Cyclone: an accessible pipeline to analyze, evaluate, and optimize multiparametric cytometry data

In the past decade, high-dimensional single-cell technologies have revolutionized basic and translational immunology research and are now a key element of the toolbox used by scientists to study the immune system. However, analysis of the data generated by these approaches often requires clustering algorithms and dimensionality reduction representation, which are computationally intense and difficult to evaluate and optimize. Here, we present Cytometry Clustering Optimization and Evaluation (Cyclone), an analysis pipeline integrating dimensionality reduction, clustering, evaluation, and optimization of clustering resolution, and downstream visualization tools facilitating the analysis of a wide range of cytometry data. We benchmarked and validated Cyclone on mass cytometry (CyTOF), full-spectrum fluorescence-based cytometry, and multiplexed immunofluorescence (IF) in a variety of biological contexts, including infectious diseases and cancer. In each instance, Cyclone not only recapitulates gold standard immune cell identification but also enables the unsupervised identification of lymphocytes and mononuclear phagocyte subsets that are associated with distinct biological features. Altogether, the Cyclone pipeline is a versatile and accessible pipeline for performing, optimizing, and evaluating clustering on a variety of cytometry datasets, which will further power immunology research and provide a scaffold for biological discovery

Cyclone: an accessible pipeline to analyze, evaluate, and optimize multiparametric cytometry data.

In the past decade, high-dimensional single-cell technologies have revolutionized basic and translational immunology research and are now a key element of the toolbox used by scientists to study the immune system. However, analysis of the data generated by these approaches often requires clustering algorithms and dimensionality reduction representation, which are computationally intense and difficult to evaluate and optimize. Here, we present Cytometry Clustering Optimization and Evaluation (Cyclone), an analysis pipeline integrating dimensionality reduction, clustering, evaluation, and optimization of clustering resolution, and downstream visualization tools facilitating the analysis of a wide range of cytometry data. We benchmarked and validated Cyclone on mass cytometry (CyTOF), full-spectrum fluorescence-based cytometry, and multiplexed immunofluorescence (IF) in a variety of biological contexts, including infectious diseases and cancer. In each instance, Cyclone not only recapitulates gold standard immune cell identification but also enables the unsupervised identification of lymphocytes and mononuclear phagocyte subsets that are associated with distinct biological features. Altogether, the Cyclone pipeline is a versatile and accessible pipeline for performing, optimizing, and evaluating clustering on a variety of cytometry datasets, which will further power immunology research and provide a scaffold for biological discovery

SARS-CoV-2 infection studies in lung organoids identify TSPAN8 as novel mediator

SARS coronavirus-2 (SARS-CoV-2) is causing a global pandemic with large variation in COVID-19 disease spectrum. SARS-CoV-2 infection requires host receptor ACE2 on lung epithelium, but epithelial underpinnings of variation are largely unknown. We capitalized on comprehensive organoid assays to report remarkable variation in SARS-CoV-2 infection rates of lung organoids from different subjects. Tropism is highest for TUBA- and MUC5AC-positive organoid cells, but levels of TUBA-, MUC5A-, or ACE2- positive cells do not predict infection rate. We identify surface molecule Tetraspanin 8 (TSPAN8) as novel mediator of SARS-CoV-2 infection, which is not downregulated by this specific virus. TSPAN8 levels, prior to infection, strongly correlate with infection rate and TSPAN8-blocking antibodies diminish SARS-CoV-2 infection. We propose TSPAN8 as novel functional biomarker and potential therapeutic target for COVID-19

SARS-CoV-2 infection studies in lung organoids identify TSPAN8 as novel mediator.

SARS coronavirus-2 (SARS-CoV-2) is causing a global pandemic with large variation in COVID-19 disease spectrum. SARS-CoV-2 infection requires host receptor ACE2 on lung epithelium, but epithelial underpinnings of variation are largely unknown. We capitalized on comprehensive organoid assays to report remarkable variation in SARS-CoV-2 infection rates of lung organoids from different subjects. Tropism is highest for TUBA- and MUC5AC-positive organoid cells, but levels of TUBA-, MUC5A-, or ACE2-positive cells do not predict infection rate. We identify surface molecule Tetraspanin 8 (TSPAN8) as novel mediator of SARS-CoV-2 infection, which is not downregulated by this specific virus. TSPAN8 levels, prior to infection, strongly correlate with infection rate and TSPAN8-blocking antibodies diminish SARS-CoV-2 infection. We propose TSPAN8 as novel functional biomarker and potential therapeutic target for COVID-19

SARS-CoV-2 infection of airway organoids reveals conserved use of Tetraspanin-8 by Ancestral, Delta, and Omicron variants

Ancestral SARS coronavirus-2 (SARS-CoV-2) and variants of concern (VOC) caused a global pandemic with a spectrum of disease severity. The mechanistic explaining variations related to airway epithelium are relatively understudied. Here, we biobanked airway organoids (AO) by preserving stem cell function. We optimized viral infection with H1N1/PR8 and comprehensively characterized epithelial responses to SARS-CoV-2 infection in phenotypically stable AO from 20 different subjects. We discovered Tetraspanin-8 (TSPAN8) as a facilitator of SARS-CoV-2 infection. TSPAN8 facilitates SARS-CoV-2 infection rates independently of ACE2-Spike interaction. In head-to-head comparisons with Ancestral SARS-CoV-2, Delta and Omicron VOC displayed lower overall infection rates of AO but triggered changes in epithelial response. All variants shared highest tropism for ciliated and goblet cells. TSPAN8-blocking antibodies diminish SARS-CoV-2 infection and may spur novel avenues for COVID-19 therapy

VUV-Sensitive Silicon Photomultipliers for Xenon Scintillation Light Detection in nEXO

Future ton-scale liquefied noble gas detectors depend on efficient light detection in the vacuum ultraviolet (VUV) range. In the past years, silicon photomultipliers (SiPMs) have emerged as a valid alternative to standard photomultiplier tubes or large-area avalanche photodiodes. The next-generation double-beta decay experiment, nEXO, with a 5-ton liquid xenon time projection chamber will use SiPMs for detecting the 175-nm xenon scintillation light, in order to achieve an energy resolution of sigma/Q(beta beta) = 1%. This paper presents recent measurements of the VUV-HD generation SiPMs from Fondazione Bruno Kessler, Trento, Italy, in two complementary setups. It includes measurements of the photon-detection efficiency (PDE) with gaseous xenon scintillation light in a vacuum setup and dark measurements in a dry nitrogen gas setup. We report improved PDE at 175 nm compared to previous generation devices that would meet the criteria of nEXO. Furthermore, we present the projected nEXO detector light collection and energy resolution that could be achieved by using these SiPMs © 2018 IEEE

DIII-D research towards establishing the scientific basis for future fusion reactors

DIII-D research is addressing critical challenges in preparation for ITER and the next generation of fusion devices through focusing on plasma physics fundamentals that underpin key fusion goals, understanding the interaction of disparate core and boundary plasma physics, and developing integrated scenarios for achieving high performance fusion regimes. Fundamental investigations into fusion energy science find that anomalous dissipation of runaway electrons (RE) that arise following a disruption is likely due to interactions with RE-driven kinetic instabilities, some of which have been directly observed, opening a new avenue for RE energy dissipation using naturally excited waves. Dimensionless parameter scaling of intrinsic rotation and gyrokinetic simulations give a predicted ITER rotation profile with significant turbulence stabilization. Coherence imaging spectroscopy confirms near sonic flow throughout the divertor towards the target, which may account for the convection-dominated parallel heat flux. Core-boundary integration studies show that the small angle slot divertor achieves detachment at lower density and extends plasma cooling across the divertor target plate, which is essential for controlling heat flux and erosion. The Super H-mode regime has been extended to high plasma current (2.0 MA) and density to achieve very high pedestal pressures (similar to 30 kPa) and stored energy (3.2 MJ) with H-98y2 approximate to 1.6-2.4. In scenario work, the ITER baseline Q = 10 scenario with zero injected torque is found to have a fusion gain metric beta(TE) independent of current between q(95) = 2.8-3.7, and a lower limit of pedestal rotation for RMP ELM suppression has been found. In the wide pedestal QH-mode regime that exhibits improved performance and no ELMs, the start-up counter torque has been eliminated so that the entire discharge uses approximate to 0 injected torque and the operating space is more ITER-relevant. Finally, the high-beta(N) (<= 3.8) hybrid scenario has been extended to the high-density levels necessary for radiating divertor operation, achieving similar to 40% divertor heat flux reduction using either argon or neon with P-tot up to 15 MW