Hypoxia Induces Astrocyte-Derived Lipocalin-2 in Ischemic Stroke.

Ischemic stroke causes rapid hypoxic damage to the core neural tissue which is followed by graded chronological tissue degeneration in the peri-infarct zone. The latter process is mainly triggered by neuroinflammation, activation of inflammasomes, proinflammatory cytokines, and pyroptosis. Besides microglia, astrocytes play an important role in the fine-tuning of the inflammatory network in the brain. Lipocalin-2 (LCN2) is involved in the control of innate immune responses, regulation of excess iron, and reactive oxygen production. In this study, we analyzed LCN2 expression in hypoxic rat brain tissue after ischemic stroke and in astrocyte cell cultures receiving standardized hypoxic treatment. Whereas no LCN2-positive cells were seen in sham animals, the number of LCN2-positive cells (mainly astrocytes) was significantly increased after stroke. In vitro studies with hypoxic cultured astroglia revealed that LCN2 expression is significantly increased after only 2 h, then further increased, followed by a stepwise decline. The expression pattern of several proinflammatory cytokines mainly followed that profile in wild type (WT) but not in cultured LCN2-deficient astrocytes. Our data revealed that astrocytes are an important source of LCN2 in the peri-infarct region under hypoxic conditions. However, we must also stress that brain-intrinsic LCN2 after the initial hypoxia period might come from other sources such as invaded immune cells and peripheral organs via blood circulation. In any case, secreted LCN2 might have an influence on peripheral organ functions and the innate immune system during brain hypoxia.

Predicting mortality, hospital length of stay and need for surgery in pediatric trauma patients.

PURPOSE: Pediatric trauma is one of the major health problems around the world which threats the life of children. The survival of injured children depends upon appropriate care, accurate triage and effective emergent surgery. The objective of this study was to determine the predictive values of injury severity score (ISS), new injury severity score (NISS) and revised trauma score (RTS) on children's mortality, hospitalization and need for surgery. METHODS: In this study, records of trauma patients under 15 years old transported from a trauma scene to emergency department of Poursina hospital from 2010 to 2011 were included. Statistical analysis was applied to determine the ISS, NISS and RTS ability in predicting the outcomes of interest. RESULTS: There were 588 records in hospital registry system. The mean age of the patients was (7.3 ± 3.8) years, and 62.1% (n = 365) of patients were male. RTS was the more ability score to predict mortality with an area under curve (AUC) of 0.99 (95% CI, 0.99-1). In the hospital length of stay (LOS), ISS was best predictor for both the hospital LOS with AUC of 0.72 (95% CI, 0.67-0.76) and need for surgical surgery with AUC of 0.94 (95% CI, 0.90-0.98). CONCLUSION: RTS as a physiological scoring system has a higher predicting AUC value in predicting mortality. The anatomic scoring systems of ISS and NISS have good performance in predicting of hospital LOS and need for surgery outcomes.

A Time Series Model for Assessing the Trend and Forecasting the Road Traffic Accident Mortality.

BACKGROUND: Road traffic accident (RTA) is one of the main causes of trauma and known as a growing public health concern worldwide, especially in developing countries. Assessing the trend of fatalities in the past years and forecasting it enables us to make the appropriate planning for prevention and control. OBJECTIVES: This study aimed to assess the trend of RTAs and forecast it in the next years by using time series modeling. MATERIALS AND METHODS: In this historical analytical study, the RTA mortalities in Zanjan Province, Iran, were evaluated during 2007 - 2013. The time series analyses including Box-Jenkins models were used to assess the trend of accident fatalities in previous years and forecast it for the next 4 years. RESULTS: The mean age of the victims was 37.22 years (SD = 20.01). From a total of 2571 deaths, 77.5% (n = 1992) were males and 22.5% (n = 579) were females. The study models showed a descending trend of fatalities in the study years. The SARIMA (1, 1, 3) (0, 1, 0) 12 model was recognized as a best fit model in forecasting the trend of fatalities. Forecasting model also showed a descending trend of traffic accident mortalities in the next 4 years. CONCLUSIONS: There was a decreasing trend in the study and the future years. It seems that implementation of some interventions in the recent decade has had a positive effect on the decline of RTA fatalities. Nevertheless, there is still a need to pay more attention in order to prevent the occurrence and the mortalities related to traffic accidents.