Dopamine Beta Hydroxylase Genotype Identifies Individuals Less Susceptible to Bias in Computer-Assisted Decision Making

Computerized aiding systems can assist human decision makers in complex tasks but can impair performance when they provide incorrect advice that humans erroneously follow, a phenomenon known as “automation bias.” The extent to which people exhibit automation bias varies significantly and may reflect inter-individual variation in the capacity of working memory and the efficiency of executive function, both of which are highly heritable and under dopaminergic and noradrenergic control in prefrontal cortex. The dopamine beta hydroxylase (DBH) gene is thought to regulate the differential availability of dopamine and norepinephrine in prefrontal cortex. We therefore examined decision-making performance under imperfect computer aiding in 100 participants performing a simulated command and control task. Based on two single nucleotide polymorphism (SNPs) of the DBH gene, −1041 C/T (rs1611115) and 444 G/A (rs1108580), participants were divided into groups of low and high DBH enzyme activity, where low enzyme activity is associated with greater dopamine relative to norepinephrine levels in cortex. Compared to those in the high DBH enzyme activity group, individuals in the low DBH enzyme activity group were more accurate and speedier in their decisions when incorrect advice was given and verified automation recommendations more frequently. These results indicate that a gene that regulates relative prefrontal cortex dopamine availability, DBH, can identify those individuals who are less susceptible to bias in using computerized decision-aiding systems

Yeast Screens Identify the RNA Polymerase II CTD and SPT5 as Relevant Targets of BRCA1 Interaction

BRCA1 has been implicated in numerous DNA repair pathways that maintain genome integrity, however the function responsible for its tumor suppressor activity in breast cancer remains obscure. To identify the most highly conserved of the many BRCA1 functions, we screened the evolutionarily distant eukaryote Saccharomyces cerevisiae for mutants that suppressed the G1 checkpoint arrest and lethality induced following heterologous BRCA1 expression. A genome-wide screen in the diploid deletion collection combined with a screen of ionizing radiation sensitive gene deletions identified mutants that permit growth in the presence of BRCA1. These genes delineate a metabolic mRNA pathway that temporally links transcription elongation (SPT4, SPT5, CTK1, DEF1) to nucleopore-mediated mRNA export (ASM4, MLP1, MLP2, NUP2, NUP53, NUP120, NUP133, NUP170, NUP188, POM34) and cytoplasmic mRNA decay at P-bodies (CCR4, DHH1). Strikingly, BRCA1 interacted with the phosphorylated RNA polymerase II (RNAPII) carboxy terminal domain (P-CTD), phosphorylated in the pattern specified by the CTDK-I kinase, to induce DEF1-dependent cleavage and accumulation of a RNAPII fragment containing the P-CTD. Significantly, breast cancer associated BRCT domain defects in BRCA1 that suppressed P-CTD cleavage and lethality in yeast also suppressed the physical interaction of BRCA1 with human SPT5 in breast epithelial cells, thus confirming SPT5 as a relevant target of BRCA1 interaction. Furthermore, enhanced P-CTD cleavage was observed in both yeast and human breast cells following UV-irradiation indicating a conserved eukaryotic damage response. Moreover, P-CTD cleavage in breast epithelial cells was BRCA1-dependent since damage-induced P-CTD cleavage was only observed in the mutant BRCA1 cell line HCC1937 following ectopic expression of wild type BRCA1. Finally, BRCA1, SPT5 and hyperphosphorylated RPB1 form a complex that was rapidly degraded following MMS treatment in wild type but not BRCA1 mutant breast cells. These results extend the mechanistic links between BRCA1 and transcriptional consequences in response to DNA damage and suggest an important role for RNAPII P-CTD cleavage in BRCA1-mediated cancer suppression

Transmission electron microscopy characterization of the bake-hardening behavior of transformation-induced plasticity and dual-phase steels

The effect of prestraining (PS) and bake hardening (BH) on the microstructures and mechanical properties has been studied in transformation-induced plasticity (TRIP) and dual-phase (DP) steels after intercritical annealing. The DP steel showed an increase in the yield strength and the appearance of the upper and lower yield points after a single BH treatment as compared with the as-received condition, whereas the mechanical properties of the TRIP steel remained unchanged. This difference appears to be because of the formation of plastic deformation zones with high dislocation density around the &ldquo;as-quenched&rdquo; martensite in the DP steel, which allowed carbon to pin these dislocations, which, in turn, increased the yield strength. It was found for both steels that the BH behavior depends on the dislocation rearrangement in ferrite with the formation of cell, microbands, and shear band structures after PS. The strain-induced transformation of retained austenite to martensite in the TRIP steel contributes to the formation of a complex dislocation structure.<br /

Strain hardening behavior of dual-phase steels

A detailed qualitative and quantitative examination of the microstructure and mechanical properties of three different classes of DP600 and DP450 dual-phase (DP) steels was carried out. The tested DP steels are characterized by different alloying elements: aluminum, boron, and phosphorus. Among them, aluminum DP steels showed the lowest percentages of hard phases, while phosphorus DP steels exhibited the highest resistance values. The Hollomon, Pickering, Crussard–Jaoul (CJ), and Bergstrom models were used to reproduce the strain hardening behavior of DP steels. Relationships that correlate the fitting parameters with the chemical composition and the thermal cycle parameters were found, and the predictive abilities of different models were evaluated. The Pickering equation, among the tested models, is the best one in the reproduction of the experimental stress-strain data