Perspectives on the use of transcriptomics to advance biofuels

As a field within the energy research sector, bioenergy is continuously expanding. Although much has been achieved and the yields of both ethanol and butanol have been improved, many avenues of research to further increase these yields still remain. This review covers current research related with transcriptomics and the application of this high-throughput analytical tool to engineer both microbes and plants with the penultimate goal being better biofuel production and yields. The initial focus is given to the responses of fermentative microbes during the fermentative production of acids, such as butyric acid, and solvents, including ethanol and butanol. As plants offer the greatest natural renewable source of fermentable sugars within the form of lignocellulose, the second focus area is the transcriptional responses of microbes when exposed to plant hydrolysates and lignin-related compounds. This is of particular importance as the acid/base hydrolysis methods commonly employed to make the plant-based cellulose available for enzymatic hydrolysis to sugars also generates significant amounts of lignin-derivatives that are inhibitory to fermentative bacteria and microbes. The article then transitions to transcriptional analyses of lignin-degrading organisms, such as Phanerochaete chrysosporium, as an alternative to acid/base hydrolysis. The final portion of this article will discuss recent transcriptome analyses of plants and, in particular, the genes involved in lignin production. The rationale behind these studies is to eventually reduce the lignin content present within these plants and, consequently, the amount of inhibitors generated during the acid/base hydrolysis of the lignocelluloses. All four of these topics represent key areas where transcriptomic research is currently being conducted to identify microbial genes and their responses to products and inhibitors as well as those related with lignin degradation/formation.clos

Evaluation of appendicitis risk prediction models in adults with suspected appendicitis

Background Appendicitis is the most common general surgical emergency worldwide, but its diagnosis remains challenging. The aim of this study was to determine whether existing risk prediction models can reliably identify patients presenting to hospital in the UK with acute right iliac fossa (RIF) pain who are at low risk of appendicitis. Methods A systematic search was completed to identify all existing appendicitis risk prediction models. Models were validated using UK data from an international prospective cohort study that captured consecutive patients aged 16–45 years presenting to hospital with acute RIF in March to June 2017. The main outcome was best achievable model specificity (proportion of patients who did not have appendicitis correctly classified as low risk) whilst maintaining a failure rate below 5 per cent (proportion of patients identified as low risk who actually had appendicitis). Results Some 5345 patients across 154 UK hospitals were identified, of which two‐thirds (3613 of 5345, 67·6 per cent) were women. Women were more than twice as likely to undergo surgery with removal of a histologically normal appendix (272 of 964, 28·2 per cent) than men (120 of 993, 12·1 per cent) (relative risk 2·33, 95 per cent c.i. 1·92 to 2·84; P < 0·001). Of 15 validated risk prediction models, the Adult Appendicitis Score performed best (cut‐off score 8 or less, specificity 63·1 per cent, failure rate 3·7 per cent). The Appendicitis Inflammatory Response Score performed best for men (cut‐off score 2 or less, specificity 24·7 per cent, failure rate 2·4 per cent). Conclusion Women in the UK had a disproportionate risk of admission without surgical intervention and had high rates of normal appendicectomy. Risk prediction models to support shared decision‐making by identifying adults in the UK at low risk of appendicitis were identified

Search for the Zγ decay mode of new high-mass resonances in pp collisions at s = 13 TeV with the ATLAS detector

This letter presents a search for narrow, high-mass resonances in the Zγ final state with the Z boson decaying into a pair of electrons or muons. The TeV pp collision data were recorded by the ATLAS detector at the CERN Large Hadron Collider and have an integrated luminosity of 140 fb−1. The data are found to be in agreement with the Standard Model background expectation. Upper limits are set on the resonance production cross section times the decay branching ratio into Zγ. For spin-0 resonances produced via gluon–gluon fusion, the observed limits at 95% confidence level vary between 65.5 fb and 0.6 fb, while for spin-2 resonances produced via gluon–gluon fusion (or quark–antiquark initial states) limits vary between 77.4 (76.1) fb and 0.6 (0.5) fb, for the mass range from 220 GeV to 3400 GeV

Pursuit of paired dijet resonances in the Run 2 dataset with ATLAS

New particles with large masses that decay into hadronically interacting particles are predicted by many models of physics beyond the Standard Model. A search for a massive resonance that decays into pairs of dijet resonances is performed using..

Fast b-tagging at the high-level trigger of the ATLAS experiment in LHC Run 3

The ATLAS experiment relies on real-time hadronic jet reconstruction and b-tagging to record fully hadronic events containing b-jets. These algorithms require track reconstruction, which is computationally expensive and could overwhelm the high-level-trigger farm, even at the reduced event rate that passes the ATLAS first stage hardware-based trigger. In LHC Run 3, ATLAS has mitigated these computational demands by introducing a fast neural-network-based b-tagger, which acts as a low-precision filter using input from hadronic jets and tracks. It runs after a hardware trigger and before the remaining high-level-trigger reconstruction. This design relies on the negligible cost of neural-network inference as compared to track reconstruction, and the cost reduction from limiting tracking to specific regions of the detector. In the case of Standard Model HH → bb̅bb̅, a key signature relying on b-jet triggers, the filter lowers the input rate to the remaining high-level trigger by a factor of five at the small cost of reducing the overall signal efficiency by roughly 2%

Search for a new pseudoscalar decaying into a pair of muons in events with a top-quark pair at s=13 TeV with the ATLAS detector

A search for a new pseudoscalar Formula Presented-boson produced in events with a top-quark pair, where the Formula Presented-boson decays into a pair of muons, is performed using Formula Presented Formula Presented collision data collected with the ATLAS detector at the LHC, corresponding to an integrated luminosity of Formula Presented. The search targets the final state where only one top quark decays to an electron or muon, resulting in a signature with three leptons Formula Presented and Formula Presented. No significant excess of events above the Standard Model expectation is observed and upper limits are set on two signal models: Formula Presented and Formula Presented with Formula Presented, Formula Presented, where Formula Presented, in the mass ranges Formula Presented and Formula Presented