Compliance to Screening Protocols for Multidrug-Resistant Microorganisms at the Emergency Departments of Two Academic Hospitals in the Dutch-German Cross-Border Region

Infections caused by multidrug-resistant organisms (MDROs) are associated with prolonged hospitalization and higher risk of mortality. Patients arriving in the hospital via the emergency department (ED) are screened for the presence of MDROs in compliance with the screening protocols in order to apply the correct isolation measures. In the Dutch-German border region, local hospitals apply their own screening protocols which are based upon national screening protocols. The contents of the national and local MDRO screening protocols were compared on vancomycin-resistant enterococci (VRE), methicillin-resistant Staphylococcus aureus (MRSA), and carbapenemase-producing and carbapenem-resistant Enterobacteriaceae (CPE/CRE). The practicality of the screening protocols was evaluated by performing an audit. As a result, the content of the MDRO screening protocols differed regarding risk factors for MDRO carriage, swab site, personal protective equipment, and isolation measures. The observations and questionnaires showed that the practicality was sufficient; however, the responsibility was not designated clearly and education regarding the screening protocols was deemed inappropriate. The differences between the MDRO screening protocols complicate patient care in the Dutch-German border region. Arrangements have to be made about the responsibility of the MDRO screening, and improvements are necessary concerning education regarding the MDRO screening protocols

Group 2 innate lymphoid cells exhibit a dynamic phenotype in allergic airway inflammation

Group 2 innate lymphoid cells (ILC2) are implicated in allergic asthma as an early innate source of the type 2 cytokines IL-5 and IL-13. However, their induction in house dust mite (HDM)-mediated airway inflammation additionally requires T cell activation. It is currently unknown whether phenotypic differences exist between ILC2s that are activated in a T cell-dependent or T cell-independent fashion. Here, we compared ILC2s in IL-33-and HDM-driven airway inflammation. Using flow cytometry, we found that surface expression levels of various markers frequently used to identify ILC2s were dependent on their mode of activation, highly variable over time, and differed between tissue compartments, including bronchoalveolar lavage (BAL) fluid, lung, draining lymph nodes, and spleen. Whereas in vivo IL-33-activated BAL fluid ILC2s exhibited an almost uniform CD25+CD127+T1/ST2+ICOS+KLRG1+ phenotype, at a comparable time point after HDM exposure BAL fluid ILC2s had a very heterogeneous surface marker phenotype. A major fraction of HDM-activated ILC2s were CD25lowCD127+T1/ST2low ICOSlowKLRG1low, but nevertheless had the capacity to produce large amounts of type 2 cytokines. HDM-activated CD25low ILC2s in BAL fluid and lung rapidly reverted to CD25high ILC2s upon in vivo stimulation with IL-33. Genome-wide transcriptional profiling of BAL ILC2s revealed ~1,600 differentially expressed genes: HDM-stimulated ILC2s specifically expressed genes involved in the regulation of adaptive immunity through B and T cell interactions, whereas IL-33-stimulated ILC2s expressed high levels of proliferation-related and cytokine genes. In both airway inflammation models ILC2s were present in the lung submucosa close to epithelial cells, as identified by confocal microscopy. In chronic HDM-driven airway inflammation ILC2s were also found inside organized cellular infiltrates near T cells. Collectively, our findings show that ILC2s are phenotypically more heterogeneous than previously thought, whereby their surface marker and gene expression profile are highly dynamic

Adolescent Depression and Negative Life Events, the Mediating Role of Cognitive Emotion Regulation.

BACKGROUND:Depression during adolescence is a serious mental health problem. Difficulties in regulating evoked emotions after stressful life events are considered to lead to depression. This study examined if depressive symptoms were mediated by various cognitive emotion regulation strategies after stressful life events, more specifically, the loss of a loved one, health threats or relational challenges. METHODS:We used a sample of 398 adolescents (Mage = 16.94, SD = 2.90), including 52 depressed outpatients, who all reported stressful life event(s). Path analyses in Mplus were used to test mediation, for the whole sample as well as separately for participants scoring high versus low on depression, using multigroup analyses. RESULTS:Health threats and relational challenging stressful life events were associated with depressive symptoms, while loss was not. More frequent use of maladaptive strategies was related to more depressive symptoms. More frequent use of adaptive strategies was related to less depressive symptoms. Specific life events were associated with specific emotion regulation strategies. The relationship between challenging, stressful life events and depressive symptoms in the whole group was mediated by maladaptive strategies (self-blame, catastrophizing and rumination). No mediation effect was found for adaptive strategies. CONCLUSION:The association between relational challenging, stressful life events and depressive symptoms was mediated by maladaptive, cognitive emotion regulation strategies

Correlations Depressed Group (N = 109) and Non-depressed Group (N = 289).

<p>Correlations Depressed Group (N = 109) and Non-depressed Group (N = 289).</p

Mediation Model.

<p>Standardized estimates of the indirect effects on the depressive symptoms (N = 398). Only significant effects are shown (* <i>p</i> < .05, *** <i>p</i> < .001). Estimates apply to the total sample (<i>N</i> = 398).</p

Direct Effects for the Total Sample.

<p>Standardized estimates of the direct effects on the cognitive emotion regulation and depressive symptoms. Only significant effects (* <i>p</i> < .05, ** <i>p</i> < .01, *** <i>p</i> < .001) within the total sample (<i>N</i> = 398) are shown.</p

Correlations Total Group (<i>N</i> = 398).

<p>Correlations Total Group (<i>N</i> = 398).</p