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Benveniste’s experiments – known in the lay press as the “water memory” phenomenon – are generally considered to be a closed case. However, the amount of data generated by twenty years of well-conducted experiments prevents closing the file so simply. An issue, which has been little highlighted so far, merits to be emphasized. Indeed, if Benveniste failed to persuade his peers of the value of his experiments, it was mainly because of a stumbling block, namely the difficulty of convincingly proving the causal relationship between the supposed cause (“informed water”) and the experimental outcomes in different biological models. To progress in the understanding of this phenomenon, we abandon the idea of any role of water in these experiments (“water memory” and its avatars). In other words, we assume that “controls” and “tests” that were evaluated were all physically identical; only their respective designations (labels) differentiated them. Since we state that there is no causal link between labels (“controls” vs. “tests”) and corresponding states of the biological system (no change vs. change), these variables are independent. Therefore, the key question is: “Is it possible to observe a correlation between independent variables that mimics a causal relationship but is itself not causal?” In this article, we show how simple considerations based on probability theory lead to describe non-classical correlations involving the experimenter. This probabilistic modelling allows to propose an alternative explanation to Benveniste’s experiments where water plays no role and where the place of the experimenter is central.

Beta-thalassemia major (β-TM) is a severe form of thalassemia caused by mutations in the β-globin gene, resulting in partial or complete deficiency of β-globin chains. This deficiency results in oxidative stress, dyserythropoiesis, and chronic anemia. Cytokine dependent hematopoietic cell linker (CLNK) belongs to the adaptor protein family and has the capacity to interact with multiple signaling proteins thereby modulating signal transduction. The aim of the present study was to examine CLNK in sera of β-TM patients and examine its association with iron overload biomarkers. Sixty β-TM patients, aged 3-12 years old and undergoing blood transfusions, and 30 healthy control children were recruited and CLNK, ferritin and iron status parameters were measured. The results showed a significant increase (p

Introduction: An epidemic of Coronavirus Disease 2019 (COVID-19) begun in December 2019 in China, causing a Public Health Emergency of International Concern. Among raised questions, clinical, laboratory, and imaging features have been partially characterized in some observational studies. No systematic reviews have been published on this matter. Methods: We performed a systematic literature review with meta-analysis, using three databases to assess clinical, laboratory, imaging features, and outcomes of COVID-19 confirmed cases. Observational studies, and also case reports, were included and analyzed separately. We performed a random-effects model meta-analysis to calculate the pooled prevalence and 95% confidence interval (95%CI). Results: 660 articles were retrieved (1/1/2020-2/23/2020). After screening by abstract/title, 27 articles were selected for full-text assessment. Of them, 19 were finally included for qualitative and quantitative analyses. Additionally, 39 case report articles were included and analyzed separately. For 656 patients, fever (88.7%, 95%CI 84.5-92.9%), cough (57.6%, 40.8-74.4%) and dyspnea (45.6%, 10.9-80.4%) were the most prevalent manifestations. Among the patients, 20.3% (95%CI 10.0-30.6%) required intensive care unit (ICU), with 32.8% presenting acute respiratory distress syndrome (ARDS) (95%CI 13.7-51.8), 6.2% (95%CI 3.1-9.3) with shock and 13.9% (95%CI 6.2-21.5%) of hospitalized patients with fatal outcomes (case fatality rate, CFR).Conclusion: COVID-19 brings a huge burden to healthcare facilities, especially in patients with comorbidities. ICU was required for approximately 20% of polymorbid, COVID-19 infected patients and this group was associated with a CFR of over 13%. As this virus spreads globally, countries need to urgently prepare human resources, infrastructure, and facilities to treat severe COVID-19.