Cognitive characteristics of older Japanese drivers

Background

Some causes of accidents among older drivers are: not paying attention to traffic signals; missing stop lines; and having to deal with and misjudging emergency situations. These causes of accidents reveal problems with attention and cognition. Such incidents are also related to driver perception and stress-coping mechanisms. It is important to examine the relation of stress reactions to attention and cognition as a factor influencing the causes of accidents commonly involving older drivers.

Finding

Subjects were 10 young drivers (23.3 ± 3.33 years) and 25 older drivers divided into two groups (older1 [60 to 65 years] and older2 [> 65 years]). This study revealed the correlation within driver stress inventory and driver coping questionnaires parameters was observed only in older drivers. They also needed a longer response time for Trail Making Test A and B. The factors affected the attention and cognition of older drivers by age but not driving experience itself, and coping parameters such as emotion focus, reappraisal, and avoidance were not included as stress inventory parameters. Being prone to fatigue was less for younger drivers than older drivers. Because they have shorter distances, shorter drive times, and no need for expressways, older drivers also had a significantly lower risk of thrill-seeking behaviour and more patience.

Conclusion

The intervention addressing their attention skills, aggressive feelings, and emotion focus should be considered. The technological improvements in cars will make older drivers feel safer and make driving easier which might lower the attention paid to the road, and regular driving training might be needed to assess and enhance their safety.     

The human‐induced imbalance between C,N and P in Earth's life system

Human‐induced carbon and nitrogen fertilization are generating a strong imbalance with P. This imbalance confers an increasingly important role to P availability and N : P ratio in the Earth's life system, affecting carbon sequestration potential and the structure, function and evolution of the Earth's ecosystems.     

Are invasive species drivers of native species decline or passengers of habitat modification? A case study of the impact of the common myna (Acridotheres tristis) on Australian bird species

Habitat modification and invasive species are significant drivers of biodiversity decline. However, distinguishing between the impacts of these two drivers on native species can be difficult. For example, habitat modification may reduce native species abundance, while an invasive species may take advantage of the new environment. This scenario has been described as the driver‐passenger model, with ‘passengers’ taking advantage of habitat modification and ‘drivers’ causing native species decline. Therefore, research must incorporate both habitat modification and invasive species impact to successfully investigate native species decline. In this paper, we used the common myna (Acridotheres tristis) as a case study to investigate the driver‐passenger model. We investigated changes in bird abundance, over 2 years, in relation to different habitat types and common myna abundance. We hypothesized that the common myna is both a passenger of habitat change and a driver of some bird species decline. Our results indicated that the abundance of many native species is greater in high tree density nature reserves, while the common myna was uncommon in these areas. Common myna abundance was almost three times higher in urban areas than nature reserves and declined rapidly as tree density in nature reserves increased. Our findings indicated that the common myna is primarily a passenger of habitat change. However, we also observed negative associations between common myna abundance and some bird species. We stress the importance of simultaneously investigating both invasive species impact and habitat modification. We suggest habitat restoration could be a useful tool for both native species recovery and invasive species control. Understanding the drivers of native species decline will help inform impact mitigation and direct further research.     

Candidate Cancer Driver Mutations in Distal Regulatory Elements and Long-Range Chromatin Interaction Networks

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From cancer genomes to cancer models: bridging the gaps

Cancer genome projects are now being expanded in an attempt to provide complete landscapes of the mutations that exist in tumours. Although the importance of cataloguing genome variations is well recognized, there are obvious difficulties in bridging the gaps between high‐throughput resequencing information and the molecular mechanisms of cancer evolution. Here, we describe the current status of the high‐throughput genomic technologies, and the current limitations of the associated computational analysis and experimental validation of cancer genetic variants. We emphasize how the current cancer‐evolution models will be influenced by the high‐throughput approaches, in particular through efforts devoted to monitoring tumour progression, and how, in turn, the integration of data and models will be translated into mechanistic knowledge and clinical applications.     

A pan-cancer transcriptome analysis of exitron splicing identifies novel cancer driver genes and neoepitopes

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Cancer‐associated mutations are preferentially distributed in protein kinase functional sites

Protein kinases are a superfamily involved in many crucial cellular processes, including signal transmission and regulation of cell cycle. As a consequence of this role, kinases have been reported to be associated with many types of cancer and are considered as potential therapeutic targets. We analyzed the distribution of pathogenic somatic point mutations (drivers) in the protein kinase superfamily with respect to their location in the protein, such as in structural, evolutionary, and functionally relevant regions. We find these driver mutations are more clearly associated with key protein features than other somatic mutations (passengers) that have not been directly linked to tumor progression. This observation fits well with the expected implication of the alterations in protein kinase function in cancer pathogenicity. To explain the relevance of the detected association of cancer driver mutations at the molecular level in the human kinome, we compare these with genetically inherited mutations (SNPs). We find that the subset of nonsynonymous SNPs that are associated to disease, but sufficiently mild to the point of being widespread in the population, tend to avoid those key protein regions, where they could be more detrimental for protein function. This tendency contrasts with the one detected for cancer associated‐driver‐mutations, which seems to be more directly implicated in the alteration of protein function. The detailed analysis of protein kinase groups and a number of relevant examples, confirm the relation between cancer associated‐driver‐mutations and key regions for protein kinase structure and function. Proteins 2009. © 2009 Wiley‐Liss, Inc.     

MEGSA: A Powerful and Flexible Framework for Analyzing Mutual Exclusivity of Tumor Mutations

The central challenges in tumor sequencing studies is to identify driver genes and pathways, investigate their functional relationships, and nominate drug targets. The efficiency of these analyses, particularly for infrequently mutated genes, is compromised when subjects carry different combinations of driver mutations. Mutual exclusivity analysis helps address these challenges. To identify mutually exclusive gene sets (MEGS), we developed a powerful and flexible analytic framework based on a likelihood ratio test and a model selection procedure. Extensive simulations demonstrated that our method outperformed existing methods for both statistical power and the capability of identifying the exact MEGS, particularly for highly imbalanced MEGS. Our method can be used for de novo discovery, for pathway-guided searches, or for expanding established small MEGS. We applied our method to the whole-exome sequencing data for 13 cancer types from The Cancer Genome Atlas (TCGA). We identified multiple previously unreported non-pairwise MEGS in multiple cancer types. For acute myeloid leukemia, we identified a MEGS with five genes (FLT3, IDH2, NRAS, KIT, and TP53) and a MEGS (NPM1, TP53, and RUNX1) whose mutation status was strongly associated with survival (p = 6.7 × 10⁻⁴). For breast cancer, we identified a significant MEGS consisting of TP53 and four infrequently mutated genes (ARID1A, AKT1, MED23, and TBL1XR1), providing support for their role as cancer drivers.     

Chromosome instability region analysis and identification of the driver genes of the epithelial ovarian cancer cell lines A2780 and SKOV3

Epithelial ovarian cancer (EOC) is one of the most prevalent gynaecological cancers worldwide. The molecular mechanisms of serous ovarian cancer (SOC) remain unclear and not well understood. SOC cases are primarily diagnosed at the late stage, resulting in a poor prognosis. Advances in molecular biology techniques allow us to obtain a better understanding of precise molecular mechanisms and to identify the chromosome instability region and key driver genes in the carcinogenesis and progression of SOC. Whole-exome sequencing was performed on the normal ovarian cell line IOSE80 and the EOC cell lines SKOV3 and A2780. The single-nucleotide variation burden, distribution, frequency and signature followed the known ovarian mutation profiles, without chromosomal bias. Recurrently mutated ovarian cancer driver genes, including LRP1B, KMT2A, ARID1A, KMT2C and ATRX were also found in two cell lines. The genome distribution of copy number alterations was found by copy number variation (CNV) analysis, including amplification of 17q12 and 4p16.1 and deletion of 10q23.33. The CNVs of MED1, GRB7 and MIEN1 located at 17q12 were found to be correlated with the overall survival of SOC patients (MED1: p = 0.028, GRB7: p = 0.0048, MIEN1: p = 0.0051), and the expression of the three driver genes in the ovarian cell line IOSE80 and EOC cell lines SKOV3 and A2780 was confirmed by western blot and cell immunohistochemistry.