Distinct cytoplasmic regions of the human granulocyte colony-stimulating factor receptor involved in induction of proliferation and maturation

The granulocyte colony-stimulating factor receptor (G-CSF-R) transduces signals important for the proliferation and maturation of myeloid progenitor cells. To identify functionally important regions in the cytoplasmic domain of the G-CSF-R, we compared the actions of the wild-type receptor, two mutants, and a natural splice variant in transfectants of the mouse pro-B cell line BAF3 and two myeloid cell lines, 32D and L-GM. A region of 55 amino acids adjacent to the transmembrane domain was found to be sufficient for generating a growth signal. The immediate downstream sequence of 30 amino acids substantially enhanced the growth signaling in the three cell lines. In contrast, the carboxy-terminal part of 98 amino acids strongly inhibited growth signaling in the two myeloid cell lines but not in BAF3 cells. Truncation of this region lead to an inability of the G-CSF-R to transduce maturation signals in L-GM cells. An alternative carboxy tail present in a splice variant of the G-CSF-R also inhibited growth signaling, notably in both the myeloid cells and BAF3 cells, but appeared not to be involved in maturation

Investigating the prevalence of problematic substance use and mental disorders in a large sample of prisoners with mental illness: network analysis

Background The relationship between psychopathology and criminal offending has been the subject of many studies. Co-occurring substance use seems to increase the risk of offending in those with mental illness. Aims To present data on the prevalence of mental disorders and demographics of prisoners with mental illness, and investigate associations between diagnoses and substance use from a network perspective. Method Data used in this study are part of a cohort study within the four penitentiary psychiatric centres in The Netherlands. It includes data of 4956 incarcerated male patients. Prevalence rates of mental disorders and demographic variables were compared between individuals with and without problematic substance use. A network of diagnoses, including three categories of substance use, was constructed with regression coefficients. Results Most patients showed prior problematic substance use (72.2%) in more than one category of substances (58.7%). Problematic substance use was associated with diagnoses of schizophrenia spectrum disorders (χ2(1) = 37.52, P < 0.001, V = 0.09) and cluster B personality disorders (χ2(1) = 56.39, P < 0.001, V = 0.11). Three major findings of the network are discussed in detail: the role of antisocial personality disorder, impulsivity and psychotic disorders in combination with problematic substance use. Conclusions Problematic substance use is highly prevalent among prisoners with mental illness, and should always be taken into account in research on this topic. Treatment should target substance use to reduce the risk of recidivism. Further differentiation in categories of substances is needed for the development of risk profiles

Improving Quinolone Use in Hospitals by Using a Bundle of Interventions in an Interrupted Time Series Analysis

The objectives of the present study were to determine the effects of multiple targeted interventions on the level of use of quinolones and the observed rates of resistance to quinolones in Escherichia coli isolates from hospitalized patients. A bundle consisting of four interventions to improve the use of quinolones was implemented. The outcome was measured from the monthly levels of use of intravenous (i.v.) and oral quinolones and the susceptibility patterns for E. coli isolates from hospitalized patients. Statistical analyses were performed using segmented regression analysis and segmented Poisson regression models. Before the bundle was implemented, the annual use of quinolones was 2.7 defined daily doses (DDDs)/100 patient days. After the interventions, in 2007, this was reduced to 1.7 DDDs/100 patient days. The first intervention, a switch from i.v. to oral medication, was associated with a stepwise reduction in i.v. quinolone use of 71 prescribed daily doses (PDDs) per month (95% confidence interval [CI] = 47 to 95 PDDs/month, P < 0.001). Intervention 2, introduction of a new antibiotic guideline and education program, was associated with a stepwise reduction in the overall use of quinolones (reduction, 107 PDDs/month [95% CI = 58 to 156 PDDs/month). Before the interventions the quinolone resistance rate was increasing, on average, by 4.6% (95% CI = 2.6 to 6.1%) per year. This increase leveled off, which was associated with intervention 2 and intervention 4, active monitoring of prescriptions and feedback. Trends in resistance to other antimicrobial agents did not change. This study showed that the hospital-wide use of quinolones can be significantly reduced by an active policy consisting of multiple interventions. There was also a stepwise reduction in the rate of quinolone resistance associated with the bundle of interventions

Ethical Considerations for Movement Mapping to Identify Disease Transmission Hotspots.

Traditional public health methods for detecting infectious disease transmission, such as contact tracing and molecular epidemiology, are time-consuming and costly. Information and communication technologies, such as global positioning systems, smartphones, and mobile phones, offer opportunities for novel approaches to identifying transmission hotspots. However, mapping the movements of potentially infected persons comes with ethical challenges. During an interdisciplinary meeting of researchers, ethicists, data security specialists, information and communication technology experts, epidemiologists, microbiologists, and others, we arrived at suggestions to mitigate the ethical concerns of movement mapping. These suggestions include a template Data Protection Impact Assessment that follows European Union General Data Protection Regulations

The Prevalence of Mental Disorders and Patterns of Comorbidity within a Large Sample of Mentally Ill Prisoners: A Network Analysis

Background. Comorbidity has profound implications in both the clinical field and research, yet little is known about the prevalence and structure of comorbid mental disorders. This article aims not only to present data on the prevalence of mental disorders and comorbidity, but also to explore relationships between comorbid mental disorders by using a network approach. Methods. Data used in this cross-sectional study are part of a prospective cohort study within penitentiary psychiatric centers (PPCs) in the Netherlands. It includes DSM diagnoses of 5,257 unique male patients incarcerated in one of the PPC's. Prevalence rates of mental disorders and comorbidity were calculated, the network of comorbid DSM diagnoses was constructed using regression coefficients. Results. Schizophrenia spectrum and substance-related disorders were most prevalent within this sample (56.7 and 43.1%, respectively), and over half of all patients were diagnosed with a comorbid disorder (56.9%). Four distinctive groups of disorders emerged from the network analysis of DSM diagnoses: substance use, impulsivity, poor social skills, and disruptive behaviors. Psychotic disorders were considered as a separate group as it was unconnected to other disorders. Conclusions. Comorbid mental disorders can be described, at least in part, as connected networks. Underlying attributes as well as direct influences of mental disorders on one another seem to be affecting the presence of comorbidity. Results could contribute to the understanding of a possible causal relation between psychopathology and criminal behavior and the development of treatment programs targeting groups of disorders

The prevalence of mental disorders and patterns of comorbidity within a large sample of mentally ill prisoners:A network analysis

BACKGROUND.: Comorbidity has profound implications in both the clinical field and research, yet little is known about the prevalence and structure of comorbid mental disorders. This article aims not only to present data on the prevalence of mental disorders and comorbidity, but also to explore relationships between comorbid mental disorders by using a network approach. METHODS.: Data used in this cross-sectional study are part of a prospective cohort study within penitentiary psychiatric centers (PPCs) in the Netherlands. It includes DSM diagnoses of 5,257 unique male patients incarcerated in one of the PPC's. Prevalence rates of mental disorders and comorbidity were calculated, the network of comorbid DSM diagnoses was constructed using regression coefficients. RESULTS.: Schizophrenia spectrum and substance-related disorders were most prevalent within this sample (56.7 and 43.1%, respectively), and over half of all patients were diagnosed with a comorbid disorder (56.9%). Four distinctive groups of disorders emerged from the network analysis of DSM diagnoses: substance use, impulsivity, poor social skills, and disruptive behaviors. Psychotic disorders were considered as a separate group as it was unconnected to other disorders. CONCLUSIONS.: Comorbid mental disorders can be described, at least in part, as connected networks. Underlying attributes as well as direct influences of mental disorders on one another seem to be affecting the presence of comorbidity. Results could contribute to the understanding of a possible causal relation between psychopathology and criminal behavior and the development of treatment programs targeting groups of disorders