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The full-body and chest injuries showed the highest correlation with Occupant Impact Velocity (OIV), Acceleration Severity Index (ASI), and Theoretical Head Impact Velocity (THIV) (R2 > 0.6). Lower correlations of thigh injuries were recorded to OIV (R2 = 0.59) and THIV (R2 = 0.46). Meanwhile, weak correlations were observed between all the other regressions which indicated that no vehicle-based criteria could be used to predict head and neck injuries. Car-to-end terminal crash FE simulations involving a dummy model were performed for the first time in this study. The results pointed out the limitations of the standard vehicle-based injury methods in terms of head and neck injury prediction. The dummy-based injury assessment methodology presented in this study could supplement the crash tests for various impact conditions. In addition, the models could be used to design new advanced guardrail end terminals.The present study has investigated the relationship between traffic volume and crash numbers by means of meta-analysis, based on 521 crash prediction models from 118 studies. The weighted pooled volume coefficient for all crashes and all levels of crash severity (excluding fatal crashes) is 0.875. The most important moderator variable is crash type. Pooled volume coefficients are systematically greater for multi vehicle crashes (1.210) than for single vehicle crashes (0.552). Regarding crash severity, the results indicate that volume coefficients are smaller for more fatal crashes (0.777 for all fatal crashes) than for injury crashes but no systematic differences were found between volume coefficients for injury and property-damage-only crashes. At higher levels of volume and on divided roads, volume coefficients tend to be greater than at lower levels of volume and on undivided roads. #link# This is consistent with the finding that freeways on average have greater volume coefficients than other types of road and that two-lane roads are the road type with the smallest average volume coefficients. The results indicate that results from crash prediction models are likely to be more precise when crashes are disaggregated by crash type, crash severity, and road type. Disaggregating models by volume level and distinguishing between divided and undivided roads may also improve the precision of the results. The results indicate further that crash prediction models may be misleading if they are used to predict crash numbers on roads that differ from those that were used for model development with respect to composition of crash types, share of fatal or serious injury crashes, road types, and volume levels.The aim of the study was to investigate the impact of digital billboards on driving performance and visual attention. The impact of dwell time, location and content of digital billboards on driving behaviour was also examined. A 3 × 2 × 2 × 2 experimental study was undertaken using a laboratory driving simulator and data analysed using factorial four-way analysis of variance. A total of 96 participants completed the study, ranging in age from 18 to 76 years. On sections of roads containing billboards, participants drove at lower mean speeds (p  less then  0.001), had more speed variability (p  less then  0.001), more variability in lane position (p  less then  0.001), more time spent at high risk headway  less then  two seconds (p = 0.013), more time spent at high risk headway less then 0.25 s (p = 0.002) and had more visual fixations (p = 0.01), compared to control sections of road with no billboards. Danusertib datasheet with simple (versus complex) content presented at a long dwell time (60 s versus 40 or 20 s) had the least negative impact on driving outcomes. Billboards with complex content had similar negative effects on driving, regardless of dwell time. In addition, post-mounted roadside billboards (versus bridge mounted) with 60 s dwell times had the least negative impact on driving. While the presence of digital billboards negatively affected driving performance, simple billboard content and longer dwell times were safer. The results of the study will assist in the development of evidence-based guidelines for digital billboards.

CDO1 is a presumed tumor suppressor gene in human cancers, the expression of which is silenced by promoter DNA methylation. Moreover, CDO1 harbors functionally oncogenic aspects through modification of mitochondrial membrane potential. We recently proposed that this oncogenic feature allows for the prediction of the efficacy of postoperative chemotherapy in colon cancer. The present study aims to elucidate the efficacy of prediction of success of postoperative chemotherapy in advanced gastric cancer to improve the treatment strategy of patients.

Forced expression of CDO1 in gastric cancer cell lines was assessed using the JC-1 assay. Promoter DNA methylation was investigated in quantitative TaqMan methylation-specific polymerase chain reaction in 321 pathological stage II/III advanced gastric cancer cases treated by curative gastrectomy with or without postoperative chemotherapy.

(1) Forced expression of CDO1 led to increased mitochondrial membrane potential, accompanied by augmented survival in gastric cancer cells under anaerobic conditions. These results suggest that CDO1-expressing cancer cells survive more easily in anaerobic lesions which are inaccessible to anticancer drugs. (2) Intriguingly, in cases with the highest CDO1 methylation (ranging from 15% to 40%), patients with postoperative chemotherapy showed significantly better survival than those with no postoperative chemotherapy. (3) A robust prognostic difference was observed that was explained by differential recurrences of distant metastasis (P=0.0031), followed by lymph node (P=0.0142) and peritoneal dissemination (P=0.0472).

The oncogenic aspects of CDO1 can be of use to determine patients with gastric cancer who will likely respond to treatment of invisible systemic dissemination by postoperative adjuvant chemotherapy.

The oncogenic aspects of CDO1 can be of use to determine patients with gastric cancer who will likely respond to treatment of invisible systemic dissemination by postoperative adjuvant chemotherapy.

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