Effects of fresh and aged vehicular exhaust emissions on breathing pattern and cellular responses--pilot single vehicle study.

The study presented here is a laboratory pilot study using diluted car exhaust from a single vehicle to assess differences in toxicological response between primary emissions and secondary products resulting from atmospheric photochemical reactions of gas phase compounds with O3, OH and other radicals. Sprague Dawley rats were exposed for 5 h to either filtered room air (sham) or one of two different atmospheres: (i) diluted car exhaust (P)+Mt. Saint Helens Ash (MSHA); (ii) P+MSHA+secondary organic aerosol (SOA, formed during simulated photochemical aging of diluted exhaust). Primary and secondary gases were removed using a nonselective diffusion denuder. Continuous respiratory data was collected during the exposure, and bronchoalveolar lavage (BAL) and complete blood counts (CBC) were performed 24 h after exposure. ANOVA models were used to assess the exposure effect and to compare those effects across different exposure types. Total average exposures were 363 ± 66 µg/m³ P+MSHA and 212 ± 95 µg/m³ P+MSHA+SOA. For both exposures, we observed decreases in breathing rate, tidal and minute volumes (TV, MV) and peak and median flows (PIF, PEF and EF50) along with increases in breathing cycle times (Ti, Te) compared to sham. These results indicate that the animals are changing their breathing pattern with these test atmospheres. Exposure to P+MSHA+SOA produced significant increases in total cells, macrophages and neutrophils in the BAL and in vivo chemiluminescence of the lung. There were no significant differences in CBC parameters. Our data suggest that simulated atmospheric photochemistry, producing SOA in the P+MSHA+SOA exposures, enhanced the toxicity of vehicular emissions.

The efficacy of Web-based cognitive behavioral interventions for chronic pain: a systematic review and meta-analysis.

UNLABELLED: Our objective was to conduct a systematic review and meta-analysis to quantify the efficacy of web-based cognitive behavioral interventions for the treatment of patients with chronic pain. MEDLINE and other databases were searched as data sources. Reference lists were examined for other relevant articles. We included 11 studies that evaluated the effects of web-based interventions on chronic pain using specific scales of pain. The pooled effect size (standardized mean difference between intervention versus waiting-list group means) from a random effects model was .285 (95% confidence interval: .145-.424), favoring the web-based intervention compared with the waiting-list group, although the effect was small. In addition, these results were not driven by any particular study, as shown by sensitivity analysis. Results from funnel plot argue against publication bias. Finally, the average dropout rate was 26.6%. In our meta-analysis, we demonstrate a small effect of web-based interventions, when using pain scale as the main outcome. Despite the minor effects and high dropout rates, the decreased costs and minor risk of adverse effects compared with pharmacological treatments support additional studies in chronic pain patients using web-based interventions. Further studies will be important to confirm the effects and determine the best responders to this intervention. PERSPECTIVE: Our findings suggest that web-based interventions for chronic pain result in small pain reductions in the intervention group compared with waiting-list control groups. These results advance the field of web-based cognitive behavioral interventions as a potential therapeutic tool for chronic pain and can potentially help clinicians and patients with chronic pain by decreasing treatment costs and side effects.