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The Eyberg Child Behavior Inventory (ECBI) is one of the most widely used and well-validated parent rating scales for children’s disruptive behavior. This screening instrument is a short, targetted and easy to implement inventory with good psychometric properties and is normed for different countries, among which the United States, Spain, Sweden and Norway. The ECBI has been successfully used for research and clinical purposes, in several countries including The Netherlands. To date, Dutch studies have relied on Scandinavian or US norm scores. However, this may be problematic because of cross-cultural differences in the degree to which certain behaviors are seen as problematic by parents. The main goal of this paper therefore was to obtain norm scores for The Netherlands among 6462 Dutch children aged 4 to 8 years (Mage = 6.37 years; SD = 1.32; 50.6% boys). In line with previous research, we found small differences on the mean sum scores across children of different ages (intensity scale) and gender (intensity and problem scale). Therefore, Dutch norm scores were provided age- and gender specific. Our results showed that disruptive behavior of children in the most rural areas was reported as occurring less frequently and was seen as less problematic by parents compared to the disruptive behavior of children in less rural areas. Finally, we found that Dutch norm scores on the ECBI were significantly lower than US norm scores, and significantly higher on the intensity scale (but not the problem scale) than Norwegian and Swedish norm scores. [ABSTRACT FROM AUTHOR]

Clinical research often focuses on resource-intensive causal inference, whereas the potential of predictive analytics with constantly increasing big data sources remains largely unexplored. Basic prediction, divorced from causal inference, is much easier with big data. Emergency care may benefit from this simpler application of big data. Historically, predictive analytics have played an important role in emergency care as simple heuristics for risk stratification. These tools generally follow a standard approach: parsimonious criteria, easy computability, and independent validation with distinct populations. Simplicity in a prediction tool is valuable, but technological advances make it no longer a necessity. Emergency care could benefit from clinical predictions built using data science tools with abundant potential input variables available in electronic medical records. Patients' risks could be stratified more precisely with large pools of data and lower resource requirements for comparing each clinical encounter to those that came before it, benefiting clinical decisionmaking and health systems operations. The largest value of predictive analytics comes early in the clinical encounter, in which diagnostic and prognostic uncertainty are high and resource-committing decisions need to be made. We propose an agenda for widening the application of predictive analytics in emergency care. Throughout, we express cautious optimism because there are myriad challenges related to database infrastructure, practitioner uptake, and patient acceptance. The quality of routinely compiled clinical data will remain an important limitation. Complementing big data sources with prospective data may be necessary if predictive analytics are to achieve their full potential to improve care quality in the emergency department. [ABSTRACT FROM AUTHOR]

Simple Summary: Childhood cancer patients receiving treatment containing alkylating agents are at risk of infertility, yet inter-individual variability in treatment-related ovarian damage is observed. Alkylating agents are metabolized by cytochrome P450 (CYP450) enzymes and polymorphisms in these CYP450 enzymes may explain this variability in ovarian damage. This study on genetic variation in CYP450 enzymes of chemotherapy-induced gonadotoxicity, using anti-Müllerian hormone (AMH) levels as a proxy for ovarian reserve, in female childhood cancer survivors (CCSs) may identify patients at risk of infertility. This unique global collaboration of two large CCS studies shows the significant gonadotoxic effect of enzyme CYP3A4*3 and significant protective effect of CYP2B6*2 on gonadal function in CCSs receiving alkylating agents. Genetic variation in CYP3A4 and CYP2B6 have previously been associated with gonadotoxicity after cancer treatment. These findings could guide risk prediction models determining patients at risk of chemotherapy-induced gonadal impairment. Background: Female childhood cancer survivors (CCSs) carry a risk of therapy-related gonadal dysfunction. Alkylating agents (AA) are well-established risk factors, yet inter-individual variability in ovarian function is observed. Polymorphisms in CYP450 enzymes may explain this variability in AA-induced ovarian damage. We aimed to evaluate associations between previously identified genetic polymorphisms in CYP450 enzymes and AA-related ovarian function among adult CCSs. Methods: Anti-Müllerian hormone (AMH) levels served as a proxy for ovarian function in a discovery cohort of adult female CCSs, from the pan-European PanCareLIFE cohort (n = 743; age (years): median 25.8, interquartile range (IQR) 22.1–30.6). Using two additive genetic models in linear and logistic regression, nine genetic variants in three CYP450 enzymes were analyzed in relation to cyclophosphamide equivalent dose (CED) score and their impact on AMH levels. The main model evaluated the effect of the variant on AMH and the interaction model evaluated the modifying effect of the variant on the impact of CED score on log-transformed AMH levels. Results were validated, and meta-analysis performed, using the USA-based St. Jude Lifetime Cohort (n = 391; age (years): median 31.3, IQR 26.6–37.4). Results: CYP3A4*3 was significantly associated with AMH levels in the discovery and replication cohort. Meta-analysis revealed a significant main deleterious effect (Beta (95% CI): −0.706 (−1.11–−0.298), p-value = 7 × 10−4) of CYP3A4*3 (rs4986910) on log-transformed AMH levels. CYP2B6*2 (rs8192709) showed a significant protective interaction effect (Beta (95% CI): 0.527 (0.126–0.928), p-value = 0.01) on log-transformed AMH levels in CCSs receiving more than 8000 mg/m2 CED. Conclusions: Female CCSs CYP3A4*3 carriers had significantly lower AMH levels, and CYP2B6*2 may have a protective effect on AMH levels. Identification of risk-contributing variants may improve individualized counselling regarding the treatment-related risk of infertility and fertility preservation options. [ABSTRACT FROM AUTHOR]

The article offers information on the feedback of two students on a society-oriented biology course in the U.S. Mathematics major Richard A. Hosley II reveals that after their careful examination, their main positive feedback of the course include better social conditions, medicines and food. He reveals that the negative feedback include slum, disease, starvation, emigration, and birth control. Moreover, education major Sherran Franze asserts that the most serious nutrition problem is protein deficiency which is suffered by 30% to 40% of the world's population.