First attempt of directionality reconstruction for atmospheric neutrinos in a large homogeneous liquid scintillator detector

The directionality information of incoming neutrinos is essential to atmospheric neutrino oscillation analysis since it is directly related to the oscillation baseline length. Large homogeneous liquid scintillator detectors, while offering excellent energy resolution, are traditionally very limited in their capabilities of measuring event directionality. In this paper, we present a novel directionality reconstruction method for atmospheric neutrino events in large homogeneous liquid scintillator detectors based on waveform analysis and machine learning techniques. We demonstrate for the first time that such detectors can achieve good direction resolution and potentially play an important role in future atmospheric neutrino oscillation measurements.Comment: Prepared for submission to PR

Bedform evolution along a submarine canyon in the South China Sea: New insights from an autonomous underwater vehicle survey

Traditional mapping of bedforms in submarine canyons relied on vessel-mounted and towed sensors, but their fine-scale geomorphology and shallow structure requires higher resolution datasets. This study utilizes a high-resolution dataset obtained from an autonomous underwater vehicle, combined with seismic reflection profiles and sediment cores, to analyze bedform sets within a 25.6 km long submarine canyon (canyon C14) in the northern South China Sea. A train of crescent-shaped axial steps, indicative of cyclic steps formed by supercritical turbidity currents, is imaged along the canyon. Axial steps in the upper course show erosional truncations and sub-horizontal reflectors on the lee and stoss sides, respectively, pointing to erosional–depositional cyclic steps formed by confined flows with high erosional capacity. This is facilitated by canyon narrowness and steeper axial gradient. After a transition segment, the lower course widens, with a gentler axial gradient, resulting in increased asymmetry and wavelength of axial steps. Backset bed deposits on the stoss sides of these steps indicate depositional cyclic steps with higher aggradation. Sediment filling, almost padding each cyclic step associated scour suggests the reworking of previously formed bedforms by gravity flows fed by destabilization processes on the canyon sidewalls and upstream lee faces and, possibly, by shelf-edge and uppermost slope spillover into the canyon. At the lowermost course, cyclic steps transition to a furrow field, likely associated to flow velocity reduction facilitated by canyon floor widening and a further decrease in slope gradient. Flow braiding and re-convergence, related to the erosion of fine-grained deposits within the canyon floor, should have played a role to produce furrows under supercritical conditions. This work enhances our understanding of the detailed morphology and shallow relief configuration of bedforms in deep-water submarine canyons, providing insights into their causative processes and evolution

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

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

Nanopillar-guided subnuclear deformations in tumor cells

Subnuclear shape irregularities, including folding and grooves of the nuclear envelope, function as a routine marker in the diagnosis and prognosis of many cancer types and show strong correlation with diverse pathological alterations. However, their assessment is primarily relying on qualitative visual inspection due to the small feature size and random distribution that are extremely difficult to be quantified using conventional technology. Consequently, lack of tool for providing quantitative evaluation of such irregularities becomes a significant bottleneck for precise cancer grading and the related fundamental studies. In this thesis, we developed a novel nanopillar-based assay to easily locate and subsequently quantitative characterization for subnuclear irregularities in cancer cells, thereby improving the precision of distinguishing malignancy for cancer diagnosis and drug screening, as well as enabling a new angle to investigate the molecular mechanism underlying the formation and regulation of subnuclear irregularities in cancer cells. This goal was pursued in three steps as detailed in three chapters from Chapter 2 to 4. In the first step in Chapter 2, we established the methodology of applying nanopillar arrays for the effective guidance and characterization of subnuclear shape irregularities in breast cancer cells. Distinct guided subnuclear features further enable quantitative differentiation of cancer cells with varying malignancies. Optimal nanopillar dimensions for malignancy differentiation have been determined. This method has been demonstrated to probe the heterogeneity within a mixed population of both low- and high-malignant cells and even within the same cell line. In addition, the differential anti-cancer drug response in low- and high-malignant cells has been revealed using this assay. In the second step in Chapter 3, the prevalence of this assay across different cancer types has been demonstrated. Nanopillar-enabled evaluation of subnuclear irregularities enables heterogeneity evaluation among individual neuroblastoma cells. The heterogeneity within neuroblastoma cells is found to strongly correlate with metastatic potential, thus holding a promise for precise risk stratification. Furthermore, this assay is able to assess drug response at single-cell level. In the third step in Chapter 4, we explored the underlying mechanism of the subnuclear irregularities through nanopillar guidance. Coupled with computer-based systematic analysis of subnuclear features on nanopillars, we developed a comprehensive characterization matrix to afford a minute characterization of the subnuclear irregularities. The impact of a wide spectrum of cellular modulators of the irregularities has been analyzed by the characterization matrix, where critical regulators such as contractility and nuclear lamina mechanics have been identified. Besides, an analysis pipeline has been proposed to provide quantitative comparison among different regulators. In summary, we developed a nanopillar-based tool for quantitatively assessment of subnuclear irregularities in cancer cells. We believe this tool constitutes a novel and powerful system for precise malignancy evaluation and elucidating nuclear biology from a new angle.Doctor of Philosoph

The role of membrane curvature in nanoscale topography-induced intracellular signaling

Over the past decade, there has been growing interest in developing biosensors and devices with nanoscale and vertical topography. Vertical nanostructures induce spontaneous cell engulfment, which enhances the cell–probe coupling efficiency and the sensitivity of biosensors. Although local membranes in contact with the nanostructures are found to be fully fluidic for lipid and membrane protein diffusions, cells appear to actively sense and respond to the surface topography presented by vertical nanostructures. For future development of biodevices, it is important to understand how cells interact with these nanostructures and how their presence modulates cellular function and activities. How cells recognize nanoscale surface topography has been an area of active research for two decades before the recent biosensor works. Extensive studies show that surface topographies in the range of tens to hundreds of nanometers can significantly affect cell functions, behaviors, and ultimately the cell fate. For example, titanium implants having rough surfaces are better for osteoblast attachment and host–implant integration than those with smooth surfaces. At the cellular level, nanoscale surface topography has been shown by a large number of studies to modulate cell attachment, activity, and differentiation. However, a mechanistic understanding of how cells interact and respond to nanoscale topographic features is still lacking. In this Account, we focus on some recent studies that support a new mechanism that local membrane curvature induced by nanoscale topography directly acts as a biochemical signal to induce intracellular signaling, which we refer to as the curvature hypothesis. The curvature hypothesis proposes that some intracellular proteins can recognize membrane curvatures of a certain range at the cell-to-material interface. These proteins then recruit and activate downstream components to modulate cell signaling and behavior. We discuss current technologies allowing the visualization of membrane deformation at the cell membrane-to-substrate interface with nanometer precision and demonstrate that vertical nanostructures induce local curvatures on the plasma membrane. These local curvatures enhance the process of clathrin-mediated endocytosis and affect actin dynamics. We also present evidence that vertical nanostructures can induce significant deformation of the nuclear membrane, which can affect chromatin distribution and gene expression. Finally, we provide a brief perspective on the curvature hypothesis and the challenges and opportunities for the design of nanotopography for manipulating cell behavior.Accepted versio

Patterning of oncogenic Ras clustering in live cells using vertically aligned nanostructure arrays

As a dominant oncogenic protein, Ras is well-known to segregate into clusters on the plasma membrane for activating downstream signaling. However, current technologies for direct measurements of Ras clustering are limited to sophisticated high-resolution techniques like electron microscopy and fluorescence lifetime imaging. To further promote fundamental investigations and the related drug development, we hereby introduce a nanobar-based platform which effectively guides Ras clusters into quantifiable patterns in live cells that is resolvable under conventional microscopy. Major Ras isoforms, K-Ras, H-Ras, and N-Ras were differentiated, as well as their highly prevalent oncogenic mutants G12V and G13D. Moreover, the isoform specificity and the sensitivity of a Ras inhibitor were successfully characterized on nanobars. We envision that this nanobar-based platform will serve as an effective tool to read Ras clustering on the plasma membrane, enabling a novel avenue both to decipher Ras regulations and to facilitate anti-Ras drug development.Ministry of Education (MOE)Nanyang Technological UniversityNational Research Foundation (NRF)Accepted versionThis work is funded by Singapore Ministry of Education (MOE) (W. Zhao, RG145/18 and RG112/20), the Singapore National Research Foundation (W. Zhao, NRF2019-NRF-ISF003-3292), the NTU Start-up Grant (W. Zhao), the NTU-NNI Neurotechnology Fellowship (W. Zhao), DFG (K. Rajalingam), and Ageing Research Institute for Society and Education (ARISE) NTU for the research scholarship (H. Mu)