Glucosamine attenuates cigarette smoke-induced lung inflammation by inhibiting ROS-sensitive inflammatory signaling.

Cigarette smoking causes persistent lung inflammation that is mainly regulated by redox-sensitive pathways. We have reported that cigarette smoke (CS) activates a NADPH oxidase-dependent reactive oxygen species (ROS)-sensitive AMP-activated protein kinase (AMPK) signaling pathway leading to induction of lung inflammation. Glucosamine, a dietary supplement used to treat osteoarthritis, has antioxidant and anti-inflammatory properties. However, whether glucosamine has similar beneficial effects against CS-induced lung inflammation remains unclear. Using a murine model we show that chronic CS exposure for 4 weeks increased lung levels of 4-hydroxynonenal (an oxidative stress biomarker), phospho-AMPK, and macrophage inflammatory protein 2 and induced lung inflammation; all of these CS-induced events were suppressed by chronic treatment with glucosamine. Using human bronchial epithelial cells, we demonstrate that cigarette smoke extract (CSE) sequentially activated NADPH oxidase; increased intracellular levels of ROS; activated AMPK, mitogen-activated protein kinases (MAPKs), nuclear factor-κB (NF-κB), and signal transducer and activator of transcription proteins 3 (STAT3); and induced interleukin-8 (IL-8). Additionally, using a ROS scavenger, a siRNA that targets AMPK, and various pharmacological inhibitors, we identified the signaling cascade that leads to induction of IL-8 by CSE. All these CSE-induced events were inhibited by glucosamine pretreatment. Our findings suggest a novel role for glucosamine in alleviating the oxidative stress and lung inflammation induced by chronic CS exposure in vivo and in suppressing the CSE-induced IL-8 in vitro by inhibiting both the ROS-sensitive NADPH oxidase/AMPK/MAPK signaling pathway and the downstream transcriptional factors NF-κB and STAT3.

Comparisons of predictive performance of breathing pattern variability measured during T-piece, automatic tube compensation, and pressure support ventilation for weaning intensive care unit patients from mechanical ventilation.

OBJECTIVE: To investigate the influence of different ventilatory supports on the predictive performance of breathing pattern variability for extubation outcomes in intensive care unit patients. DESIGN AND SETTING: A prospective measurement of retrospectively analyzed breathing pattern variability in a medical center. PATIENTS: Sixty-eight consecutive and ready-for-weaning patients were divided into success (n=45) and failure (n=23) groups based on their extubation outcomes. MEASUREMENTS: Breath-to-breath analyses of peak inspiratory flow, total breath duration, tidal volume, and rapid shallow breathing index were performed for three 30-min periods while patients randomly received T-piece, 100% inspiratory automatic tube compensation with 5 cm H2O positive end-expiratory pressure, and 5 cm H2O pressure support ventilation with 5 cm H2O positive end-expiratory pressure trials. Coefficient of variations and data dispersion (standard descriptor values SD1 and SD2 of the Poincaré plot) were analyzed to serve as breathing pattern variability indices. MAIN RESULTS: Under all three trials, breathing pattern variability in extubation failure patients was smaller than in extubation success patients. Compared to the T-piece trial, 100% inspiratory automatic tube compensation with 5 cm H2O positive end-expiratory pressure and 5 cm H2O pressure support ventilation with 5 cm H2O positive end-expiratory pressure decreased the ability of certain breathing pattern variability indices to discriminate extubation success from extubation failure. The areas under the receiver operating characteristic curve of these breathing pattern variability indices were: T-piece (0.73-0.87)>100% inspiratory automatic tube compensation with 5 cm H2O positive end-expiratory pressure (0.60-0.79)>5 cm H2O pressure support ventilation with 5 cm H2O positive end-expiratory pressure (0.53-0.76). Analysis of the classification and regression tree indicated that during the T-piece trial, a SD1 of peak inspiratory flow>3.36 L/min defined a group including all extubation success patients. Conversely, the combination of a SD1 of peak inspiratory flow ≤3.36 L/min and a coefficient of variations of rapid shallow breathing index ≤0.23 defined a group of all extubation failure patients. The decision strategies using SD1 of peak inspiratory flow and coefficient of variations of rapid shallow breathing index measured during 100% inspiratory automatic tube compensation with 5 cm H2O positive end-expiratory pressure and 5 cm H2O pressure support ventilation with 5 cm H2O positive end-expiratory pressure trials achieved a less clear separation of extubation failure from extubation success. CONCLUSIONS: Since 100% inspiratory automatic tube compensation with 5 cm H2O positive end-expiratory pressure and 5 cm H2O pressure support ventilation with 5 cm H2O positive end-expiratory pressure reduce the predictive performance of breathing pattern variability, breathing pattern variability measurement during the T-piece trial is the best choice for predicting extubation outcome in intensive care unit patients patients.