated through a simple solution formulation or powder formulation to generate supersaturated concentrations and faster dissolution rates to overcome those drugs with solubility and/or dissolution limited bioavailability. However, a polymer-based CBZ cocrystal tablet formulation has not shown any advantage of an improved CBZ release rate compared with the formulation of CBZ III or physical mixtures of CBZ III and coformers. This is in contrast to the solution behaviours of CBZ cocrystals in the solubility and powder dissolution tests because crystallization of the stable solid form of CBZ dihydrate (CBZ DH) within the tablet has taken place, leading to a reduced drug release rate and incomplete release. The mechanism of a polymer inhibition effect on drug precipitation in solution has been elucidated through investigating the molecular interactions among CBZ, coformers and polymers in solution using infrared spectroscopy. Finally, a formulation strategy has been proposed to capture the significant advantages of cocrystals

Co-infecting pathogens can contribute to inflammatory responses and severe symptoms in COVID-19

Background: The current COVID-19 pandemic is posing a major challenge to public health on a global scale. While it is generally believed that severe COVID-19 results from over-expression of inflammatory mediators (i.e., a "cytokine storm"), it is still unclear whether and how co-infecting pathogens contribute to disease pathogenesis. To address this, we followed the entire course of the disease in cases with severe or critical COVID-19 to determine the presence and abundance of all potential pathogens present-the total "infectome"-and how they interact with the host immune system in the context of severe COVID-19. Methods: We examined one severe and three critical cases of COVID-19, as well as a set of healthy controls, with longitudinal samples (throat swab, whole blood, and serum) collected from each case. Total RNA sequencing (meta-transcriptomics) was performed to simultaneously investigate pathogen diversity and abundance, as well as host immune responses, in each sample. A Bio-Plex method was used to measure serum cytokine and chemokine levels. Results: Eight pathogens, SARS-CoV-2, Aspergillus fumigatus (A. fumigatus), Mycoplasma orale (M. orale), Myroides odoratus (M. odoratus), Acinetobacter baumannii (A. baumannii), Candida tropicalis, herpes simplex virus (HSV) and human cytomegalovirus (CMV), identified in patients with COVID-19 appeared at different stages of the disease. The dynamics of inflammatory mediators in serum and the respiratory tract were more strongly associated with the dynamics of the infectome compared with SARS-CoV-2 alone. Correlation analysis revealed that pulmonary injury was directly associated with cytokine levels, which in turn were associated with the proliferation of SARS-CoV-2 and co-infecting pathogens. Conclusions: For each patient, the cytokine storm that resulted in acute lung injury and death involved a dynamic and highly complex infectome, of which SARS-CoV-2 was a component. These results indicate the need for a precision medicine approach to investigate both the infection and host response as a standard means of infectious disease characterization