A host signature based on TRAIL, IP-10, and CRP for reducing antibiotic overuse in children by differentiating bacterial from viral infections: a prospective, multicentre cohort study

Objectives: Identifying infection aetiology is essential for appropriate antibiotic use. Previous studies have shown that a host-protein signature consisting of TNF-related apoptosis-induced ligand (TRAIL), interferon-γ-induced protein-10 (IP-10), and C-reactive protein (CRP) can accurately differentiate bacterial from viral infections. Methods: This prospective, multicentre cohort study, entitled AutoPilot-Dx, aimed to validate signature performance and to estimate its potential impact on antibiotic use across a broad paediatric population (>90 days to 18 years) with respiratory tract infections, or fever without source, at emergency departments and wards in Italy and Germany. Infection aetiology was adjudicated by experts based on clinical and laboratory investigations, including multiplex PCR and follow-up data. Results: In total, 1140 patients were recruited (February 2017–December 2018), of which 1008 met the eligibility criteria (mean age 3.5 years, 41.9% female). Viral and bacterial infections were adjudicated for 628 (85.8%) and 104 (14.2%) children, respectively; 276 patients were assigned an indeterminate reference standard outcome. For the 732 children with reference standard aetiology, the signature discriminated bacterial from viral infections with a sensitivity of 93.7% (95%CI 88.7–98.7), a specificity of 94.2% (92.2–96.1), positive predictive value of 73.0% (65.0–81.0), and negative predictive value of 98.9% (98.0–99.8); in 9.8% the test results were equivocal. The signature performed consistently across different patient subgroups and detected bacterial immune responses in viral PCR-positive patients. Conclusions: The findings validate the high diagnostic performance of the TRAIL/IP-10/CRP signature in a broad paediatric cohort, and support its potential to reduce antibiotic overuse in children with viral infections

Directing carbohydrates toward ethanol using mesophilic microbial communities

Bioethanol production is an established biotechnological process. Margins are low which prevent a larger scale production of bioethanol. As a large part of the production cost is due to the feedstock, the use of low value unsterile feedstocks fermented by microbial communities will enable a more cost-competitive bioethanol production. To select for high yield ethanol producing communities, three selective conditions are proposed: acid washing of the cells after fermentation, a low pH (<5) during the fermentation and microaerobiosis at the start of the fermentation. Ethanol producers, such as Zymomonas species and yeasts, compete for carbohydrates with volatile fatty acid and lactic acid producing bacteria. Creating effective consortia of lactic acid bacteria and homo-ethanol producers at low pH will lead to robust and competitive ethanol yields and titres. A conceptual design of an ecology-based bioethanol production process is proposed using food waste to produce bioethanol, electricity, digestate and heat.BT/Environmental BiotechnologyApplied Science

Unraveling the literature chaos around free ammonia inhibition in anaerobic digestion

This review aims at providing a unified methodology for free ammonia nitrogen (FAN) calculation in anaerobic digesters, also identifying the factors causing the huge disparity in FAN inhibitory limits. Results show that assuming ideal equilibria overestimates the FAN concentrations up to 37% when compared to MINTEQA2 Equilibrium Speciation Model, used as reference. The Davies equation led to major improvements. Measuring the concentrations of NH , Na and K was enough to achieve major corrections. The best compromise between complexity and accuracy was achieved with a novel modified Davies equation, with systematic differences in FAN concentrations of 2% when compared to MINTEQA2. Applying this modified Davies equation, data from the literature (1590 data points from over 50 scientific studies) were used to recalculate FAN inhibitory limits using a clustering approach. This procedure allowed to link inhibition resilience with operational conditions and microbial communities, providing also generalized values of inhibitory constants. The results showed that pH and temperature are the main factors affecting FAN inhibition, with thermophilic systems having a higher resilience towards FAN inhibition. The clustering results showed that Methanosaeta-dominated reactors have the lowest resilience towards FAN, verifying the relatively low inhibition limits for acetoclastic archaea. Mixotrophic Methanosarcina dominated at intermediate FAN concentrations, being more resistant than Methanosaeta but less resilient than hydrogenotrophic archaea. Methanoculleus appeared as the most resilient methanogen. This article provides general guidelines for accurate FAN calculation, explaining also how FAN resilience relates to the operational conditions and the microbial communities, underlying the importance of microbial adaptation