A922 Sequential measurement of 1 hour creatinine clearance (1-CRCL) in critically ill patients at risk of acute kidney injury (AKI)

Meeting abstrac

Recent advances in radiotherapy

Radiation therapy has come a long way from treatment planning based on orthogonal radiographs with large margins around tumours. Advances in imaging and radiation planning software have led to three-dimensional conformal radiotherapy and, further, to intensity modulated radiotherapy (IMRT). IMRT permits sparing of normal tissues and hence dose-escalation to tumours. IMRT is the current standard in treatment of head and prostate cancer and is being investigated in other tumour sites. Exquisitely sculpted dose distributions (increased geographical miss) with IMRT, plus tumour motion and anatomical changes during radiotherapy make image guided radiotherapy an essential part of modern radiation delivery. Various hardware and software tools are under investigation for optimal IGRT

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

Novel mutations in TLR genes cause hyporesponsiveness to Mycobacterium avium subsp. paratuberculosis infection

<p>Abstract</p> <p>Background</p> <p>Toll like receptors (TLR) play the central role in the recognition of pathogen associated molecular patterns (PAMPs). Mutations in the TLR1, TLR2 and TLR4 genes may change the ability to recognize PAMPs and cause altered responsiveness to the bacterial pathogens.</p> <p>Results</p> <p>The study presents association between TLR gene mutations and increased susceptibility to <it>Mycobacterium avium </it>subsp. <it>paratuberculosis </it>(MAP) infection. Novel mutations in TLR genes (TLR1- Ser150Gly and Val220Met; TLR2 – Phe670Leu) were statistically correlated with the hindrance in recognition of MAP legends. This correlation was confirmed subsequently by measuring the expression levels of cytokines (IL-4, IL-8, IL-10, IL-12 and IFN-γ) in the mutant and wild type moDCs (mocyte derived dendritic cells) after challenge with MAP cell lysate or LPS. Further <it>in silico </it>analysis of the TLR1 and TLR4 ectodomains (ECD) revealed the polymorphic nature of the central ECD and irregularities in the central LRR (leucine rich repeat) motifs.</p> <p>Conclusion</p> <p>The most critical positions that may alter the pathogen recognition ability of TLR were: the 9^thamino acid position in LRR motif (TLR1–LRR10) and 4^thresidue downstream to LRR domain (exta-LRR region of TLR4). The study describes novel mutations in the TLRs and presents their association with the MAP infection.</p

Combination of searches for heavy spin-1 resonances using 139 fb−1 of proton-proton collision data at √s = 13 TeV with the ATLAS detector

A combination of searches for new heavy spin-1 resonances decaying into diferent pairings of W, Z, or Higgs bosons, as well as directly into leptons or quarks, is presented. The data sample used corresponds to 139 fb−1 of proton-proton collisions at √ s = 13 TeV collected during 2015–2018 with the ATLAS detector at the CERN Large Hadron Collider. Analyses selecting quark pairs (qq, bb, tt¯, and tb) or third-generation leptons (τν and τ τ ) are included in this kind of combination for the frst time. A simplifed model predicting a spin-1 heavy vector-boson triplet is used. Cross-section limits are set at the 95% confdence level and are compared with predictions for the benchmark model. These limits are also expressed in terms of constraints on couplings of the heavy vector-boson triplet to quarks, leptons, and the Higgs boson. The complementarity of the various analyses increases the sensitivity to new physics, and the resulting constraints are stronger than those from any individual analysis considered. The data exclude a heavy vector-boson triplet with mass below 5.8 TeV in a weakly coupled scenario, below 4.4 TeV in a strongly coupled scenario, and up to 1.5 TeV in the case of production via vector-boson fusion

Search for new phenomena with top-quark pairs and large missing transverse momentum using 140 fb−1 of pp collision data at \sqrt{s} = 13 TeV with the ATLAS detector

A search is conducted for new phenomena in events with a top quark pair and large missing transverse momentum, where the top quark pair is reconstructed in final states with one isolated electron or muon and multiple jets. The search is performed using the Large Hadron Collider proton-proton collision data sample at a centre-of-mass energy of \sqrt{s} = 13 TeV recorded by the ATLAS detector that corresponds to an integrated luminosity of 140 fb^{−1}. An analysis based on neural network classifiers is optimised to search for directly produced pairs of supersymmetric partners of the top quark (stop), and to search for spin-0 mediators, produced in association with a pair of top quarks, that decay into dark-matter particles. In the stop search, the analysis is designed to target models in which the mass difference between the stop and the neutralino from the stop decay is close to the top quark mass. This new search is combined with previously published searches in final states with different lepton multiplicities. No significant excess above the Standard Model background is observed, and limits at 95% confidence level are set. Models with neutralinos with masses up to 570 GeV are excluded, while for small neutralino masses models are excluded for stop masses up to 1230 GeV. Scalar (pseudoscalar) dark matter mediator masses as large as 350 (370) GeV are excluded when the coupling strengths of the mediator to Standard Model and dark-matter particles are both set to one. At lower mediator masses, models with production cross-sections as small as 0.15 (0.16) times the nominal predictions are excluded. Results of this search are also used to set constraints on effective four-fermion contact interactions between top quarks and neutrinos

The interstitium in cardiac repair: role of the immune-stromal cell interplay

Cardiac regeneration, that is, restoration of the original structure and function in a damaged heart, differs from tissue repair, in which collagen deposition and scar formation often lead to functional impairment. In both scenarios, the early-onset inflammatory response is essential to clear damaged cardiac cells and initiate organ repair, but the quality and extent of the immune response vary. Immune cells embedded in the damaged heart tissue sense and modulate inflammation through a dynamic interplay with stromal cells in the cardiac interstitium, which either leads to recapitulation of cardiac morphology by rebuilding functional scaffolds to support muscle regrowth in regenerative organisms or fails to resolve the inflammatory response and produces fibrotic scar tissue in adult mammals. Current investigation into the mechanistic basis of homeostasis and restoration of cardiac function has increasingly shifted focus away from stem cell-mediated cardiac repair towards a dynamic interplay of cells composing the less-studied interstitial compartment of the heart, offering unexpected insights into the immunoregulatory functions of cardiac interstitial components and the complex network of cell interactions that must be considered for clinical intervention in heart diseases

Accuracy versus precision in boosted top tagging with the ATLAS detector

Abstract The identification of top quark decays where the top quark has a large momentum transverse to the beam axis, known as top tagging, is a crucial component in many measurements of Standard Model processes and searches for beyond the Standard Model physics at the Large Hadron Collider. Machine learning techniques have improved the performance of top tagging algorithms, but the size of the systematic uncertainties for all proposed algorithms has not been systematically studied. This paper presents the performance of several machine learning based top tagging algorithms on a dataset constructed from simulated proton-proton collision events measured with the ATLAS detector at √ s = 13 TeV. The systematic uncertainties associated with these algorithms are estimated through an approximate procedure that is not meant to be used in a physics analysis, but is appropriate for the level of precision required for this study. The most performant algorithms are found to have the largest uncertainties, motivating the development of methods to reduce these uncertainties without compromising performance. To enable such efforts in the wider scientific community, the datasets used in this paper are made publicly available.</jats:p