Interleukin 20 regulates dendritic cell migration and expression of co-stimulatory molecules

BACKGROUND: Psoriasis is an inflammatory disease characterized by leukocyte skin infiltration. Interestingly, recent works suggest that the migration of dendritic cells (DCs) is abnormal in psoriatic skin. DCs have significant role in regulating the function of T lymphocytes, at least in part influenced by the local environment of cytokines. In psoriatic skin lesions the expression of IL-20 is highly up-regulated. It is unclear if this cytokine has any influence on DCs. METHODS: Here, we investigated the influence of IL-20 in monocyte-derived dendritic cell (MDDCs) in vitro. This work addressed IL-20 effects on DC maturation, receptor expression and signaling. By use of extra cellular matrix components mimicking the skin environment, we also studied the functional effects of IL-20 on the chemotactic migration of DCs. Based on the recent finding that CD18 integrin are shed during migration of myeloid leukocytes, the concentration of these adhesion molecules was measured in MDDCs culture supernatants post migration. RESULTS: Following stimulation with IL-20, immature human MDDCs enhanced the expression of the co-stimulatory molecule CD86, further enabling activation of the p38 MAPK, but not the STAT3, pathway. IL-20 increased the migration of MDDCs in a biphasic response narrowly controlled by the interleukin concentration. A concomitant change in the shedding of CD18 integrins suggested that these adhesion molecules play a role in the migration of the MDDCs through the extracellular matrix layer. CONCLUSION: Taken together, our findings points to a possible, yet subtle, role of IL-20 in DCs migration. The biphasic response suggests that the aberrant IL-20 expression in psoriasis impedes DC migration, which could be a part of the processes that precipitates the dysregulated inflammatory response associated with this disease

Letbane på Ring 3

Referat af udvidet Special Session vedr. Letbane på Ring 3 Mødeleder: Jørgen Østergaard, Metroselskabe

A Quantitative General Population Job Exposure Matrix for Occupational Noise Exposure

Occupational noise exposure is a known risk factor for hearing loss and also adverse cardiovascular effects have been suggested. A job exposure matrix (JEM) would enable studies of noise and health on a large scale. The objective of this study was to create a quantitative JEM for occupational noise exposure assessment of the general working population. Between 2001-2003 and 2009-2010, we recruited workers from companies within the 10 industries with the highest reporting of noise-induced hearing loss according to the Danish Working Environment Authority and in addition workers of financial services and children day care to optimize the range in exposure levels. We obtained 1343 personal occupational noise dosimeter measurements among 1140 workers representing 100 different jobs according to the Danish version of the International Standard Classification of Occupations 1988 (DISCO 88). Four experts used 35 of these jobs as benchmarks and rated noise levels for the remaining 337 jobs within DISCO 88. To estimate noise levels for all 372 jobs, we included expert ratings together with sex, age, occupational class, and calendar year as fixed effects, while job and worker were included as random effects in a linear mixed regression model. The fixed effects explained 40% of the total variance: 72% of the between-jobs variance, -6% of the between-workers variance and 4% of the within-worker variance. Modelled noise levels showed a monotonic increase with increasing expert score and a 20 dB difference between the highest and lowest exposed jobs. Based on the JEM estimates, metal wheel-grinders were among the highest and finance and sales professionals among the lowest exposed. This JEM of occupational noise exposure can be used to prioritize preventive efforts of occupational noise exposure and to provide quantitative estimates of contemporary exposure levels in epidemiological studies of health effects potentially associated with noise exposure

Crowding in the emergency department in the absence of boarding – a transition regression model to predict departures and waiting time

Abstract Background Crowding in the emergency department (ED) is associated with increased mortality, increased treatment cost, and reduced quality of care. Crowding arises when demand exceed resources in the ED and a first sign may be increasing waiting time. We aimed to quantify predictors for departure from the ED, and relate this to waiting time in the ED before departure. Methods We utilised administrative data from the ED and calculated number of arrivals, departures, and the resulting queue in 30 min time steps for all of 2013 (N = 17,520). We build a transition model for each time step using the number of past departures and pre-specified risk factors (arrivals, weekday/weekend and shift) to predict the expected number of departures and from this the expected waiting time in the ED. The model was validated with data from the same ED collected March through August 2014. Results We found that the number of arrivals had the greatest independent impact on departures with an odds ratio of 0.942 (95%CI: 0.937;0.948) corresponding to additional 7 min waiting time per new arrival in a 30 min time interval with an a priori time spend in the ED of two hours. The serial correlation of departures was present up to one and a half hour previous but had very little effect on the estimates of the risk factors. Boarding played a negligible role in the studied ED. Conclusions We present a transition regression model with high predictive power to predict departures from the ED utilising only system level data. We use this to present estimates of expected waiting time and ultimately crowding in the ED. The model shows good internal validity though further studies are needed to determine generalisability to the performance in other settings