Impact of wound edge protection devices on surgical site infection after laparotomy: multicentre randomised controlled trial (ROSSINI Trial).

OBJECTIVE: To determine the clinical effectiveness of wound edge protection devices in reducing surgical site infection after abdominal surgery. DESIGN: Multicentre observer blinded randomised controlled trial. PARTICIPANTS: Patients undergoing laparotomy at 21 UK hospitals. INTERVENTIONS: Standard care or the use of a wound edge protection device during surgery. MAIN OUTCOME MEASURES: Surgical site infection within 30 days of surgery, assessed by blinded clinicians at seven and 30 days and by patient's self report for the intervening period. Secondary outcomes included quality of life, duration of stay in hospital, and the effect of characteristics of the patient and operation on the efficacy of the device. RESULTS: 760 patients were enrolled with 382 patients assigned to the device group and 378 to the control group. Six patients in the device group and five in the control group did not undergo laparotomy. Fourteen patients, seven in each group, were lost to follow-up. A total of 184 patients experienced surgical site infection within 30 days of surgery, 91/369 (24.7%) in the device group and 93/366 (25.4%) in the control group (odds ratio 0.97, 95% confidence interval 0.69 to 1.36; P=0.85). This lack of benefit was consistent across wound assessments performed by clinicians and those reported by patients and across all secondary outcomes. In the secondary analyses no subgroup could be identified in which there was evidence of clinical benefit associated with use of the device. CONCLUSIONS: Wound edge protection devices do not reduce the rate of surgical site infection in patients undergoing laparotomy, and therefore their routine use for this role cannot be recommended. TRIAL REGISTRATION: Current Controlled Trials ISRCTN 40402832

Low pre-exercise muscle glycogen availability offsets the effect of post-exercise cold water immersion in augmenting PGC-1α gene expression

We assessed the effects of post-exercise cold-water immersion (CWI) in modulating PGC-1α expression in response to exercise commenced with low muscle glycogen availability. In a randomized repeated-measures design, nine recreationally active males completed an acute two-legged high-intensity cycling protocol (8 x 5 min at 82.5% peak power output) followed by 10 minutes of two-legged post-exercise CWI (8°C) or control conditions (CON). During each trial, one limb commenced exercise with low (LOW: <300 mmol.kg-1 dw) or very low (VLOW: <150 mmol.kg-1 dw) pre-exercise glycogen concentration, achieved via completion of a one-legged glycogen depletion protocol undertaken the evening prior. Exercise increased (P<0.05) PGC-1α mRNA at 3 h post-exercise. Very low muscle glycogen attenuated the increase in PGC-1α mRNA expression compared with the LOW limbs in both the control (CON VLOW ~3.6-fold vs. CON LOW ~5.6-fold: P = 0.023, ES 1.22 Large) and CWI conditions (CWI VLOW ~2.4-fold vs. CWI LOW ~8.0 fold: P = 0.019, ES 1.43 Large). Furthermore, PGC-1α mRNA expression in the CWI-LOW trial was not significantly different to the CON LOW limb (P = 0.281, ES 0.67 Moderate). Data demonstrate that the previously reported effects of post-exercise CWI on PGC-1α expression (as regulated systemically via β-adrenergic mediated cell signalling) are offset in those conditions in which local stressors (i.e. high-intensity exercise and low muscle glycogen availability) have already sufficiently activated the AMPK- PGC-1α signaling axis. Additionally, data suggest that commencing exercise with very low muscle glycogen availability attenuates PGC-1α signaling

i-Rheo: Measuring the materials' linear viscoelastic properties “in a step”!

A new analytical technique for determining a materials' linear viscoelastic properties from a simple step-strain measurement is reported. The technique avoids the need for idealisation of real measurements. The technique involves evaluating the Fourier transforms of raw experimental data describing both the time-dependent stress and strain functions. A comparison with conventional linear oscillatory measurements for a diverse range of complex materials is made and the technique is shown to be superior to existing linear oscillatory measurements in all cases

Managing for RADical ecosystem change: applying the Resist-Accept- Direct (RAD) framework

Ecosystem transformation involves the emergence of persistent ecological or social–ecological systems that diverge, dramatically and irreversibly, from prior ecosystem structure and function. Such transformations are occurring at increasing rates across the planet in response to changes in climate, land use, and other factors. Consequently, a dynamic view of ecosystem processes that accommodates rapid, irreversible change will be critical for effectively conserving fish, wildlife, and other natural resources, and maintaining ecosystem services. However, managing ecosystems toward states with novel structure and function is an inherently unpredictable and difficult task. Managers navigating ecosystem transformation can benefit from considering broader objectives, beyond a traditional focus on resisting ecosystem change, by also considering whether accepting inevitable change or directing it along some desirable pathway is more feasible (that is, practical and appropriate) under some circumstances (the RAD framework). By explicitly acknowledging transformation and implementing an iterative RAD approach, natural resource managers can be deliberate and strategic in addressing profound ecosystem change

Search for squarks and gluinos in events with isolated leptons, jets and missing transverse momentum at s√=8 TeV with the ATLAS detector

The results of a search for supersymmetry in final states containing at least one isolated lepton (electron or muon), jets and large missing transverse momentum with the ATLAS detector at the Large Hadron Collider are reported. The search is based on proton-proton collision data at a centre-of-mass energy s√=8 TeV collected in 2012, corresponding to an integrated luminosity of 20 fb−1. No significant excess above the Standard Model expectation is observed. Limits are set on supersymmetric particle masses for various supersymmetric models. Depending on the model, the search excludes gluino masses up to 1.32 TeV and squark masses up to 840 GeV. Limits are also set on the parameters of a minimal universal extra dimension model, excluding a compactification radius of 1/R c = 950 GeV for a cut-off scale times radius (ΛR c) of approximately 30

Evidence for the Higgs-boson Yukawa coupling to tau leptons with the ATLAS detector

Results of a search for H → τ τ decays are presented, based on the full set of proton-proton collision data recorded by the ATLAS experiment at the LHC during 2011 and 2012. The data correspond to integrated luminosities of 4.5 fb−1 and 20.3 fb−1 at centre-of-mass energies of √s = 7 TeV and √s = 8 TeV respectively. All combinations of leptonic (τ → `νν¯ with ` = e, µ) and hadronic (τ → hadrons ν) tau decays are considered. An excess of events over the expected background from other Standard Model processes is found with an observed (expected) significance of 4.5 (3.4) standard deviations. This excess provides evidence for the direct coupling of the recently discovered Higgs boson to fermions. The measured signal strength, normalised to the Standard Model expectation, of µ = 1.43 +0.43 −0.37 is consistent with the predicted Yukawa coupling strength in the Standard Model

Measurement of the top pair production cross section in 8 TeV proton-proton collisions using kinematic information in the lepton plus jets final state with ATLAS

A measurement is presented of the $t\bar{t}$ inclusive production cross-section in $pp$ collisions at a center-of-mass energy of $\sqrt{s}=8$ TeV using data collected by the ATLAS detector at the CERN Large Hadron Collider. The measurement was performed in the lepton+jets final state using a data set corresponding to an integrated luminosity of 20.3 fb$^{-1}$. The cross-section was obtained using a likelihood discriminant fit and $b$-jet identification was used to improve the signal-to-background ratio. The inclusive $t\bar{t}$ production cross-section was measured to be $260\pm 1{\textrm{(stat.)}} ^{+22}_{-23} {\textrm{(syst.)}}\pm 8{\textrm{(lumi.)}}\pm 4{\mathrm{(beam)}}$ pb assuming a top-quark mass of 172.5 GeV, in good agreement with the theoretical prediction of $253^{+13}_{-15}$ pb. The $t\bar{t}\to (e,\mu)+{\mathrm{jets}}$ production cross-section in the fiducial region determined by the detector acceptance is also reported.Comment: Published version, 19 pages plus author list (35 pages total), 3 figures, 2 tables, all figures including auxiliary figures are available at http://atlas.web.cern.ch/Atlas/GROUPS/PHYSICS/PAPERS/TOPQ-2013-06

Measurement of the charge asymmetry in dileptonic Decays of top quark pairs in pp collisions at √ s = 7 TeV using the ATLAS detector

A measurement of the top-antitop (tt) charge asymmetry is presented using data corresponding to an integrated luminosity of 4.6 fb −1 of LHC pp collisions at a centre- of-mass energy of 7 TeV collected by the ATLAS detector. Events with two charged leptons, at least two jets and large missing transverse momentum are selected. Two observables are studied: A tt/C, based on the reconstructed tt final state. The asymmetries are measured to be A ll/C = 0.024 +/- 0.015 (stat.) +/- 0.009 (syst.) Att/C = 0.021 +/- 0.025 (stat.) +/- 0.017 (syst.) The measured values are in agreement with the Standard Model predictions

Fully transformer-based biomarker prediction from colorectal cancer histology: a large-scale multicentric study

Background: Deep learning (DL) can extract predictive and prognostic biomarkers from routine pathology slides in colorectal cancer. For example, a DL test for the diagnosis of microsatellite instability (MSI) in CRC has been approved in 2022. Current approaches rely on convolutional neural networks (CNNs). Transformer networks are outperforming CNNs and are replacing them in many applications, but have not been used for biomarker prediction in cancer at a large scale. In addition, most DL approaches have been trained on small patient cohorts, which limits their clinical utility. Methods: In this study, we developed a new fully transformer-based pipeline for end-to-end biomarker prediction from pathology slides. We combine a pre-trained transformer encoder and a transformer network for patch aggregation, capable of yielding single and multi-target prediction at patient level. We train our pipeline on over 9,000 patients from 10 colorectal cancer cohorts. Results: A fully transformer-based approach massively improves the performance, generalizability, data efficiency, and interpretability as compared with current state-of-the-art algorithms. After training on a large multicenter cohort, we achieve a sensitivity of 0.97 with a negative predictive value of 0.99 for MSI prediction on surgical resection specimens. We demonstrate for the first time that resection specimen-only training reaches clinical-grade performance on endoscopic biopsy tissue, solving a long-standing diagnostic problem. Interpretation: A fully transformer-based end-to-end pipeline trained on thousands of pathology slides yields clinical-grade performance for biomarker prediction on surgical resections and biopsies. Our new methods are freely available under an open source license