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Ein 7 Monate alter weiblicher Säugling wurde mit Kontaktverbrennungen 2. Grades an beiden Beinen von seinen Eltern in der Notaufnahme eines Krankenhauses vorgestellt. Die Eltern berichteten, das Kind sei unbeaufsichtigt und nur mit einem Body bekleidet gegen den Nachtspeicherofen im Kinderzimmer gekrabbelt. Bei der 10 Tage später durchgeführten klinisch-rechtsmedizinischen Untersuchung zeigten sich streifige, teils parallel zueinander gestellte und gelenkübergreifende Verbrennungen an der rechten Oberschenkelaußen- und Unterschenkelrückaußenseite, an beiden Fußrücken und den Zehen sowie ein flächenhaftes Verbrennungsareal an der linken Unterschenkelaußenseite mit abgrenzbaren streifigen Anteilen.
Im Rahmen einer Ortsbegehung der elterlichen Wohnung mit Vermessung und Begutachtung der in der Wohnung befindlichen 3 Nachtspeicheröfen konnte zunächst festgestellt werden, dass sich die Verbrennungsmuster an den Beinen des Kindes mit dem Luftauslassgitter der beiden Nachtspeicheröfen im Wohn- und im Elternschlafzimmer (jeweils identisches Modell), hingegen nicht mit dem des Nachtspeicherofens im Kinderzimmer in Deckung bringen ließen. Für die Begutachtung konnte durch ergänzende Informationen eines technischen Sachverständigen zu den entsprechenden Nachtspeicheröfen und durch eine Literaturrecherche ein möglicher Geschehensablauf rekonstruiert werden.
Dieser Fall verdeutlicht zum einen, welche Gefahr für Säuglinge und Kleinkinder von Nachtspeicheröfen ausgehen kann, wenn diese nicht regelrecht gesichert und die Kinder unbeaufsichtigt sind. Zum anderen wird die Bedeutung einer detaillierten und – wenn nötig – interdisziplinären Rekonstruktion, inklusive einer Ortsbegehung, zur Abgrenzung eines möglichen Unfallhergangs von einer Kindesmisshandlung unterstrichen.
Although researchers and practitioners increasingly focus on health promotion in organizations, research has been mainly fragmented and fails to integrate different organizational levels in terms of their effects on employee health. Drawing on organizational climate and social identity research, we present a cascading model of organizational health climate and demonstrate how and when leaders' perceptions of organizational health climate are linked to employee well-being. We tested our model in two multisource studies (NStudy 1 = 65 leaders and 291 employees; NStudy 2 = 401 leader–employee dyads). Results showed that leaders' perceptions of organizational health climate were positively related to their health mindsets (i.e., their health awareness). These in turn were positively associated with their health-promoting leadership behavior, which ultimately went along with better employee well-being. Additionally, in Study 1, the relationship between perceived organizational health climate and leaders' health mindsets was moderated by their organizational identification. High leader identification strengthened the relationship between perceived organizational health climate and leaders' health mindsets. These findings have important implications for theory and practice as they show how the dynamics of an organizational health climate can unfold in organizations and how it is related to employee well-being via the novel concept of health-promoting leadership.
Although researchers and practitioners increasingly focus on health promotion in organizations, research has been mainly fragmented and fails to integrate different organizational levels in terms of their effects on employee health. Drawing on organizational climate and social identity research, we present a cascading model of organizational health climate and demonstrate how and when leaders' perceptions of organizational health climate are linked to employee well‐being. We tested our model in two multisource studies (NStudy 1 = 65 leaders and 291 employees; NStudy 2 = 401 leader–employee dyads). Results showed that leaders' perceptions of organizational health climate were positively related to their health mindsets (i.e., their health awareness). These in turn were positively associated with their health‐promoting leadership behavior, which ultimately went along with better employee well‐being. Additionally, in Study 1, the relationship between perceived organizational health climate and leaders' health mindsets was moderated by their organizational identification. High leader identification strengthened the relationship between perceived organizational health climate and leaders' health mindsets. These findings have important implications for theory and practice as they show how the dynamics of an organizational health climate can unfold in organizations and how it is related to employee well‐being via the novel concept of health‐promoting leadership.
Existing social stressor concepts disregard the variety of task-related situations at work that require skillful social behavior to maintain good social relationships while achieving certain task goals. In this article, we challenge the view that social stressors at work are solely dysfunctional aspects evoking employee ill health. Drawing from the challenge-hindrance stressor framework, we introduce the concept of social challenge stressors as a job characteristic and examine their relationships with individual well-and ill-being. In study 1, we developed a new scale for the measurement of social challenge stressors and tested the validity of the scale. Results from two independent samples indicated support for a single-factor structure and showed that social challenge stressors are distinct from related stressor concepts. Using two samples, one of which was already used to test the factor structure, we analyzed the unique contribution of social challenge stressors in predicting employee well- and ill-being. As expected, social challenge stressors were simultaneously related to psychological strain and well-being. Using time-lagged data, study 2 investigated mechanisms that may explain how social challenge stressors are linked to well-being and strain. In line with the stress-as-offense-to-self approach, we expected indirect relationships via self-esteem. Additionally, social support was expected to moderate the relationships between social stressors and self-esteem. Whereas the indirect relationships were mostly confirmed, we found no support for the buffering role of social support in the social hindrance stressors-self-esteem link. Although we found a moderation effect for social challenge stressors, results indicated a compensation model that conflicted with expectations.
Background: Enhancers play a fundamental role in orchestrating cell state and development. Although several methods have been developed to identify enhancers, linking them to their target genes is still an open problem. Several theories have been proposed on the functional mechanisms of enhancers, which triggered the development of various methods to infer promoter–enhancer interactions (PEIs). The advancement of high-throughput techniques describing the three-dimensional organization of the chromatin, paved the way to pinpoint long-range PEIs. Here we investigated whether including PEIs in computational models for the prediction of gene expression improves performance and interpretability.
Results: We have extended our TEPIC framework to include DNA contacts deduced from chromatin conformation capture experiments and compared various methods to determine PEIs using predictive modelling of gene expression from chromatin accessibility data and predicted transcription factor (TF) motif data. We designed a novel machine learning approach that allows the prioritization of TFs binding to distal loop and promoter regions with respect to their importance for gene expression regulation. Our analysis revealed a set of core TFs that are part of enhancer–promoter loops involving YY1 in different cell lines.
Conclusion: We present a novel approach that can be used to prioritize TFs involved in distal and promoter-proximal regulatory events by integrating chromatin accessibility, conformation, and gene expression data. We show that the integration of chromatin conformation data can improve gene expression prediction and aids model interpretability.
Background Enhancers play a fundamental role in orchestrating cell state and development. Although several methods have been developed to identify enhancers, linking them to their target genes is still an open problem. Several theories have been proposed on the functional mechanisms of enhancers, which triggered the development of various methods to infer promoter enhancer interactions (PEIs). The advancement of high-throughput techniques describing the three-dimensional organisation of the chromatin, paved the way to pinpoint long-range PEIs. Here we investigated whether including PEIs in computational models for the prediction of gene expression improves performance and interpretability.
Results We have extended our Tepic framework to include DNA contacts deduced from chromatin conformation capture experiments and compared various methods to determine PEIs using predictive modelling of gene expression from chromatin accessibility data and predicted transcription factor (TF) motif data. We found that including long-range PEIs deduced from both HiC and HiChIP data indeed improves model performance. We designed a novel machine learning approach that allows to prioritize TFs in distal loop and promoter regions with respect to their importance for gene expression regulation. Our analysis revealed a set of core TFs that are part of enhancer-promoter loops involving YY1 in different cell lines.
Conclusion: We show that the integration of chromatin conformation data improves gene expression prediction, underlining the importance of enhancer looping for gene expression regulation. Our general approach can be used to prioritize TFs that are involved in distal and promoter-proximal regulation using accessibility, conformation and expression data.
