Bacterial contamination of platelet concentrates (PCs) poses the highest transfusion-associated infectious risk, with Staphylococcus epidermidis being a predominant contaminant. Herein, the growth dynamics of 20 S. epidermidis strains in PCs and regular media were characterized. Strains were categorized as fast (short lag phase) or slow (long lag phase) growers in PCs. All strains were evaluated for the presence of the biofilm-associated icaAD genes by PCR, their capability to produce extracellular polysaccharide (slime) on Congo red agar plates and their ability to form surface-attached aggregates (biofilms) in glucose-supplemented trypticase soy broth (TSBg) using a crystal violet staining assay. A subset of four strains (two slow growers and two fast growers) was further examined for the ability for biofilm formation in PCs. Two of these strains carried the icAD genes, formed slime and produced biofilms in TSBg and PCs, while the other two strains, which did not carry icaAD, did not produce slime or form biofilms in TSBg. Although the two ica-negative slime-negative strains did not form biofilms in media, they displayed a biofilm-positive phenotype in PCs. Although all four strains formed biofilms in PCs, the two slow growers formed significantly more biofilms than the fast growers. Furthermore, growth experiments of the two ica-positive strains in plasma-conditioned platelet bags containing TSBg revealed that a slow grower isolate was more likely to escape culture-based screening than a fast grower strain. Therefore, this study provides novel evidence that links S. epidermidis biofilm formation with slow growth in PCs and suggests that slow-growing biofilm-positive S. epidermidis would be more likely to be missed with automate culture.

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BackgroundGliomas are the most common and aggressive tumors of the central nervous system. A robust and widely used blood-based biomarker for glioma has not yet been identified. In recent years, a plethora of new research on blood-based biomarkers for glial tumors has been published. In this review, we question which molecules, including proteins, nucleic acids, circulating cells, and metabolomics, are most promising blood-based biomarkers for glioma diagnosis, prognosis, monitoring and other purposes, and align them to the seminal processes of cancer.MethodsThe Pubmed and Embase databases were systematically searched. Biomarkers were categorized in the identified biomolecules and biosources. Biomarker characteristics were assessed using the area under the curve (AUC), accuracy, sensitivity and/or specificity values and the degree of statistical significance among the assessed clinical groups was reported.Results7,919 references were identified: 3,596 in PubMed and 4,323 in Embase. Following screening of titles, abstracts and availability of full-text, 262 articles were included in the final systematic review. Panels of multiple biomarkers together consistently reached AUCs >0.8 and accuracies >80% for various purposes but especially for diagnostics. The accuracy of single biomarkers, consisting of only one measurement, was far more variable, but single microRNAs and proteins are generally more promising as compared to other biomarker types.ConclusionPanels of microRNAs and proteins are most promising biomarkers, while single biomarkers such as GFAP, IL-10 and individual miRNAs also hold promise. It is possible that panels are more accurate once these are involved in different, complementary cancer-related molecular pathways, because not all pathways may be dysregulated in cancer patients. As biomarkers seem to be increasingly dysregulated in patients with short survival, higher tumor grades and more pathological tumor types, it can be hypothesized that more pathways are dysregulated as the degree of malignancy of the glial tumor increases. Despite, none of the biomarkers found in the literature search seem to be currently ready for clinical implementation, and most of the studies report only preliminary application of the identified biomarkers. Hence, large-scale validation of currently identified and potential novel biomarkers to show clinical utility is warranted.