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Findings suggest children who are chronically victimized may be at a developmental disadvantage compared to children who report little or declining peer victimization over time. © 2020 Wiley Periodicals, Inc.Though the pathogenesis of acute myeloid leukemia (AML) is still unknown, accumulating evidence has revealed that immune response plays a vital part in the pathogenesis. Here, we investigated the involvement of 21 single-nucleotide polymorphisms (SNPs) of immuno-related genes, including cytokines (IL2, IL4, IL9, IL12A, IL22, IFNG, and TGFB1), transcriptional regulatory genes (TBX21, STAT1, STAT3, STAT5B, STAT6, GATA3, FOXP3, and IRF4), and others (IL2RA IL6R NFKBIA), in 269 AML inpatients and 200 healthy controls. Furthermore, we analyzed the relationship between the SNPs and clinical characteristics. Immuno-related SNP genotyping was performed on the Sequenom MassARRAY iPLEX platform. All the SNPs in healthy controls were consistent with Hardy-Weinberg equilibrium. All final p values were adjusted by Bonferroni multiple testing. Our results showed that IL22 (rs2227491) was significantly associated with the white blood cell (WBC) counts. STAT5B (rs6503691) showed a close relationship with the recurrent genetic abnormalities in patients with AML. We verified the negatively independent effect of age and risk of cytogenetics on overall survival (OS). More importantly, the GG genotype of IL12A (rs6887695) showed a negative impact on AML prognosis independently. Furthermore, the relative expression of IL12 was decreased in GG genotype, no matter under codominant or recessive model. However, no correlation was observed between the SNPs mentioned above and disease susceptibility, risk stratification, and survival. Our findings suggest that immuno-related gene polymorphisms are associated with prognosis in AML, which may perform as novel inspection targets for AML patients. This article is protected by copyright. All rights reserved.CONTEXT NCI-H295 cells are the most widely used model for adrenal steroidogenesis and adrenocortical carcinoma and have been used for decades in laboratories worldwide. However, reported steroidogenic properties differ considerably. OBJECTIVE To evaluate heterogeneity of steroidogenesis among NCI-H295 cell strains, clarify the influence of culture media and test response to inhibitors of steroidogenesis by using liquid chromatography tandem mass spectrometry (LC-MS/MS). METHODS NCI-H295 cells were obtained from two cell banks and cultivated in different media. An LC-MS/MS-based panel analysis of thirteen steroids was adapted for cell culture supernatant. Cells were treated with metyrapone, abiraterone and mitotane. RESULTS Mineralocorticoid synthesis was strongly affected by passaging as reflected by reduction of aldosterone secretion from 0.158±0.006 to 0.017±0.001 µg/106 cells (p4-fold difference (40.6±5.5 vs. 182.1±23 µg/106 cells) and reflected differential activation of the glucocorticoid pathway. Exposure to abiraterone, metyrapone and mitotane resulted in characteristic steroidogenic profiles consistent with known mechanism of drug action with considerable differences in metabolites upstream of the blocked enzyme. CONCLUSION We demonstrate that steroid hormone secretion in NCI-H295 cells is strongly affected by the individual strain, passage and growing conditions. These factors should be taken into account in the evaluation of experiments analyzing steroid parameters directly or as surrogate parameters of cell viability. © Georg Thieme Verlag KG Stuttgart · New York.BACKGROUND  Managing research data in biomedical informatics research requires solid data governance rules to guarantee sustainable operation, as it generally involves several professions and multiple sites. As every discipline involved in biomedical research applies its own set of tools and methods, research data as well as applied methods tend to branch out into numerous intermediate and output data objects, making it very difficult to reproduce research results. OBJECTIVES  This article gives an overview of our implementation status applying the Findability, Accessibility, Interoperability and Reusability (FAIR) Guiding Principles for scientific data management and stewardship onto our research data management pipeline focusing on the software tools that are in use. 3-AP in vivo METHODS  We analyzed our progress FAIRificating the whole data management pipeline, from processing non-FAIR data up to data usage. We looked at software tools for data integration, data storage, and data usage as well as how the FAIR Guiding Principles helped to choose appropriate tools for each task. RESULTS  We were able to advance the degree of FAIRness of our data integration as well as data storage solutions, but lack enabling more FAIR Guiding Principles regarding Data Usage. Existing evaluation methods regarding the FAIR Guiding Principles (FAIRmetrics) were not applicable to our analysis of software tools. CONCLUSION  Using the FAIR Guiding Principles, we FAIRificated relevant parts of our research data management pipeline improving findability, accessibility, interoperability and reuse of datasets and research results. We aim to implement the FAIRmetrics to our data management infrastructure and-where required-to contribute to the FAIRmetrics for research data in the biomedical informatics domain as well as for software tools to achieve a higher degree of FAIRness of our research data management pipeline. Georg Thieme Verlag KG Stuttgart · New York.OBJECTIVES  The current study sought to evaluate whether nursing narratives can be used to predict postoperative length of hospital stay (LOS) following curative surgery for ovarian cancer. METHODS  A total of 33 patients, aged over 65 years, underwent curative surgery for newly diagnosed ovarian cancer between 2008 and 2012. Based on the median postoperative LOS, patients were divided into two groups long-stay (>12 days; n = 13) and short-stay (≤12 days; n = 20). Patterns in nursing narratives were examined and compared through a quantitative analysis. Specifically, the total number (TN) of narratives pertaining to care and the standardized number (SN), which was calculated by dividing the TN by the LOS, were compared. Experts evaluated the relevance of the phrases extracted. LOS was then predicted using machine learning techniques. RESULTS  The median postoperative LOS was 18 days (interquartile range [IQR] 16-24 days) in the long-stay group and 9.5 days (IQR 8-11.25 days) in the short-stay group. In the long-stay group, surgery duration was longer.