End-to-End Modeling of the TDM Readout System for CMB-S4

The CMB-S4 experiment is developing next-generation ground-based microwave telescopes to observe the Cosmic Microwave Background with unprecedented sensitivity. This will require an order of magnitude increase in the 100 mK detector count, which in turn increases the demands on the readout system. The CMB-S4 readout will use time division multiplexing (TDM), taking advantage of faster switches and amplifiers in order to achieve an increased multiplexing factor. To facilitate the design of the new readout system, we have developed a model that predicts the bandwidth and noise performance of this circuity and its interconnections. This is then used to set requirements on individual components in order to meet the performance necessary for the full system. We present an overview of this model and compare the model results to the performance of both legacy and prototype readout hardware.Comment: This manuscript was submitted to the Journal of Low Temperature Physics as part of the special issue "LTD20", supporting the conference contribution RP-00

International consensus conference recommendations on ultrasound education for undergraduate medical students

Objectives: The purpose of this study is to provide expert consensus recommendations to establish a global ultrasound curriculum for undergraduate medical students. Methods: 64 multi-disciplinary ultrasound experts from 16 countries, 50 multi-disciplinary ultrasound consultants, and 21 medical students and residents contributed to these recommendations. A modified Delphi consensus method was used that included a systematic literature search, evaluation of the quality of literature by the GRADE system, and the RAND appropriateness method for panel judgment and consensus decisions. The process included four in-person international discussion sessions and two rounds of online voting. Results: A total of 332 consensus conference statements in four curricular domains were considered: (1) curricular scope (4 statements), (2) curricular rationale (10 statements), (3) curricular characteristics (14 statements), and (4) curricular content (304 statements). Of these 332 statements, 145 were recommended, 126 were strongly recommended, and 61 were not recommended. Important aspects of an undergraduate ultrasound curriculum identified include curricular integration across the basic and clinical sciences and a competency and entrustable professional activity-based model. The curriculum should form the foundation of a life-long continuum of ultrasound education that prepares students for advanced training and patient care. In addition, the curriculum should complement and support the medical school curriculum as a whole with enhanced understanding of anatomy, physiology, pathophysiological processes and clinical practice without displacing other important undergraduate learning. The content of the curriculum should be appropriate for the medical student level of training, evidence and expert opinion based, and include ongoing collaborative research and development to ensure optimum educational value and patient care. Conclusions: The international consensus conference has provided the first comprehensive document of recommendations for a basic ultrasound curriculum. The document reflects the opinion of a diverse and representative group of international expert ultrasound practitioners, educators, and learners. These recommendations can standardize undergraduate medical student ultrasound education while serving as a basis for additional research in medical education and the application of ultrasound in clinical practice

Recent Progress and Next Steps for the MATHUSLA LLP Detector

We report on recent progress and next steps in the design of the proposed MATHUSLA Long Lived Particle (LLP) detector for the HL-LHC as part of the Snowmass 2021 process. Our understanding of backgrounds has greatly improved, aided by detailed simulation studies, and significant R&D has been performed on designing the scintillator detectors and understanding their performance. The collaboration is on track to complete a Technical Design Report, and there are many opportunities for interested new members to contribute towards the goal of designing and constructing MATHUSLA in time for HL-LHC collisions, which would increase the sensitivity to a large variety of highly motivated LLP signals by orders of magnitude.Comment: Contribution to Snowmass 2021 (EF09, EF10, IF6, IF9), 18 pages, 12 figures. v2: included additional endorser

Whole-genome sequencing reveals host factors underlying critical COVID-19

Critical COVID-19 is caused by immune-mediated inflammatory lung injury. Host genetic variation influences the development of illness requiring critical care1 or hospitalization2–4 after infection with SARS-CoV-2. The GenOMICC (Genetics of Mortality in Critical Care) study enables the comparison of genomes from individuals who are critically ill with those of population controls to find underlying disease mechanisms. Here we use whole-genome sequencing in 7,491 critically ill individuals compared with 48,400 controls to discover and replicate 23 independent variants that significantly predispose to critical COVID-19. We identify 16 new independent associations, including variants within genes that are involved in interferon signalling (IL10RB and PLSCR1), leucocyte differentiation (BCL11A) and blood-type antigen secretor status (FUT2). Using transcriptome-wide association and colocalization to infer the effect of gene expression on disease severity, we find evidence that implicates multiple genes—including reduced expression of a membrane flippase (ATP11A), and increased expression of a mucin (MUC1)—in critical disease. Mendelian randomization provides evidence in support of causal roles for myeloid cell adhesion molecules (SELE, ICAM5 and CD209) and the coagulation factor F8, all of which are potentially druggable targets. Our results are broadly consistent with a multi-component model of COVID-19 pathophysiology, in which at least two distinct mechanisms can predispose to life-threatening disease: failure to control viral replication; or an enhanced tendency towards pulmonary inflammation and intravascular coagulation. We show that comparison between cases of critical illness and population controls is highly efficient for the detection of therapeutically relevant mechanisms of disease

Genetic mechanisms of critical illness in COVID-19.

Host-mediated lung inflammation is present1, and drives mortality2, in the critical illness caused by coronavirus disease 2019 (COVID-19). Host genetic variants associated with critical illness may identify mechanistic targets for therapeutic development3. Here we report the results of the GenOMICC (Genetics Of Mortality In Critical Care) genome-wide association study in 2,244 critically ill patients with COVID-19 from 208 UK intensive care units. We have identified and replicated the following new genome-wide significant associations: on chromosome 12q24.13 (rs10735079, P = 1.65 × 10-8) in a gene cluster that encodes antiviral restriction enzyme activators (OAS1, OAS2 and OAS3); on chromosome 19p13.2 (rs74956615, P = 2.3 × 10-8) near the gene that encodes tyrosine kinase 2 (TYK2); on chromosome 19p13.3 (rs2109069, P = 3.98 ×  10-12) within the gene that encodes dipeptidyl peptidase 9 (DPP9); and on chromosome 21q22.1 (rs2236757, P = 4.99 × 10-8) in the interferon receptor gene IFNAR2. We identified potential targets for repurposing of licensed medications: using Mendelian randomization, we found evidence that low expression of IFNAR2, or high expression of TYK2, are associated with life-threatening disease; and transcriptome-wide association in lung tissue revealed that high expression of the monocyte-macrophage chemotactic receptor CCR2 is associated with severe COVID-19. Our results identify robust genetic signals relating to key host antiviral defence mechanisms and mediators of inflammatory organ damage in COVID-19. Both mechanisms may be amenable to targeted treatment with existing drugs. However, large-scale randomized clinical trials will be essential before any change to clinical practice

Common, low-frequency, rare, and ultra-rare coding variants contribute to COVID-19 severity

The combined impact of common and rare exonic variants in COVID-19 host genetics is currently insufficiently understood. Here, common and rare variants from whole-exome sequencing data of about 4000 SARS-CoV-2-positive individuals were used to define an interpretable machine-learning model for predicting COVID-19 severity. First, variants were converted into separate sets of Boolean features, depending on the absence or the presence of variants in each gene. An ensemble of LASSO logistic regression models was used to identify the most informative Boolean features with respect to the genetic bases of severity. The Boolean features selected by these logistic models were combined into an Integrated PolyGenic Score that offers a synthetic and interpretable index for describing the contribution of host genetics in COVID-19 severity, as demonstrated through testing in several independent cohorts. Selected features belong to ultra-rare, rare, low-frequency, and common variants, including those in linkage disequilibrium with known GWAS loci. Noteworthily, around one quarter of the selected genes are sex-specific. Pathway analysis of the selected genes associated with COVID-19 severity reflected the multi-organ nature of the disease. The proposed model might provide useful information for developing diagnostics and therapeutics, while also being able to guide bedside disease management. © 2021, The Author(s)

CMB-S4: Forecasting Constraints on Primordial Gravitational Waves

CMB-S4---the next-generation ground-based cosmic microwave background (CMB) experiment---is set to significantly advance the sensitivity of CMB measurements and enhance our understanding of the origin and evolution of the Universe, from the highest energies at the dawn of time through the growth of structure to the present day. Among the science cases pursued with CMB-S4, the quest for detecting primordial gravitational waves is a central driver of the experimental design. This work details the development of a forecasting framework that includes a power-spectrum-based semi-analytic projection tool, targeted explicitly towards optimizing constraints on the tensor-to-scalar ratio, $r$, in the presence of Galactic foregrounds and gravitational lensing of the CMB. This framework is unique in its direct use of information from the achieved performance of current Stage 2--3 CMB experiments to robustly forecast the science reach of upcoming CMB-polarization endeavors. The methodology allows for rapid iteration over experimental configurations and offers a flexible way to optimize the design of future experiments given a desired scientific goal. To form a closed-loop process, we couple this semi-analytic tool with map-based validation studies, which allow for the injection of additional complexity and verification of our forecasts with several independent analysis methods. We document multiple rounds of forecasts for CMB-S4 using this process and the resulting establishment of the current reference design of the primordial gravitational-wave component of the Stage-4 experiment, optimized to achieve our science goals of detecting primordial gravitational waves for $r > 0.003$ at greater than $5\sigma$, or, in the absence of a detection, of reaching an upper limit of $r < 0.001$ at $95\%$ CL.Comment: 24 pages, 8 figures, 9 tables, submitted to ApJ. arXiv admin note: text overlap with arXiv:1907.0447