Animal cells counteract oxidative stress and electrophilic attack through coordinated expression of a set of detoxifying and antioxidant enzyme genes mediated by transcription factor Nrf2. In unstressed cells, Nrf2 appears to be sequestered in the cytoplasm via association with an inhibitor protein, Keap1. Here, by using the yeast two-hybrid screen, human Keap1 has been identified as a partner of the nuclear protein prothymosin ␣. The in vivo and in vitro data indicated that the prothymosin ␣-Keap1 interaction is direct, highly specific, and functionally relevant. Furthermore, we showed that Keap1 is a nuclear-cytoplasmic shuttling protein equipped with a nuclear export signal that is important for its inhibitory action. Prothymosin ␣ was able to liberate Nrf2 from the Nrf2-Keap1 inhibitory complex in vitro through competition with Nrf2 for binding to the same domain of Keap1. In vivo, the level of Nrf2-dependent transcription was correlated with the intracellular level of prothymosin ␣ by using prothymosin ␣ overproduction and mRNA interference approaches. Our data attribute to prothymosin ␣ the role of intranuclear dissociator of the Nrf2-Keap1 complex, thus revealing a novel function for prothymosin ␣ and adding a new dimension to the molecular mechanisms underlying expression of oxidative stress-protecting genes.

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Introduction Coronavirus disease 2019 (COVID‐19) is characterized by a high contagiousness requiring isolation measures. At this time, diagnosis is based on the positivity of specific RT‐PCR and/or chest computed tomography scan, which are time‐consuming and may delay diagnosis. Complete blood count (CBC) can potentially contribute to the diagnosis of COVID‐19. We studied whether the analysis of cellular population data (CPD), provided as part of CBC‐Diff analysis by the DxH 800 analyzers (Beckman Coulter), can help to identify SARS‐CoV‐2 infection. Methods Cellular population data of the different leukocyte subpopulations were analyzed in 137 controls, 322 patients with proven COVID‐19 (COVID+), and 285 patients for whom investigations were negative for SARS‐CoV‐2 infection (COVID−). When CPD of COVID+ were different from controls and COVID− patients, we used receiver operating characteristic analysis to test the discriminating capacity of the individual parameters. Using a random forest classifier, we developed the algorithm based on the combination of 4 monocyte CPD to discriminate COVID+ from COVID− patients. This algorithm was tested prospectively in a series of 222 patients referred to the emergency unit. Results Among the 222 patients, 86 were diagnosed as COVID‐19 and 60.5% were correctly identified using the discriminating protocol. Among the 136 COVID− patients, 10.3% were misclassified (specificity 89.7%, sensitivity 60.5%). False negatives were observed mainly in patients with a low inflammatory state whereas false positives were mainly seen in patients with sepsis. Conclusion Consideration of CPD could constitute a first step and potentially aid in the early diagnosis of COVID‐19.

Objectives Sepsis is a time-dependent and life-threating condition. Despite several biomarkers are available, none of them is completely reliable for the diagnosis. This study aimed to evaluate the diagnostic utility of monocyte distribution width (MDW) to early detect sepsis in adult patients admitted in the Emergency Department (ED) with a five part differential analysis as part of the standard clinical practice. Methods A prospective cohort study was conducted on 985 patients aged from 18 to 96 and included in the study between November 2019 and December 2019. Enrolled subjects were classified into four groups based on sepsis-2 diagnostic criteria: control, Systemic Inflammatory Response Syndrome (SIRS), infection and sepsis. The hematology analyzer DxH 900 (Beckman Coulter Inc.) provides the new reportable parameter MDW, included in the leukocyte 5 part differential analysis, cleared by Food and Drug administration (FDA) and European Community In-Vitro-Diagnostic Medical Device (CE IVD) marked as early sepsis indicator (ESId). Results MDW was able to differentiate the sepsis group from all other groups with Area Under the Curve (AUC) of 0.849, sensitivity of 87.3% and specificity of 71.7% at cut-off of 20.1. MDW in combination with white blood cell (WBC) improves the performance for sepsis detection with a sensitivity increased up to 96.8% when at least one of the two biomarkers are abnormal, and a specificity increased up to 94.6% when both biomarkers are abnormal. Conclusions MDW can predict sepsis increasing the clinical value of Leukocyte 5 Part Differential analysis and supporting the clinical decision making in sepsis management at the admission to the ED.