A Comparison of Shiga-Toxin 2 Bacteriophage from Classical Enterohemorrhagic Escherichia coli Serotypes and the German E. coli O104:H4 Outbreak Strain

Escherichia coli O104:H4 was associated with a severe foodborne disease outbreak originating in Germany in May 2011. More than 4000 illnesses and 50 deaths were reported. The outbreak strain was a typical enteroaggregative E. coli (EAEC) that acquired an antibiotic resistance plasmid and a Shiga-toxin 2 (Stx2)-encoding bacteriophage. Based on whole-genome phylogenies, the O104:H4 strain was most closely related to other EAEC strains; however, Stx2-bacteriophage are mobile, and do not necessarily share an evolutionary history with their bacterial host. In this study, we analyzed Stx2-bacteriophage from the E. coli O104:H4 outbreak isolates and compared them to all available Stx2-bacteriophage sequences. We also compared Stx2 production by an E. coli O104:H4 outbreak-associated isolate (ON-2011) to that of E. coli O157:H7 strains EDL933 and Sakai. Among the E. coli Stx2-phage sequences studied, that from O111:H- strain JB1-95 was most closely related phylogenetically to the Stx2-phage from the O104:H4 outbreak isolates. The phylogeny of most other Stx2-phage was largely concordant with their bacterial host genomes. Finally, O104:H4 strain ON-2011 produced less Stx2 than E. coli O157:H7 strains EDL933 and Sakai in culture; however, when mitomycin C was added, ON-2011 produced significantly more toxin than the E. coli O157:H7 strains. The Stx2-phage from the E. coli O104:H4 outbreak strain and the Stx2-phage from O111:H- strain JB1-95 likely share a common ancestor. Incongruence between the phylogenies of the Stx2-phage and their host genomes suggest the recent Stx2-phage acquisition by E. coli O104:H4. The increase in Stx2-production by ON-2011 following mitomycin C treatment may or may not be related to the high rates of hemolytic uremic syndrome associated with the German outbreak strain. Further studies are required to determine whether the elevated Stx2-production levels are due to bacteriophage or E. coli O104:H4 host related factors

A Signature of Maternal Anti-Fetal Rejection in Spontaneous Preterm Birth: Chronic Chorioamnionitis, Anti-Human Leukocyte Antigen Antibodies, and C4d

Chronic chorioamnionitis is found in more than one-third of spontaneous preterm births. Chronic chorioamnionitis and villitis of unknown etiology represent maternal anti-fetal cellular rejection. Antibody-mediated rejection is another type of transplantation rejection. We investigated whether there was evidence for antibody-mediated rejection against the fetus in spontaneous preterm birth.This cross-sectional study included women with (1) normal pregnancy and term delivery (n = 140) and (2) spontaneous preterm delivery (n = 140). We analyzed maternal and fetal sera for panel-reactive anti-HLA class I and class II antibodies, and determined C4d deposition on umbilical vein endothelium by immunohistochemistry. Maternal anti-HLA class I seropositivity in spontaneous preterm births was higher than in normal term births (48.6% vs. 32.1%, p = 0.005). Chronic chorioamnionitis was associated with a higher maternal anti-HLA class I seropositivity (p<0.01), significant in preterm and term birth. Villitis of unknown etiology was associated with increased maternal and fetal anti-HLA class I and II seropositivity (p<0.05, for each). Fetal anti-HLA seropositivity was closely related to maternal anti-HLA seropositivity in both groups (p<0.01, for each). C4d deposition on umbilical vein endothelium was more frequent in preterm labor than term labor (77.1% vs. 11.4%, p<0.001). Logistic regression analysis revealed that chronic chorioamnionitis (OR = 6.10, 95% CI 1.29–28.83), maternal anti-HLA class I seropositivity (OR = 5.90, 95% CI 1.60–21.83), and C4d deposition on umbilical vein endothelium (OR = 36.19, 95% CI 11.42–114.66) were associated with preterm labor and delivery.A major subset of spontaneous preterm births has a signature of maternal anti-fetal cellular and antibody-mediated rejections with links to fetal graft-versus-host disease and alloimmune reactions

Breast MRI: guidelines from the European Society of Breast Imaging

The aim of breast MRI is to obtain a reliable evaluation of any lesion within the breast. It is currently always used as an adjunct to the standard diagnostic procedures of the breast, i.e., clinical examination, mammography and ultrasound. Whereas the sensitivity of breast MRI is usually very high, specificity—as in all breast imaging modalities—depends on many factors such as reader expertise, use of adequate techniques and composition of the patient cohorts. Since breast MRI will always yield MR-only visible questionable lesions that require an MR-guided intervention for clarification, MRI should only be offered by institutions that can also offer a MRI-guided breast biopsy or that are in close contact with a site that can perform this type of biopsy for them. Radiologists involved in breast imaging should ensure that they have a thorough knowledge of the MRI techniques that are necessary for breast imaging, that they know how to evaluate a breast MRI using the ACR BI-RADS MRI lexicon, and most important, when to perform breast MRI. This manuscript provides guidelines on the current best practice for the use of breast MRI, and the methods to be used, from the European Society of Breast Imaging (EUSOBI)

Paternal effects on early embryogenesis

Historically, less attention has been paid to paternal effects on early embryogenesis than maternal effects. However, it is now apparent that certain male factor infertility phenotypes are associated with increased DNA fragmentation and/or chromosome aneuploidies that may compromise early embryonic development. In addition, there is a growing body of evidence that the fertilizing sperm has more function than just carrying an intact, haploid genome. The paternally inherited centrosome is essential for normal fertilization, and the success of higher order chromatin packaging may impact embryogenesis. Epigenetic modifications of sperm chromatin may contribute to the reprogramming of the genome, and sperm delivered mRNA has also been hythesized to be necessary for embryogenesis. There is less information about the epigenetic factors affecting embryogenesis than genetic factors, but the epigenetics of gamete and early embryogenesis is a rapidly advancing field

Bridging the gap between field experiments and machine learning: the EC H2020 B-GOOD project as a case study towards automated predictive health monitoring of honey bee colonies

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies’ exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony’s health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project’s data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping