Introduction: Translational science has gained prominence in medicine, but there is still much work to be done before scientific results are used optimally and incorporated into everyday health practice. As the main focus is still on generating new scientific data with financial resources primarily available for that purpose, other activities that are necessary in the transition from research to community benefit are considered less needy. The European Statistical Office of the European Commission has recently reported that 1.7 million people under 75 years of age died in Europe in 2016, with around 1.2 million of those deaths being avoidable through effective primary prevention and public health intervention. Therefore, Academia Europaea, one of the five Pan-European networks that form SAPEA (Science Advice for Policy by European Academies), a key element of the European Commission’s Scientific Advice Mechanism (SAM), has launched a project to develop a model to facilitate and accelerate the utilisation of scientific knowledge for public and community benefit. Methods: During the process, leaders in the field, including prominent basic and clinical researchers, editors-in-chief of high-impact journals publishing translational research articles, translational medicine (TM) centre leaders, media representatives, academics and university leaders, developed the TM cycle, a new model that we believe could significantly advance the development of TM. Results: This model focuses equally on the acquisition of new scientific results healthcare, understandable and digestible summation of results, and their communication to all participants. We have also renewed the definition in TM, identified challenges and recommended solutions. Conclusion: The authors, including senior officers of Academia Europaea, produced this document to serve as a basis for revising thinking on TM with the end result of enabling more efficient and cost-effective healthcare.

Background: Probiotics are often used to prevent antibiotic-induced low-diversity dysbiosis, however their effect is not yet sufficiently summarized in this regard. We aimed to investigate the effects of concurrent probiotic supplementation on gut microbiome composition during antibiotic therapy.Methods: We performed a systematic review and meta-analysis of randomized controlled trials reporting the differences in gut microbiome diversity between patients on antibiotic therapy with and without concomitant probiotic supplementation. The systematic search was performed in three databases (MEDLINE (via PubMed), Embase, and Cochrane Central Register of Controlled Trials (CENTRAL)) without filters on 15 October 2021. A random-effects model was used to estimate pooled mean differences (MD) with 95% confidence intervals (CI). This review was registered on PROSPERO (CRD42021282983).Results: Of 11,769 identified articles, 15 were eligible in the systematic review and 5 in the meta-analyses. Quantitative data synthesis for Shannon (MD = 0.23, 95% CI: [(−)0.06–0.51]), Chao1 (MD = 11.59 [(−)18.42–41.60]) and observed OTUs (operational taxonomic unit) (MD = 17.15 [(−)9.43–43.73]) diversity indices revealed no significant difference between probiotic supplemented and control groups. Lacking data prevented meta-analyzing other diversity indices; however, most of the included studies reported no difference in the other reported α- and ß-diversity indices between the groups. Changes in the taxonomic composition varied across the eligible studies but tended to be similar in both groups. However, they showed a potential tendency to restore baseline levels in both groups after 3–8 weeks.This is the first meta-analysis and the most comprehensive review of the topic to date using high quality methods. The limited number of studies and low sample sizes are the main limitations of our study. Moreover, there was high variability across the studies regarding the indication of antibiotic therapy and the type, dose, and duration of antimicrobials and probiotics.Conclusions: Our results showed that probiotic supplementation during antibiotic therapy was not found to be influential on gut microbiome diversity indices. Defining appropriate microbiome diversity indices, their standard ranges, and their clinical relevance would be crucial.

Introduction: The prevalence of Helicobacter pylori infection (HPI) has been decreasing in developed countries, with an increasing prevalence of Barrett's esophagus (BE) and esophageal adenocarcinoma (EAC) at the same time. The aim of our meta‐analysis was to quantify the risk of BE in the context of HPI.Methods: A systematic search was conducted in 3 databases for studies on BE with data on prevalence of HPI from inception until December 2016. Odds ratios for BE in HPI were calculated by the random effects model with subgroup analyses for geographical location, presence of dysplasia in BE, and length of the BE segment.Results: Seventy‐two studies were included in the meta‐analysis, including 84 717 BE cases and 390 749 controls. The overall analysis showed that HPI reduces the risk of BE; OR = 0.68 (95% CI: 0.58‐0.79, P < .001). Subgroup analyses revealed risk reduction in Asia OR = 0.53 (95% CI: 0.33‐0.84, P = .007), Australia OR = 0.56 (95% CI: 0.39‐0.80, P = .002), Europe OR = 0.77 (95% CI: 0.60‐0.98, P = .035), and North‐America OR = 0.59 (95% CI: 0.47‐0.74, P < .001). The risk was significantly reduced for dysplastic BE, OR = 0.37 (95% CI: 0.26‐0.51, P < .001) for non‐dysplastic BE, OR = 0.51 (95% CI: 0.35‐0.75, P = .001), and for long segment BE, OR = 0.25 (95% CI: 0.11‐0.59, P = .001) in case of HPI.Conclusions: This extensive meta‐analysis provides additional evidence that HPI is associated with reduced risk of BE. Subgroup analyses confirmed that this risk reduction is independent of geographical location. HPI is associated with significantly lower risk of dysplastic, non‐dysplastic, and long segment BE.

Background: The role of artificial and bioartificial liver support systems in acute-on-chronic liver failure (ACLF) is still controversial. We aimed to perform the first network meta-analysis comparing and ranking different liver support systems and standard medical therapy (SMT) in patients with ACLF. Methods: The study protocol was registered with PROSPERO (CRD42020155850). A systematic search was conducted in five databases. We conducted a Bayesian network meta-analysis of randomized controlled trials assessing the effect of artificial or bioartificial liver support systems on survival in patients with ACLF. Ranking was performed by calculating the surface under cumulative ranking (SUCRA) curve values. The RoB2 tool and a modified GRADE approach were used for the assessment of the risk of bias and quality of evidence (QE). Results: In the quantitative synthesis 16 trials were included, using MARS®, Prometheus®, ELAD®, plasma exchange (PE) and BioLogic-DT®. Overall (OS) and transplant-free (TFS) survival were assessed at 1 and 3 months. PE significantly improved 3-month OS compared to SMT (RR 0.74, CrI: 0.6–0.94) and ranked first on the cumulative ranking curves for both OS outcomes (SUCRA: 86% at 3 months; 77% at 1 month) and 3-month TFS (SUCRA: 87%) and second after ELAD for 1-month TFS (SUCRA: 76%). Other comparisons did not reach statistical significance. QE was moderate for PE concerning 1-month OS and both TFS outcomes. Other results were of very low certainty. Conclusion: PE seems to be the best currently available liver support therapy in ACLF regarding 3-month OS. Based on the low QE, randomized trials are needed to confirm our findings for already existing options and to introduce new devices.

Coronavirus Disease 2019 (COVID-19) is a viral infection caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with a mortality rate of 3-7% [1]. The high mortality results from fulminant pneumonia leading to acute respiratory distress syndrome and multiple organ failure [2, 3]. Initial reports suggest that comorbidities cause a more severe course of infection and a poorer prognosis [4, 5]. Considering the fast spread and high mortality of COVID-19, it is necessary to understand the possible risk factors affecting its progression. We aimed to perform a systematic search to evaluate the potential role of all reported comorbidities on the disease course. Details of our report are provided in Supplementary file 1. We searched MEDLINE, Embase, Cochrane Central Register of Controlled Trials, Web of Science, and Scopus between 01/01/2020 and 05/11/2020. The main outcomes were mortality, intensive care unit (ICU) admission and severity. Definitions of the investigated outcomes are available in Supplementary file 2, Table 2. Odds ratios (OR) with 95% confidence intervals (CI) were calculated to objectify the association between comorbidities and the outcomes by the random-effects model. The study was registered on PROSPERO (CRD42020176781). Of 33,987 records screened, 61 cohort studies with 31,089 (median 162; IQR: 103-338) patients were included in the meta-analysis. The overall mortality rate was 10.0%, 19.9% of patients needed intensive, while the reported severity was 24.0%. Underlying chronic