Active lane change for safety enhanced autonomous driving

This paper proposed an active lane change algorithm for autonomous vehicles using safety-critical model predictive control method. By incorporating safety-critical constraints into the algorithm, the safety hazard caused by surrounding vehicles are addressed. The proposed algorithm can actively react to mandatory lane change requirement. This has been evaluated in random generated driving scenarios. A safety hazard caused by merging surrounding vehicle is highlighted to demonstrate the effectiveness of the control algorithm.</p

Targeted Re-Sequencing Identified rs3106189 at the 5′ UTR of TAPBP and rs1052918 at the 3′ UTR of TCF3 to Be Associated with the Overall Survival of Colorectal Cancer Patients

<div><p>Recent studies have demonstrated the power of deep re-sequencing of the whole genome or exome in understanding cancer genomes. However, targeted capture of selected genomic whole gene-body regions, rather than the whole exome, have several advantages: 1) the genes can be selected based on biology or a hypothesis; 2) mutations in promoter and intronic regions, which have important regulatory roles, can be investigated; and 3) less expensive than whole genome or whole exome sequencing. Therefore, we designed custom high-density oligonucleotide microarrays (NimbleGen Inc.) to capture approximately 1.7 Mb target regions comprising the genomic regions of 28 genes related to colorectal cancer including genes belonging to the WNT signaling pathway, as well as important transcription factors or colon-specific genes that are over expressed in colorectal cancer (CRC). The 1.7 Mb targeted regions were sequenced with a coverage ranged from 32× to 45× for the 28 genes. We identified a total of 2342 sequence variations in the CRC and corresponding adjacent normal tissues. Among them, 738 were novel sequence variations based on comparisons with the SNP database (dbSNP135). We validated 56 of 66 SNPs in a separate cohort of 30 CRC tissues using Sequenom MassARRAY iPLEX Platform, suggesting a validation rate of at least 85% (56/66). We found 15 missense mutations among the exonic variations, 21 synonymous SNPs that were predicted to change the exonic splicing motifs, 31 UTR SNPs that were predicted to occur at the transcription factor binding sites, 20 intronic SNPs located near the splicing sites, 43 SNPs in conserved transcription factor binding sites and 32 in CpG islands. Finally, we determined that rs3106189, localized to the 5′ UTR of antigen presenting tapasin binding protein (TAPBP), and rs1052918, localized to the 3′ UTR of transcription factor 3 (TCF3), were associated with overall survival of CRC patients.</p></div

The clinicopathological characteristics of 117 Chinese CRC patients.

<p>The clinicopathological characteristics of 117 Chinese CRC patients.</p

The association of single SNP with CRC patient survival.

<p>Note: The significant P values (≤0.05) are in bold.</p><p>WW, homozygous wild-type genotype; WV heterozygous genotype; VV, homozygous variant genotype.</p><p>Abbreviations: CI, confidence interval; HR, hazard ratio; omit, no results due to missing information on the death status.</p

List of UTR SNPs with transcription factor binding sites changed using TFSEARCH.

a<p>Tissue samples with SNP detected by NGS. CRC is the colorectal cancer tissue, and CRN is the colorectal cancer adjacent normal tissue.</p>b<p>“+” indicates “validated” and “−” indicated “not tested” by Sequenom.</p

PolyPhen, SIFT and PROVEAN prediction results for non-synonymous variations identified.

a<p>Tissue samples with SNP detected by NGS. CRC is the colorectal cancer tissue pool, and CRN is the colorectal cancer adjacent normal tissue pool.</p>b<p>“+”indicates “validated” and “−” indicated “not tested” by Sequenom.</p

The sequence coverage of 28 selected genes and number of SNPs in CRC and CRN identified by NGS.

a.<p>NG coverage (%): the percentage of regions covered by final reads out of the whole NimbleGen captured regions for each gene, including 10-kb upstream and 5-kb downstream.</p>b.<p>total coverage (%): the percentage of regions covered by final reads out of the whole designed regions for each gene.</p>c.<p>folds coverage (x): the average read depth.</p>d.<p>no. SNPs: the total SNPs identified for the gene.</p>e.<p>SNP rate (‰): the average count of SNP in a 1k-bp window.</p>f.<p>The chromosome names and locations of the genomic regions that were captured for each gene.</p

List of synonymous SNPs with ESE/ESS motifs changed.

a<p>Tissue samples with SNP detected by NGS. CRC is the colorectal cancer tissue, and CRN is the colorectal cancer adjacent normal tissue.</p>b<p>“+”indicates “validated” and “−” indicated “not tested” by Sequenom.</p

GC content, coverage and SNP count.

<p>(A) The GC content and coverage in CRC (colorectal cancer) tissue. (B) The GC content and coverage in CRN (colorectal normal tissue) tissue. (C) The relationship between sequence coverage and SNP detection. Red line shows the sequence coverage and percentage of SNPs detected at that coverage in CRC pool, and green line in CRN pool (D) Venn diagram of SNPs for CRC and CRN samples. (E) An overview of SNPs identified in cancer and adjacent normal tissue.</p

Intronic SNPs near splice sites (<30 nt).

a<p>Tissue samples with SNP detected by NGS. CRC is the colorectal cancer tissue, and CRN is the colorectal cancer adjacent normal tissue.</p>b<p>“+” indicates “validated” and “−” indicated “not tested” by Sequenom.</p