Behavioural effects of Advanced Cruise Control Use

 In this study, a meta-analytic approach was used to analyse effects of Advanced Cruise Control (ACC) on driving behaviour reported in seven driving simulator studies. The effects of ACC on three consistent outcome measures, namely, driving speed, headway and driver workload have been analysed. The indicators of speed, headway and workload have been chosen because they are assumed to be directly affected by the ACC support, their relationship with road safety is reasonably established and they are the most frequently used outcome measures in the sample of analysed studies. The results suggest that different operational settings of ACC that are important for the level of support provided by the system, are significant for the effects ACC have on various aspects of driving behaviour, i.e. on mean driving speed and mean time headway. The obtained effect sizes clustered in two groups, with more intervening ACCs having the effects of an increased driving speed and decreased mean time headway. These results are further discussed in the context of road safety, especially in the context of behavioural adaptation

The distinctive gastric fluid proteome in gastric cancer reveals a multi-biomarker diagnostic profile

<p>Abstract</p> <p>Background</p> <p>Overall gastric cancer survival remains poor mainly because there are no reliable methods for identifying highly curable early stage disease. Multi-protein profiling of gastric fluids, obtained from the anatomic site of pathology, could reveal diagnostic proteomic fingerprints.</p> <p>Methods</p> <p>Protein profiles were generated from gastric fluid samples of 19 gastric cancer and 36 benign gastritides patients undergoing elective, clinically-indicated gastroscopy using surface-enhanced laser desorption/ionization time-of-flight mass spectrometry on multiple ProteinChip arrays. Proteomic features were compared by significance analysis of microarray algorithm and two-way hierarchical clustering. A second blinded sample set (24 gastric cancers and 29 clinically benign gastritides) was used for validation.</p> <p>Results</p> <p>By significance analysyis of microarray, 60 proteomic features were up-regulated and 46 were down-regulated in gastric cancer samples (<it>p </it>< 0.01). Multimarker clustering showed two distinctive proteomic profiles independent of age and ethnicity. Eighteen of 19 cancer samples clustered together (sensitivity 95%) while 27/36 of non-cancer samples clustered in a second group. Nine non-cancer samples that clustered with cancer samples included 5 pre-malignant lesions (1 adenomatous polyp and 4 intestinal metaplasia). Validation using a second sample set showed the sensitivity and specificity to be 88% and 93%, respectively. Positive predictive value of the combined data was 0.80. Selected peptide sequencing identified pepsinogen C and pepsin A activation peptide as significantly down-regulated and alpha-defensin as significantly up-regulated.</p> <p>Conclusion</p> <p>This simple and reproducible multimarker proteomic assay could supplement clinical gastroscopic evaluation of symptomatic patients to enhance diagnostic accuracy for gastric cancer and pre-malignant lesions.</p