Wave functions and properties of massive states in three-dimensional supersymmetric Yang-Mills theory

We apply supersymmetric discrete light-cone quantization (SDLCQ) to the study of supersymmetric Yang-Mills theory on R x S^1 x S^1. One of the compact directions is chosen to be light-like and the other to be space-like. Since the SDLCQ regularization explicitly preserves supersymmetry, this theory is totally finite, and thus we can solve for bound-state wave functions and masses numerically without renormalizing. We present an overview of all the massive states of this theory, and we see that the spectrum divides into two distinct and disjoint sectors. In one sector the SDLCQ approximation is only valid up to intermediate coupling. There we find a well defined and well behaved set of states, and we present a detailed analysis of these states and their properties. In the other sector, which contains a completely different set of states, we present a much more limited analysis for strong coupling only. We find that, while these state have a well defined spectrum, their masses grow with the transverse momentum cutoff. We present an overview of these states and their properties.Comment: RevTeX, 25 pages, 16 figure

In vivo imaging reveals increased eosinophil uptake in the lungs of obese asthmatic patients.

To The Editor: Eosinophils play an important pathogenic role in pulmonary and systemic conditions including eosinophilic asthma and eosinophilic granulomatosis with polyangiitis.1,2 While progress has been made in understanding the mechanisms responsible for the activation of these cells, existing biomarkers of eosinophilic inflammation are indirect and/or invasive and do not always correlate with tissue eosinophilia. Hence, there is a need to develop non-invasive biomarkers of tissue eosinophilia. We have previously demonstrated the capacity of SPECT (single photon emission computed tomography) to quantify neutrophil uptake into the lungs of COPD patients.3 We sought to determine whether this methodology could be used to quantify eosinophil kinetics and pulmonary uptake, which may differ amongst diseases characterized by eosinophilic inflammation. In particular, the role of the eosinophil in asthma with obesity, a distinct asthma endotype associated with increased severity,4 is controversial. We hypothesized that injection of radiolabeled eosinophils, coupled with SPECT/CT, would reveal changes in eosinophil kinetics in patients compared to healthy volunteers.This work was supported by Asthma UK [08/11], the Medical Research Council [grant number MR/J00345X/1], the Wellcome Trust [grant number 098351/Z/12/Z], Cambridge NIHR Biomedical Research Centre, Wellcome Trust Senior Fellowship (to CEB) [grant number WT082265], AirPROM 7th EU Framework grant and Leicester NIHR Biomedical Research Centre

Application of Pauli-Villars Regularization and Discretized Light-Cone Quantization to a (3+1)-Dimensional Model

We apply Pauli-Villars regularization and discrete light-cone quantization to the nonperturbative solution of a (3+1)-dimensional model field theory. The matrix eigenvalue problem is solved for the lowest-mass state with use of the complex symmetric Lanczos algorithm. This permits the calculation of each Fock-sector wave function, and from these we obtain values for various quantities, such as average multiplicities and average momenta of constituents, structure functions, and a form factor slope.Comment: RevTex, 27 page

A randomised controlled trial of compression therapies for the treatment of venous leg ulcers (VenUS 6) : study protocol for a pragmatic, multicentre, parallel group, three arm randomised controlled trial

Background Venous leg ulcer(s), are common, recurring, open wounds on the lower leg, resulting from diseased or damaged leg veins impairing blood flow. Wound healing is the primary treatment aim for venous leg ulceration, alongside management of pain, wound exudate and infection. Full (high) compression therapy delivering 40mmHg of pressure at the ankle is the recommended first line treatment for venous leg ulcers. There are several different forms of compression therapy available including wraps, two-layer hosiery, and two-layer or four-layer bandages. There is good evidence for the clinical and cost effectiveness of four-layer bandage and two-layer hosiery but more limited evidence for other treatments (two-layer bandage and compression wraps). Robust evidence is required to compare clinical and cost effectiveness of these and to investigate which is the best compression treatment for reducing time to healing of venous leg ulcers whilst offering value for money. VenUS 6 will therefore investigate the clinical and cost effectiveness of evidence-based compression, two-layer bandage and compression wraps for time to healing of venous leg ulcers. Methods VenUS 6 is a pragmatic, multi-centre, three arm, parallel group, randomised controlled trial. Adult patients with a venous leg ulcer will be randomised to receive 1) compression wraps, 2) two-layer bandage or 3) evidence-based compression (two-layer hosiery or four-layer bandage). Participants will followed up for between 4 and 12 months. The primary outcome will be time to healing (full epithelial cover in absence of a scab) in days since randomisation. Secondary outcomes will include key clinical events (e.g., healing of the reference leg; ulcer recurrence; ulcer/skin deterioration, amputation, admission/discharge, surgery to close/remove incompetent superficial veins, infection, or death), treatment changes, adherence and ease of use, ulcer related pain, health-related quality of life and resource use. Discussion VenUS 6 will provide robust evidence on the clinical and cost-effectiveness of the different forms of compression therapies for venous leg ulceration. VenUS 6 opened to recruitment in January 2021 and is currently recruiting across 30 participating centres. Clinical Trial Registry: ISRCTN 67321719 (https://doi.org/10.1186/ISRCTN67321719). Prospectively Registered: 14.09.202

A General Synthetic Approach for Designing Epitope Targeted Macrocyclic Peptide Ligands

We describe a general synthetic strategy for developing high-affinity peptide binders against specific epitopes of challenging protein biomarkers. The epitope of interest is synthesized as a polypeptide, with a detection biotin tag and a strategically placed azide (or alkyne) presenting amino acid. This synthetic epitope (SynEp) is incubated with a library of complementary alkyne or azide presenting peptides. Library elements that bind the SynEp in the correct orientation undergo the Huisgen cycloaddition, and are covalently linked to the SynEp. Hit peptides are tested against the full-length protein to identify the best binder. We describe development of epitope-targeted linear or macrocycle peptide ligands against 12 different diagnostic or therapeutic analytes. The general epitope targeting capability for these low molecular weight synthetic ligands enables a range of therapeutic and diagnostic applications, similar to those of monoclonal antibodies

Prognostic model to predict postoperative acute kidney injury in patients undergoing major gastrointestinal surgery based on a national prospective observational cohort study.

Background: Acute illness, existing co-morbidities and surgical stress response can all contribute to postoperative acute kidney injury (AKI) in patients undergoing major gastrointestinal surgery. The aim of this study was prospectively to develop a pragmatic prognostic model to stratify patients according to risk of developing AKI after major gastrointestinal surgery. Methods: This prospective multicentre cohort study included consecutive adults undergoing elective or emergency gastrointestinal resection, liver resection or stoma reversal in 2-week blocks over a continuous 3-month period. The primary outcome was the rate of AKI within 7 days of surgery. Bootstrap stability was used to select clinically plausible risk factors into the model. Internal model validation was carried out by bootstrap validation. Results: A total of 4544 patients were included across 173 centres in the UK and Ireland. The overall rate of AKI was 14·2 per cent (646 of 4544) and the 30-day mortality rate was 1·8 per cent (84 of 4544). Stage 1 AKI was significantly associated with 30-day mortality (unadjusted odds ratio 7·61, 95 per cent c.i. 4·49 to 12·90; P < 0·001), with increasing odds of death with each AKI stage. Six variables were selected for inclusion in the prognostic model: age, sex, ASA grade, preoperative estimated glomerular filtration rate, planned open surgery and preoperative use of either an angiotensin-converting enzyme inhibitor or an angiotensin receptor blocker. Internal validation demonstrated good model discrimination (c-statistic 0·65). Discussion: Following major gastrointestinal surgery, AKI occurred in one in seven patients. This preoperative prognostic model identified patients at high risk of postoperative AKI. Validation in an independent data set is required to ensure generalizability

New insights into the genetic etiology of Alzheimer's disease and related dementias

Characterization of the genetic landscape of Alzheimer's disease (AD) and related dementias (ADD) provides a unique opportunity for a better understanding of the associated pathophysiological processes. We performed a two-stage genome-wide association study totaling 111,326 clinically diagnosed/'proxy' AD cases and 677,663 controls. We found 75 risk loci, of which 42 were new at the time of analysis. Pathway enrichment analyses confirmed the involvement of amyloid/tau pathways and highlighted microglia implication. Gene prioritization in the new loci identified 31 genes that were suggestive of new genetically associated processes, including the tumor necrosis factor alpha pathway through the linear ubiquitin chain assembly complex. We also built a new genetic risk score associated with the risk of future AD/dementia or progression from mild cognitive impairment to AD/dementia. The improvement in prediction led to a 1.6- to 1.9-fold increase in AD risk from the lowest to the highest decile, in addition to effects of age and the APOE ε4 allele

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

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 hospitalization2,3,4 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