Large expert-curated database for benchmarking document similarity detection in biomedical literature search

Document recommendation systems for locating relevant literature have mostly relied on methods developed a decade ago. This is largely due to the lack of a large offline gold-standard benchmark of relevant documents that cover a variety of research fields such that newly developed literature search techniques can be compared, improved and translated into practice. To overcome this bottleneck, we have established the RElevant LIterature SearcH consortium consisting of more than 1500 scientists from 84 countries, who have collectively annotated the relevance of over 180 000 PubMed-listed articles with regard to their respective seed (input) article/s. The majority of annotations were contributed by highly experienced, original authors of the seed articles. The collected data cover 76% of all unique PubMed Medical Subject Headings descriptors. No systematic biases were observed across different experience levels, research fields or time spent on annotations. More importantly, annotations of the same document pairs contributed by different scientists were highly concordant. We further show that the three representative baseline methods used to generate recommended articles for evaluation (Okapi Best Matching 25, Term Frequency–Inverse Document Frequency and PubMed Related Articles) had similar overall performances. Additionally, we found that these methods each tend to produce distinct collections of recommended articles, suggesting that a hybrid method may be required to completely capture all relevant articles. The established database server located at https://relishdb.ict.griffith.edu.au is freely available for the downloading of annotation data and the blind testing of new methods. We expect that this benchmark will be useful for stimulating the development of new powerful techniques for title and title/abstract-based search engines for relevant articles in biomedical research

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Impact of spatial organization on a novel auxotrophic interaction among soil microbes

A key prerequisite to achieve a deeper understanding of microbial communities and to engineer synthetic ones is to identify the individual metabolic interactions among key species and how these interactions are affected by different environmental factors. Deciphering the physiological basis of species-species and species-environment interactions in spatially organized environment requires reductionist approaches using ecologically and functionally relevant species. To this end, we focus here on a specific defined system to study the metabolic interactions in a spatial context among a plant-beneficial endophytic fungus Serendipita indica, and the soil-dwelling model bacterium Bacillus subtilis. Focusing on the growth dynamics of S. indica under defined conditions, we identified an auxotrophy in this organism for thiamine, which is a key co-factor for essential reactions in the central carbon metabolism. We found that S. indica growth is restored in thiamine-free media, when co-cultured with B. subtilis. The success of this auxotrophic interaction, however, was dependent on the spatial and temporal organization of the system; the beneficial impact of B. subtilis was only visible when its inoculation was separated from that of S. indica either in time or space. These findings describe a key auxotrophic interaction in the soil among organisms that are shown to be important for plant ecosystem functioning, and point to the potential importance of spatial and temporal organization for the success of auxotrophic interactions. These points can be particularly important for engineering of minimal functional synthetic communities as plant-seed treatments and for vertical farming under defined conditions

Impact of early haemodynamic goal-directed therapy in patients undergoing emergency surgery: an open prospective, randomised trial

Haemodynamic goal-directed therapies (GDT) may improve outcome following elective major surgery. So far, few data exist regarding haemodynamic optimization during emergency surgery. In this randomized, controlled trial, 50 surgical patients with hypovolemic or septic conditions were enrolled and we compared two algorithms of GDTs based either on conventional parameters and pressure pulse variation (control group) or on cardiac index, global end-diastolic volume index and stroke volume variation as derived from the PiCCO monitoring system (optimized group). Postoperative outcome was estimated by a composite index including major complications and by the Sequential Organ Failure Assessment (SOFA) Score within the first 3 days after surgery (POD1, POD2 and POD3). Data from 43 patients were analyzed (control group, N = 23; optimized group, N = 20). Similar amounts of fluid were given in the two groups. Intraoperatively, dobutamine was given in 45 % optimized patients but in no control patients. Major complications occurred more frequently in the optimized group [19 (95 %) versus 10 (40 %) in the control group, P < 0.001]. Likewise, SOFA scores were higher in the optimized group on POD1 (10.2 ± 2.5 versus 6.6 ± 2.2 in the control group, P = 0.001), POD2 (8.4 ± 2.6 vs 5.0 ± 2.4 in the control group, P = 0.002) and POD 3 (5.2 ± 3.6 and 2.2 ± 1.3 in the control group, P = 0.01). There was no significant difference in hospital mortality (13 % in the control group and 25 % in the optimized group). Haemodynamic optimization based on volumetric and flow PiCCO-derived parameters was associated with a less favorable postoperative outcome compared with a conventional GDT protocol during emergency surgery